Evaluating the Cytokine-Modulating Anti-inflammatory Effects of Ayurvedic Treatments on Non-Communicable Diseases: A Prospective Observational Study

Evaluating the Cytokine-Modulating Anti-inflammatory Effects of Ayurvedic Treatments on Non-Communicable Diseases: A Prospective Observational Study | 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 Evaluating the Cytokine-Modulating Anti-inflammatory Effects of Ayurvedic Treatments on Non-Communicable Diseases: A Prospective Observational Study Prathiban Rengarajan, Ramkumar Kunka Mohanram, Satish Kumar, Bala Pesala This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8052543/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives Chronic inflammation drives non-communicable diseases (NCDs) like diabetes, GERD, hypertension, and osteoarthritis. Ayurveda, an ancient system of medicine, emphasizes personalized treatments to restore balance and modulate immunity; however, its effects on cytokine profiles remain incompletely characterized. This study evaluated the impact of Ayurvedic interventions on pro-inflammatory cytokines (IFN-γ, IL-6, IL-17, TNF-α) and anti-inflammatory cytokines (IL-4, IL-10) in patients with non-communicable diseases (NCDs). Methods This prospective observational study included 60 patients receiving Ayurvedic treatment for various NCDs. Cytokine levels were measured pre- and post-treatment using multiplex bead-based assays. Statistical analyses included paired-sample t-tests, Wilcoxon signed-rank tests, effect size determinations, and permutation tests to assess changes in cytokine levels and ratios. Results Ayurvedic treatment was associated with significant reductions in pro-inflammatory cytokines, particularly in patients with diabetes and GERD. Anti-inflammatory cytokines increased in select subgroups, indicating a shift towards reduced inflammation. Pro-inflammatory to anti-inflammatory cytokine ratios decreased significantly, reflecting restored immune balance. Large effect sizes were observed for pro-inflammatory cytokine reductions, while anti-inflammatory cytokines showed moderate-to-small effect sizes. Permutation tests validated these findings, especially for diabetes and GERD. Conclusion Personalized Ayurvedic treatments demonstrate immunomodulatory potential by reducing pro-inflammatory cytokines and enhancing anti-inflammatory cytokines, thereby restoring immune balance in patients with NCDs. These findings support integrating Ayurveda into modern clinical practices for managing inflammatory conditions. However, larger, controlled trials are needed to validate results and explore mechanisms. Integrative & Complementary Medicine Immunomodulation Non-communicable diseases Inflammation Cytokines Ayurvedic medicine Figures Figure 1 Figure 2 Figure 3 1. Introduction Ayurveda, an ancient medical system with well-documented origins, emphasizes health preservation and disease prevention. When diseases arise, Ayurveda provides a detailed description of their prodromal signs, manifested symptoms, and possible complications. Despite technological advancements, Ayurvedic practitioners still mainly rely on subjective symptoms for diagnosis. Disease is a complex phenomenon involving multiple biomolecules and pathways that contribute to its initiation and progression. Measuring these biomolecules is essential for diagnosis, treatment evaluation, and disease monitoring. Cytokines, which are small proteins or glycoproteins, act as chemical messengers for intercellular communication and are mainly produced by leukocytes and other cells to modulate the immune response [ 1 ]. Their levels are modulated by numerous factors, reflecting the complexity of cytokine regulation [ 2 ]. Chronic non-communicable diseases are marked by systemic inflammation, a protective immune response regulated by the innate immune system against harmful stimuli such as pathogens, damaged cells, or irritants. Insufficient inflammation can result in persistent infections, whereas excessive inflammation may lead to chronic or systemic inflammatory disorders [ 3 ]. Inflammageing, a condition common among the elderly, is characterized by increased pro-inflammatory markers in the bloodstream and is closely associated with a higher risk of chronic diseases, physical disability, frailty, and premature mortality [ 4 ]. Research highlights the roles of cytokines like IL-6 and IL-10 in the low-grade inflammation often found in metabolic diseases such as diabetes and hypertension. Systemic chronic inflammation (SCI) is characterized by elevated pro-inflammatory cytokines, which worsen disease progression and complications. In type 2 diabetes mellitus (T2DM), an imbalance between pro- and anti-inflammatory cytokines regulates the inflammatory response [ 5 ]. Individuals with T2DM exhibit increased IFN-γ and reduced IL-10 levels [ 6 ], with genetic polymorphisms in the IL-10 gene linked to higher diabetes risk. IFN-γ, a key pro-inflammatory cytokine, significantly contributes to T2DM development [ 7 – 9 ]. Similarly, cytokines have been implicated in the pathogenesis of other conditions, including Gastroesophageal Reflux Disease [ 10 ] [ 11 ], Osteoarthritis [ 12 ] [ 13 ], and Hypertension [ 14 ]. Ayurveda seeks to protect and improve well-being by defining good health, recognizing variations in health states, and providing methods to maintain balance. It addresses the causes, progression, symptoms, and treatments of diseases, with focus on both health preservation and disease management. Beyond medicinal interventions, Ayurveda emphasizes nutrition, lifestyle, environmental factors, and daily routines as integral to health maintenance and disease management. Ayurvedic therapeutic formulations typically combine herbal, mineral, and metal ingredients, containing synergistic compounds that act on multiple bodily systems. Network pharmacology studies have revealed the molecular mechanisms of these formulations, such as immunomodulation by Withania somnifera [ 15 ], molecular targets of Triphala in cancer treatment [ 16 ], and the regulation of key genes in CKD and CVD pathways by Chandanasava [ 17 ]. These findings highlight the multi-targeted efficacy of Ayurvedic drugs. In Ayurveda, Prakriti refers to an individual’s unique constitutional phenotype, determined by observable physical characteristics that allow for classification into distinct categories. Personalized treatments in Ayurveda are tailored to an individual's Prakriti (unique phenotype) along with other relevant factors. Recent research has highlighted significant differences across Prakriti groups in areas such as gene expression, biochemical markers [ 18 ], gut microbiome [ 19 ], genetic variations [ 20 ], DNA methylation [ 21 ], and physiological responses to head-up-tilt [ 22 ]. Traditionally, Ayurveda practitioners evaluate treatment efficacy by monitoring symptom improvement, severity reduction, and disease-specific biochemical markers. However, the role of inflammatory markers, such as cytokines, is often neglected in clinical practice. This study aims to bridge this gap by evaluating the impact of Ayurvedic treatment protocols on cytokine profiles. 2. Materials and Methods 2.1. Methods This prospective observational study was conducted at the Interdisciplinary Institute of Indian System of Medicine (IIISM), SRM Institute of Science and Technology, Kattankulathur, Chennai, India. The study complies with all applicable national regulations and institutional policies and was conducted in accordance with the principles of the Helsinki Declaration. Ethical approval was obtained from the institution’s ethics committee, and the study was registered with the Clinical Trials Registry of India (CTRI/2021/12/038909). Participants were recruited from the IIISM Outpatient Department at SRM Hospital after being fully informed about the study. Informed consent was obtained from all participants. Data were collected and analyzed over 16 months, from December 2021 to March 2023, to assess the effectiveness of prescribed Ayurvedic therapies. 2.2. Participants Participants were adults aged 20–80 years (both sexes) seeking Ayurvedic treatment at the outpatient department. Exclusion criteria included patients below 20 years and pregnant or lactating women. Upon enrolment, Ayurvedic physicians diagnosed participants, recorded symptoms, assigned severity scores, and prescribed personalized treatments tailored to each patient’s condition. Treatments consisted of Ayurvedic formulations (tablets, capsules, and syrups) administered two or three times daily for one month, with dosage and timing customized for optimal outcomes. Specific medication details for various diseases are listed in Supplemental Table 1; demographic and disease-related details are provided in Supplemental Tables 2 and 3. Participants were reassessed during follow-up visits to evaluate therapeutic effectiveness, with medications continued for a total treatment duration of three months. Initial screening rigorously excluded individuals using allopathic or over-the-counter (OTC) medications to ensure that results were attributable solely to Ayurvedic treatment. Adherence to the protocol was ensured through regular monitoring, self-reported logs, and patient education. Follow-up visits were scheduled intermittently to track progress and address any deviations. Sixty participants were included to assess the impact of Ayurveda treatment on cytokine markers, measuring both pro-inflammatory (IFN-γ, IL-6, IL-17, TNF-α, IL-1) and anti-inflammatory (IL-4, IL-10) cytokines. The progression of participants through the trial phases is illustrated in the STROBE flow diagram (Fig. 1 ). As there were no prior studies on Ayurveda’s effects on cytokine levels, effect size estimates could not be derived from existing literature. To evaluate statistical robustness, a power analysis was conducted using G*Power for Student’s t-tests, comparing pre- and post-intervention outcomes. With a sample size of 60, an effect size (dz) of 0.9, and a balanced Type I and Type II error minimization ratio of 1, the analysis yielded a non-centrality parameter of 6.9713700 and a critical t-value of 3.5980410. The test demonstrated a power of 99.93%, with a 0.065% probability of Type II and Type I errors. These findings emphasize the study’s robust design and high sensitivity in detecting significant differences. Flow diagram illustrating the screening, enrolment, follow-up, sub-group analysis, and final inclusion of patients in the study. 2.3. Pro-inflammatory & Anti-inflammatory cytokine profiling The collected blood samples were transferred to vacutainers and centrifuged at 800 g for 30 minutes to separate plasma. Cytokine levels (IFN-γ, IL-6, IL-17, TNF-α, IL-1, IL-4, and IL-10) were measured using the Bio-Plex Pro™ Human Inflammation Panel, a multiplex bead-based assay system (Bio-Rad). Briefly, 50 µl of plasma was added to a 96-well plate, and the assay was performed in duplicate per the manufacturer’s protocol, with automated washing using a Bio-Plex Pro™ wash station. Cytometric analysis was conducted using a Luminex xMAP analyzer (Luminex 100 Milliplex), and data were analyzed using Bio-Plex Manager™ 6.1 software. Cytokine concentrations were derived from standard curves and reported in picograms per milliliter (pg/mL). 