Enhancement of Postpartum Cow Health and Calf Performance through Maternal‒Offspring Interactions: Effects on the Immunity, Antioxidants, and Bacterial Flora Induced by Guiqi Yimu Powder

Enhancement of Postpartum Cow Health and Calf Performance through Maternal‒Offspring Interactions: Effects on the Immunity, Antioxidants, and Bacterial Flora Induced by Guiqi Yimu Powder | 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 Enhancement of Postpartum Cow Health and Calf Performance through Maternal‒Offspring Interactions: Effects on the Immunity, Antioxidants, and Bacterial Flora Induced by Guiqi Yimu Powder Kaikai Bao, Hao Zhang, Weidong Ma, Peng Ji, Yanming Wei, Yongli Hua This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7702358/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract This study evaluated the effects of dietary supplementation with Guiqi Yimu powder (GYP) on the postpartum health of cows and the growth performance of their calves, with an emphasis on immune function, antioxidant capacity, and the bacterial flora. Twenty-two postpartum cows were randomly assigned to either a control group (CON; basal diet) or a GYP group (basal diet + GYP). After 7 d of supplementation, the serum samples from the cows and calves were analyzed for antioxidant indices [superoxide dismutase (SOD), malondialdehyde (MDA), and glutathione (GSH)] and immunoglobulins [IgA, IgM, and IgG]. Fecal samples from cows were assessed for gut microbiota diversity and short-chain fatty acids (SCFAs) content; milk samples were analyzed for microbial composition and immunoglobulins. Compared with those in the CON group, calves in the GYP group presented significantly greater weaning weights and average daily gains. The calf survival rate tended to increase, whereas the incidence of diarrhea tended to decrease in the GYP group. Among cows in the GYP group, both postpartum conception rates and estrus rates tended to increase; conversely, return-to-estrus rates and semen doses per conception tended to decrease. Serum levels of superoxide dismutase (SOD) and glutathione (GSH) were elevated, whereas malondialdehyde (MDA) levels were reduced ( P < 0.05) in GYP cows. Moreover, supplementation with GYP significantly increased the serum IgG levels ( P < 0.05), the milk IgM, IgA, and IgG levels ( P < 0.05), and the serum IgG levels in calves ( P < 0.05). Analysis of the gut microbiota of these cows revealed that, compared with CON, GYP improved the gut bacterial diversity and increased the relative abundances of Faecalibacterium , g_norank_f_F082 , and Oscillibacter . Furthermore, examination of the milk microbiota revealed that GYP increased the relative abundances of Acetobacter , Lactobacillus , and Prevotellaceae_UCG-003 . In addition, compared with CON, GYP significantly increased the contents of short-chain fatty acids (SCFAs), including acetic acid, propionic acid, isobutyric acid, n-butyric acid, isovaleric acid, and n-valeric acid, in the feces of postpartum cows ( P < 0.05). GYP improves postpartum cow health and calf performance via (1) direct antioxidant and immunomodulatory effects, (2) gut microbiota remodeling and SCFAs promotion, and (3) vertical transfer of immunoglobulins and probiotics through milk. These findings support the use of GYP as a functional feed additive for optimizing postpartum management in beef cattle. Guiqi Yimu powder SCFAs Growth performance Gut microbiota Milk microbiota Calf health Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Background The periparturient period spanning late gestation to early postpartum imposes the most severe physiological stress on cows. Rapid fetal development and initiation of colostrogenesis substantially increase maternal energy demands. Oxidative stress triggered by parturition manifested through elevated malondialdehyde (MDA) and reduced superoxide dismutase (SOD) and glutathione (GSH) activity may induce immunosuppression and homeostatic imbalance [ 4 ]. Concurrently, insufficient postpartum dry matter intake (DMI) exacerbates negative energy balance (NEB) and compromises host immunity, which may reduce conception rates at the second service while increasing return-to-estrus rates and services per conception. These factors collectively contribute to a decline in secondary breeding efficiency. The current clinical dependence on broad-spectrum antimicrobials disrupts gut microbiota equilibrium, reduces SCFAs production, and may exacerbate immunosuppression [ 34 ]. Such symptomatic interventions fail to achieve comprehensive physiological regulation, necessitating safer alternatives. Natural product extracts and herbal medicines have been well established as viable strategies for managing postpartum disorders [3; 32]. GYP is a modernized adaptation of the classical formula Guiqi Yimu San, which was originally documented in Essential Prescriptions for Bovine Diseases. This optimized phytocomposition contains three medicinal components: Astragalus membranaceus (Huangqi), Angelica sinensis (Danggui), and Leonurus japonicus (Yimucao). Through two evidence-based modifications, i.e., enhancing Leonurus proportion to potentiate its triple therapeutic effects via blood-activating properties (via leonurine alkaloids), promoting uterine repair (through TGF-β pathway modulation), and anti-inflammatory action (NF-κB inhibition) [ 25 ], we scientifically optimized the formulation through two evidence-based modifications: increasing the ratio of Astragalus to Angelica ; augmenting Qi-invigorating effects (astragaloside IV-mediated mitochondrial biogenesis); and maintaining optimal blood-nourishing capacity (ferulic acid-regulated hematopoiesis) [10; 40]. Although bioactive constituents, including astragalus polysaccharides, ferulic acid and leonurine, demonstrate antioxidative and immunomodulatory activities in in vitro or murine models, the clinical efficacy and mechanisms of GYP in periparturient cows remain unverified [1; 15; 16; 26; 29]. We hypothesize a dual-pathway mechanism for GYP. Maternal axis modulation: GYP potentially remodeled the gut microbiota by enriching beneficial genera such as Faecalibacterium , thereby increasing SCFAs acetate and propionate output, mitigating oxidative stress and enhancing systemic immunity. Neonatal axis transmission: GYP-derived bioactive compounds increase the levels of the milk immunoglobulins IgG, IgM and IgA and probiotics, including Lactobacillus , promoting microbial colonization in calves, reducing diarrhea incidence and improving growth performance, as quantified through average daily gain (ADG). This study aimed to systematically evaluate the regulatory role of GYP in the cow-calf health chain, providing a theoretical basis for the development of alternative Chinese herbal feed additives while also expanding the understanding of the 'gut-milk-immune' pathway mechanisms. Materials and methods Experimental animals Twenty-two healthy pregnant Qinchuan cows (parity: 2 ± 0.5; age: 23 ± 11 months; body weight: 550 ± 50 kg) were selected from the Qinchuan Cattle Breeding Farm in Shaanxi Province, China. The inclusion criteria were as follows: body condition score (BCS, on a 5-point scale) of 3.0--3.5, no history of dystocia/reproductive disorders, and expected calving dates within ± 3 days of each other. The cows were fed a basal diet ad libitum for seven days prior to the experiment, with free access to water. The experimental protocol was conducted according to the Chinese National Standard GB/T 35892-2018 (Laboratory animal - Guidelines for ethical review of animal welfare) and was approved by the Animal Ethics Committee of Gansu Agricultural University (Approval No. GSAU-Eth-VMC-2024-048). Main instruments The experimental equipment used included an FK-058 full-wavelength enzyme-linked immunosorbent assay (ELISA) machine from Beijing Putian Xinqiao Technology Co., Ltd., a UV spectrophotometer (725 N) from Shanghai Yuanxi Instrument Co., Ltd., a gas chromatograph (model: Agilent 8890 GC, equipped with a flame ionization detector (FID)) and a chromatographic column (DB-FFAP, 30 mm × 0.25 mm, 0.25 μm) from Agilent Technologies Co., Ltd. in the United States, an AL104 electronic balance from Shanghai Mettler Toledo Instrument Co., Ltd., and a HITACHI-CT15RE Hitachi ultracentrifuge from Hitachi, Ltd. Preparation of GYP Angelica sinensis , Astragalus membranaceus , and Leonurus japonicus are dried medicinal herbs purchased from the Yellow River medicinal market in Lanzhou, Gansu Province, and are stored in Laboratory 612 of the Cognitive Building of Gansu Agricultural University. The identification of medicinal herbs was conducted by Professor Wei Yanming from the Department of Veterinary Medicine at Gansu Agricultural University. The medicinal materials were finely ground (particle size ≤ 80 μm), and the uniformity of mixing was verified (RSD<5%). The GYP formulation consisted of 200 g of Leonurus japonicus , 50 g of Angelica sinensis , and 50 g of Astragalus membranaceus per 300 g aliquot. Animals and Experimental Design Twenty-two healthy cows that are about to give birth are selected and randomly divided into CON (basic diet) and GYP (basic diet + 300 g/d GYP) groups according to the feeding pen after the cows give birth. The experimental period lasted for a total of 7 days. During the experiment, feeding and management were carried out according to the routine procedures of the cattle farm. Disinfection was carried out once a day in the morning, and the drug feeding time was 2 noon every day. Each feeding was based on the bottom of the trough to ensure that there was no residue before the next feeding. GYP was used continuously for 7 days after delivery. Sample collection and processing Blood sample collection Before morning feeding on the eighth day after delivery, blood was collected from the cows and calves via a disposable, sterile blood collector to draw blood from the jugular vein. The blood was placed in a covered 10 mL centrifuge tube. Then, the blood samples were centrifuged at 4,000r/min for 15 minutes, the serum was separated, and the samples were stored at -80 °C. Collection of fecal samples On the morning of the eighth day after delivery, 10 g of fresh rectal feces was collected, frozen in liquid nitrogen, and stored at -80 °C. Collection of Milk Samples On the morning of the eighth day after delivery, during the first milking, the front milk was discarded, and 10 mL of middle milk was collected, which was stored at -80 °C. Determination of antioxidant, immune, microbial, and short-chain fatty acid contents Reproductive performance of cows and growth performance of calves Statistics on the oestrus rate, conception rate during oestrus, oestrus reversal rate, and sperm consumption rate of cows. Newborn calves and weaned calves were weighed separately, and the 20-day calf diarrhea rate, 60-day mortality rate, and calf survival rate were recorded during the experiment. The attributed score for diarrhea was as follows: 0, standard; 1, loose stool; 2, loose or some diarrhea; 3, diarrhea; and 4, severe watery diarrhea. The diarrhea rate was calculated according to the following formula: Calf diarrhea rate = (number of calves with diarrhea during the observation period ÷ total number of surviving calves in the same period) × 100%, Calf survival rate = (number of calves surviving at the end of the observation period ÷ (initial number of calves at the start of the period + number of calves born during the period)) × 100%, average daily gain percentage = (final body weight - initial body weight) ÷ number of days in the period) × 100%, preweaning weight gain percentage = ((weaning weight - birth weight) ÷ birth weight) × 100%. Serum antioxidant indicators GSH, MDA, and SOD assay kits built in Nanjing, China, were used to determine the antioxidant levels in the serum. The information on the reagent kit is shown in Table 1. Table 1 Serum antioxidant index kit and its product codes. P roject P roduct name P roduct number GSH Reduced glutathione (GSH) assay kit (microplate method) A006-2-1 MDA MDA Determination Kit (TBA Method) A003-1-2 SOD Total Superoxide Dismutase (T-SOD) Assay Kit (WST-1 Method) A001-3-2 Serum immunoglobulin levels Serum immunoglobulin levels, including IgA, IgG, and IgM, were detected via an ELISA according to the kit instructions. The information on the reagent kit is shown in Table 2. Table 2: Serum Immune Indicator Kit and Its Product Number. P roject P roduct name P roduct number IgA Bovine immunoglobulin A (IgA) ELISA research kit F4042-A IgG Bovine immunoglobulin G (IgG) ELISA research kit F3995-A IgM Bovine immunoglobulin M (IgM) ELISA research kit F6685-A Bacterial DNA extraction , Illumina MiSeq sequencing , and data processing Microbial DNA was extracted via the Hi Pure Fecal DNA Kit (Guangzhou Meiji Biotech, China). An ABI Gene Amp 9700 PCR thermal cycler (ABI Corporation, California, USA) was used to amplify the V3-V4 hypervariable region of the bacterial 16S rRNA gene via the primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GACTACHVGGGTWTTAAT-3′). The PCR product was extracted from a 2% agarose gel and purified via the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, California, USA). Quantification was performed via a fluorescence meter (Promega, USA). The purified PCR product was subjected to sequencing library preparation via the NEXTFLEX rapid DNA sequencing kit, which includes the following steps: (1) linker ligation; (2) magnetic bead method for removing dimers from the joint; (3) PCR amplification enrichment of the library template; and (4) retrieval of PCR products from magnetic beads to obtain the final library. Sequencing was performed on the Illumina PE300/PE250 platform (Shanghai Meiji Biomedical Technology Co., Ltd.). The optimized sequence was subsequently clustered into operational taxonomic units (OTUs) at a 97% similarity level via UPARSE 7.1 software [11]. The representative sequences of each OTU were subjected to taxonomic analysis via RDP Classifier 2.2 software and compared with the 16S rRNA gene database (Silva v138). Bacterial classification and data analysis were completed on the Meiji Cloud platform (). Statistical Analysis Based on the OTUs information, alpha diversity indices including Chao1 and Shannon index were calculated with Mothur v1.30.1 [39] (http://www.mothur.org/wiki/Calculators), and the Wilcoxon rank-sum test was used to analyze intergroup differences in alpha diversity of fecal and milk microbiota. The similarity among the microbial communities in fecal samples was determined by principal coordinate analysis (PCoA) based on unweighted UniFrac dissimilarity using Vegan v2.5-3 package. The non-parametric PERMANOVA test was used to assess whether the differences in microbial community structure among sample groups were significant using Vegan v2.5-3 package; The similarity among the microbial communities in milk samples was determined by non-metric multidimensional scaling (NMDS) analysis based on abund_jaccard dissimilarity using Vegan v2.5-3 package; the non-parametric PERMANOVA test was used to assess whether the differences in microbial community structure among sample groups were significant using Vegan v2.5-3 package. The linear discriminant analysis (LDA) effect size (LEfSe) [40] (http://huttenhower.sph.harvard.edu/LEfSe) was performed to identify the significantly abundant intestinal