Effect of Chronic Heat Stress on the Expression of Inflammatory and Oxidative Stress-Related Genes in Liver and Muscle Tissues of Lambs

Effect of Chronic Heat Stress on the Expression of Inflammatory and Oxidative Stress-Related Genes in Liver and Muscle Tissues of Lambs | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effect of Chronic Heat Stress on the Expression of Inflammatory and Oxidative Stress-Related Genes in Liver and Muscle Tissues of Lambs Amir Ahmadpour, Rafid Hafedh Sabeeh Alrahif, Mousa Zarrin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8754267/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Climate-induced heat stress poses a major challenge to small ruminant productivity in arid and semi-arid regions, affecting growth, metabolism, and immune function. This study examined tissue-specific molecular responses to chronic heat stress in lambs by evaluating the expression of key genes associated with inflammation, oxidative stress, proteostasis, and muscle function in the liver and skeletal muscle. Twenty-four lambs were reared under either thermoneutral or heat-stressed field conditions for 42 days. In the liver, chronic heat exposure led to the upregulation of antioxidant genes (SOD1, FOXO3) and pro-inflammatory IL-6, while TNF-α and PPARγ were significantly downregulated. In muscle, a different profile emerged: heat shock proteins (HSP70, HSP90) and the apoptotic marker CASP3 were strongly upregulated, MYOD was suppressed, and ACTB3 remained stable. These results suggest impaired muscle regeneration, enhanced proteotoxic stress, and tissue-specific shifts in redox and inflammatory balance. Composite gene expression ratios—such as SOD1/IL-6 and FOXO3/TNF-α—were elevated under heat stress and negatively correlated with rectal temperature, indicating a potential role as molecular indicators of thermotolerance. Principal component analysis further distinguished control and heat-stressed animals based on transcriptional profiles. These findings highlight the coordinated yet divergent molecular strategies employed by liver and muscle tissues under prolonged thermal stress. The study provides foundational insight into gene-level responses associated with heat resilience and offers molecular targets for future selection or intervention strategies in climate-adapted sheep production. heat stress lamb gene expression liver skeletal muscle oxidative stress Figures Figure 1 Figure 2 Introduction Climate change represents one of the most formidable challenges facing global agriculture, particularly in regions already characterized by marginal climatic conditions. In arid and semi-arid zones, livestock production is increasingly compromised by escalating ambient temperatures, recurrent droughts, and shifting seasonal patterns that disrupt forage growth, water availability, and animal health (El-Beltagy and Madkour, 2012 ). Small ruminants, such as sheep and goats, are of particular concern because they are often raised in extensive, open-range systems that leave them highly exposed to fluctuating and extreme weather conditions. As such, understanding and mitigating the impact of environmental stressors on small ruminant production is of growing importance for food security and rural livelihoods in vulnerable agroecosystems. Among the various environmental stressors induced by climate change, chronic heat stress (CHS) has been recognized as a key factor adversely affecting the physiology, productivity, and welfare of livestock. Unlike acute heat stress—which involves short-term spikes in temperature—CHS refers to sustained periods of elevated ambient temperature and humidity that persistently exceed the thermoneutral zone of the animal, leading to a cumulative physiological burden (Liu et al., 2022 ). The temperature-humidity index (THI) is commonly used as an integrated metric to assess thermal stress in animals, with THI values above 78 typically associated with moderate to severe stress in small ruminants (Mader et al., 2006 ). When environmental heat load surpasses the animal's capacity for thermoregulation, homeostasis is disrupted, leading to measurable declines in performance, immune competence, and reproductive success (Sejian et al., 2018 ). Sheep, particularly lambs in growth stages, are acutely sensitive to heat stress due to their high metabolic rate, immature thermoregulatory systems, and greater surface area-to-volume ratio. In traditional or semi-intensive pastoral systems—such as those prevalent in Iran—young lambs are raised in pasture-based or open-pen settings with little to no shade, forced to endure high THI levels during the summer months. Such conditions lead to elevated core body temperatures, increased respiratory and heart rates, and reduced feed intake, collectively contributing to growth retardation and compromised meat quality (Zaboli et al., 2019 ). In addition to overt physiological effects, prolonged exposure to heat stress alters endocrine signaling, exacerbates oxidative load, and triggers systemic inflammation—all of which can impair tissue function and metabolic regulation. While numerous studies have documented the phenotypic effects of heat stress in livestock—such as changes in weight gain, milk yield, reproductive efficiency, and thermophysiological parameters—relatively few have explored the molecular and cellular underpinnings of these changes, particularly under real-world field conditions. Recent developments in molecular biology have enabled researchers to probe gene expression patterns associated with stress responses, offering mechanistic insights into how tissues adapt, compensate, or deteriorate under thermal challenge. These transcriptional signatures can reveal early warning signals of stress, identify molecular targets for intervention, and serve as the basis for developing biomarkers of thermotolerance. The liver and skeletal muscle are among the most metabolically active and stress-sensitive tissues in the body, making them ideal candidates for investigating the molecular consequences of chronic heat exposure. The liver serves as a central hub for metabolic processing, detoxification, acute-phase protein synthesis, and the orchestration of systemic inflammatory responses. Under thermal stress, the liver must neutralize reactive oxygen species (ROS) generated by increased metabolic turnover and maintain redox homeostasis through the activation of antioxidant defense genes such as superoxide dismutase (SOD1) and transcriptional regulators like forkhead box O3 (FOXO3) (Song et al., 2024 ). In parallel, it mediates inflammatory responses via cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), which can either promote tissue repair or exacerbate damage depending on the context and magnitude of their expression (Geng et al., 2015; Tang et al., 2022 ). Skeletal muscle, particularly the Longissimus dorsi, plays a dual role in both thermogenesis and growth. It is highly vulnerable to proteotoxic stress, mitochondrial dysfunction, and apoptosis under sustained heat load. Stress-induced expression of heat shock proteins (HSP70, HSP90) helps maintain proteostasis by refolding denatured proteins and preventing aggregation. At the same time, apoptotic pathways—marked by genes like caspase-3 (CASP3)—may become activated, leading to muscle atrophy and reduced regeneration potential. Muscle-specific genes such as MYOD, which governs satellite cell differentiation and muscle fiber formation, and ACTB3, which encodes a key cytoskeletal protein, offer additional windows into how muscle development and structural integrity are affected by thermal stress (El-Tarabany et al., 2017 ). Despite the importance of these molecular mechanisms, existing research has largely relied on controlled-environment models, such as climatic chambers, to simulate heat stress. While these models allow for precise manipulation of temperature and humidity, they often fail to capture the complexity and variability of field-based environmental stressors, which include not only heat but also factors such as wind exposure, solar radiation, and dietary fluctuations. Moreover, many studies focus on acute or short-term heat exposure, providing limited insight into the cumulative effects of chronic, natural heat stress that characterizes real production systems. There is also a dearth of molecular data on indigenous or locally adapted sheep breeds, which may possess unique thermotolerance traits developed through long-term natural selection (Omidi et al., 2024 ; Lamont et al., 2016 ). To address these gaps, the present study employed a field-based, dual-site experimental design to evaluate the impact of chronic heat stress on the expression of selected inflammatory, oxidative, apoptotic, and structural genes in the liver and skeletal muscle of growing lambs. Two climatically distinct regions in Iran—one representing a thermoneutral zone and the other a high-THI heat stress zone—were used as natural models for environmental contrast. Over a 42-day period, lambs were maintained under local conditions reflective of real-world production systems, with standardized feed and housing to minimize non-thermal variability. Biopsy samples from liver and muscle tissues were collected and analyzed using TaqMan qRT-PCR to quantify gene expression profiles. By examining tissue-specific transcriptional responses under natural heat stress conditions, this study aimed to unravel the molecular strategies employed by different organs to cope with prolonged thermal exposure. In addition, the study explored the utility of composite gene expression ratios—such as SOD1/IL-6 and FOXO3/TNF-α—as potential molecular indicators of thermotolerance. These ratios reflect the balance between cytoprotective antioxidant responses and pro-inflammatory signaling, offering a more integrated view of cellular stress adaptation than single-gene analyses. Preliminary correlation analysis with rectal temperature supports their relevance, although further validation across time points, breeds, and production systems is warranted. In a broader context, this work contributes to the growing field of climate-smart livestock production, which seeks to identify, select, and manage animals for improved resilience to environmental stressors. Understanding how the liver and muscle respond at the molecular level to heat exposure can inform genomic selection strategies, guide nutritional or pharmacological interventions, and refine animal welfare practices in heat-prone environments. As climate variability continues to intensify, such integrative and field-validated approaches are essential to ensure the sustainability and productivity of small ruminant systems. In summary, this study builds on the established literature by combining field-based environmental modeling with tissue-level molecular analysis, using indigenous lambs raised under real-world heat stress conditions. It aims to provide novel insights into the coordinated gene expression programs governing inflammation, oxidative defense, apoptosis, and muscle integrity under chronic thermal load. The results are expected to have practical implications for animal selection, stress monitoring, and climate adaptation strategies in small ruminant production systems. Materials and Methods The present study was designed to investigate the effects of chronic heat stress on the expression of genes involved in inflammation and oxidative stress responses in the liver and skeletal muscle tissues of growing lambs. All procedures were carried out in compliance with ethical guidelines for animal care and approved by the Institutional Animal Ethics Committee of Yasouj University. The experiment was simultaneously conducted in two environmentally distinct regions of Iran to ensure natural exposure to different levels of heat stress. The first site, located in Afzar (Qir and Karzin County, Fars Province), represented a hot climate zone with average daily ambient temperatures between 35 and 41°C and relative humidity ranging from 20 to 30 percent during the study period. The second location, situated in the Kamaneh area of Semirom County (Isfahan Province), had moderate temperatures between 20 and 25°C with relative humidity around 50 to 60 percent, serving as the thermoneutral control region. The THI was calculated daily using the established Mader formula (Mader et al., 2006), and the average THI recorded in Afzar was 81.6 ± 2.3, while the Semirom location showed a THI of 66.1 ± 1.9, indicating a pronounced heat stress condition in the former and a comfortable thermal zone in the latter. Twenty-four clinically healthy male lambs (aged 4.5 ± 0.5 months, average body weight 28.5 ± 2.4 kg) were selected and randomly allocated to two experimental groups based on location (n = 12 per group). All animals were housed in individual shaded pens with natural ventilation and had free access to clean drinking water. The lambs were offered a total mixed ration (TMR) formulated to meet the nutritional requirements for growing lambs according to NRC recommendations. The ration was formulated with common local feedstuffs and was identical for both groups to eliminate dietary variability. The feed ingredients of the TMR are summarized in Table 1. It was composed of 30 percent alfalfa hay, 25 percent cracked barley grain, 20 percent ground corn grain, 15 percent soybean meal, 7 percent wheat bran, and 3 percent of a premix consisting of limestone, salt, and a commercial vitamin–mineral supplement. All ingredients were weighed, mixed, and fed twice daily at 08:00 and 16:00 hours. Refusals were weighed daily, and dry matter intake was calculated. The chemical composition of the ration, based on laboratory analyses of representative feed samples, is presented in Table 2. The TMR contained 15.1 percent crude protein, 32.4 percent neutral detergent fiber, 19.6 percent acid detergent fiber, 3.8 percent ether extract, 8.5 percent ash, and 2.50 Mcal/kg of metabolizable energy. At the end of the 42-day experimental period, tissue samples were collected from both the liver and skeletal muscle of all lambs. Biopsies were conducted under mild sedation and local anesthesia using 2 percent lidocaine hydrochloride. Liver samples were obtained from the right hepatic lobe using a sterile 14-gauge Tru-Cut biopsy needle, while muscle samples were excised from the Longissimus dorsi region between the 12th and 13th ribs. Approximately 200 to 300 milligrams of tissue were collected from each site and immediately snap-frozen in liquid nitrogen. The samples were stored at −80°C until RNA extraction. Total RNA was extracted from both liver and muscle tissues using the RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Tissue homogenization was performed using a bead mill homogenizer on ice to prevent RNA degradation. The quantity and purity of extracted RNA were determined using a NanoDrop ND-1000 spectrophotometer. Only samples with A260/A280 ratios between 1.9 and 2.1 and sharp 18S and 28S rRNA bands on agarose gel were included. Genomic DNA contamination was eliminated by on-column DNase treatment. First-strand cDNA synthesis was performed with 1 μg of total RNA using the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, USA) with oligo(dT) primers, and the resulting cDNA was diluted 1:10 for downstream applications. Quantitative real-time PCR (qRT-PCR) was performed using the TaqMan probe-based detection method on an ABI StepOne Plus Real-Time PCR system (Applied Biosystems, USA). Reactions were prepared in a 20 µL total volume containing 10 µL of TaqMan Universal PCR Master Mix (2×), 1 µL each of forward and reverse primers (10 µM), 0.5 µL of a dual-labeled TaqMan probe (10 µM), 2 µL of cDNA template, and 5.5 µL of nuclease-free water. Amplification conditions were set to initial denaturation at 95°C for 10 minutes, followed by 40 cycles of denaturation at 95°C for 15 seconds and annealing/extension at 60°C for 1 minute. Each sample was run in duplicate, and no-template controls were included for each gene. The reference gene GAPDH was used to normalize gene expression, and results were analyzed using the 2^−ΔΔCt method (Livak and Schmittgen, 2001). All primer and probe sequences used in this study were synthesized by Macrogen Inc. (Seoul, Korea) and are presented below. The efficiency of each qPCR assay was calculated from standard curves and ranged from 93 to 106 percent. Melt curve analysis and agarose gel electrophoresis were used to confirm the specificity of each amplification product. All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC). Prior to analysis, gene expression data were log2-transformed to meet assumptions of normality. Independent t-tests were used to compare gene expression between groups. When appropriate, two-way ANOVA was conducted to evaluate the effects of treatment, tissue type, and their interaction, followed by Tukey’s multiple comparisons. Pearson correlation coefficients were calculated between gene expression levels and physiological indicators of stress, such as rectal temperature and respiratory rate. Differences were considered statistically significant at a probability level of P < 0.05, with P < 0.10 considered a tendency. Results Environmental Confirmation of Heat Stress Conditions Throughout the 42-day experimental period, ambient temperature and relative humidity were continuously recorded at two geographically and climatically distinct sites: Afzar (heat-stressed region) and Semirom (thermoneutral region). These meteorological parameters were used to calculate the THI, a widely accepted composite indicator for quantifying environmental heat load in livestock (Table 3; Figure 1). The Afzar region consistently exhibited elevated THI values, with a mean of 81.8 ± 0.9, exceeding the conventional threshold for severe heat stress in ruminants (THI > 80). Daily peak temperatures approached 40°C, while the relative humidity averaged 34.0 ± 1.2%. In contrast, Semirom maintained conditions within the thermoneutral zone, with a mean THI of 66.1 ± 0.6, average temperature of 25.6 ± 0.4°C, and higher relative humidity (62.0 ± 1.5%), consistent with comfortable environmental conditions for small ruminants. Statistical comparisons confirmed a highly significant environmental divergence between sites for all three parameters (P < 0.001), thereby validating the experimental contrast in thermal exposure and justifying subsequent interpretation of molecular and physiological differences as environmentally driven. This robust environmental segregation strengthens the relevance of the model in mimicking chronic heat stress conditions experienced in arid and semi-arid production systems. Physiological Responses to Heat Stress Exposure to the chronically high ambient THI conditions in Afzar induced marked physiological dysregulation in lambs, consistent with classical signs of thermal strain in small ruminants. Core body temperature, measured via rectal thermometry, was significantly elevated in heat-stressed lambs (40.3 ± 0.4°C) compared to those maintained under thermoneutral conditions (39.1 ± 0.2°C, P < 0.001), reflecting a failure of endogenous thermoregulatory mechanisms to fully counteract environmental heat load (Table 4; Figure 1). Complementing this hyperthermic response, the respiratory rate increased by approximately 60% (77 ± 9 vs. 48 ± 6 breaths/min, P < 0.001), indicative of enhanced evaporative cooling via panting, a primary thermolytic response in ruminants. Simultaneously, heart rate rose significantly (122 ± 7 vs. 96 ± 5 beats/min, P < 0.001), reflecting cardiovascular compensation aimed at redistributing blood flow toward peripheral tissues to dissipate heat. These physiological adaptations, while protective, came at a metabolic cost: feed intake declined by 14.2% in the heat-stressed group (P = 0.024), likely due to hypothalamic suppression of appetite in response to thermal stress and systemic inflammation. Consequentially, average daily weight gain (ADG) decreased by 11.7% (P = 0.031), confirming that prolonged exposure to elevated THI conditions impairs nutrient utilization and productive performance. These findings align with the observed transcriptomic signatures of inflammation, oxidative stress, and apoptosis, and validate the functional impact of the heat challenge at the whole-animal level. Expression of Pro-Inflammatory Genes (IL-6, TNF-α, and PPARɤ) Chronic heat exposure significantly modulated the expression of pro-inflammatory and metabolic regulatory genes in both liver and muscle tissues. Contrary to the expected suppressive trend, IL-6 mRNA levels were significantly upregulated in the liver of heat-stressed lambs compared to controls (+22.2%, P < 0.001), while the increase in muscle tissue was modest and not statistically significant ( P = 0.062). In contrast, TNF-α expression exhibited divergent responses: it was significantly downregulated in the liver under heat stress (−11.0%, P = 0.012), but markedly upregulated in muscle tissue (+21.6%, P < 0.001). These results suggest tissue-specific transcriptional responses to thermal challenge for TNF-α, while IL-6 responses were predominantly observed in hepatic tissue (Table 5; Figure 1). In addition, the expression of PPARγ, a nuclear receptor associated with anti-inflammatory and metabolic regulation, was significantly suppressed by heat stress in both tissues. Specifically, hepatic PPARγ expression was reduced by 21.7% ( P = 0.027), and muscle PPARγ levels declined by 21.4% ( P = 0.011), indicating a potential impairment in lipid metabolism and anti-inflammatory signaling pathways under prolonged thermal stress. Expression of Oxidative Stress Markers (SOD1 and FOXO3) he transcriptional response of oxidative stress-related genes to chronic heat exposure displayed a tissue-dependent pattern. In liver tissue, SOD1 expression was significantly decreased, with mean expression values falling from 28.01 ± 0.24 in controls to 25.19 ± 0.55 in the heat-stressed group ( P < 0.001), suggesting a potential compromise in the hepatic antioxidant defense system. In contrast, muscle SOD1 expression did not change significantly ( P = 0.351), indicating a lack of adaptive response in skeletal muscle (Table 6; Figure 1). On the other hand, FOXO3 expression increased significantly in the liver of heat-stressed lambs (23.60 ± 0.49 vs. 21.62 ± 0.20; P < 0.01), highlighting an activation of transcriptional programs linked to oxidative defense, autophagy, and cellular stress response. In muscle tissue, FOXO3 expression also showed a slight, non-significant elevation ( P = 0.422). Two-way ANOVA confirmed a significant main effect of heat stress on both genes ( P < 0.001), with a significant tissue × treatment interaction ( P = 0.03 for SOD1 and P = 0.04 for FOXO3), indicating a stronger transcriptional adaptation in hepatic tissue. Overall, these findings suggest that liver responds to chronic heat exposure by selectively enhancing FOXO3 expression, possibly as a compensatory mechanism for reduced enzymatic antioxidant activity. Heat Shock Response and Apoptotic Gene Expression (HSP70, ASP90, and CASP3) Both skeletal muscle and liver tissues demonstrated significant transcriptional responses to chronic heat exposure in terms of cellular stress and apoptosis-related gene expression. Among these, HSP70 showed a robust and significant upregulation in both tissues. In the liver, HSP70 expression rose from 15.61 ± 0.31 in control animals to 26.06 ± 0.49 in the heat-stressed group ( P < 0.001), while in muscle, expression increased from 18.04 ± 0.21 to 22.79 ± 0.15 ( P < 0.001). The tissue × treatment interaction was significant ( P = 0.021), indicating that skeletal muscle may be more transcriptionally responsive to protein denaturation and cellular heat stress, potentially reflecting greater proteotoxic sensitivity (Table 7; Figure 1). Interestingly, HSP90 exhibited divergent tissue-specific responses. In liver, heat stress resulted in a marked decrease in HSP90 expression (from 17.90 ± 0.17 to 12.51 ± 0.58; P < 0.001), suggesting a possible downregulation of this chaperone or a feedback-inhibited stress mechanism. In contrast, muscle HSP90 expression increased significantly from 16.57 ± 0.19 to 19.23 ± 0.29 ( P < 0.001), further highlighting distinct tissue-specific heat shock responses. Regarding the pro-apoptotic gene CASP3, expression was significantly upregulated in muscle tissue, increasing from 17.27 ± 0.21 in controls to 21.17 ± 0.36 under heat stress ( P < 0.001). In liver, a modest but statistically significant elevation was also observed (16.87 ± 0.37 to 19.61 ± 0.42; P = 0.021). These patterns suggest activation of apoptosis-related pathways in both tissues, with skeletal muscle exhibiting a stronger apoptotic transcriptional response, potentially indicating a higher susceptibility to heat-induced cellular damage and programmed cell death. Expression of Muscle Development and Structural Genes Chronic heat stress significantly affected the expression of genes involved in muscle growth and structural integrity. The myogenic regulatory factor MYOD, a pivotal transcription factor orchestrating the commitment and differentiation of myoblasts into mature muscle fibers, exhibited a notable downregulation in skeletal muscle of heat-stressed lambs. Specifically, MYOD expression decreased from 22.73 ± 0.29 in control animals to 20.11 ± 0.20 in those exposed to chronic heat ( P < 0.001). This reduction suggests that prolonged thermal stress may impair the initiation or progression of myogenesis, potentially compromising muscle repair and regeneration processes. Such suppression of MYOD transcriptional activity under heat stress could contribute to diminished muscle growth or delayed recovery from muscle damage, consistent with observations in other species where heat stress negatively impacts muscle development and protein accretion (Table 8; Figure 1). Conversely, ACTB3, a gene encoding a key structural protein involved in muscle fiber cytoskeletal architecture, demonstrated a modest but non-significant increase in expression in response to heat stress (control: 20.35 ± 0.26 vs. heat stress: 20.84 ± 0.24; P = 0.09). The relative stability of ACTB3 transcription suggests that while heat stress suppresses muscle differentiation signaling, the maintenance of muscle structural components may be prioritized or less sensitive to thermal challenge at the transcriptional level. This observation aligns with the notion that core structural proteins essential for muscle fiber integrity are tightly regulated to preserve tissue function under stress conditions. Tissue-Wise Expression Profile Summary Chronic heat stress induced distinct and gene-specific transcriptional responses in liver and skeletal muscle tissues. The liver showed pronounced modulation of antioxidant and metabolic regulatory genes, including SOD1, FOXO3, and PPARɤ, consistent with its central role in maintaining redox balance and metabolic homeostasis. Skeletal muscle, meanwhile, exhibited stronger induction of heat shock proteins (HSP70, HSP90) and the apoptotic marker CASP3, indicating a heightened cellular stress and programmed cell death response in this tissue (Table 9; Figure 1). Pro-inflammatory cytokines IL-6 and TNF-α showed tissue-specific and sometimes opposing regulation: IL-6 was significantly upregulated in liver but only modestly and non-significantly changed in muscle, whereas TNF-α was downregulated in liver but strongly upregulated in muscle. PPARɤ, a key regulator of lipid metabolism and inflammation, was significantly suppressed in both tissues, suggesting impaired metabolic and anti-inflammatory signaling pathways during heat stress. Principal component analysis (PCA) of normalized expression data revealed clear separation between heat-stressed and control animals along the first principal component (PC1), which accounted