2.4. Statistical analysis The normality of the data was assessed using the Shapiro-Wilk test. Normally distributed data were presented as mean ± standard deviation and analyzed using paired-samples t-tests, while non-normally distributed data were expressed as median (interquartile range) and evaluated using Wilcoxon signed-rank tests. To quantify the magnitude of changes in cytokine levels, effect sizes were calculated: Cohen’s d for normally distributed data and rank biserial correlation for nonparametric data, ensuring robust and standardized measures of practical significance. Analyses were conducted using JASP (version 0.18.1); p < 0.05 was considered statistically significant. Additionally, permutation tests with 1,000 iterations were conducted in Python to evaluate changes in cytokine ratios, providing a non-parametric, assumption-free method to complement traditional tests. The observed differences between pre- and post-treatment ratios were compared against a null distribution generated by random shuffling, with statistical significance set at p < 0.01. This approach enhanced the reliability and validity of the findings by addressing potential limitations of parametric tests and offering a flexible, distribution-independent alternative for hypothesis testing. 3. Results 3.1. Effect of Ayurveda treatment on cytokine levels Analysis revealed significant reductions in pro-inflammatory cytokines post-treatment, with IFN-γ, IL-6, IL-17, and TNF-α showing marked decreases (all p < 0.001, large effect sizes). IL-4 and IL-10 levels increased significantly (p < 0.001 and p = 0.044, respectively), showing moderate and small-to-moderate effect sizes. Conversely, IL-1 levels showed no significant change (p = 0.971), suggesting minimal treatment effect (see Table 1 ). Permutation analysis confirmed significant reductions in pro-inflammatory cytokines (IFN-γ, IL-6, TNF-α, IL-17) and minimal changes in IL-1 (p = 0.986). Changes in anti-inflammatory cytokines (IL-4 and IL-10) were less robust and varied between subgroups. Overall, these findings suggest immunomodulatory effects of the intervention, as inflammation was alleviated primarily through modulation of key pro-inflammatory cytokines, while effects on IL-1 and anti-inflammatory pathways were more limited and complex. Table 1 Cytokine levels before & after Ayurveda treatment in overall diseases Cytokines Before treatment After treatment Paired Samples t – Test Cohen’s d 95% CI for Cohen’s d Mean ± (SD) Mean ± (SD) t value p value Lower Upper IFN- γ 7.16 ± 3.37 5.15 ± 2.94 8.867 < 0.001 1.145 0.815 1.468 IL-6 8.66 ± 3.73 6.47 ± 3.25 8.961 < 0.001 1.157 0.826 1.482 IL-17 6.74 ± 3.48 5.45 ± 3.34 7.384 < 0.001 0.953 0.645 1.256 TNF- α 7.38 ± 3.73 5.15 ± 2.89 8.316 < 0.001 1.074 0.752 1.389 IL-1 5.68 ± 3.19 5.67 ± 2.77 0.036 0.971 0.005 -0.248 0.258 IL-4 5.65 ± 2.49 6.29 ± 2.47 -4.296 < 0.001 -0.555 -0.825 -0.281 IL-10 5.36 ± 2.55 5.81 ± 2.58 -2.058 0.044 -0.266 -0.522 -0.007 Values are presented as mean ± SD. Cytokine levels before and after treatment were compared using a paired samples t-test, with a sample size of n = 60. 3.2. Effect of Ayurveda treatment on cytokine levels in diabetes mellitus In the next phase of statistical analysis, the patient cohort was categorized into subgroups based on their specific diseases to evaluate the effect of Ayurveda treatment on cytokine levels within each subgroup. In the diabetes mellitus subgroup (n = 16), significant reductions were observed in pro-inflammatory cytokines following Ayurveda treatment. Specifically, IFN-γ decreased from 9.26 ± 3.67 pg/mL to 6.75 ± 3.45 pg/mL (p < 0.001, Cohen’s d = 1.169), IL-6 dropped from 10.43 ± 3.82 pg/mL to 7.55 ± 3.28 pg/mL (p < 0.001, d = 1.475), IL-17 declined from 9.32 ± 3.70 pg/mL to 7.76 ± 3.64 pg/mL (p < 0.001, d = 1.162), and TNF-α reduced from 10.32 ± 3.06 pg/mL to 7.05 ± 2.86 pg/mL (p < 0.001, d = 1.279); all changes were associated with large effect sizes. Among anti-inflammatory cytokines, IL-4 increased slightly but significantly (7.87 ± 2.34 pg/mL to 8.61 ± 2.51 pg/mL, p = 0.044, d = -0.549), while IL-1 and IL-10 showed no significant changes (p = 0.493 and p = 0.806, respectively; (see Table 2 and Fig. 2 (a - e)). Permutation analysis confirmed significant reductions in IFN-γ (p = 0.054), IL-6 (p < 0.025), and TNF-α (p = 0.0001) but not in IL-17, IL-1, IL-10, or IL-4. Additionally, IL-6 and TNF-α levels showed further significant reductions by the 3rd month of treatment, emphasizing the importance of treatment duration for optimal anti-inflammatory effects (Fig. 3 ). These results highlight the efficacy of Ayurveda treatment in modulating pro-inflammatory cytokines while having limited impact on certain anti-inflammatory cytokines like IL-1 and IL-10. Table 2 Cytokine levels in diabetes patients’ group before & after Ayurveda treatment Cytokines Before treatment After treatment Paired Samples t – Test Cohen’s d 95% CI for Cohen’s d Mean ± (SD) Mean ± (SD) t value p value Lower Upper IFN- γ 9.26 ± 3.67 6.75 ± 3.45 4.677 < 0.001 1.169 0.516 1.800 IL-6 10.43 ± 3.82 7.55 ± 3.28 5.902 < 0.001 1.475 0.747 2.181 IL-17 9.32 ± 3.70 7.76 ± 3.64 4.649 < 0.001 1.162 0.511 1.791 TNF- α 10.32 ± 3.06 7.05 ± 2.86 5.117 < 0.001 1.279 0.600 1.936 IL-1 8.12 ± 3.31 7.79 ± 3.22 0.702 0.493 0.175 -0.321 0.667 IL-4 7.87 ± 2.34 8.61 ± 2.51 -2.195 0.044 -0.549 -1.068 -0.014 IL-10 6.76 ± 2.54 6.60 ± 3.31 0.250 0.806 0.062 -0.429 0.552 Values are presented as mean ± SD. Cytokine levels before and after treatment were compared using a paired samples t-test, with a sample size of n = 16. 3.3. Effect of Ayurveda treatment on cytokine levels in GERD Seventeen GERD patients were analyzed, and Ayurveda treatment was associated with significant reductions in pro-inflammatory cytokines and increases in anti-inflammatory cytokines (see Table 6). Paired samples t-tests and Cohen’s d analyses showed: IFN-γ declined from 5.26 ± 2.50 pg/mL to 3.55 ± 1.21 pg/mL (t(16) = 4.476, p < 0.001, d = 1.086), IL-6 from 7.06 ± 3.10 pg/mL to 5.55 ± 3.04 pg/mL (t(16) = 3.014, p = 0.008, d = 0.731), IL-17 from 5.12 ± 2.45 pg/mL to 4.01 ± 2.10 pg/mL (t(16) = 3.300, p = 0.005, d = 0.800), and TNF-α from 5.30 ± 2.71 pg/mL to 3.71 ± 1.51 pg/mL (t(16) = 3.990, p = 0.001, d = 0.968). Anti-inflammatory cytokines also increased significantly: IL-4 rose from 4.47 ± 2.11 pg/mL to 5.28 ± 1.86 pg/mL (t(16) = -2.966, p = 0.009, d = -0.719); IL-10 from 4.64 ± 1.97 pg/mL to 5.48 ± 1.98 pg/mL (t(16) = -3.185, p = 0.006, d = -0.773), with large to moderate effect sizes. IL-1 levels showed no significant change (4.33 ± 2.69 pg/mL vs. 4.33 ± 1.86 pg/mL, t(16) = 0.002, p = 0.988, d = 0.004; see Table 3 ). Permutation tests further supported these findings, with significant reductions in IFN-γ (p = 0.009, difference: 1.96), IL-6 (p = 0.039, difference: 2.16), and TNF-α (p = 0.034, difference: 1.69), while IL-17, IL-4, IL-10, and IL-1 showed no significant changes (p > 0.05). These results highlight the treatment’s efficacy in modulating pro-inflammatory cytokines and enhancing anti-inflammatory responses, underscoring its selective impact on immune regulation in GERD. The results for other diseases are presented in supplemental material. Table 3 Cytokine levels in GERD patients’ group before & after Ayurveda treatment Cytokines Before treatment After treatment Paired Samples t – Test Cohen’s d 95% CI for Cohen’s d Mean ± (SD) Mean ± (SD) t value p value Lower Upper IFN- γ 5.26 ± 2.50 3.55 ± 1.21 4.476 < 0.001 1.086 0.471 1.679 IL-6 7.06 ± 3.10 5.55 ± 3.04 3.014 0.008 0.731 0.184 1.260 IL-17 5.12 ± 2.45 4.01 ± 2.10 3.300 0.005 0.800 0.242 1.340 TNF- α 5.30 ± 2.71 3.71 ± 1.51 3.990 0.001 0.968 0.378 1.538 IL-1 4.33 ± 2.69 4.33 ± 1.86 0.002 0.988 0.004 -0.475 0.76 IL-4 4.47 ± 2.11 5.28 ± 1.86 -2.966 0.009 -0.719 -1.246 -0.175 IL-10 4.64 ± 1.97 5.48 ± 1.98 -3.185 0.006 -0.773 -1.308 -0.219 Values are presented as mean ± SD. Cytokine levels before and after treatment were compared using a paired samples t-test, with a sample size of n = 17, GERD – Gastroesophageal reflux disease. 3.7. Effect of Ayurveda treatment on cytokine ratio levels in overall diseases The ratio of pro-inflammatory to anti-inflammatory cytokines serves as a key marker of treatment efficacy, indicating a shift in immune balance. After Ayurveda treatment, significant reductions in these ratios were observed across all disease groups (see Table 10). Paired samples t-tests revealed substantial decreases: IFN-γ/IL-4 dropped from 1.32 ± 0.48 to 0.80 ± 0.29 (t(59) = 8.438, p < 0.001, d = 1.099); IFN-γ/IL-10 fell from 1.35 ± 0.51 to 0.90 ± 0.44 (t(59) = 6.210, p < 0.001, d = 0.837); IL-6/IL-4 declined from 1.69 ± 0.88 to 1.08 ± 0.56 (t(59) = 6.900, p < 0.001, d = 0.891); IL-6/IL-10 reduced from 1.83 ± 0.91 to 1.22 ± 0.69 (t(59) = 7.391, p < 0.001, d = 0.962), and similar significant reductions were observed for IL-17/IL-4, IL-17/IL-10, TNF-α/IL-4, and TNF-α/IL-10 ratios with large to moderate effect sizes (see Table 4 ). Permutation tests confirmed these findings, with all ratios showing highly significant p-values (p < 0.001) and substantial observed differences, underscoring a favourable shift toward an anti-inflammatory state. These results highlight the treatment’s ability to effectively modulate cytokine balance, reducing inflammation across diverse conditions. Table 4 Cytokine ratio before & after Ayurveda treatment in overall diseases Cytokines Before treatment After treatment Paired Samples t – Test Cohen’s d 95% CI for Cohen’s d Mean ± (SD) Mean ± (SD) t value p value Lower Upper IFN-γ/IL-4 1.32 ± 0.48 0.80 ± 0.29 8.438 < 0.001 1.099 0.772 1.419 IFN-γ /IL-10 1.35 ± 0.51 0.90 ± 0.44 6.210 < 0.001 0.837 0.527 1.142 IL-6/IL-4 1.69 ± 0.88 1.08 ± 0.56 6.900 < 0.001 0.891 0.588 1.188 IL-6/IL-10 1.83 ± 0.91 1.22 ± 0.69 7.391 < 0.001 0.962 0.650 1.269 IL-17/IL-4 1.25 ± 0.48 0.84 ± 0.32 7.170 < 0.001 0.926 0.620 1.226 IL-17/IL-10 1.35 ± 0.54 0.94 ± 0.44 5.958 < 0.001 0.776 0.482 1.065 TNF-α/IL-4 1.39 ± 0.62 0.81 ± 0.31 7.727 < 0.001 0.998 0.684 1.305 TNF-α/IL-10 1.57 ± 0.64 0.92 ± 0.48 5.311 < 0.001 0.691 0.405 0.973 Values are expressed in mean ± SD, cytokine levels before and after treatment were compared using paired samples t – test, and n = 60 4. Discussion This study investigated the effects of Ayurveda treatment on pro-inflammatory and anti-inflammatory cytokine levels, revealing significant post-treatment changes. Pro-inflammatory cytokines, including IFN-γ, IL-6, IL-17, and TNF-α, showed marked reductions across various diseases, while anti-inflammatory cytokines