bacterial taxa (phylum to genera) among the different groups (LDA score > 2, P < 0.05). The Analysis of Intergroup Differences [48] was performed to identify the significantly abundant milk bacterial taxa (phylum to genera) among the different groups. The co-occurrence networks were constructed to explore the internal community relationships across the samples [2]. Microbial taxa were selected for network analysis based on Spearman’s correlation over 0.6 or less than -0.6, and the P-value less than 0.05. Analysis of SCFAs GC conditions The injection port temperature was 280 °C, and the chromatographic column heating program was as follows: the initial temperature was maintained at 60 °C for 2 min, then increased to 140 °C at a rate of 10 °C/min, and then increased to 170 °C at a rate of 3 °C/min. The sample was measured via the split flow method, with a split ratio of 20:1, a manual injection volume of 1 μL, a carrier gas of high-purity (purity>99%) nitrogen gas, a flow rate of 1 mL/min, a detector of FID, and a temperature of 300 °C. Establishment of the Standard Curve First, six standard samples of acetic acid (20 μL), propionic acid (10 μL), n-butyric acid (5 μL), isobutyric acid (5 μL), n-valeric acid (2 μL), and isovaleric acid (1 μL) were accurately measured at a volume ratio of 20:10:5:5:2:1. The six standard solutions were then mixed evenly and diluted with ultrapure water to obtain six different concentrations (5000-fold, 4000-fold, 3000-fold, 2000-fold, 1000-fold, and 500-fold) of mixed standard solutions. A total of 20 μL of n-butanol was diluted with 980 μL of ultrapure water. If a 5000-fold dilution was used, one μL of the mixed standard solution was aspirated. Subsequently, 4949 μL of ultrapure water and 50 μL of internal standard diluent were added, and the concentration of the n-butanol sample was 2.1856 mmol/L. Then, n-butanol was used as the internal standard, and 1 μL of the sample was accurately aspirated and detected with an instrument. Finally, the standard curve is obtained by plotting the content ratio on the x-axis and the peak-to-height ratio on the y-axis. Preparation of Fecal Sample Solution For the comprehensive analysis of gut microbiota and short-chain fatty acids (SCFAs), a subset of 6 cows per group was randomly selected from the original cohort of 11 for sample collection and sequencing. A 0.20 g fecal sample was accurately placed into a 2 mL EP tube. Then, four volumes of ultrapure water were added, mixed evenly, and allowed to stand at room temperature for 20 minutes. The mixture was centrifuged at 4,000r/min at 4 °C for 15 minutes. The obtained supernatant was added to a 2 mL EP tube. The fecal sediment was then treated with four volumes of ultrapure water in the same manner. Then, the combined supernatant from the two operations was centrifuged again, and the resulting supernatant was aspirated to 990 μL. Next, 10 μL of n-butanol diluent was added, the mixture was mixed well, and the mixture was filtered through a 0.22 μm membrane. Finally, 1 μL was accurately transferred for GC detection. Statistical analysis All the data were initially organized via Excel 2021 and are presented as the means ± standard errors of the means (SEMs). The experimental data were analyzed via SPSS Statistics 27.0 software. Normally distributed (Shapiro‒Wilk test, P>0.05) and homogeneous (Levene test, P>0.05) data were analyzed via an independent sample t test; parametric data were tested via the Mann‒Whitney U test. Statistical significance was defined as P<0.05. GraphPad Prism 9.5 software was used for plotting. Results Effects of GYP on the reproductive performance of cows and growth performance of calves As shown in Table 3, the weaning weight, average daily gain, and lactation period gain of calves in the GYP group were greater than those in the CON group. Additionally, the survival rate of calves in the GYP group reached 100%, and the diarrhea rate was 9.09% lower than that in the CON group. In terms of maternal reproductive performance, the GYP group presented a 10% increase in the conception rate during the oestrus period, a 10% decrease in the return to oestrus rate, and a 10% reduction in the semen consumption rate compared with those of the CON group (Table 4). Table 3 Growth Performance of Calves Growth performance of calves GYP group CON group Weaning weight, kg 129.63±20.44 119.75±25.11 Average daily weight gain, kg/d 0.85±0.16 0.77±0.19 Percentage of weight gain during lactation, % 4.27±0.68 3.39±0.89 Survival rate of calves, % 100% 81.82% 20 d diarrhea rate of calves, % 9.09% 22.18% Table 4 Reproductive Performance of Cows Reproductive performance of cows GYP group CON group Cycle conception rate, % 50 40 Estrus rate, % 70 70 Reaction rate, % 30 40 Precision consumption rate, % 120 130 Effects of GYP on serum antioxidant levels in postpartum cows As shown in Fig. 1, the addition of GYP significantly increased the serum antioxidant capacity of cows (SOD activity increased by 11.88%, the GSH level increased by 12.26%, and the MDA content decreased by 21.06%). The GSH and MDA levels in the GYP group were significantly increased (P<0.05, Fig. 1A and 1B), whereas the SOD was significantly decreased (P<0.01, Fig. 1C). Compared with the CON group. Effects of GYP on the serum immune level of cows As shown in Fig. 1D-F, the addition of GYP increased the serum immune ability of the cows (IgM activity increased by 4.16%, the IgG level decreased by 10.99%, and the IgA content increased by 1.62%). The IgG levels in the GYP group were significantly greater than those in the CON group (P<0.05, Fig. 1E), indicating that GYP can improve the immune protein levels of pregnant cows and enhance their immunity. Effects of GYP on the immune level of breast milk As shown in Fig. 2, the addition of GYP increased the immune ability of cow milk (IgM activity increased by 4.51%, the IgG level increased by 5.68%, and the IgA content increased by 16.68%). The IgG, IgM, and IgA levels in milk from the GYP group were significantly greater than those in milk from the CON group (P<0.05, Fig. 2A-C), indicating that GYP can increase the immune protein level in milk. Effects of GYP on serum antioxidant levels in calves As shown in Fig. 3A-C, the addition of GYP resulted in a 2.96% decrease in SOD activity, a 6.23% increase in the GSH level, and a 10.94% decrease in the MDA content in calf serum. However, there were no significant changes in GSH, SOD, or MDA in the GYP group compared with the CON group. Effects of GYP on the immune level of calves As shown in Fig. 3, the addition of GYP indirectly enhanced the serum immune ability of calves (IgM activity increased by 17.26%, the IgG level increased by 12.72%, and the IgA content increased by 7.98%). The IgG level of calves in the GYP group was significantly greater than that in the CON group (P<0.05, Fig. 3E), indicating that feeding with GYP can indirectly improve the immunoglobulin IgG level of calves and enhance their immunity. Effects of GYP on the gut microbiota of postpartum cows High-throughput sequencing of 16S rRNA gene was used to characterize changes in the gut microbiota of postpartum cows. The species accumulation curve of the Shannon curves was flat, indicating that the bacterial community composition between asv/otu was uniform and that the abundance difference was minimal, which met the sequencing requirements. To investigate the effect of adding GYP to the gut microbiota of postpartum cows, 16S rRNA gene sequencing was performed on fecal samples from postpartum cows. After quality control, an average of 77,843 sequence readings were obtained from each sample. The dilution curve analysis in Fig. 4A indicates that almost all microorganisms were detected in the feces of postpartum cows. The Venn diagram analysis in Fig. 4B shows that the total number of operable taxonomic units is 7,881, with a total of 2,861 shared. The CON group included 2,502 endemic species, whereas the GYP group included 2,418 endemic species. Alpha Diversity Analysis As shown in Fig. 4C, there was no significant difference in the alpha diversity indices (ace, chao, coverage, Sobs, Pd, Shannon, Simpson, and Pielou_e) of the gut microbiota between the two groups. Beta diversity analysis As shown in Fig. 4D, principal coordinate analysis (PCoA) indicated that effective separation can be achieved between the CON group and the GYP group. The effective separation suggested that the gut microbiota of postpartum cows, which were treated with GYP, and those fed these cows typically underwent specific changes. Species composition analysis - Community structure atlas To further investigate the effects of GYP on the gut microbiota of postpartum cows, species composition analysis was continued. As shown in Fig. 4E, the dominant gastrointestinal microbiota at the phylum level is displayed. The phyla Bacillus was present in all the samples (GYP: 80.26% ± 5.07% vs. CON: 84.40% ± 4.54%), Bacteroidetes (16.46% ± 4.31% vs. 12.01% ± 4.48%), and Spirogyra (1.10% ± 0.62% vs. 1.01% ± 0.87%), which accounted for more than 97% of the total relative abundance. Compared with that in the CON group, the richness of Actinobacteria in the GYP group decreased (P<0.05), whereas the richness of Proteobacteria increased (P<0.05). As shown in Fig. 4F, the dominant gastrointestinal microbiota at the family level is displayed. The families Streptococcus, Tremella, Kristensen, and Riken dominated all the samples. Compared with the GYP group, the CON group presented relatively high relative richness (P<0.05) of [Eubacterium]_coprostanoligenes_group, Clostridia_UCG-014, and unclassified_Oscillospirales, whereas the GYP group presented relatively high relative abundance (P<0.05) for Oscillospiraceae, the NK4A214_group, and UCG-002. As shown in Fig. 4G, the dominant gastrointestinal microbiota at the genus level is displayed. The dominant bacterial group in all the samples was UCG-005, belonging to the Rombous , Christensenellaceae_R-7_group , Clostridium , and Rikenellaceae_RC9_gut_ groups . Compared with the GYP group, the CON group [Eubacterium]_coprostanoligenes_group , Clostridia_UCG-014 , Coprococcus , and UCG-011 had relatively high relative richness (P<0.05), whereas the GYP groups UCG-002 , F082 , Oscillibacter , WCHB1- -41 , Colidexribacter , and Brevibacillus . The relative richness was relatively high (P<0.05). As shown in Fig. 4H, LEfSe analysis (LDA=2) revealed that Faecalibacterium , F082 , Oscillibacter , and WCHB1-41 were significantly enriched taxa in the gut microbiota of cows enriched with GYP. Effects of GYP on the microbiota of postpartum cow milk High-throughput sequencing of 16S rRNA was used to characterize changes in the microbiota of postpartum cow milk. The species accumulation curve of the Shannon curves was flat, indicating that the bacterial community composition between asv/otu was uniform and that the abundance difference was minimal, which met the sequencing requirements. To investigate the effect of adding GYP to the microbiota of cow milk, 16S rRNA gene sequencing was performed on cow milk samples. After quality control, an average of 47,163 sequence readings were obtained from each sample. As shown in Fig. 5A, dilution curve analysis revealed that almost all microorganisms were detected in the milk of postpartum cows. The Venn diagram analysis in Fig. 5B shows that there are total of 2,329 operable taxonomic units, with 1,208 shared. The CON group included 752 endemic species, whereas the GYP group included 1,051 endemic species. Alpha Diversity Analysis As shown in Fig. 5C, there was no significant difference in the alpha diversity indices (ace, chao1, coverage, sobs, Pd, Shannon, Simpson, and Pielou_e) of the milk microbiota between the two groups. Beta diversity analysis As shown in Fig. 5D, the Non-metric Multidimensional Scaling (NMDS) results demonstrate a clear separation between the CON (control) and GYP groups. Their relatively effective separation indicates that the milk microbiota of postpartum cows and normal postpartum cows underwent specific changes after intervention with traditional Chinese medicine. Species composition analysis - Community structure atlas To further investigate the impact of GYP on the microbiota of cow milk, species composition analysis was continued. As shown in Fig. 5E, the dominant milk microbiota at the phylum level is displayed. The phylum Pseudomonas was the most abundant, followed by the phylum Pseudomonas. The dominant bacterial groups in the GYP group were Pseudomonas, Bacillus, Actinobacteria, Cyanobacteria, Bacteroidetes, Sphingomonas, and Streptococcus. The dominant phyla of the CON group were Pseudomonas, Bacillus, Actinobacteria, and Cyanobacteria. Compared with that in the GYP group, the richness of the Pseudomonas phylum in the CON group decreased significantly (P<0.05). In contrast, the richness of Actinobacteria, Cyanobacteria, Bacteroidetes, Sphingomonas, and Vibrio showed the opposite trend (P<0.05). As shown in Fig. 5F, the dominant milk microbiota at the family level is displayed. The advantageous microbial communities of the GYP group included Chloroplast, Moraxellaceae, Saccharimonadales, and Propionibacteriaceae. The dominant microbial community in the CON group included Moraxellaceae, Sphingomonadaceae, Pseudomonadaceae, Burkholderiaceae, Comamonadaceae, unclassified bacteria, and Staphylococcaceae. Compared with the GYP group, the CON group presented an increase in the richness of Sphingomonadaceae (P<0.05). In contrast, the GYP group presented an increase in the richness of Propionibacterium, Devosiaceae, Lactobacillus, Saccharimonadaceae, and Longimicrobiaceae (P<0.05). As shown in Fig. 5G and 5H, the dominant milk microbiota at the genus level is displayed. Compared with the CON group, the GYP group presented an increase in the richness of Acetobacter , Devosia , Moraxella , TM7a , Rhodospirillales , Lactobacillus , Tetrasperera , Prevotella -UGC-003 , and Mesohizobium (P<0.05). Compared with that in the GYP group, the richness of Caulobacter in the CON group tended to increase (P<0.05). Effects of GYP on SCFAs in postpartum cows Establishment of SCFAs determination method Retention time and chromatographic peaks of SCFAs According to the chromatographic conditions in “GC conditions”, 1 μL of the mixed standard or sample solution was taken separately. The residence time results are shown in Table 5. The peak separation of each component was good, the baseline was smooth, and the retention times of the standard and sample corresponded well (Fig. 6). Table 5 Retention times of six SCFAs and n-butanol (internal standard) SCFAs Peak time/minute (standard) Peak time/minute (sample) N-butanol 5.125 5.123 Acetic acid 9.284 9.307 Propionic acid 10.263 10.267 Isobutyric acid 10.565 10.556 N-butyric acid 11.395 11.395 Isovaleric acid 11.942 11.940 N-valeric acid 13.011 13.013 Linear relationship testing The regression equations, linear ranges, and correlation coefficients of acetic acid, propionic acid, isobutyric acid, n-butyric acid, isovaleric acid, and n-valeric acid were obtained according to the chromatographic conditions of “GC conditions” with the ratio of the content as the horizontal coordinate (X) and the ratio of the peak height as the vertical coordinate (Y). The mixed standard solution was diluted into different gradients of mixed standards, and the concentrations