ObjectiveTo evaluate the impact of yang-reinforcing and blood-activating therapy on the long-term prognosis for patients with dilated cardiomyopathy （DCM） of yang deficiency and blood stasis syndrome. MethodsA retrospective cohort study was conducted involving 371 DCM patients with yang deficiency and blood stasis syndrome. The yang-reinforcing and blood-activating therapy was defined as the exposure factor. Patients were categorized into exposure group （186 cases） and non-exposure group （185 cases） according to whether they received yang-reinforcing and blood-activating therapy combined with conventional western medicine for 6 months or longer. The follow-up period was set at 48 months， and the Kaplan-Meier survival analysis was used to assess the cumulative incidence of major adverse cardiovascular events （MACE） in both groups. Cox regression analysis was used to explore the impact of yang-reinforcing and blood-activating therapy on the risk of MACE， and subgroup analysis was performed. Changes in traditional Chinese medicine （TCM） syndrome score， left ventricular ejection fraction （LVEF）， left ventricular fractional shortening （LVFS）， left ventricular end-diastolic diameter （LVEDD）， and Minnesota Living with Heart Failure Questionnaire （MLHFQ） score were compared between groups at the time of first combined use of yang-reinforcing and blood-activating therapy （before treatment） and 1 year after receiving the therapy （after treatment）. ResultsMACE occurred in 31 cases （16.67%） in the exposure group and 47 cases （25.41%） in the non-exposure group. The cumulative incidence of MACE in the exposure group was significantly lower than that in the non-exposure group ［HR=0.559， 95%CI（0.361，0.895）， P=0.014］. Cox regression analysis showed that yang-reinforcing and blood-activating therapy was an independent factor for reducing the risk of MACE in DCM patients ［HR=0.623， 95%CI（0.396，0.980）， P=0.041］， and consistent results were observed in different subgroups. Compared with pre-treatment， the exposure group showed decreased TCM syndrome score and MLHFQ score， reduced LVEDD， and increased LVEF and LVFS after treatment （P＜0.05）； in the non-exposure group， TCM syndrome score decreased， LVEF and LVFS increased， and LVEDD reduced after treatment （P＜0.05）. After treatment， the exposure group had higher LVEF and LVFS， smaller LVEDD， and lower TCM syndrome score and MLHFQ score compared with the non-exposure group （P＜0.05）. ConclusionCombining yang-reinforcing and blood-activating therapy with conventional western medicine can reduce the risk of MACE in DCM patients with yang deficiency and blood stasis syndrome， meanwhile improving their clinical symptoms， cardiac function， and quality of life.

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.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Objective:To apply the Timed Up and Go Test(TUGT)to investigate the correlation between motor function, emotional state, cognitive function, and sleep quality among elderly individuals in the Chinese community.Methods:A cross-sectional study was conducted, involving 739 subjects aged 60 to 90 years, who were randomly recruited from December 2021 to August 2023 across Beijing, Tianjin, Zhejiang, Guangdong, and Hainan Provinces in China.Basic demographic information was collected, and the TUGT was utilized to assess motor function.Based on the TUGT time(t), the subjects were divided into three groups: normal motor function group, mild motor abnormality group, and significant motor abnormality group.Cognitive function was evaluated using the Chinese Revised Mini-Mental State Examination(MMSE), while the Patient Health Questionnaire Depression Scale(PHQ-9)was employed to measure the degree of depression.Additionally, the Epworth Sleepiness Scale(ESS)was used to assess excessive daytime sleepiness.The correlation between subjects' motor function and their cognitive abilities, mood, and sleep was subsequently analyzed.Results:Systolic blood pressure, heart rate, PHQ-9, MMSE, and ESS scores were identified as significant factors influencing TUGT time.Specifically, TUGT time was positively correlated with PHQ-9 and ESS scores, while exhibiting negative correlations with systolic blood pressure, heart rate, and MMSE scores.Additionally, TUGT time was negatively correlated with the MMSE subcomponents of orientation, immediate memory, and verbal ability.All observed differences were statistically significant(all P<0.05).Logistic regression analysis indicated that an increase in the PHQ-9 score was associated with an odds ratio( OR)of 1.099(95% CI: 1.045-1.155, P<0.001)(mild motor abnormality group)and 1.150(95% CI: 1.066-1.242, P<0.001)(Significant motor abnormality group).Additionally, a reduction in the MMSE score was observed, with an OR of 0.939(95% CI: 0.886-0.995, P<0.001)(mild motor abnormality group)and 0.793(95% CI: 0.729-0.862, P<0.001)(Significant motor abnormality group).Furthermore, an increase in the ESS score was noted, with ORs of 1.139(95% CI: 1.094-1.186, P<0.001)(mild motor abnormality group)and 1.203(95% CI: 1.132-1.279, P<0.001)(Significant motor abnormality group).These findings suggest that these variables are independently related to decreased motor function. Conclusions:Depression, cognitive impairment, and excessive daytime sleepiness are independent risk factors for motor dysfunction among elderly individuals in community settings.The Timed Up and Go Test TUGT can be utilized for the early screening of motor function decline in this population.