IL-4 and IL-10 increased significantly. Notably, diabetes patients exhibited higher baseline inflammatory markers, consistent with the role of systemic inflammation in diabetes-related complications. The treatment's impact varied by condition: diabetes patients experienced significant reductions in all four pro-inflammatory cytokines, GERD patients showed notable declines, HTN patients demonstrated reductions in IFN-γ and IL-6. These findings underscore the disease-specific variability in Ayurveda's anti-inflammatory effects, highlighting its potential to modulate cytokine levels and restore immune balance. Our analysis revealed an overall increase in anti-inflammatory cytokines IL-4 and IL-10 following Ayurveda treatment, though responses varied by disease. In diabetes patients, only IL-4 levels increased significantly, while GERD patients showed elevated levels of both IL-4 and IL-10. These findings underscore the disease-specific variability in Ayurveda's effects on anti-inflammatory cytokines. Pro-inflammatory and anti-inflammatory cytokines play critical roles in immune regulation, with their balance essential for maintaining immune homeostasis through complex feedback mechanisms [ 23 ]. To assess Ayurveda's impact on this equilibrium, we calculated pro- to anti-inflammatory cytokine ratios, which decreased across all diseases post-treatment. This reduction suggests a rebalancing effect, potentially restoring immune system stability and highlighting Ayurveda's immunomodulatory potential. The effect sizes observed for cytokine levels before and after Ayurveda treatment provide valuable insights into its impact. Paired samples t-tests revealed large effect sizes for pro-inflammatory cytokines, including IFN-γ (Cohen’s d = 1.145), IL-6 (d = 1.157), IL-17 (d = 0.953), and TNF-α (d = 1.074), indicating substantial reductions and a strong biological response to the treatment. In contrast, negligible effects were seen for IL-1 (d = 0.005), suggesting it was largely unaffected. Moderate effect sizes for anti-inflammatory cytokines like IL-4 (d = -0.555) and IL-10 (d = -0.266) indicate a significant but less pronounced shift toward reduced inflammation. Similarly, Wilcoxon signed-rank tests showed perfect Rank-Biserial Correlations (r = 1.000) for IFN-γ, IL-6, IL-17, and TNF-α, reinforcing the robust treatment effects on pro-inflammatory markers. Conversely, negligible correlations for IL-1 (r = -0.429), IL-4 (r = -0.333), and IL-10 (r = -0.333) suggest minimal changes in these cytokines. Collectively, these findings highlight Ayurveda’s targeted efficacy in reducing pro-inflammatory cytokines while having limited impact on certain anti-inflammatory markers, underscoring its potential in managing inflammatory conditions by modulating key pathways. Permutation test results across multiple datasets reveal heterogeneous effects of Ayurveda treatment on cytokine modulation in various diseases. Significant reductions were observed in key pro-inflammatory cytokines, such as IFN-γ (p = 0.002), IL-6 (p = 0.001), and TNF-α (p = 0.000), highlighting the treatment's efficacy in reducing inflammation. In diabetic patients, robust decreases were noted in IFN-γ (p = 0.054), IL-6 (p = 0.025), and TNF-α (p = 0.001). Similarly, GERD patients showed significant declines in IFN-γ (p = 0.009), IL-6 (p = 0.039), and a trend for TNF-α (p = 0.034). Anti-inflammatory cytokines like IL-4, IL-10, and IL-1 generally showed minimal changes, with consistently high p-values (e.g., IL-10: p = 0.88 in DM), suggesting resistance to modulation. These findings underscore the treatment’s selective efficacy in modulating pro-inflammatory cytokines while having limited effects on anti-inflammatory markers. The analysis of cytokine ratios revealed highly significant decreases in pro-inflammatory-to-anti-inflammatory ratios (all p = 0.0), reflecting a systemic shift toward an anti-inflammatory state. Notably, the IFN-γ/IL-4 ratio showed an observed decrease of − 0.519 (pre: 1.44 ± 0.75; post: 0.84 ± 0.37), and the IL-6/IL-10 ratio decreased by − 0.614 (pre: 1.83 ± 0.91; post: 1.22 ± 0.69), indicating reduced pro-inflammatory signalling. These findings underscore the need for personalized approaches to effectively modulate immune responses and call for further investigation into the mechanisms driving these differences. Previous studies on Ayurveda treatment in asthma patients have examined cytokine levels, including TNF-α, IL-4, IL-6, IL-10, and others, before and after treatment. These studies reported reductions in pro-inflammatory cytokines like IFN-γ, IL-6, TNF-α, and IL-4, alongside an increase in the anti-inflammatory cytokine IL-10. Similarly, our study observed decreases in IFN-γ, IL-6, and TNF-α, as well as an increase in IL-10 post-treatment. However, unlike the study by Joshi et al., which noted a reduction in IL-4, our findings showed an increase in IL-4 levels after treatment. These differences may arise from disease-specific inflammatory pathways and variations in treatment protocols [ 24 ]. A study on the Ayurvedic herb Ashwagandha ( Withania somnifera ) in healthy individuals found increased levels of IFN-γ and IL-4 after 30 days of treatment, in contrast to our findings of reduced IFN-γ. While the rise in IL-4 aligns with our findings, the discrepancy in IFN-γ may be due to the inclusion of only healthy participants in that study, as our observed decrease in IFN-γ could reflect disease-specific responses [ 25 ]. Similarly, a study on Andrographis paniculata reported increases in IFN-γ and IL-4, along with a reduction in IL-2, following 30 days of administration. Although the increase in IL-4 is consistent with our results, the rise in IFN-γ differs from our findings [ 26 ]. These variations likely stem from differences in disease contexts and the tailored nature of Ayurvedic treatments for specific conditions. Although this study offers promising insights into the effects of Ayurveda treatment on cytokine levels, several limitations must be acknowledged. The small sample size for each disease subgroup may limit statistical power and generalizability, highlighting the need for larger, more diverse cohorts to strengthen the robustness of the findings and enable nuanced subgroup analyses. Additionally, the lack of a control group (e.g., placebo or standard care) precludes definitive attribution of observed changes to Ayurvedic treatment, as confounding factors like disease progression or placebo effects cannot be ruled out. Including a control group in future studies would enhance validity. The short follow-up period also restricts understanding of the long-term effects of Ayurveda treatment, particularly for chronic conditions where extended observation is necessary to assess sustainability and clinical relevance. To address these gaps, future research should prioritize larger, well-controlled studies with longer follow-up durations to validate findings and explore underlying mechanisms. Investigating disease-specific responses and individual variability could further optimize Ayurvedic interventions. Overcoming these limitations will be crucial for advancing the evidence base of Ayurveda's role in managing inflammatory conditions and integrating it into evidence-based practice. 5. Conclusion In conclusion, this study suggests that Ayurvedic treatment may modulate cytokine profiles by reducing pro-inflammatory cytokines and enhancing anti-inflammatory cytokines. This dual action highlights its potential to attenuate inflammatory responses across various diseases, restoring the balance critical for immune homeostasis. The observed decrease in pro- to anti-inflammatory cytokine ratios further supports its potential immunomodulatory role. These findings suggest Ayurveda's promise as a personalized therapeutic approach for inflammation-related conditions. However, further research is needed to elucidate underlying mechanisms, refine treatment protocols, and validate these results through larger, controlled trials. Such efforts will strengthen the evidence base for integrating Ayurveda into evidence-based medicine, particularly for managing immune dysregulation and chronic inflammation. Declarations Acknowledgements: The authors acknowledge the financial support of Technology Innovation Hub (TIH-IOT), IIT Bombay, India for this clinical study. Research Funding: This study was funded by the Technology Innovation Hub (TIH-IOT), IIT Bombay, India Author contributions: Prathiban Rengarajan (PR) : Conceptualization, Methodology, Writing- Original draft preparation, Data Curation, Formal analysis. Ramkumar Kunka Mohanram (RM) : Conceptualization, Methodology, Supervision, Investigation, Resources, Writing - Review & Editing. Satish Kumar Rajappan Chandra (SK) : Supervision, Investigation, Resources, Project administration. Bala Pesala (BP) : Conceptualization, Methodology, Supervision, Investigation, Funding acquisition, Writing - Review & Editing. All the authors have accepted responsibility for the entire content of this manuscript and approved submission. Competing interest: The authors declare that they have no competing financial or personal interests that could have appeared to influence the work reported in this paper. Informed consent: Informed consent was obtained from all individuals included in this study. Ethical approval: The study received approval from the institutional ethics committee and was registered with the Clinical Trials Registry of India (CTRI) under the registration number CTRI/2021/12/038909 References Zhang J-M, An J, Cytokines (2007) Inflammation and Pain. Int Anesthesiol Clin 45:27–37. https://doi.org/10.1097/AIA.0b013e318034194e Chaplin DD (2010) Overview of the Immune Response. J Allergy Clin Immunol 125:S3–23. https://doi.org/10.1016/j.jaci.2009.12.980 Guo H, Callaway JB, Ting JP-Y (2015) Inflammasomes: mechanism of action, role in disease, and therapeutics. Nat Med 21:677–687. https://doi.org/10.1038/nm.3893 Ferrucci L, Fabbri E (2018) Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Nat Rev Cardiol 15:505–522. https://doi.org/10.1038/s41569-018-0064-2 van Exel E, Gussekloo J, de Craen AJM, Frölich M, Bootsma-Van Der Wiel A, Westendorp RGJ (2002) Leiden 85 Plus Study. Low production capacity of interleukin-10 associates with the metabolic syndrome and type 2 diabetes: the Leiden 85-Plus Study. Diabetes 51:1088–1092. https://doi.org/10.2337/diabetes.51.4.1088 Pierson W, Liston A (2010) A new role for interleukin-10 in immune regulation. Immunol Cell Biology 88:769–770. https://doi.org/10.1038/icb.2010.105 Bai H, Jing D, Guo A, Yin S (2014) Association between interleukin 10 gene polymorphisms and risk of type 2 diabetes mellitus in a Chinese population. J Int Med Res 42:702–710. https://doi.org/10.1177/0300060513505813 Hua Y, Shen J, Song Y, Xing Y, Ye X (2013) Interleukin-10 -592C/A, -819C/T and – 1082A/G Polymorphisms with Risk of Type 2 Diabetes Mellitus: A HuGE Review