of individual standards at each shaving were calculated. As shown in Table 6, the substances exhibited good linear relationships, with correlation coefficients greater than 0.99. Table 6 Regression Equations for Six SCFAs SCFAs R egression equation L inear range Correlation coefficient Acetic acid Y=0.31687458X-0.0885057 1.6260~8.132 0.99852 Propionic acid Y=1.0601326X+0.0026214 0.6274~3.137 0.99904 Isobutyric acid Y=1.59288244X+0.012189 0.2506~1.253 0.99795 N-butyric acid Y=1.58844994X-0.0143923 0.2532~1.266 0.99824 Isovaleric acid Y=1.3396296X-0.0029241 0.0856~0.428 0.99754 N-valeric acid Y=3.42610113X-0.009635 0.0423~0.212 0.99574 Y: peak height ratio; X: content ratio. Effects of adding GYP on SCFAs contents in cows As shown in Table 7, the total SCFAs content in the GYP group (4.923 ± 1.488 mmol/L) was significantly greater than that in the CON group (3.136 ± 0.914 mmol/L) (P<0.05), with acetic acid (+64.8%), propionic acid (+84.3%), and butyric acid (+95.9%) showing the greatest increase. Table 7 Effect of GYP on SCFAs Content in Postpartum Cows P roject GYP (mmol/L) CON (mmol/L) P- value Acetic acid 3.86±1.30 a 2.34±0.78 b 0.034 Propionic acid 0.71±0.24 a 0.39±0.10 b 0.012 Isobutyric acid 0.16±0.07 a 0.08±0.03 b 0.036 Butyric acid 0.40±0.22 a 0.21±0.05 b 0.008 Isovaleric acid 0.04±0.01 a 0.03±0.00 b 0.003 Valeric acid 0.16±0.01 a 0.10±0.03 b 0.002 Total acid 4.92±1.49 a 3.14±0.91 b 0.031 CON: postpartum cows fed basic feed; GYP: postpartum cows fed basic feed supplemented with 300 g/d GYP. Data are presented as mean ± SEM (n = 6). Within a row, values with different superscript letters (a, b) differ significantly (P < 0.05). Correlation analysis between SCFAs and the gut microbiota As shown in Fig. 7, there were 20 positive correlations (P<0.05) and nine negative correlations (P<0.05) between the relative abundance of bacterial genera and the concentration of SCFAs. Spearman's correlation analysis revealed that UGC-002 was positively correlated with Oscillibacter and acetic acid, propionic acid, butyric acid, valeric acid, and isovaleric acid (P<0.05). Additionally, Akkermansia was positively correlated with isobutyric acid (P<0.05). Discussion Oxidative stress is a significant underlying factor in the dysfunction of host immune and inflammatory responses, which increases the susceptibility of cows to various diseases, especially during the postpartum period [5; 39]. Supplementing diets with Chinese herbal medicines that possess antioxidant capacity and prebiotics can, to some extent, improve postpartum production performance in cows and calf health [ 28 ]. Recent studies have reported that GYP can enhance the growth performance, production performance, and immune function of livestock and poultry through mechanisms such as antioxidant, anti-inflammatory, and immunomodulatory effects [ 22 ]. This study also confirmed that adding GYP can significantly improve the antioxidant levels and immune function of postpartum cows. The reason may be that the active ingredients in Astragalus membranaceus and Angelica sinensis have antioxidant effects, which positively impact the cows' antioxidant levels [21; 45]. Increasing the activity of antioxidant enzymes and reducing the content of oxidation products within cows helps maintain their health status. Studies have shown that Angelica sinensis polysaccharides have effects against cellular oxidative damage and improve immune function [ 17 ], and Astragalus membranaceus polysaccharides significantly impact cow antioxidant levels and immune function. Leonurus japonicus extract may also have significant antioxidant effects and immune-enhancing properties [ 31 ]. This GYP-mediated increase in antioxidant capacity and immunity was ultimately reflected in the improvement in the cows' reproductive performance: the conception rate at first service in the GYP group increased by 10%, the return-to-estrus rate decreased by 10%, and the semen dose per conception also tended to decrease. These findings suggest that GYP provides an internal safeguard for improving reproductive efficiency by ameliorating maternal redox status and immune function. The diversity and stability of the gut microbiota are crucial for organisms. Generally, the greater the diversity of the gut microbiota is, the greater its ability to enhance the stability of the gut bacterial community [ 43 ]. A decrease in diversity may reduce beneficial microorganisms and the expansion of pathogenic microbes [24; 38]. The metabolites of the gut microbiota are interconnected with the immune system, regulating immune responses [ 2 ] through direct and indirect interactions with host immune cells [ 19 ]. Some bacteria, including Faecalibacterium and Oscillibacter , generate SCFAs through carbohydrate fermentation. SCFAs can regulate host immune cells and provide a carbon source for colonocytes [8; 18]. Through LEfSe analysis, this study identified Faecalibacterium , WCHB1-41 , F082 , and Oscillibacter as the main affected genera. Notably, these key genera are closely related to the production of SCFAs. Faecalibacterium can synthesize SCFAs (especially butyrate), which not only have protective effects on digestive system health but also enhance the body's immune system, promote metabolism, and maintain intestinal barrier integrity [ 12 ]. Moreover, it has been reported that its abundance is significantly positively correlated with the expression levels of antioxidant-related genes [ 41 ], which is consistent with the increased antioxidant levels found in the GYP group in this study. F082 belongs to the Bacteroidota phylum and is involved primarily in noncellulose degradation, with its main metabolic products being propionate and butyrate [ 23 ]. Oscillibacter is considered a potential probiotic because it plays a key role in sugar fermentation [ 47 ] and starch degradation [ 20 ]. The products of sugar fermentation and starch degradation are SCFAs. WCHB1–41 can degrade mucin and convert fiber-rich feed into SCFAs, providing nutrients for other bacteria and cells [ 14 ]. The primary function of SCFAs is to serve as the primary energy source and substrates for glucose and fat synthesis in ruminants, accounting for 70–80% of their total energy requirements [ 48 ]. They regulate gene expression by binding to G protein-coupled receptors (GPCRs) and inhibiting the activity of histone deacetylases (HDACs). These mechanisms are crucial for reducing local inflammation, resisting pathogen invasion, and maintaining intestinal barrier integrity [ 46 ]. This study revealed that the concentrations of total SCFAs, acetate, propionate, and butyrate in the GYP group were greater than those in the CON group. The reason may be closely related to the increased abundance of the key SCFAs-producing genera mentioned above: Faecalibacterium , F082 , Oscillibacter , and WCHB1–41 . Furthermore, Spearman correlation analysis further indicated that Oscillibacter , UGC-002 , and Akkermansia were strongly correlated with SCFAs. Akkermansia can increase intestinal barrier integrity, regulate immune responses, mitigate inflammatory responses, and support the proliferation of butyrate-producing bacteria [ 33 ]. In summary, the gut microbiota and microenvironment are interdependent. GYP promoted SCFAs production by modulating the microbiota. These SCFAs not only provide energy but also, through their immunomodulatory and barrier-protective functions, create a microenvironment conducive to the colonization and growth of beneficial bacteria while inhibiting the proliferation of harmful bacteria. Ultimately, they act synergistically to restore and maintain the integrity of the intestinal mucosal barrier. Calf health is associated with milk microbiota. The dam milk calf constitutes a closely related biological system. The components of milk, a key medium, including immune factors and microorganisms, may influence the early life processes of newborn calves. Microorganisms in milk can not only promote the establishment and development of calf gut microbiota but are also related to nutrient digestion in calves. The study revealed that GYP significantly increased IgG levels in cow serum. This immune enhancement was directly reflected in the milk composition, as the contents of IgA, IgG, and IgM in the milk of the GYP group cows significantly increased. When milk from GYP group cows rich in immunoglobulins (especially IgG) was consumed, the serum IgG levels in calves significantly increased (by 12.72%, p < 0.05). Immunoglobulins (IgA, IgG, and IgM) are important defense molecules in the body that protect calves by clearing antigens, neutralizing toxins, and preventing pathogen invasion. This increase in passive immunity was directly linked to a significant 16.6% reduction in the calf diarrhea rate, indicating that GYP indirectly but effectively enhanced the disease resistance of calves through maternal immune enhancement and vertical transmission of milk immunoglobulins. The human milk microbiota has been confirmed to promote the maturation of the intestinal epithelial barrier, immune system, and endocrine system in early life, regulating the intestinal microenvironment [ 6 ]. This study revealed that GYP altered the microbial composition of cow milk, increasing the abundance of key beneficial genera. Acetobacter is a primary producer of acetate in the rumen [ 27 ]. Lactobacillus is a classic probiotic that exerts potent antibacterial activity through the production of lactic acid, organic acids, H 2 O 2 , or bacteriocins, thereby antagonizing pathogenic bacteria and maintaining healthy gut ecology [13; 35]. It can also improve intestinal inflammation and support the ability of beneficial microbiota to resist infection [ 7 ]. Prevotellaceae_UCG-003 belongs to the Prevotellaceae family, whose members are involved in plant cell wall polysaccharide degradation [ 9 ], protein catabolism [42; 44], etc., and are important acetate and propionate producers. Studies suggest that it may reduce inflammation and protect the intestinal barrier by lowering the concentrations of inflammatory markers (such as LPS-binding protein and C-reactive protein) [36; 49]. Through suckling, the high-abundance beneficial bacteria in milk, particularly Lactobacillus and Prevotellaceae_UCG-003 , are directly transferred to newborn calves. High-abundance incoming lactobacillius can rapidly colonize calf intestines, utilizing their inherent antibacterial properties to antagonize pathogens and reduce the risk of diarrhea directly. Lactobacillus enhances the activity of intestinal digestive enzymes (such as lactase and lipase), improving the absorption efficiency of nutrients such as colostrum by calves and assisting in establishing and strengthening intestinal immune barrier function. As a vertically transmitted key bacterium, Prevotellaceae_UCG-003 produces SCFAs, provides energy substrates, and is associated with the shaping of a healthy calf intestinal microenvironment and promoting barrier integrity through its potential anti-inflammatory properties and metabolic functions. This study revealed that the abundance of Prevotellaceae_UGC-003 in milk was significantly greater than that in milk, which echoes the high abundance of this bacterial family observed in the colon of piglets fed with breast milk by Rosa et al [ 37 ]. This study revealed that GYP improved calf growth performance. However, its mechanism of action did not involve directly enhancing the antioxidant capacity of calves (serum SOD, GSH, and MDA levels did not significantly change). The data suggest that the core effect of GYP may involve dual vertical transmission via the maternal‒milk pathway: on the one hand, the high levels of immunoglobulins, particularly IgG, in milk provide calves with immediate passive immune protection, significantly increasing their serum IgG levels (P < 0.05)[ 30 ]; on the other hand, specific beneficial bacterial communities in milk, such as Acetobacter , Lactobacillus , and Prevotellaceae_UGC-003 , are transferred to calves, colonizing their intestines early on and exerting antimicrobial, anti-inflammatory, digestive absorption-promoting, intestinal barrier-enhancing, and energy substrate-providing effects, thereby optimizing the intestinal microbiota structure and function. Immunoglobulins and beneficial microbial communities synergistically interact within calves to jointly establish calf health. This is directly reflected in the reduced diarrhea rate in the GYP group calves, improved growth performance, and ultimately, a calf survival rate of 100%, which is higher than the 81.82% reported in the CON group. Conclusion Our findings demonstrate that GYP supplementation may exert multifaceted benefits through distinct pathways in both mothers and offspring. In postpartum cows, GYP significantly (1) enhances systemic antioxidant capacity (increased SOD, GSH; decreased MDA) and immune function (elevated serum and milk immunoglobulins), (2) modulates the gut microbiota composition (enriched Faecalibacterium and Oscillibacter ), and (3) increases SCFAs production. These effects collectively promote faster postpartum recovery through a proposed "herb-gut microbiota-immunity" axis. For offspring, GYP-mediated improvements in calf performance (increased weaning weight, average daily gain) and health (reduced diarrhea incidence) appear to be mediated through milk-based pathways, as evidenced by (i) elevated immunoglobulins (IgG) in calf serum and (ii) probiotic enrichment ( Lactobacillus , Acetobacter ) in maternal milk (Fig. 8). Abbreviations ADG average daily gain BCS body condition score DMI dry matter intake FID flame ionization detector GSH glutathione GPCRs G protein-coupled receptors GYP Guiqi Yimu Powder HDACs inhibit the activity of histone deacetylases IgA immunoglobulin A IgG immunoglobulin G IgM immunoglobulin M MDA malondialdehyde NEB negative energy balance NMDS Non-metric multidimensional scaling， OTUs Operational taxonomic units PCoA Principal co-ordinates analysis SCFAs short-chain fatty acids SEM Standard error of the mean SOD superoxide dismutase Declarations Authors’ contributions B.K., W.M. and Y.H. designed the study; X.Y., H.Z. and B.K. performed the research and analyzed the data with the support of Y.H. in statistics; P.J., W.M., Y.W. and Y.H. supervised the project; B.K. prepared and wrote the original draft; Y.H. and Y.W. reviewed the paper. All the authors have read and agreed to the published version of the manuscript. Funding This research was funded by the China Agriculture Research System of MOF and MARA (CARS-37) and the Fuxi Foundation of Gansu Agricultural University (No. Gaufx-03J01). Availability of data and materials The sequence files determined in the present study were deposited at the Sequence Read Archive (SRA; http://www.ncbi.nlm.nih.gov/subs/ (accessed on 01 January 2026); SRA accession number: PRJNA1333447). Ethics approval and consent to participate The experimental protocol was conducted by the Chinese National Standard GB/T 35892-2018 (Laboratory animal - Guidelines for ethical review of animal welfare) and was approved by the Animal Ethics Committee of Gansu Agricultural University (Approval No.: GSAU-Eth-VMC-2024-048). Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Bai F, Bi S, Yue S, Xu D, Fu R, Sun Y et al. The serum lipidomics reveal the action mechanism of danggui-yimucao herbal pair in abortion mice. