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 early effects of birth weight at different gestational ages on blood pressure trajectory among primary school students, so as to provide evidence for incorporating gestational age birth weight into individualized early warning and intervention strategies for childhood hypertension. Methods: From May to November 2023, a purposeful sampling method was used to recruit 1 676 students in grade 1-3 from three primary schools in a certain urban district of Chongqing. Follow up assessments were conducted in May 2024(T1), November 2024(T2), and May 2025(T3). General demographic and birth related information were collected via self administered questionnaires, while height, weight and blood pressure were obtained through physical examinations. Linear mixed effects model was used to analyze the associations between birth weight at different gestational ages and blood pressure trajectories. Results: During the T1-T3 period, the systolic blood pressure of boys were 98.5 (93.0, 104.5 ),98.5 (93.5, 105.0), and 97.5 (92.5, 103.5)mmHg, respectively, while the diastolic blood pressure were 60.5 (56.5, 65.0), 61.5 ( 57.0 , 65.5), and 60.0 (56.0, 64.0)mmHg, respectively. For girls, the systolic blood pressure were 95.5 (90.0, 102.0),95.5 (90.5, 101.5), and 96.0 (90.5, 101.5)mmHg, respectively, and the diastolic blood pressure were 60.5 (56.0, 64.5 ),61.5 (57.5, 65.5), and 59.5 (56.0, 63.0)mmHg, respectively. Through Friedman test within both boys and girls, diostolic blood pressure were statistically significant across three measurements( χ 2=48.85，81.54，both P <0.01). The proportion of normal blood pressure increased , and the proportion of prehypertension and hypertension decreased with time( χ 2=39.72，25.62，both P < 0.01 ). Linear mixed effects model analysis revealed that after adjusting for age, sex, household income monthly, parental education, family history of hypertension and maternal pregnancy complications, large for gestational age had significantly higher trajectories of systolic ( β = 1.50) and diastolic( β =0.94) blood pressure compared to appropriate for gestational age(both P <0.01). Conclusion Large for gestational age is associated with elevated blood pressure trajectories during school age, and it may be considered as an early indicator for individualized screening and intervention for childhood hypertension.

Objective To explore the construction of heart preservation model of empty beating donor based on extracorporeal membrane oxygenation (ECMO). Methods From January 2022 to August 2023, 20 Guangxi Bama miniature pigs weighing 25-30 kg were selected, half male and half female. Under general anesthesia and heparinization, a midline thoracotomy was performed. The pericardium was cut after freeing the anterior and posterior vena cavae, and a perfusion needle was inserted near the brachiocephalic artery in the ascending aorta, connected to a blood collection bag to collect 500-600 mL of blood. The anterior and posterior vena cavae were ligated, the aorta was blocked and perfused with HTK solution to stop the heart beating. The superior and inferior vena cavae were cut off, the right pulmonary vein was decompressed, the aorta and left and right pulmonary arteries and veins were cut off, and the whole heart was removed. An ECMO device was used to continuously perfuse a cardioprotective solution mainly composed of oxygenated warm blood, maintaining the isolated pig heart beating for 8 hours, monitoring (once/hour) ECMO perfusion parameters, blood gas indicators, perfusate electrolytes, inflammatory factors, myocardial enzymes, myoglobin, and troponin levels. Myocardial tissue was taken for hematoxylin-eosin (HE) staining to observe myocardial cell damage and evaluate the quality of heart preservation. Results Among the 20 isolated beating pig hearts, 17 successfully resumed beating, 3 experienced ventricular fibrillation, resuscitated after intracardiac electrical defibrillation, and all 20 pig hearts successfully beat for 8 hours. There was no statistical difference in ECMO perfusion parameters, blood gas indicators, perfusate electrolytes, and inflammatory factors at each time point (P>0.05). There were statistical increases in myocardial enzymes, myoglobin, and troponin levels (P<0.05). HE staining results suggested that there was no severe myocardial damage. Conclusion ECMO technology can be used for pig heart preservation with good results, and this study provides experimental evidence for improving heart preservation research in clinical heart transplantation.

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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To develop a method for rapidly identifying Clostridioides difficile(C.difficile)and de-termining high-producing toxin strains,conduct clinical evaluation.Methods The loop-mediated isothermal amplifi-cation(LAMP)method was used to identify C.difficile based on the tcdC,tcdA,and tcdB genes.The sensitivi-ty,specificity,and overall consistency of the detection method were evaluated.Results Feces specimens from 499 hospitalized patients suspected of C.difficile-associated diarrhea were detected,with C.difficile detection rate of 12.8％(64/499),out of which the detection rate of toxin-producing C.difficile was 10.8％(54/499).The sensi-tivity,specificity,positive predictive value,and negative predictive value of the detection method for tcdA were 87.2％,98.9％,89.1％,and 98.6％,respectively,and 88.2％,99.6％,90.0％,and 98.73％for tcdB,respec-tively.The total toxin levels of different strains were different,but the average toxin production level of A+B+strains(1.79 μg/mL)was higher than those of A-B+strains(0.72 μg/mL)and A-B-strains(＜0.10 μg/mL).Conclusion The portable high-throughput LAMP detection method can rapidly and efficiently identify C.difficile and determine high-producing toxin strains.

