Objective To construct an index system for assessment of schistosomiasis transmission risk following natural disasters such as rainstorms, floods, earthquakes, mudslides, and landslides, so as to provide insights into rapid identification of schistosomiasis transmission risk post-disasters and formulation of targeted schistosomiasis control strategies. Methods An initial framework for the index system for assessment of schistosomiasis transmission risk following natural disasters was drafted through literature review, brainstorming, and focus group discussions. Two rounds of expert correspondence consultations were conducted using the Delphi method to refine and finalize the system, and the degrees of expert activeness, authority and endorse ment, and consensus were evaluated. In addition, the weights of each index were calculated using the analytic hierarchy process. Results A total of 18 experts participated in the consultation. The expert positive coefficients were 100.00% and 94.44% for two rounds of consultations, with authority coefficients of 0.92 and 0.94, respectively. The coefficients of coordination on the index importance, rationality and operability were 0.209, 0.185, 0.222 and 0.407, 0.214, 0.257 for two rounds of consultations, respectively, and all consistency tests were statistically significant (χ² = 246.771 to 505.278, all P values < 0.001). Following two rounds of expert consultations, an index system consisting of 6 first-level indicators, 15 second-level indicators, and 49 third-level indicators was ultimately constructed. In terms of first-level indicators, “disaster situation”, “previous epidemics”, “healthcare guarantee”, “response capacity” and “emergency recovery” had the highest weights, each at 18.18%. Regarding second-level indicators, “Schistosoma japonicum infections in animals”, “S. japonicum infections in snails” and “medical treatment” had the highest weights, each at 7.35%. In terms of third-level indicators, ten items had the highest weights, including “identification of schistosomiasis cases”, “detection of S. japonicum infections in wild feces”, “detection of S. japonicum infections in snails”, “reserves of schistosomiasis diagnostic/testing reagents and consumables”, “reserves of chemotherapy agents for human and animal schistosomiasis”, “reserves of cercariacides”, “periodical surveillance on schistosomiasis”, “identification of schistosomiasis transmission risk and timely response”, “normal provision of diagnosis and treatment services” and “post-disaster schistosomiasis surveillance”, each at 2.40%. Conclusion A scientific, systematic, and practical index system has been constructed for assessment of schistosomiasis transmission risk following natural disasters, which may provide insights into rapid post-disaster identification of schistosomiasis transmission risk, formulation of targeted schistosomiasis control strategies and optimization of resource allocation.

ObjectiveTo construct an automatic measurement model for palmar tilt and radial inclination suitable for traditional Chinese medicine （TCM） clinical scenarios， and to validate its accuracy and efficiency in TCM manipulative reduction settings. MethodsData on anteroposterior （AP） and lateral X-rays of distal radius fractures were collected from patients admitted to 18 TCM/ integrated TCM and western medicine hospitals in Jiangsu province between September 1st， 2023， and September 1st， 2024， via the Jiangsu Diagnosis and Treatment Big Data Platform for TCM Dominant Diseases. A medical image segmentation framework based on multi-scale feature fusion and edge-awareness was employed， combined with anatomical knowledge specific to TCM orthopedics， to optimize the feature extraction strategy of an artificial intelligence （AI） model. This framework enabled automatic segmentation of fracture regions and measurement of distal radius palmar tilt and radial inclination. The accuracy of the AI model in measuring radial inclination and volar tilt was validated， and the measurement time and average time gain rate of the AI model were compared to those of manual measurement. ResultsA total of 15,444 AP and lateral X-ray images of distal radius fractures were collected， and were divided into a training set （11,144 images， 5066 AP and 6078 lateral）， a validation set （3700 images， 1840 AP and 1860 lateral）， and an independent test set （600 images， 300 AP and 300 lateral） after preprocessing. In the measurement of 300 AP X-rays in the independent test set for radial inclination， when the degree error between AI measurement and manual measurement was ＜3° and ＜5°， AI measurement accuracy was 83% and 93%， respectively. In 300 lateral X-rays in the test set for palmar tilt， when AI measurements had an error of ＜3° and ＜5° compared to manual measurements， corresponding accuracy rate was 78% and 90%， respectively. For 50 X-ray images， AI measurement time was （1.37±0.05） min for radial inclination while manual measurement time was （22.57±2.52） min （P＜0.001）； in terms of palmar tilt， the AI measurement time was （1.33±0.14） min， shorter than （23.70±2.80） min for manual measurement time （P＜0.001）. Average time gain rates for manual and AI measurements were 93.93% and 94.39% respectively. ConclusionAn automatic measurement model for palmar tilt and radial inclination in distal radius fractures has been established， enabling more accurate and efficient assessment as well as providing a tool to support the quantitative evaluation of the efficacy of TCM manipulative reduction and large-sample clinical research.