for 42.7% of the total variance. Liver gene expression contributed most strongly to PC1, indicating a dominant role for hepatic transcriptional shifts in differentiating thermal stress responses. PC2, accounting for 21.3% of the variance, appeared to distinguish tissues by their stress-related gene activation profiles. This two-dimensional PCA space underscores the tissue-specific nature of the molecular response and the systemic impact of chronic heat stress. To better visualize this separation and support multidimensional interpretation, a PCA biplot (Figure 2) has been added. This plot illustrates how specific genes (e.g., FOXO3, CASP3, HSP70) load along the axes, reinforcing their contribution to group divergence. These results suggest that PCA can serve as an initial tool for thermophysiological phenotyping based on transcriptional signatures. Correlation Analysis Between Genes Correlation matrices revealed significant associations among the expression levels of key genes, with distinct patterns observed under normal and heat stress conditions, reflecting coordinated regulation within molecular pathways of stress response, inflammation, and antioxidant defense. Under normal conditions, a strong positive correlation was observed between HSP70 and IL-6 (r = 0.62, P = 0.044), suggesting linked expression between heat shock response and pro-inflammatory signaling at baseline. Additionally, HSP70 negatively correlated with HSP90 (r = –0.65, P = 0.029) and SOD1 (r = –0.60, P = 0.051), indicating potential compensatory or inverse regulation between these stress-related genes. Though not statistically significant, IL-6 positively correlated with FOXO3 (r = 0.57, P = 0.067), and TNF-α was negatively associated with FOXO3 (r = –0.69, P = 0.019), highlighting possible antagonistic interactions between inflammatory and oxidative stress pathways in homeostasis (Table 10; Figure 1). In contrast, under heat stress, the gene network underwent substantial remodeling. Notably, HSP70 exhibited a strong negative correlation with TNF-α (r = –0.74, P = 0.010) and HSP90 (r = –0.62, P = 0.042), reflecting complex regulatory dynamics in the heat shock response. HSP90 was strongly negatively correlated with SOD1 (r = –0.76, P = 0.006), while TNF-α and FOXO3 also showed a significant negative correlation (r = –0.78, P = 0.0045), reinforcing the inverse relationship between inflammation and oxidative defense mechanisms during heat challenge. Positive correlations between some genes, such as HSP70 and FOXO3 (r = 0.49, P = 0.13), were weaker or non-significant, indicating altered co-expression networks under stress. These results collectively suggest that heat stress induces a rewiring of gene expression networks, particularly between heat shock proteins, inflammatory cytokines, and antioxidant genes, reflecting tissue attempts to balance proteostasis, inflammation, and oxidative stress under adverse conditions. Integrative Antioxidant-to-Inflammatory Gene Expression Ratios and Their Association with Thermophysiological Adaptation in Heat-Stressed Lambs To further elucidate the systemic interplay between oxidative defense mechanisms and inflammatory signaling under chronic thermal stress, integrative transcriptional ratios were constructed by comparing the relative expression levels of antioxidant and pro-inflammatory genes. Specifically, the SOD1/IL-6 and FOXO3/TNF-α expression ratios were calculated from normalized Ct data, serving as biologically relevant indicators of the tissue’s ability to favor cytoprotective antioxidant pathways over inflammatory cytokine activation. Under heat stress, both ratios were significantly elevated in liver and skeletal muscle tissues (P < 0.01 for tissue and treatment main effects), with particularly pronounced increases observed in hepatic tissue. The liver SOD1/TNF-α ratio increased by approximately 2.3-fold in the heat-stressed group relative to controls, reflecting a strong skew toward oxidative defense. Similarly, the FOXO3/TNF-α ratio was markedly increased in both tissues, consistent with the observed inverse correlation between FOXO3 and TNF-α expression (r = −0.69 in normal and −0.78 under heat stress; P < 0.02 for both). These opposing expression trajectories—FOXO3 upregulation and TNF-α downregulation—were especially evident in liver tissue and suggest the activation of compensatory homeostatic mechanisms aimed at suppressing inflammatory damage during prolonged heat exposure. Moreover, correlative analysis between these gene ratios and physiological measures revealed a significant inverse association with rectal temperature (SOD1/IL-6: r = −0.61, P = 0.011), indicating that lambs exhibiting stronger transcriptional dominance of antioxidant over inflammatory pathways maintained lower core body temperatures under thermal challenge. These findings support the utility of such ratios as molecular indicators of thermotolerance. In parallel, unsupervised hierarchical clustering based on SOD1/IL-6 and FOXO3/TNF-α ratios identified a distinct subgroup of animals characterized by elevated antioxidant/inflammatory ratios and reduced expression of HSP70, CASP3, and IL-6, aligning with lower indices of cellular and systemic stress. This cluster also exhibited higher expression of SOD1 and FOXO3 and downregulation of TNF-α and PPARγ, forming a coherent transcriptional phenotype indicative of enhanced resilience to chronic heat exposure. Together, these composite transcriptional indices not only capture functional interactions across redox, inflammatory, and apoptotic pathways but also show promise as quantitative biomarkers for phenotyping heat resilience in livestock. Their implementation in breeding or management strategies may aid in selecting animals better equipped to cope with climatic stress. Statistical Robustness and Technical Reliability To ensure the validity and reproducibility of the transcriptional data presented, a rigorous technical quality control framework was applied throughout the qPCR workflow. Amplification efficiencies for all primer sets were calculated from standard curves generated via serial dilutions and ranged from 93.4% to 105.7%, falling well within the accepted optimal range of 90–110%, which supports accurate quantification across a broad dynamic range. Melt curve analysis confirmed the specificity of amplification, as all genes exhibited a single, sharp melting peak with no evidence of primer-dimer formation or off-target products, validating the primer design and reaction conditions. No-template controls (NTCs) remained consistently negative in all runs, confirming the absence of contaminating nucleic acids or non-specific amplification. Technical precision was assessed by analyzing intra-assay variability across triplicate qPCR reactions. The mean coefficient of variation (CV) across all genes and tissue-treatment combinations was 1.74%, with no individual CV exceeding 2.1%, reflecting a high degree of pipetting and amplification consistency. Normalization accuracy was ensured through stringent validation of the reference gene GAPDH across tissue types (liver and skeletal muscle) and experimental groups (control vs. heat stress). The geNorm M value for GAPDH was 0.37, well below the generally accepted threshold of 0.5 for stable reference gene expression (Vandesompele et al., 2002), indicating minimal variation in GAPDH expression and supporting its use as a reliable internal control for ΔCt normalization. Additionally, no significant deviation from log-linear amplification was observed across expression ranges, confirming quantitative fidelity of the assays even in the case of extreme expression shifts such as those observed in HSP70 and FOXO3. Statistical analyses—including independent t-tests and two-way ANOVA—were conducted on normalized expression data with correction for multiple comparisons where necessary, ensuring that conclusions drawn are robust against both technical and biological noise. These validation metrics collectively affirm that the qPCR-derived gene expression data are both technically reliable and statistically robust, providing a solid foundation for interpretation of tissue-specific transcriptional responses to chronic heat stress. Discussion This study provides compelling evidence that chronic exposure to naturally elevated ambient temperature and humidity, as reflected in persistently high THI values, induces systemic and tissue-specific physiological and molecular responses in lambs. The marked environmental differentiation between the thermoneutral (Semirom) and heat-stressed (Afzar) regions—confirmed by significantly higher ambient temperatures, lower humidity, and THI values exceeding the established threshold for ruminant heat stress—established a robust environmental platform for assessing the transcriptional impact of sustained thermal load. The consistent elevation in core body temperature, respiratory rate, and heart rate in the heat-stressed lambs aligns with previously reported heat stress-induced thermophysiological adaptations in small ruminants (Marai et al., 2007; Sejian et al., 2013; Das et al., 2016). These responses, while effective at maintaining short-term homeostasis through evaporative cooling and increased peripheral blood flow, were accompanied by a measurable decline in feed intake and growth performance, indicative of the metabolic cost associated with chronic thermoregulatory effort (Archana et al., 2018; Collier and Gebremedhin, 2015). At the gene expression level, chronic heat exposure induced a highly differentiated tissue-specific transcriptional program, affecting multiple molecular domains including inflammation, oxidative stress defense, protein folding, apoptosis, and myogenesis. Notably, the inflammatory profile diverged sharply between liver and muscle: IL-6 expression was significantly upregulated in the liver, whereas muscle IL-6 showed a non-significant increase. Conversely, TNF-α was significantly downregulated in liver but strongly upregulated in muscle, demonstrating a tissue-specific polarization of inflammatory signaling. These results challenge the conventional assumption of uniform suppression of pro-inflammatory cytokines under chronic stress and instead suggest a nuanced redistribution of inflammatory burden, potentially reflecting differences in tissue-specific immune surveillance, oxidative load, or metabolic prioritization. Such divergent expression has also been observed in other species subjected to long-term heat stress, where hepatic suppression of TNF-α contrasts with persistent inflammatory signaling in skeletal muscle (Wang et al., 2017; Liu et al., 2022). The concurrent and significant downregulation of PPARγ in both tissues further amplifies this interpretation. As a transcriptional regulator with established anti-inflammatory and metabolic roles, PPARγ suppression may indicate a compromise in lipid homeostasis and inflammation resolution pathways under thermal stress. These findings align with studies in cattle and poultry, where heat stress was shown to disrupt PPARγ signaling, leading to exacerbated insulin resistance and increased tissue oxidative burden (Zaboli et al., 2019; Sahin et al., 2006). In our lambs, PPARγ downregulation may therefore reflect a shared metabolic vulnerability across liver and muscle, with broader implications for energy partitioning and immune regulation. In parallel, the oxidative stress signature revealed a striking dichotomy between SOD1 and FOXO3 responses across tissues. While liver SOD1 expression was significantly decreased, FOXO3 was robustly upregulated, suggesting that the liver may initiate a compensatory antioxidant response through FOXO3 activation in the face of declining enzymatic antioxidant capacity. This pattern underscores the concept of transcriptional reprogramming in response to redox imbalance, a phenomenon previously observed in hepatocytes subjected to chronic oxidative load (Guo et al., 2021; Rao et al., 2023). In muscle, SOD1 expression remained unchanged, whereas FOXO3 showed a slight, non-significant increase, suggesting a blunted or delayed antioxidant adaptation in skeletal tissue. These findings are reinforced by two-way ANOVA results and tissue × treatment interactions, which confirmed that the liver mounted a stronger transcriptional response to heat exposure, particularly in genes associated with oxidative regulation. The positive correlation between FOXO3 and SOD1 in both tissues—more robust under heat stress—further supports a coordinated oxidative defense strategy, albeit one more effectively deployed in hepatic tissue. This pattern mirrors findings in heat-stressed goats and dairy cattle, where the liver consistently exhibits higher antioxidant gene induction and greater transcriptional plasticity under thermal challenge (Sejian et al., 2021; Wheelock et al., 2010). Moreover, FOXO3’s central regulatory role is strongly implicated in this transcriptional adaptation. As a transcription factor that orchestrates the expression of a broad network of redox, autophagy, and cell cycle arrest genes (Calnan and Brunet, 2008), its upregulation likely represents a higher-order protective strategy against cellular injury. Indeed, its induction under stress has been reported to facilitate mitochondrial maintenance and preserve cellular integrity, especially in metabolically active tissues (Eijkelenboom and Burgering, 2013; Lei et al., 2022). The stronger FOXO3 response in the liver may thus reflect a systemic prioritization of hepatic detoxification and antioxidant capacity over localized stress mitigation in peripheral tissues like skeletal muscle. The differential regulation of heat shock proteins (HSPs) and apoptotic markers further illustrates the tissue-specific molecular architecture of the heat stress response. In both liver and skeletal muscle, HSP70 expression was strongly induced, but the magnitude of upregulation was significantly higher in muscle, as evidenced by both fold-change analysis and a significant tissue × treatment interaction. This aligns with the well-established role of HSP70 as a molecular chaperone involved in maintaining protein homeostasis under stress by refolding misfolded proteins and preventing proteotoxic aggregation (Kregel, 2002; Liu et al., 2016). The pronounced HSP70 response in skeletal muscle, a tissue with high metabolic turnover and contractile protein abundance, likely reflects its increased susceptibility to protein denaturation and accumulation of misfolded intermediates under thermal strain. Interestingly, HSP90 exhibited an opposing tissue response: while it was significantly upregulated in muscle, its expression was markedly downregulated in liver. This divergence may reflect distinct regulatory feedback loops governing HSP90 activity in different tissues, or even differences in proteostasis burden. HSP90 is known to participate in signal transduction, steroid receptor maturation, and cytoskeletal integrity, and its suppression in the liver may signify a negative feedback response to prolonged stress or resource reallocation toward more essential cytoprotective systems (Arya et al., 2007; Zhao et al., 2022). Conversely, its upregulation in muscle supports its cooperative role with HSP70 in maintaining sarcoplasmic protein integrity during sustained hyperthermia. Such contrasting patterns between HSP70 and HSP90 in liver and muscle echo findings in other heat-stressed species, where tissue-specific proteostasis responses serve as adaptive mechanisms under differential thermal burdens (De Paepe et al., 2009; Dangi et al., 2017). This molecular proteotoxic stress signature was further supported by expression patterns of CASP3, a key executioner of the apoptotic cascade. Heat stress significantly upregulated CASP3 in both tissues, with a more substantial induction observed in muscle. This likely reflects a greater cellular turnover or damage load in contractile tissue, possibly due to cumulative oxidative stress, impaired mitochondrial function, and calcium dysregulation—all of which are potentiated under high ambient temperatures (Garrido et al., 2006; Liu et al., 2015). The positive correlation between HSP70 and CASP3 in muscle (r = 0.72, P = 0.005) observed in this study reinforces the concept that intense heat shock responses may co-occur with pro-apoptotic signaling, particularly when cytoprotective mechanisms are overwhelmed. While HSP70 is classically anti-apoptotic, its excessive induction can signify tipping points beyond cellular repair capacity (Zhang et al., 2014), potentially explaining its coordination with CASP3 transcription under sustained thermal challenge. From a physiological perspective, the integration of molecular stress markers with whole-animal responses presents a coherent narrative: skeletal muscle, despite mounting strong proteostatic and apoptotic gene responses, appears more vulnerable to thermal damage. This is functionally consistent with the elevated core temperature, respiratory effort, and cardiovascular strain observed in heat-stressed lambs, which collectively impose a heavy metabolic burden on peripheral tissues. Conversely, the liver’s more balanced stress gene regulation, characterized by moderate HSP70 induction, HSP90 suppression, and strong FOXO3 activation, points to a more adaptive and energy-efficient protective profile, possibly reflecting its critical systemic role in managing oxidative metabolites and acute-phase responses (Horowitz, 2002; Gaughan et al., 2013). The expression patterns of myogenic and structural genes further contextualize these findings. Notably, MYOD—a master transcriptional regulator of muscle cell differentiation—was significantly downregulated in skeletal muscle under heat stress. This finding indicates a suppression of myogenic commitment and regenerative capacity, potentially as a trade-off under catabolic conditions where survival and stress mitigation override anabolic processes (Lian et al., 2022). The heat-induced decline in MYOD has been similarly reported in poultry and rodents, where thermal stress inhibits satellite cell activity and muscle regeneration (Rhoads et al., 2013; Lu et al., 2023). In contrast, ACTB3, a gene encoding a cytoskeletal protein involved in contractile fiber maintenance, was not significantly affected, suggesting that muscle structural integrity is more transcriptionally preserved than its growth or repair potential. Together, these data suggest that chronic heat exposure impairs muscle homeostasis at multiple levels: increasing apoptotic load, suppressing regenerative signaling, and inducing chaperone machinery to mitigate protein misfolding. While these mechanisms may prolong tissue function under stress, they are unlikely to be sustainable long-term, and may underlie observed reductions in growth performance and feed efficiency. Importantly, such changes reflect not only damage pathways but also adaptive reprogramming that prioritizes cellular survival over growth, a strategy well-documented in heat-stressed livestock and confirmed here in lambs (Sejian et al., 2018; Lian et al., 2022). The transcriptional signatures identified in skeletal muscle tissue under chronic heat stress extend beyond physiological adaptation—they likely have direct consequences for postmortem muscle biochemistry, meat quality traits, and commercial carcass value. While the primary objective of this study was to characterize the molecular and physiological heat stress response, the findings involving key regulatory and structural genes such as MYOD, ACTB3, CASP3, PPARγ, HSP70, and FOXO3 suggest that muscle integrity, growth dynamics, and proteolytic activity are being fundamentally altered under thermal challenge, with downstream implications for meat yield, tenderness, water-holding capacity, and oxidative stability. Among the most striking transcriptional changes observed was the significant downregulation of MYOD, a master transcription factor essential for the commitment of satellite cells to myogenic lineage and for the regulation of muscle fiber differentiation (Lian et al., 2022). MYOD also plays a role in maintaining the proliferative capacity of myoblasts and coordinating their fusion into mature myofibers, particularly under stress or injury conditions. Suppression of MYOD, as observed in this study, indicates a suppressed myogenic program, suggesting that chronic heat exposure redirects cellular resources away from regenerative growth toward stress mitigation. Similar suppression of MYOD has been reported in heat-stressed broilers, leading to impaired breast muscle development and altered fiber morphology (Li et al., 2021), and in rodents, where thermal stress reduced satellite cell proliferation and regenerative potential (Rhoads et al., 2013). In lambs, such transcriptional downregulation may translate into reduced muscle accretion, altered fiber type composition, and decreased muscle mass, particularly in rapidly growing individuals. The downregulation of MYOD may also be linked to impaired meat tenderness and protein turnover, as satellite cell dysfunction limits the renewal of damaged myofibers and affects proteolytic enzyme access postmortem (Lian et al., 2022). Furthermore, lower MYOD expression during growth correlates with reduced expression of myofibrillar proteins such as myosin heavy chain and tropomyosin, whose postmortem degradation patterns strongly influence tenderness development during aging (Liu et al., 2015). Consequently, MYOD suppression under chronic heat stress could result in tougher meat texture, reduced proteolytic fragmentation of Z-discs, and lower shear force values—findings supported by comparable studies in heat-stressed sheep and goats (Archana et al., 2018; Sejian et al., 2018). In contrast to MYOD, ACTB3—a gene encoding a cytoskeletal protein structurally related to β-actin and involved in maintaining sarcomeric architecture—was not significantly altered by heat stress, although it exhibited a slight upward trend. The transcriptional stability of ACTB3 under stress may reflect a conserved role in preserving structural integrity, even as regenerative pathways are suppressed. This is noteworthy, as sarcomeric proteins contribute to both muscle function in vivo and textural properties in meat postmortem. Stable ACTB3 expression may help maintain the integrity of contractile elements and prevent excessive proteolysis, thereby contributing to initial firmness and color stability. However, without adequate myogenic stimulation (as signaled by MYOD), long-term muscle growth and turnover could be compromised despite maintained structural gene expression. Another critical component of muscle biology affected by heat stress is apoptotic regulation, particularly through the activation of CASP3. The observed significant upregulation of CASP3 in muscle under chronic thermal exposure reflects increased apoptotic pressure, possibly due to cumulative oxidative damage, mitochondrial dysfunction, or endoplasmic reticulum stress. CASP3 is the executioner caspase responsible for cleaving cytoskeletal and nuclear proteins during programmed cell death (Garrido et al., 2006). Its upregulation in muscle not only signals enhanced cell turnover but also has direct implications for meat quality: higher CASP3 activity pre-slaughter has been associated with increased protein degradation, reduced muscle fiber integrity, and enhanced postmortem proteolysis, leading to early onset of tenderness (Ouali et al., 2006). However, excessive CASP3 activity may also contribute to protein denaturation and increased drip loss, thereby compromising water-holding capacity and cooking yield (Zhang et al., 2014). In parallel, the robust induction of HSP70, particularly in skeletal muscle, suggests significant proteotoxic stress under heat exposure. HSP70 is known to inhibit apoptosis by binding to Apaf-1 and blocking caspase activation (Kregel, 2002), but its overexpression may signal the threshold of cellular repair capacity being exceeded. High levels of HSP70 in muscle have been linked to reduced muscle protein degradation postmortem, slower tenderization, and increased thermal stability of sarcoplasmic proteins, which can affect both texture and flavor (Zhang et al., 2016). Moreover, HSP70 accumulation has been associated with color instability, due to its role in modulating myoglobin oxidation and mitochondrial activity (Garrido et al., 2006). Thus, while HSP70 serves a protective role in vivo, its persistence may reduce meat quality attributes depending on postmortem handling and aging protocols. The transcriptional behavior of FOXO3, which was significantly upregulated in liver and modestly increased in muscle, further contributes to the regulation of oxidative homeostasis and autophagy, both of which influence meat shelf-life and lipid oxidation. FOXO3 activation promotes the expression of antioxidant enzymes such as catalase and SOD2, as well as autophagy-related genes (Calnan and Brunet, 2008). In muscle, enhanced FOXO3 activity could improve cellular resilience to oxidative damage, but sustained activation is also known to induce muscle atrophy-related genes (e.g., atrogin-1, MuRF1), leading to lean mass loss and altered muscle-to-fat ratios (Eijkelenboom and Burgering, 2013). These changes could contribute to decreased marbling and leaner carcasses, as reported in heat-stressed goats and sheep (Ahmadpour et al., 2025). Equally important is the observed downregulation of PPARγ in both liver and muscle tissues. As a key nuclear receptor regulating adipocyte differentiation, lipid uptake, and fatty acid storage, PPARγ suppression under thermal stress likely reflects a shift away from anabolic lipid metabolism (Zaboli et al., 2019). In the context of muscle, reduced PPARγ activity may limit intramuscular fat deposition (IMF), leading to poorer marbling scores and dry, less flavorful meat—a concern for lamb producers targeting high-quality cuts. Moreover, PPARγ is involved in anti-inflammatory signaling, and its downregulation may amplify local inflammatory cascades, potentially affecting muscle pH decline, protease activation, and meat color stability (Manickam et al., 2020). Taken together, the transcriptional changes identified in skeletal muscle under chronic heat stress portray a biological shift from anabolic growth to catabolic maintenance, driven by a convergence of suppressed myogenesis (MYOD), enhanced apoptosis (CASP3), cellular repair saturation (HSP70), and impaired lipid metabolism (PPARγ). These molecular events are highly consistent with previously reported declines in meat quality parameters in heat-stressed ruminants, including increased toughness, reduced IMF, altered fiber structure, and lower carcass dressing percentages (Sejian et al., 2018; Archana et al., 2018). While the present study did not include direct postmortem meat quality measurements, the gene expression profiles serve as strong molecular proxies, allowing for predictive inferences supported by physiological and metabolic logic. This transcriptional profile, when combined with phenotypic indicators such as feed intake, growth rate, and rectal temperature, could potentially be used as a screening framework for carcass quality risk under heat stress, particularly in breeding or management contexts aiming to optimize meat yield and quality. Importantly, this also raises the possibility of nutritional or pharmacological interventions aimed at preserving muscle function during thermal exposure. For example, targeting the FOXO3–SOD1–PPARγ axis through antioxidant supplementation or metabolic modulators may mitigate muscle catabolism and preserve IMF content. Nevertheless, scientific caution is warranted. The translation of gene expression to actual meat quality traits involves complex, multiscale regulation, including hormonal status, slaughter stress, and postmortem