AIM To investigate the clinical effects of Supplemented Jiao'ai Decoction combined with warm acupuncture and moxibustion on patients with endometriosis due to Congealing Cold with Blood Stasis.METHODS Eighty-six patients were randomly assigned into control group(43 cases)for 3-menstrual cycle intervention of warm acupuncture and moxibustion,and observation group(43 cases)for 3-menstrual cycle intervention of both Supplemented Jiao'ai Decoction and warm acupuncture and moxibustion.The changes in clinical effects,TCM syndrome scores,dysmenorrhea degree indices(VAS score,PGE2,PGF2α),hemodynamic indices(RI,PI),sexhormones(E2,FSH,LH),inflammatory factors(IL-1β,IL-6,TNF-α)and incidence of adverse reactions were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P＜0.05).After the treatment,the two groups displayed decreased TCM syndrome scores,dysmenorrhea degree indices,hemodynamic indices,sexhormones and inflammatory factors(P＜0.05),especially for the observation group(P＜0.05).No significant difference in incidence of adverse reactions was found between the two groups(P＞0.05).CONCLUSION For the patients with endometriosis due to Congealing Cold with Blood Stasis,Supplemented Jiao'ai Decoction combined with warm acupuncture and moxibustion can safely and effectively regulate sexhormone levels,endometrial hemodynamics,inhibit inflammatory responses,and alleviate dysmenorrhea symptoms.

To establish a method for detecting Toxoplasma gondii based on recombinant polymerase amplification(RPA)technology and apply it to clinical sample validation of pet cats.Using the 529 repeat sequence of the Toxoplasma gondii gene as the target gene sequence,primers and probes were designed,and the Rep-529 recombinant plasmid was constructed as the standard.A fluorescent RPA reaction system was established.Dilute the plasmid standard 10 times to different concentrations as the detection template for sensitivity testing;Specific testing was conducted using genomic DNA from several parasitic spe-cies,including Toxoplasma gondii,Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia flagellata,Babesia bo-vis and Theileria annulata as templates;Simultaneously,fluorescence RPA and RT-PCR were used to detect 52 positive and 40 negative cats clinical samples,and the coincidence rate of the detection results of the two methods were compared and ana-lyzed.The RPA reaction system was successfully established using PTRep recombinant plasmid as the standard,ToxD-F/ToxD-R as the primer,and RepD-P as the fluorescent probe.The reaction temperature was constant at 39 ℃,the reaction time was 30 minutes,and the detection sensitivity was 1 copy/μL.There is no significant cross reaction with parasites such as Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia,Babesia bovis and Theileria annulata,and the specificity is good.A total of 92 clinical fecal samples from cats were tested,and the positive coincidence rate of fluorescence RPA detection method was higher than that of conventional RT-PCR method(98.08％vs.82.69％),and the difference of the positive rate was not statistically significant(X2=1.392,P＞0.05).The fluorescence RPA detection method for Toxoplasma gondii suc-cessfully established in this study has the characteristics of being fast,sensitive,specific,accurate,and reliable.It can be used as a rapid clinical detection kit for Toxoplasma gondii in cats and other animals,providing new technical support for the subsequent epidemiological monitoring and precise clinical diagnosis of toxoplasmosis in cats,other animals,and humans in the future.

Objective To develop a method for rapidly identifying Clostridioides difficile(C.difficile)and de-termining high-producing toxin strains,conduct clinical evaluation.Methods The loop-mediated isothermal amplifi-cation(LAMP)method was used to identify C.difficile based on the tcdC,tcdA,and tcdB genes.The sensitivi-ty,specificity,and overall consistency of the detection method were evaluated.Results Feces specimens from 499 hospitalized patients suspected of C.difficile-associated diarrhea were detected,with C.difficile detection rate of 12.8％(64/499),out of which the detection rate of toxin-producing C.difficile was 10.8％(54/499).The sensi-tivity,specificity,positive predictive value,and negative predictive value of the detection method for tcdA were 87.2％,98.9％,89.1％,and 98.6％,respectively,and 88.2％,99.6％,90.0％,and 98.73％for tcdB,respec-tively.The total toxin levels of different strains were different,but the average toxin production level of A+B+strains(1.79 μg/mL)was higher than those of A-B+strains(0.72 μg/mL)and A-B-strains(＜0.10 μg/mL).Conclusion The portable high-throughput LAMP detection method can rapidly and efficiently identify C.difficile and determine high-producing toxin strains.

Objective:To perform RHD gene detection on a blood sample with serological weak D phenotype.Methods:A specimen received by the People's Hospital of Zhijin County was serologically identified by the microcolumn gel method and saline method.RHD gene detection was conducted by the PCR-SSP method,and the full sequence determination of the 10 exons amplified was performed.The sequencing results were compared with the ISBT database to determine the genotype.Bioinformatics tool was used to predict the functional damage of mutant proteins,and Alphafold-3 was used for tertiary structural modeling of wild-type and mutant RhD proteins,and the structures of the two proteins were compared and analyzed to explore the reasons why mutations lead to weak serological manifestations.Results:The patient's genotype was identified as RHD*DV.5/RHD*01N.01 heterozygote,with the complete deletion of RHD genes on one chromosome,unable to express the D antigen.On the other chromosome,a G＞A mutation occurred at the 697th base of the 5th exon,resulting in a partial D phenotype.This mutation causes internal hydrogen bond changes at the 233 position of RhD protein,resulting in a change in the conformation of the protein,affecting binding to the corresponding antibody.Conclusion:The patient is a heterozygous mutant individual with RHD*DV.5/RHD*01N.01,exhibiting a partial D phenotype serologically.This variation is extremely rare and has been scarcely reported globally.