Objective To study the five-year survival status and influencing factors of elderly patients with lung cancer complicated with chronic obstructive pulmonary disease (COPD). Methods A cohort study was conducted to follow up 450 patients with lung cancer and chronic obstructive pulmonary disease who were hospitalized in our hospital from January 2018 to December 2023. The endpoint of the follow-up was the end of a five-year period or death. The Life Tables method was used to calculate survival rates and plot survival curves. The Cox proportional hazards model was used to analyze the influencing factors of five-year survival. Results The results indicated that the overall five-year survival rate of patients was 4.89%, and it decreased year by year. Cox regression analysis showed that age, gender, family functioning, and psychological status significantly influenced patient survival rate (all P<0.05). Stratified analysis found that the smoking status, family functioning, and psychological status of male patients all had an impact on survival rate (all P<0.05), while the psychological status of female patients had a more significant impact on survival (P=0.008). Conclusion This study provides a scientific basis for comprehensive intervention of elderly lung cancer patients with COPD. It is recommended that clinical attention should be paid to psychological and family factors to improve patient prognosis.

ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

Inteins are unique protein insertion sequences capable of self-excision, enabling the covalent ligation of flanking extein peptides via amide bond formation. This process proceeds spontaneously without requiring external enzymes, cofactors, or chemical reagents, granting inteins exceptional biocompatibility and traceless performance in protein engineering applications. Split inteins represent a specialized and versatile subclass whose splicing domains are encoded by two separate gene fragments rather than a single continuous open reading frame. These fragments, known as the N-terminal (IntN) and C-terminal (IntC) split inteins, associate through non-covalent interactions including hydrophobic forces, hydrogen bonds, and van der Waals forces to assemble into an active three-dimensional structure, which then drives efficient extein ligation and enables protein trans-splicing. Protein trans-splicing mediated by split inteins has become a cornerstone for traceless protein ligation owing to its high specificity and irreversibility, fundamentally reshaping strategies for protein modification, assembly, and functional regulation. Compared with traditional chemical ligation methods, split intein systems require no complex chemical derivatization of peptide fragments and can operate efficiently at micromolar concentrations under physiological conditions, thus avoiding structural and functional damage caused by organic reagents. In contrast to enzymatic ligation tools such as sortase, split inteins eliminate the need for additional enzymes or cofactors, simplifying reaction systems, reducing costs, and minimizing non-specific side products. These distinctive advantages render split inteins highly promising for applications in chemical biology, synthetic biology, and biopharmaceutical development. In recent years, deepened mechanistic understanding has established structure-guided rational design as the primary approach to overcoming key limitations of split inteins, including intrinsic aggregation propensity, strict extein sequence dependence, and limited splicing efficiency. Bioinformatic tools have been used to identify aggregation-prone regions in the IntN fragment, and site-directed mutagenesis of hydrophobic residues, relocation of split sites, or removal of misfolding-prone sequences has substantially reduced in vitro aggregation and improved soluble expression and assembly activity. Rational engineering of catalytic residues and adjacent flexible loops has relaxed strict amino acid preferences at extein junctions, enhancing sequence tolerance and reducing the risk of functional impairment in target proteins. Consensus design based on multiple sequence alignments has yielded ultra-fast splicing variants such as Cfa DnaE and Cat-TerL, which exhibit significantly accelerated kinetics and improved tolerance to denaturing conditions. Meanwhile, advances in structural biology have further clarified the conformational dynamics and catalytic mechanisms of splicing, supporting the precise design of high-performance intein modules. On this basis, electrostatic interaction tuning and metagenomic screening have yielded multiple mutually orthogonal split intein pairs, enabling selective multi-fragment protein ligation and providing new routes for the efficient synthesis of large multi-domain functional proteins. With these engineered split inteins offering continuously improved performance and expanded applicability, protein trans-splicing has been widely applied in numerous cutting-edge areas of protein research and biomedicine. In gene delivery, split intein-based systems overcome the packaging limit of adeno-associated viral vectors, enabling the accurate reconstitution of large therapeutic proteins and base editors in target cells, thereby enhancing the efficacy and scope of gene therapy for genetic diseases. In internal protein sequence editing, split inteins mediate precise sequence replacement and modification in flexible regions or loops of target proteins, without the need for complex multi-step ligation and protein refolding involved in traditional protein semisynthesis. In protein-protein interaction studies, intein-mediated splicing covalently captures transient and weak intracellular complexes, enabling sensitive, high-throughput interaction detection and drug screening. In synthetic biology, conditionally controllable splicing systems support the construction of diverse intracellular and cell-surface biological logic gates for the precise regulation of cellular behavior. In mechanistic biochemical research, split inteins enable photocatalytic proximity labeling and site-specific tagging, allowing the preparation of homogeneous protein samples carrying precise post-translational modifications such as ubiquitination and polyglutamylation for chromatin interactome analysis and epigenetic studies. Moreover, covalent trapping strategies using split inteins stabilize transient enzymatic intermediates, providing unprecedented insights into molecular mechanisms such as nucleosome ubiquitination that are difficult to elucidate using conventional methods. This review systematically summarizes key technological advances in split inteins over the past decade, highlighting engineering strategies, mechanistic insights, and the development of orthogonal components. It comprehensively surveys emerging applications at the frontiers of protein research, analyzes current core challenges, and proposes future directions, particularly emphasizing artificial intelligence-driven de novo design and novel splicing pathways to break existing technical bottlenecks. By enabling traceless, efficient, and versatile protein manipulation, split inteins continue to serve as indispensable tools that drive innovation in protein engineering and fundamental life science research.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective This study conducted molecular biological identification of the viruses carried by Culex pipiens pallens specimens collected in Shunyi District, Beijing in 2023, and observed the changes in the infection rate of the viruses carried by Cx. pipiens pallens at different collection times. Methods Cx. pipiens pallens were collected using carbon dioxide mosquito traps. The mosquito samples were ground in batches and analyzed by molecular biology technologies. The virus infection rate at different collection times was analyzed statistically. Results 17 strains of Culex pipiens pallens densovirus(CppDNV)were identified from Cx. pipiens pallens samples collected in Shunyi District, Beijing, in 2023. The nucleotide sequence analysis of the virus genome coding region showed that CppDNV was a single-stranded DNA virus with a total length of 3 335 nt, encoding 2 non-structural proteins(NS1, NS2)and 1 capsid protein(VP). The nucleotide(amino acid)sequence lengths of the three proteins were 2 376 nt(791 aa),1 092 nt(363 aa)and 1 071 nt(356 aa), respectively. Phylogenetic analysis showed that CppDNV was located in genus Brevihamaparvovirus. Statistical analysis showed no significant difference in infection rates across collection times(χ2=4.429, P=0.194). Conclusions CppDNV was identified in Cx. pipiens pallens in Beijing, and it was stably maintained in this natural population.