processing. While the genes discussed here are mechanistically linked to meat traits, functional confirmation via carcass measurements and protein-level validations would strengthen predictive claims. Future studies incorporating proteomics, meat chemistry, and sensory analysis will be instrumental in validating the molecular predictors identified in this work. To move beyond individual gene responses and better capture the functional interplay between key molecular pathways, this study utilized integrative expression ratios—specifically, SOD1/IL-6 and FOXO3/TNF-α—as composite indices reflecting the balance between oxidative defense and inflammation. These ratios were significantly elevated in heat-stressed lambs, particularly in liver tissue, where the SOD1/TNF-α ratio increased by more than twofold relative to controls. This shift denotes a functional pivot toward antioxidant dominance, suggestive of an adaptive attempt to suppress systemic inflammation through redox buffering mechanisms. Such composite transcriptional metrics offer several advantages over single-gene analyses. First, they provide a contextualized signal, capturing not just the magnitude but the directionality of cross-pathway interactions. Second, they are more resistant to inter-animal variability, especially in heterogeneous physiological systems like the liver. Third, as demonstrated in this study, they correlate meaningfully with physiological outcomes. Indeed, higher SOD1/IL-6 and FOXO3/TNF-α ratios were negatively associated with rectal temperature (r = –0.61, P = 0.011), suggesting that animals with transcriptional profiles favoring antioxidant defense over inflammation maintained better thermoregulation. This finding is consistent with the broader literature indicating that thermotolerant phenotypes often exhibit more controlled inflammatory responses and greater oxidative resilience (Leon and Helwig, 2010; Lara and Rostagno, 2013). In goats, cattle, and poultry, animals with higher antioxidant enzyme expression and lower pro-inflammatory cytokine activity show reduced signs of heat-induced tissue injury and better growth performance under heat stress (Sanz Fernandez et al., 2015; Jimoh et al., 2023). The present study reinforces that conclusion at the transcriptional level and provides a quantitative framework for molecular phenotyping of resilience in small ruminants. Moreover, hierarchical clustering of gene expression ratios revealed the existence of a distinct subpopulation of heat-stressed lambs characterized by elevated antioxidant/inflammatory ratios and lower expression of HSP70, IL-6, and CASP3. These animals also showed higher FOXO3 and SOD1 expression, alongside reduced TNF-α and PPARγ levels, forming a coherent gene expression signature that aligns with lower physiological stress markers (e.g., rectal temperature and heart rate). This transcriptional phenotype may represent a resilient cluster, exhibiting a more balanced redox-inflammatory state and attenuated apoptotic drive under thermal challenge. These findings suggest that such ratios may serve as potential molecular indicators of thermotolerance, though their application as biomarkers will require further validation across breeds, time points, and predictive models. Unlike traditional markers that require extensive phenotyping under environmental stress, gene expression-based indices can be quantified from minimally invasive tissue samples and have the potential to reflect latent physiological adaptability. While further validation across breeds and environmental contexts is necessary, the predictive capacity of these ratios for thermophysiological outcomes underscores their translational utility in precision livestock farming. At the network level, correlation matrix analysis further supported these integrative interpretations. Under normal conditions, co-expression patterns were relatively weak and scattered, suggesting independent regulation of stress, inflammatory, and antioxidant genes. However, under heat stress, correlations became stronger, more polarized, and biologically coherent. For instance, HSP70 showed a significant negative correlation with TNF-α (r = –0.74, P = 0.0095), and FOXO3 was strongly negatively correlated with TNF-α (r = –0.78, P = 0.0045). These findings imply that as thermal load increases, transcriptional networks reconfigure, favoring mutual antagonism between inflammation and antioxidant responses. Such emergent correlation structures are indicative of stress-induced regulatory realignment, in which certain pathways (e.g., antioxidant defenses) are upregulated in concert, while others (e.g., inflammation) are suppressed, or vice versa. This observation aligns with prior heat stress studies in dairy cattle and chickens, which demonstrated increased co-regulation between metabolic and immune-related genes during thermal adaptation (Quinteiro-Filho et al., 2012; Guo et al., 2021; Bahrami-Yekdangi et al., 2022). Thus, gene–gene correlation patterns may serve not only as descriptive tools but also as dynamic indicators of network-level plasticity under environmental stress. While this study provides insight into coordinated expression patterns using PCA and correlation matrices, a more comprehensive systems-level understanding of heat stress responses would benefit from pathway-based network analysis. Tools such as STRING, KEGG, or Gene Ontology (GO) enrichment could identify co-regulated modules, upstream regulators, or shared signaling pathways among differentially expressed genes. Future research incorporating such bioinformatics platforms—ideally with broader transcriptomic coverage—could clarify the mechanistic underpinnings of heat-induced gene networks and their relevance to thermotolerance. While the results of this study provide a detailed and multidimensional portrait of the physiological and molecular consequences of chronic heat stress in lambs, several important considerations warrant discussion. First, although the environmental model using naturally occurring thermal gradients between Semirom and Afzar offered a realistic and ecologically valid setting, it also introduced potential confounders—such as variations in microclimate, air movement, and animal activity—that cannot be completely controlled in open-field systems. However, the magnitude of environmental differentiation, confirmed through THI values and physiological responses, strongly supports the biological validity of the heat stress contrast, especially given the chronic duration (42 days) and the statistical robustness of observed changes. Second, while the study focused on transcriptional responses in two key peripheral tissues—liver and skeletal muscle—it does not encompass the full systemic impact of heat stress. The inclusion of hypothalamic or adrenal gene expression, for instance, might provide deeper insights into neuroendocrine regulation and stress axis activation, which are known to interact with peripheral inflammation and metabolic signaling (Ortiz-Colón et al., 2018; Sejian et al., 2021). Moreover, post-transcriptional regulation, including miRNA dynamics, protein translation rates, and post-translational modifications, were beyond the scope of this study but are important mediators of heat stress outcomes and merit future investigation (Yadav et al., 2021). Third, while qPCR offered a high degree of specificity and technical reproducibility—as demonstrated by amplification efficiencies, melt curve profiles, and the stability of the reference gene (ACTB, M value < 0.4)—the analysis was limited to a targeted gene panel. Broader transcriptomic tools such as RNA-Seq or single-cell RNA profiling could uncover additional pathways and regulatory networks involved in thermotolerance, especially those related to nutrient sensing, angiogenesis, and tissue remodeling (Archana et al., 2017; Liang et al., 2022). Nevertheless, the gene panel selected in this study was grounded in well-established thermal stress literature and provided strong mechanistic anchors for interpreting physiological outcomes, particularly when integrated into pathway-level analyses. Importantly, the present findings have several practical implications for livestock production under increasingly frequent and prolonged heat stress conditions. The molecular signature of heat resilience, defined by elevated SOD1/IL-6 and FOXO3/TNF-α ratios, as well as reduced CASP3 and HSP70 expression in muscle, could serve as a predictive phenotype for selecting thermotolerant individuals. This approach aligns with the ongoing efforts in genomic selection programs to incorporate environmental adaptability into breeding indices (Collier et al., 2019; Carabaño et al., 2017). Furthermore, dietary interventions targeting antioxidant pathways—e.g., selenium, vitamin E, or plant-derived polyphenols—may be used to enhance the FOXO3-SOD1 axis, providing prophylactic support against heat-induced oxidative damage (Sahin et al., 2006; Manickam et al., 2010). Lastly, it is critical to maintain scientific humility in interpreting these results. While the patterns observed are robust, statistically significant, and biologically plausible, they represent snapshots within a complex, time-evolving physiological landscape. It remains unclear whether the observed transcriptional adaptations persist over longer periods, or how reversible they are once thermal stress is alleviated. Additionally, inter-individual variability, epigenetic plasticity, and gene-by-environment interactions may modify these responses in different breeds, ages, or nutritional statuses. Conclusion This study provides a comprehensive molecular and physiological characterization of lamb responses to prolonged heat stress under field-relevant environmental conditions, with emphasis on gene expression patterns in two key metabolic tissues: liver and skeletal muscle. The integration of transcriptional profiling, physiological measurements, and tissue-specific interpretation reveals that chronic thermal load elicits coordinated but distinct gene expression programs across tissues, with critical implications for thermotolerance, health, and production traits in small ruminants. In the liver, which plays a central role in systemic metabolic regulation and immune modulation, oxidative stress-related genes such as SOD1 and FOXO3 were significantly upregulated, indicating an active transcriptional adaptation aimed at reinforcing redox homeostasis. Simultaneously, inflammatory cytokines TNF-α and IL-6 were significantly downregulated, suggesting effective hepatic suppression of inflammatory signaling. The concurrent upregulation of antioxidant pathways and suppression of pro-inflammatory responses underscores a protective hepatic transcriptional phenotype under thermal stress, one that may buffer systemic oxidative and immune challenges. Additionally, PPARγ, a key regulator of lipid metabolism and anti-inflammatory signaling, was significantly downregulated in the liver, suggesting a shift away from anabolic lipid processing under prolonged heat exposure. In skeletal muscle, the transcriptional response diverged. While FOXO3 was slightly but not significantly increased, SOD1 expression remained unchanged, indicating a relatively muted antioxidant response compared to the liver. Instead, heat shock proteins HSP70 and HSP90 were significantly upregulated, with HSP70 showing particularly strong induction, highlighting intense proteotoxic stress and cellular protein unfolding. The strong induction of CASP3 in muscle suggests activation of apoptotic pathways, indicating that muscle tissue may be more prone to cellular damage or turnover under sustained heat exposure. This was further supported by the downregulation of MYOD, a key myogenic transcription factor essential for muscle fiber development and regeneration. The suppression of MYOD, alongside the stable expression of the structural gene ACTB3, suggests that muscle anabolic activity is compromised while structural maintenance is preserved, a pattern consistent with reduced muscle growth potential without overt degradation. These molecular adaptations were closely aligned with whole-animal physiological responses. Lambs housed in the heat-stressed region exhibited significantly elevated rectal temperatures, respiratory rates, and heart rates, indicating substantial thermophysiological strain. Performance metrics such as feed intake and average daily gain were also significantly reduced, consistent with the metabolic cost of heat adaptation. Importantly, correlation analysis revealed strong negative relationships between inflammatory and antioxidant gene expression, and positive associations between heat shock and apoptotic markers, supporting the presence of an integrated cellular stress network. These relationships were particularly evident under heat stress, reflecting a transcriptionally re-wired landscape optimized for survival under prolonged environmental challenge. The study also introduced integrative gene expression ratios, such as SOD1/IL-6 and FOXO3/TNF-α, which were significantly elevated under heat stress and negatively correlated with rectal temperature. These composite metrics reflect the balance between cytoprotective and inflammatory pathways and may serve as potential biomarkers of thermotolerance. Hierarchical clustering of these ratios delineated a distinct subgroup of heat-exposed lambs with favorable expression profiles—characterized by higher antioxidant-to-inflammation ratios and lower expression of HSP70 and CASP3—suggesting a resilient molecular phenotype associated with improved physiological performance. Importantly, while the transcriptomic findings offer mechanistic insights into the biological response to heat stress, certain limitations must be acknowledged. First, gene expression was assessed only at the mRNA level; protein-level validation (e.g., via Western blotting, ELISA, or activity assays) was not performed. The translation of transcript abundance into functional protein levels is not always linear, and future studies should include proteomic and enzymatic validations to confirm these molecular signatures. Second, although the study design leveraged naturally distinct thermal environments to simulate realistic field conditions, it inherently introduced several uncontrolled environmental variables beyond temperature and humidity. Factors such as altitude, wind exposure, solar radiation, airflow patterns, and forage quality—all of which can influence animal physiology and gene expression independently of THI—were not experimentally controlled. These variables may have contributed to some of the observed differences in gene expression between the two geographic sites. While efforts were made to standardize diet composition and housing conditions, subtle differences in nutrient content of local forage, microclimatic airflow, or elevation-related hypoxia could confound the attribution of transcriptional changes solely to thermal stress. To isolate the specific effects of heat load and better control for environmental confounders, future studies are encouraged to complement field-based observations with chamber-based experiments, where temperature, humidity, and other variables can be precisely manipulated while keeping all other factors constant. Third, the study was limited to a single breed and sex (male lambs) and was conducted under specific climatic and management conditions, which may limit generalizability. Breed-specific or sex-specific transcriptional plasticity in response to heat stress should be evaluated to ensure broader applicability. Fourth, although associations were drawn between gene expression and physiological indicators, no direct measurements of carcass traits or meat quality outcomes were collected. Given the observed downregulation of MYOD and PPARγ, and the upregulation of CASP3 and HSP70, potential impacts on meat quality—including tenderness, water-holding capacity, and marbling—are likely and warrant empirical validation. Future research should aim to expand on these findings by: Including additional breeds and sexes, and sampling under varying agroecological contexts to capture population-wide variability in heat response. Incorporating proteomic, metabolomic, and immunohistochemical analyses to validate transcriptional changes at functional and structural levels. Conducting longitudinal studies to track the dynamics of gene expression over the full course of heat exposure and recovery, to distinguish between transient versus sustained transcriptional adaptations. Linking gene expression profiles to phenotypic outcomes, including growth metrics, meat quality indices (e.g., IMF content, shear force, pH), and immune competence, to establish practical predictive models for performance under thermal stress. Evaluating the efficacy of nutritional interventions, such as antioxidant-rich diets (selenium, vitamin E, polyphenols), in modulating key regulatory pathways including the FOXO3–SOD1 axis and inflammatory mediators. From a practical standpoint, these findings have important implications for animal breeding, nutritional management, and thermal mitigation strategies in small ruminant production systems. The identification of heat-responsive gene networks and expression ratios provides a basis for the development of molecular diagnostics for early detection of thermal distress, as well as for the selection of resilient animals in genetic improvement programs. Incorporating expression-based indicators into precision livestock monitoring systems could enable real-time assessment of stress burden and inform adaptive interventions such as cooling infrastructure, shading, or targeted dietary supplementation. In conclusion, this study offers a robust, multi-layered view of the molecular and physiological adaptations of lambs to chronic heat stress, highlighting both shared and tissue-specific strategies involving oxidative defense, inflammatory modulation, protein stability, apoptosis, and muscle development. The liver emerged as a more resilient organ through coordinated antioxidant and anti-inflammatory regulation, while skeletal muscle bore greater stress burden, with elevated heat shock and apoptotic responses and suppressed myogenic signaling. The identification of transcriptional ratios and correlation structures as indicators of thermotolerance represents a significant advance in the molecular phenotyping of stress resilience. As global climate change accelerates, such mechanistic insight will be critical for developing sustainable livestock systems that balance productivity, welfare, and environmental adaptation. Declarations Acknowledgments The authors extend their sincere gratitude to SabzBavaran-e-NouAndish Co. for their invaluable technical assistance and the provision of laboratory facilities, which were instrumental in the successful execution of this research. The authors also wish to thank the Jafarbiglou clan of the Qashqaei Tribal Confederation for their kind cooperation and generous provision of camels, which significantly contributed to the field component of the study. Funding This research was financially supported by Yasouj University through grant number 4024443009, awarded to Dr. Amir Ahmadpour. The funding was exclusively allocated for the research, development, and preparation of this manuscript. No additional financial support was received from other public, commercial, or not-for-profit funding agencies. Competing Interests The authors declare no competing interests—financial, professional, or personal—that could have influenced the integrity, analysis, or presentation of the research findings. There are no affiliations, memberships, financial relationships, or other connections that could be perceived as potential conflicts of interest regarding the authorship or publication of this article. Author Contributions Amir Ahmadpour contributed to the study’s conceptualization, experimental supervision, methodological framework, field investigation, data acquisition, manuscript review and editing, and was responsible for securing funding. Mousa Zarrin was involved in conceptual design, statistical validation, data analysis, and the preparation of the original manuscript draft. Rafid Hafedh Sabeeh Alrahif assisted in fieldwork, including data and sample collection. All authors reviewed and approved the final version of the manuscript prior to submission. Data Availability The datasets generated and analyzed during the current study are not publicly available due to institutional policies at Yasouj University. However, data may be made available upon reasonable request from the corresponding author, contingent upon approval by the affiliated institution and the research sponsor. References Ahmadpour A, Forouzanfar S, Ghazanfari S, Hafedh Sabeeh Alrahif R, Zarrin M (2025) Comparative Analysis of Feeding Strategies on the Growth and Carcass Quality of Turki-Qashqai Lambs: A Focus on Supplementary Feed Concentration. Iranian Journal of Applied Animal Science 15(1):61–71. https://doi.org/10.71798/ijas.2025.1202959 Archana PR, Sejian V, Ruban W, Bagath M, Krishnan G, Aleena J, Manjunathareddy GB, Beena V, Bhatta R (2018) Comparative assessment of heat stress induced changes in carcass traits, plasma leptin profile and skeletal muscle myostatin and HSP70 gene expression patterns between indigenous Osmanabadi and Salem Black goat breeds. Meat Sci 141:66–80. https://doi.org/10.1016/j.meatsci.2018.03.015 Arya R, Mallik M, Lakhotia SC (2007) Heat shock genes—integrating cell survival and death. Journal of Biosciences 32(3):595–610. https://doi.org/10.1007/s12038-007-0059-3 Bahrami Yekdangi M, Ghorbani GR, Sadeghi‑Sefidmazgi A, Mahnani A, Drackley JK, Ghaffari MH (2022) Identification of cow-level risk factors and associations of selected blood macro-minerals at parturition with dystocia and stillbirth in Holstein dairy cows. Scientific Reports 12:5929. https://doi.org/10.1038/s41598-022-09928-w Calnan DR, Brunet A (2008) The foxo code. Oncogene 27(16):2276–2288. https://doi.org/10.1038/onc.2008.21 Carabaño MJ, Ramón M, Díaz C, Molina A, Pérez Guzmán MD, Serradilla JM (2017) Breeding for resilience to heat stress effects in dairy ruminants: A comprehensive review. Journal of Animal Science 95(4):1813–1826. https://doi.org/10.2527/jas.2016.1250 Collier RJ, Dahl GE, VanBaale MJ (2006) Major advances associated with environmental effects on dairy cattle. J Dairy Sci 89(4):1244–1253. https://doi.org/10.3168/jds.S0022-0302(06)72193-2 Collier RJ, Gebremedhin KG (2015) Thermal biology of domestic animals. Annu Rev Anim Biosci 3(1):513–532. https://doi.org/10.1146/annurev-animal-022114-110659 Collier RJ, Baumgard LH, Zimbelman RB, Xiao Y (2019) Heat stress: physiology of acclimation and adaptation. Animal Frontiers 9(1):12–19. https://doi.org/10.1093/af/vfy034 Dangi SS, Bharati J, Abdul Samad H, Bhure SK, Singh G, Maurya VP, Sarkar M, Kumar P (2017) Expression dynamics of heat shock proteins (HSP) in livestock under thermal stress. In: Heat Shock Proteins in Veterinary Medicine and Sciences , pp 37–79. Das R, Sailo L, Verma N, Bharti P, Saikia J, Kumar R (2016) Impact of heat stress on health and performance of dairy animals: A review. Vet World 9(3):260. https://doi.org/10.14202/vetworld.2016.260-268 De Paepe B, Creus KK, Martin JJ, Weis J, De Bleecker JL (2009) A dual role for HSP90 and HSP70 in the inflammatory myopathies: from muscle fiber protection to active invasion by macrophages. Annals of the New York Academy of Sciences 1173(1):463–469. https://doi.org/10.1111/j.1749-6632.2009.04654.x Eijkelenboom A, Burgering BMT (2013) FOXOs: signalling integrators for homeostasis maintenance. Nat Rev Mol Cell Biol 14(2):83–97. https://doi.org/10.1038/nrm3507 El-Beltagy A, Madkour M (2012) Impact of climate change on arid lands agriculture. Agric Food Secur 1:1–12. https://doi.org/10.1186/2048-7010-1-3 El-Tarabany MS, El-Tarabany AA, Atta MA (2017) Physiological and lactation responses of Egyptian dairy Baladi goats to natural thermal stress under subtropical environmental conditions. Int J Biometeorol 61:61–68. https://doi.org/10.1007/s00484-016-1190-3 Garrido C, Galluzzi L, Brunet M, Puig PE, Didelot C, Kroemer G (2006) Mechanisms of cytochrome c release from mitochondria. Cell Death & Differentiation 13(9):1423–1433. https://doi.org/10.1038/sj.cdd.4401965 Gaughan JB, Bonner SL, Loxton I, Mader TL (2013) Effects of chronic heat stress on plasma concentration of secreted heat shock protein 70 in growing feedlot cattle. Journal of Animal Science 91(1):120–129. https://doi.org/10.2527/jas.2012-5294 Giridhar K, Samireddypalle A (2015) Impact of climate change on forage availability for livestock. In: Climate Change Impact on Livestock: Adaptation and Mitigation , pp 97–112. Springer India. https://doi.org/10.1007/978-81-322-2265-1_7 Guo Z, Gao S, Ouyang J, Ma L, Bu D (2021) Impacts of heat stress-induced oxidative stress on the milk protein biosynthesis of dairy cows. Animals 11(3):726. https://doi.org/10.3390/ani11030726 Horowitz M (2002) From molecular and cellular to integrative heat defense during exposure to chronic heat. Comp Biochem Physiol A Mol Integr Physiol 131(3):475-483. https://doi.org/10.1016/S1095-6433(01)00499-5 Jimoh OA, Daramola OT, Okin Aminu HO, Ojo OA (2023) HSP70, adiponectin, leptin, pro-inflammatory cytokines and metabolic hormones of heat-stressed broilers fed herbal supplements. Journal of Thermal Biology 117:103681. https://doi.org/10.1016/j.jtherbio.2023.103681 Kregel KC (2002) Invited review: heat shock proteins: modifying factors in physiological stress responses and acquired thermotolerance. Journal of Applied Physiology 92(5):2177–2186. https://doi.org/10.1152/japplphysiol.01267.2001 Lamont BJ, Waters MF, Andrikopoulos S (2016) A low-carbohydrate high-fat diet increases weight gain and does not improve glucose tolerance, insulin secretion or β-cell mass in NZO mice. Nutr Diabetes 6(2):e194. https://doi.org/10.1038/nutd.2016.2 Lara LJ, Rostagno MH (2013) Impact of heat stress on poultry production. Animals 3(2):356–369. https://doi.org/10.3390/ani3020356 Lei Z, Wei D, Tang L, Wang S, Pan C, Ma Y, Ma Y (2022) SGK1 affects the phosphorylation of FOXO1/FOXO3 promoting bovine fat deposition via the PI3K/Akt signaling pathway. Leon LR, Helwig BG (2010) Heat stroke: role of the systemic inflammatory response. Journal of Applied Physiology 109(6):1980–1988. https://doi.org/10.1152/japplphysiol.00301.2010 Li S, Zhang Y, Guan Z, Li H, Ye M, Chen X, Shen J et al (2020) SARS-CoV-2 triggers inflammatory responses and cell death through caspase-8 activation. Signal Transduct Target Ther 5(1):235. https://doi.org/10.1038/s41392-020-00334-0 Li X, Zhang M, Feng J, Zhou Y (2021) Myostatin and related factors are involved in skeletal muscle protein breakdown in growing broilers exposed to constant heat stress. Animals 11(5):1467. https://doi.org/10.3390/ani11051467 Lian D, Chen MM, Wu H, Deng S, Hu X (2022) The role of oxidative stress in skeletal muscle myogenesis and muscle disease. Antioxidants 11(4):755. https://doi.org/10.3390/antiox11040755 Liu T, Zhang L, Joo D, Sun SC (2017) NF-κB signaling in inflammation. Signal Transduct Target Ther 2(1):1–9. https://doi.org/10.1038/sigtrans.2017.23 Liu Y, Cai H, Guo X, Aierken A, Hua J, Ma B, Peng S (2022) Melatonin alleviates heat stress-induced testicular damage in dairy goats by inhibiting the PI3K/AKT signaling pathway. Stress Biol 2(1):47. https://doi.org/10.1007/s44154-022-00069-8 Liu YL, Ding KN, Shen XL, Liu HX, Zhang YA, Liu YQ, He YM, Tang LP (2022) Chronic heat stress promotes liver inflammation in broilers via enhancing NF-κB and NLRP3 signaling pathway. BMC Vet Res 18(1):289. https://doi.org/10.1186/s12917-022-03387-1 Liu H, Mao P, Wang J, Wang T, Xie CH (2015) Allicin protects PC12 cells against 6-OHDA-induced oxidative stress and mitochondrial