Cytokeratin 19 fragment antigen 21-1(CYFRA21-1)is a new biomarker which has received much attention in recent years for cancer screening,and has shown great potentials for screening and diagnosis of various cancers,especially non-small cell lung cancer.CYFRA21-1 level in human serum has important clinical significance in the diagnosis,prognosis and treatment of lung cancer.Recently,a variety of detection techniques have been established to effectively enrich the detection technology system of CYFRA21-1,such as enzyme-linked immunosorbent assay,chemiluminescence,fluorescence,immunochromatography,electrochemical method,and surface enhanced Raman spectroscopy,etc.These techniques provide technical support for early diagnosis of lung cancer.However,the research progress of CYFRA21-1 detection methods is rarely reported.In this paper,CYFRA21-1 and its clinical significance were briefly introduced,and the progress of detection technology in recent ten years was reviewed,which was expected to provide reference for developing more sensitive,accurate,fast and convenient detection methods.

A pyrene-phenol-based fluorescent probe PyP which showed typical intramolecular charge transfer(ICT)and monomer-excimer activities was synthesized by using pyrene carboxaldehyde hydrazone and 4-tert-butyl-2,6-diformylphenol as the raw materials.The effects of solvents on PyP were studied,and the results showed that the color of protic polar solvents(Ethanol,N,N-dimethylformamide,methanol and H2O)were successfully identified.Based on the solvent polarity-regulated PyP monomer-excimer switching,the rapid and highly sensitive ratiometric probe,"Turn-off"and"Turn-on"multimodal probes were established for detection of trace water content in organic solvents(Dimethyl sulfoxide,N,N-dimethylformamide,ethanol and methanol),with detection limits(3σ/k)of 0.0021％,0.046％,0.062％and 0.024％.The method was successfully used to detect water content in dimethyl sulfoxide,N,N-dimethy lformamide,ethanol and methanol commercial organic solvents,with recoveries ranging from 97.2％to 108.0％.The developed method showed good accuracy and stability,and had good application prospect.

The objective assessment of hearing loss is one of the critical components in forensic clini-cal research.Auditory brainstem response(ABR)is an important method for objectively assessing hearing levels.It is divided into various types based on different stimulus signals,each with its own characteris-tics and applications.Among them,narrow-band Chirp ABR,due to its frequency specificity,fulfills the basic requirements for objective assessment of forensic audiology,promising to be an important method of objective hearing assessment in forensic medicine.This article reviews the development history,charac-teristics and clinical applications of Chirp ABR,and envisions its application prospects in forensic audi-tory identification.