Objective:To construct a recommended list of high-alert medication (HAM) based on big data from medication error (ME) reports in China, providing reference for preventing and reducing HAM-related risks.Methods:The drugs involved in the serious ME reports of the National Monitoring Network for Clinical Safe Medication (Monitoring Network) were collected (as of December 31, 2023), and the candidate drugs were preliminarily determined referring to the HAM list of China 2023 (Chinese list) and the latest three lists of American Institute for Safe Medication Practices (ISMP). Candidate drugs that were included in both the Chinese list and ISMP lists, as well as those existed in the Chinese list but had never been included in the ISMP lists were included in the current list, and their risk levels followed the original risks in the Chinese list. Candidate drugs that existed in the Chinese list but had been excluded from the ISMP lists, and those existed in the ISMP lists but had not been included in the Chinese list were listed as suspected drugs. For the other candidate drugs, those did not meet the definition of HAM were excluded firstly, and those related to ME that had caused serious harm were listed as suspected drugs, according to the judicial cases on ME of China Judgements Online and PKULAW database. Two methods, including Delphi expert consultation and questionnaire survey, were used to determine whether the above suspected drugs were included in the HAM list and their risk levels.Results:A total of 138 drugs were obtained through the initial screening, 106 of which were directly included in the current list, and 32 of which were listed as drugs requiring further assessment. After 2 rounds of Delphi expert consultation by 18 experts and surveys with 136 valid questionnaires, 32 suspected drugs did not meet the inclusion criteria. Finally, a total of 106 drugs were included in the current list, including 51 A-class drugs in 9 categories, 33 B-class drugs in 9 categories, and 22 C-class drugs in 5 categories.Conclusion:Based on the big data of the ME reports in China, a HAM list is constructed, which is accurate and concise and better fits the actual clinical drug risks in China, helping to improve the drug safety management.

Objective To explore the short-term and long-term efficacy of partial splenic artery embolization(PSE)in the treat-ment of cirrhosis with hypersplenism.Methods A retrospective analysis was conducted on 35 patients with cirrhosis and hyper-splenism who underwent PSE treatment.Data on white blood cell(WBC),red blood cell(RBC),platelet count(PLT),hemoglobin(HGB),total bilirubin(TBiL),albumin(ALB),prothrombin time(PT),and D-dimer were collected at the three time points:before surgery,1 week after surgery,and 1 year after surgery.The changes in these parameters across the three time points were observed and compared.One-way ANOVA was used for repeated measurements,and time pairwise comparisons were made between the three time points.According to the formation of portal thrombosis,patients were divided into thrombus group and no-thrombus group.The D-dimer values were compared before surgery and 1 week after surgery.Results WBC and PLT were significantly higher 1 week and 1 year after surgery than those before surgery,with the most significant increase 1 week after surgery,and there was also statistically sig-nificant difference between 1 week after surgery and 1 year after surgery(P1,P2,P3<0.05).There were no significant differences in RBC and HGB between 1 week after surgery and before surgery(RBC P1=0.835,HGB P1=0.446).However,RBC and HGB 1 year after surgery were significantly higher than those before surgery and 1 week after surgery(RBC P2=0.039,P3=0.015;HGB P2=0.001,P3=0.010).There were significant differences in TBiL,ALB,PT,and D-dimer 1 week after surgery compared with those before surgery(TBiL P1=0.006,ALB P1<0.001,PT P1=0.001,D-dimer P1<0.001),but there was no significant differ-ence between 1 year after surgery and before surgery(all P2>0.05).The D-dimer of the thrombus group was significantly higher than that of the no-thrombus group 1 week after surgery,with a statistical significance(P=0.024),however,there was no signifi-cant difference in D-dimer between the two groups before surgery.Conclusion PSE in the treatment of cirrhosis with hypersplenism shows positive short-term and long-term efficacy for WBC and PLT.The short-term increase of RBC and HGB is not obvious,however the long-term efficacy is significant.In the short-term after surgery,TBiL increase,ALB decrease,PT prolonge,and liver reserve function decrease,but there was no long-term effect.The increase of D-dimer after surgery can easily induce portal thrombosis,and anticoagulation therapy can be given in the short-term after surgery.