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7702358","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":573822232,"identity":"d28defe0-eda2-4f73-9668-f9c7f94038db","order_by":0,"name":"Kaikai 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08:14:36","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":182671,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/e303714944c15fb7f2262ef0.html"},{"id":100293154,"identity":"01c3d21e-b2df-4004-9930-326cf5d1a73b","added_by":"auto","created_at":"2026-01-15 07:18:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":653285,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of GYP addition on antioxidant and immunoglobulin levels in cow serum.\u003c/p\u003e\n\u003cp\u003e(A) Serum GSH levels in cows. (B) Serum MDA levels in cows. (C) Serum SOD levels in cows. (D) Serum IgM levels in cows. (E) IgG levels in cow serum. (F) Serum IgA levels in cows. CON: postpartum cows fed basic feed; GYP: postpartum cows fed basic feed supplemented with 300 g/d GYP. Data are presented as mean ± SEM (n = 11). * Indicates statistically significant differences between groups, *P\u0026lt;0.05, * *P\u0026lt;0.01, * * * P\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/e8f59ad7d662f2cf5724c88d.png"},{"id":100293150,"identity":"0498e47b-f9eb-4758-986f-e24dc00ebe60","added_by":"auto","created_at":"2026-01-15 07:18:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":339660,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of GYP addition on immunoglobulin levels in postpartum cow milk. (A) IgA levels in breast milk. (B) IgG levels in breast milk. (C) IgM levels in breast milk. CON: postpartum cows fed basic feed; GYP: postpartum cows fed basic feed supplemented with 300 g/d GYP. Data are presented as mean ± SEM (n = 11). * Indicates statistically significant differences between groups, * P\u0026lt;0.05; ** P\u0026lt;0.01; ***P\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/3347c3715e9f87737ffc03dd.png"},{"id":100293153,"identity":"d3570daa-fd48-404c-8ed1-a85b2a687698","added_by":"auto","created_at":"2026-01-15 07:18:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":619855,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of GYP addition on antioxidant and immunoglobulin levels in the serum of lactating calves. (A) Serum GSH levels in lactating calves. (B) Serum MDA levels in lactating calves. (C) Serum SOD levels in lactating calves. (D) Serum IgA levels in calves. (E) IgG levels in calf serum. (F) Serum IgM levels in calves. CON: postpartum cows fed basic feed; GYP: postpartum cows fed basic feed supplemented with 300 g/d GYP. Data are presented as mean ± SEM (n = 11). * Indicates statistically significant differences between groups, * P\u0026lt;0.05; ** P\u0026lt;0.01; ***P\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/a4dae5aead23a00782b62b6f.png"},{"id":100293152,"identity":"9399800f-48ab-4de4-b7e8-7bdcf29ac9db","added_by":"auto","created_at":"2026-01-15 07:18:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1654663,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of GYP on the gut microbiota of postpartum cows. (A) Microbial sparse curves based on observed indices are used to evaluate the coverage depth of each sample (different colored lines distinguish samples). (B) Display the Venn diagram of the operational taxonomic unit (OTU) composition of gut microbiota in GYP and CON groups. (C) Two-dimensional sorting chart of Beta Diversity PCOA analysis samples. (D) Box plot of Alpha diversity index grouping. (a) Simpson Diversity Index; (b) Ace richness index; (c) Pd lineage diversity index; (d) Pielou_e uniformity index; (e) Chao richness index; (f) Coverage diversity index; (g) Sobs richness index; (h) Shannon diversity index. (E) The distribution of classification components at the door level. (F) The distribution of classification components at the scientific level. (G) The distribution of classification components at the genus level. (H) Lefse analysis (LDA = 2) revealed differences between gut microbiota groups.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/46ebfbbd6e6670e0431dac95.png"},{"id":100293160,"identity":"a780824b-e223-417a-bded-192e0aa85e6a","added_by":"auto","created_at":"2026-01-15 07:18:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1815749,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of GYP on the microbiota of postpartum cow milk. (A) Microbial sparse curves based on observed indices are used to evaluate the coverage depth of each sample (different colored lines distinguish samples). (B) Display the Venn diagram of the operational taxonomic unit (OTU) composition of milk microbiota in GYP and CON groups. (C) Two-dimensional sorting chart of Beta Diversity NMDS analysis samples. (D) Box plot of Alpha diversity index grouping. (a) Simpson Diversity Index; (b) Ace richness index; (c) Pd lineage diversity index; (d) Pielou_e uniformity index; (e) Chao richness index; (f) Coverage diversity index; (g) Sobs richness index; (h) Shannon diversity index. (E) The distribution of classification components at the door level. (F) The distribution of classification components at the scientific level. (G) The distribution of classification components at the genus level. (H) Classification composition shows differences between the two groups at the genus level. * Indicates statistically significant differences between groups, * P\u0026lt;0.05; ** P\u0026lt;0.01; ***P\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/301e8d24389d26cdf2a22433.png"},{"id":100373222,"identity":"4e2dd1d5-123c-4bec-9af3-74cde0058af9","added_by":"auto","created_at":"2026-01-16 08:13:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":851867,"visible":true,"origin":"","legend":"\u003cp\u003eChromatogram of SCFAs. (A) SCFA chromatogram of mixed standard samples. (B) SCFA chromatogram of fecal sample. (1) N-butanol (internal label); (2) Acetic acid; (3) Propionic acid; (4) Isobutyric acid; (5)N- butyric acid; (6) Isovaleric acid; (7) N-valproic acid\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/ed2246157e5fe966c0373fe5.png"},{"id":100293162,"identity":"69ec64c6-c4a4-4731-b1f4-c2f42df5ff16","added_by":"auto","created_at":"2026-01-15 07:18:28","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":668477,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation between microbiota and SCFAs. Red indicates a positive correlation, while blue indicates a negative correlation. The intensity of the color is directly proportional to the intensity of the Spearman correlation. *There is a statistically significant difference between the groups, * P\u0026lt;0.05; **P\u0026lt;0.01; ***P\u0026lt;0.001。\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/7357282b32a6597383e4783d.png"},{"id":100373482,"identity":"b4218677-4c49-4ce3-8448-f727b68da7d1","added_by":"auto","created_at":"2026-01-16 08:14:37","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":749285,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram illustrating the effects of GYP on reproductive performance, immune levels, and gut microbiota in cows and beef calves.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/b532c0433b1fa26d12df16d5.png"},{"id":100383962,"identity":"d17de9da-db42-4fed-b842-742235e4a30b","added_by":"auto","created_at":"2026-01-16 10:48:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8818461,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7702358/v1/2c38567e-d1bf-4938-8e37-135d682c8d73.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enhancement of Postpartum Cow Health and Calf Performance through Maternal‒Offspring Interactions: Effects on the Immunity, Antioxidants, and Bacterial Flora Induced by Guiqi Yimu Powder","fulltext":[{"header":"Background","content":"\u003cp\u003eThe periparturient period spanning late gestation to early postpartum imposes the most severe physiological stress on cows. Rapid fetal development and initiation of colostrogenesis substantially increase maternal energy demands. Oxidative stress triggered by parturition manifested through elevated malondialdehyde (MDA) and reduced superoxide dismutase (SOD) and glutathione (GSH) activity may induce immunosuppression and homeostatic imbalance [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Concurrently, insufficient postpartum dry matter intake (DMI) exacerbates negative energy balance (NEB) and compromises host immunity, which may reduce conception rates at the second service while increasing return-to-estrus rates and services per conception. These factors collectively contribute to a decline in secondary breeding efficiency. The current clinical dependence on broad-spectrum antimicrobials disrupts gut microbiota equilibrium, reduces SCFAs production, and may exacerbate immunosuppression [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Such symptomatic interventions fail to achieve comprehensive physiological regulation, necessitating safer alternatives. Natural product extracts and herbal medicines have been well established as viable strategies for managing postpartum disorders [3; 32].\u003c/p\u003e \u003cp\u003eGYP is a modernized adaptation of the classical formula Guiqi Yimu San, which was originally documented in Essential Prescriptions for Bovine Diseases. This optimized phytocomposition contains three medicinal components: \u003cem\u003eAstragalus membranaceus\u003c/em\u003e (Huangqi), \u003cem\u003eAngelica sinensis\u003c/em\u003e (Danggui), and \u003cem\u003eLeonurus japonicus\u003c/em\u003e (Yimucao). Through two evidence-based modifications, i.e., enhancing \u003cem\u003eLeonurus\u003c/em\u003e proportion to potentiate its triple therapeutic effects via blood-activating properties (via leonurine alkaloids), promoting uterine repair (through TGF-β pathway modulation), and anti-inflammatory action (NF-κB inhibition) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], we scientifically optimized the formulation through two evidence-based modifications: increasing the ratio of \u003cem\u003eAstragalus\u003c/em\u003e to \u003cem\u003eAngelica\u003c/em\u003e; augmenting Qi-invigorating effects (astragaloside IV-mediated mitochondrial biogenesis); and maintaining optimal blood-nourishing capacity (ferulic acid-regulated hematopoiesis) [10; 40]. Although bioactive constituents, including astragalus polysaccharides, ferulic acid and leonurine, demonstrate antioxidative and immunomodulatory activities in in vitro or murine models, the clinical efficacy and mechanisms of GYP in periparturient cows remain unverified [1; 15; 16; 26; 29].\u003c/p\u003e \u003cp\u003eWe hypothesize a dual-pathway mechanism for GYP. Maternal axis modulation: GYP potentially remodeled the gut microbiota by enriching beneficial genera such as \u003cem\u003eFaecalibacterium\u003c/em\u003e, thereby increasing SCFAs acetate and propionate output, mitigating oxidative stress and enhancing systemic immunity. Neonatal axis transmission: GYP-derived bioactive compounds increase the levels of the milk immunoglobulins IgG, IgM and IgA and probiotics, including \u003cem\u003eLactobacillus\u003c/em\u003e, promoting microbial colonization in calves, reducing diarrhea incidence and improving growth performance, as quantified through average daily gain (ADG). This study aimed to systematically evaluate the regulatory role of GYP in the cow-calf health chain, providing a theoretical basis for the development of alternative Chinese herbal feed additives while also expanding the understanding of the 'gut-milk-immune' pathway mechanisms.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eExperimental animals\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwenty-two healthy pregnant Qinchuan cows (parity: 2 \u0026plusmn; 0.5; age: 23 \u0026plusmn; 11 months; body weight: 550 \u0026plusmn; 50 kg) were selected from the Qinchuan Cattle Breeding Farm in Shaanxi Province, China. The inclusion criteria were as follows: body condition score (BCS, on a 5-point scale) of 3.0--3.5, no history of dystocia/reproductive disorders, and expected calving dates within \u0026plusmn; 3 days of each other. The cows were fed a basal diet ad libitum for seven days prior to the experiment, with free access to water. The experimental protocol was conducted according to the Chinese National Standard GB/T 35892-2018 (Laboratory animal - Guidelines for ethical review of animal welfare) and was approved by the Animal Ethics Committee of Gansu Agricultural University (Approval No. GSAU-Eth-VMC-2024-048).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMain instruments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental equipment used included an FK-058 full-wavelength enzyme-linked immunosorbent assay (ELISA) machine from Beijing Putian Xinqiao Technology Co., Ltd., a UV spectrophotometer (725 N) from Shanghai Yuanxi Instrument Co., Ltd., a gas chromatograph (model: Agilent 8890 GC, equipped with a flame ionization detector (FID)) and a chromatographic column (DB-FFAP, 30 mm \u0026times; 0.25 mm, 0.25 \u0026mu;m) from Agilent Technologies Co., Ltd. in the United States, an AL104 electronic balance from Shanghai Mettler Toledo Instrument Co., Ltd., and a HITACHI-CT15RE Hitachi ultracentrifuge from Hitachi, Ltd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePreparation of GYP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAngelica sinensis\u003c/em\u003e, \u003cem\u003eAstragalus\u003c/em\u003e \u003cem\u003emembranaceus\u003c/em\u003e, and \u003cem\u003eLeonurus\u003c/em\u003e \u003cem\u003ejaponicus\u003c/em\u003e are dried medicinal herbs purchased from the Yellow River medicinal market in Lanzhou, Gansu Province, and are stored in Laboratory 612 of the Cognitive Building of Gansu Agricultural University. The identification of medicinal herbs was conducted by Professor Wei Yanming from the Department of Veterinary Medicine at Gansu Agricultural University. The medicinal materials were finely ground (particle size \u0026le; 80 \u0026mu;m), and the uniformity of mixing was verified (RSD\u0026lt;5%). The GYP formulation consisted of 200 g of \u003cem\u003eLeonurus\u003c/em\u003e \u003cem\u003ejaponicus\u003c/em\u003e, 50 g of \u003cem\u003eAngelica sinensis\u003c/em\u003e, and 50 g of \u003cem\u003eAstragalus\u003c/em\u003e \u003cem\u003emembranaceus\u003c/em\u003e per 300 g aliquot.