BACKGROUND:Exosomes derived from mesenchymal stem cells play pivotal roles in cell communication and epigenetic regulation due to their low immunogenicity and targeted delivery effects,and have been clinically applied in the treatment of various diseases.OBJECTIVE:To review the isolation,purification,identification methods,and application progress of mesenchymal stem cell-derived exosomes,and to facilitate the development of large-scale preparation techniques and clinical translation of mesenchymal stem cell-derived exosomes.METHODS:The Chinese search terms"exosome,mesenchymal stem cells,isolation,purification,characterization,clinical application"and the English search terms"exosome,extracellular vesicles,mesenchymal stem cells,isolation,characterization,application"were used to search the literature published before September 2024 in CNKI,PubMed,and Web of Science databases.Articles with poor relevance to the topic,outdated,or duplicated content were excluded,and finally,109 articles were included for review.RESULTS AND CONCLUSION:(1)This paper reviews recent methods for isolating and purifying exosomes,comparing the characteristics of ultracentrifugation,ultrafiltration,size-exclusion chromatography,polymer precipitation,immunoaffinity,microfluidic methods,and other novel approaches based on their underlying principles.(2)Methods for identifying exosomes can be categorized into physical and biochemical analyses,characterizing exosomes based on their shape,size,and characteristic proteins.(3)Mesenchymal stem cell-derived exosomes have broad applications in multiple fields such as medical aesthetics,wound repair,and cancer treatment,due to their immune-regulatory properties and ability to cross biological barriers.(4)The clinical translation of exosomes faces challenges due to their complex structure,lack of universal isolation techniques,and poor stability,making it difficult to achieve in a short period of time.

BACKGROUND:One of the advantages of clear aligner treatment is molar distalization.However,tooth tilting movement and loss of anterior anchorage may occur during treatment.There are few studies on whether these problems can be improved by selecting clear aligners with different thicknesses and edges to improve the clinical treatment effect.OBJECTIVE:To analyze the control ability of clear aligners with different thickness and edges on the central incisor,lateral incisor,and second molar when pushing the maxillary second molar distally by three-dimensional finite element analysis.METHODS:Three-dimensional finite element analysis models of bilateral maxillary second molar distalization with clear aligner,maxillary dentition,periodontal ligament,and alveolar bone with different thicknesses and margins were established by Mimics,Geomagic Wrap,3-matic and SolidWorks software,respectively.There were 16 combinations of four thicknesses(0.4,0.5,0.625,and 0.75 mm)and four margins(scallop,straight,straight extension 2 mm and straight extension 4 mm).The data were imported into Ansys Workbench software for design and solution.The mean value,peak value and distribution of the periodontal ligament equivalent stress of the second molar,the equivalent stress and the maximum initial displacement of the second molar,and the control ability of each appliance on the second molar,central incisor,and lateral incisor were analyzed.RESULTS AND CONCLUSION:(1)The mean equivalent stress of periodontal ligament of the second molar,the equivalent stress of the second molar and the maximum initial displacement of the second molar increased with the extension of the appliance edge and the increase of the thickness of the appliance in the 16 groups of models.(2)When the thickness of appliances was the same,the maximum equivalent stress of the second molar in the linear appliance group was the highest,and the maximum equivalent stress of the second molar in the linear extended appliance group was greater than that in the scallop appliance group.When the edge of the appliance was the same,the periodontal ligament equivalent stress peak of the second molar increased with the increase of the thickness of the appliance.The equivalent stress distribution in the periodontal ligament of the second molar in the linear extendable appliance group was more uniform than that in the scallop appliance group and the linear appliance group.(3)When the thickness of the appliance was the same,the scallop-shaped appliance had the worst control on the second molar.When the edge of the appliance was the same,with the increase of the thickness of the appliance,the control of the second molar by the linear extender appliance was gradually stronger than that by the linear appliance.The control of the central incisor was stronger and more stable with the linear extended 2 mm appliance,while the control of the lateral incisor was stronger and more stable with the linear appliance.(4)The results showed that when using clear aligners to push molars distally,extending the edge of the appliance could improve the control of the molars and reduce the tilting movement of the teeth.The design of a straight extension margin of 2 mm for the central incisor and a straight edge for the lateral incisor can enhance the control of the anchorage incisor and reduce the labial inclination of the anterior teeth.

