The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTo evaluate the impact of yang-reinforcing and blood-activating therapy on the long-term prognosis for patients with dilated cardiomyopathy （DCM） of yang deficiency and blood stasis syndrome. MethodsA retrospective cohort study was conducted involving 371 DCM patients with yang deficiency and blood stasis syndrome. The yang-reinforcing and blood-activating therapy was defined as the exposure factor. Patients were categorized into exposure group （186 cases） and non-exposure group （185 cases） according to whether they received yang-reinforcing and blood-activating therapy combined with conventional western medicine for 6 months or longer. The follow-up period was set at 48 months， and the Kaplan-Meier survival analysis was used to assess the cumulative incidence of major adverse cardiovascular events （MACE） in both groups. Cox regression analysis was used to explore the impact of yang-reinforcing and blood-activating therapy on the risk of MACE， and subgroup analysis was performed. Changes in traditional Chinese medicine （TCM） syndrome score， left ventricular ejection fraction （LVEF）， left ventricular fractional shortening （LVFS）， left ventricular end-diastolic diameter （LVEDD）， and Minnesota Living with Heart Failure Questionnaire （MLHFQ） score were compared between groups at the time of first combined use of yang-reinforcing and blood-activating therapy （before treatment） and 1 year after receiving the therapy （after treatment）. ResultsMACE occurred in 31 cases （16.67%） in the exposure group and 47 cases （25.41%） in the non-exposure group. The cumulative incidence of MACE in the exposure group was significantly lower than that in the non-exposure group ［HR=0.559， 95%CI（0.361，0.895）， P=0.014］. Cox regression analysis showed that yang-reinforcing and blood-activating therapy was an independent factor for reducing the risk of MACE in DCM patients ［HR=0.623， 95%CI（0.396，0.980）， P=0.041］， and consistent results were observed in different subgroups. Compared with pre-treatment， the exposure group showed decreased TCM syndrome score and MLHFQ score， reduced LVEDD， and increased LVEF and LVFS after treatment （P＜0.05）； in the non-exposure group， TCM syndrome score decreased， LVEF and LVFS increased， and LVEDD reduced after treatment （P＜0.05）. After treatment， the exposure group had higher LVEF and LVFS， smaller LVEDD， and lower TCM syndrome score and MLHFQ score compared with the non-exposure group （P＜0.05）. ConclusionCombining yang-reinforcing and blood-activating therapy with conventional western medicine can reduce the risk of MACE in DCM patients with yang deficiency and blood stasis syndrome， meanwhile improving their clinical symptoms， cardiac function， and quality of life.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

Background/Aims: Chronic constipation is prevalent yet under-diagnosed across Asia, compromising quality of life and burdening healthcare systems. Cultural stigma, varied diets, and limited access to standardized diagnostic tools delay timely care. Methods: The Bali Chronic Constipation Roundtable in November 2024, brought together experts from 11 Asian countries. The group reviewed epidemiological data, analyzed multinational questionnaire on clinical practice pattern, and conducted structured discussions to identify key barriers and propose region-specific recommendations. Results: Chronic constipation prevalence varies across Asia, ranging from 1.8% in India to 16.6% in Japan, with women and the elderly disproportionately affected. Under-reporting persists owing to cultural taboos and widespread self treatment with laxatives and traditional medications. Although the Rome IV criteria remains the global standard, they may not fully reflect Asian symptom profiles, and diagnosis is limited by scarce motility laboratories. First line therapies such as dietary-fiber optimization and osmotic laxatives are widely available, but newer pharmacotherapies (prucalopride, linaclotide, lubiprostone, and elobixibat) remain costly and unevenly accessible. Biofeedback for dyssynergic defecation is underutilized due to limited availability. Experts recommend expanded regional research on to refine diagnostic criteria, coupled with enhanced physician education and public awareness. They advocate accessibility to second-line and novel therapies that incorporate culturally attuned regional guidelines, and improved access to gastrointestinal motility testing. Conclusions The Bali Chronic Constipation Roundtable highlighted Asia’s need for region specific diagnostics and management. Addressing diagnostic and treatment gaps will improve outcomes, while ongoing researcher clinician policy collaboration must standardize guidelines, advance research, and ensure equitable care across Asia.