and Meta-analysis. PLoS ONE 8:e66568. https://doi.org/10.1371/journal.pone.0066568 Leung OM, Li J, Li X, Chan VW, Yang KY, Ku M et al (2018) Regulatory T Cells Promote Apelin-Mediated Sprouting Angiogenesis in Type 2 Diabetes. Cell Rep 24:1610–1626. https://doi.org/10.1016/j.celrep.2018.07.019 Rieder F, Cheng L, Harnett KM, Chak A, Cooper GS, Isenberg G et al (2007) Gastroesophageal Reflux Disease–Associated Esophagitis Induces Endogenous Cytokine Production Leading to Motor Abnormalities. Gastroenterology 132:154–165. https://doi.org/10.1053/j.gastro.2006.10.009 Morozov S, Sentsova T (2022) Local inflammatory response to gastroesophageal reflux: Association of gene expression of inflammatory cytokines with esophageal multichannel intraluminal impedance-pH data. World J Clin Cases 10:9254–9263. https://doi.org/10.12998/wjcc.v10.i26.9254 Molnar V, Matišić V, Kodvanj I, Bjelica R, Jeleč Ž, Hudetz D et al (2021) Cytokines and Chemokines Involved in Osteoarthritis Pathogenesis. Int J Mol Sci 22:9208. https://doi.org/10.3390/ijms22179208 Kapoor M, Martel-Pelletier J, Lajeunesse D, Pelletier J-P, Fahmi H (2011) Role of proinflammatory cytokines in the pathophysiology of osteoarthritis. Nat Rev Rheumatol 7:33–42. https://doi.org/10.1038/nrrheum.2010.196 Mirhafez SR, Mohebati M, Feiz Disfani M, Saberi Karimian M, Ebrahimi M, Avan A et al (2014) An imbalance in serum concentrations of inflammatory and anti-inflammatory cytokines in hypertension. J Am Soc Hypertens 8:614–623. https://doi.org/10.1016/j.jash.2014.05.007 Chandran U, Patwardhan B (2017) Network ethnopharmacological evaluation of the immunomodulatory activity of Withania somnifera. J Ethnopharmacol 197:250–256. https://doi.org/10.1016/j.jep.2016.07.080 Chandran U, Mehendale N, Tillu G, Patwardhan B (2015) Network Pharmacology of Ayurveda Formulation Triphala with Special Reference to Anti-Cancer Property. Comb Chem High Throughput Screen 18:846–854. https://doi.org/10.2174/1386207318666151019093606 Vinothkanna A, Prathiviraj R, Sivakumar TR, Ma Y, Sekar S (2023) GC–MS and Network Pharmacology Analysis of the Ayurvedic Fermented Medicine, Chandanasava, Against Chronic Kidney and Cardiovascular Diseases. Appl Biochem Biotechnol 195:2803–2828. https://doi.org/10.1007/s12010-022-04242-7 Prasher B, Negi S, Aggarwal S, Mandal AK, Sethi TP, Deshmukh SR et al (2008) Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda. J Translational Med 6:48. https://doi.org/10.1186/1479-5876-6-48 Chauhan NS, Pandey R, Mondal AK, Gupta S, Verma MK, Jain S et al (2018) Western Indian Rural Gut Microbial Diversity in Extreme Prakriti Endo-Phenotypes Reveals Signature Microbes. Front Microbiol 9:118. https://doi.org/10.3389/fmicb.2018.00118 Govindaraj P, Nizamuddin S, Sharath A, Jyothi V, Rotti H, Raval R et al (2015) Genome-wide analysis correlates Ayurveda Prakriti. Sci Rep 5:15786. https://doi.org/10.1038/srep15786 Rotti H, Mallya S, Kabekkodu SP, Chakrabarty S, Bhale S, Bharadwaj R et al (2015) DNA methylation analysis of phenotype specific stratified Indian population. J Transl Med 13:151. https://doi.org/10.1186/s12967-015-0506-0 Rani R, Rengarajan P, Sethi T, Khuntia BK, Kumar A, Punera DS et al (2022) Heart rate variability during head-up tilt shows inter-individual differences among healthy individuals of extreme Prakriti types. Physiol Rep 10:e15435. https://doi.org/10.14814/phy2.15435 Cicchese JM, Evans S, Hult C, Joslyn LR, Wessler T, Millar JA et al (2018) Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology. Immunol Rev 285:147–167. https://doi.org/10.1111/imr.12671 Joshi KS, Nesari TM, Dedge AP, Dhumal VR, Shengule SA, Gadgil MS et al (2017) Dosha phenotype specific Ayurveda intervention ameliorates asthma symptoms through cytokine modulations: Results of whole system clinical trial. J Ethnopharmacol 197:110–117. https://doi.org/10.1016/j.jep.2016.07.071 Tharakan A, Shukla H, Benny IR, Tharakan M, George L, Koshy S (2021) Immunomodulatory Effect of Withania somnifera (Ashwagandha) Extract—A Randomized, Double-Blind, Placebo Controlled Trial with an Open Label Extension on Healthy Participants. J Clin Med 10:3644. https://doi.org/10.3390/jcm10163644 Rajanna M, Bharathi B, Shivakumar BR, Deepak M, Prashanth D, Prabakaran D et al (2021) Immunomodulatory effects of Andrographis paniculata extract in healthy adults – An open-label study. J Ayurveda Integr Med 12:529–534. https://doi.org/10.1016/j.jaim.2021.06.004 Additional Declarations The authors declare no competing interests. Supplementary Files JAIMmanuscriptsupplements.docx Cite Share Download PDF Status: Posted Version 1 posted 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. 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17:10:30","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":117642,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8052543/v1/e2891ab34ff51888e5af3ab3.html"},{"id":95669345,"identity":"127f15ef-c311-4819-ab4f-15f4a6c262ae","added_by":"auto","created_at":"2025-11-11 17:10:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47988,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSTROBE Flow Diagram\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFlow diagram illustrating the screening, enrolment, follow-up, sub-group analysis, and final inclusion of patients in the study\u003c/p\u003e","description":"","filename":"image.png","url":"https://assets-eu.researchsquare.com/files/rs-8052543/v1/ec143f6db454b49c51cb4ca1.png"},{"id":95669348,"identity":"accb64bc-b0ab-4e1c-af6c-b82562172098","added_by":"auto","created_at":"2025-11-11 17:10:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":273007,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of ayurveda treatment on cytokine levels in diabetes mellitus\u003c/p\u003e","description":"","filename":"image.png","url":"https://assets-eu.researchsquare.com/files/rs-8052543/v1/8f8138b93483baa7172dbe82.png"},{"id":95669347,"identity":"9915081f-7134-46b8-b77f-43210877f192","added_by":"auto","created_at":"2025-11-11 17:10:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48710,"visible":true,"origin":"","legend":"\u003cp\u003eImpact of Ayurveda Treatment Duration on IL-6 and TNF-α Levels in Diabetes Mellitus\u003c/p\u003e","description":"","filename":"image.png","url":"https://assets-eu.researchsquare.com/files/rs-8052543/v1/67bdb7f9be5e95d932fdafad.png"},{"id":95804490,"identity":"9689436a-acc9-4b1f-8ac3-28cc3fb7ccfc","added_by":"auto","created_at":"2025-11-13 08:37:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1522617,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8052543/v1/52911b0e-6e8b-4c83-ba5f-2ab562e96536.pdf"},{"id":95669344,"identity":"3faf12a5-826f-4deb-ba6d-2e23b9dac542","added_by":"auto","created_at":"2025-11-11 17:10:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22383,"visible":true,"origin":"","legend":"","description":"","filename":"JAIMmanuscriptsupplements.docx","url":"https://assets-eu.researchsquare.com/files/rs-8052543/v1/feecc0590fbb25b1e8b7b33b.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eEvaluating the Cytokine-Modulating Anti-inflammatory Effects of Ayurvedic Treatments on Non-Communicable Diseases: A Prospective Observational Study\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAyurveda, an ancient medical system with well-documented origins, emphasizes health preservation and disease prevention. When diseases arise, Ayurveda provides a detailed description of their prodromal signs, manifested symptoms, and possible complications. Despite technological advancements, Ayurvedic practitioners still mainly rely on subjective symptoms for diagnosis.\u003c/p\u003e\u003cp\u003eDisease is a complex phenomenon involving multiple biomolecules and pathways that contribute to its initiation and progression. Measuring these biomolecules is essential for diagnosis, treatment evaluation, and disease monitoring. Cytokines, which are small proteins or glycoproteins, act as chemical messengers for intercellular communication and are mainly produced by leukocytes and other cells to modulate the immune response [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Their levels are modulated by numerous factors, reflecting the complexity of cytokine regulation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eChronic non-communicable diseases are marked by systemic inflammation, a protective immune response regulated by the innate immune system against harmful stimuli such as pathogens, damaged cells, or irritants. Insufficient inflammation can result in persistent infections, whereas excessive inflammation may lead to chronic or systemic inflammatory disorders [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Inflammageing, a condition common among the elderly, is characterized by increased pro-inflammatory markers in the bloodstream and is closely associated with a higher risk of chronic diseases, physical disability, frailty, and premature mortality [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Research highlights the roles of cytokines like IL-6 and IL-10 in the low-grade inflammation often found in metabolic diseases such as diabetes and hypertension. Systemic chronic inflammation (SCI) is characterized by elevated pro-inflammatory cytokines, which worsen disease progression and complications. In type 2 diabetes mellitus (T2DM), an imbalance between pro- and anti-inflammatory cytokines regulates the inflammatory response [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Individuals with T2DM exhibit increased IFN-γ and reduced IL-10 levels [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], with genetic polymorphisms in the IL-10 gene linked to higher diabetes risk. IFN-γ, a key pro-inflammatory cytokine, significantly contributes to T2DM development [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Similarly, cytokines have been implicated in the pathogenesis of other conditions, including Gastroesophageal Reflux Disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], Osteoarthritis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and Hypertension [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAyurveda seeks to protect and improve well-being by defining good health, recognizing variations in health states, and providing methods to maintain balance. It addresses the causes, progression, symptoms, and treatments of diseases, with focus on both health preservation and disease management. Beyond medicinal interventions, Ayurveda emphasizes nutrition, lifestyle, environmental factors, and daily routines as integral to health maintenance and disease management. Ayurvedic therapeutic formulations typically combine herbal, mineral, and metal ingredients, containing synergistic compounds that act on multiple bodily systems. Network pharmacology studies have revealed the molecular mechanisms of these formulations, such as immunomodulation by \u003cem\u003eWithania somnifera\u003c/em\u003e [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], molecular targets of \u003cem\u003eTriphala\u003c/em\u003e in cancer treatment [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and the regulation of key genes in CKD and CVD pathways by \u003cem\u003eChandanasava\u003c/em\u003e [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These findings highlight the multi-targeted efficacy of Ayurvedic drugs.