BACKGROUND:Obesity is not only related to metabolic diseases such as diabetes and cardiovascular disease,but also closely related to the increased risk of cognitive decline,dementia and other neurodegenerative diseases.Studies have found that aerobic exercise and resistance exercise can help improve obesity-related cognitive impairment,but their therapeutic effects and related mechanisms of action are still unclear.OBJECTIVE:To explore the protective effects of aerobic and resistance exercises on the nervous center of obesity-related cognitive impairment mice.METHODS:Forty-eight 8-week-old C57BL/6J wild-type male mice were randomly divided into four groups:a control group was fed normally for 20 weeks;a high fat group was fed with high fat diet(60％fat energy)for 20 weeks;an aerobic exercise group was fed with 12 weeks of high-fat diet followed by 8 weeks of aerobic exercise;and a resistance exercise group was fed with 12 weeks of high-fat diet followed by 8 weeks of resistance exercise.After the exercise intervention,body mass was weighed,insulin tolerance and glucose tolerance were tested to evaluate insulin resistance,and cognitive function of mice in each group was detected by new object recognition experiment and Y-maze experiment.The morphology of hippocampal and cortical tissue cells was observed by hematoxylin-eosin staining.The mRNA relative expression levels of tumor necrosis factor-α and interleukin-6 were detected by real-time fluorescence quantitative PCR,and the protein expressions of Bax,Bcl-2,nuclear factor-κB,Cleaved Caspase-1,Caspase-3,synapsin 1 and brain-derived neurotrophic factor were detected by western blot.RESULTS AND CONCLUSION:(1)Compared with the control group,the body mass of mice increased in the high-fat group(P＜0.05),accompanied by insulin resistance and cognitive dysfunction,the expression levels of nuclear factor-κB,Bax,Caspase-3,Cleaved Caspase-1 in the hippocampus were significantly increased(P＜0.05),the expression levels of brain-derived neurotrophic factor,synapsin 1and Bcl-2 proteins were significantly decreased(P＜0.05),Bcl-2/Bax ratio was significantly decreased(P＜0.05),and the mRNA levels of inflammatory cytokines,tumor necrosis factor-α and interleukin-6,were significantly up-regulated(P＜0.05).(2)Compared with the high-fat group,the above indexes were significantly improved in the aerobic exercise group(P＜0.05),while in the resistance exercise group,the body mass of mice was significantly decreased,the levels of inflammatory cytokines tumor necrosis factor-α and interleukin-6 mRNA were significantly decreased(P＜0.05),the protein expression of Caspase-3 was significantly decreased(P＜0.05),and the protein expression of brain-derived neurotrophic factor was significantly up-regulated(P＜0.05),but no significant changes were observed in the other indexes(P＞0.05).In conclusion,long-term exercise can reduce insulin resistance,down-regulate the expression of nuclear factor-κB pathway,weaken inflammatory response,inhibit neuronal apoptosis and improve synaptic plasticity,resulting in neuroprotective effects,and effectively alleviate obesity-related cognitive dysfunction in obese mice.The therapeutic effect of aerobic exercise is superior to that of resistance exercise.