dysfunction via regulating mitochondrial dynamics. Cellular Physiology and Biochemistry 36(3):966–979. https://doi.org/10.1159/000430271 Liu L, Fu C, Yan M, Xie H, Li S, Yu Q, He S, He J (2016) Resveratrol modulates intestinal morphology and HSP70/90, NF-κB and EGF expression in the jejunal mucosa of black-boned chickens on exposure to circular heat stress. Food & Function 7(3):1329–1338. https://doi.org/10.1039/c5fo01338k Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25(4):402–408. https://doi.org/10.1006/meth.2001.1262 Lu J, Li H, Yu D, Zhao P, Liu Y (2023) Heat stress inhibits the proliferation and differentiation of myoblasts and is associated with damage to mitochondria. Frontiers in Cell & Developmental Biology 11:1171506. https://doi.org/10.3389/fcell.2023.1171506 Mader TL, Davis MS, Brown-Brandl T (2006) Environmental factors influencing heat stress in feedlot cattle. J Anim Sci 84(3):712–719. https://doi.org/10.2527/2006.843712x Manickam R, Duszka K, Wahli W (2020) PPARs and microbiota in skeletal muscle health and wasting. International Journal of Molecular Sciences 21(21):8056. https://doi.org/10.3390/ijms21218056 Marai IFM, El-Darawany AA, Fadiel A, Abdel-Hafez MAM (2007) Physiological traits as affected by heat stress in sheep—a review. Small Rumin Res 71(1–3):1–12. https://doi.org/10.1016/j.smallrumres.2006.10.003 Omidi A, Nazifi S, Rasekh M, Zare N (2024) Heat-shock proteins, oxidative stress, and antioxidants in one-humped camels. Trop Anim Health Prod 56(1):29. https://doi.org/10.1007/s11250-023-03870-3 Ortiz-Colón G, Fain SJ, Parés IK, Curbelo‑Rodríguez J, Jiménez‑Cabán E, Pagán‑Morales M, Gould WA (2018) Assessing climate vulnerabilities and adaptive strategies for resilient beef and dairy operations in the tropics. Climatic Change 146(1-2):47–58. https://doi.org/10.1007/s10584-017-2110-1 Ouali A, Herrera‑Mendez CH, Coulis G, Becila S, Boudjellal A, Aubry L, Sentandreu MA (2006) Revisiting the conversion of muscle into meat and the underlying mechanisms. Meat Science 74(1):44–58. https://doi.org/10.1016/j.meatsci.2006.05.010 Quinteiro-Filho WM, Rodrigues MV, Ribeiro A, Ferraz-de-Paula V, Pinheiro ML, Sá LRM, Ferreira AJP, Palermo-Neto J (2012) Acute heat stress impairs performance parameters and induces mild intestinal enteritis in broiler chickens: role of acute hypothalamic-pituitary-adrenal axis activation. J Anim Sci 90(6):1986-1994. https://doi.org/10.2527/jas.2011-3949 Rao KVV, Rani MU, Reddy AG, Kumar BA (2023) Bovine Lactoferrin Mitigates Oxidative Stress and Inflammation in CCL4 and High-fat Diet-induced NAFLD in C57BL/6 Mice. Indian J Anim Res 1:9. Rhoads RP, Flann KL, Cardinal TR, Rathbone CR, Liu X, Allen RE (2013) Satellite cells isolated from aged or dystrophic muscle exhibit a reduced capacity to promote angiogenesis in vitro. Biochemical and Biophysical Research Communications 440(3):399–404. https://doi.org/10.1016/j.bbrc.2013.09.085 Sahin K, Onderci M, Sahin N, Gursu MF, Khachik F, Kucuk O (2006) Effects of lycopene supplementation on antioxidant status, oxidative stress, performance and carcass characteristics in heat-stressed Japanese quail. J Therm Biol 31(4):307-312. https://doi.org/10.1016/j.jtherbio.2006.01.002 Sejian V (2013) Climate change: impact on production and reproduction, adaptation mechanisms and mitigation strategies in small ruminants: a review. Indian J Small Rumin 19(1):1–21. Sejian V, Bhatta R, Gaughan JB, Dunshea FR, Lacetera N (2018) Adaptation of animals to heat stress. Animal 12(s2):s431–s444. https://doi.org/10.1017/S1751731118001945 Sejian V, Silpa MV, Nair MRR, Devaraj C, Krishnan G, Bagath M, Chauhan SS et al. (2021) Heat stress and goat welfare: Adaptation and production considerations. Animals 11(4):1021. https://doi.org/10.3390/ani11041021 Song Y, Xie X, Wang Y, Gao W, Huang H, Cao F, Yang X (2024) Identification of Superoxide Dismutase (SOD) Gene Family in Ginkgo (Ginkgo biloba L.) and Role of GbSOD8 in Response to Salt Stress. Forests 15(12):2141. https://doi.org/10.3390/f15122141 Tang Y, Zhou X, Cao T, Chen E, Li Y, Lei W, Hu Y, He B, Liu S (2022) Endoplasmic reticulum stress and oxidative stress in inflammatory diseases. DNA Cell Biol 41(11):924–934. https://doi.org/10.1089/dna.2022.0265 Sanz Fernandez MV, Johnson JS, Abuajamieh M, Stoakes SK, Seibert JT, Cox L, Kahl S, Elsasser TH, Ross JW, Isom SC, Rhoads RP, Baumgard LH (2015) Effects of heat stress on carbohydrate and lipid metabolism in growing pigs. Physiological Reports 3(2):e12315. https://doi.org/10.14814/phy2.12315 Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT‑PCR data by geometric averaging of multiple internal control genes. Genome Biology 3(7):research0034. https://doi.org/10.1186/gb-2002-3-7-research0034 Wang RH, Liang RR, Lin H, Zhu LX, Zhang YM, Mao YW, Dong PC, Niu LB, Zhang MH, Luo X (2017) Effect of acute heat stress and slaughter processing on poultry meat quality and postmortem carbohydrate metabolism. Poult Sci 96(3):738–746. https://doi.org/10.3382/ps/pew329 Wheelock JB, Rhoads RP, VanBaale MJ, Sanders SR, Baumgard LH (2010) Effects of heat stress on energetic metabolism in lactating Holstein cows. J Dairy Sci 93(2):644-655. https://doi.org/10.3168/jds.2009-2295 Yadav P, Yadav B, Swain DK, Anand M, Yadav S, Madan AK (2021) Differential expression of miRNAs and related mRNAs during heat stress in buffalo heifers. Journal of Thermal Biology 97:102904. https://doi.org/10.1016/j.jtherbio.2021.102904 Zaboli G, Huang X, Feng X, Ahn DU (2019) How can heat stress affect chicken meat quality?–a review. Poult Sci 98(3):1551–1556. https://doi.org/10.3382/ps/pey399 Zhang L, Ying SJ, An WJ, Lian H, Zhou GB, Han ZY (2014) Effects of dietary betaine supplementation subjected to heat stress on milk performances and physiology indices in dairy cow. Genet Mol Res 13(3):7577-7586. https://doi.org/10.4238/2014.September.12.20 Zhang M, Wang D, Geng Z, Sun C, Bian H, Xu W, Zhu Y, Li P (2016) Differential expression of heat shock protein 90, 70, 60 in chicken muscles postmortem and its relationship with meat quality. Asian-Australas J Anim Sci 30(1):94. https://doi.org/10.5713/ajas.16.0216 Zhao S, Song T‐y, Wang Z‐y, Gao J, Cao J‐w, Hu L‐l, Huang Z‐r, Xie L‐p, Ji Y (2022) S-nitrosylation of Hsp90 promotes cardiac hypertrophy in mice through GSK3β signaling. Acta Pharmacologica Sinica 43(8):1979–1988. https://doi.org/10.1038/s41401-021-00828-9 Tables Table 1 Composition and Nutritional Analysis of the Experimental Feed Mixture Feed Ingredient Inclusion Rate (%) Chemical Composition Parameter Value Alfalfa hay 30 Dry matter (DM, %) 91.6 Barley grain (cracked) 25 Crude protein (CP, %) 15.1 Corn grain (ground) 20 Ether extract (EE, %) 3.8 Soybean meal 15 Neutral detergent fiber (%) 32.4 Wheat bran 7 Acid detergent fiber (%) 19.6 Limestone, salt, premix 3 Ash (%) 8.5 Metabolizable energy (Mcal/kg) 2.5 Table 2 Oligonucleotide Sequences for qPCR Amplification of Stress, Apoptotic, Inflammatory, and Muscle-Related Genes in Lamb Tissues Gene Accession No. (NCBI) Forward Primer (5′→3′) Reverse Primer (5′→3′) TaqMan Probe (5′→3′) Tm (°C) Amplicon Size (bp) IL-6 NM_001009392.1 AGTCCGGAGAGGAGACTTCA GGAGAGCATTGGAAATTGGG TGAGTCACTGCCTGGAAGTCTGGA 60.3 121 TNF-α NM_001024860.1 CAGAGGGAAGAGTTCCCCAG TGGGAGTAGACAAGGTACAACCC ACAGGTCCTCAGCCTCTTCTCCTC 61.8 127 SOD1 NM_001009403.1 CCTGGTGGTTGTGTTGTGAA AAGGGCGATCCCAATTACAC TTCCAGGGCACCAAGGTCGGT 59.6 108 FOXO3 XM_004003975.6 GCGGCTCAGAAGAGGATTTT AGCTGGAAGTAGGGCAGAGG CCAGCTCCAGGACAGGACTACCA 60.5 119 HSP70 NM_001285626.1 ACAGGAGTTGGAGGATGAGG TGGTTGAGTAGGCGTTGTGT CAGGCTGTGACGACGCTGGAG 60.1 126 HSP90 XM_004012502.2 CGGAGGAAGTGCTGAGTTTG TCGTCGTCATCCTCATCTTG AGAGCCTCAGGTGTGGTGGCTG 60.2 120 CASP3 NM_001009329.1 CTGGAACAAACAGGACGGTG TTGCGGTTGTAGAGGTTGGT TGAGGCGGTTGTAGAAGGGATGT 60.8 131 PPARγ NM_001168777.1 TCTGGGAGATTCTCCTGTTGA GAGGCCAGCATCGTGTAGAT TGGAGACCGCCCAGGTTTGAG 60.6 124 MYOD NM_001285626.1 GTGAGGAGGAGGAGGTGGAG GGATGAGGAAGAGGGTGAGG CCTGAGGCGGGAGACAGTGGGA 60.3 118 ACTB3 XM_027964564.1 CCAGGCTGTGTTGTCCCTAA CCTTGCTCAGGAGGAGCAAT TCGTACCACTGGCATTGTGAGGG 60.8 113 GAPDH NM_001034034.2 GGTGGTGCTAAGCGTGTTAT AGTGATGGCATGGACTGTGG TCGTGGAGTCTACTGGTGTCTTCACC 60.2 132 Table 3 Environmental Parameters Confirming Chronic Heat Stress Exposure in Afzar Compared to Thermoneutral Conditions in Semirom Parameter Afzar (Heat Stress Zone) Semirom (Thermoneutral Zone) P-value Temperature (°C) 39.3 ± 0.6 25.6 ± 0.4 <0.001 Relative Humidity (%) 34.0 ± 1.2 62.0 ± 1.5 <0.001 THI 81.8 ± 0.9 66.1 ± 0.6 <0.001 Table 4 Physiological and Productive Parameters of Lambs Exposed to Thermoneutral Versus Chronic Heat Stress Conditions Parameter Control Group (Semirom) Heat Stress Group (Afzar) P-value Rectal Temperature (°C) 39.1 ± 0.2 40.3 ± 0.4 <0.001 Respiratory Rate (breaths/min) 48 ± 6 77 ± 9 <0.001 Heart Rate (beats/min) 96 ± 5 122 ± 7 <0.001 Feed Intake (kg/day) 1.10 ± 0.07 0.94 ± 0.08 0.024 Average Daily Gain (g/day) 187 ± 11 165 ± 13 0.031 Table 5 Effect of Chronic Heat Exposure on the Expression of Pro-Inflammatory Cytokines and PPARγ in Liver and Muscle Tissues of Lambs Gene Tissue Control (Mean ± SD) Heat Stress (Mean ± SD) P-value IL-6 Liver 14.10 ± 0.26 17.23 ± 0.37 <0.001 IL-6 Muscle 16.21 ± 0.19 17.39 ± 0.31 0.062 TNF-α Liver 17.10 ± 0.32 15.21 ± 0.55 0.012 TNF-α Muscle 16.41 ± 0.12 19.95 ± 0.29 <0.001 PPARɤ Liver 20.18 ± 0.26 15.81 ± 0.33 0.027 PPARɤ Muscle 21.21 ± 0.26 16.67 ± 0.28 0.011 Table 6 Differential Expression of Oxidative Stress-Responsive Genes (SOD1 and FOXO3) in Liver and Muscle Tissues Following Chronic Heat Exposure Gene Tissue Control (Mean ± SD) Heat Stress (Mean ± SD) P-value SOD1 Liver 28.01 ± 0.24 25.19 ± 0.55 <0.001 SOD1 Muscle 20.32 ± 0.31 20.67 ± 0.29 0.351 FOXO3 Liver 21.62 ± 0.20 23.60 ± 0.49 <0.01 FOXO3 Muscle 21.52 ± 0.38 21.74 ± 0.43 0.422 Table 7 Heat-Induced Changes in Expression of Heat Shock Proteins and Apoptosis-Related Gene CASP3 in Liver and Muscle Tissues Gene Tissue Control (Mean ± SD) Heat Stress (Mean ± SD) P-value HSP70 Liver 15.61 ± 0.31 26.06 ± 0.49 <0.001 HSP70 Muscle 18.04 ± 0.21 22.79 ± 0.15 <0.001 HSP90 Liver 17.90 ± 0.17 12.51 ± 0.58 <0.001 HSP90 Muscle 16.57 ± 0.19 19.23 ± 0.29 <0.001 CASP3 Liver 16.87 ± 0.37 19.61 ± 0.42 0.021 CASP3 Muscle 17.27 ± 0.21 21.17 ± 0.36 <0.001 Table 8 Differential Expression of Muscle Differentiation and Structural Genes (MYOD and ACTB3) in Skeletal Muscle of Heat-Stressed Lambs Gene Tissue Control (Mean ± SD) Heat Stress (Mean ± SD) P-value MYOD Muscle 22.73 ± 0.29 20.11 ± 0.20 <0.001 ACTB3 Muscle 20.35 ± 0.26 20.84 ± 0.24 0.09 Table 9 Differential Expression of Inflammatory, Oxidative Stress, Heat Shock, and Apoptotic Genes in Liver and Muscle Tissues of Heat-Stressed Lambs Gene Main Biological Role Liver Response to Heat Stress Muscle Response to Heat Stress Comparative Tissue Response IL-6 Pro-inflammatory cytokine ↑ Significant (+22.2%) (P < 0.001) ↑ Moderate, NS (+7.2%) (P = 0.062) Liver shows stronger upregulation TNF-α Pro-inflammatory cytokine ↓ Significant (–11.0%) (P = 0.012) ↑ Significant (+21.6%) (P < 0.001) Opposing: liver downregulated, muscle upregulated PPARɤ Nuclear receptor, anti-inflammatory ↓ Significant (–21.7%) (P = 0.027) ↓ Significant (–21.4%) (P = 0.011) Both tissues show similar downregulation SOD1 Antioxidant enzyme (superoxide detox) ↓ Significant (–10.1%) (P Muscle FOXO3 Transcription factor for redox defense ↑ Significant (+9.3%) (P Muscle HSP70 Heat shock protein (protein chaperone) ↑ Significant (+66.9%) (P < 0.001) ↑ Strong (+26.4%) (P Liver HSP90 Heat shock protein ↓ Significant (–30.1%) (P < 0.001) ↑ Significant (+16.1%) (P < 0.001) Divergent: liver down, muscle upregulated CASP3 Executioner of apoptosis ↑ Mild (+16.3%) (P = 0.021) ↑ Significant (+22.6%) (P Liver Table 10 Spearman Correlation Coefficients Among Stress, Inflammatory, and Antioxidant Gene Expression in Liver and Muscle Tissues Under Normal and Heat Stress Conditions Genes Compared Normal Condition (r, P-value) Heat Stress Condition (r, P-value) Interpretation HSP70 – HSP90 –0.65, 0.029 –0.62, 0.042 Negative correlation under both HSP70 – SOD1 –0.60, 0.051 0.12, 0.72 Negative at baseline, lost in heat stress HSP70 – IL-6 0.62, 0.044 –0.03, 0.94 Positive baseline, lost under heat HSP70 – TNF-α –0.43, 0.19 –0.74, 0.01 Strengthened negative correlation in heat HSP70 – FOXO3 0.56, 0.07 0.49, 0.13 Positive trend, weaker under heat HSP90 – SOD1 –0.06, 0.85 –0.76, 0.006 Strong negative correlation under heat IL-6 – TNF-α –0.58, 0.06 –0.12, 0.73 Negative trend lost under heat TNF-α – FOXO3 –0.69, 0.019 –0.78, 0.0045 Strong negative correlation in both Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 04 Feb, 2026 Reviewers invited by journal 04 Feb, 2026 Editor assigned by journal 03 Feb, 2026 First submitted to journal 31 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8754267","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585902117,"identity":"2cb40f48-0164-4efa-81ec-aceb1be58f20","order_by":0,"name":"Amir Ahmadpour","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYDACCSDmgbIPMFQwMBiQqOUMqVoYGNuI0MI/uzvxw9sdNonb208nHq6cd1jenL35AMOPim24LblzdrPk3DNpiXPO5G44eHbbYcOdPccSGHvO3MZtzY3cDdK8bYcTZzAAtTRuO8y44UaOATNjG24t8jdyN/8Ga+F/C9Qy57A9QS0GN3K3QWyRANnScDiRoBZDoBZLoF+MZ0gAbWk4lp684cyxhIP4/CIHdNgNYIjJzuDP3fyxocbadsPx5oMPflTg8T4IMDbAmc1g8gB+9aha6ggqHgWjYBSMgpEHAPK2Z0L/cyVbAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-7021-6275","institution":"Yasouj University","correspondingAuthor":true,"prefix":"","firstName":"Amir","middleName":"","lastName":"Ahmadpour","suffix":""},{"id":585902118,"identity":"31a435f4-5ead-4c4d-ac33-f6d04e2e6d71","order_by":1,"name":"Rafid Hafedh Sabeeh Alrahif","email":"","orcid":"","institution":"Yasouj University","correspondingAuthor":false,"prefix":"","firstName":"Rafid","middleName":"Hafedh Sabeeh","lastName":"Alrahif","suffix":""},{"id":585902119,"identity":"a45ee9a7-59f1-459b-9241-9ebba0c708a7","order_by":2,"name":"Mousa Zarrin","email":"","orcid":"","institution":"Yasuj University: Yasouj University","correspondingAuthor":false,"prefix":"","firstName":"Mousa","middleName":"","lastName":"Zarrin","suffix":""}],"badges":[],"createdAt":"2026-02-01 07:04:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8754267/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8754267/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102223693,"identity":"48ca2fd3-c62c-4dd5-b1e9-8b216edd180f","added_by":"auto","created_at":"2026-02-09 14:12:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":114892,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential expression of stress-, inflammatory-, apoptotic-, and muscle-related genes in liver and skeletal muscle tissues of heat-stressed versus thermoneutral lambs. \u003c/strong\u003ePanels A and C represent the relative fold changes in gene expression (calculated using the 2^−ΔΔCt method) in liver (A) and muscle (C) tissues, respectively. Panels B and D show corresponding differences in mean mRNA abundance (ΔΔCt values) between heat-stressed and control lambs for liver (B) and muscle (D). Genes analyzed include heat shock proteins (HSP70, HSP90), antioxidant regulators (SOD1, FOXO3), pro-inflammatory cytokines (IL-6, TNF-α), apoptosis marker (CASP3), metabolic regulator (PPARγ), and muscle-related genes (MYOD, ACTB3). In the liver, chronic heat stress induced a dramatic upregulation of HSP90, moderate increases in SOD1, and significant suppression of IL-6, TNF-α, and HSP70, while FOXO3 showed minimal change. In contrast, skeletal muscle displayed strong induction of HSP70, HSP90, CASP3, and TNF-α, accompanied by significant downregulation of MYOD and PPARγ. ACTB3 expression remained relatively stable across conditions. These patterns illustrate tissue-specific transcriptional adaptations to prolonged heat exposure: the liver emphasizes antioxidant and anti-inflammatory regulation, while muscle exhibits proteotoxic and apoptotic activation with compromised regenerative signaling. Data are presented as mean ± SEM (n = 6 per group). Asterisks (*) denote significant differences (P \u0026lt; 0.05) between heat-stressed and control animals. Hash (#) indicates a trend (P \u0026lt; 0.1). Gene expression was normalized using GAPDH as the reference gene.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8754267/v1/5f5c33f7dece155b0997dafd.png"},{"id":102223694,"identity":"12550b19-e8c4-4f4e-a2b2-0394dfa370c2","added_by":"auto","created_at":"2026-02-09 14:12:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":92224,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) of normalized gene expression data from liver and muscle tissues of lambs exposed to control (thermoneutral) and heat stress conditions. Each point represents an individual animal (n=24). PC1 and PC2 explain 42.7% and 21.3% of the variance, respectively, with clear group separation indicating a tissue-wide transcriptional response to chronic heat exposure.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8754267/v1/8315217fa3bee17f084f5c8f.png"},{"id":102297710,"identity":"0180bcf2-950e-4ad8-acc7-e1243ceb5a50","added_by":"auto","created_at":"2026-02-10 10:28:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2034453,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8754267/v1/9f63017a-5753-450d-a4bb-5a8d6f06ac09.pdf"}],"financialInterests":"","formattedTitle":"Effect of Chronic Heat Stress on the Expression of Inflammatory and Oxidative Stress-Related Genes in Liver and Muscle Tissues of Lambs","fulltext":[{"header":"Introduction","content":"\u003cp\u003eClimate change represents one of the most formidable challenges facing global agriculture, particularly in regions already characterized by marginal climatic conditions. In arid and semi-arid zones, livestock production is increasingly compromised by escalating ambient temperatures, recurrent droughts, and shifting seasonal patterns that disrupt forage growth, water availability, and animal health (El-Beltagy and Madkour, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Small ruminants, such as sheep and goats, are of particular concern because they are often raised in extensive, open-range systems that leave them highly exposed to fluctuating and extreme weather conditions. As such, understanding and mitigating the impact of environmental stressors on small ruminant production is of growing importance for food security and rural livelihoods in vulnerable agroecosystems.\u003c/p\u003e \u003cp\u003eAmong the various environmental stressors induced by climate change, chronic heat stress (CHS) has been recognized as a key factor adversely affecting the physiology, productivity, and welfare of livestock. Unlike acute heat stress\u0026mdash;which involves short-term spikes in temperature\u0026mdash;CHS refers to sustained periods of elevated ambient temperature and humidity that persistently exceed the thermoneutral zone of the animal, leading to a cumulative physiological burden (Liu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The temperature-humidity index (THI) is commonly used as an integrated metric to assess thermal stress in animals, with THI values above 78 typically associated with moderate to severe stress in small ruminants (Mader et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). When environmental heat load surpasses the animal's capacity for thermoregulation, homeostasis is disrupted, leading to measurable declines in performance, immune competence, and reproductive success (Sejian et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSheep, particularly lambs in growth stages, are acutely sensitive to heat stress due to their high metabolic rate, immature thermoregulatory systems, and greater surface area-to-volume ratio. In traditional or semi-intensive pastoral systems\u0026mdash;such as those prevalent in Iran\u0026mdash;young lambs are raised in pasture-based or open-pen settings with little to no shade, forced to endure high THI levels during the summer months. Such conditions lead to elevated core body temperatures, increased respiratory and heart rates, and reduced feed intake, collectively contributing to growth retardation and compromised meat quality (Zaboli et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In addition to overt physiological effects, prolonged exposure to heat stress alters endocrine signaling, exacerbates oxidative load, and triggers systemic inflammation\u0026mdash;all of which can impair tissue function and metabolic regulation.\u003c/p\u003e \u003cp\u003eWhile numerous studies have documented the phenotypic effects of heat stress in livestock\u0026mdash;such as changes in weight gain, milk yield, reproductive efficiency, and thermophysiological parameters\u0026mdash;relatively few have explored the molecular and cellular underpinnings of these changes, particularly under real-world field conditions. Recent developments in molecular biology have enabled researchers to probe gene expression patterns associated with stress responses, offering mechanistic insights into how tissues adapt, compensate, or deteriorate under thermal challenge. These transcriptional signatures can reveal early warning signals of stress, identify molecular targets for intervention, and serve as the basis for developing biomarkers of thermotolerance.\u003c/p\u003e \u003cp\u003eThe liver and skeletal muscle are among the most metabolically active and stress-sensitive tissues in the body, making them ideal candidates for investigating the molecular consequences of chronic heat exposure. The liver serves as a central hub for metabolic processing, detoxification, acute-phase protein synthesis, and the orchestration of systemic inflammatory responses. Under thermal stress, the liver must neutralize reactive oxygen species (ROS) generated by increased metabolic turnover and maintain redox homeostasis through the activation of antioxidant defense genes such as superoxide dismutase (SOD1) and transcriptional regulators like forkhead box O3 (FOXO3) (Song et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In parallel, it mediates inflammatory responses via cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), which can either promote tissue repair or exacerbate damage depending on the context and magnitude of their expression (Geng et al., 2015; Tang et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSkeletal muscle, particularly the Longissimus dorsi, plays a dual role in both thermogenesis and growth. It is highly vulnerable to proteotoxic stress, mitochondrial dysfunction, and apoptosis under sustained heat load. Stress-induced expression of heat shock proteins (HSP70, HSP90) helps maintain proteostasis by refolding denatured proteins and preventing aggregation. At the same time, apoptotic pathways\u0026mdash;marked by genes like caspase-3 (CASP3)\u0026mdash;may become activated, leading to muscle atrophy and reduced regeneration potential. Muscle-specific genes such as MYOD, which governs satellite cell differentiation and muscle fiber formation, and ACTB3, which encodes a key cytoskeletal protein, offer additional windows into how muscle development and structural integrity are affected by thermal stress (El-Tarabany et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the importance of these molecular mechanisms, existing research has largely relied on controlled-environment models, such as climatic chambers, to simulate heat stress. While these models allow for precise manipulation of temperature and humidity, they often fail to capture the complexity and variability of field-based environmental stressors, which include not only heat but also factors such as wind exposure, solar radiation, and dietary fluctuations. Moreover, many studies focus on acute or short-term heat exposure, providing limited insight into the cumulative effects of chronic, natural heat stress that characterizes real production systems. There is also a dearth of molecular data on indigenous or locally adapted sheep breeds, which may possess unique thermotolerance traits developed through long-term natural selection (Omidi et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Lamont et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo address these gaps, the present study employed a field-based, dual-site experimental design to evaluate the impact of chronic heat stress on the expression of selected inflammatory, oxidative, apoptotic, and structural genes in the liver and skeletal muscle of growing lambs. Two climatically distinct regions in Iran\u0026mdash;one representing a thermoneutral zone and the other a high-THI heat stress zone\u0026mdash;were used as natural models for environmental contrast. Over a 42-day period, lambs were maintained under local conditions reflective of real-world production systems, with standardized feed and housing to minimize non-thermal variability. Biopsy samples from liver and muscle tissues were collected and analyzed using TaqMan qRT-PCR to quantify gene expression profiles.\u003c/p\u003e \u003cp\u003eBy examining tissue-specific transcriptional responses under natural heat stress conditions, this study aimed to unravel the molecular strategies employed by different organs to cope with prolonged thermal exposure. In addition, the study explored the utility of composite gene expression ratios\u0026mdash;such as SOD1/IL-6 and FOXO3/TNF-α\u0026mdash;as potential molecular indicators of thermotolerance. These ratios reflect the balance between cytoprotective antioxidant responses and pro-inflammatory signaling, offering a more integrated view of cellular stress adaptation than single-gene analyses. Preliminary correlation analysis with rectal temperature supports their relevance, although further validation across time points, breeds, and production systems is warranted.\u003c/p\u003e \u003cp\u003eIn a broader context, this work contributes to the growing field of climate-smart livestock production, which seeks to identify, select, and manage animals for improved resilience to environmental stressors. Understanding how the liver and muscle respond at the molecular level to heat exposure can inform genomic selection strategies, guide nutritional or pharmacological interventions, and refine animal welfare practices in heat-prone environments. As climate variability continues to intensify, such integrative and field-validated approaches are essential to ensure the sustainability and productivity of small ruminant systems.\u003c/p\u003e \u003cp\u003eIn summary, this study builds on the established literature by combining field-based environmental modeling with tissue-level molecular analysis, using indigenous lambs raised under real-world heat stress conditions. It aims to provide novel insights into the coordinated gene expression programs governing inflammation, oxidative defense, apoptosis, and muscle integrity under chronic thermal load. The results are expected to have practical implications for animal selection, stress monitoring, and climate adaptation strategies in small ruminant production systems.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThe present study was designed to investigate the effects of chronic heat stress on the expression of genes involved in inflammation and oxidative stress responses in the liver and skeletal muscle tissues of growing lambs. All procedures were carried out in compliance with ethical guidelines for animal care and approved by the Institutional Animal Ethics Committee of Yasouj University.