\u003c/p\u003e\u003cp\u003eIn Ayurveda, Prakriti refers to an individual\u0026rsquo;s unique constitutional phenotype, determined by observable physical characteristics that allow for classification into distinct categories. Personalized treatments in Ayurveda are tailored to an individual's Prakriti (unique phenotype) along with other relevant factors. Recent research has highlighted significant differences across Prakriti groups in areas such as gene expression, biochemical markers [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], gut microbiome [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], genetic variations [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], DNA methylation [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and physiological responses to head-up-tilt [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTraditionally, Ayurveda practitioners evaluate treatment efficacy by monitoring symptom improvement, severity reduction, and disease-specific biochemical markers. However, the role of inflammatory markers, such as cytokines, is often neglected in clinical practice. This study aims to bridge this gap by evaluating the impact of Ayurvedic treatment protocols on cytokine profiles.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Methods\u003c/h2\u003e\u003cp\u003eThis prospective observational study was conducted at the Interdisciplinary Institute of Indian System of Medicine (IIISM), SRM Institute of Science and Technology, Kattankulathur, Chennai, India. The study complies with all applicable national regulations and institutional policies and was conducted in accordance with the principles of the Helsinki Declaration. Ethical approval was obtained from the institution\u0026rsquo;s ethics committee, and the study was registered with the Clinical Trials Registry of India (CTRI/2021/12/038909). Participants were recruited from the IIISM Outpatient Department at SRM Hospital after being fully informed about the study. Informed consent was obtained from all participants. Data were collected and analyzed over 16 months, from December 2021 to March 2023, to assess the effectiveness of prescribed Ayurvedic therapies.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Participants\u003c/h2\u003e\u003cp\u003eParticipants were adults aged 20\u0026ndash;80 years (both sexes) seeking Ayurvedic treatment at the outpatient department. Exclusion criteria included patients below 20 years and pregnant or lactating women. Upon enrolment, Ayurvedic physicians diagnosed participants, recorded symptoms, assigned severity scores, and prescribed personalized treatments tailored to each patient\u0026rsquo;s condition. Treatments consisted of Ayurvedic formulations (tablets, capsules, and syrups) administered two or three times daily for one month, with dosage and timing customized for optimal outcomes. Specific medication details for various diseases are listed in Supplemental Table\u0026nbsp;1; demographic and disease-related details are provided in Supplemental Tables\u0026nbsp;2 and 3.\u003c/p\u003e\u003cp\u003eParticipants were reassessed during follow-up visits to evaluate therapeutic effectiveness, with medications continued for a total treatment duration of three months. Initial screening rigorously excluded individuals using allopathic or over-the-counter (OTC) medications to ensure that results were attributable solely to Ayurvedic treatment. Adherence to the protocol was ensured through regular monitoring, self-reported logs, and patient education. Follow-up visits were scheduled intermittently to track progress and address any deviations. Sixty participants were included to assess the impact of Ayurveda treatment on cytokine markers, measuring both pro-inflammatory (IFN-γ, IL-6, IL-17, TNF-α, IL-1) and anti-inflammatory (IL-4, IL-10) cytokines. The progression of participants through the trial phases is illustrated in the STROBE flow diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As there were no prior studies on Ayurveda\u0026rsquo;s effects on cytokine levels, effect size estimates could not be derived from existing literature. To evaluate statistical robustness, a power analysis was conducted using G*Power for Student\u0026rsquo;s t-tests, comparing pre- and post-intervention outcomes. With a sample size of 60, an effect size (dz) of 0.9, and a balanced Type I and Type II error minimization ratio of 1, the analysis yielded a non-centrality parameter of 6.9713700 and a critical t-value of 3.5980410. The test demonstrated a power of 99.93%, with a 0.065% probability of Type II and Type I errors. These findings emphasize the study\u0026rsquo;s robust design and high sensitivity in detecting significant differences.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFlow diagram illustrating the screening, enrolment, follow-up, sub-group analysis, and final inclusion of patients in the study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Pro-inflammatory \u0026amp; Anti-inflammatory cytokine profiling\u003c/h2\u003e\u003cp\u003eThe collected blood samples were transferred to vacutainers and centrifuged at 800 g for 30 minutes to separate plasma. Cytokine levels (IFN-γ, IL-6, IL-17, TNF-α, IL-1, IL-4, and IL-10) were measured using the Bio-Plex Pro\u0026trade; Human Inflammation Panel, a multiplex bead-based assay system (Bio-Rad). Briefly, 50 \u0026micro;l of plasma was added to a 96-well plate, and the assay was performed in duplicate per the manufacturer\u0026rsquo;s protocol, with automated washing using a Bio-Plex Pro\u0026trade; wash station. Cytometric analysis was conducted using a Luminex xMAP analyzer (Luminex 100 Milliplex), and data were analyzed using Bio-Plex Manager\u0026trade; 6.1 software. Cytokine concentrations were derived from standard curves and reported in picograms per milliliter (pg/mL).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Statistical analysis\u003c/h2\u003e\u003cp\u003eThe normality of the data was assessed using the Shapiro-Wilk test. Normally distributed data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and analyzed using paired-samples t-tests, while non-normally distributed data were expressed as median (interquartile range) and evaluated using Wilcoxon signed-rank tests. To quantify the magnitude of changes in cytokine levels, effect sizes were calculated: Cohen\u0026rsquo;s d for normally distributed data and rank biserial correlation for nonparametric data, ensuring robust and standardized measures of practical significance. Analyses were conducted using JASP (version 0.18.1); p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Additionally, permutation tests with 1,000 iterations were conducted in Python to evaluate changes in cytokine ratios, providing a non-parametric, assumption-free method to complement traditional tests. The observed differences between pre- and post-treatment ratios were compared against a null distribution generated by random shuffling, with statistical significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. This approach enhanced the reliability and validity of the findings by addressing potential limitations of parametric tests and offering a flexible, distribution-independent alternative for hypothesis testing.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Effect of Ayurveda treatment on cytokine levels\u003c/h2\u003e\u003cp\u003eAnalysis revealed significant reductions in pro-inflammatory cytokines post-treatment, with IFN-γ, IL-6, IL-17, and TNF-α showing marked decreases (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, large effect sizes). IL-4 and IL-10 levels increased significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and p\u0026thinsp;=\u0026thinsp;0.044, respectively), showing moderate and small-to-moderate effect sizes. Conversely, IL-1 levels showed no significant change (p\u0026thinsp;=\u0026thinsp;0.971), suggesting minimal treatment effect (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Permutation analysis confirmed significant reductions in pro-inflammatory cytokines (IFN-γ, IL-6, TNF-α, IL-17) and minimal changes in IL-1 (p\u0026thinsp;=\u0026thinsp;0.986). Changes in anti-inflammatory cytokines (IL-4 and IL-10) were less robust and varied between subgroups. Overall, these findings suggest immunomodulatory effects of the intervention, as inflammation was alleviated primarily through modulation of key pro-inflammatory cytokines, while effects on IL-1 and anti-inflammatory pathways were more limited and complex.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCytokine levels before \u0026amp; after Ayurveda treatment in overall diseases\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCytokines\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eBefore\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003etreatment\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eAfter\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003etreatment\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003ePaired Samples\u003c/p\u003e\u003cp\u003et \u0026ndash; Test\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e95% CI for Cohen\u0026rsquo;s d\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean \u0026plusmn; (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean \u0026plusmn; (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLower\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eUpper\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIFN- γ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e7.16\u0026thinsp;\u0026plusmn;\u0026thinsp;3.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.15\u0026thinsp;\u0026plusmn;\u0026thinsp;2.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.867\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e1.145\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.468\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e8.66\u0026thinsp;\u0026plusmn;\u0026thinsp;3.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e6.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e1.157\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.482\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e6.74\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.953\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.645\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.256\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF- α\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e7.38\u0026thinsp;\u0026plusmn;\u0026thinsp;3.