ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Anti-CD20 monoclonal antibodies for the treatment of refractory nephrotic syndrome （RNS） in children. The first- generation rituximab is the most widely used in clinical practice； it shows definite efficacy in children with RNS， is recommended by guidelines， particularly for achieving a high remission rate in minimal change nephrosis， and can significantly reduce the cumulative use of glucocorticoids and immunosuppressants. The second-generation ofatumumab has potential as an alternative treatment for patients who are intolerant or resistant to rituximab， while the third-generation obinutuzumab has shown efficacy in complex cases such as rituximab resistance or post-transplant recurrence. However， there is still controversy regarding the optimization of rituximab treatment dosage and whether ofatumumab and obinutuzumab offer greater advantages than rituximab for the treatment of RNS in children. The most common adverse reaction induced by anti-CD20 monoclonal antibodies is infusion reactions， and long-term adverse events mainly include increased risks of sustained immunosuppression and infections. Rituximab has significant economic advantages for the treatment of RNS， but additional pharmacoeconomic research based on China’s healthcare environment is needed to evaluate the cost-effectiveness of ofatumumab and obinutuzumab in this population. Given that the current use of ofatumumab and obinutuzumab in this field is considered off-label use， clinical application should only proceed after a rigorous evaluation of the patient’s benefits and risks.

Objective To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database,to explore research hotspots and developmen-tal trends.Methods A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the litera-ture measuring tool CiteSpace.The authors,institution,country(region),title,journal,keywords,cited references and other information of relevant literatures were analyzed.Results A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries(regions)were identi-fied,with the number of articles published showing an increasing trend year by year.Among them,the United States had the highest number of publications and China ranked the second.Academy of Forensic Science had the highest number of publications among the institutions.Forensic Science Inter-national,Journal of Forensic Sciences,International Journal of Legal Medicine ranked high in publica-tion and citation frequency.Through the analysis of keywords,it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technol-ogy for sex and age estimation,cause of death analysis,postmortem interval estimation,individual identification and so on.Conclusion It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research.Exploring the combination of advanced ar-tificial intelligence technologies with forensic research will be a hotspot and direction for future re-search.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Objective:To investigate the effects of different tube voltages combined with artificial intelligence reconstruction algorithm(CI)on the computed tomography(CT)imaging quality and radiation dose of chest phantom on the basis of the CT scan for an adult male simulated chest phantom(PH-N1).Methods:A 512-slice CT scanner of ultrahigh-end was adopted to conduct scan,and the images were divided into 70 kV group,80 kV group,100 kV group and 120 kV group according to different tube voltage.For 4 groups of CT scan images with different tube voltages,the 10%,30%,50%,70%and 90%CI were adopted to reconstruct 1mm thin layer image.The CT volume dose index(CTDIvol)and the dose-length product(DLP)of the scans of 4 groups were compared.The CT values and standard deviation(SD)values of the aorta,abdominal wall fat and erector spine muscle were measured.Two senior diagnostic physicians with more than 5 years of work experience independently and double-blindly evaluated the image quality by using 5-point scale.A Kappa consistency test was conducted.One-way analysis of variance was adopted to compare the differences of CT values and SD values of the tissues of image targets.The Friedman rank-sum test was adopted to compare the differences of subjective image qualities among different groups.Results:The differences of CTDIvol and DLP among 4 groups with different tube voltages were significant(F=1855.617,3996.118,P<0.05),respectively.Under 70 kV tube voltage,there were no significant differences in CT values of the aorta,abdominal wall fat and erector spine muscle,which were reconstructed by using 10%,30%,50%,70%and 90%CI(P>0.05),while the differences of SD values among them were statistically significant(F=32.267,53.327,14.873,P<0.05),respectively.Under the different tube voltages of 4 groups,which were reconstructed by 90%CI,the CT values of aorta,abdominal wall fat and erector spine muscle gradually decreased with decreasing of tube voltage,the differences were significant(F=139.899,2563.93,219.231,P<0.05),respectively.The consistency of subjective scores between two diagnostic physicians was better for each group of images(Kappa=0.712～0.869).Conclusion:Compared with 80 kV,90 kV and 120 kV images,the reconstructed images with 90%CI algorithm under 70 kV tube voltage can significantly reduce the radiation dose,and the images have a favorable signal-to-noise ratio at the same time.