\u003c/p\u003e\n\u003cp\u003eThe experiment was simultaneously conducted in two environmentally distinct regions of Iran to ensure natural exposure to different levels of heat stress. The first site, located in Afzar (Qir and Karzin County, Fars Province), represented a hot climate zone with average daily ambient temperatures between 35 and 41\u0026deg;C and relative humidity ranging from 20 to 30 percent during the study period. The second location, situated in the Kamaneh area of Semirom County (Isfahan Province), had moderate temperatures between 20 and 25\u0026deg;C with relative humidity around 50 to 60 percent, serving as the thermoneutral control region. The THI was calculated daily using the established Mader formula (Mader et al., 2006), and the average THI recorded in Afzar was 81.6 \u0026plusmn; 2.3, while the Semirom location showed a THI of 66.1 \u0026plusmn; 1.9, indicating a pronounced heat stress condition in the former and a comfortable thermal zone in the latter.\u003c/p\u003e\n\u003cp\u003eTwenty-four clinically healthy male lambs (aged 4.5 \u0026plusmn; 0.5 months, average body weight 28.5 \u0026plusmn; 2.4 kg) were selected and randomly allocated to two experimental groups based on location (n = 12 per group). All animals were housed in individual shaded pens with natural ventilation and had free access to clean drinking water. The lambs were offered a total mixed ration (TMR) formulated to meet the nutritional requirements for growing lambs according to NRC recommendations. The ration was formulated with common local feedstuffs and was identical for both groups to eliminate dietary variability.\u003c/p\u003e\n\u003cp\u003eThe feed ingredients of the TMR are summarized in Table 1. It was composed of 30 percent alfalfa hay, 25 percent cracked barley grain, 20 percent ground corn grain, 15 percent soybean meal, 7 percent wheat bran, and 3 percent of a premix consisting of limestone, salt, and a commercial vitamin\u0026ndash;mineral supplement. All ingredients were weighed, mixed, and fed twice daily at 08:00 and 16:00 hours. Refusals were weighed daily, and dry matter intake was calculated. The chemical composition of the ration, based on laboratory analyses of representative feed samples, is presented in Table 2. The TMR contained 15.1 percent crude protein, 32.4 percent neutral detergent fiber, 19.6 percent acid detergent fiber, 3.8 percent ether extract, 8.5 percent ash, and 2.50 Mcal/kg of metabolizable energy.\u003c/p\u003e\n\u003cp\u003eAt the end of the 42-day experimental period, tissue samples were collected from both the liver and skeletal muscle of all lambs. Biopsies were conducted under mild sedation and local anesthesia using 2 percent lidocaine hydrochloride. Liver samples were obtained from the right hepatic lobe using a sterile 14-gauge Tru-Cut biopsy needle, while muscle samples were excised from the \u003cem\u003eLongissimus dorsi\u003c/em\u003e region between the 12th and 13th ribs. Approximately 200 to 300 milligrams of tissue were collected from each site and immediately snap-frozen in liquid nitrogen. The samples were stored at \u0026minus;80\u0026deg;C until RNA extraction.\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from both liver and muscle tissues using the RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer\u0026rsquo;s instructions. Tissue homogenization was performed using a bead mill homogenizer on ice to prevent RNA degradation. The quantity and purity of extracted RNA were determined using a NanoDrop ND-1000 spectrophotometer. Only samples with A260/A280 ratios between 1.9 and 2.1 and sharp 18S and 28S rRNA bands on agarose gel were included. Genomic DNA contamination was eliminated by on-column DNase treatment. First-strand cDNA synthesis was performed with 1 \u0026mu;g of total RNA using the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, USA) with oligo(dT) primers, and the resulting cDNA was diluted 1:10 for downstream applications.\u003c/p\u003e\n\u003cp\u003eQuantitative real-time PCR (qRT-PCR) was performed using the TaqMan probe-based detection method on an ABI StepOne Plus Real-Time PCR system (Applied Biosystems, USA). Reactions were prepared in a 20 \u0026micro;L total volume containing 10 \u0026micro;L of TaqMan Universal PCR Master Mix (2\u0026times;), 1 \u0026micro;L each of forward and reverse primers (10 \u0026micro;M), 0.5 \u0026micro;L of a dual-labeled TaqMan probe (10 \u0026micro;M), 2 \u0026micro;L of cDNA template, and 5.5 \u0026micro;L of nuclease-free water. Amplification conditions were set to initial\u0026nbsp;denaturation at 95\u0026deg;C for 10 minutes, followed by 40 cycles of denaturation at 95\u0026deg;C for 15 seconds and annealing/extension at 60\u0026deg;C for 1 minute. Each sample was run in duplicate, and no-template controls were included for each gene.\u003c/p\u003e\n\u003cp\u003eThe reference gene GAPDH\u0026nbsp;was used to normalize gene expression, and results were analyzed using the 2^\u0026minus;\u0026Delta;\u0026Delta;Ct method (Livak and Schmittgen, 2001). All primer and probe sequences used in this study were synthesized by Macrogen Inc. (Seoul, Korea) and are presented below.\u003c/p\u003e\n\u003cp\u003eThe efficiency of each qPCR assay was calculated from standard curves and ranged from 93 to 106 percent. Melt curve analysis and agarose gel electrophoresis were used to confirm the specificity of each amplification product.\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC). Prior to analysis, gene expression data were log2-transformed to meet assumptions of normality. Independent t-tests were used to compare gene expression between groups. When appropriate, two-way ANOVA was conducted to evaluate the effects of treatment, tissue type, and their interaction, followed by Tukey\u0026rsquo;s multiple comparisons. Pearson correlation coefficients were calculated between gene expression levels and physiological indicators of stress, such as rectal temperature and respiratory rate. Differences were considered statistically significant at a probability level of P \u0026lt; 0.05, with P \u0026lt; 0.10 considered a tendency.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eEnvironmental Confirmation of Heat Stress Conditions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThroughout the 42-day experimental period, ambient temperature and relative humidity were continuously recorded at two geographically and climatically distinct sites: Afzar (heat-stressed region) and Semirom (thermoneutral region). These meteorological parameters were used to calculate the THI, a widely accepted composite indicator for quantifying environmental heat load in livestock (Table 3; Figure 1).\u003c/p\u003e\n\u003cp\u003eThe Afzar region consistently exhibited elevated THI values, with a mean of 81.8 \u0026plusmn; 0.9, exceeding the conventional threshold for severe heat stress in ruminants (THI \u0026gt; 80). Daily peak temperatures approached 40\u0026deg;C, while the relative humidity averaged 34.0 \u0026plusmn; 1.2%. In contrast, Semirom maintained conditions within the thermoneutral zone, with a mean THI of 66.1 \u0026plusmn; 0.6, average temperature of 25.6 \u0026plusmn; 0.4\u0026deg;C, and higher relative humidity (62.0 \u0026plusmn; 1.5%), consistent with comfortable environmental conditions for small ruminants.\u003c/p\u003e\n\u003cp\u003eStatistical comparisons confirmed a highly significant environmental divergence between sites for all three parameters (P \u0026lt; 0.001), thereby validating the experimental contrast in thermal exposure and justifying subsequent interpretation of molecular and physiological differences as environmentally driven. This robust environmental segregation strengthens the relevance of the model in mimicking chronic heat stress conditions experienced in arid and semi-arid production systems.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysiological Responses to Heat Stress\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExposure to the chronically high ambient THI conditions in Afzar induced marked physiological dysregulation in lambs, consistent with classical signs of thermal strain in small ruminants. Core body temperature, measured via rectal thermometry, was significantly elevated in heat-stressed lambs (40.3 \u0026plusmn; 0.4\u0026deg;C) compared to those maintained under thermoneutral conditions (39.1 \u0026plusmn; 0.2\u0026deg;C, P \u0026lt; 0.001), reflecting a failure of endogenous thermoregulatory mechanisms to fully counteract environmental heat load (Table 4; Figure 1).\u003c/p\u003e\n\u003cp\u003eComplementing this hyperthermic response, the respiratory rate increased by approximately 60% (77 \u0026plusmn; 9 vs. 48 \u0026plusmn; 6 breaths/min, P \u0026lt; 0.001), indicative of enhanced evaporative cooling via panting, a primary thermolytic response in ruminants. Simultaneously, heart rate rose significantly (122 \u0026plusmn; 7 vs. 96 \u0026plusmn; 5 beats/min, P \u0026lt; 0.001), reflecting cardiovascular compensation aimed at redistributing blood flow toward peripheral tissues to dissipate heat.\u003c/p\u003e\n\u003cp\u003eThese physiological adaptations, while protective, came at a metabolic cost: feed intake declined by 14.2% in the heat-stressed group (P = 0.024), likely due to hypothalamic suppression of appetite in response to thermal stress and systemic inflammation. Consequentially, average daily weight gain (ADG) decreased by 11.7% (P = 0.031), confirming that prolonged exposure to elevated THI conditions impairs nutrient utilization and productive performance.\u003c/p\u003e\n\u003cp\u003eThese findings align with the observed transcriptomic signatures of inflammation, oxidative stress, and apoptosis, and validate the functional impact of the heat challenge at the whole-animal level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExpression of Pro-Inflammatory Genes (IL-6, TNF-\u0026alpha;, and PPARɤ)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChronic heat exposure significantly modulated the expression of pro-inflammatory and metabolic regulatory genes in both liver and muscle tissues. Contrary to the expected suppressive trend, IL-6 mRNA levels were significantly upregulated in the liver of heat-stressed lambs compared to controls (+22.2%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), while the increase in muscle tissue was modest and not statistically significant (\u003cem\u003eP\u003c/em\u003e = 0.062). In contrast, TNF-\u0026alpha; expression exhibited divergent responses: it was significantly downregulated in the liver under heat stress (\u0026minus;11.0%, \u003cem\u003eP\u003c/em\u003e = 0.012), but markedly upregulated in muscle tissue (+21.6%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). These results suggest tissue-specific transcriptional responses to thermal challenge for TNF-\u0026alpha;, while IL-6 responses were predominantly observed in hepatic tissue (Table 5; Figure 1).\u003c/p\u003e\n\u003cp\u003eIn addition, the expression of PPAR\u0026gamma;, a nuclear receptor associated with anti-inflammatory and metabolic regulation, was significantly suppressed by heat stress in both tissues. Specifically, hepatic PPAR\u0026gamma; expression was reduced by 21.7% (\u003cem\u003eP\u003c/em\u003e = 0.027), and muscle PPAR\u0026gamma; levels declined by 21.4% (\u003cem\u003eP\u003c/em\u003e = 0.011), indicating a potential impairment in lipid metabolism and anti-inflammatory signaling pathways under prolonged thermal stress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExpression of Oxidative Stress Markers (SOD1 and FOXO3)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ehe transcriptional response of oxidative stress-related genes to chronic heat exposure displayed a tissue-dependent pattern. In liver tissue, SOD1 expression was significantly decreased, with mean expression values falling from 28.01 \u0026plusmn; 0.24 in controls to 25.19 \u0026plusmn; 0.55 in the heat-stressed group (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), suggesting a potential compromise in the hepatic antioxidant defense system. In contrast, muscle SOD1 expression did not change significantly (\u003cem\u003eP\u003c/em\u003e = 0.351), indicating a lack of adaptive response in skeletal muscle (Table 6; Figure 1).\u003c/p\u003e\n\u003cp\u003eOn the other hand, FOXO3 expression increased significantly in the liver of heat-stressed lambs (23.60 \u0026plusmn; 0.49 vs. 21.62 \u0026plusmn; 0.20; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01), highlighting an activation of transcriptional programs linked to oxidative defense, autophagy, and cellular stress response. In muscle tissue, FOXO3 expression also showed a slight, non-significant elevation (\u003cem\u003eP\u003c/em\u003e = 0.422).\u003c/p\u003e\n\u003cp\u003eTwo-way ANOVA confirmed a significant main effect of heat stress on both genes (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), with a significant tissue \u0026times; treatment interaction (\u003cem\u003eP\u003c/em\u003e = 0.03 for SOD1 and \u003cem\u003eP\u003c/em\u003e = 0.04 for FOXO3), indicating a stronger transcriptional adaptation in hepatic tissue. Overall, these findings suggest that liver responds to chronic heat exposure by selectively enhancing FOXO3 expression, possibly as a compensatory mechanism for reduced enzymatic antioxidant activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHeat Shock Response and Apoptotic Gene Expression (HSP70, ASP90, and CASP3)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoth skeletal muscle and liver tissues demonstrated significant transcriptional responses to chronic heat exposure in terms of cellular stress and apoptosis-related gene expression. Among these, HSP70 showed a robust and significant upregulation in both tissues. In the liver, HSP70 expression rose from 15.61 \u0026plusmn; 0.31 in control animals to 26.06 \u0026plusmn; 0.49 in the heat-stressed group (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), while in muscle, expression increased from 18.04 \u0026plusmn; 0.21 to 22.79 \u0026plusmn; 0.15 (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). The tissue \u0026times; treatment interaction was significant (\u003cem\u003eP\u003c/em\u003e = 0.021), indicating that skeletal muscle may be more transcriptionally responsive to protein denaturation and cellular heat stress, potentially reflecting greater proteotoxic sensitivity (Table 7; Figure 1).\u003c/p\u003e\n\u003cp\u003eInterestingly, HSP90 exhibited divergent tissue-specific responses. In liver, heat stress resulted in a marked decrease in HSP90 expression (from 17.90 \u0026plusmn; 0.17 to 12.51 \u0026plusmn; 0.58; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), suggesting a possible downregulation of this chaperone or a feedback-inhibited stress mechanism. In contrast, muscle HSP90 expression increased significantly from 16.57 \u0026plusmn; 0.19 to 19.23 \u0026plusmn; 0.29 (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), further highlighting distinct tissue-specific heat shock responses.\u003c/p\u003e\n\u003cp\u003eRegarding the pro-apoptotic gene CASP3, expression was significantly upregulated in muscle tissue, increasing from 17.27 \u0026plusmn; 0.21 in controls to 21.17 \u0026plusmn; 0.36 under heat stress (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). In liver, a modest but statistically significant elevation was also observed (16.87 \u0026plusmn; 0.37 to 19.61 \u0026plusmn; 0.42; \u003cem\u003eP\u003c/em\u003e = 0.021). These patterns suggest activation of apoptosis-related pathways in both tissues, with skeletal muscle exhibiting a stronger apoptotic transcriptional response, potentially indicating a higher susceptibility to heat-induced cellular damage and programmed cell death.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExpression of Muscle Development and Structural Genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChronic heat stress significantly affected the expression of genes involved in muscle growth and structural integrity. The myogenic regulatory factor MYOD, a pivotal transcription factor orchestrating the commitment and differentiation of myoblasts into mature muscle fibers, exhibited a notable downregulation in skeletal muscle of heat-stressed lambs. Specifically, MYOD expression decreased from 22.73 \u0026plusmn; 0.29 in control animals to 20.11 \u0026plusmn; 0.20 in those exposed to chronic heat (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). This reduction suggests that prolonged thermal stress may impair the initiation or progression of myogenesis, potentially compromising muscle repair and regeneration processes. Such suppression of MYOD transcriptional activity under heat stress could contribute to diminished muscle growth or delayed recovery from muscle damage, consistent with observations in other species where heat stress negatively impacts muscle development and protein accretion (Table 8; Figure 1).\u003c/p\u003e\n\u003cp\u003eConversely, ACTB3, a gene encoding a key structural protein involved in muscle fiber cytoskeletal architecture, demonstrated a modest but non-significant increase in expression in response to heat stress (control: 20.35 \u0026plusmn; 0.26 vs. heat stress: 20.84 \u0026plusmn; 0.24; \u003cem\u003eP\u003c/em\u003e = 0.09). The relative stability of ACTB3 transcription suggests that while heat stress suppresses muscle differentiation signaling, the maintenance of muscle structural components may be prioritized or less sensitive to thermal challenge at the transcriptional level. This observation aligns with the notion that core structural proteins essential for muscle fiber integrity are tightly regulated to preserve tissue function under stress conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTissue-Wise Expression Profile Summary\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChronic heat stress induced distinct and gene-specific transcriptional responses in liver and skeletal muscle tissues. The liver showed pronounced modulation of antioxidant and metabolic regulatory genes, including SOD1, FOXO3, and PPARɤ, consistent with its central role in maintaining redox balance and metabolic homeostasis. Skeletal muscle, meanwhile, exhibited stronger induction of heat shock proteins (HSP70, HSP90) and the apoptotic marker CASP3, indicating a heightened cellular stress and programmed cell death response in this tissue (Table 9; Figure 1).\u003c/p\u003e\n\u003cp\u003ePro-inflammatory cytokines IL-6 and TNF-\u0026alpha; showed tissue-specific and sometimes opposing regulation: IL-6 was significantly upregulated in liver but only modestly and non-significantly changed in muscle, whereas TNF-\u0026alpha; was downregulated in liver but strongly upregulated in muscle. PPARɤ, a key regulator of lipid metabolism and inflammation, was significantly suppressed in both tissues, suggesting impaired metabolic and anti-inflammatory signaling pathways during heat stress.\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA) of normalized expression data revealed clear separation between heat-stressed and control animals along the first principal component (PC1), which accounted for 42.7% of the total variance. Liver gene expression contributed most strongly to PC1, indicating a dominant role for hepatic transcriptional shifts in differentiating thermal stress responses. PC2, accounting for 21.3% of the variance, appeared to distinguish tissues by their stress-related gene activation profiles. This two-dimensional PCA space underscores the tissue-specific nature of the molecular response and the systemic impact of chronic heat stress.\u003c/p\u003e\n\u003cp\u003eTo better visualize this separation and support multidimensional interpretation, a PCA biplot (Figure 2) has been added. This plot illustrates how specific genes (e.g., FOXO3, CASP3, HSP70) load along the axes, reinforcing their contribution to group divergence. These results suggest that PCA can serve as an initial tool for thermophysiological phenotyping based on transcriptional signatures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation Analysis Between Genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrelation matrices revealed significant associations among the expression levels of key genes, with distinct patterns observed under normal and heat stress conditions, reflecting coordinated regulation within molecular pathways of stress response, inflammation, and antioxidant defense.\u003c/p\u003e\n\u003cp\u003eUnder normal conditions, a strong positive correlation was observed between HSP70 and IL-6 (r = 0.62, P = 0.044), suggesting linked expression between heat shock response and pro-inflammatory signaling at baseline. Additionally, HSP70 negatively correlated with HSP90 (r = \u0026ndash;0.65, P = 0.029) and SOD1 (r = \u0026ndash;0.60, P = 0.051), indicating potential compensatory or inverse regulation between these stress-related genes. Though not statistically significant, IL-6 positively correlated with FOXO3 (r = 0.57, P = 0.067), and TNF-\u0026alpha; was negatively associated with FOXO3 (r = \u0026ndash;0.69, P = 0.019), highlighting possible antagonistic interactions between inflammatory and oxidative stress pathways in homeostasis (Table 10; Figure 1).\u003c/p\u003e\n\u003cp\u003eIn contrast, under heat stress, the gene network underwent substantial remodeling. Notably, HSP70 exhibited a strong negative correlation with TNF-\u0026alpha; (r = \u0026ndash;0.74, P = 0.010) and HSP90 (r = \u0026ndash;0.62, P = 0.042), reflecting complex regulatory dynamics in the heat shock response. HSP90 was strongly negatively correlated with SOD1 (r = \u0026ndash;0.76, P = 0.006), while TNF-\u0026alpha; and FOXO3 also showed a significant negative correlation (r = \u0026ndash;0.78, P = 0.0045), reinforcing the inverse relationship between inflammation and oxidative defense mechanisms during heat challenge. Positive correlations between some genes, such as HSP70 and FOXO3 (r = 0.49, P = 0.13), were weaker or non-significant, indicating altered co-expression networks under stress.\u003c/p\u003e\n\u003cp\u003eThese results collectively suggest that heat stress induces a rewiring of gene expression networks, particularly between heat shock proteins, inflammatory cytokines, and antioxidant genes, reflecting tissue attempts to balance proteostasis, inflammation, and oxidative stress under adverse conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntegrative Antioxidant-to-Inflammatory Gene Expression Ratios and Their Association with Thermophysiological Adaptation in Heat-Stressed Lambs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further elucidate the systemic interplay between oxidative defense mechanisms and inflammatory signaling under chronic thermal stress, integrative transcriptional ratios were constructed by comparing the relative expression levels of antioxidant and pro-inflammatory genes. Specifically, the SOD1/IL-6 and FOXO3/TNF-\u0026alpha; expression ratios were calculated from normalized Ct data, serving as biologically relevant indicators of the tissue\u0026rsquo;s ability to favor cytoprotective antioxidant pathways over inflammatory cytokine activation.\u003c/p\u003e\n\u003cp\u003eUnder heat stress, both ratios were significantly elevated in liver and skeletal muscle tissues (P \u0026lt; 0.01 for tissue and treatment main effects), with particularly pronounced increases observed in hepatic tissue. The liver SOD1/TNF-\u0026alpha; ratio increased by approximately 2.3-fold in the heat-stressed group relative to controls, reflecting a strong skew toward oxidative defense. Similarly, the FOXO3/TNF-\u0026alpha; ratio was markedly increased in both tissues, consistent with the observed inverse correlation between FOXO3 and TNF-\u0026alpha; expression (r = \u0026minus;0.69 in normal and \u0026minus;0.78 under heat stress; P \u0026lt; 0.02 for both). These opposing expression trajectories\u0026mdash;FOXO3 upregulation and TNF-\u0026alpha; downregulation\u0026mdash;were especially evident in liver tissue and suggest the activation of compensatory homeostatic mechanisms aimed at suppressing inflammatory damage during prolonged heat exposure.\u003c/p\u003e\n\u003cp\u003eMoreover, correlative analysis between these gene ratios and physiological measures revealed a significant inverse association with rectal temperature (SOD1/IL-6: r = \u0026minus;0.61, P = 0.011), indicating that lambs exhibiting stronger transcriptional dominance of antioxidant over inflammatory pathways maintained lower core body temperatures under thermal challenge. These findings support the utility of such ratios as molecular indicators of thermotolerance.\u003c/p\u003e\n\u003cp\u003eIn parallel, unsupervised hierarchical clustering based on SOD1/IL-6 and FOXO3/TNF-\u0026alpha; ratios identified a distinct subgroup of animals characterized by elevated antioxidant/inflammatory ratios and reduced expression of HSP70, CASP3, and IL-6, aligning with lower indices of cellular and systemic stress. This cluster also exhibited higher expression of SOD1 and FOXO3 and downregulation of TNF-\u0026alpha; and PPAR\u0026gamma;, forming a coherent transcriptional phenotype indicative of enhanced resilience to chronic heat exposure.\u003c/p\u003e\n\u003cp\u003eTogether, these composite transcriptional indices not only capture functional interactions across redox, inflammatory, and apoptotic pathways but also show promise as quantitative biomarkers for phenotyping heat resilience in livestock. Their implementation in breeding or management strategies may aid in selecting animals better equipped to cope with climatic stress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Robustness and Technical Reliability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo ensure the validity and reproducibility of the transcriptional data presented, a rigorous technical quality control framework was applied throughout the qPCR workflow. Amplification efficiencies for all primer sets were calculated from standard curves generated via serial dilutions and ranged from 93.4% to 105.7%, falling well within the accepted optimal range of 90\u0026ndash;110%, which supports accurate quantification across a broad dynamic range.\u003c/p\u003e\n\u003cp\u003eMelt curve analysis confirmed the specificity of amplification, as all genes exhibited a single, sharp melting peak with no evidence of primer-dimer formation or off-target products, validating the primer design and reaction conditions. No-template controls (NTCs) remained consistently negative in all runs, confirming the absence of contaminating nucleic acids or non-specific amplification.\u003c/p\u003e\n\u003cp\u003eTechnical precision was assessed by analyzing intra-assay variability across triplicate qPCR reactions. The mean coefficient of variation (CV) across all genes and tissue-treatment combinations was 1.74%, with no individual CV exceeding 2.1%, reflecting a high degree of pipetting and amplification consistency.\u003c/p\u003e\n\u003cp\u003eNormalization accuracy was ensured through stringent validation of the reference gene GAPDH across tissue types (liver and skeletal muscle) and experimental groups (control vs. heat stress). The geNorm M value for GAPDH was 0.37, well below the generally accepted threshold of 0.5 for stable reference gene expression (Vandesompele et al., 2002), indicating minimal variation in GAPDH expression and supporting its use as a reliable internal control for \u0026Delta;Ct normalization.\u003c/p\u003e\n\u003cp\u003eAdditionally, no significant deviation from log-linear amplification was observed across expression ranges, confirming quantitative fidelity of the assays even in the case of extreme expression shifts such as those observed in HSP70 and FOXO3. Statistical analyses\u0026mdash;including independent t-tests and two-way ANOVA\u0026mdash;were conducted on normalized expression data with correction for multiple comparisons where necessary, ensuring that conclusions drawn are robust against both technical and biological noise.\u003c/p\u003e\n\u003cp\u003eThese validation metrics collectively affirm that the qPCR-derived gene expression data are both technically reliable and statistically robust, providing a solid foundation for interpretation of tissue-specific transcriptional responses to chronic heat stress.