Objective: To assess the effect of 12-year-old children s pit and fissure sealants on the health of first permanent molars, so as to provide evidence for optimizing caries prevention strategies among children. Methods: In March 2025, a cluster random sampling method was used to conduct oral examinations on 965 students aged 12 from Chengdu s 2021 Comprehensive Intervention Program for Pediatric Oral Diseases. Data from the Comprehensive Intervention System for Children s Oral Diseases were referenced. Participants were divided into a sealed group ( n =755) and an unsealed group ( n =210) based on whether they had received sealants on their first permanent molars. Chi square test or analysis of variance were used to compare indicators such as caries incidence, new caries detection rate, and new caries mean (DMFT increment) between the two groups Results: The sealed group showed significantly lower caries incidence, new caries detection rate, and new caries mean (33.38%, 17.65%, 0.59±1.00) compared to the unsealed group (43.81%, 24.70%, 0.87±1.22)( χ 2/F =7.79, 18.26, 9.55, all P <0.05). However, no significant difference was found in the filled teeth ratio between the two groups (20.38% , 20.16%; χ 2=0.01, P =0.94). In girls, the sealed group exhibited significantly lower caries incidence, new caries detection rate, and new caries mean (36.78%, 20.99%, 0.69± 1.10 ) than the unsealed group (57.55%, 33.52%, 1.15±1.29) ( χ 2/F =14.42, 23.76, 10.92, all P <0.05), whereas no significant differences were observed between boys in the sealed (30.47%, 14.85%, 0.50±0.89) and unsealed groups (29.81%, 16.18%, 0.59± 1.08) ( χ 2/F =0.02, 0.41, 0.74, all P >0.05). Boys had significantly lower new caries detection rates and new caries means than girls in both groups ( χ 2/F =16.20, 6.94; 29.93, 11.84, all P <0.05). In urban areas, the sealed group had lower new caries detection rates and new caries means (19.37%, 0.68±1.04) than the unsealed group (24.66%, 0.90±1.20) ( χ 2/F =6.86, 3.94, both P <0.05). In suburban areas, all indicators for the sealed group (24.71%, 13.77%, 0.42±0.87) were significantly lower than those for the unsealed group (38.81%, 24.77%, 0.82±1.28) ( χ 2/F =5.28, 15.36, 6.00, all P <0.05). Indicators from specialized dental institutions (11.25%, 4.81%, 0.16±0.56) were significantly lower than those from county level or above general hospitals (33.33%, 19.11%, 0.38±1.00) and primary healthcare institutions (37.59%, 19.24%, 0.67±1.05) ( χ 2/F =20.99, 34.31, 21.08 , all P <0.01). Conclusions The 12-year-old children s pit and fissure sealants effectively reduce the caries incidence in first permanent molars, particularly showing significant effectiveness in girls and suburban children. Intervention strategies should be optimized according to gender.

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 effects of transcutaneous auricular vagus nerve stimula-tion(taVNS)on preoperative anxiety and sleep quality in patients undergoing laparoscopic myomecto-my.Methods A total of 106 patients scheduled for elective laparoscopic myomectomy were randomly divided into active stimulation group(a-taVNS group,n=53)and sham stimulation group(s-taVNS group,n=53).Trait Anxiety Inventory(TAI)scores,State Anxiety Inventory(SAI)scores,Hos-pital Anxiety and Depression Scale-anxiety(HADS-A)scores,Amsterdam Preoperative Anxiety and Information Scale-anxiety(APAISa)scores,Athens Insomnia Scale(AIS)scores,hemodynamic parameters,and adverse reactions were evaluated before intervention(T0),30 min after interven-tion(T1),and the next morning(T2).The degrees of anxiety improvement(△SAI=SAIT0-SAIT1;△HADS-A=HADS-AT0-HADS-AT1;△APAISa=APAISaT0-APAISaT1)and sleep improvement(△AIS=AIST0-AIST2)were calculated,and their correlations were assessed.Results At T0,there were no significant differences in SAI,HADS-A,and APAISa scores between the two groups(P=0.376,0.682,0.144).At T1,there were significant differences in SAI and HADS-A scores between the two groups(adjusted P＜0.05),while there was no significant difference in APAISa scores(P=0.141).Compared with the s-taVNS group,the a-taVNS group had higher improvement values of △SAI,△HADS-A,and △APAISa(P＜0.001).Compared with T0,the AIS score de-creased and the incidence of sleep disorders decreased at T2 in the a-taVNS group(P＜0.05).Compared with the s-taVNS group,the AIS score and the proportion of patients with sleep disorders decreased at T2 in the a-taVNS group(P＜0.05).There was a positive correlation between the de-gree of anxiety improvement and the degree of sleep improvement in the a-taVNS group(P＜0.05),while there was no significant correlation in the s-taVNS group(P＞0.05).Compared with T0,sys-tolic blood pressure,diastolic blood pressure,and heart rate decreased at T1 in both groups,but there were no significant differences in these parameters between the two groups(P＞0.05).During the study period,no adverse events such as tinnitus,dizziness,headache,nausea,vomiting,or fa-cial flushing occurred in either group.Conclusion The method taVNS can improve preoperative anxiety and reduce the incidence of sleep disorders in patients undergoing laparoscopic myomectomy.