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.15\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.316\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e1.074\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.389\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.68\u0026thinsp;\u0026plusmn;\u0026thinsp;3.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.971\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.258\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e6.29\u0026thinsp;\u0026plusmn;\u0026thinsp;2.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-4.296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.555\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.825\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.281\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.81\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.058\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.266\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.522\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Cytokine levels before and after treatment were compared using a paired samples t-test, with a sample size of n\u0026thinsp;=\u0026thinsp;60.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Effect of Ayurveda treatment on cytokine levels in diabetes mellitus\u003c/h2\u003e\u003cp\u003eIn the next phase of statistical analysis, the patient cohort was categorized into subgroups based on their specific diseases to evaluate the effect of Ayurveda treatment on cytokine levels within each subgroup. In the diabetes mellitus subgroup (n\u0026thinsp;=\u0026thinsp;16), significant reductions were observed in pro-inflammatory cytokines following Ayurveda treatment. Specifically, IFN-γ decreased from 9.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.67 pg/mL to 6.75\u0026thinsp;\u0026plusmn;\u0026thinsp;3.45 pg/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;1.169), IL-6 dropped from 10.43\u0026thinsp;\u0026plusmn;\u0026thinsp;3.82 pg/mL to 7.55\u0026thinsp;\u0026plusmn;\u0026thinsp;3.28 pg/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;1.475), IL-17 declined from 9.32\u0026thinsp;\u0026plusmn;\u0026thinsp;3.70 pg/mL to 7.76\u0026thinsp;\u0026plusmn;\u0026thinsp;3.64 pg/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;1.162), and TNF-α reduced from 10.32\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06 pg/mL to 7.05\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86 pg/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;1.279); all changes were associated with large effect sizes. Among anti-inflammatory cytokines, IL-4 increased slightly but significantly (7.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.34 pg/mL to 8.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.51 pg/mL, p\u0026thinsp;=\u0026thinsp;0.044, d = -0.549), while IL-1 and IL-10 showed no significant changes (p\u0026thinsp;=\u0026thinsp;0.493 and p\u0026thinsp;=\u0026thinsp;0.806, respectively; (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (a - e)). Permutation analysis confirmed significant reductions in IFN-γ (p\u0026thinsp;=\u0026thinsp;0.054), IL-6 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.025), and TNF-α (p\u0026thinsp;=\u0026thinsp;0.0001) but not in IL-17, IL-1, IL-10, or IL-4. Additionally, IL-6 and TNF-α levels showed further significant reductions by the 3rd month of treatment, emphasizing the importance of treatment duration for optimal anti-inflammatory effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These results highlight the efficacy of Ayurveda treatment in modulating pro-inflammatory cytokines while having limited impact on certain anti-inflammatory cytokines like IL-1 and IL-10.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCytokine levels in diabetes patients\u0026rsquo; group before \u0026amp; after Ayurveda treatment\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCytokines\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eBefore\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003etreatment\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eAfter\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003etreatment\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003ePaired Samples\u003c/p\u003e\u003cp\u003et \u0026ndash; Test\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e95% CI for Cohen\u0026rsquo;s d\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean \u0026plusmn; (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean \u0026plusmn; (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLower\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eUpper\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIFN- γ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e9.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e6.75\u0026thinsp;\u0026plusmn;\u0026thinsp;3.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.677\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e1.169\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.516\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.800\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e10.43\u0026thinsp;\u0026plusmn;\u0026thinsp;3.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.55\u0026thinsp;\u0026plusmn;\u0026thinsp;3.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.902\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e1.475\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.747\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2.181\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e9.32\u0026thinsp;\u0026plusmn;\u0026thinsp;3.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.76\u0026thinsp;\u0026plusmn;\u0026thinsp;3.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.649\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e1.162\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.511\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.791\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF- α\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e10.32\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.05\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e1.279\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.936\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e8.12\u0026thinsp;\u0026plusmn;\u0026thinsp;3.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.79\u0026thinsp;\u0026plusmn;\u0026thinsp;3.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.493\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.667\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e7.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e8.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.549\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-1.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e6.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e6.60\u0026thinsp;\u0026plusmn;\u0026thinsp;3.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.806\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.552\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Cytokine levels before and after treatment were compared using a paired samples t-test, with a sample size of n\u0026thinsp;=\u0026thinsp;16.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Effect of Ayurveda treatment on cytokine levels in GERD\u003c/h2\u003e\u003cp\u003eSeventeen GERD patients were analyzed, and Ayurveda treatment was associated with significant reductions in pro-inflammatory cytokines and increases in anti-inflammatory cytokines (see Table\u0026nbsp;6). Paired samples t-tests and Cohen\u0026rsquo;s d analyses showed: IFN-γ declined from 5.26\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50 pg/mL to 3.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21 pg/mL (t(16)\u0026thinsp;=\u0026thinsp;4.476, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;1.086), IL-6 from 7.06\u0026thinsp;\u0026plusmn;\u0026thinsp;3.10 pg/mL to 5.55\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04 pg/mL (t(16)\u0026thinsp;=\u0026thinsp;3.014, p\u0026thinsp;=\u0026thinsp;0.008, d\u0026thinsp;=\u0026thinsp;0.731), IL-17 from 5.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45 pg/mL to 4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;2.10 pg/mL (t(16)\u0026thinsp;=\u0026thinsp;3.300, p\u0026thinsp;=\u0026thinsp;0.005, d\u0026thinsp;=\u0026thinsp;0.800), and TNF-α from 5.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71 pg/mL to 3.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51 pg/mL (t(16)\u0026thinsp;=\u0026thinsp;3.990, p\u0026thinsp;=\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;0.968). Anti-inflammatory cytokines also increased significantly: IL-4 rose from 4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11 pg/mL to 5.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86 pg/mL (t(16) = -2.966, p\u0026thinsp;=\u0026thinsp;0.009, d = -0.719); IL-10 from 4.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97 pg/mL to 5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98 pg/mL (t(16) = -3.185, p\u0026thinsp;=\u0026thinsp;0.006, d = -0.773), with large to moderate effect sizes. IL-1 levels showed no significant change (4.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.69 pg/mL vs. 4.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86 pg/mL, t(16)\u0026thinsp;=\u0026thinsp;0.002, p\u0026thinsp;=\u0026thinsp;0.988, d\u0026thinsp;=\u0026thinsp;0.004; see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Permutation tests further supported these findings, with significant reductions in IFN-γ (p\u0026thinsp;=\u0026thinsp;0.009, difference: 1.96), IL-6 (p\u0026thinsp;=\u0026thinsp;0.039, difference: 2.16), and TNF-α (p\u0026thinsp;=\u0026thinsp;0.034, difference: 1.69), while IL-17, IL-4, IL-10, and IL-1 showed no significant changes (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). These results highlight the treatment\u0026rsquo;s efficacy in modulating pro-inflammatory cytokines and enhancing anti-inflammatory responses, underscoring its selective impact on immune regulation in GERD. The results for other diseases are presented in supplemental material.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCytokine levels in GERD patients\u0026rsquo; group before \u0026amp; after Ayurveda treatment\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCytokines\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eBefore\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003etreatment\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eAfter\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003etreatment\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003ePaired Samples\u003c/p\u003e\u003cp\u003et \u0026ndash; Test\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e95% CI for Cohen\u0026rsquo;s d\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean \u0026plusmn; (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean \u0026plusmn; (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLower\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eUpper\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIFN- γ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.26\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.476\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.471\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.679\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e7.06\u0026thinsp;\u0026plusmn;\u0026thinsp;3.