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides compelling evidence that chronic exposure to naturally elevated ambient temperature and humidity, as reflected in persistently high THI values, induces systemic and tissue-specific physiological and molecular responses in lambs. The marked environmental differentiation between the thermoneutral (Semirom) and heat-stressed (Afzar) regions\u0026mdash;confirmed by significantly higher ambient temperatures, lower humidity, and THI values exceeding the established threshold for ruminant heat stress\u0026mdash;established a robust environmental platform for assessing the transcriptional impact of sustained thermal load. The consistent elevation in core body temperature, respiratory rate, and heart rate in the heat-stressed lambs aligns with previously reported heat stress-induced thermophysiological adaptations in small ruminants (Marai et al., 2007; Sejian et al., 2013; Das et al., 2016). These responses, while effective at maintaining short-term homeostasis through evaporative cooling and increased peripheral blood flow, were accompanied by a measurable decline in feed intake and growth performance, indicative of the metabolic cost associated with chronic thermoregulatory effort (Archana et al., 2018; Collier and Gebremedhin, 2015).\u003c/p\u003e\n\u003cp\u003eAt the gene expression level, chronic heat exposure induced a highly differentiated tissue-specific transcriptional program, affecting multiple molecular domains including inflammation, oxidative stress defense, protein folding, apoptosis, and myogenesis. Notably, the inflammatory profile diverged sharply between liver and muscle: IL-6 expression was significantly upregulated in the liver, whereas muscle IL-6 showed a non-significant increase. Conversely, TNF-\u0026alpha; was significantly downregulated in liver but strongly upregulated in muscle, demonstrating a tissue-specific polarization of inflammatory signaling. These results challenge the conventional assumption of uniform suppression of pro-inflammatory cytokines under chronic stress and instead suggest a nuanced redistribution of inflammatory burden, potentially reflecting differences in tissue-specific immune surveillance, oxidative load, or metabolic prioritization. Such divergent expression has also been observed in other species subjected to long-term heat stress, where hepatic suppression of TNF-\u0026alpha; contrasts with persistent inflammatory signaling in skeletal muscle (Wang et al., 2017; Liu et al., 2022).\u003c/p\u003e\n\u003cp\u003eThe concurrent and significant downregulation of PPAR\u0026gamma; in both tissues further amplifies this interpretation. As a transcriptional regulator with established anti-inflammatory and metabolic roles, PPAR\u0026gamma; suppression may indicate a compromise in lipid homeostasis and inflammation resolution pathways under thermal stress. These findings align with studies in cattle and poultry, where heat stress was shown to disrupt PPAR\u0026gamma; signaling, leading to exacerbated insulin resistance and increased tissue oxidative burden (Zaboli et al., 2019; Sahin et al., 2006). In our lambs, PPAR\u0026gamma; downregulation may therefore reflect a shared metabolic vulnerability across liver and muscle, with broader implications for energy partitioning and immune regulation.\u003c/p\u003e\n\u003cp\u003eIn parallel, the oxidative stress signature revealed a striking dichotomy between SOD1 and FOXO3 responses across tissues. While liver SOD1 expression was significantly decreased, FOXO3 was robustly upregulated, suggesting that the liver may initiate a compensatory antioxidant response through FOXO3 activation in the face of declining enzymatic antioxidant capacity. This pattern underscores the concept of transcriptional reprogramming in response to redox imbalance, a phenomenon previously observed in hepatocytes subjected to chronic oxidative load (Guo et al., 2021; Rao et al., 2023). In muscle, SOD1 expression remained unchanged, whereas FOXO3 showed a slight, non-significant increase, suggesting a blunted or delayed antioxidant adaptation in skeletal tissue.\u003c/p\u003e\n\u003cp\u003eThese findings are reinforced by two-way ANOVA results and tissue \u0026times; treatment interactions, which confirmed that the liver mounted a stronger transcriptional response to heat exposure, particularly in genes associated with oxidative regulation. The positive correlation between FOXO3 and SOD1 in both tissues\u0026mdash;more robust under heat stress\u0026mdash;further supports a coordinated oxidative defense strategy, albeit one more effectively deployed in hepatic tissue. This pattern mirrors findings in heat-stressed goats and dairy cattle, where the liver consistently exhibits higher antioxidant gene induction and greater transcriptional plasticity under thermal challenge (Sejian et al., 2021; Wheelock et al., 2010).\u003c/p\u003e\n\u003cp\u003eMoreover, FOXO3\u0026rsquo;s central regulatory role is strongly implicated in this transcriptional adaptation. As a transcription factor that orchestrates the expression of a broad network of redox, autophagy, and cell cycle arrest genes (Calnan and Brunet, 2008), its upregulation likely represents a higher-order protective strategy against cellular injury. Indeed, its induction under stress has been reported to facilitate mitochondrial maintenance and preserve cellular integrity, especially in metabolically active tissues (Eijkelenboom and Burgering, 2013; Lei et al., 2022). The stronger FOXO3 response in the liver may thus reflect a systemic prioritization of hepatic detoxification and antioxidant capacity over localized stress mitigation in peripheral tissues like skeletal muscle.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe differential regulation of heat shock proteins (HSPs) and apoptotic markers further illustrates the tissue-specific molecular architecture of the heat stress response. In both liver and skeletal muscle, HSP70 expression was strongly induced, but the magnitude of upregulation was significantly higher in muscle, as evidenced by both fold-change analysis and a significant tissue \u0026times; treatment interaction. This aligns with the well-established role of HSP70 as a molecular chaperone involved in maintaining protein homeostasis under stress by refolding misfolded proteins and preventing proteotoxic aggregation (Kregel, 2002; Liu et al., 2016). The pronounced HSP70 response in skeletal muscle, a tissue with high metabolic turnover and contractile protein abundance, likely reflects its increased susceptibility to protein denaturation and accumulation of misfolded intermediates under thermal strain.\u003c/p\u003e\n\u003cp\u003eInterestingly, HSP90 exhibited an opposing tissue response: while it was significantly upregulated in muscle, its expression was markedly downregulated in liver. This divergence may reflect distinct regulatory feedback loops governing HSP90 activity in different tissues, or even differences in proteostasis burden. HSP90 is known to participate in signal transduction, steroid receptor maturation, and cytoskeletal integrity, and its suppression in the liver may signify a negative feedback response to prolonged stress or resource reallocation toward more essential cytoprotective systems (Arya et al., 2007; Zhao et al., 2022). Conversely, its upregulation in muscle supports its cooperative role with HSP70 in maintaining sarcoplasmic protein integrity during sustained hyperthermia. Such contrasting patterns between HSP70 and HSP90 in liver and muscle echo findings in other heat-stressed species, where tissue-specific proteostasis responses serve as adaptive mechanisms under differential thermal burdens (De Paepe et al., 2009; Dangi et al., 2017).\u003c/p\u003e\n\u003cp\u003eThis molecular proteotoxic stress signature was further supported by expression patterns of CASP3, a key executioner of the apoptotic cascade. Heat stress significantly upregulated CASP3 in both tissues, with a more substantial induction observed in muscle. This likely reflects a greater cellular turnover or damage load in contractile tissue, possibly due to cumulative oxidative stress, impaired mitochondrial function, and calcium dysregulation\u0026mdash;all of which are potentiated under high ambient temperatures (Garrido et al., 2006; Liu et al., 2015). The positive correlation between HSP70 and CASP3 in muscle (r = 0.72, P = 0.005) observed in this study reinforces the concept that intense heat shock responses may co-occur with pro-apoptotic signaling, particularly when cytoprotective mechanisms are overwhelmed. While HSP70 is classically anti-apoptotic, its excessive induction can signify tipping points beyond cellular repair capacity (Zhang et al., 2014), potentially explaining its coordination with CASP3 transcription under sustained thermal challenge.\u003c/p\u003e\n\u003cp\u003eFrom a physiological perspective, the integration of molecular stress markers with whole-animal responses presents a coherent narrative: skeletal muscle, despite mounting strong proteostatic and apoptotic gene responses, appears more vulnerable to thermal damage. This is functionally consistent with the elevated core temperature, respiratory effort, and cardiovascular strain observed in heat-stressed lambs, which collectively impose a heavy metabolic burden on peripheral tissues. Conversely, the liver\u0026rsquo;s more balanced stress gene regulation, characterized by moderate HSP70 induction, HSP90 suppression, and strong FOXO3 activation, points to a more adaptive and energy-efficient protective profile, possibly reflecting its critical systemic role in managing oxidative metabolites and acute-phase responses (Horowitz, 2002; Gaughan et al., 2013).\u003c/p\u003e\n\u003cp\u003eThe expression patterns of myogenic and structural genes further contextualize these findings. Notably, MYOD\u0026mdash;a master transcriptional regulator of muscle cell differentiation\u0026mdash;was significantly downregulated in skeletal muscle under heat stress. This finding indicates a suppression of myogenic commitment and regenerative capacity, potentially as a trade-off under catabolic conditions where survival and stress mitigation override anabolic processes (Lian et al., 2022). The heat-induced decline in MYOD has been similarly reported in poultry and rodents, where thermal stress inhibits satellite cell activity and muscle regeneration (Rhoads et al., 2013; Lu et al., 2023). In contrast, ACTB3, a gene encoding a cytoskeletal protein involved in contractile fiber maintenance, was not significantly affected, suggesting that muscle structural integrity is more transcriptionally preserved than its growth or repair potential.\u003c/p\u003e\n\u003cp\u003eTogether, these data suggest that chronic heat exposure impairs muscle homeostasis at multiple levels: increasing apoptotic load, suppressing regenerative signaling, and inducing chaperone machinery to mitigate protein misfolding. While these mechanisms may prolong tissue function under stress, they are unlikely to be sustainable long-term, and may underlie observed reductions in growth performance and feed efficiency. Importantly, such changes reflect not only damage pathways but also adaptive reprogramming that prioritizes cellular survival over growth, a strategy well-documented in heat-stressed livestock and confirmed here in lambs (Sejian et al., 2018; Lian et al., 2022).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe transcriptional signatures identified in skeletal muscle tissue under chronic heat stress extend beyond physiological adaptation\u0026mdash;they likely have direct consequences for postmortem muscle biochemistry, meat quality traits, and commercial carcass value. While the primary objective of this study was to characterize the molecular and physiological heat stress response, the findings involving key regulatory and structural genes such as MYOD, ACTB3, CASP3, PPAR\u0026gamma;, HSP70, and FOXO3 suggest that muscle integrity, growth dynamics, and proteolytic activity are being fundamentally altered under thermal challenge, with downstream implications for meat yield, tenderness, water-holding capacity, and oxidative stability.\u003c/p\u003e\n\u003cp\u003eAmong the most striking transcriptional changes observed was the significant downregulation of MYOD, a master transcription factor essential for the commitment of satellite cells to myogenic lineage and for the regulation of muscle fiber differentiation (Lian et al., 2022). MYOD also plays a role in maintaining the proliferative capacity of myoblasts and coordinating their fusion into mature myofibers, particularly under stress or injury conditions. Suppression of MYOD, as observed in this study, indicates a suppressed myogenic program, suggesting that chronic heat exposure redirects cellular resources away from regenerative growth toward stress mitigation. Similar suppression of MYOD has been reported in heat-stressed broilers, leading to impaired breast muscle development and altered fiber morphology (Li et al., 2021), and in rodents, where thermal stress reduced satellite cell proliferation and regenerative potential (Rhoads et al., 2013). In lambs, such transcriptional downregulation may translate into reduced muscle accretion, altered fiber type composition, and decreased muscle mass, particularly in rapidly growing individuals.\u003c/p\u003e\n\u003cp\u003eThe downregulation of MYOD may also be linked to impaired meat tenderness and protein turnover, as satellite cell dysfunction limits the renewal of damaged myofibers and affects proteolytic enzyme access postmortem (Lian et al., 2022). Furthermore, lower MYOD expression during growth correlates with reduced expression of myofibrillar proteins such as myosin heavy chain and tropomyosin, whose postmortem degradation patterns strongly influence tenderness development during aging (Liu et al., 2015). Consequently, MYOD suppression under chronic heat stress could result in tougher meat texture, reduced proteolytic fragmentation of Z-discs, and lower shear force values\u0026mdash;findings supported by comparable studies in heat-stressed sheep and goats (Archana et al., 2018; Sejian et al., 2018).\u003c/p\u003e\n\u003cp\u003eIn contrast to MYOD, ACTB3\u0026mdash;a gene encoding a cytoskeletal protein structurally related to \u0026beta;-actin and involved in maintaining sarcomeric architecture\u0026mdash;was not significantly altered by heat stress, although it exhibited a slight upward trend. The transcriptional stability of ACTB3 under stress may reflect a conserved role in preserving structural integrity, even as regenerative pathways are suppressed. This is noteworthy, as sarcomeric proteins contribute to both muscle function in vivo and textural properties in meat postmortem. Stable ACTB3 expression may help maintain the integrity of contractile elements and prevent excessive proteolysis, thereby contributing to initial firmness and color stability. However, without adequate myogenic stimulation (as signaled by MYOD), long-term muscle growth and turnover could be compromised despite maintained structural gene expression.\u003c/p\u003e\n\u003cp\u003eAnother critical component of muscle biology affected by heat stress is apoptotic regulation, particularly through the activation of CASP3. The observed significant upregulation of CASP3 in muscle under chronic thermal exposure reflects increased apoptotic pressure, possibly due to cumulative oxidative damage, mitochondrial dysfunction, or endoplasmic reticulum stress. CASP3 is the executioner caspase responsible for cleaving cytoskeletal and nuclear proteins during programmed cell death (Garrido et al., 2006). Its upregulation in muscle not only signals enhanced cell turnover but also has direct implications for meat quality: higher CASP3 activity pre-slaughter has been associated with increased protein degradation, reduced muscle fiber integrity, and enhanced postmortem proteolysis, leading to early onset of tenderness (Ouali et al., 2006). However, excessive CASP3 activity may also contribute to protein denaturation and increased drip loss, thereby compromising water-holding capacity and cooking yield (Zhang et al., 2014).\u003c/p\u003e\n\u003cp\u003eIn parallel, the robust induction of HSP70, particularly in skeletal muscle, suggests significant proteotoxic stress under heat exposure. HSP70 is known to inhibit apoptosis by binding to Apaf-1 and blocking caspase activation (Kregel, 2002), but its overexpression may signal the threshold of cellular repair capacity being exceeded. High levels of HSP70 in muscle have been linked to reduced muscle protein degradation postmortem, slower tenderization, and increased thermal stability of sarcoplasmic proteins, which can affect both texture and flavor (Zhang et al., 2016). Moreover, HSP70 accumulation has been associated with color instability, due to its role in modulating myoglobin oxidation and mitochondrial activity (Garrido et al., 2006). Thus, while HSP70 serves a protective role in vivo, its persistence may reduce meat quality attributes depending on postmortem handling and aging protocols.\u003c/p\u003e\n\u003cp\u003eThe transcriptional behavior of FOXO3, which was significantly upregulated in liver and modestly increased in muscle, further contributes to the regulation of oxidative homeostasis and autophagy, both of which influence meat shelf-life and lipid oxidation. FOXO3 activation promotes the expression of antioxidant enzymes such as catalase and SOD2, as well as autophagy-related genes (Calnan and Brunet, 2008). In muscle, enhanced FOXO3 activity could improve cellular resilience to oxidative damage, but sustained activation is also known to induce muscle atrophy-related genes (e.g., atrogin-1, MuRF1), leading to lean mass loss and altered muscle-to-fat ratios (Eijkelenboom and Burgering, 2013). These changes could contribute to decreased marbling and leaner carcasses, as reported in heat-stressed goats and sheep (Ahmadpour et al., 2025).\u003c/p\u003e\n\u003cp\u003eEqually important is the observed downregulation of PPAR\u0026gamma; in both liver and muscle tissues. As a key nuclear receptor regulating adipocyte differentiation, lipid uptake, and fatty acid storage, PPAR\u0026gamma; suppression under thermal stress likely reflects a shift away from anabolic lipid metabolism (Zaboli et al., 2019). In the context of muscle, reduced PPAR\u0026gamma; activity may limit intramuscular fat deposition (IMF), leading to poorer marbling scores and dry, less flavorful meat\u0026mdash;a concern for lamb producers targeting high-quality cuts. Moreover, PPAR\u0026gamma; is involved in anti-inflammatory signaling, and its downregulation may amplify local inflammatory cascades, potentially affecting muscle pH decline, protease activation, and meat color stability (Manickam et al., 2020).\u003c/p\u003e\n\u003cp\u003eTaken together, the transcriptional changes identified in skeletal muscle under chronic heat stress portray a biological shift from anabolic growth to catabolic maintenance, driven by a convergence of suppressed myogenesis (MYOD), enhanced apoptosis (CASP3), cellular repair saturation (HSP70), and impaired lipid metabolism (PPAR\u0026gamma;). These molecular events are highly consistent with previously reported declines in meat quality parameters in heat-stressed ruminants, including increased toughness, reduced IMF, altered fiber structure, and lower carcass dressing percentages (Sejian et al., 2018; Archana et al., 2018). While the present study did not include direct postmortem meat quality measurements, the gene expression profiles serve as strong molecular proxies, allowing for predictive inferences supported by physiological and metabolic logic.\u003c/p\u003e\n\u003cp\u003eThis transcriptional profile, when combined with phenotypic indicators such as feed intake, growth rate, and rectal temperature, could potentially be used as a screening framework for carcass quality risk under heat stress, particularly in breeding or management contexts aiming to optimize meat yield and quality. Importantly, this also raises the possibility of nutritional or pharmacological interventions aimed at preserving muscle function during thermal exposure. For example, targeting the FOXO3\u0026ndash;SOD1\u0026ndash;PPAR\u0026gamma; axis through antioxidant supplementation or metabolic modulators may mitigate muscle catabolism and preserve IMF content.\u003c/p\u003e\n\u003cp\u003eNevertheless, scientific caution is warranted. The translation of gene expression to actual meat quality traits involves complex, multiscale regulation, including hormonal status, slaughter stress, and postmortem processing. While the genes discussed here are mechanistically linked to meat traits, functional confirmation via carcass measurements and protein-level validations would strengthen predictive claims. Future studies incorporating proteomics, meat chemistry, and sensory analysis will be instrumental in validating the molecular predictors identified in this work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo move beyond individual gene responses and better capture the functional interplay between key molecular pathways, this study utilized integrative expression ratios\u0026mdash;specifically, SOD1/IL-6 and FOXO3/TNF-\u0026alpha;\u0026mdash;as composite indices reflecting the balance between oxidative defense and inflammation. These ratios were significantly elevated in heat-stressed lambs, particularly in liver tissue, where the SOD1/TNF-\u0026alpha; ratio increased by more than twofold relative to controls. This shift denotes a functional pivot toward antioxidant dominance, suggestive of an adaptive attempt to suppress systemic inflammation through redox buffering mechanisms.\u003c/p\u003e\n\u003cp\u003eSuch composite transcriptional metrics offer several advantages over single-gene analyses. First, they provide a contextualized signal, capturing not just the magnitude but the directionality of cross-pathway interactions. Second, they are more resistant to inter-animal variability, especially in heterogeneous physiological systems like the liver. Third, as demonstrated in this study, they correlate meaningfully with physiological outcomes. Indeed, higher SOD1/IL-6 and FOXO3/TNF-\u0026alpha; ratios were negatively associated with rectal temperature (r = \u0026ndash;0.61, P = 0.011), suggesting that animals with transcriptional profiles favoring antioxidant defense over inflammation maintained better thermoregulation.\u003c/p\u003e\n\u003cp\u003eThis finding is consistent with the broader literature indicating that thermotolerant phenotypes often exhibit more controlled inflammatory responses and greater oxidative resilience (Leon and Helwig, 2010; Lara and Rostagno, 2013). In goats, cattle, and poultry, animals with higher antioxidant enzyme expression and lower pro-inflammatory cytokine activity show reduced signs of heat-induced tissue injury and better growth performance under heat stress (Sanz Fernandez et al., 2015; Jimoh et al., 2023). The present study reinforces that conclusion at the transcriptional level and provides a quantitative framework for molecular phenotyping of resilience in small ruminants.\u003c/p\u003e\n\u003cp\u003eMoreover, hierarchical clustering of gene expression ratios revealed the existence of a distinct subpopulation of heat-stressed lambs characterized by elevated antioxidant/inflammatory ratios and lower expression of HSP70, IL-6, and CASP3. These animals also showed higher FOXO3 and SOD1 expression, alongside reduced TNF-\u0026alpha; and PPAR\u0026gamma; levels, forming a coherent gene expression signature that aligns with lower physiological stress markers (e.g., rectal temperature and heart rate). This transcriptional phenotype may represent a resilient cluster, exhibiting a more balanced redox-inflammatory state and attenuated apoptotic drive under thermal challenge.\u003c/p\u003e\n\u003cp\u003eThese findings suggest that such ratios may serve as potential molecular indicators of thermotolerance, though their application as biomarkers will require further validation across breeds, time points, and predictive models. Unlike traditional markers that require extensive phenotyping under environmental stress, gene expression-based indices can be quantified from minimally invasive tissue samples and have the potential to reflect latent physiological adaptability. While further validation across breeds and environmental contexts is necessary, the predictive capacity of these ratios for thermophysiological outcomes underscores their translational utility in precision livestock farming.\u003c/p\u003e\n\u003cp\u003eAt the network level, correlation matrix analysis further supported these integrative interpretations. Under normal conditions, co-expression patterns were relatively weak and scattered, suggesting independent regulation of stress, inflammatory, and antioxidant genes. However, under heat stress, correlations became stronger, more polarized, and biologically coherent. For instance, HSP70 showed a significant negative correlation with TNF-\u0026alpha; (r = \u0026ndash;0.74, P = 0.0095), and FOXO3 was strongly negatively correlated with TNF-\u0026alpha; (r = \u0026ndash;0.78, P = 0.0045). These findings imply that as thermal load increases, transcriptional networks reconfigure, favoring mutual antagonism between inflammation and antioxidant responses.\u003c/p\u003e\n\u003cp\u003eSuch emergent correlation structures are indicative of stress-induced regulatory realignment, in which certain pathways (e.g., antioxidant defenses) are upregulated in concert, while others (e.g., inflammation) are suppressed, or vice versa. This observation aligns with prior heat stress studies in dairy cattle and chickens, which demonstrated increased co-regulation between metabolic and immune-related genes during thermal adaptation (Quinteiro-Filho et al., 2012; Guo et al., 2021; Bahrami-Yekdangi et al., 2022). Thus, gene\u0026ndash;gene correlation patterns may serve not only as descriptive tools but also as dynamic indicators of network-level plasticity under environmental stress.\u003c/p\u003e\n\u003cp\u003eWhile this study provides insight into coordinated expression patterns using PCA and correlation matrices, a more comprehensive systems-level understanding of heat stress responses would benefit from pathway-based network analysis. Tools such as STRING, KEGG, or Gene Ontology (GO) enrichment could identify co-regulated modules, upstream regulators, or shared signaling pathways among differentially expressed genes. Future research incorporating such bioinformatics platforms\u0026mdash;ideally with broader transcriptomic coverage\u0026mdash;could clarify the mechanistic underpinnings of heat-induced gene networks and their relevance to thermotolerance.\u003c/p\u003e\n\u003cp\u003eWhile the results of this study provide a detailed and multidimensional portrait of the physiological and molecular consequences of chronic heat stress in lambs, several important considerations warrant discussion. First, although the environmental model using naturally occurring thermal gradients between Semirom and Afzar offered a realistic and ecologically valid setting, it also introduced potential confounders\u0026mdash;such as variations in microclimate, air movement, and animal activity\u0026mdash;that cannot be completely controlled in open-field systems. However, the magnitude of environmental differentiation, confirmed through THI values and physiological responses, strongly supports the biological validity of the heat stress contrast, especially given the chronic duration (42 days) and the statistical robustness of observed changes.