AIM To establish the preparation process and quality standard for Zhenggu Pills.METHODS With decoction time,decoction frequency and water addition as influencing factors,comprehensive score for extract yield and transfer rates of epicatechin and naringin as an evaluation index,the decoction process was optimized by orthogonal test.With sugarless paste relative density,medicinal powder fineness,sugarless paste-corn starch ratio,drying temperature and drying time as influencing factors,soft material traits,pill formability,moisture and disintegration time limit as evaluation indices,the formability process was optimized by single factor test.TLC was adopted in the qualitative identification of Dipsaci Radix,salt-processed Psoraleae Fructus,cooked Rhei Radix et Rhizoma and Notoginseng Radix et Rhizoma.HPLC was used for the content determination of paeoniflorin and naringin.RESULTS The optimal decoction process was determined to be 0.5 h for decoction time,two times for decoction frequency,and 10 times for water addition,the comprehensive score was 0.93.The optimal formability process was determined to be 1.21-1.22 for sugarless paste relative density,80 mesh for medicinal powder fineness,1∶0.17-1∶0.18 for sugarless paste-corn starch ratio,70 ℃ for drying temperature,and 24 h for drying time,good soft material traits and pill formability were observable,and moisture and disintegration time limit accored with 2020 edition of Chinese Pharmacopoeia requirements.The TLC spots were clear without negative interference.Two constituents showed good linear relationships within 61.30-490.41 μg/mL(r=0.999 8)and 3.27-26.18 μg/mL(r=0.999 8),whose average recoveries were 100.15％and 98.15％with the RSDs of 0.55％and 2.30％,respectively.CONCLUSION This stable,reliable and specific method can be used for the production and quality evaluation of Zhenggu Pills.

AIM To establish the quantitative models for gallic acid,mononucleoside,loganin,resveratrol,and rhein in Yishen Xiezhuo Mixture.METHODS HPLC was adopted in the content determination of various effective components,after which the near-infrared spectroscopy(NIRS)data were collected in 128 batches of samples and pretreatment was conducted,competitive adaptive reweighting sampling(CARS)algorithm was used for screening wavelength,partial least square method(PLS)regression analysis was performed.RESULTS There were no significant differences between the predicted values obtained by PLS models and measured values obtained by HPLC for various effective components(P＞0.05).CONCLUSION The quantitative models established by NIRS combined with chemometrics display good predictive performance,which can be used for the rapid determination of effective components in Yishen Xiezhuo Mixture,and provide a reference for the rapid monitoring of other traditional Chinese medicine preparations in production processes.

Objective:To investigate the feasibility and safety of intracardiac echocardiography(ICE)combined with total three-dimensional(T3D)technique in zero-fluoroscopy individualized transseptal puncture.Methods:A total of 112 patients with atrial fibrillation who underwent radiofrequency ablation in Yongchuan Hospital Affiliated to Chongqing Medical University from April 2021 to March 2024 were enrolled,and according to the method for transseptal puncture,they were randomly divided into ICE+T3D group with 56 patients and ICE group with 56 patients.The two groups were analyzed in terms of baseline data,time to atrial reconstruc-tion,time to coronary sinus electrode placement,frequency of ICE probe adjustment during transseptal puncture,duration of transsep-tal puncture,pretreatment time before ablation,incidence rate of complications,and the duration and dosage of X-ray exposure.Results:There were no significant differences in baseline data between the two groups.Compared with the ICE group,the ICE+T3D group had a significantly lower frequency of ICE probe adjustment during transseptal puncture(1.70±0.63 vs.5.34±1.71,P<0.001)and the duration of transseptal puncture(3.66±1.09 min vs.4.90±1.92 min,P<0.001).Compared with the ICE group,the ICE+T3D group had significantly longer time to atrial reconstruction(22.44±3.13 min vs.12.34±2.12 min,P<0.001)and pretreatment time be-fore ablation(49.41±3.52 min vs.37.65±4.04 min,P<0.001).In the ICE+T3D group,43(76.8%)patients achieved zero radiation during pretreatment before ablation,and 13 patients received X-ray due to the difficulty in catheter placement;compared with the ICE group,the ICE+T3D group had a significantly shorter duration of X-ray exposure(1.68±0.72 min vs.3.14±1.95 min,P=0.010)and a significantly lower dosage of X-ray exposure(6.28±2.78 mGy vs.23.85±21.32 mGy,P=0.004).During the stage of transseptal punc-ture,all patients in the ICE+T3D group achieved zero radiation,while 45 patients(80.4%)in the ICE patients received X-ray.In terms of complications,there were no life-threatening complications such as cardiac tamponade,perforation of the aorta by mistake,and embolization in either group,while there was one case(1.8%)of vascular complications in each group.Conclusions:ICE combined with T3D after integration and improvement is a safe and reliable procedure for zero-fluoroscopy individualized transseptal puncture.

In recent years,significant breakthroughs have been achieved in the immunotherapy for Alzheimer's disease.In line with global advancements,two anti-amyloid-β monoclonal antibodies have been approved and successfully launched in China for clinical use.Lecanemab and Donanemab were officially used in June 2024 and April 2025 in China,respectively.In order to standardize the rational and safe application of anti-amyloid-β monoclonal antibodies for Alzheimer's disease in China,this article integrates recom-mendations from the clinical trials and real-world experience from the author's team and domestic peers to further update the recom-mendations for the clinical use of anti-amyloid-β monoclonal antibody based on the 2024 version.It includes indications for therapy,pre-treatment evaluation and preparation,administration protocols and safety measures during treatment,and post-treatment monitor-ing strategies.

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.

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.