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

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

Objective:To investigate the current status of standardized residency training (SRT) teaching activities at Zhongshan Hospital affiliated to Fudan University, and to explore optimization strategies.Methods:We collected behavioral data from the SRT course selection platform and resident questionnaire survey data throughout 2024. Descriptive analysis, chi-square test, Mann-Whitney U test, and multivariable logistic regression analysis were performed. Results:A total of 170 teaching sessions were conducted in 2024, with interactive practice-based sessions accounting for 42.35% and lecture-based sessions accounting for 47.06%. According to 536 questionnaires, residents' overall satisfaction with teaching activities scored 87.83 points (high satisfaction, ≥85 points; moderate satisfaction, <85 points). The proportion of high satisfaction with interactive practice-based sessions was significantly higher than that with lecture-based sessions (82.81% vs. 75.46%, P=0.034). The enrollment for weekday evening courses filled up significantly faster than that for weekday daytime courses [4 (2, 6) seconds vs. 12 (8, 15) seconds, P<0.001]. Interactive practice-based sessions [odds ratio ( OR)=1.6, 95% CI=1.1-2.3, P=0.018] and weekday evening sessions ( OR=1.4, 95% CI=1.0-2.0, P=0.048) significantly improved resident satisfaction. Conclusions:Optimizing course formats and scheduling can enhance the quality of SRT teaching activities.

P53 is a key tumor suppressor gene,which is regulated in many ways.Zinc finger 148(ZNF148)and SP5,as zinc finger transcription factors(TFs),play important roles in tumor suppression and carcinogenesis.The regulatory relationship between these two TFs and p53 has not been reported.In this paper,Ishikawa and A549 cell lines with different p53 expression levels were used as research mod-els to explore the transcriptional regulation of the P53 gene by ZNF148 and SP5.The data showed that there were differences in the expression of ZNF148 and SP5 in the two cell lines.The mRNA expression of ZNF148 in Ishikawa was 1.9 times higher than that of A549,and the mRNA expression of SP5 in A549 was 802.4 times that of ZNF148.Data showed that in Ishikawa cells,the expression of P53 de-creased(81.8％)after ZNF148 knockdown,and increased(2.6 times)after SP5 overexpression.Transfection of si-SP5 and ZNF148 expression plasmids into A549 cells increased the mRNA expression of P53 by 6.6 times and 14.6 times,respectively.These results indicate that ZNF148 could activate,whereas SP5 could inhibit,P53 expression.The conserved cis-element of ZNF148 and SP5 TFs was found in the region of the P53 promoter by bioinformatics methods.The data from dual luciferase reporter gene assay showed that the luciferase activity of ZNF148 in Ishikawa and A549 cells was increased by 2.1-fold and 4.2-fold compared with the control group(P＜0.05).Compared with the control group,the normalized relative luciferase activity of transfected SP5 decreased by 77.1％and 35.7％(P＜0.05).However,when the cis-element of ZNF148 and SP5 was mutated,the effect disappeared.Further trans-fection of ZNF148 and SP5 with different ratios revealed that SP5 could reverse the transcriptional activa-tion of P53 by ZNF148.Studies have shown that ZNF148 shares a common site with SP5,and the ratio of the two TFs may influence the transcriptional activity of P53.The expression of the Wnt pathway and the cell proliferation rate after knockdown of ZNF148 and SP5 were further studied to explore the role of the two TFs.Our data show that ZNF148 and SP5 could regulate the transcriptional activity of P53,and their expression levels and interaction may be the key factors regulating P53 expression.

OBJECTIVE To explore and establish the working mechanism for prevention and control of hospital-as-sociated infections in regional oral medical institutions so as to standardize the prevention and control of the hospi-tal-associated infections in the regional oral medical institutions.METHODS Taking an administrative division of Chongqing as example,the matrix evaluation was carried out based on the quality control mode for management of hospital-associated infections in oral medical institutions' action planning,training guidance,quality control super-vision,summary review' organically in combination with'quality control plus law enforcement',a color-co-ded management of the oral medical institutions in the region was implemented,and the effectiveness of improved work in infection control was examined.RESULTS From the perspective of the grade of medical institution,the qualified rates of hospital infection management system construction,architectural layout and process,cleaning,disinfection and sterilization of oral instruments,environmental cleaning and disinfection,isolation,safe injection,use of occupational protection supplies and disposal of medical waste of the primary and unrated medical institu-tions were respectively 26.51％,49.40％,24.10％,37.35％,31.33％,46.99％,67.47％and 51.81％before the improvement and were respectively increased to 67.47％,63.86％,45.78％,66.27％,63.86％,73.49％,84.34％and 66.27％after the improvement,and there were significant differences(P＜0.05).From the perspec-tive of the property of the medical institution,the qualified rates of the above items of the private medical institu-tions were respectively 24.66％,47.95％,21.92％,34.25％,31.51％,45.21％,69.86％and 50.68％before the improvement and were respectively increased to 65.75％,61.64％,42.47％,64.38％,63.01％,71.23％,84.93％and 63.01％after the improvement,and there were significant differences(P＜0.05).CONCLUSION The working mechanism on prevention and control of hospital-associated infections in regional oral medical institu-tions that is established based on'quality control plus law enforcement'with the introduction of social credit can effectively raise the qualified rates of the infection prevention and control measures,which achieves more remarka-ble improvement effectiveness in grass-roots oral medical institutions such as the private,primary and unrat-ed medical institutions.

