BACKGROUND:Osteoarthritis is pathologically characterized by progressive degeneration of the articular cartilage and abnormal deformation of the subchondral bone.In recent years,with the deepening of medical research,it has been found that the mitogen-activated protein kinases(MAPK)signaling pathway has a regulatory role in inflammatory cell infiltration,inflammatory factor release,and chondrocyte proliferation,which is particularly important for the treatment of osteoarthritis.OBJECTIVE:To briefly review the main research progress in the mechanism of MAPK signaling pathway regulating osteoarthritis in recent years,aiming to provide new ideas for the treatment of osteoarthritis.METHODS:CNKI,WanFang and PubMed databases were searched for relevant literature using the search terms of"mitogen-activated protein kinases,osteoarthritis,extracellular signal-regulated MAP kinases,p38 mitogen-activated protein kinases,JNK mitogen-activated protein kinase"in Chinese and English.Relevant literature published from January 2019 to November 2024 was searched,and 108 articles were finally included for summary analysis.RESULTS AND CONCLUSION:(1)Various stimuli inside and outside the cells activate the MAPK signaling pathway,regulate gene transcription and protein synthesis,and promote the release of inflammatory factors,such as tumor necrosis factor-α,interleukin-1β,and interleukin-6.The release of these inflammatory factors aggravates the progression of osteoarthritis.(2)The active ingredients of traditional Chinese medicine,mainly saponins and flavonoids,as well as Chinese herbal formulas and preparations with the main effects of activating blood circulation and removing blood stasis,tonifying the liver and kidney,can play a therapeutic role in osteoarthritis by inhibiting the MAPK signaling pathway,regulating the release of matrix metalloproteinases,balancing the homeostatic state of osteogenesis and osteoblastogenesis,attenuating the synovial inflammation,decreasing the release of inflammatory factors and inflammatory vesicles,decreasing cellular pyroptosis,promoting autophagy,and ameliorating oxidative stress.(3)Although traditional Chinese medicine has become popular in the treatment of osteoarthritis by virtue of its own advantages of multi-components,multi-targets,multi-pathways,and low side effects,the use of MAPK signaling pathway to guide the treatment of individual osteoarthritis is the difficulty of the technology,which needs to be continuously researched and explored.(4)Therefore,further development of relevant herbal inhibitors that can modulate the MAPK signaling pathway may be a potential drug strategy for the treatment of osteoarthritis in the future.

BACKGROUND:Osteoarthritis is pathologically characterized by progressive degeneration of the articular cartilage and abnormal deformation of the subchondral bone.In recent years,with the deepening of medical research,it has been found that the mitogen-activated protein kinases(MAPK)signaling pathway has a regulatory role in inflammatory cell infiltration,inflammatory factor release,and chondrocyte proliferation,which is particularly important for the treatment of osteoarthritis.OBJECTIVE:To briefly review the main research progress in the mechanism of MAPK signaling pathway regulating osteoarthritis in recent years,aiming to provide new ideas for the treatment of osteoarthritis.METHODS:CNKI,WanFang and PubMed databases were searched for relevant literature using the search terms of"mitogen-activated protein kinases,osteoarthritis,extracellular signal-regulated MAP kinases,p38 mitogen-activated protein kinases,JNK mitogen-activated protein kinase"in Chinese and English.Relevant literature published from January 2019 to November 2024 was searched,and 108 articles were finally included for summary analysis.RESULTS AND CONCLUSION:(1)Various stimuli inside and outside the cells activate the MAPK signaling pathway,regulate gene transcription and protein synthesis,and promote the release of inflammatory factors,such as tumor necrosis factor-α,interleukin-1β,and interleukin-6.The release of these inflammatory factors aggravates the progression of osteoarthritis.(2)The active ingredients of traditional Chinese medicine,mainly saponins and flavonoids,as well as Chinese herbal formulas and preparations with the main effects of activating blood circulation and removing blood stasis,tonifying the liver and kidney,can play a therapeutic role in osteoarthritis by inhibiting the MAPK signaling pathway,regulating the release of matrix metalloproteinases,balancing the homeostatic state of osteogenesis and osteoblastogenesis,attenuating the synovial inflammation,decreasing the release of inflammatory factors and inflammatory vesicles,decreasing cellular pyroptosis,promoting autophagy,and ameliorating oxidative stress.(3)Although traditional Chinese medicine has become popular in the treatment of osteoarthritis by virtue of its own advantages of multi-components,multi-targets,multi-pathways,and low side effects,the use of MAPK signaling pathway to guide the treatment of individual osteoarthritis is the difficulty of the technology,which needs to be continuously researched and explored.(4)Therefore,further development of relevant herbal inhibitors that can modulate the MAPK signaling pathway may be a potential drug strategy for the treatment of osteoarthritis in the future.

