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: This prospective study evaluated the feasibility of chemical exchange saturation transfer (CEST) MRI for assessing disease activity in thyroid-associated ophthalmopathy (TAO). Materials and Methods: A total of 88 patients with active TAO, 76 with inactive TAO, and 30 healthy controls were enrolled. CEST MRI-derived magnetization transfer ratio (MTR) and MTR asymmetry (MTRasym) at 1 ppm, 2 ppm, and 3.5 ppm were calculated. Clinical data, MTR, and MTRasym values for the extraocular muscles (one representative muscle per eye, yielding two measurements per participant) were compared among the groups. Spearman’s correlation was used to examine associations between imaging parameters and the clinical activity score (CAS) in patients with TAO. Logistic regression analysis was used to identify independent associations between imaging parameters and disease activity in patients with TAO (active vs. inactive). Receiver operating characteristic (ROC) analysis was conducted to evaluate the diagnostic performance for discriminating active from inactive TAO. Results: Patients with active TAO showed lower MTR values (P < 0.001) and higher MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) (all P < 0.001) compared with those with inactive TAO. MTR was negatively correlated with CAS (r = -0.402; P < 0.001), while MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) were positively correlated with CAS (r = 0.369, 0.350, and 0.349, respectively;all P < 0.001). MTR and MTRasym (1 ppm) were independently associated with TAO activity. The areas under the ROC curve (AUCs) for MTR and MTRasym (1 ppm) in discriminating active from inactive TAO were 0.772 and 0.730, respectively. Combining MTR with MTRasym (1 ppm) significantly improved diagnostic performance compared with either parameter alone, achieving an AUC of 0.805 (P = 0.029 and 0.001). Conclusion MTR and MTRasym (1 ppm) were independently associated with TAO activity. Their combination further enhanced diagnostic performance in distinguishing active from inactive TAO, suggesting their potential as quantitative imaging biomarkers to guide treatment in patients with TAO.

Through reviewing literature on thyroid cancer management strategies, this article discusses the problems of active monitoring strategies, the real implementation status, and the hidden dangers of thermal ablation as a downgrade treatment. It points out that further research is needed to accurately identify low-risk PTMCs and implement active monitoring methods. The improvement in the 5-year survival rate of thyroid cancer is due to standardized diagnosis and treatment. At present, it is still too early to downgrade the diagnosis and treatment of thyroid cancer in China. The World Health Organization recommends the three early principles of early detection, early diagnosis, and early treatment for the treatment of malignant tumors as the fundamental principles of thyroid cancer diagnosis and treatment.

AIM To study the chemical constituents from the stems and leaves of Dendrobium formosum Roxb.ex Lindl.and their biological activities.METHODS The 95％ethanol extract from the stems and leaves of D.formosum was isolated and purified by silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their inhibitory activities onα-glucosidase were determined by PNPG method,and their in vitro anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Fifteen compounds were isolated and identified as coniferyl p-coumarate(1),(-)-pinoresinol(2),2,5,7-trihydroxy-4-methoxy-9,10-dihydrophenanthrene(3),naringenin(4),spiropreussomerin A(5),7-hydroxy-14-de-O-methyl-lasiodiplodin(6),(4S,5S,6Z,8E)-5-hydroxydeca-6,8-dien-4-olide(7),(6S,9R)-blumenol C(8),p-hydroxybenzoic acid(9),m-hydroxybenzoic acid(10),p-hydroxy benzenepropanoic acid(11),5,7-dihydroxy-isobenzofuran(12),2-(4-hydroxyphenyl)-ethanol(13),β-sitostenone(14),β-sitosterol(15).The IC50 values of compounds 1 and 4 on α-glucosidase inhibition were(65.60±3.31)and(98.95±2.53)μmol/L,respectively.Compound 3 presented inhibitory activity on NO production in RAW 264.7 cells,with IC50 value of(3.97±0.12)μmol/L.CONCLUSION Compounds 5-6,8 and 12 are isolated from Orchidacae family for the first time,and 2-15 are first isolated from this plant.Compounds 1 and 4 have α-glucosidase inhibitory activities,and 3 has anti-inflammatory activity.