Objective To identify the risk factors of patients with frequent acute exacerbations of chro-nic obstructive pulmonary disease(AECOPD)and construct a prediction model based on the clinical data,provi-ding a theoretical basis for the clinical prevention and treatment.Methods A total of 25 638 COPD patients ad-mitted to the Department of Respiratory and Critical Care Medicine,the Third People's Hospital of Chengdu from January 1,2013 to May 1,2023 were selected.Among them,11 315 patients were included according to the inclusion and exclusion criteria,and their clinical characteristics were analyzed.Multivariate Logistic regression was carried out to identify the risk factors for frequent AECOPD.A nomogram model was utilized to quantify the risk of acute exacerbation,and the performance of the prediction model was assessed based on the area under the receiver operating characteristic(ROC)curve.Results In the patients with frequent AECOPD,male percentage(P＜0.001),age(P＜0.001),urban residence(P＜0.001),smoking(P＜0.001),length of stay(P＜0.001),total cost(P＜0.001),antibiotic cost(P＜0.001),diabetes(P=0.003),respiratory failure(P＜0.001),heart disease(P＜0.001),application of systemic glucocorticoids(P＜0.001),white blood cell count(P＜0.001),neutrophil percentage(P＜0.001),C-reactive protein(P＜0.001),total cholesterol(P＜0.001),and brain natriuretic peptide(BNP)(P＜0.001)were all higher than those in the patients with infre-quent AECOPD.Multivariate Logistic regression analysis revealed that age,urban residence,smoking,diabe-tes,heart disease,Pseudomonas aeruginosa infection,application of systemic glucocorticoids,antibiotics,re-spiratory failure,and elevated white blood cell count,total cholesterol,and BNP were independent risk factors for hospitalization due to frequent AECOPD.A nomogram model of hospitalization due to frequent AECOPD was constructed according to risk factors.The ROC curve was established to evaluate the performance of the model,which showed the area under the ROC curve of 0.899(95％CI=0.892-0.905),the sensitivity of 85.30％,and the specificity of 79.80％.Conclusions Frequent AECOPD is associated with smoking,heart disease,ap-plication of systemic glucocorticoids,Pseudomonas aeruginosa infection,age,low body mass index,and elevat-ed BNP.Predicting the risks of hospitalization due to frequent AECOPD by the established model can provide the-oretical support for the treatment and risk factor management of the patients.

Isocitrate dehydrogenase 1 (IDH1) R132H is the most common mutated gene in grade II-III gliomas and oligodendrogliomas. Instead of activating telomerase (a reverse transcriptase which using RNA as a template to extend telomere length), the majority of IDH1^R132H mutant glioma maintain telomere length through an alternative mechanism that relies on homologous recombination (HR), which is known as alterative lengthening of telomere (ALT).The phenotype of ALT mechanism include: ALT associated promyelocytic leukemia protein (PML) bodies (APBs); extrachromosomal telomeric DNA repeats such as C- and T-loops; telomeric sister chromatid exchange (T-SCE), etc. The mechanism of ALT activation is not fully understood. Recent studies have shown that mutation IDH1 contributes to ALT phenotype in glioma cells in at least three key ways. Firstly, the IDH1^R132H mutation mediates RAP1 down-regulation leading to telomere dysfunction, thus ensuring persistent endogenous telomeric DNA damage, which is important for ALT activation. Spontaneous DNA damage at telomeres may provide a substrate for mutation break-induced replication (BIR)‑mediated ALT telomere lengthening, and it has been demonstrated that RAP1 inhibits telomeric repeat-containing RNA, transcribed from telomeric DNA repeat sequences (TERRA) transcription to down-regulate ALT telomere DNA replication stress and telomeric DNA damage, thereby inhibiting ALT telomere synthesis. Similarly, in ALT cells, knockdown of telomere-specific RNaseH1 nuclease triggers TERRA accumulation, which leads to increased replication pressure. Overexpression of RNaseH1, on the other hand, attenuates the recombination capacity of ALT telomeres, leading to telomere depletion, suggesting that RAP1 can regulate the level of replication pressure and thus ALT activity by controlling TERRA expression. Secondly, the IDH1^R132H also alters the preference of the telomere damage repair pathway by down-regulating XRCC1, which inhibits the alternative non-homologous end joining (A-NHEJ) pathway at telomeres and alters cellular preference for the HR pathway to promote ALT. Finally, the IDH1^R132H has a decreased affinity for isocitric acid and NADP+ and an increased affinity for α ketoglutarate (α‑KG) and NADPH, so that the mutant IDH1^R132H catalyzes the hydrogenation of α‑KG to produce 2-hydroxyglutarate (2-HG)in a NADPH-dependent manner. Because 2-HG is structurally similar to α‑KG, which maintains the trimethylation level of H3k9me3 by competitively inhibiting the activity of the α‑KG-dependent histone demethylase KDM4B, and recruits heterochromatin protein HP1α to heterochromatinize telomeres, and promote ALT phenotypes in cooperation with the inactivating of ATRX. In addition, it has been shown that APBs contain telomeric chromatin, which is essentially heterochromatin, and HP1α is directly involved in the formation of APBs. Based on these studies, this article reviews the mechanism of IDH1^R132H mediated telomere dysfunction and the preference of DNA repair pathway at telomeres in cooperate with ATRX loss to promote ALT, which may provide references for clinical targeted therapy of IDH1^R132H mutant glioma.