Objective: To observe the distribution characteristics of sex differences in physical growth among children and adolescents aged 6-15 years in Taiwan, China from 2007 to 2024, so as to provide clues for improving growth assessment standards and promoting the health of children and adolescents. Methods: Using publicly available height and weight data for children and adolescents aged 6-15 years in Taiwan, China from 2007 to 2024 released by the statistics agency of the Taiwan education authorities, sex difference indices were analyzed. Growth curve charts and Pearson correlation were used to analyze the correlation between height/weight and year, as well as trends of change with age and year. These were compared with data from the 8th National Survey on Students Constitution and Health in 2019, covering Han and ethnic minority groups aged 6-15 years in mainland China. Results: The sex difference index for height among children and adolescents in Taiwan, China ranged from -1.20% to 6.67%, showed a trend of decreasing first and then increasing with age. The sex difference index for weight ranged from 3.76% to 19.15%, exhibited an age related trend of a slight initial increase, followed by a decrease, and then an increase. The sex difference indices for height in the 12-15 age groups and for weight in the 15-year-old group were positively correlated with the year ( r =0.74, 0.66, 0.61, 0.92 ; 0.63), while the sex difference indices for weight in the 6-8 age groups were negatively correlated with the year ( r =-0.71, -0.77, -0.53) (all P <0.05). In 2024, the height of children and adolescents in Taiwan, China increased gradually with age, but the growth rate for girls slowed down after age 12. A "two crossover" was observed in height between boys and girls, with boys being taller than girls in the 6-9 age range and after age 12. Weight for both sexes gradually increases with age, but boys have greater weight than girls at all ages. In 2019, the sexual differences in body size among children and adolescents in the Taiwan region, China (the sex difference indices for height:-0.96% to 6.49%；the sex difference indices for weight:4.69%-17.89%) fell within the variation ranges of counterparts in mainland China (the sex difference indices for height:-5.43% to 7.69%；the sex difference indices for weight:-10.12% to 21.56%). Conclusion The sex differences in physical growth among children and adolescents in Taiwan, China are dynamically changing with age and over the long term.

Objective: To investigate the association between screening detected myopia in primary school students and mixed exposure to air pollutants, so as to provide a scientific basis for the prevention and control of myopia in children and adolescents. Methods: From May to July 2023, a cluster random sampling method was used to select 15 102 primary school students in grades 3 through 6 from Hefei, Zhongshan, Shenyang, and Nanchang citys. Data were collected through questionnaires, distance vision screening, and computerized refraction. Monthly average concentration data for particulate matter (PM 10 ), fine particulate matter (PM 2. 5), NO 2 and SO 2 were used to calculate the annual average pollutant concentrations for primary school students. Quantile g computation model was employed to analyze the association between mixed exposure to air pollutants and screening detected myopia. Results: The differences in concentrations of the four pollutants among cities were statistically significant ( H =12 886.0, 13 285.0, 8 559.0, 13 181.0, all P <0.01). In the overall sample, there was no statistically significant association between combined exposure to air pollutants and the risk of myopia ( β=0.033, 95%CI=-0.004-0.072, P =0.08). Stratified analysis by outdoor activity time showed that among primary school students with outdoor activity time ≤1 h/d, mixed exposure to air pollutants was positively associated with the risk of myopia ( β=0.050, 95%CI=0.002-0.099, P =0.04); after stratification by city, combined exposure to air pollutants was significantly associated with the risk of myopia among primary school students in Nanchang and Shenyang [ β (95% CI )= 0.232(0.175-0.289), 0.080(0.006-0.155), both P <0.05], whereas no statistically significant association was observed among primary school students in Hefei and Zhongshan [ β (95% CI )=-0.010(-0.071-0.051), -0.032(-0.167-0.102), both P ＞ 0.05 ]. Conclusions Exposure to multiple air pollutants may increase the risk of myopia in primary school students, with the risk influenced by time spent outdoors and geographical location. It is recommended that outdoor activity management for children be strengthened in areas with higher air pollution levels, and that environmental factors be incorporated into comprehensive myopia prevention and control strategies.