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.55\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.731\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.260\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.340\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF- α\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.990\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.968\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.378\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.538\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.988\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.475\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.966\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.719\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-1.246\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.175\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.773\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-1.308\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.219\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Cytokine levels before and after treatment were compared using a paired samples t-test, with a sample size of n\u0026thinsp;=\u0026thinsp;17, GERD \u0026ndash; Gastroesophageal reflux disease.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.7. Effect of Ayurveda treatment on cytokine ratio levels in overall diseases\u003c/h2\u003e\u003cp\u003eThe ratio of pro-inflammatory to anti-inflammatory cytokines serves as a key marker of treatment efficacy, indicating a shift in immune balance. After Ayurveda treatment, significant reductions in these ratios were observed across all disease groups (see Table\u0026nbsp;10). Paired samples t-tests revealed substantial decreases: IFN-γ/IL-4 dropped from 1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48 to 0.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29 (t(59)\u0026thinsp;=\u0026thinsp;8.438, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;1.099); IFN-γ/IL-10 fell from 1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51 to 0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44 (t(59)\u0026thinsp;=\u0026thinsp;6.210, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;0.837); IL-6/IL-4 declined from 1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88 to 1.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56 (t(59)\u0026thinsp;=\u0026thinsp;6.900, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;0.891); IL-6/IL-10 reduced from 1.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91 to 1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69 (t(59)\u0026thinsp;=\u0026thinsp;7.391, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;0.962), and similar significant reductions were observed for IL-17/IL-4, IL-17/IL-10, TNF-α/IL-4, and TNF-α/IL-10 ratios with large to moderate effect sizes (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Permutation tests confirmed these findings, with all ratios showing highly significant p-values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and substantial observed differences, underscoring a favourable shift toward an anti-inflammatory state. These results highlight the treatment\u0026rsquo;s ability to effectively modulate cytokine balance, reducing inflammation across diverse conditions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCytokine ratio before \u0026amp; after Ayurveda treatment in overall diseases\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCytokines\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eBefore\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003etreatment\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eAfter\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003etreatment\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003ePaired Samples\u003c/p\u003e\u003cp\u003et \u0026ndash; Test\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e95% CI for Cohen\u0026rsquo;s d\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean \u0026plusmn; (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean \u0026plusmn; (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLower\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eUpper\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIFN-γ/IL-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.772\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.419\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIFN-γ /IL-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.837\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.142\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-6/IL-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.900\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.891\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.588\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.188\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-6/IL-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.962\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.650\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.269\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-17/IL-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.926\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.226\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-17/IL-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.958\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.776\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.482\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.065\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF-α/IL-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.684\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.305\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF-α/IL-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.311\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026nbsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.691\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.405\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.973\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eValues are expressed in mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, cytokine levels before and after treatment were compared using paired samples t \u0026ndash; test, and n\u0026thinsp;=\u0026thinsp;60\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study investigated the effects of Ayurveda treatment on pro-inflammatory and anti-inflammatory cytokine levels, revealing significant post-treatment changes. Pro-inflammatory cytokines, including IFN-γ, IL-6, IL-17, and TNF-α, showed marked reductions across various diseases, while anti-inflammatory cytokines IL-4 and IL-10 increased significantly. Notably, diabetes patients exhibited higher baseline inflammatory markers, consistent with the role of systemic inflammation in diabetes-related complications. The treatment's impact varied by condition: diabetes patients experienced significant reductions in all four pro-inflammatory cytokines, GERD patients showed notable declines, HTN patients demonstrated reductions in IFN-γ and IL-6. These findings underscore the disease-specific variability in Ayurveda's anti-inflammatory effects, highlighting its potential to modulate cytokine levels and restore immune balance.\u003c/p\u003e\u003cp\u003eOur analysis revealed an overall increase in anti-inflammatory cytokines IL-4 and IL-10 following Ayurveda treatment, though responses varied by disease. In diabetes patients, only IL-4 levels increased significantly, while GERD patients showed elevated levels of both IL-4 and IL-10. These findings underscore the disease-specific variability in Ayurveda's effects on anti-inflammatory cytokines. Pro-inflammatory and anti-inflammatory cytokines play critical roles in immune regulation, with their balance essential for maintaining immune homeostasis through complex feedback mechanisms [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. To assess Ayurveda's impact on this equilibrium, we calculated pro- to anti-inflammatory cytokine ratios, which decreased across all diseases post-treatment. This reduction suggests a rebalancing effect, potentially restoring immune system stability and highlighting Ayurveda's immunomodulatory potential.\u003c/p\u003e\u003cp\u003eThe effect sizes observed for cytokine levels before and after Ayurveda treatment provide valuable insights into its impact. Paired samples t-tests revealed large effect sizes for pro-inflammatory cytokines, including IFN-γ (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;1.145), IL-6 (d\u0026thinsp;=\u0026thinsp;1.157), IL-17 (d\u0026thinsp;=\u0026thinsp;0.953), and TNF-α (d\u0026thinsp;=\u0026thinsp;1.074), indicating substantial reductions and a strong biological response to the treatment. In contrast, negligible effects were seen for IL-1 (d\u0026thinsp;=\u0026thinsp;0.005), suggesting it was largely unaffected. Moderate effect sizes for anti-inflammatory cytokines like IL-4 (d = -0.555) and IL-10 (d = -0.266) indicate a significant but less pronounced shift toward reduced inflammation. Similarly, Wilcoxon signed-rank tests showed perfect Rank-Biserial Correlations (r\u0026thinsp;=\u0026thinsp;1.000) for IFN-γ, IL-6, IL-17, and TNF-α, reinforcing the robust treatment effects on pro-inflammatory markers. Conversely, negligible correlations for IL-1 (r = -0.429), IL-4 (r = -0.333), and IL-10 (r = -0.333) suggest minimal changes in these cytokines. Collectively, these findings highlight Ayurveda\u0026rsquo;s targeted efficacy in reducing pro-inflammatory cytokines while having limited impact on certain anti-inflammatory markers, underscoring its potential in managing inflammatory conditions by modulating key pathways.