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimals and Experimental Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwenty-two healthy cows that are about to give birth are selected and randomly divided into CON (basic diet) and GYP (basic diet + 300 g/d GYP) groups according to the feeding pen after the cows give birth. The experimental period lasted for a total of 7 days. During the experiment, feeding and management were carried out according to the routine procedures of the cattle farm. Disinfection was carried out once a day in the morning, and the drug feeding time was 2 noon every day. Each feeding was based on the bottom of the trough to ensure that there was no residue before the next feeding. GYP was used continuously for 7 days after delivery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample \u003c/strong\u003e\u003cstrong\u003ecollection and processing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlood sample collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore morning feeding on the eighth day after delivery, blood was collected from the cows and calves via a disposable, sterile blood collector to draw blood from the jugular vein. The blood was placed in a covered 10 mL centrifuge tube. Then, the blood samples were centrifuged at 4,000r/min for 15 minutes, the serum was separated, and the samples were stored at -80 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCollection of fecal samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn the morning of the eighth day after delivery, 10 g of fresh rectal feces was collected, frozen in liquid nitrogen, and stored at -80 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCollection of Milk Samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn the morning of the eighth day after delivery, during the first milking, the front milk was discarded, and 10 mL of middle milk was collected, which was stored at -80 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of antioxidant, immune, microbial, and short-chain fatty \u003c/strong\u003e\u003cstrong\u003eacid contents\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReproductive performance of cows and growth performance of calves\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistics on the oestrus rate, conception rate during oestrus, oestrus reversal rate, and sperm consumption rate of cows. Newborn calves and weaned calves were weighed separately, and the 20-day calf diarrhea rate, 60-day mortality rate, and calf survival rate were recorded during the experiment. The attributed score for diarrhea was as follows: 0, standard; 1, loose stool; 2, loose or some diarrhea; 3, diarrhea; and 4, severe watery diarrhea. The diarrhea rate was calculated according to the following formula: Calf diarrhea rate = (number of calves with diarrhea during the observation period \u0026divide; total number of surviving calves in the same period) \u0026times; 100%, Calf survival rate = (number of calves surviving at the end of the observation period \u0026divide; (initial number of calves at the start of the period + number of calves born during the period)) \u0026times; 100%, average daily gain percentage = (final body weight - initial body weight) \u0026divide; number of days in the period) \u0026times; 100%, preweaning weight gain percentage = ((weaning weight - birth weight) \u0026divide; birth weight) \u0026times; 100%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSerum antioxidant indicators\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGSH, MDA, and SOD assay kits built in Nanjing, China, were used to determine the antioxidant levels in the serum. The information on the reagent kit is shown in Table 1.\u003c/p\u003e\n\u003cp\u003eTable 1 Serum antioxidant index kit and its product codes.\u003c/p\u003e\n\u003ctable\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003eroject\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"378\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003eroduct name\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003eroduct number\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eGSH\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"378\"\u003e\n\u003cp\u003eReduced glutathione (GSH) assay kit (microplate method)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003eA006-2-1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eMDA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"378\"\u003e\n\u003cp\u003eMDA Determination Kit (TBA Method)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003eA003-1-2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eSOD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"378\"\u003e\n\u003cp\u003eTotal Superoxide Dismutase (T-SOD) Assay Kit (WST-1 Method)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003eA001-3-2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSerum immunoglobulin levels\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum immunoglobulin levels, including IgA, IgG, and IgM, were detected via an ELISA according to the kit instructions. The information on the reagent kit is shown in Table 2.\u003c/p\u003e\n\u003cp\u003eTable 2: Serum Immune Indicator Kit and Its Product Number.\u003c/p\u003e\n\u003ctable\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003eroject\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"378\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003eroduct name\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003eroduct number\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eIgA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"378\"\u003e\n\u003cp\u003eBovine immunoglobulin A (IgA) ELISA research kit\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003eF4042-A\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eIgG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"378\"\u003e\n\u003cp\u003eBovine immunoglobulin G (IgG) ELISA research kit\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003eF3995-A\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eIgM\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"378\"\u003e\n\u003cp\u003eBovine immunoglobulin M (IgM) ELISA research kit\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003eF6685-A\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eBacterial DNA \u003c/strong\u003e\u003cstrong\u003eextraction\u003c/strong\u003e\u003cstrong\u003e, Illumina \u003c/strong\u003e\u003cstrong\u003eMiSeq sequencing\u003c/strong\u003e\u003cstrong\u003e, and \u003c/strong\u003e\u003cstrong\u003edata processing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMicrobial DNA was extracted via the Hi Pure Fecal DNA Kit (Guangzhou Meiji Biotech, China). An ABI Gene Amp 9700 PCR thermal cycler (ABI Corporation, California, USA) was used to amplify the V3-V4 hypervariable region of the bacterial 16S rRNA gene via the primers 338F (5\u0026prime;-ACTCCTACGGGAGGCAGCAG-3\u0026prime;) and 806R (5\u0026prime;-GACTACHVGGGTWTTAAT-3\u0026prime;). The PCR product was extracted from a 2% agarose gel and purified via the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, California, USA). Quantification was performed via a fluorescence meter (Promega, USA). The purified PCR product was subjected to sequencing library preparation via the NEXTFLEX rapid DNA sequencing kit, which includes the following steps: (1) linker ligation; (2) magnetic bead method for removing dimers from the joint; (3) PCR amplification enrichment of the library template; and (4) retrieval of PCR products from magnetic beads to obtain the final library. Sequencing was performed on the Illumina PE300/PE250 platform (Shanghai Meiji Biomedical Technology Co., Ltd.).\u003c/p\u003e\n\u003cp\u003eThe optimized sequence was subsequently clustered into operational taxonomic units (OTUs) at a 97% similarity level via UPARSE 7.1 software [11]. The representative sequences of each OTU were subjected to taxonomic analysis via RDP Classifier 2.2 software and compared with the 16S rRNA gene database (Silva v138). Bacterial classification and data analysis were completed on the Meiji Cloud platform ().\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the OTUs information, alpha diversity indices including Chao1 and Shannon index were calculated with Mothur v1.30.1 [39] (http://www.mothur.org/wiki/Calculators), and the Wilcoxon rank-sum test was used to analyze intergroup differences in alpha diversity of fecal and milk microbiota. The similarity among the microbial communities in fecal samples was determined by principal coordinate analysis (PCoA) based on unweighted UniFrac dissimilarity using Vegan v2.5-3 package. The non-parametric PERMANOVA test was used to assess whether the differences in microbial community structure among sample groups were significant using Vegan v2.5-3 package; The similarity among the microbial communities in milk samples was determined by non-metric multidimensional scaling (NMDS) analysis based on abund_jaccard dissimilarity using Vegan v2.5-3 package; the non-parametric PERMANOVA test was used to assess whether the differences in microbial community structure among sample groups were significant using Vegan v2.5-3 package. The linear discriminant analysis (LDA) effect size (LEfSe) [40] (http://huttenhower.sph.harvard.edu/LEfSe) was performed to identify the significantly abundant intestinal bacterial taxa (phylum to genera) among the different groups (LDA score \u0026gt; 2, P \u0026lt; 0.05). The Analysis of Intergroup Differences [48] was performed to identify the significantly abundant milk bacterial taxa (phylum to genera) among the different groups. The co-occurrence networks were constructed to explore the internal community relationships across the samples [2]. Microbial taxa were selected for network analysis based on Spearman\u0026rsquo;s correlation over 0.6 or less than -0.6, and the P-value less than 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of SCFAs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGC conditions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe injection port temperature was 280 \u0026deg;C, and the chromatographic column heating program was as follows: the initial temperature was maintained at 60 \u0026deg;C for 2 min, then increased to 140 \u0026deg;C at a rate of 10 \u0026deg;C/min, and then increased to 170 \u0026deg;C at a rate of 3 \u0026deg;C/min. The sample was measured via the split flow method, with a split ratio of 20:1, a manual injection volume of 1 \u0026mu;L, a carrier gas of high-purity (purity\u0026gt;99%) nitrogen gas, a flow rate of 1 mL/min, a detector of FID, and a temperature of 300 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablishment of \u003c/strong\u003e\u003cstrong\u003ethe \u003c/strong\u003e\u003cstrong\u003eStandard Curve\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, six standard samples of acetic acid (20 \u0026mu;L), propionic acid (10 \u0026mu;L), n-butyric acid (5 \u0026mu;L), isobutyric acid (5 \u0026mu;L), n-valeric acid (2 \u0026mu;L), and isovaleric acid (1 \u0026mu;L) were accurately measured at a volume ratio of 20:10:5:5:2:1. The six standard solutions were then mixed evenly and diluted with ultrapure water to obtain six different concentrations (5000-fold, 4000-fold, 3000-fold, 2000-fold, 1000-fold, and 500-fold) of mixed standard solutions. A total of 20 \u0026mu;L of n-butanol was diluted with 980 \u0026mu;L of ultrapure water. If a 5000-fold dilution was used, one \u0026mu;L of the mixed standard solution was aspirated. Subsequently, 4949 \u0026mu;L of ultrapure water and 50 \u0026mu;L of internal standard diluent were added, and the concentration of the n-butanol sample was 2.1856 mmol/L. Then, n-butanol was used as the internal standard, and 1 \u0026mu;L of the sample was accurately aspirated and detected with an instrument. Finally, the standard curve is obtained by plotting the content ratio on the x-axis and the peak-to-height ratio on the y-axis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePreparation of Fecal Sample Solution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the comprehensive analysis of gut microbiota and short-chain fatty acids (SCFAs), a subset of 6 cows per group was randomly selected from the original cohort of 11 for sample collection and sequencing. A 0.20 g fecal sample was accurately placed into a 2 mL EP tube. Then, four volumes of ultrapure water were added, mixed evenly, and allowed to stand at room temperature for 20 minutes. The mixture was centrifuged at 4,000r/min at 4 \u0026deg;C for 15 minutes. The obtained supernatant was added to a 2 mL EP tube. The fecal sediment was then treated with four volumes of ultrapure water in the same manner. Then, the combined supernatant from the two operations was centrifuged again, and the resulting supernatant was aspirated to 990 \u0026mu;L. Next, 10 \u0026mu;L of n-butanol diluent was added, the mixture was mixed well, and the mixture was filtered through a 0.22 \u0026mu;m membrane. Finally, 1 \u0026mu;L was accurately transferred for GC detection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical \u003c/strong\u003e\u003cstrong\u003eanalysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data were initially organized via Excel 2021 and are presented as the means \u0026plusmn; standard errors of the means (SEMs). The experimental data were analyzed via SPSS Statistics 27.0 software. Normally distributed (Shapiro‒Wilk test, P\u0026gt;0.05) and homogeneous (Levene test, P\u0026gt;0.05) data were analyzed via an independent sample t test; parametric data were tested via the Mann‒Whitney U test. Statistical significance was defined as P\u0026lt;0.05. GraphPad Prism 9.5 software was used for plotting.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eEffects of GYP on the\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ereproductive performance of cows and growth performance of calves\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table 3, the weaning weight, average daily gain, and lactation period gain of calves in the GYP group were greater than those in the CON group. Additionally, the survival rate of calves in the GYP group reached 100%, and the diarrhea rate was 9.09% lower than that in the CON group. In terms of maternal reproductive performance, the GYP group presented a 10% increase in the conception rate during the oestrus period, a 10% decrease in the return to oestrus rate, and a 10% reduction in the semen consumption rate compared with those of the CON group (Table 4).\u003c/p\u003e\n\u003cp\u003eTable 3 Growth Performance of Calves\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.8881%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrowth performance of calves\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6318%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGYP group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4801%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCON group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.8881%;\"\u003e\n \u003cp\u003eWeaning weight, kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6318%;\"\u003e\n \u003cp\u003e129.63\u0026plusmn;20.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4801%;\"\u003e\n \u003cp\u003e119.75\u0026plusmn;25.