AIM To evaluate the chemical constituent consistency in formula granules and traditional decoctions of Gouteng Jiangya Formula.METHODS HPLC characteristic chromatograms were established,the analysis was performed on a 30 ℃ thermostatic YMC-Triart C18 column(4.6 mm× 250 mm,5 μm),with the mobile phase comprising of acetonitrile-0.2％phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelength was set at 240 nm.Puerarin was used as an internal standard to calculate the relative correction factors of 3'-methoxy puerarin,puerarin apioside,magnolflorine,paeoniflora,daidzin,baicalin,palmatine,berberine,wogonoside and benzoylpaeoniflorin,after which the content detemination was made by quantitative analysis of multi-components by single-marker(QAMS).RESULTS The characteristic chromatograms of 9 batches of formula granules and 15 bacthes of traditional decoctions demonstrated the similarities of more than 0.90 at the detection wavelengths of 192,210,240,260,280,300,320,360 nm,along with similar total peak areas.Eleven constituents showed good linear relationships within their own ranges(r＞0.999 0),whose average recoveries were 97.27％-101.64％with the RSDs of 0.36％-1.11％,the result obtained by QAMS and external standard method demonstrated no significant differences(P＞0.05).The contents of various constituents in the formula granules approximated those in the traditional decoctions.CONCLUSION The consistent kinds and contents of various constituents are obversable in formula granules and traditional decoctions of Gouteng Jiangya Formula,which can provide a reference for the reasonable clinical application of this formula.

P53 is a key tumor suppressor gene,which is regulated in many ways.Zinc finger 148(ZNF148)and SP5,as zinc finger transcription factors(TFs),play important roles in tumor suppression and carcinogenesis.The regulatory relationship between these two TFs and p53 has not been reported.In this paper,Ishikawa and A549 cell lines with different p53 expression levels were used as research mod-els to explore the transcriptional regulation of the P53 gene by ZNF148 and SP5.The data showed that there were differences in the expression of ZNF148 and SP5 in the two cell lines.The mRNA expression of ZNF148 in Ishikawa was 1.9 times higher than that of A549,and the mRNA expression of SP5 in A549 was 802.4 times that of ZNF148.Data showed that in Ishikawa cells,the expression of P53 de-creased(81.8％)after ZNF148 knockdown,and increased(2.6 times)after SP5 overexpression.Transfection of si-SP5 and ZNF148 expression plasmids into A549 cells increased the mRNA expression of P53 by 6.6 times and 14.6 times,respectively.These results indicate that ZNF148 could activate,whereas SP5 could inhibit,P53 expression.The conserved cis-element of ZNF148 and SP5 TFs was found in the region of the P53 promoter by bioinformatics methods.The data from dual luciferase reporter gene assay showed that the luciferase activity of ZNF148 in Ishikawa and A549 cells was increased by 2.1-fold and 4.2-fold compared with the control group(P＜0.05).Compared with the control group,the normalized relative luciferase activity of transfected SP5 decreased by 77.1％and 35.7％(P＜0.05).However,when the cis-element of ZNF148 and SP5 was mutated,the effect disappeared.Further trans-fection of ZNF148 and SP5 with different ratios revealed that SP5 could reverse the transcriptional activa-tion of P53 by ZNF148.Studies have shown that ZNF148 shares a common site with SP5,and the ratio of the two TFs may influence the transcriptional activity of P53.The expression of the Wnt pathway and the cell proliferation rate after knockdown of ZNF148 and SP5 were further studied to explore the role of the two TFs.Our data show that ZNF148 and SP5 could regulate the transcriptional activity of P53,and their expression levels and interaction may be the key factors regulating P53 expression.

