BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:The quadriceps strength of patients with osteoporosis and sarcopenia is significantly reduced,which can further reduce the function of the knee joint,affect the function of the lower limbs and even lead to a decrease in whole-body coordination.It is speculated that a reasonable quadriceps training program and personalized guidance are beneficial to the recovery of knee joint function in patients with osteoporosis and sarcopenia.OBJECTIVE:To observe the effect of short-term moderate-intensity resistance rehabilitation training on the mass and function of the quadriceps and knee joint function in patients with osteoporosis and sarcopenia.METHODS:Using the integrated physical examination and rehabilitation model,375 patients with osteoporosis and sarcopenia were screened at the Health Management Center of Shanghai Public Health Clinical Center.They underwent 12 weeks of combined/comprehensive exercise rehabilitation based on resistance exercise,including quadriceps resistance isotonic and isometric contraction training twice a week(3-5 sets each time,10-15 minutes per set)and aerobic exercise/balance exercise two or three times a week(30 minutes each time).Assessments and data collection were performed before rehabilitation training,12 weeks after rehabilitation training,and at follow-up 12 weeks after stopping rehabilitation training,mainly including knee joint range of motion and proprioception,quadriceps muscle strength,and cross-sectional area(magnetic resonance imaging results),pain,knee joint function(Hospital for Special Surgery score)and walking function("up-and-go"time and 6 m pace test results)as well as the patient's psychological status assessment.RESULTS AND CONCLUSION:All 375 patients completed 12 weeks of rehabilitation training and 12 weeks of follow-up without any adverse events.(1)Compared with before training,the patients' gait speed and knee range of motion increased significantly after 12 weeks of rehabilitation training(P＜0.01),the time of"stand-to-walk"decreased(P＜0.01),and the proprioception of the knee joint and the strength of the quadriceps femoris were significantly improved(P＜0.01);and at the follow-up visit 12 weeks after stopping training,the above indicators and functions of the patients were well maintained(P＞0.05).(2)Magnetic resonance imaging results showed that the effective cross-sectional area of the quadriceps femoris did not improve significantly after 12 weeks of rehabilitation training(P＞0.05);but the Hospital for Special Surgery score of knee joint function increased significantly(P＜0.01),and the visual analog pain scale score decreased significantly(P＜0.01),suggesting that this may be related to the improvement of quadriceps femoris quality by resistance rehabilitation training.(3)The results of the Hospital Anxiety and Depression Scale score showed that the anxiety and depression scores of the patients continued to decrease,both at 12 weeks of rehabilitation training and at 12 weeks after stopping training(P＜0.01).It is suggested that resistance rehabilitation training of the quadriceps can help patients with osteoporosis and sarcopenia to restore quadriceps muscle strength,increase range of motion,improve proprioception and joint stability,thereby enhancing knee joint function,reducing pain,improving depression and anxiety,and to a certain extent promoting the coordinated recovery of the musculoskeletal system.

BACKGROUND:Long-term blood flow restriction combined with low-intensity resistance training has been shown to effectively treat obesity by alleviating chronic inflammation and endothelial dysfunction.However,the immediate effects of a single session on serum concentrations of vascular endothelial function and inflammatory biomarkers remain unclear.OBJECTIVE:To explore the short-term effects and recovery capacity of blood flow restriction during low-intensity resistance training on serum biomarkers of vascular endothelial function and inflammation in obese male college students.METHODS:Twenty obese male college students(body mass index＞30 kg/m2,body fat percentage＞25％)were randomly assigned to a control group(0％arterial occlusion pressure)or a blood flow restriction group(80％arterial occlusion pressure).Both groups performed a single session of low-intensity resistance training at an intensity corresponding to a perceived exertion of 11-13 on the Rate of Perceived Exertion Scale.The training was repeated three times,with each session lasting 30 minutes,totaling 1.5 hours.Serum biomarkers were measured before exercise,immediately post-exercise,1 hour post-exercise,and 24 hours post-exercise.The assessed biomarkers included vascular endothelial function markers,inflammatory markers,and insulin function indicators.RESULTS AND CONCLUSION:(1)Vascular endothelial function:Acute exercise increased vascular endothelial growth factor A concentrations in both groups.The blood flow restriction group significantly elevated serum platelet-derived growth factor and nitric oxide levels(P＜0.05),while the control group showed a significant increase in nitric oxide synthase levels(P＜0.05).Angiotensin Ⅱ concentrations decreased immediately after acute exercise in both groups but remained significantly higher than baseline in the blood flow restriction group after 24 hours of recovery,and there was a significant difference between the two groups(P＜0.05).(2)Regarding inflammatory markers,the blood flow restriction group induced higher levels of hypoxia and significantly upregulated tumor necrosis factor-α and hypoxia-inducible factor-1α concentrations(P＜0.05).Adiponectin and leptin levels upregulated in both groups,with a more pronounced rise in adiponectin level in the blood flow restriction group than the control group(P＜0.05).lnterleukin-6 concentrations decreased in both groups,with a greater reduction in the blood flow restriction group.(3)For insulin function,the blood flow restriction and control groups showed immediate increases and decreases in insulin levels after exercise,respectively,but these returned to below and above baseline levels after 24 hours of recovery.Both groups reduced insulin resistance index in adipose tissue,with a more significant improvement in the blood flow restriction group(P＜0.05).To conclude,compared with low-intensity resistance training,short-term blood flow restriction induces more favorable changes in inflammatory and vascular endothelial biomarkers,improving inflammation and endothelial dysfunction with longer-lasting effects.However,further studies are needed to validate these findings over long-term interventions.