Objective:To evaluate the impact of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality and calculate the attributable mortality burden.Methods:This study collected road traffic mortality data from the Disease Surveillance System in Guangdong, Hunan, Zhejiang, Yunnan, and Jilin Provinces from 2013 to 2018. A time-stratified case-crossover design was used in this study, with the death date for each case serving as the case day. Control days were selected from the same year, month, and day of the week as the case day. A conditional logistic regression model was employed to estimate the cumulative associations of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality (lag 0-1 day) and to calculate the attributable fractions (AF).Results:Compared to non-heatwave days, the excess risk ( ER) of road traffic mortality on daytime heatwave days, nighttime heatwave days, and compound heatwave days was 5.3% (95% CI: 0.5%-10.2%), 4.9% (95% CI: 0.5%-9.4%) and 7.5% (95% CI: 2.3%- 12.9%), with corresponding AF of 5.0% (95% CI: 0.5%-9.3%), 4.7% (95% CI: 0.5%-8.6%), and 6.9% (95% CI: 2.3%-11.4%), respectively. Stratified analysis showed that the risk of traffic mortalities caused by daytime heatwaves was higher in females ( ER=15.7%, 95% CI: 5.8%-26.5%) than in males ( ER=1.8%, 95% CI: -3.6%-7.4%). Elderly individuals over 64 years old ( ER=10.9%, 95% CI: 0.3%- 22.6%) had a higher risk of road traffic mortalities from compound heatwaves than those under 45 years old ( ER=2.6%, 95% CI: -5.4%-11.2%). The risk of road traffic injury mortality from motor vehicle accidents caused by compound heatwaves ( ER=16.6%, 95% CI:2.4%-32.7%) was higher than that from non-motor vehicle accidents ( ER=5.7%, 95% CI:0.1%-11.5%). Conclusions:Short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves was associated with an increased risk of road traffic mortality, with the strongest association observed for compound heatwaves. The mortality burden attributable to compound heatwaves was higher than that for daytime and nighttime heatwaves. Heatwaves were more significantly associated with road traffic mortality risk among females, elderly individuals over 64 years old, and motor vehicle accidents.

Aim To evaluate the role of the glucose transporter protein 1(GLUT1)-dependent glycolytic in the attenuation of oxygen-glucose deprivation-reoxygen-ation(OGD/R)injury in HK-2 cells by dexmedetomi-dine(Dex).Methods C57/BL6 mice were random-ly divided into three groups(n=6),namely,sham operation group(Sham group),renal ischemia reper-fusion group(I/R group)and Dex group(I/R+Dex group).Serum creatinine(Cr)and urea nitrogen(BUN)were measured,while the levels of key glyco-lytic enzymes HK2,PFKFB3 and GLUT1 were meas-ured.HK-2 cells were cultured and randomised into seven groups(n=6),which was treated with OGD/R,overexpression or interference with GLUT1,Dex and glycolysis inhibitor 2-DG.CCK-8 and LDH activi-ty were used to detect cellular damage.Glycolysis lev-els were detected by lactate and ECAR.The inflamma-tory level was reflected by qRT-PCR for IL-6 and TNF-α.qRT-PCR and Western blot were performed to de-tect the levels of GLUT1,HK2,and PFKFB3.Results Dex significantly ameliorated kidney injury and HK-2 cell injury(P＜0.05).Dex inhibited the OGD/R-induced rise in lactate and extracellular acidification rate(ECAR),as evidenced by suppression of the ex-pression of GLUT1,HK2 and PFKFB3(P＜0.05).In vitro experiments showed that GLUT1 knockdown sig-nificantly improved OGD/R-induced cellular damage.Lactate,ECAR,glycolysis-related mRNAs and pro-teins were inhibited by GLUT1 knockdown(P＜0.05).Significantly,there were no significant differ-ences in above indexes after Dex treatment based on GLUT1 knockdown.Overexpression of GLUT1 abroga-ted the protective effects of Dex,while reversing the inhibitory effects of Dex on the expression of GLUT1,HK2,and PFKFB3(P＜0.05).Conclusions Dexmedetomidine attenuates OGD/R induced injury in HK-2 cells by inhibiting GLUT1-dependent glycolysis.