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.8881%;\"\u003e\n \u003cp\u003eAverage daily weight gain, kg/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6318%;\"\u003e\n \u003cp\u003e0.85\u0026plusmn;0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4801%;\"\u003e\n \u003cp\u003e0.77\u0026plusmn;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.8881%;\"\u003e\n \u003cp\u003ePercentage of weight gain during lactation,\u0026nbsp;%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6318%;\"\u003e\n \u003cp\u003e4.27\u0026plusmn;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4801%;\"\u003e\n \u003cp\u003e3.39\u0026plusmn;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.8881%;\"\u003e\n \u003cp\u003eSurvival rate of calves, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6318%;\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4801%;\"\u003e\n \u003cp\u003e81.82%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.8881%;\"\u003e\n \u003cp\u003e20 d diarrhea rate of calves, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6318%;\"\u003e\n \u003cp\u003e9.09%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4801%;\"\u003e\n \u003cp\u003e22.18%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4 Reproductive Performance of Cows\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.9837%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReproductive performance of cows\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6781%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGYP group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3382%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCON group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.9837%;\"\u003e\n \u003cp\u003eCycle conception rate,\u0026nbsp;%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6781%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3382%;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.9837%;\"\u003e\n \u003cp\u003eEstrus rate, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6781%;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3382%;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.9837%;\"\u003e\n \u003cp\u003eReaction rate, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6781%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3382%;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.9837%;\"\u003e\n \u003cp\u003ePrecision consumption rate, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6781%;\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3382%;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eEffects\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of GYP on serum antioxidant levels in postpartum cows\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 1, the addition of GYP significantly increased the serum antioxidant capacity of cows (SOD activity increased by 11.88%, the GSH level increased by 12.26%, and the MDA content decreased by 21.06%). The GSH and MDA levels in the GYP group were significantly increased (P\u0026lt;0.05, Fig. 1A and 1B), whereas the SOD was significantly decreased (P\u0026lt;0.01, Fig. 1C). Compared with the CON group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of GYP on the serum immune level of cows\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 1D-F, the addition of GYP increased the serum immune ability of the cows (IgM activity increased by 4.16%, the IgG level decreased by 10.99%, and the IgA content increased by 1.62%). The IgG levels in the GYP group were significantly greater than those in the CON group (P\u0026lt;0.05, Fig. 1E), indicating that GYP can improve the immune protein levels of pregnant cows and enhance their immunity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of GYP on the immune level of breast milk\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 2, the addition of GYP\u0026nbsp;increased the immune ability of cow milk (IgM activity increased by 4.51%, the IgG level increased by 5.68%, and the IgA content increased by 16.68%). The IgG, IgM, and IgA levels in\u0026nbsp;milk from\u0026nbsp;the GYP group were significantly\u0026nbsp;greater\u0026nbsp;than those in\u0026nbsp;milk from\u0026nbsp;the CON group (P\u0026lt;0.05, Fig. 2A-C), indicating that GYP can\u0026nbsp;increase\u0026nbsp;the immune protein level in milk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of GYP on serum antioxidant levels in calves\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 3A-C, the addition of GYP resulted in a 2.96% decrease in SOD activity, a 6.23% increase in\u0026nbsp;the GSH level, and a 10.94% decrease in the MDA content in calf serum. However, there were no significant changes in GSH, SOD,\u0026nbsp;or\u0026nbsp;MDA in the GYP group compared\u0026nbsp;with\u0026nbsp;the CON group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of GYP on the immune level of calves\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 3, the addition of GYP indirectly enhanced the serum immune ability of calves (IgM activity increased by 17.26%, the IgG level increased by 12.72%, and the IgA content increased by 7.98%). The IgG level of calves in the GYP group was significantly greater than that in the CON group (P\u0026lt;0.05, Fig. 3E), indicating that feeding with GYP can indirectly improve the immunoglobulin IgG level of calves and enhance their immunity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects of GYP on the gut microbiota of postpartum cows\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigh-throughput sequencing of 16S rRNA gene\u0026nbsp;was used to characterize\u0026nbsp;changes in the gut microbiota of postpartum cows. The species accumulation curve of\u0026nbsp;the\u0026nbsp;Shannon curves was flat, indicating that the bacterial community composition between asv/otu\u0026nbsp;was\u0026nbsp;uniform and\u0026nbsp;that\u0026nbsp;the abundance difference\u0026nbsp;was\u0026nbsp;minimal, which\u0026nbsp;met\u0026nbsp;the sequencing requirements. To investigate the effect of adding GYP\u0026nbsp;to\u0026nbsp;the gut microbiota of postpartum cows, 16S rRNA gene sequencing was performed on fecal samples from postpartum cows. After quality control, an average of 77,843 sequence readings were obtained from each sample. The dilution curve analysis in Fig. 4A indicates that almost all microorganisms were detected in the feces of postpartum cows. The Venn diagram analysis in Fig. 4B shows that the total number of operable taxonomic units is 7,881, with a total of 2,861 shared. The CON group\u0026nbsp;included\u0026nbsp;2,502 endemic species,\u0026nbsp;whereas\u0026nbsp;the GYP group\u0026nbsp;included\u0026nbsp;2,418 endemic species.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAlpha Diversity Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 4C, there was no significant difference in the alpha diversity indices (ace, chao, coverage,\u0026nbsp;Sobs, Pd, Shannon, Simpson, and Pielou_e) of\u0026nbsp;the\u0026nbsp;gut microbiota between the two groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBeta\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ediversity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 4D, principal coordinate analysis (PCoA)\u0026nbsp;indicated\u0026nbsp;that effective separation can be achieved between the CON group and the GYP group.\u0026nbsp;The\u0026nbsp;effective separation\u0026nbsp;suggested\u0026nbsp;that the gut microbiota of postpartum cows, which were\u0026nbsp;treated\u0026nbsp;with GYP, and those fed\u0026nbsp;these cows typically underwent\u0026nbsp;specific changes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSpecies\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecomposition analysis\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;- Community\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003estructure atlas\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further investigate the effects of GYP on the gut microbiota of postpartum cows, species composition analysis was continued.\u003c/p\u003e\n\u003cp\u003eAs shown in\u0026nbsp;Fig.\u0026nbsp;4E, the dominant gastrointestinal microbiota at the phylum level is displayed. The phyla Bacillus\u0026nbsp;was present in\u0026nbsp;all\u0026nbsp;the\u0026nbsp;samples (GYP: 80.26% \u0026plusmn; 5.07% vs. CON: 84.40% \u0026plusmn; 4.54%), Bacteroidetes (16.46% \u0026plusmn; 4.31% vs.\u0026nbsp;12.01% \u0026plusmn; 4.48%), and Spirogyra (1.10% \u0026plusmn; 0.62% vs.\u0026nbsp;1.01% \u0026plusmn; 0.87%), which accounted for\u0026nbsp;more than\u0026nbsp;97% of the total relative abundance. Compared with\u0026nbsp;that in\u0026nbsp;the CON group, the richness of Actinobacteria in the GYP group decreased (P\u0026lt;0.05),\u0026nbsp;whereas\u0026nbsp;the richness of Proteobacteria increased (P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 4F, the dominant gastrointestinal microbiota at the family level is displayed. The families Streptococcus, Tremella, Kristensen, and Riken dominated all\u0026nbsp;the\u0026nbsp;samples. Compared with the GYP group, the CON group\u0026nbsp;presented\u0026nbsp;relatively high relative richness (P\u0026lt;0.05)\u0026nbsp;of\u0026nbsp;[Eubacterium]_coprostanoligenes_group, Clostridia_UCG-014, and unclassified_Oscillospirales,\u0026nbsp;whereas\u0026nbsp;the GYP group\u0026nbsp;presented relatively high\u0026nbsp;relative abundance (P\u0026lt;0.05) for Oscillospiraceae,\u0026nbsp;the\u0026nbsp;NK4A214_group, and UCG-002.\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 4G, the dominant gastrointestinal microbiota at the genus level is displayed. The dominant bacterial group in all the samples was UCG-005, belonging to the \u003cem\u003eRombous\u003c/em\u003e, \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e, \u003cem\u003eClostridium\u003c/em\u003e, and \u003cem\u003eRikenellaceae_RC9_gut_\u003c/em\u003e\u003cem\u003egroups\u003c/em\u003e. Compared with the GYP group, the CON group \u003cem\u003e[Eubacterium]_coprostanoligenes_group\u003c/em\u003e, \u003cem\u003eClostridia_UCG-014\u003c/em\u003e, \u003cem\u003eCoprococcus\u003c/em\u003e,\u0026nbsp;and\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eUCG-011\u003c/em\u003e had relatively high relative richness (P\u0026lt;0.05), whereas the GYP groups \u003cem\u003eUCG-002\u003c/em\u003e, \u003cem\u003eF082\u003c/em\u003e, \u003cem\u003eOscillibacter\u003c/em\u003e, \u003cem\u003eWCHB1-\u003c/em\u003e\u003cem\u003e-41\u003c/em\u003e, \u003cem\u003eColidexribacter\u003c/em\u003e, and \u003cem\u003eBrevibacillus\u003c/em\u003e. The relative richness was relatively high (P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 4H, LEfSe analysis (LDA=2) revealed that \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eF082\u003c/em\u003e, \u003cem\u003eOscillibacter\u003c/em\u003e, and\u003cem\u003e\u0026nbsp;WCHB1-41\u003c/em\u003e were significantly enriched taxa in the gut microbiota of cows enriched with GYP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of GYP on the microbiota of postpartum cow milk\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigh-throughput sequencing of 16S rRNA was used to characterize changes in the microbiota of postpartum cow milk. The species accumulation curve of the Shannon curves was flat, indicating that the bacterial community composition between asv/otu was uniform and that the abundance difference was minimal, which met the sequencing requirements. To investigate the effect of adding GYP to the microbiota of cow milk, 16S rRNA gene sequencing was performed on cow milk samples. After quality control, an average of 47,163 sequence readings were obtained from each sample. As shown in Fig. 5A, dilution curve analysis revealed that almost all microorganisms were detected in the milk of postpartum cows. The Venn diagram analysis in Fig. 5B shows that there are total of 2,329 operable taxonomic units, with 1,208 shared. The CON group included 752 endemic species, whereas the GYP group included 1,051 endemic species.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAlpha Diversity Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 5C, there was no significant difference in the alpha diversity indices (ace, chao1, coverage, sobs, Pd, Shannon, Simpson, and Pielou_e) of the milk microbiota between the two groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBeta\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ediversity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 5D, the Non-metric Multidimensional Scaling (NMDS) results demonstrate a clear separation between the CON (control) and GYP groups. Their relatively effective separation indicates that the milk microbiota of postpartum cows and normal postpartum cows underwent specific changes after intervention with traditional Chinese medicine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSpecies\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecomposition analysis\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;- Community\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003estructure atlas\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further investigate the impact of GYP on the microbiota of cow milk, species composition analysis was continued.\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 5E, the dominant milk microbiota at the phylum level is displayed. The phylum Pseudomonas was the most abundant, followed by the phylum Pseudomonas. The dominant bacterial groups in the GYP group were Pseudomonas, Bacillus, Actinobacteria, Cyanobacteria, Bacteroidetes, Sphingomonas, and Streptococcus. The dominant phyla of the CON group were Pseudomonas, Bacillus, Actinobacteria, and Cyanobacteria. Compared with that in the GYP group, the richness of the Pseudomonas phylum in the CON group decreased significantly (P\u0026lt;0.05). In contrast, the richness of Actinobacteria, Cyanobacteria, Bacteroidetes, Sphingomonas, and Vibrio showed the opposite trend (P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 5F, the dominant milk microbiota at the family level is displayed. The advantageous microbial communities of the GYP group included Chloroplast, Moraxellaceae, Saccharimonadales, and Propionibacteriaceae. The dominant microbial community in the CON group included Moraxellaceae, Sphingomonadaceae, Pseudomonadaceae, Burkholderiaceae, Comamonadaceae, unclassified bacteria, and Staphylococcaceae. Compared with the GYP group, the CON group presented an increase in the richness of Sphingomonadaceae (P\u0026lt;0.05). In contrast, the GYP group presented an increase in the richness of Propionibacterium, Devosiaceae, Lactobacillus, Saccharimonadaceae, and Longimicrobiaceae (P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 5G and 5H, the dominant milk microbiota at the genus level is displayed. Compared with the CON group, the GYP group presented an increase in the richness of \u003cem\u003eAcetobacter\u003c/em\u003e, \u003cem\u003eDevosia\u003c/em\u003e, \u003cem\u003eMoraxella\u003c/em\u003e,\u003cem\u003e\u0026nbsp;TM7a\u003c/em\u003e, \u003cem\u003eRhodospirillales\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eTetrasperera\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e\u003cem\u003e-UGC-003\u003c/em\u003e, and\u003cem\u003e\u0026nbsp;Mesohizobium\u003c/em\u003e (P\u0026lt;0.05). Compared with that in the GYP group, the richness of Caulobacter in the CON group tended to increase (P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of GYP on SCFAs in postpartum cows\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablishment of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSCFAs determination method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRetention time and chromatographic peaks of SCFAs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the chromatographic conditions in \u0026ldquo;GC conditions\u0026rdquo;, 1 \u0026mu;L of the mixed standard or sample solution was taken separately. The residence time results are shown in Table 5. The peak separation of each component was good, the baseline was smooth, and the retention times of the standard and sample corresponded well (Fig. 6).\u003c/p\u003e\n\u003cp\u003eTable 5 Retention times of six SCFAs and n-butanol (internal standard)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCFAs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeak time/minute (standard)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeak time/minute (sample)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eN-butanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e5.