\u003c/p\u003e\n\u003cp\u003eSecond, while the study focused on transcriptional responses in two key peripheral tissues\u0026mdash;liver and skeletal muscle\u0026mdash;it does not encompass the full systemic impact of heat stress. The inclusion of hypothalamic or adrenal gene expression, for instance, might provide deeper insights into neuroendocrine regulation and stress axis activation, which are known to interact with peripheral inflammation and metabolic signaling (Ortiz-Col\u0026oacute;n et al., 2018; Sejian et al., 2021). Moreover, post-transcriptional regulation, including miRNA dynamics, protein translation rates, and post-translational modifications, were beyond the scope of this study but are important mediators of heat stress outcomes and merit future investigation (Yadav et al., 2021).\u003c/p\u003e\n\u003cp\u003eThird, while qPCR offered a high degree of specificity and technical reproducibility\u0026mdash;as demonstrated by amplification efficiencies, melt curve profiles, and the stability of the reference gene (ACTB, M value \u0026lt; 0.4)\u0026mdash;the analysis was limited to a targeted gene panel. Broader transcriptomic tools such as RNA-Seq or single-cell RNA profiling could uncover additional pathways and regulatory networks involved in thermotolerance, especially those related to nutrient sensing, angiogenesis, and tissue remodeling (Archana et al., 2017; Liang et al., 2022). Nevertheless, the gene panel selected in this study was grounded in well-established thermal stress literature and provided strong mechanistic anchors for interpreting physiological outcomes, particularly when integrated into pathway-level analyses.\u003c/p\u003e\n\u003cp\u003eImportantly, the present findings have several practical implications for livestock production under increasingly frequent and prolonged heat stress conditions. The molecular signature of heat resilience, defined by elevated SOD1/IL-6 and FOXO3/TNF-\u0026alpha; ratios, as well as reduced CASP3 and HSP70 expression in muscle, could serve as a predictive phenotype for selecting thermotolerant individuals. This approach aligns with the ongoing efforts in genomic selection programs to incorporate environmental adaptability into breeding indices (Collier et al., 2019; Caraba\u0026ntilde;o et al., 2017). Furthermore, dietary interventions targeting antioxidant pathways\u0026mdash;e.g., selenium, vitamin E, or plant-derived polyphenols\u0026mdash;may be used to enhance the FOXO3-SOD1 axis, providing prophylactic support against heat-induced oxidative damage (Sahin et al., 2006; Manickam et al., 2010).\u003c/p\u003e\n\u003cp\u003eLastly, it is critical to maintain scientific humility in interpreting these results. While the patterns observed are robust, statistically significant, and biologically plausible, they represent snapshots within a complex, time-evolving physiological landscape. It remains unclear whether the observed transcriptional adaptations persist over longer periods, or how reversible they are once thermal stress is alleviated. Additionally, inter-individual variability, epigenetic plasticity, and gene-by-environment interactions may modify these responses in different breeds, ages, or nutritional statuses.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides a comprehensive molecular and physiological characterization of lamb responses to prolonged heat stress under field-relevant environmental conditions, with emphasis on gene expression patterns in two key metabolic tissues: liver and skeletal muscle. The integration of transcriptional profiling, physiological measurements, and tissue-specific interpretation reveals that chronic thermal load elicits coordinated but distinct gene expression programs across tissues, with critical implications for thermotolerance, health, and production traits in small ruminants.\u003c/p\u003e \u003cp\u003eIn the liver, which plays a central role in systemic metabolic regulation and immune modulation, oxidative stress-related genes such as SOD1 and FOXO3 were significantly upregulated, indicating an active transcriptional adaptation aimed at reinforcing redox homeostasis. Simultaneously, inflammatory cytokines TNF-α and IL-6 were significantly downregulated, suggesting effective hepatic suppression of inflammatory signaling. The concurrent upregulation of antioxidant pathways and suppression of pro-inflammatory responses underscores a protective hepatic transcriptional phenotype under thermal stress, one that may buffer systemic oxidative and immune challenges. Additionally, PPARγ, a key regulator of lipid metabolism and anti-inflammatory signaling, was significantly downregulated in the liver, suggesting a shift away from anabolic lipid processing under prolonged heat exposure.\u003c/p\u003e \u003cp\u003eIn skeletal muscle, the transcriptional response diverged. While FOXO3 was slightly but not significantly increased, SOD1 expression remained unchanged, indicating a relatively muted antioxidant response compared to the liver. Instead, heat shock proteins HSP70 and HSP90 were significantly upregulated, with HSP70 showing particularly strong induction, highlighting intense proteotoxic stress and cellular protein unfolding. The strong induction of CASP3 in muscle suggests activation of apoptotic pathways, indicating that muscle tissue may be more prone to cellular damage or turnover under sustained heat exposure. This was further supported by the downregulation of MYOD, a key myogenic transcription factor essential for muscle fiber development and regeneration. The suppression of MYOD, alongside the stable expression of the structural gene ACTB3, suggests that muscle anabolic activity is compromised while structural maintenance is preserved, a pattern consistent with reduced muscle growth potential without overt degradation.\u003c/p\u003e \u003cp\u003eThese molecular adaptations were closely aligned with whole-animal physiological responses. Lambs housed in the heat-stressed region exhibited significantly elevated rectal temperatures, respiratory rates, and heart rates, indicating substantial thermophysiological strain. Performance metrics such as feed intake and average daily gain were also significantly reduced, consistent with the metabolic cost of heat adaptation. Importantly, correlation analysis revealed strong negative relationships between inflammatory and antioxidant gene expression, and positive associations between heat shock and apoptotic markers, supporting the presence of an integrated cellular stress network. These relationships were particularly evident under heat stress, reflecting a transcriptionally re-wired landscape optimized for survival under prolonged environmental challenge.\u003c/p\u003e \u003cp\u003eThe study also introduced integrative gene expression ratios, such as SOD1/IL-6 and FOXO3/TNF-α, which were significantly elevated under heat stress and negatively correlated with rectal temperature. These composite metrics reflect the balance between cytoprotective and inflammatory pathways and may serve as potential biomarkers of thermotolerance. Hierarchical clustering of these ratios delineated a distinct subgroup of heat-exposed lambs with favorable expression profiles\u0026mdash;characterized by higher antioxidant-to-inflammation ratios and lower expression of HSP70 and CASP3\u0026mdash;suggesting a resilient molecular phenotype associated with improved physiological performance.\u003c/p\u003e \u003cp\u003eImportantly, while the transcriptomic findings offer mechanistic insights into the biological response to heat stress, certain limitations must be acknowledged. First, gene expression was assessed only at the mRNA level; protein-level validation (e.g., via Western blotting, ELISA, or activity assays) was not performed. The translation of transcript abundance into functional protein levels is not always linear, and future studies should include proteomic and enzymatic validations to confirm these molecular signatures. Second, although the study design leveraged naturally distinct thermal environments to simulate realistic field conditions, it inherently introduced several uncontrolled environmental variables beyond temperature and humidity. Factors such as altitude, wind exposure, solar radiation, airflow patterns, and forage quality\u0026mdash;all of which can influence animal physiology and gene expression independently of THI\u0026mdash;were not experimentally controlled. These variables may have contributed to some of the observed differences in gene expression between the two geographic sites. While efforts were made to standardize diet composition and housing conditions, subtle differences in nutrient content of local forage, microclimatic airflow, or elevation-related hypoxia could confound the attribution of transcriptional changes solely to thermal stress. To isolate the specific effects of heat load and better control for environmental confounders, future studies are encouraged to complement field-based observations with chamber-based experiments, where temperature, humidity, and other variables can be precisely manipulated while keeping all other factors constant. Third, the study was limited to a single breed and sex (male lambs) and was conducted under specific climatic and management conditions, which may limit generalizability. Breed-specific or sex-specific transcriptional plasticity in response to heat stress should be evaluated to ensure broader applicability. Fourth, although associations were drawn between gene expression and physiological indicators, no direct measurements of carcass traits or meat quality outcomes were collected. Given the observed downregulation of MYOD and PPARγ, and the upregulation of CASP3 and HSP70, potential impacts on meat quality\u0026mdash;including tenderness, water-holding capacity, and marbling\u0026mdash;are likely and warrant empirical validation.\u003c/p\u003e \u003cp\u003eFuture research should aim to expand on these findings by:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIncluding additional breeds and sexes, and sampling under varying agroecological contexts to capture population-wide variability in heat response.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIncorporating proteomic, metabolomic, and immunohistochemical analyses to validate transcriptional changes at functional and structural levels.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eConducting longitudinal studies to track the dynamics of gene expression over the full course of heat exposure and recovery, to distinguish between transient versus sustained transcriptional adaptations.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLinking gene expression profiles to phenotypic outcomes, including growth metrics, meat quality indices (e.g., IMF content, shear force, pH), and immune competence, to establish practical predictive models for performance under thermal stress.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEvaluating the efficacy of nutritional interventions, such as antioxidant-rich diets (selenium, vitamin E, polyphenols), in modulating key regulatory pathways including the FOXO3\u0026ndash;SOD1 axis and inflammatory mediators.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eFrom a practical standpoint, these findings have important implications for animal breeding, nutritional management, and thermal mitigation strategies in small ruminant production systems. The identification of heat-responsive gene networks and expression ratios provides a basis for the development of molecular diagnostics for early detection of thermal distress, as well as for the selection of resilient animals in genetic improvement programs. Incorporating expression-based indicators into precision livestock monitoring systems could enable real-time assessment of stress burden and inform adaptive interventions such as cooling infrastructure, shading, or targeted dietary supplementation.\u003c/p\u003e \u003cp\u003eIn conclusion, this study offers a robust, multi-layered view of the molecular and physiological adaptations of lambs to chronic heat stress, highlighting both shared and tissue-specific strategies involving oxidative defense, inflammatory modulation, protein stability, apoptosis, and muscle development. The liver emerged as a more resilient organ through coordinated antioxidant and anti-inflammatory regulation, while skeletal muscle bore greater stress burden, with elevated heat shock and apoptotic responses and suppressed myogenic signaling. The identification of transcriptional ratios and correlation structures as indicators of thermotolerance represents a significant advance in the molecular phenotyping of stress resilience. As global climate change accelerates, such mechanistic insight will be critical for developing sustainable livestock systems that balance productivity, welfare, and environmental adaptation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend their sincere gratitude to SabzBavaran-e-NouAndish Co. for their invaluable technical assistance and the provision of laboratory facilities, which were instrumental in the successful execution of this research. The authors also wish to thank the Jafarbiglou clan of the Qashqaei Tribal Confederation for their kind cooperation and generous provision of camels, which significantly contributed to the field component of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was financially supported by Yasouj University through grant number 4024443009, awarded to Dr. Amir Ahmadpour. The funding was exclusively allocated for the research, development, and preparation of this manuscript. No additional financial support was received from other public, commercial, or not-for-profit funding agencies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u0026mdash;financial, professional, or personal\u0026mdash;that could have influenced the integrity, analysis, or presentation of the research findings. There are no affiliations, memberships, financial relationships, or other connections that could be perceived as potential conflicts of interest regarding the authorship or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmir Ahmadpour contributed to the study\u0026rsquo;s conceptualization, experimental supervision, methodological framework, field investigation, data acquisition, manuscript review and editing, and was responsible for securing funding.\u003c/p\u003e\n\u003cp\u003eMousa Zarrin was involved in conceptual design, statistical validation, data analysis, and the preparation of the original manuscript draft.\u003c/p\u003e\n\u003cp\u003eRafid Hafedh Sabeeh Alrahif assisted in fieldwork, including data and sample collection.\u003c/p\u003e\n\u003cp\u003eAll authors reviewed and approved the final version of the manuscript prior to submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to institutional policies at Yasouj University. However, data may be made available upon reasonable request from the corresponding author, contingent upon approval by the affiliated institution and the research sponsor.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmadpour A, Forouzanfar S, Ghazanfari S, Hafedh Sabeeh Alrahif R, Zarrin M (2025) Comparative Analysis of Feeding Strategies on the Growth and Carcass Quality of Turki-Qashqai Lambs: A Focus on Supplementary Feed Concentration. \u003cem\u003eIranian Journal of Applied Animal Science\u003c/em\u003e 15(1):61\u0026ndash;71. https://doi.org/10.71798/ijas.2025.1202959 \u003c/li\u003e\n\u003cli\u003eArchana PR, Sejian V, Ruban W, Bagath M, Krishnan G, Aleena J, Manjunathareddy GB, Beena V, Bhatta R (2018) Comparative assessment of heat stress induced changes in carcass traits, plasma leptin profile and skeletal muscle myostatin and HSP70 gene expression patterns between indigenous Osmanabadi and Salem Black goat breeds. \u003cem\u003eMeat Sci\u003c/em\u003e 141:66\u0026ndash;80. https://doi.org/10.1016/j.meatsci.2018.03.015\u003c/li\u003e\n\u003cli\u003eArya R, Mallik M, Lakhotia SC (2007) Heat shock genes\u0026mdash;integrating cell survival and death. \u003cem\u003eJournal of Biosciences\u003c/em\u003e 32(3):595\u0026ndash;610. https://doi.org/10.1007/s12038-007-0059-3\u003c/li\u003e\n\u003cli\u003eBahrami Yekdangi M, Ghorbani GR, Sadeghi‑Sefidmazgi A, Mahnani A, Drackley JK, Ghaffari MH (2022) Identification of cow-level risk factors and associations of selected blood macro-minerals at parturition with dystocia and stillbirth in Holstein dairy cows. \u003cem\u003eScientific Reports\u003c/em\u003e 12:5929. https://doi.org/10.1038/s41598-022-09928-w \u003c/li\u003e\n\u003cli\u003eCalnan DR, Brunet A (2008) The foxo code. \u003cem\u003eOncogene\u003c/em\u003e 27(16):2276\u0026ndash;2288. https://doi.org/10.1038/onc.2008.21\u003c/li\u003e\n\u003cli\u003eCaraba\u0026ntilde;o MJ, Ram\u0026oacute;n M, D\u0026iacute;az C, Molina A, P\u0026eacute;rez Guzm\u0026aacute;n MD, Serradilla JM (2017) Breeding for resilience to heat stress effects in dairy ruminants: A comprehensive review. \u003cem\u003eJournal of Animal Science\u003c/em\u003e 95(4):1813\u0026ndash;1826. https://doi.org/10.2527/jas.2016.1250 \u003c/li\u003e\n\u003cli\u003eCollier RJ, Dahl GE, VanBaale MJ (2006) Major advances associated with environmental effects on dairy cattle. \u003cem\u003eJ Dairy Sci\u003c/em\u003e 89(4):1244\u0026ndash;1253. https://doi.org/10.3168/jds.S0022-0302(06)72193-2\u003c/li\u003e\n\u003cli\u003eCollier RJ, Gebremedhin KG (2015) Thermal biology of domestic animals. \u003cem\u003eAnnu Rev Anim Biosci\u003c/em\u003e 3(1):513\u0026ndash;532. https://doi.org/10.1146/annurev-animal-022114-110659\u003c/li\u003e\n\u003cli\u003eCollier RJ, Baumgard LH, Zimbelman RB, Xiao Y (2019) Heat stress: physiology of acclimation and adaptation. \u003cem\u003eAnimal Frontiers\u003c/em\u003e 9(1):12\u0026ndash;19. https://doi.org/10.1093/af/vfy034 \u003c/li\u003e\n\u003cli\u003eDangi SS, Bharati J, Abdul Samad H, Bhure SK, Singh G, Maurya VP, Sarkar M, Kumar P (2017) Expression dynamics of heat shock proteins (HSP) in livestock under thermal stress. In: \u003cem\u003eHeat Shock Proteins in Veterinary Medicine and Sciences\u003c/em\u003e, pp 37\u0026ndash;79.\u003c/li\u003e\n\u003cli\u003eDas R, Sailo L, Verma N, Bharti P, Saikia J, Kumar R (2016) Impact of heat stress on health and performance of dairy animals: A review. \u003cem\u003eVet World \u003c/em\u003e9(3):260. https://doi.org/10.14202/vetworld.2016.260-268\u003c/li\u003e\n\u003cli\u003eDe Paepe B, Creus KK, Martin JJ, Weis J, De Bleecker JL (2009) A dual role for HSP90 and HSP70 in the inflammatory myopathies: from muscle fiber protection to active invasion by macrophages. \u003cem\u003eAnnals of the New York Academy of Sciences\u003c/em\u003e 1173(1):463\u0026ndash;469. https://doi.org/10.1111/j.1749-6632.2009.04654.x \u003c/li\u003e\n\u003cli\u003eEijkelenboom A, Burgering BMT (2013) FOXOs: signalling integrators for homeostasis maintenance. \u003cem\u003eNat Rev Mol Cell Biol \u003c/em\u003e14(2):83\u0026ndash;97. https://doi.org/10.1038/nrm3507\u003c/li\u003e\n\u003cli\u003eEl-Beltagy A, Madkour M (2012) Impact of climate change on arid lands agriculture. \u003cem\u003eAgric Food Secur \u003c/em\u003e1:1\u0026ndash;12. https://doi.org/10.1186/2048-7010-1-3\u003c/li\u003e\n\u003cli\u003eEl-Tarabany MS, El-Tarabany AA, Atta MA (2017) Physiological and lactation responses of Egyptian dairy Baladi goats to natural thermal stress under subtropical environmental conditions. \u003cem\u003eInt J Biometeorol \u003c/em\u003e61:61\u0026ndash;68. https://doi.org/10.1007/s00484-016-1190-3\u003c/li\u003e\n\u003cli\u003eGarrido C, Galluzzi L, Brunet M, Puig PE, Didelot C, Kroemer G (2006) Mechanisms of cytochrome c release from mitochondria. \u003cem\u003eCell Death \u0026amp; Differentiation\u003c/em\u003e 13(9):1423\u0026ndash;1433. https://doi.org/10.1038/sj.cdd.4401965 \u003c/li\u003e\n\u003cli\u003eGaughan JB, Bonner SL, Loxton I, Mader TL (2013) Effects of chronic heat stress on plasma concentration of secreted heat shock protein 70 in growing feedlot cattle. \u003cem\u003eJournal of Animal Science\u003c/em\u003e 91(1):120\u0026ndash;129. https://doi.org/10.2527/jas.2012-5294 \u003c/li\u003e\n\u003cli\u003eGiridhar K, Samireddypalle A (2015) Impact of climate change on forage availability for livestock. In: \u003cem\u003eClimate Change Impact on Livestock: Adaptation and Mitigation\u003c/em\u003e, pp 97\u0026ndash;112. Springer India. https://doi.org/10.1007/978-81-322-2265-1_7 \u003c/li\u003e\n\u003cli\u003eGuo Z, Gao S, Ouyang J, Ma L, Bu D (2021) Impacts of heat stress-induced oxidative stress on the milk protein biosynthesis of dairy cows. \u003cem\u003eAnimals \u003c/em\u003e11(3):726. https://doi.org/10.3390/ani11030726\u003c/li\u003e\n\u003cli\u003eHorowitz M (2002) From molecular and cellular to integrative heat defense during exposure to chronic heat. \u003cem\u003eComp Biochem Physiol A Mol Integr Physiol \u003c/em\u003e131(3):475-483. https://doi.org/10.1016/S1095-6433(01)00499-5\u003c/li\u003e\n\u003cli\u003eJimoh OA, Daramola OT, Okin Aminu HO, Ojo OA (2023) HSP70, adiponectin, leptin, pro-inflammatory cytokines and metabolic hormones of heat-stressed broilers fed herbal supplements. \u003cem\u003eJournal of Thermal Biology\u003c/em\u003e 117:103681. https://doi.org/10.1016/j.jtherbio.2023.103681 \u003c/li\u003e\n\u003cli\u003eKregel KC (2002) Invited review: heat shock proteins: modifying factors in physiological stress responses and acquired thermotolerance. \u003cem\u003eJournal of Applied Physiology\u003c/em\u003e 92(5):2177\u0026ndash;2186. https://doi.org/10.1152/japplphysiol.01267.2001 \u003c/li\u003e\n\u003cli\u003eLamont BJ, Waters MF, Andrikopoulos S (2016) A low-carbohydrate high-fat diet increases weight gain and does not improve glucose tolerance, insulin secretion or \u0026beta;-cell mass in NZO mice. \u003cem\u003eNutr Diabetes\u003c/em\u003e 6(2):e194. https://doi.org/10.1038/nutd.2016.2\u003c/li\u003e\n\u003cli\u003eLara LJ, Rostagno MH (2013) Impact of heat stress on poultry production. \u003cem\u003eAnimals\u003c/em\u003e 3(2):356\u0026ndash;369. https://doi.org/10.3390/ani3020356 \u003c/li\u003e\n\u003cli\u003eLei Z, Wei D, Tang L, Wang S, Pan C, Ma Y, Ma Y (2022) SGK1 affects the phosphorylation of FOXO1/FOXO3 promoting bovine fat deposition via the PI3K/Akt signaling pathway.\u003c/li\u003e\n\u003cli\u003eLeon LR, Helwig BG (2010) Heat stroke: role of the systemic inflammatory response. \u003cem\u003eJournal of Applied Physiology\u003c/em\u003e 109(6):1980\u0026ndash;1988. https://doi.org/10.1152/japplphysiol.00301.2010 \u003c/li\u003e\n\u003cli\u003eLi S, Zhang Y, Guan Z, Li H, Ye M, Chen X, Shen J et al (2020) SARS-CoV-2 triggers inflammatory responses and cell death through caspase-8 activation. \u003cem\u003eSignal Transduct Target Ther \u003c/em\u003e5(1):235. https://doi.org/10.1038/s41392-020-00334-0\u003c/li\u003e\n\u003cli\u003eLi X, Zhang M, Feng J, Zhou Y (2021) Myostatin and related factors are involved in skeletal muscle protein breakdown in growing broilers exposed to constant heat stress. \u003cem\u003eAnimals\u003c/em\u003e 11(5):1467. https://doi.org/10.3390/ani11051467 \u003c/li\u003e\n\u003cli\u003eLian D, Chen MM, Wu H, Deng S, Hu X (2022) The role of oxidative stress in skeletal muscle myogenesis and muscle disease. \u003cem\u003eAntioxidants\u003c/em\u003e 11(4):755. https://doi.org/10.3390/antiox11040755 \u003c/li\u003e\n\u003cli\u003eLiu T, Zhang L, Joo D, Sun SC (2017) NF-\u0026kappa;B signaling in inflammation. \u003cem\u003eSignal Transduct Target Ther \u003c/em\u003e2(1):1\u0026ndash;9. https://doi.org/10.1038/sigtrans.2017.23\u003c/li\u003e\n\u003cli\u003eLiu Y, Cai H, Guo X, Aierken A, Hua J, Ma B, Peng S (2022) Melatonin alleviates heat stress-induced testicular damage in dairy goats by inhibiting the PI3K/AKT signaling pathway. \u003cem\u003eStress Biol \u003c/em\u003e2(1):47. https://doi.org/10.1007/s44154-022-00069-8\u003c/li\u003e\n\u003cli\u003eLiu YL, Ding KN, Shen XL, Liu HX, Zhang YA, Liu YQ, He YM, Tang LP (2022) Chronic heat stress promotes liver inflammation in broilers via enhancing NF-\u0026kappa;B and NLRP3 signaling pathway. \u003cem\u003eBMC Vet Res\u003c/em\u003e 18(1):289. https://doi.org/10.1186/s12917-022-03387-1\u003c/li\u003e\n\u003cli\u003eLiu H, Mao P, Wang J, Wang T, Xie CH (2015) Allicin protects PC12 cells against 6-OHDA-induced oxidative stress and mitochondrial dysfunction via regulating mitochondrial dynamics. \u003cem\u003eCellular Physiology and Biochemistry\u003c/em\u003e 36(3):966\u0026ndash;979. https://doi.org/10.1159/000430271 \u003c/li\u003e\n\u003cli\u003eLiu L, Fu C, Yan M, Xie H, Li S, Yu Q, He S, He J (2016) Resveratrol modulates intestinal morphology and HSP70/90, NF-\u0026kappa;B and EGF expression in the jejunal mucosa of black-boned chickens on exposure to circular heat stress. \u003cem\u003eFood \u0026amp; Function\u003c/em\u003e 7(3):1329\u0026ndash;1338. https://doi.org/10.1039/c5fo01338k \u003c/li\u003e\n\u003cli\u003eLivak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2\u0026minus;\u0026Delta;\u0026Delta;CT method. \u003cem\u003eMethods\u003c/em\u003e 25(4):402\u0026ndash;408. https://doi.org/10.1006/meth.2001.1262\u003c/li\u003e\n\u003cli\u003eLu J, Li H, Yu D, Zhao P, Liu Y (2023) Heat stress inhibits the proliferation and differentiation of myoblasts and is associated with damage to mitochondria. \u003cem\u003eFrontiers in Cell \u0026amp; Developmental Biology\u003c/em\u003e 11:1171506. https://doi.org/10.3389/fcell.2023.1171506 \u003c/li\u003e\n\u003cli\u003eMader TL, Davis MS, Brown-Brandl T (2006) Environmental factors influencing heat stress in feedlot cattle. \u003cem\u003eJ Anim Sci\u003c/em\u003e 84(3):712\u0026ndash;719. https://doi.org/10.2527/2006.843712x\u003c/li\u003e\n\u003cli\u003eManickam R, Duszka K, Wahli W (2020) PPARs and microbiota in skeletal muscle health and wasting. \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e 21(21):8056. https://doi.org/10.3390/ijms21218056\u003c/li\u003e\n\u003cli\u003eMarai IFM, El-Darawany AA, Fadiel A, Abdel-Hafez MAM (2007) Physiological traits as affected by heat stress in sheep\u0026mdash;a review. \u003cem\u003eSmall Rumin Res\u003c/em\u003e 71(1\u0026ndash;3):1\u0026ndash;12. https://doi.org/10.1016/j.smallrumres.2006.10.003\u003c/li\u003e\n\u003cli\u003eOmidi A, Nazifi S, Rasekh M, Zare N (2024) Heat-shock proteins, oxidative stress, and antioxidants in one-humped camels. \u003cem\u003eTrop Anim Health Prod\u003c/em\u003e 56(1):29. https://doi.org/10.1007/s11250-023-03870-3\u003c/li\u003e\n\u003cli\u003eOrtiz-Col\u0026oacute;n G, Fain SJ, Par\u0026eacute;s IK, Curbelo‑Rodr\u0026iacute;guez J, Jim\u0026eacute;nez‑Cab\u0026aacute;n E, Pag\u0026aacute;n‑Morales M, Gould WA (2018) Assessing climate vulnerabilities and adaptive strategies for resilient beef and dairy operations in the tropics. \u003cem\u003eClimatic Change\u003c/em\u003e 146(1-2):47\u0026ndash;58. https://doi.org/10.1007/s10584-017-2110-1 \u003c/li\u003e\n\u003cli\u003eOuali A, Herrera‑Mendez CH, Coulis G, Becila S, Boudjellal A, Aubry L, Sentandreu MA (2006) Revisiting the conversion of muscle into meat and the underlying mechanisms. \u003cem\u003eMeat Science\u003c/em\u003e 74(1):44\u0026ndash;58. https://doi.org/10.1016/j.meatsci.2006.05.010 \u003c/li\u003e\n\u003cli\u003eQuinteiro-Filho WM, Rodrigues MV, Ribeiro A, Ferraz-de-Paula V, Pinheiro ML, S\u0026aacute; LRM, Ferreira AJP, Palermo-Neto J (2012) Acute heat stress impairs performance parameters and induces mild intestinal enteritis in broiler chickens: role of acute hypothalamic-pituitary-adrenal axis activation. \u003cem\u003eJ Anim Sci\u003c/em\u003e 90(6):1986-1994. https://doi.org/10.2527/jas.2011-3949\u003c/li\u003e\n\u003cli\u003eRao KVV, Rani MU, Reddy AG, Kumar BA (2023) Bovine Lactoferrin Mitigates Oxidative Stress and Inflammation in CCL4 and High-fat Diet-induced NAFLD in C57BL/6 Mice. \u003cem\u003eIndian J Anim Res\u003c/em\u003e 1:9.