As a rapidly developing frontier discipline, structural biology has penetrated into every field of life science research. The course of “Structural Biology” plays an important role in expanding the knowledge system of undergraduate students and promoting students’ scientific spirit and innovation. For the high-quality training of highly skilled talents, we aimed to promote the original innovation of students, the ability of thinking, and the ability of engineering practice. The trinity education concept, including shape of the value, passing on knowledge, and ability cultivation, was applied. During the reform, we explored a step-by-step course content and searched for factors involved in ideological and political education. Based on the problem-based learning (PBL) method, a hybrid teaching model was designed to cultivate the problem-thinking and problem-solving skills of students. Meanwhile, a number of evaluation systems for students and teachers were established, which may be generally adopted for the course of “Structural Biology”. The survey data suggested that the exploration has a good effect on teaching and training and is conducive to the cultivation of research-oriented, comprehensive, innovative talents under the background of “New Engineering”.

Piperazines are a class of new psychoactive substances with hallucinogenic effects that af-fect the central nervous system by affecting the level of monoamine neurotransmitters.Abuse of pipera-zines will produce stimulating and hallucinogenic effects,accompanied by headache,dizziness,anxiety,insomnia,vomiting,chest pain,tachycardia,hypertension and other adverse reactions,and may even cause cardiovascular diseases and multiple organ failure and lead to death,seriously affecting human physical and mental health and public safety.The abuse of new psychoactive substance piperazines has attracted extensive attention from the international community.The study of its pharmacological toxi-cology and analytical methods has become a research hotspot in the field of forensic medicine.This paper reviews the in vivo processes,sample treatment and analytical methods of existing piperazines,in order to provide reference for forensic identification.

Objective To construct a knowledge graph of Hai Yao Ben Cao(Oversea Materia Medica)based on Neo4j technology,and to analyze the knowledge graph and discuss its significance.Methods Taking the original text of Hai Yao Ben Cao as the data source,the data information related to Chinese medicine was extracted,and then the Excel data table was established.The data information included a total of 13 items,and covered the serial number of Chinese medicines,name of Chinese medicines,medicinal part,origin,medicinal property,medicinal flavor,efficacy,toxicity,and various indicators.The extracted information was preprocessed and standardized.And then the constructed knowledge graph was stored and analyzed by graph database Neo4j.Results The knowledge graph of Hai Yao Ben Cao based on Neo4j was constructed,and a total of 518 entities and 1 046 entity relationships were obtained,which were mainly related with origin,medicinal flavor,and efficacy.The results of the entity statistics presented the status of medicinal development and the distribution of oversea medicines in Late Tang and Five Dynasties.The constructed knowledge graph of Hai Yao Ben Cao ensured the realization of information query and content visualization.Conclusion The constructed knowledge graph of Hai Yao Ben Cao intuitively shows the relationship among the category,origin,medicinal property,medicinal flavor,toxicity and efficacy of the medicines in the book,which will lay a foundation for further research on the medicine-medicine relationship and medicine-disease relationship,and for the study of the history of traditional Chinese medicine(TCM)development.The knowledge graph of Hai Yao Ben Cao will also provide methods for the rational and effective utilization of ancient TCM books,being beneficial to the modernization of TCM.