ObjectiveTo construct and validate a clinical prediction model for inflammatory remission outcomes in rheumatoid arthritis （RA） patients with liver and kidney deficiency syndrome treated with Bushen Zhiwang Decoction （补肾治尪汤， BZD） based on metabolomics. MethodsA prospective cohort study was conducted， enrol-ling 60 RA patients with liver and kidney deficiency syndrome. All patients were treated with BZD and conventional-dose oral conventional synthetic disease-modifying antirheumatic drugs （csDMARDs） for 12 months. Clinical data were collected， and the change in disease activity score in 28 joints （DAS28） after treatment compared with baseline （△DAS28） was used as the primary outcome and grouping criterion. Peripheral blood samples were collected before treatment to analyze plasma metabolites. Differential analysis and least absolute shrinkage and selection operator （LASSO） regression were used to preliminarily screen differential metabolites， followed by machine learning algorithms to further identify a core metabolite combination. Based on the expression levels of the core metabolite combination， a novel metabolite index， namely the metabolomics-based inflammatory remission score （Met-IRS）， was calculated using standar-dized metabolite values， and its clinical applicability was evaluated. A clinical prediction model was constructed by integrating clinical characteristics and Met-IRS， and the model performance was assessed. ResultsAmong the 60 patients， those with △DAS28 ≥ 0.27 were assigned to the high inflammatory remission group， while those with △DAS28 ＜ 0.27 were assigned to the low inflammatory remission group， with 30 cases in each group. Compared to the low inflammatory remission group， the high inflammatory remission group showed a higher frequency of methotrexate use and a lower positive rate of rheumatoid factor （RF） （P＜0.05）. Seven core metabolites were identified as the optimal combination， including mangiferic acid， fatty acid-hydroxy fatty acid ester 40∶6， fatty acid-hydroxy fatty acid ester 18∶0， fatty acid-hydroxy fatty acid ester 36∶1， glucosylceramide， lysophosphatidylcholine 22∶5， and pregnanetriol ketone. The calculated Met-IRS comprehensively reflected the characteristics of differential metabolites and demonstrated clinical applicability. Met-IRS was significantly higher in the high inflammatory remission group than in the low inflammatory remission group， and was positively correlated with high inflammatory remission outcomes （P＜0.05）. Based on the variables Met-IRS， methotrexate use， leflunomide use， and RF positivity， a clinical prediction model for inflammatory remission in RA treatment （Cj-RTRM） was constructed. Model performance evaluation demonstrated that the model had good clinical predictive ability， with an area under the receiver operating characteristic curve （AUC） of 0.880， sensitivity 0.967， specificity 0.700 and Youden's index 0.667. ConclusionThe clinical prediction model Cj-RTRM constructed based on the metabolomics-based inflammatory remission score Met-IRS can effectively predict clinical inflammatory remission outcomes in RA patients treated with BZD and accurately identify the advantageous population for this treatment. This model provides guiding evidence for dynamic inflammation monitoring， targeted management， and identification of populations with advantages in traditional Chinese medicine.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

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.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

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 observe the clinical efficacy of Sanren Runchang formula in treating constipation-predominant irritable bowel syndrome （IBS-C） by regulating the brain-gut axis and the effects of the formula on serum levels of 5-hydroxytryptamine （5-HT）， vasoactive intestinal peptide （VIP）， and substance P （SP）. MethodsA randomized controlled design was adopted， and 72 IBS-C patients meeting Rome Ⅳ criteria were randomized into observation and control groups （36 cases）.The observation group received Sanren Runchang formula granules twice daily， and the control group received lactulose oral solution daily for 4 weeks. IBS Symptom Severity Scale （IBS-SSS）， IBS Quality of Life Scale （IBS-QOL）， and Bristol Stool Form Scale （BSFS） were used to assess clinical symptoms， and bowel movement frequency was recorded. The Self-Rating Anxiety Scale （SAS） and Self-Rating Depression Scale （SDS） were employed to evaluate psychological status. ELISA was employed to measure the serum levels of 5-HT， VIP， and SP. ResultsThe total response rate in the observation group was 91.67% （33/36）， which was higher than that （77.78%， 28/36） in the control group （χ²=4.50， P<0.05）. After treatment， both groups showed increased defecation frequency and BSFS scores， decreased IBS-SSS total score， abdominal pain and bloating scores， IBS-QOL health anxiety， anxiety， food avoidance， and behavioral disorders scores， SAS and SDS scores， serum 5-HT and VIP levels， and increased SP levels （P<0.05， P<0.01）. Moreover， the observation group showed more significant changes in the indicators above than the control group （P<0.05， P<0.01）. The SP level showed no significant difference between the two groups. During the 4-week follow-up， the recurrence rate was 5.88% in the observation group and 31.25% in the control group. No adverse events occurred in observation group， and 2 cases of mild diarrhea occurred in the control group. ConclusionSanren Runchang formula demonstrated definitive efficacy in alleviating gastrointestinal symptoms and improving the psychological status and quality of life in IBS-C patients， with a low recurrence rate. The formula can regulate serum levels of neurotransmitters such as 5-HT and VIP， suggesting its potential regulatory effect on the brain-gut axis through modulating neurotransmitters and neuropeptides. However， its complete mechanism of action requires further investigation through detection of additional brain-gut axis-related biomarkers.