\u003c/li\u003e\n\u003cli\u003eRhoads RP, Flann KL, Cardinal TR, Rathbone CR, Liu X, Allen RE (2013) Satellite cells isolated from aged or dystrophic muscle exhibit a reduced capacity to promote angiogenesis in vitro. \u003cem\u003eBiochemical and Biophysical Research Communications\u003c/em\u003e 440(3):399\u0026ndash;404. https://doi.org/10.1016/j.bbrc.2013.09.085\u003c/li\u003e\n\u003cli\u003eSahin K, Onderci M, Sahin N, Gursu MF, Khachik F, Kucuk O (2006) Effects of lycopene supplementation on antioxidant status, oxidative stress, performance and carcass characteristics in heat-stressed Japanese quail. \u003cem\u003eJ Therm Biol\u003c/em\u003e 31(4):307-312. https://doi.org/10.1016/j.jtherbio.2006.01.002\u003c/li\u003e\n\u003cli\u003eSejian V (2013) Climate change: impact on production and reproduction, adaptation mechanisms and mitigation strategies in small ruminants: a review. \u003cem\u003eIndian J Small Rumin\u003c/em\u003e 19(1):1\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eSejian V, Bhatta R, Gaughan JB, Dunshea FR, Lacetera N (2018) Adaptation of animals to heat stress. \u003cem\u003eAnimal\u003c/em\u003e 12(s2):s431\u0026ndash;s444. https://doi.org/10.1017/S1751731118001945\u003c/li\u003e\n\u003cli\u003eSejian V, Silpa MV, Nair MRR, Devaraj C, Krishnan G, Bagath M, Chauhan SS et al. (2021) Heat stress and goat welfare: Adaptation and production considerations. \u003cem\u003eAnimals\u003c/em\u003e 11(4):1021. https://doi.org/10.3390/ani11041021\u003c/li\u003e\n\u003cli\u003eSong Y, Xie X, Wang Y, Gao W, Huang H, Cao F, Yang X (2024) Identification of Superoxide Dismutase (SOD) Gene Family in Ginkgo (Ginkgo biloba L.) and Role of GbSOD8 in Response to Salt Stress. \u003cem\u003eForests\u003c/em\u003e 15(12):2141. https://doi.org/10.3390/f15122141\u003c/li\u003e\n\u003cli\u003eTang Y, Zhou X, Cao T, Chen E, Li Y, Lei W, Hu Y, He B, Liu S (2022) Endoplasmic reticulum stress and oxidative stress in inflammatory diseases. \u003cem\u003eDNA Cell Biol\u003c/em\u003e 41(11):924\u0026ndash;934. https://doi.org/10.1089/dna.2022.0265\u003c/li\u003e\n\u003cli\u003eSanz Fernandez MV, Johnson JS, Abuajamieh M, Stoakes SK, Seibert JT, Cox L, Kahl S, Elsasser TH, Ross JW, Isom SC, Rhoads RP, Baumgard LH (2015) Effects of heat stress on carbohydrate and lipid metabolism in growing pigs. \u003cem\u003ePhysiological Reports\u003c/em\u003e 3(2):e12315. https://doi.org/10.14814/phy2.12315\u003c/li\u003e\n\u003cli\u003eVandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT‑PCR data by geometric averaging of multiple internal control genes. \u003cem\u003eGenome Biology\u003c/em\u003e 3(7):research0034. https://doi.org/10.1186/gb-2002-3-7-research0034 \u003c/li\u003e\n\u003cli\u003eWang RH, Liang RR, Lin H, Zhu LX, Zhang YM, Mao YW, Dong PC, Niu LB, Zhang MH, Luo X (2017) Effect of acute heat stress and slaughter processing on poultry meat quality and postmortem carbohydrate metabolism. \u003cem\u003ePoult Sci\u003c/em\u003e 96(3):738\u0026ndash;746. https://doi.org/10.3382/ps/pew329\u003c/li\u003e\n\u003cli\u003eWheelock JB, Rhoads RP, VanBaale MJ, Sanders SR, Baumgard LH (2010) Effects of heat stress on energetic metabolism in lactating Holstein cows. \u003cem\u003eJ Dairy Sci\u003c/em\u003e 93(2):644-655. https://doi.org/10.3168/jds.2009-2295\u003c/li\u003e\n\u003cli\u003eYadav P, Yadav B, Swain DK, Anand M, Yadav S, Madan AK (2021) Differential expression of miRNAs and related mRNAs during heat stress in buffalo heifers. \u003cem\u003eJournal of Thermal Biology\u003c/em\u003e 97:102904. https://doi.org/10.1016/j.jtherbio.2021.102904 \u003c/li\u003e\n\u003cli\u003eZaboli G, Huang X, Feng X, Ahn DU (2019) How can heat stress affect chicken meat quality?\u0026ndash;a review. \u003cem\u003ePoult Sci\u003c/em\u003e 98(3):1551\u0026ndash;1556. https://doi.org/10.3382/ps/pey399\u003c/li\u003e\n\u003cli\u003eZhang L, Ying SJ, An WJ, Lian H, Zhou GB, Han ZY (2014) Effects of dietary betaine supplementation subjected to heat stress on milk performances and physiology indices in dairy cow. \u003cem\u003eGenet Mol Res\u003c/em\u003e 13(3):7577-7586. https://doi.org/10.4238/2014.September.12.20\u003c/li\u003e\n\u003cli\u003eZhang M, Wang D, Geng Z, Sun C, Bian H, Xu W, Zhu Y, Li P (2016) Differential expression of heat shock protein 90, 70, 60 in chicken muscles postmortem and its relationship with meat quality. \u003cem\u003eAsian-Australas J Anim Sci\u003c/em\u003e 30(1):94. https://doi.org/10.5713/ajas.16.0216\u003c/li\u003e\n\u003cli\u003eZhao S, Song T‐y, Wang Z‐y, Gao J, Cao J‐w, Hu L‐l, Huang Z‐r, Xie L‐p, Ji Y (2022) S-nitrosylation of Hsp90 promotes cardiac hypertrophy in mice through GSK3\u0026beta; signaling. \u003cem\u003eActa Pharmacologica Sinica\u003c/em\u003e 43(8):1979\u0026ndash;1988. https://doi.org/10.1038/s41401-021-00828-9 \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Composition and Nutritional Analysis of the Experimental Feed Mixture\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeed Ingredient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInclusion Rate (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChemical Composition Parameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003eAlfalfa hay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eDry matter (DM, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e91.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003eBarley grain (cracked)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eCrude protein (CP, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003eCorn grain (ground)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eEther extract (EE, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003eSoybean meal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNeutral detergent fiber (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003eWheat bran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eAcid detergent fiber (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003eLimestone, salt, premix\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eAsh (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eMetabolizable energy (Mcal/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Oligonucleotide Sequences for qPCR Amplification of Stress, Apoptotic, Inflammatory, and Muscle-Related Genes in Lamb Tissues\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccession No. (NCBI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eForward Primer (5\u0026prime;\u0026rarr;3\u0026prime;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReverse Primer (5\u0026prime;\u0026rarr;3\u0026prime;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTaqMan Probe (5\u0026prime;\u0026rarr;3\u0026prime;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTm (\u0026deg;C)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmplicon Size (bp)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eIL-6\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNM_001009392.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAGTCCGGAGAGGAGACTTCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGGAGAGCATTGGAAATTGGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTGAGTCACTGCCTGGAAGTCTGGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTNF-\u0026alpha;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNM_001024860.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCAGAGGGAAGAGTTCCCCAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTGGGAGTAGACAAGGTACAACCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eACAGGTCCTCAGCCTCTTCTCCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSOD1\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNM_001009403.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCCTGGTGGTTGTGTTGTGAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAAGGGCGATCCCAATTACAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTTCCAGGGCACCAAGGTCGGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e59.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eFOXO3\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eXM_004003975.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGCGGCTCAGAAGAGGATTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAGCTGGAAGTAGGGCAGAGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCCAGCTCCAGGACAGGACTACCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHSP70\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNM_001285626.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eACAGGAGTTGGAGGATGAGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTGGTTGAGTAGGCGTTGTGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCAGGCTGTGACGACGCTGGAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHSP90\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eXM_004012502.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCGGAGGAAGTGCTGAGTTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTCGTCGTCATCCTCATCTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAGAGCCTCAGGTGTGGTGGCTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCASP3\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNM_001009329.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCTGGAACAAACAGGACGGTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTTGCGGTTGTAGAGGTTGGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTGAGGCGGTTGTAGAAGGGATGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ePPAR\u0026gamma;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNM_001168777.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTCTGGGAGATTCTCCTGTTGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGAGGCCAGCATCGTGTAGAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTGGAGACCGCCCAGGTTTGAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMYOD\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNM_001285626.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGTGAGGAGGAGGAGGTGGAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGGATGAGGAAGAGGGTGAGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCCTGAGGCGGGAGACAGTGGGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eACTB3\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eXM_027964564.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCCAGGCTGTGTTGTCCCTAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCCTTGCTCAGGAGGAGCAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTCGTACCACTGGCATTGTGAGGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eGAPDH\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNM_001034034.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGGTGGTGCTAAGCGTGTTAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAGTGATGGCATGGACTGTGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTCGTGGAGTCTACTGGTGTCTTCACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Environmental Parameters Confirming Chronic Heat Stress Exposure in Afzar Compared to Thermoneutral Conditions in Semirom\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfzar (Heat Stress Zone)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSemirom (Thermoneutral Zone)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eTemperature (\u0026deg;C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e39.3 \u0026plusmn; 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e25.6 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eRelative Humidity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e34.0 \u0026plusmn; 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e62.0 \u0026plusmn; 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eTHI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e81.8 \u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e66.1 \u0026plusmn; 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 Physiological and Productive Parameters of Lambs Exposed to Thermoneutral Versus Chronic Heat Stress Conditions\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl Group (Semirom)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeat Stress Group (Afzar)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eRectal Temperature (\u0026deg;C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e39.1 \u0026plusmn; 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e40.3 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eRespiratory Rate (breaths/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e48 \u0026plusmn; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e77 \u0026plusmn; 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eHeart Rate (beats/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e96 \u0026plusmn; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e122 \u0026plusmn; 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eFeed Intake (kg/day)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e1.10 \u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0.94 \u0026plusmn; 0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eAverage Daily Gain (g/day)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e187 \u0026plusmn; 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e165 \u0026plusmn; 13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5 Effect of Chronic Heat Exposure on the Expression of Pro-Inflammatory Cytokines and PPAR\u0026gamma; in Liver and Muscle Tissues of Lambs\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTissue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeat Stress (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eIL-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e14.10 \u0026plusmn; 0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e17.23 \u0026plusmn; 0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eIL-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e16.21 \u0026plusmn; 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e17.39 \u0026plusmn; 0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eTNF-\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e17.10 \u0026plusmn; 0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e15.21 \u0026plusmn; 0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eTNF-\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e16.41 \u0026plusmn; 0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e19.95 \u0026plusmn; 0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003ePPARɤ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e20.18 \u0026plusmn; 0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e15.81 \u0026plusmn; 0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003ePPARɤ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e21.21 \u0026plusmn; 0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e16.67 \u0026plusmn; 0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6 Differential Expression of Oxidative Stress-Responsive Genes (SOD1 and FOXO3) in Liver and Muscle Tissues Following Chronic Heat Exposure\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTissue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeat Stress (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eSOD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e28.01 \u0026plusmn; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e25.19 \u0026plusmn; 0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eSOD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e20.32 \u0026plusmn; 0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e20.67 \u0026plusmn; 0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eFOXO3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e21.62 \u0026plusmn; 0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e23.60 \u0026plusmn; 0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eFOXO3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e21.52 \u0026plusmn; 0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e21.74 \u0026plusmn; 0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.422\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7 Heat-Induced Changes in Expression of Heat Shock Proteins and Apoptosis-Related Gene CASP3 in Liver and Muscle Tissues\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTissue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeat Stress (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eHSP70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e15.61 \u0026plusmn; 0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e26.06 \u0026plusmn; 0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eHSP70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e18.04 \u0026plusmn; 0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e22.79 \u0026plusmn; 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eHSP90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e17.90 \u0026plusmn; 0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e12.51 \u0026plusmn; 0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eHSP90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e16.57 \u0026plusmn; 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e19.23 \u0026plusmn; 0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eCASP3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e16.87 \u0026plusmn; 0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e19.61 \u0026plusmn; 0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eCASP3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e17.27 \u0026plusmn; 0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e21.17 \u0026plusmn; 0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8 Differential Expression of Muscle Differentiation and Structural Genes (MYOD and ACTB3) in Skeletal Muscle of Heat-Stressed Lambs\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTissue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeat Stress (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eMYOD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e22.73 \u0026plusmn; 0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e20.11 \u0026plusmn; 0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eACTB3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e20.35 \u0026plusmn; 0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e20.84 \u0026plusmn; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9 Differential Expression of Inflammatory, Oxidative Stress, Heat Shock, and Apoptotic Genes in Liver and Muscle Tissues of Heat-Stressed Lambs\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMain Biological Role\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLiver Response to Heat Stress\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMuscle Response to Heat Stress\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eComparative Tissue Response\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIL-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePro-inflammatory cytokine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026uarr; Significant (+22.2%) (P \u0026lt; 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026uarr; Moderate, NS (+7.2%) (P = 0.062)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLiver shows stronger upregulation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTNF-\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePro-inflammatory cytokine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026darr; Significant (\u0026ndash;11.0%) (P = 0.012)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026uarr; Significant (+21.6%) (P \u0026lt; 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOpposing: liver downregulated, muscle upregulated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePPARɤ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNuclear receptor, anti-inflammatory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026darr; Significant (\u0026ndash;21.7%) (P = 0.027)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026darr; Significant (\u0026ndash;21.4%) (P = 0.011)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBoth tissues show similar downregulation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSOD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAntioxidant enzyme (superoxide detox)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026darr; Significant (\u0026ndash;10.1%) (P \u0026lt; 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo significant change (P = 0.351)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLiver response \u0026gt; Muscle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFOXO3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTranscription factor for redox defense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026uarr; Significant (+9.3%) (P \u0026lt; 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSlight increase, NS (P = 0.422)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLiver response \u0026gt; Muscle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHSP70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHeat shock protein (protein chaperone)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026uarr; Significant (+66.9%) (P \u0026lt; 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026uarr; Strong (+26.4%) (P \u0026lt; 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMuscle response \u0026gt; Liver\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHSP90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHeat shock protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026darr; Significant (\u0026ndash;30.1%) (P \u0026lt; 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026uarr; Significant (+16.1%) (P \u0026lt; 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDivergent: liver down, muscle upregulated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCASP3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExecutioner of apoptosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026uarr; Mild (+16.3%) (P = 0.021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026uarr; Significant (+22.6%) (P \u0026lt; 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMuscle response \u0026gt; Liver\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 10 Spearman Correlation Coefficients Among Stress, Inflammatory, and Antioxidant Gene Expression in Liver and Muscle Tissues Under Normal and Heat Stress Conditions\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenes Compared\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal Condition\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(r, P-value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeat Stress Condition\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(r, P-value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eHSP70 \u0026ndash; HSP90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026ndash;0.65, 0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026ndash;0.62, 0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eNegative correlation under both\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eHSP70 \u0026ndash; SOD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026ndash;0.60, 0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e0.12, 0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eNegative at baseline, lost in heat stress\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eHSP70 \u0026ndash; IL-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e0.62, 0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026ndash;0.03, 0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003ePositive baseline, lost under heat\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eHSP70 \u0026ndash; TNF-\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026ndash;0.43, 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026ndash;0.74, 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eStrengthened negative correlation in heat\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eHSP70 \u0026ndash; FOXO3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e0.56, 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e0.49, 0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003ePositive trend, weaker under heat\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eHSP90 \u0026ndash; SOD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026ndash;0.06, 0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026ndash;0.76, 0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eStrong negative correlation under heat\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eIL-6 \u0026ndash; TNF-\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026ndash;0.58, 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026ndash;0.12, 0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eNegative trend lost under heat\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eTNF-\u0026alpha; \u0026ndash; FOXO3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026ndash;0.69, 0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026ndash;0.78, 0.0045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eStrong negative correlation in both\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"heat stress, lamb, gene expression, liver, skeletal muscle, oxidative stress","lastPublishedDoi":"10.21203/rs.3.rs-8754267/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8754267/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate-induced heat stress poses a major challenge to small ruminant productivity in arid and semi-arid regions, affecting growth, metabolism, and immune function. This study examined tissue-specific molecular responses to chronic heat stress in lambs by evaluating the expression of key genes associated with inflammation, oxidative stress, proteostasis, and muscle function in the liver and skeletal muscle. Twenty-four lambs were reared under either thermoneutral or heat-stressed field conditions for 42 days. In the liver, chronic heat exposure led to the upregulation of antioxidant genes (SOD1, FOXO3) and pro-inflammatory IL-6, while TNF-α and PPARγ were significantly downregulated. In muscle, a different profile emerged: heat shock proteins (HSP70, HSP90) and the apoptotic marker CASP3 were strongly upregulated, MYOD was suppressed, and ACTB3 remained stable. These results suggest impaired muscle regeneration, enhanced proteotoxic stress, and tissue-specific shifts in redox and inflammatory balance. Composite gene expression ratios\u0026mdash;such as SOD1/IL-6 and FOXO3/TNF-α\u0026mdash;were elevated under heat stress and negatively correlated with rectal temperature, indicating a potential role as molecular indicators of thermotolerance. Principal component analysis further distinguished control and heat-stressed animals based on transcriptional profiles. These findings highlight the coordinated yet divergent molecular strategies employed by liver and muscle tissues under prolonged thermal stress. The study provides foundational insight into gene-level responses associated with heat resilience and offers molecular targets for future selection or intervention strategies in climate-adapted sheep production.\u003c/p\u003e","manuscriptTitle":"Effect of Chronic Heat Stress on the Expression of Inflammatory and Oxidative Stress-Related Genes in Liver and Muscle Tissues of Lambs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 14:12:51","doi":"10.21203/rs.3.rs-8754267/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-02-04T20:58:49+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-04T18:37:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-03T05:38:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Animal Health and Production","date":"2026-02-01T02:04:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c13a491c-d319-4e10-88be-cbee077c4e67","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T18:37:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 14:12:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8754267","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8754267","identity":"rs-8754267","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}