Objective: To investigate the associations between childhood obesity and performance of six minute walk test (6MWT), providing evidence for exercise tolerance assessment and exercise intervention strategies for children and adolescents. Methods: From March 2021 to December 2023, a cohort study was conducted among students recruited from a primary and secondary school in Chongqing, a total of 709 valid samples were included. The 6MWT was used to assess exercise tolerance, with vital signs measured before and after the test. Anthropometric indicators, including height, weight, and waist circumference, were measured using standardized procedures. Generalized additive models (GAM) and restricted cubic spline (RCS) regression were employed to analyze the nonlinear relationships between obesity related indicators and six minute walk distance (6MWD). Results: The mean 6MWD of participants was (602.59±70.73)m. GAM showed that after adjusting for confounding factors, body mass index (BMI) and weight had non linear relationships with 6MWD [effective degrees of freedom were 1.55 and 7.13 respectively], and overweight/obesity was associated with a decrease in 6MWD ( β =-18.65) (all P <0.01). Further RCS regression analysis showed that both BMI and weight showed an "inverted U shaped" non linear relationship with 6MWD in the overall population and sex stratified subgroups; the 6MWD of females was lower than that of males, and it showed a significant downward trend with the increase of BMI or weight (all P <0.05). Conclusion Body weight and BMI in children and adolescents have an important impact on 6MWD, and obesity in children and adolescents is markedly associated with decline in exercise tolerance.

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 compare the clinical efficacy of traditional Chinese medicine （TCM） manipulative reduction combined with small splint fixation versus surgical treatment for type A distal radius fracture （DRF） and to explore the factors influencing the choice of treatment. MethodsA multi-center retrospective study was conducted， collecting data from 1237 type A DRF patients treated in 11 hospitals in Jiangsu province from September， 2023 to April， 2025. Among them， 851 patients in the TCM group received manipulative reduction combined with small splint fixation， and 386 patients in the surgical group underwent open reduction and internal fixation. Visual analog scale （VAS） scores for pain and radiographic indicators including palmar tilt， ulnar deviation， and radial height were compared before treatment， 5-7 days after treatment， and 4-6 weeks after treatment. The wrist joint function scores including Dienst and Gartland-Werley scores at 12 weeks after treatment were recorded. Subgroup analysis was conducted for the excellent rate of Dienst and Gartland-Werley scores， stratified by age （＜50， 50-59， 60-69， ≥70 years old） and AO subtypes （A1， A2， A3）. A multivariate logistic regression model was used to identify independent factors influencing treatment choice. ResultsOn 5-7 days after treatment， the surgical group had lower VAS scores than the TCM group， while 4-6 weeks after treatment， the TCM group showed lower VAS scores than the surgical group （P＜0.01）. In terms of radiographic indicators， except for the palmar tilt before treatment being higher in the surgical group than in the TCM group （P＜0.01）， there were no significant differences in palmar tilt， ulnar deviation， and radial height at other timepoints （P＞0.05）. Twelve weeks after treatment， the surgical group had a higher average Gartland-Werley score and the excellent rate than the TCM group （P＜0.01）. Subgroup analysis showed that in patients with A2 type DRF aged 50-59 and 60-69 years old， the excellent rates of Dienst and Gartland-Werley scores in the TCM group were higher than those in the surgical group （P＜0.05）. Multivariate logistic regression analysis revealed that age， palmar tilt， ulnar deviation， and the degree of swelling on the affected side were independent factors influencing the choice of treatment （P＜0.05）. ConclusionBoth TCM manipulative reduction combined with small splint fixation and surgical treatment for type A DRF can achieve good therapeutic effects. TCM manipulative reduction combined with small splint fixation has certain advantages in medium- and long-term pain relief， especially in elderly patients， where wrist joint function recovery is more stable. Age， palmar tilt， ulnar deviation， and swelling degree are the main factors influencing the treatment choice.

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 expression of CPEB2 in triple-negative breast cancer (TNBC) and its impact on the malignant progression of tumors. Methods The expression level of CPEB2 in breast cancer was analyzed through a database, and the differential expression in clinical pathological specimens was verified by immunohistochemical experiments. Stable CPEB2 overexpressing TNBC cell lines were constructed, and CCK-8 and Transwell assays were used to detect the changes in cell phenotypes. Western blot was used to explore the expression of key molecules in the MEK/ERK signaling pathway. Results The expression of CPEB2 in TNBC tissues was significantly lower than that in adjacent tissues (χ²=16.57, P<0.001). Patients with high expression of CPEB2 had a significantly longer overall survival than those with low expression. Overexpression of CPEB2 inhibited the proliferation, migration, and invasion abilities of TNBC cells and the activation of the MEK/ERK signaling pathway. Conclusion The expression of CPEB2 is downregulated in TNBC. Upregulation of CPEB2 inhibits the proliferation, migration, and invasion of TNBC cells, accompanied by decreased activation of the MEK/ERK pathway (reduced p-MEK and p-ERK levels), suggesting that CPEB2 may participate in the malignant progression of TNBC by regulating the MEK/ERK pathway.

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.