Objective To observe the clinical effect of pressing needle in preventing and reducing nausea and vomiting in patients after gynecological laparoscopic surgery.Methods A total of 199 patients undergoing gynecological laparoscopic surgery from May to Nov 2023 at Obstetrics and Gynecology Hospital,Fudan University were randomly divided into research group(n=99)and control group(n=100).The observation group was given Tanzhong,zanzhu and Taichong pressing needles on the basis of the control group.The postoperative nausea and vomiting were observed in the two groups.Results There were significant differences in the incidence and duration of postoperative nausea,the incidence of postoperative vomiting between the two groups(P<0.05),but there was no significant difference in the duration of postoperative vomiting.The incidence of nausea and vomiting in the observation group was lower than that in the control group.Conclusion Pressing needle can effectively prevent the occurrence of nausea and vomiting after gynecological laparoscopic surgery,and reduce the degree of nausea and vomiting,and reduce the duration of nausea.

Objective To summarize the clinical and genetic characteristics of children with sodium taurocholate co-transporting polypeptide(NTCP)deficiency.Methods Clinical data of children with NTCP deficiency diagnosed and treated at the First People's Hospital of Yunnan Province from July 2022 to March 2025 were retrospectively analyzed.Results A total of 14 children were included(6 males,8 females),all with normal growth and development.Reasons for initial consultation included elevated serum bile acids in 7 cases,jaundice in 4 cases,cholestatic hepatitis in 1 case,and one case each of pneumonia and cow's milk protein allergy.At the first visit,all patients had elevated serum total bile acids beyond the normal range,with a mean of 152.5 μmol/L.Elevated alanine aminotransferase was observed in 1 case,elevated aspartate aminotransferase in 2 cases,and elevated total bilirubin in 10 cases.Genetic sequencing revealed that all children carried the homozygous SLC10A1 variant c.800C>T(p.Ser267Phe),classified as likely pathogenic.Conclusions NTCP deficiency often lacks obvious clinical symptoms and signs.Some children present with transient hyperbilirubinemia,cholestasis,or other liver function abnormalities.Persistent isolated elevation of serum bile acids warrants suspicion for this disease.Biallelic pathogenic variants in SLC10A1 constitute the basis for definitive diagnosis.There is no specific treatment for this disease,and management is mainly symptomatic.

Objective To summarize the clinical and genetic characteristics of children with sodium taurocholate co-transporting polypeptide(NTCP)deficiency.Methods Clinical data of children with NTCP deficiency diagnosed and treated at the First People's Hospital of Yunnan Province from July 2022 to March 2025 were retrospectively analyzed.Results A total of 14 children were included(6 males,8 females),all with normal growth and development.Reasons for initial consultation included elevated serum bile acids in 7 cases,jaundice in 4 cases,cholestatic hepatitis in 1 case,and one case each of pneumonia and cow's milk protein allergy.At the first visit,all patients had elevated serum total bile acids beyond the normal range,with a mean of 152.5 μmol/L.Elevated alanine aminotransferase was observed in 1 case,elevated aspartate aminotransferase in 2 cases,and elevated total bilirubin in 10 cases.Genetic sequencing revealed that all children carried the homozygous SLC10A1 variant c.800C>T(p.Ser267Phe),classified as likely pathogenic.Conclusions NTCP deficiency often lacks obvious clinical symptoms and signs.Some children present with transient hyperbilirubinemia,cholestasis,or other liver function abnormalities.Persistent isolated elevation of serum bile acids warrants suspicion for this disease.Biallelic pathogenic variants in SLC10A1 constitute the basis for definitive diagnosis.There is no specific treatment for this disease,and management is mainly symptomatic.

Through reviewing literature on thyroid cancer management strategies, this article discusses the problems of active monitoring strategies, the real implementation status, and the hidden dangers of thermal ablation as a downgrade treatment. It points out that further research is needed to accurately identify low-risk PTMCs and implement active monitoring methods. The improvement in the 5-year survival rate of thyroid cancer is due to standardized diagnosis and treatment. At present, it is still too early to downgrade the diagnosis and treatment of thyroid cancer in China. The World Health Organization recommends the three early principles of early detection, early diagnosis, and early treatment for the treatment of malignant tumors as the fundamental principles of thyroid cancer diagnosis and treatment.

Gastric cancer (GC) is one of the most common malignant tumors of the digestive system in China. With the progress of immunotherapy research, programmed death receptor-1 (PD-1) inhibitor-based combinatory therapy offers new ideas for the treatment of advanced gastric cancer. In recent years, with the increasing status of immunotherapy in the treatment of advanced gastric cancer, a growing number of domestic and international clinical studies shown that immunotherapy could achieve better efficacy in the neoadjuvant therapy and conversion therapy for patients with advanced gastric cancer. This paper reviews the current research progress on the application of PD-1 inhibitors in the neoadjuvant therapy and conversion therapy of gastric cancer.