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.

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.

Objective: To investigate the association between brain and muscle Arnt like protein 1( BMAL 1) gene and ambulatory blood pressure (ABP) parameters in college students, and to explore the influence of the interaction between the gene and weight status on the ABP levels, so as to provide reference for early prevention of chronic cardiovascular diseases related to hypertension. Methods: During September 2022 to June 2024, a total of 510 college students were recruited from a university in Changsha, China for on site questionnaire investigation, physical examination, ABP monitoring and genotyping testing. Multiple linear regression method was used to explore the association between the BMAL 1 gene and ABP indicators. An interaction term was included in the general linear model of multiple linear regression to analyze the interactive effects of BMAL 1 gene polymorphisms and weight status on ABP levels. Results: The prevalence of abnormal 24 hour blood pressure, abnormal daytime blood pressure, and abnormal nighttime blood pressure were 3.3%, 3.1%, and 3.9%, respectively. Multiple linear regression analysis showed that the BMAL 1/rs7950226 polymorphism was positively correlated with the 24 hour diastolic blood pressure(DBP) and the daytime DBP level after adjusting for gender, age, and body mass index( β =0.87,0.99, both P <0.05). Also, interaction between BMAL 1/ rs 11022775 and weight status on the nighttime DBP level ( P interaction =0.03) was found. The CC genotype carriers had significantly higher nighttime DBP level ( β =3.52, P <0.05) among overweight/obesity college students, but no differences in nocturnal DBP levels were observed between CC genotype carriers and TT+CT genotype carriers among college students with normal body weight( P > 0.05). Conclusions The rs 7950226 polymorphism is associated with 24 hours DBP and daytime DBP levels. Significant interaction between rs 11022775 with weight status on the nighttime DBP level is found among college students.

ObjectiveTo establish the mouse models of psoriasis-like lesions induced by continuous cold exposure or intermittent cold exposure combined with imiquimod （IMQ）， and to evaluate the interventional effects of Kaixuan Jiedu core prescription （KXJD） on the two models. MethodsMale C57BL/6J mice were selected and classified into two experimental batches. The first batch of 36 mice was randomized into a room temperature group， a continuous cold exposure （10 ℃/24 h） group， and an intermittent cold exposure （10 ℃/6 h） group. Each group was further divided into a normal subgroup and a model subgroup （topical application of IMQ to induce skin lesions）， with 6 mice in each subgroup， for modeling and evaluation. The second batch of 54 mice， with 6 in each group， were subjected to the same temperature grouping with an additional KXJD （30.42 g·kg^-1， continuous gavage for 5 days） group. Comprehensive evaluation of model characteristics and KXJD efficacy was conducted through Psoriasis Area and Severity Index （PASI） scoring， skin temperature measurement by infrared thermography， histopathological observation by hematoxylin-eosin （HE） staining， detection of vascular endothelial growth factor （VEGF） and platelet endothelial cell adhesion molecule 1 （CD31） by immunohistochemistry， detection of Claudin-1 and Occludin by immunofluorescence assay， determination of serum levels of tumor necrosis factor-α （TNF-α） and interleukin （IL）-10 by enzyme-linked immunosorbent assay （ELISA）， and quantification of mRNA levels of IL-17A， IL-23， IL-6， and chemokine ligand 20 （CCL20） in skin lesions by quantitative Real-time polymerase chain reaction （Real-time PCR）. ResultsModel mice in all temperature groups exhibited typical psoriasis-like skin lesions. Compared with the normal groups， the model groups showed increased PASI scores， decreased skin temperatures （P<0.05）， obvious epidermal thickening， parakeratosis， and dermal inflammatory cell infiltration， as well as elevated mRNA levels of IL-17A， IL-23， IL-6， and CCL20 （P<0.05）. Cold exposure further aggravated psoriasis. The total PASI score of the intermittent cold exposure model group was higher than that of the room temperature model group （P<0.05）. The serum IL-10 did not show a compensatory elevation， and the blood vessels presented a characteristic of elevated CD31 expression （P<0.05） without a synchronous increase in VEGF. The continuous cold exposure model group exhibited more significant dermal capillary tortuosity and dilation， with the highest mRNA levels of IL-17A， IL-23， IL-6， and CCL20 among all groups. Compared with the respective model groups， KXJD intervention alleviated skin lesions， reduced epidermal thickness and inflammatory cell infiltration， and increased skin temperature， with the temperature increase being particularly significant in the intermittent cold exposure+KXJD group （P<0.05）. Furthermore， KXJD down-regulated the expression of VEGF and CD31， restored the expression of Claudin-1 and Occludin， decreased the mRNA levels of IL-17A and IL-23 （P<0.05）， and reduced the serum TNF-α level. ConclusionThis study successfully established compound psoriasis-like mouse models induced by cold exposure combined with IMQ. It confirms that cold aggravates the severity of psoriasis by exacerbating the closure of Xuanfu （sweat pores）， microcirculation disorders， and immune imbalance. Moreover， different cold exposure patterns have distinct mechanism differences. Continuous cold exposure focuses on enhancing the inflammatory response via the IL-23/IL-17 axis and angiogenesis， simulating chronic aggravation under a long-term cold environment. Intermittent cold exposure tends to impair immune regulation and induce microvascular endothelial stress， corresponding to acute exacerbations caused by sudden temperature drops. KXJD can effectively alleviate psoriasis-like skin lesions under cold conditions by unblocking Xuanfu， regulating vasomotor function， and correcting abnormal immune-inflammatory responses.