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e5.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eAcetic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e9.284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e9.307\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003ePropionic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e10.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e10.267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eIsobutyric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e10.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e10.556\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eN-butyric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e11.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e11.395\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eIsovaleric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e11.942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e11.940\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eN-valeric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e13.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e13.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eLinear\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003erelationship testing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regression equations, linear ranges, and correlation coefficients of acetic acid, propionic acid, isobutyric acid, n-butyric acid, isovaleric acid, and n-valeric acid were obtained according to the chromatographic conditions of \u0026ldquo;GC conditions\u0026rdquo; with the ratio of the content as the horizontal coordinate (X) and the ratio of the peak height as the vertical coordinate (Y). The mixed standard solution was diluted into different gradients of mixed standards, and the concentrations of individual standards at each shaving were calculated. As shown in Table 6, the substances exhibited good linear relationships, with correlation coefficients greater than 0.99.\u003c/p\u003e\n\u003cp\u003eTable 6 Regression Equations for Six SCFAs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2873%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCFAs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.9318%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003cstrong\u003eegression equation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6715%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eL\u003c/strong\u003e\u003cstrong\u003einear range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27.1095%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelation\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2873%;\"\u003e\n \u003cp\u003eAcetic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.9318%;\"\u003e\n \u003cp\u003eY=0.31687458X-0.0885057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6715%;\"\u003e\n \u003cp\u003e1.6260~8.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27.1095%;\"\u003e\n \u003cp\u003e0.99852\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2873%;\"\u003e\n \u003cp\u003ePropionic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.9318%;\"\u003e\n \u003cp\u003eY=1.0601326X+0.0026214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6715%;\"\u003e\n \u003cp\u003e0.6274~3.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27.1095%;\"\u003e\n \u003cp\u003e0.99904\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2873%;\"\u003e\n \u003cp\u003eIsobutyric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.9318%;\"\u003e\n \u003cp\u003eY=1.59288244X+0.012189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6715%;\"\u003e\n \u003cp\u003e0.2506~1.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27.1095%;\"\u003e\n \u003cp\u003e0.99795\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2873%;\"\u003e\n \u003cp\u003eN-butyric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.9318%;\"\u003e\n \u003cp\u003eY=1.58844994X-0.0143923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6715%;\"\u003e\n \u003cp\u003e0.2532~1.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27.1095%;\"\u003e\n \u003cp\u003e0.99824\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2873%;\"\u003e\n \u003cp\u003eIsovaleric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.9318%;\"\u003e\n \u003cp\u003eY=1.3396296X-0.0029241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6715%;\"\u003e\n \u003cp\u003e0.0856~0.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27.1095%;\"\u003e\n \u003cp\u003e0.99754\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2873%;\"\u003e\n \u003cp\u003eN-valeric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.9318%;\"\u003e\n \u003cp\u003eY=3.42610113X-0.009635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6715%;\"\u003e\n \u003cp\u003e0.0423~0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27.1095%;\"\u003e\n \u003cp\u003e0.99574\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eY: peak height ratio; X: content ratio.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of adding GYP on\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSCFAs contents\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;in cows\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table 7, the total SCFAs content in the GYP group (4.923 \u0026plusmn; 1.488 mmol/L) was significantly greater than that in the CON group (3.136 \u0026plusmn; 0.914 mmol/L) (P\u0026lt;0.05), with acetic acid (+64.8%), propionic acid (+84.3%), and butyric acid (+95.9%) showing the greatest increase.\u003c/p\u003e\n\u003cp\u003eTable 7 Effect of GYP on SCFAs Content in Postpartum Cows\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003eroject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGYP\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(mmol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCON\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(mmol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP-\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eAcetic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e3.86\u0026plusmn;1.30\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e2.34\u0026plusmn;0.78\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003ePropionic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.71\u0026plusmn;0.24\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.39\u0026plusmn;0.10\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eIsobutyric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.16\u0026plusmn;0.07\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.08\u0026plusmn;0.03\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eButyric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.40\u0026plusmn;0.22\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.21\u0026plusmn;0.05\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eIsovaleric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.04\u0026plusmn;0.01\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.03\u0026plusmn;0.00\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eValeric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.16\u0026plusmn;0.01\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.10\u0026plusmn;0.03\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eTotal acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e4.92\u0026plusmn;1.49\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e3.14\u0026plusmn;0.91\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCON: postpartum cows fed basic feed; GYP: postpartum cows fed basic feed supplemented with 300 g/d GYP. Data are presented as mean \u0026plusmn; SEM (n = 6). Within a row, values with different superscript letters (a, b) differ significantly (P \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation analysis between SCFAs and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ethe\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003egut microbiota\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 7, there were 20 positive correlations (P\u0026lt;0.05) and nine negative correlations (P\u0026lt;0.05) between the relative abundance of bacterial genera and the concentration of SCFAs. Spearman\u0026apos;s correlation analysis revealed that UGC-002 was positively correlated with Oscillibacter and acetic acid, propionic acid, butyric acid, valeric acid, and isovaleric acid (P\u0026lt;0.05). Additionally, Akkermansia was positively correlated with isobutyric acid (P\u0026lt;0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOxidative stress is a significant underlying factor in the dysfunction of host immune and inflammatory responses, which increases the susceptibility of cows to various diseases, especially during the postpartum period [5; 39]. Supplementing diets with Chinese herbal medicines that possess antioxidant capacity and prebiotics can, to some extent, improve postpartum production performance in cows and calf health [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Recent studies have reported that GYP can enhance the growth performance, production performance, and immune function of livestock and poultry through mechanisms such as antioxidant, anti-inflammatory, and immunomodulatory effects [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This study also confirmed that adding GYP can significantly improve the antioxidant levels and immune function of postpartum cows. The reason may be that the active ingredients in \u003cem\u003eAstragalus membranaceus\u003c/em\u003e and \u003cem\u003eAngelica sinensis\u003c/em\u003e have antioxidant effects, which positively impact the cows' antioxidant levels [21; 45]. Increasing the activity of antioxidant enzymes and reducing the content of oxidation products within cows helps maintain their health status. Studies have shown that \u003cem\u003eAngelica sinensis\u003c/em\u003e polysaccharides have effects against cellular oxidative damage and improve immune function [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and \u003cem\u003eAstragalus membranaceus\u003c/em\u003e polysaccharides significantly impact cow antioxidant levels and immune function. \u003cem\u003eLeonurus japonicus\u003c/em\u003e extract may also have significant antioxidant effects and immune-enhancing properties [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This GYP-mediated increase in antioxidant capacity and immunity was ultimately reflected in the improvement in the cows' reproductive performance: the conception rate at first service in the GYP group increased by 10%, the return-to-estrus rate decreased by 10%, and the semen dose per conception also tended to decrease. These findings suggest that GYP provides an internal safeguard for improving reproductive efficiency by ameliorating maternal redox status and immune function.\u003c/p\u003e \u003cp\u003eThe diversity and stability of the gut microbiota are crucial for organisms. Generally, the greater the diversity of the gut microbiota is, the greater its ability to enhance the stability of the gut bacterial community [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. A decrease in diversity may reduce beneficial microorganisms and the expansion of pathogenic microbes [24; 38]. The metabolites of the gut microbiota are interconnected with the immune system, regulating immune responses [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] through direct and indirect interactions with host immune cells [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Some bacteria, including \u003cem\u003eFaecalibacterium\u003c/em\u003e and \u003cem\u003eOscillibacter\u003c/em\u003e, generate SCFAs through carbohydrate fermentation. SCFAs can regulate host immune cells and provide a carbon source for colonocytes [8; 18].\u003c/p\u003e \u003cp\u003eThrough LEfSe analysis, this study identified \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eWCHB1-41\u003c/em\u003e, \u003cem\u003eF082\u003c/em\u003e, and \u003cem\u003eOscillibacter\u003c/em\u003e as the main affected genera. Notably, these key genera are closely related to the production of SCFAs. \u003cem\u003eFaecalibacterium\u003c/em\u003e can synthesize SCFAs (especially butyrate), which not only have protective effects on digestive system health but also enhance the body's immune system, promote metabolism, and maintain intestinal barrier integrity [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Moreover, it has been reported that its abundance is significantly positively correlated with the expression levels of antioxidant-related genes [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], which is consistent with the increased antioxidant levels found in the GYP group in this study. \u003cem\u003eF082\u003c/em\u003e belongs to the Bacteroidota phylum and is involved primarily in noncellulose degradation, with its main metabolic products being propionate and butyrate [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. \u003cem\u003eOscillibacter\u003c/em\u003e is considered a potential probiotic because it plays a key role in sugar fermentation [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] and starch degradation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The products of sugar fermentation and starch degradation are SCFAs. \u003cem\u003eWCHB1\u0026ndash;41\u003c/em\u003e can degrade mucin and convert fiber-rich feed into SCFAs, providing nutrients for other bacteria and cells [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The primary function of SCFAs is to serve as the primary energy source and substrates for glucose and fat synthesis in ruminants, accounting for 70\u0026ndash;80% of their total energy requirements [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. They regulate gene expression by binding to G protein-coupled receptors (GPCRs) and inhibiting the activity of histone deacetylases (HDACs). These mechanisms are crucial for reducing local inflammation, resisting pathogen invasion, and maintaining intestinal barrier integrity [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This study revealed that the concentrations of total SCFAs, acetate, propionate, and butyrate in the GYP group were greater than those in the CON group. The reason may be closely related to the increased abundance of the key SCFAs-producing genera mentioned above: \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eF082\u003c/em\u003e, \u003cem\u003eOscillibacter\u003c/em\u003e, and \u003cem\u003eWCHB1\u0026ndash;41\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eFurthermore, Spearman correlation analysis further indicated that \u003cem\u003eOscillibacter\u003c/em\u003e, \u003cem\u003eUGC-002\u003c/em\u003e, and \u003cem\u003eAkkermansia\u003c/em\u003e were strongly correlated with SCFAs. \u003cem\u003eAkkermansia\u003c/em\u003e can increase intestinal barrier integrity, regulate immune responses, mitigate inflammatory responses, and support the proliferation of butyrate-producing bacteria [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In summary, the gut microbiota and microenvironment are interdependent. GYP promoted SCFAs production by modulating the microbiota. These SCFAs not only provide energy but also, through their immunomodulatory and barrier-protective functions, create a microenvironment conducive to the colonization and growth of beneficial bacteria while inhibiting the proliferation of harmful bacteria. Ultimately, they act synergistically to restore and maintain the integrity of the intestinal mucosal barrier.