BACKGROUND:Exosomes derived from mesenchymal stem cells play pivotal roles in cell communication and epigenetic regulation due to their low immunogenicity and targeted delivery effects,and have been clinically applied in the treatment of various diseases.OBJECTIVE:To review the isolation,purification,identification methods,and application progress of mesenchymal stem cell-derived exosomes,and to facilitate the development of large-scale preparation techniques and clinical translation of mesenchymal stem cell-derived exosomes.METHODS:The Chinese search terms"exosome,mesenchymal stem cells,isolation,purification,characterization,clinical application"and the English search terms"exosome,extracellular vesicles,mesenchymal stem cells,isolation,characterization,application"were used to search the literature published before September 2024 in CNKI,PubMed,and Web of Science databases.Articles with poor relevance to the topic,outdated,or duplicated content were excluded,and finally,109 articles were included for review.RESULTS AND CONCLUSION:(1)This paper reviews recent methods for isolating and purifying exosomes,comparing the characteristics of ultracentrifugation,ultrafiltration,size-exclusion chromatography,polymer precipitation,immunoaffinity,microfluidic methods,and other novel approaches based on their underlying principles.(2)Methods for identifying exosomes can be categorized into physical and biochemical analyses,characterizing exosomes based on their shape,size,and characteristic proteins.(3)Mesenchymal stem cell-derived exosomes have broad applications in multiple fields such as medical aesthetics,wound repair,and cancer treatment,due to their immune-regulatory properties and ability to cross biological barriers.(4)The clinical translation of exosomes faces challenges due to their complex structure,lack of universal isolation techniques,and poor stability,making it difficult to achieve in a short period of time.

BACKGROUND:One of the advantages of clear aligner treatment is molar distalization.However,tooth tilting movement and loss of anterior anchorage may occur during treatment.There are few studies on whether these problems can be improved by selecting clear aligners with different thicknesses and edges to improve the clinical treatment effect.OBJECTIVE:To analyze the control ability of clear aligners with different thickness and edges on the central incisor,lateral incisor,and second molar when pushing the maxillary second molar distally by three-dimensional finite element analysis.METHODS:Three-dimensional finite element analysis models of bilateral maxillary second molar distalization with clear aligner,maxillary dentition,periodontal ligament,and alveolar bone with different thicknesses and margins were established by Mimics,Geomagic Wrap,3-matic and SolidWorks software,respectively.There were 16 combinations of four thicknesses(0.4,0.5,0.625,and 0.75 mm)and four margins(scallop,straight,straight extension 2 mm and straight extension 4 mm).The data were imported into Ansys Workbench software for design and solution.The mean value,peak value and distribution of the periodontal ligament equivalent stress of the second molar,the equivalent stress and the maximum initial displacement of the second molar,and the control ability of each appliance on the second molar,central incisor,and lateral incisor were analyzed.RESULTS AND CONCLUSION:(1)The mean equivalent stress of periodontal ligament of the second molar,the equivalent stress of the second molar and the maximum initial displacement of the second molar increased with the extension of the appliance edge and the increase of the thickness of the appliance in the 16 groups of models.(2)When the thickness of appliances was the same,the maximum equivalent stress of the second molar in the linear appliance group was the highest,and the maximum equivalent stress of the second molar in the linear extended appliance group was greater than that in the scallop appliance group.When the edge of the appliance was the same,the periodontal ligament equivalent stress peak of the second molar increased with the increase of the thickness of the appliance.The equivalent stress distribution in the periodontal ligament of the second molar in the linear extendable appliance group was more uniform than that in the scallop appliance group and the linear appliance group.(3)When the thickness of the appliance was the same,the scallop-shaped appliance had the worst control on the second molar.When the edge of the appliance was the same,with the increase of the thickness of the appliance,the control of the second molar by the linear extender appliance was gradually stronger than that by the linear appliance.The control of the central incisor was stronger and more stable with the linear extended 2 mm appliance,while the control of the lateral incisor was stronger and more stable with the linear appliance.(4)The results showed that when using clear aligners to push molars distally,extending the edge of the appliance could improve the control of the molars and reduce the tilting movement of the teeth.The design of a straight extension margin of 2 mm for the central incisor and a straight edge for the lateral incisor can enhance the control of the anchorage incisor and reduce the labial inclination of the anterior teeth.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

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 explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

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.