ObjectiveTo investigate the ameliorative effect and potential mechanisms of Kaixuan Jiedu core prescription （KXJD） on imiquimod （IMQ）-combined restraint stress-induced psoriasis-like skin lesions in mice. MethodsA total of 36 C57BL/6J mice were randomly assigned to six groups （n=6 per group）： Normal group， restraint stress blank group， model group， restraint stress model group， KXJD group （30.42 g·kg^-1）， and methotrexate group （0.001 g·kg^-1）. Psoriasis-like lesions were induced by topical IMQ application combined with restraint stress. After 5 days of intervention， the severity of skin lesions was evaluated using the Psoriasis Area and Severity Index （PASI）. The following parameters were assessed： Hypothalamic-pituitary-adrenal （HPA） axis-related hormones， including adrenocorticotropic hormone （ACTH）， corticotropin-releasing hormone （CRH）， and corticosterone （CORT）， central neuronal markers， including neuronal nuclei antigen （NeuN）， microtubule-associated protein 2 （MAP2）， and beta Ⅲ-tubulin （β-Ⅲ tubulin）， microglial activation markers， including ionized calcium-binding adapter molecule-1 （Iba-1） and cluster of differentiation 11b （CD11b）， and skin nerve fiber markers， including protein gene product 9.5 （PGP9.5） and serotonin （5-HT）， as well as the expression levels of inflammatory cytokines tumor necrosis factor-alpha （TNF-α）， interleukin-6 （IL-6）， and interleukin-1 beta （IL-1β）. ResultsCompared with the normal group， both the model group and the restraint stress model group exhibited more severe psoriasis-like skin lesions， with significantly elevated serum levels of ACTH， CRH， and CORT （P<0.01）. The expression of glucocorticoid receptor （GR） and corticotropin-releasing hormone receptor 1 （CRHR1） in the skin was significantly downregulated. The expression of NeuN， MAP2， β-Ⅲ tubulin， Iba-1， and CD11b in the hypothalamus and hippocampus was significantly upregulated， suggesting abnormal changes in neuronal number or structure and aberrant activation of glial cells （P<0.05， P<0.01）. In addition， the expression of PGP9.5 and 5-HT in the skin， as well as the mRNA levels of TNF-α， IL-6， and IL-1β were all markedly elevated （P<0.05， P<0.01）. Compared with the model group， the restraint stress model group showed further exacerbation in most parameters. Compared with the restraint stress model group， the KXJD group exhibited significantly reduced PASI scores （P<0.01）， significantly decreased serum CRH， ACTH， and CORT levels （P<0.05， P<0.01）， upregulated skin GR and CRHR1 expression， inhibited abnormal neuronal changes and microglial activation in the hypothalamus and hippocampus， attenuated skin nerve fiber hyperplasia and amine signaling molecule release， and significantly reduced pro-inflammatory cytokine mRNA expression （P<0.05， P<0.01）. ConclusionKaixuan Jiedu Core prescription can effectively ameliorate IMQ combined with restraint stress-induced psoriasis-like skin lesions in mice by modulating HPA axis function， inhibiting central neuropathological changes， and attenuating skin nerve fiber hyperplasia， amine signaling molecule （5‑HT） release and local inflammatory responses.