ObjectiveThe theory of homotherapy for heteropathy is one of the classical rules in traditional Chinese medicine. Taking this theory as a breakthrough point， this study employed gas chromatography-mass spectrometry （GC-MS） to elucidate the mechanism underlying the therapeutic effects of Zhuyuwan on both intrahepatic cholestasis （IC） and ulcerative colitis （UC） from the viewpoint of serum metabolic homeostasis. MethodsThe rat models of α-naphthylisothiocyanate （ANIT）-induced cholestasis and 2，4，6-trinitro-benzenesulfonic acid （TNBS）-induced UC were treated with low （0.6 g·kg^-1） and high （1.2 g·kg^-1） doses of Zhuyuwan by gavage. In the experiment regarding IC， 24 Sprague-Dawley （SD） rats were randomly assigned into four groups： normal， ANIT model， low-dose Zhuyuwan， and high-dose Zhuyuwan. In the experiment regarding UC， 24 SD rats were randomly allocated into four groups： normal， TNBS model， low-dose Zhuyuwan， and high-dose Zhuyuwan. Firstly， the two disease models and the intervention effects of Zhuyuwan on the two diseases were evaluated based on serum levels of biochemical indicators ［alanine aminotransferase （ALT）， aspartate transaminase （AST）， γ-glutamyltranspeptidase （γ-GT）， and total bile acid （TBA）］， colon damage score， colon weight index， disease activity index， and histopathological changes in rats. Secondly， the rat serum samples were analyzed by gas chromatography-mass spectrometry （GC-MS） to screen the common core pathways of the two disease models， and the expression of core genes in the pathways was determined by Real-time PCR， on the basis of which the biological mechanism of the treatment of the two disease models by Zhuyuwan was ultimately elucidated. ResultsThe results of the experiment regarding IC showed that the ANIT model group had higher ALT， AST， γ-GT， and TBA levels than the normal group （P<0.01）. Compared with the ANIT model group， the low-dose Zhuyuwan group showed declined ALT and TBA levels （P<0.01） and the high-dose Zhuyuwan group showed lowered ALT， TBA， AST， and γ-GT levels （P<0.01）. The results of the experiment regarding UC showed that compared with the normal group， the TNBS model group presented increases in the colonic damage score， colon weight index， and disease activity index （P<0.01）. Compared with the TNBS model group， the low-dose Zhuyuwan group showcased declines in colon weight index （P<0.01） and disease activity index （P<0.05）， and the high-dose Zhuyuwan group showed reductions in the colon damage score， colon weight index， and disease activity index （P<0.01）. GC-MS metabolomics analysis combined with qRT-PCR demonstrated that Zhuyuwan had a similar inverse regulatory effect on arginine metabolism disruption in the above two disease models. ConclusionZhuyuwan exhibited definite therapeutic effects on both IC and UC， and the regulation of arginine biosynthesis pathway is the core mechanism for the treatment of both diseases by Zhuyuwan.

ObjectiveThe theory of homotherapy for heteropathy is one of the classical rules in traditional Chinese medicine. Taking this theory as a breakthrough point， this study employed gas chromatography-mass spectrometry （GC-MS） to elucidate the mechanism underlying the therapeutic effects of Zhuyuwan on both intrahepatic cholestasis （IC） and ulcerative colitis （UC） from the viewpoint of serum metabolic homeostasis. MethodsThe rat models of α-naphthylisothiocyanate （ANIT）-induced cholestasis and 2，4，6-trinitro-benzenesulfonic acid （TNBS）-induced UC were treated with low （0.6 g·kg^-1） and high （1.2 g·kg^-1） doses of Zhuyuwan by gavage. In the experiment regarding IC， 24 Sprague-Dawley （SD） rats were randomly assigned into four groups： normal， ANIT model， low-dose Zhuyuwan， and high-dose Zhuyuwan. In the experiment regarding UC， 24 SD rats were randomly allocated into four groups： normal， TNBS model， low-dose Zhuyuwan， and high-dose Zhuyuwan. Firstly， the two disease models and the intervention effects of Zhuyuwan on the two diseases were evaluated based on serum levels of biochemical indicators ［alanine aminotransferase （ALT）， aspartate transaminase （AST）， γ-glutamyltranspeptidase （γ-GT）， and total bile acid （TBA）］， colon damage score， colon weight index， disease activity index， and histopathological changes in rats. Secondly， the rat serum samples were analyzed by gas chromatography-mass spectrometry （GC-MS） to screen the common core pathways of the two disease models， and the expression of core genes in the pathways was determined by Real-time PCR， on the basis of which the biological mechanism of the treatment of the two disease models by Zhuyuwan was ultimately elucidated. ResultsThe results of the experiment regarding IC showed that the ANIT model group had higher ALT， AST， γ-GT， and TBA levels than the normal group （P<0.01）. Compared with the ANIT model group， the low-dose Zhuyuwan group showed declined ALT and TBA levels （P<0.01） and the high-dose Zhuyuwan group showed lowered ALT， TBA， AST， and γ-GT levels （P<0.01）. The results of the experiment regarding UC showed that compared with the normal group， the TNBS model group presented increases in the colonic damage score， colon weight index， and disease activity index （P<0.01）. Compared with the TNBS model group， the low-dose Zhuyuwan group showcased declines in colon weight index （P<0.01） and disease activity index （P<0.05）， and the high-dose Zhuyuwan group showed reductions in the colon damage score， colon weight index， and disease activity index （P<0.01）. GC-MS metabolomics analysis combined with qRT-PCR demonstrated that Zhuyuwan had a similar inverse regulatory effect on arginine metabolism disruption in the above two disease models. ConclusionZhuyuwan exhibited definite therapeutic effects on both IC and UC， and the regulation of arginine biosynthesis pathway is the core mechanism for the treatment of both diseases by Zhuyuwan.