Objective We aimed to evaluate the efficacy and safety of Shengxuebao Mixture in the treatment of cancer-related anemia(CRA)presenting with syndrome of deficiency of liver and kidney combined with syndrome of deficiency of both qi and blood.Methods A randomized,double-blind,placebo-controlled,multicenter clinical trial was conducted.Eligible patients with malignant tumors meeting the inclusion and exclusion criteria were enrolled from 26 hospitals,including Dongzhimen Hospital,Beijing University of Chinese Medicine,Xiaogan Central Hospital,and Yangzhou Hospital of Traditional Chinese Medicine,from June 1,2022,to September 30,2024.Patients were allocated 1:1 to either the experimental group receiving Shengxuebao Mixture or the control group receiving its simulator(placebo)using a block randomization method under double-blind conditions.Both groups received 15 mL orally three times daily for 28 consecutive days.The primary efficacy indicators included the hemoglobin(Hb)improvement rate(RHb)and the traditional Chinese medicine(TCM)syndrome improvement rate(RTCM)at week 4 of treatment.The secondary efficacy indicators encompassed Hb and red blood cell(RBC)count,Karnofsky Performance Status(KPS)score,TCM syndrome score,individual TCM symptom scores,and changes in each of these indicators compared to the baseline period at weeks 2,4,and 6 of treatment.Safety evaluations were conducted at week 4 of treatment.Results A total of 239 patients were enrolled,with 225 cases included in the Full Analysis Set(FAS)(109 in the experimental group vs.116 control group),163 in the Per Protocol Set(PPS)(77 vs.86),and 225 in the Safety Set(SS)(109 vs.116).Baseline characteristics between groups showed no significant differences.Significant differences were observed between the experimental and control groups in RHb at week 4(FAS:49.51%vs.35.24%,P<0.05;PPS:53.25%vs.36.05%,P<0.05)and RTCM at week 4(FAS:61.54%vs.39.62%,P<0.01;PPS:64.94%vs.40.70%,P<0.01).At weeks 2,4,and 6,the experimental group showed greater improvements in Hb and RBC counts than the control group.Additionally,the TCM syndrome scores were lower in the experimental group than in the control group at these time points.Except for week 2 in PPS,the KPS improvement was better in the experimental group than in the control group(P<0.05).The experimental group also demonstrated a greater reduction in scores for individual TCM symptoms such as spiritlessness and weakness,poor appetite and reduced food intake at weeks 4 and 6 compared to the control group(P<0.05,P<0.01).Furthermore,the reduction in vertigo score was more pronounced in the experimental group at week 6(P<0.01).For the score of pale and lusterless complexion,only in the PPS was the reduction from baseline more significant in the experimental group than in the control group at weeks 4 and 6(P<0.05).No significant differences were observed between the experimental and control groups in the incidence of all adverse events or drug-related adverse reactions.Conclusion Shengxuebao Mixture demonstrates significant efficacy in patients with CRA presenting syndrome of deficiency of liver and kidney combined with syndrome of deficiency of both qi and blood,effectively increasing Hb levels,ameliorating TCM syndromes,alleviating clinical symptoms,and enhancing functional status,with no significant difference in adverse drug reactions compared to the placebo.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To evaluate the ability of ENDOANGEL artificial intelligence system to predict invasion depth and differentiation status of early gastric cancer using more diverse multi-center videos, and to test the performance of the new system upgraded from ENDOANGEL.Methods:Based on the completed 2020 man-machine competition for early gastric cancer diagnosis using single-center videos, the second man-machine competition was conducted in 2022, involving 30 endoscopists from 30 hospitals across 10 Chinese provinces. A multi-center video cohort was retrospectively collected from 12 institutions in 8 provinces/municipalities in China. The study proceeded in 3 stages. First, the ENDOANGEL was re-tested on multi-center videos, its performance on single and multi-center videos was compared, then the ENDOANGEL was upgraded to ENDOANGEL-2022. Second, the second man-machine competition was conducted between ENDOANGEL-2022 and 30 endoscopists using multi-center videos, and the performance between ENDOANGEL-2022, ENDOANGEL and endoscopists on multi-center videos were compared. Third, the ENDOANGEL-2022 was re-tested on the single-center videos previously collected in 2020, its performance on single and multi-center videos was also compared.Results:Compared with the performance on