\u003c/p\u003e \u003cp\u003eCalf health is associated with milk microbiota. The dam milk calf constitutes a closely related biological system. The components of milk, a key medium, including immune factors and microorganisms, may influence the early life processes of newborn calves. Microorganisms in milk can not only promote the establishment and development of calf gut microbiota but are also related to nutrient digestion in calves.\u003c/p\u003e \u003cp\u003eThe study revealed that GYP significantly increased IgG levels in cow serum. This immune enhancement was directly reflected in the milk composition, as the contents of IgA, IgG, and IgM in the milk of the GYP group cows significantly increased. When milk from GYP group cows rich in immunoglobulins (especially IgG) was consumed, the serum IgG levels in calves significantly increased (by 12.72%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Immunoglobulins (IgA, IgG, and IgM) are important defense molecules in the body that protect calves by clearing antigens, neutralizing toxins, and preventing pathogen invasion. This increase in passive immunity was directly linked to a significant 16.6% reduction in the calf diarrhea rate, indicating that GYP indirectly but effectively enhanced the disease resistance of calves through maternal immune enhancement and vertical transmission of milk immunoglobulins.\u003c/p\u003e \u003cp\u003eThe human milk microbiota has been confirmed to promote the maturation of the intestinal epithelial barrier, immune system, and endocrine system in early life, regulating the intestinal microenvironment [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This study revealed that GYP altered the microbial composition of cow milk, increasing the abundance of key beneficial genera. Acetobacter is a primary producer of acetate in the rumen [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. \u003cem\u003eLactobacillus\u003c/em\u003e is a classic probiotic that exerts potent antibacterial activity through the production of lactic acid, organic acids, H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, or bacteriocins, thereby antagonizing pathogenic bacteria and maintaining healthy gut ecology [13; 35]. It can also improve intestinal inflammation and support the ability of beneficial microbiota to resist infection [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. \u003cem\u003ePrevotellaceae_UCG-003\u003c/em\u003e belongs to the Prevotellaceae family, whose members are involved in plant cell wall polysaccharide degradation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], protein catabolism [42; 44], etc., and are important acetate and propionate producers. Studies suggest that it may reduce inflammation and protect the intestinal barrier by lowering the concentrations of inflammatory markers (such as LPS-binding protein and C-reactive protein) [36; 49]. Through suckling, the high-abundance beneficial bacteria in milk, particularly \u003cem\u003eLactobacillus\u003c/em\u003e and \u003cem\u003ePrevotellaceae_UCG-003\u003c/em\u003e, are directly transferred to newborn calves. High-abundance incoming \u003cem\u003elactobacillius\u003c/em\u003e can rapidly colonize calf intestines, utilizing their inherent antibacterial properties to antagonize pathogens and reduce the risk of diarrhea directly. \u003cem\u003eLactobacillus\u003c/em\u003e enhances the activity of intestinal digestive enzymes (such as lactase and lipase), improving the absorption efficiency of nutrients such as colostrum by calves and assisting in establishing and strengthening intestinal immune barrier function. As a vertically transmitted key bacterium, \u003cem\u003ePrevotellaceae_UCG-003\u003c/em\u003e produces SCFAs, provides energy substrates, and is associated with the shaping of a healthy calf intestinal microenvironment and promoting barrier integrity through its potential anti-inflammatory properties and metabolic functions. This study revealed that the abundance of \u003cem\u003ePrevotellaceae_UGC-003\u003c/em\u003e in milk was significantly greater than that in milk, which echoes the high abundance of this bacterial family observed in the colon of piglets fed with breast milk by Rosa et al [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study revealed that GYP improved calf growth performance. However, its mechanism of action did not involve directly enhancing the antioxidant capacity of calves (serum SOD, GSH, and MDA levels did not significantly change). The data suggest that the core effect of GYP may involve dual vertical transmission via the maternal‒milk pathway: on the one hand, the high levels of immunoglobulins, particularly IgG, in milk provide calves with immediate passive immune protection, significantly increasing their serum IgG levels (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]; on the other hand, specific beneficial bacterial communities in milk, such as \u003cem\u003eAcetobacter\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, and \u003cem\u003ePrevotellaceae_UGC-003\u003c/em\u003e, are transferred to calves, colonizing their intestines early on and exerting antimicrobial, anti-inflammatory, digestive absorption-promoting, intestinal barrier-enhancing, and energy substrate-providing effects, thereby optimizing the intestinal microbiota structure and function. Immunoglobulins and beneficial microbial communities synergistically interact within calves to jointly establish calf health. This is directly reflected in the reduced diarrhea rate in the GYP group calves, improved growth performance, and ultimately, a calf survival rate of 100%, which is higher than the 81.82% reported in the CON group.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings demonstrate that GYP supplementation may exert multifaceted benefits through distinct pathways in both mothers and offspring. In postpartum cows, GYP significantly (1) enhances systemic antioxidant capacity (increased SOD, GSH; decreased MDA) and immune function (elevated serum and milk immunoglobulins), (2) modulates the gut microbiota composition (enriched \u003cem\u003eFaecalibacterium\u003c/em\u003e and \u003cem\u003eOscillibacter\u003c/em\u003e), and (3) increases SCFAs production. These effects collectively promote faster postpartum recovery through a proposed \u0026quot;herb-gut microbiota-immunity\u0026quot; axis. For offspring, GYP-mediated improvements in calf performance (increased weaning weight, average daily gain) and health (reduced diarrhea incidence) appear to be mediated through milk-based pathways, as evidenced by (i) elevated immunoglobulins (IgG) in calf serum and (ii) probiotic enrichment (\u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eAcetobacter\u003c/em\u003e) in maternal milk (Fig. 8).\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADG \u0026nbsp; average daily gain\u003c/p\u003e\n\u003cp\u003eBCS \u0026nbsp; body condition score\u003c/p\u003e\n\u003cp\u003eDMI \u0026nbsp; dry matter intake\u003c/p\u003e\n\u003cp\u003eFID \u0026nbsp; flame ionization detector\u003c/p\u003e\n\u003cp\u003eGSH \u0026nbsp; glutathione\u003c/p\u003e\n\u003cp\u003eGPCRs \u0026nbsp; G protein-coupled receptors\u003c/p\u003e\n\u003cp\u003eGYP \u0026nbsp; Guiqi Yimu Powder\u003c/p\u003e\n\u003cp\u003eHDACs \u0026nbsp; inhibit the activity of histone deacetylases\u003c/p\u003e\n\u003cp\u003eIgA \u0026nbsp; immunoglobulin A\u003c/p\u003e\n\u003cp\u003eIgG \u0026nbsp; immunoglobulin G\u003c/p\u003e\n\u003cp\u003eIgM \u0026nbsp; immunoglobulin M\u003c/p\u003e\n\u003cp\u003eMDA \u0026nbsp; malondialdehyde\u003c/p\u003e\n\u003cp\u003eNEB \u0026nbsp; negative energy balance\u003c/p\u003e\n\u003cp\u003eNMDS \u0026nbsp; Non-metric multidimensional scaling，\u003c/p\u003e\n\u003cp\u003eOTUs \u0026nbsp; Operational taxonomic units\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePCoA \u0026nbsp; Principal co-ordinates analysis\u003c/p\u003e\n\u003cp\u003eSCFAs \u0026nbsp; short-chain fatty acids\u003c/p\u003e\n\u003cp\u003eSEM \u0026nbsp; Standard error of the mean\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSOD \u0026nbsp; superoxide dismutase\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eB.K., W.M. and Y.H. designed the study; X.Y., H.Z. and B.K. performed the research and analyzed the data with the support of Y.H. in statistics; P.J., W.M., Y.W. and Y.H. supervised the project; B.K. prepared and wrote the original draft; Y.H. and Y.W. reviewed the paper. All the authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the China Agriculture Research System of MOF and MARA (CARS-37) and the Fuxi Foundation of Gansu Agricultural University (No. Gaufx-03J01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequence files determined in the present study were deposited at the Sequence Read Archive (SRA; http://www.ncbi.nlm.nih.gov/subs/ (accessed on 01 January 2026); SRA accession number: PRJNA1333447).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental protocol was conducted by the Chinese National Standard GB/T 35892-2018 (Laboratory animal - Guidelines for ethical review of animal welfare) and was approved by the Animal Ethics Committee of Gansu Agricultural University (Approval No.: GSAU-Eth-VMC-2024-048).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBai F, Bi S, Yue S, Xu D, Fu R, Sun Y et al. 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Fish Shellfish Immunol. 2018;75(48-57. doi:10.1016/j.fsi.2018.01.046.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"animal-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"amic","sideBox":"Learn more about [Animal Microbiome](http://animalmicrobiome.biomedcentral.com)","snPcode":"42523","submissionUrl":"https://submission.nature.com/new-submission/42523/3","title":"Animal Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Guiqi Yimu powder, SCFAs, Growth performance, Gut microbiota, Milk microbiota, Calf health","lastPublishedDoi":"10.21203/rs.3.rs-7702358/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7702358/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study evaluated the effects of dietary supplementation with Guiqi Yimu powder (GYP) on the postpartum health of cows and the growth performance of their calves, with an emphasis on immune function, antioxidant capacity, and the bacterial flora. Twenty-two postpartum cows were randomly assigned to either a control group (CON; basal diet) or a GYP group (basal diet\u0026thinsp;+\u0026thinsp;GYP). After 7 d of supplementation, the serum samples from the cows and calves were analyzed for antioxidant indices [superoxide dismutase (SOD), malondialdehyde (MDA), and glutathione (GSH)] and immunoglobulins [IgA, IgM, and IgG]. Fecal samples from cows were assessed for gut microbiota diversity and short-chain fatty acids (SCFAs) content; milk samples were analyzed for microbial composition and immunoglobulins. Compared with those in the CON group, calves in the GYP group presented significantly greater weaning weights and average daily gains. The calf survival rate tended to increase, whereas the incidence of diarrhea tended to decrease in the GYP group. Among cows in the GYP group, both postpartum conception rates and estrus rates tended to increase; conversely, return-to-estrus rates and semen doses per conception tended to decrease. Serum levels of superoxide dismutase (SOD) and glutathione (GSH) were elevated, whereas malondialdehyde (MDA) levels were reduced (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in GYP cows. Moreover, supplementation with GYP significantly increased the serum IgG levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), the milk IgM, IgA, and IgG levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the serum IgG levels in calves (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Analysis of the gut microbiota of these cows revealed that, compared with CON, GYP improved the gut bacterial diversity and increased the relative abundances of \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eg_norank_f_F082\u003c/em\u003e, and \u003cem\u003eOscillibacter\u003c/em\u003e. Furthermore, examination of the milk microbiota revealed that GYP increased the relative abundances of \u003cem\u003eAcetobacter\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, and \u003cem\u003ePrevotellaceae_UCG-003\u003c/em\u003e. In addition, compared with CON, GYP significantly increased the contents of short-chain fatty acids (SCFAs), including acetic acid, propionic acid, isobutyric acid, n-butyric acid, isovaleric acid, and n-valeric acid, in the feces of postpartum cows (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). GYP improves postpartum cow health and calf performance via (1) direct antioxidant and immunomodulatory effects, (2) gut microbiota remodeling and SCFAs promotion, and (3) vertical transfer of immunoglobulins and probiotics through milk. These findings support the use of GYP as a functional feed additive for optimizing postpartum management in beef cattle.\u003c/p\u003e","manuscriptTitle":"Enhancement of Postpartum Cow Health and Calf Performance through Maternal‒Offspring Interactions: Effects on the Immunity, Antioxidants, and Bacterial Flora Induced by Guiqi Yimu Powder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-15 07:18:22","doi":"10.21203/rs.3.rs-7702358/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-04T09:06:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-04T16:57:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-21T05:25:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31561219176330194917000239480888398204","date":"2026-01-15T15:20:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"193139794920868199860854738224893710458","date":"2026-01-15T06:39:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-13T10:00:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"111356087340446054651969838745903538854","date":"2026-01-13T09:02:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324428634177732238367011256315911483568","date":"2026-01-13T09:00:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-13T08:47:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-04T03:55:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-31T18:12:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Animal Microbiome","date":"2025-10-31T05:32:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"animal-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"amic","sideBox":"Learn more about [Animal Microbiome](http://animalmicrobiome.biomedcentral.com)","snPcode":"42523","submissionUrl":"https://submission.nature.com/new-submission/42523/3","title":"Animal Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"62334984-87aa-4f66-a9c9-828a9c3ad589","owner":[],"postedDate":"January 15th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T22:39:05+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-15 07:18:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7702358","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7702358","identity":"rs-7702358","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}