Objective On the basis of the theory of the tumor metastatic state, this work aims to explore the metastasis trajectories and peripheral immune response patterns in patients with non-small cell lung cancer (NSCLC) receiving vital qi-strengthening and toxin-eliminating therapy (Fuzheng Juandu) and reveal the value of peripheral immunity in assessing vital qi deficiency during metastasis. Methods A retrospective study design was adopted. Patients with NSCLC admitted from January 1, 2018, to October 31, 2025 were enrolled. Data on metastasis status and peripheral immune indices were collected at the follow-up time points of one, two, three, and five years. Group-based trajectory modeling was used to fit metastasis trajectories, and the independent predictors of trajectory grouping were analyzed through multifactor and multiclassification logistic regression. Results A total of 184 patients with NSCLC were included, and three different groups of metastasis trajectories were identified, namely, the low-risk stable (46.74%, n=86), low-risk rising (13.59%, n=25), and high-risk stable (39.67%, n=73) groups. Univariate analysis revealed substantial differences in peripheral immune indices among the three trajectory groups. Multivariate analysis showed that TNM stage, absolute neutrophil count, lymphocyte count, absolute monocyte count, platelet volume, SAA:CRP ratio, and NLR were independent predictors of the low-risk rising group, whereas TNM stage, absolute monocyte count, basophil count, SII, and NLR were independent predictors of the high-risk stable group. Conclusion Under Fuzheng Juandu therapy, patients with NSCLC exhibit three distinct metastasis trajectories, each corresponding to a specific peripheral immune response pattern. Elucidating these peripheral immune response patterns may facilitate the objective quantification of the degree of vital qi deficiency, prediction of future metastasis risk, and providing an important reference for the individualized clinical implementation of Fuzheng Juandu therapy.

ObjectiveTo investigate the mechanism of action of modified Shaofu Zhuyutang in antagonizing cellular pyroptosis and fibrosis in ectopic endometrial tissues of endometriosis through the Toll-like receptor 4/nuclear factor-κB/NOD-like receptor protein 3 （TRL4/NF-κB/NLPR3） signaling pathway. MethodsSeventy-two SPF-grade female SD rats were randomly divided into a sham-operated group （n = 12） and a modeling group （n = 60）. The rats in the sham-operated group underwent a caesarean section， while the rats in the modeling group were used to establish an endometriosis model through the auto-transplantation method. After successful modeling， the animals were randomly divided into the model group， progesterone group （0.25 mg·kg^-1）， and modified Shaofu Zhuyutang low-， medium-， and high-dose groups （7.5， 15， 30 g·kg^-1）， with 12 animals in each group. After 4 weeks of drug administration， voluntary activity and heat pain latency were observed. The rats were sacrificed for tissue collection， and Masson staining were used to observe histopathological changes in the endometrial tissues. Enzyme-linked immunosorbent assay （ELISA） was used to measure serum levels of interleukin-18 （IL-18）， interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， and transforming growth factor-β （TGF-β）. Immunohistochemistry （IHC） was used to detect the protein expression area of tumor necrosis factor-related factor 6 （TRAF6） and NLPR3 in the endometrial tissues. Immunofluorescence （IF） was used to detect the relative fluorescence intensity of Caspase-1 and gasdermin D （GSDMD） in the endometrial tissues. Western blot was employed to measure the relative expression of TRL4， myeloid differentiation factor 88 （MyD88）， TRAF6， NF-κB p65， phosphorylated NF-κB p65 （p-NF-κB p65）， and NLPR3 proteins in endometrial tissues. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of TRL4， MyD88， TRAF6， NF-κB， and NLPR3 in the endometrial tissues. ResultsCompared with the sham-operated group， rats in the model group showed reduced voluntary activity and shorter heat pain latency. Serum levels of IL-18， IL-1β， TNF-α， and TGF-β were elevated. The relative expression areas of TRAF6 and NLPR3 proteins were increased， and the relative fluorescence intensity of Caspase-1 and GSDMD was enhanced. The relative expression of TRL4， MyD88， TRAF6， NF-κB p65， p-NF-κB p65， and NLPR3 proteins， along with the expression of TRL4， MyD88， TRAF6， NF-κB， and NLPR3 mRNA， were significantly increased （P<0.01）. Compared with the model group， rats in the progesterone group and the modified Shaofu Zhuyutang medium- and high-dose groups exhibited improved voluntary activity， longer heat pain latency， the fibrosis of endometrial tissue is alleviated. Serum levels of IL-18， IL-1β， TNF-α， and TGF-β were decreased. The relative expression areas of TRAF6 and NLPR3 proteins decreased， and the relative fluorescence intensity of Caspase-1 and GSDMD weakened. The relative expression of TRL4， MyD88， TRAF6， p-NF-κB p65， NLPR3 proteins， and TRL4， MyD88， TRAF6， NF-κB， and NLPR3 mRNA expression were reduced （P<0.05， P<0.01）. ConclusionModified Shaofu Zhuyutang may play a therapeutic role in endometriosis by interfering with key proteins in the TRL4/NF-κB/NLPR3 signaling pathway， reducing NLRP3 inflammasome-induced cellular pyroptosis， antagonizing the fibrosis process in ectopic endometrial tissues， improving the inflammatory microenvironment in the pelvic cavity， and alleviating pain.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.