single-center videos, the sensitivity of ENDOANGEL for predicting submucosal invasion of early gastric cancer decreased significantly [18.18% (2/11) VS 70.00% (7/10), P=0.030], but demonstrated comparable ability to predict undifferentiated type of early gastric cancer ( P>0.05). On multi-center videos, in the respect of predicting submucosal invasion of early gastric cancer, the sensitivity of ENDOANGEL-2022 was higher than that of ENDOANGEL [40.00% (4/10) VS 18.18% (2/11), P=0.361], but inferior to that of 30 endoscopists [40.00% VS 52.04% (95% CI: 43.70%-60.38%), P<0.001]. The specificity of ENDOANGEL-2022 was lower than that of ENDOANGEL [82.86% (29/35) VS 100.00% (34/34), χ2=4.41, P=0.036] and higher than that of 30 endoscopists [82.86% VS 68.97% (95% CI: 60.83%-77.11%), P=0.018], the accuracy of ENDOANGEL-2022 was lower than that of ENDOANGEL [73.33% (33/45) VS 80.00% (36/45), χ2=0.56, P=0.455] and higher than that of 30 endoscopists [73.33% VS 65.30% (95% CI: 60.61%-69.99%), P=0.018]. In the respect of predicting undifferentiated type of early gastric cancer, the sensitivity of ENDOANGEL-2022 was higher than that of ENDOANGEL [71.43% (5/7) VS 57.14% (4/7), P>0.999] and 30 endoscopists [71.43% VS 63.11% (95% CI: 55.58%-70.64%), P=0.031], the specificity of ENDOANGEL-2022 was lower than that of ENDOANGEL [76.32% (29/38) VS 78.95% (30/38), χ2=0.08, P=0.783] and higher than that of 30 endoscopists [76.32% VS 65.27% (95% CI: 59.10%-71.44%), P=0.004],the accuracy of ENDOANGEL-2022 was similar to that of ENDOANGEL [75.56% (34/45) VS 75.56% (34/45), χ2=0.00, P>0.999] and higher than that of 30 endoscopists [75.56% VS 65.10% (95% CI: 59.96%- 70.24%), P<0.001]. Compared with performance in single center videos, the sensitivity [40.00% VS 60.00%(6/10), P=0.656], specificity [82.86% VS 93.75% (15/16), χ2=0.37, P=0.542] and accuracy [73.33% VS 80.77% (21/26), χ2=0.50, P=0.479] of ENDOANGEL-2022 for predicting submucosal invasion of early gastric cancer decreased; in predicting undifferentiated type of early gastric cancer, the sensitivity of ENDOANGEL-2022 increased [71.43% VS 37.50% (3/8), P=0.315], while the specificity [76.32% VS 100.00% (18/18), χ2=3.48, P=0.062] and accuracy [75.56% VS 80.77% (21/26), χ2=0.26, P=0.612] decreased. Conclusion:Multi-center cases introduce greater heterogeneity that may reduce artificial intelligence prediction accuracy, but the artificial intelligence system still outperforms endoscopists.

This study examines the effects of zearalenone(ZEA)on the survival and function of lu-teinized granulosa cells,and studies the role of activating transcription factor 6(ATF6)in regula-ting apoptosis and functional abnormalities of luteinized granulosa cells induced by ZEA.An in vitro model of luteinized granulosa cells was utilized to examine the effects of ZEA treatment on apoptosis,hormone secretion,and the expression of relevant proteins.Furthermore,the expression of ATF6 was manipulated using siRNA to elucidate its regulatory function in the ZEA-induced damage of luteinized granulosa cells in mice.Our findings revealed that ZEA inhibited the activity of luteinized granulosa cells and reduced the secretion of estradiol(E2)and progesterone(P4)in a dose-dependent manner.The expression levels of p-IRE1,ATF6 and StAR in both low(20 pmol/L)and high(40 μmol/L)ZEA groups were significantly increased after 24 h(P＜0.05).GRP78 had no significant change at low concentration treatment(P＞0.05),but significantly increased at high concentration treatment(P＜0.05).Similarly,ATF4 and p-EIF2α had no significant change at low concentration treatment(P＞0.05),but significantly decreased at high concentration treat-ment(P＜0.05).HSD3B2 and CYP19A1 were significantly decreased in both low and high concentration treatments(P＜0.05).After 48 h of treatment,ATF6 and GRP78 were significantly increased in both low and high concentration treatments(P＜0.05).p-IRE1 was significantly de-creased at low concentration treatment(P＜0.05),but remained unchanged at high concentration treatment(P＞0.05).ATF4,p-EIF2α,HSD3B2 and CYP19A1 were significantly decreased in both low and high concentration treatments(P＜0.05).St AR was significantly increased in both low and high concentration treatments(P＜0.05).Interference with the expression of ATF6 could sig-nificantly reduce the apoptosis induced by low concentration group(P＜0.05),and enhanced the hormone secretion in both high and low concentration groups(P＜0.05).In conclusion,ZEA can cause damage to luteinized granulosa cells and activate ATF6 signaling pathway.Interference with ATF6 can alleviate apoptosis and hormone secretion disturbance induced by low concentration ZEA,but has limited effect on damage caused by high concentration ZEA.