\u003c/p\u003e\u003cp\u003ePermutation test results across multiple datasets reveal heterogeneous effects of Ayurveda treatment on cytokine modulation in various diseases. Significant reductions were observed in key pro-inflammatory cytokines, such as IFN-γ (p\u0026thinsp;=\u0026thinsp;0.002), IL-6 (p\u0026thinsp;=\u0026thinsp;0.001), and TNF-α (p\u0026thinsp;=\u0026thinsp;0.000), highlighting the treatment's efficacy in reducing inflammation. In diabetic patients, robust decreases were noted in IFN-γ (p\u0026thinsp;=\u0026thinsp;0.054), IL-6 (p\u0026thinsp;=\u0026thinsp;0.025), and TNF-α (p\u0026thinsp;=\u0026thinsp;0.001). Similarly, GERD patients showed significant declines in IFN-γ (p\u0026thinsp;=\u0026thinsp;0.009), IL-6 (p\u0026thinsp;=\u0026thinsp;0.039), and a trend for TNF-α (p\u0026thinsp;=\u0026thinsp;0.034). Anti-inflammatory cytokines like IL-4, IL-10, and IL-1 generally showed minimal changes, with consistently high p-values (e.g., IL-10: p\u0026thinsp;=\u0026thinsp;0.88 in DM), suggesting resistance to modulation. These findings underscore the treatment\u0026rsquo;s selective efficacy in modulating pro-inflammatory cytokines while having limited effects on anti-inflammatory markers.\u003c/p\u003e\u003cp\u003eThe analysis of cytokine ratios revealed highly significant decreases in pro-inflammatory-to-anti-inflammatory ratios (all p\u0026thinsp;=\u0026thinsp;0.0), reflecting a systemic shift toward an anti-inflammatory state. Notably, the IFN-γ/IL-4 ratio showed an observed decrease of \u0026minus;\u0026thinsp;0.519 (pre: 1.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75; post: 0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37), and the IL-6/IL-10 ratio decreased by \u0026minus;\u0026thinsp;0.614 (pre: 1.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91; post: 1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69), indicating reduced pro-inflammatory signalling. These findings underscore the need for personalized approaches to effectively modulate immune responses and call for further investigation into the mechanisms driving these differences.\u003c/p\u003e\u003cp\u003ePrevious studies on Ayurveda treatment in asthma patients have examined cytokine levels, including TNF-α, IL-4, IL-6, IL-10, and others, before and after treatment. These studies reported reductions in pro-inflammatory cytokines like IFN-γ, IL-6, TNF-α, and IL-4, alongside an increase in the anti-inflammatory cytokine IL-10. Similarly, our study observed decreases in IFN-γ, IL-6, and TNF-α, as well as an increase in IL-10 post-treatment. However, unlike the study by Joshi et al., which noted a reduction in IL-4, our findings showed an increase in IL-4 levels after treatment. These differences may arise from disease-specific inflammatory pathways and variations in treatment protocols [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA study on the Ayurvedic herb Ashwagandha (\u003cem\u003eWithania somnifera\u003c/em\u003e) in healthy individuals found increased levels of IFN-γ and IL-4 after 30 days of treatment, in contrast to our findings of reduced IFN-γ. While the rise in IL-4 aligns with our findings, the discrepancy in IFN-γ may be due to the inclusion of only healthy participants in that study, as our observed decrease in IFN-γ could reflect disease-specific responses [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Similarly, a study on Andrographis paniculata reported increases in IFN-γ and IL-4, along with a reduction in IL-2, following 30 days of administration. Although the increase in IL-4 is consistent with our results, the rise in IFN-γ differs from our findings [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These variations likely stem from differences in disease contexts and the tailored nature of Ayurvedic treatments for specific conditions.\u003c/p\u003e\u003cp\u003eAlthough this study offers promising insights into the effects of Ayurveda treatment on cytokine levels, several limitations must be acknowledged. The small sample size for each disease subgroup may limit statistical power and generalizability, highlighting the need for larger, more diverse cohorts to strengthen the robustness of the findings and enable nuanced subgroup analyses. Additionally, the lack of a control group (e.g., placebo or standard care) precludes definitive attribution of observed changes to Ayurvedic treatment, as confounding factors like disease progression or placebo effects cannot be ruled out. Including a control group in future studies would enhance validity. The short follow-up period also restricts understanding of the long-term effects of Ayurveda treatment, particularly for chronic conditions where extended observation is necessary to assess sustainability and clinical relevance. To address these gaps, future research should prioritize larger, well-controlled studies with longer follow-up durations to validate findings and explore underlying mechanisms. Investigating disease-specific responses and individual variability could further optimize Ayurvedic interventions. Overcoming these limitations will be crucial for advancing the evidence base of Ayurveda's role in managing inflammatory conditions and integrating it into evidence-based practice.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, this study suggests that Ayurvedic treatment may modulate cytokine profiles by reducing pro-inflammatory cytokines and enhancing anti-inflammatory cytokines. This dual action highlights its potential to attenuate inflammatory responses across various diseases, restoring the balance critical for immune homeostasis. The observed decrease in pro- to anti-inflammatory cytokine ratios further supports its potential immunomodulatory role. These findings suggest Ayurveda's promise as a personalized therapeutic approach for inflammation-related conditions. However, further research is needed to elucidate underlying mechanisms, refine treatment protocols, and validate these results through larger, controlled trials. Such efforts will strengthen the evidence base for integrating Ayurveda into evidence-based medicine, particularly for managing immune dysregulation and chronic inflammation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThe authors acknowledge the financial support of Technology Innovation Hub (TIH-IOT), IIT Bombay, India for this clinical study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch Funding:\u0026nbsp;\u003c/strong\u003eThis study was funded by the Technology Innovation Hub (TIH-IOT), IIT Bombay, India\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrathiban Rengarajan (PR)\u003c/strong\u003e: Conceptualization, Methodology, Writing- Original draft preparation, Data Curation, Formal analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRamkumar Kunka Mohanram (RM)\u003c/strong\u003e:\u0026nbsp;Conceptualization, Methodology, Supervision, Investigation, Resources, Writing - Review \u0026amp; Editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSatish Kumar Rajappan Chandra (SK)\u003c/strong\u003e: Supervision, Investigation, Resources, Project administration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBala Pesala (BP)\u003c/strong\u003e: Conceptualization, Methodology, Supervision, Investigation, Funding acquisition, Writing - Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003eAll the authors have accepted responsibility for the entire content of this manuscript and approved submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing financial or personal interests that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent:\u003c/strong\u003e Informed consent was obtained from all individuals included in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval:\u0026nbsp;\u003c/strong\u003eThe study received approval from the institutional ethics committee and was registered with the Clinical Trials Registry of India (CTRI) under the registration number CTRI/2021/12/038909\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhang J-M, An J, Cytokines (2007) Inflammation and Pain. 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J Ayurveda Integr Med 12:529\u0026ndash;534. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jaim.2021.06.004\u003c/span\u003e\u003cspan address=\"10.1016/j.jaim.2021.06.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Immunomodulation, Non-communicable diseases, Inflammation, Cytokines, Ayurvedic medicine","lastPublishedDoi":"10.21203/rs.3.rs-8052543/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8052543/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eObjectives\u003c/b\u003e\u003c/p\u003e\u003cp\u003eChronic inflammation drives non-communicable diseases (NCDs) like diabetes, GERD, hypertension, and osteoarthritis. Ayurveda, an ancient system of medicine, emphasizes personalized treatments to restore balance and modulate immunity; however, its effects on cytokine profiles remain incompletely characterized. This study evaluated the impact of Ayurvedic interventions on pro-inflammatory cytokines (IFN-γ, IL-6, IL-17, TNF-α) and anti-inflammatory cytokines (IL-4, IL-10) in patients with non-communicable diseases (NCDs).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis prospective observational study included 60 patients receiving Ayurvedic treatment for various NCDs. Cytokine levels were measured pre- and post-treatment using multiplex bead-based assays. Statistical analyses included paired-sample t-tests, Wilcoxon signed-rank tests, effect size determinations, and permutation tests to assess changes in cytokine levels and ratios.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAyurvedic treatment was associated with significant reductions in pro-inflammatory cytokines, particularly in patients with diabetes and GERD. Anti-inflammatory cytokines increased in select subgroups, indicating a shift towards reduced inflammation. Pro-inflammatory to anti-inflammatory cytokine ratios decreased significantly, reflecting restored immune balance. Large effect sizes were observed for pro-inflammatory cytokine reductions, while anti-inflammatory cytokines showed moderate-to-small effect sizes. Permutation tests validated these findings, especially for diabetes and GERD.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePersonalized Ayurvedic treatments demonstrate immunomodulatory potential by reducing pro-inflammatory cytokines and enhancing anti-inflammatory cytokines, thereby restoring immune balance in patients with NCDs. These findings support integrating Ayurveda into modern clinical practices for managing inflammatory conditions. However, larger, controlled trials are needed to validate results and explore mechanisms.\u003c/p\u003e","manuscriptTitle":"Evaluating the Cytokine-Modulating Anti-inflammatory Effects of Ayurvedic Treatments on Non-Communicable Diseases: A Prospective Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-11 17:10:25","doi":"10.21203/rs.3.rs-8052543/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3fd6fe47-eba6-4066-b9c6-b937a2f6b9e6","owner":[],"postedDate":"November 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57585918,"name":"Integrative \u0026 Complementary Medicine"}],"tags":[],"updatedAt":"2025-11-11T17:10:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-11 17:10:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8052543","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8052543","identity":"rs-8052543","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}