Aim To explore the role and mechanism of epimedokoreanin B(EKB)in HepaRG cell pyroptosis through endoplasmic reticulum stress and NLRP1-me-diated pyroptosis pathway.Methods The effect of EKB on the viability of HepaRG cells at different con-centrations was determined by MTT assay,and the cell growth status was recorded by Incucyte.Four groups of HepaRG cells were set up.The control group was cul-tured with complete medium for 24 h;the drug admin-istration group was cultured with three concentration gradients of 6.25,12.5 and 25 μmol·L-1 of EKB for 24 h.Western blot was used to detect the expression levels of endoplasmic reticulum stress-related proteins and pyroptosis-related proteins in the cells of each group.Results HepaRG cells showed cytotoxicity at a concentration of 6.25 μmol·L-1 for 24 h,and the half maximal inhibitory concentration(IC50)was 12.41 μmol·L-1.Incucyte recordings of the cell growth status showed that the cells in the control group were in good growth status,and the vesicular pyropto-sis cells appeared in the different concentrations of EKB and the cells swelled and ruptured after 24 h.Western blot showed that the protein expression levels of endoplasmic reticulum stress-related proteins pERK,eIF-2α,ATF-4,GRP78,and CHOP significantly in-creased in HepaRG cells at 25 μmol·L-1 of EKB compared with the control group.The proteins of the classical pathway of cellular pyroptosis mediated by NLRP1,caspase-1,cleaved caspase-1,GSDMD,GS-DMD-N significantly increased in HepaRG cells.Con-clusion EKB administration induces HepaRG cell py-roptosis,and EKB activates HepaRG cells to undergo endoplasmic reticulum stress and activates the NLRP1/caspase-1/GSDMD-mediated pyroptosis pathway.

Objective Prepubertal mice are administered subcutaneously with letrozole sustained-release pellets behind the neck and treated with a high-fat diet to establish a mouse model of polycystic ovary syndrome(PCOS).The liver transcriptomes of the model mice are compared with those of the placebo control mice to investigate the underlying mechanisms of liver involvement in the pathogenesis of PCOS.Methods A customized 2 mg dose of letrozole sustained-release pellets with a 40-day release period was used.The control placebo and letrozole pellets were implanted subcutaneously in the dorsal cervical region of 3-4-week-old C57BL/6J mice(8 mice per group)to establish the control group and letrozole-induced PCOS model group.Both groups were treated with a high-fat diet starting the day after administration.The modeling period lasted for 5 weeks,during which body weight and 24-hour food intake were monitored in each group every week.When samples were collected,liver weight was recorded.Pathological changes in ovarian and hepatic tissues were examined by hematoxylin-eosin(HE)staining,while hepatic lipid deposition was observed by Oil Red O staining.The extent of macrophage infiltration in the liver was evaluated via F4/80 immunohistochemical staining,and hepatic fibrosis levels were observed by Masson's trichrome staining.Transcriptomic sequencing was performed to analyze differentially expressed genes(DEGs)in liver tissues between the control and model groups,followed by enrichment analysis of significant DEGs.Quantitative real-time fluorescent quantitative PCR(qPCR)was subsequently used to validate the expression of significant DEGs in liver tissues of both groups.Results Compared with the control group,the model group which received subcutaneous letrozole sustained-release pellets combined with a high-fat diet exhibited significantly increased body weight(P＜0.001),prominent polycystic ovarian morphology,and significantly decreased liver-to-body weight ratio(P＜0.05).However,no significant changes were observed in absolute liver weight(P＞0.05),hepatic histomorphology,or lipid deposition.Transcriptome sequencing identified 119 upregulated and 217 downregulated DEGs in the liver tissues of letrozole-treated mice,which were predominantly enriched in pathways related to cholesterol and steroid biosynthesis,steroid hormone metabolism,and inflammatory responses.qPCR validation demonstrated that mRNA expression of HSD3B2 and HMGCR was significantly upregulated in liver(P＜0.01),while mRNA expression of IL4,CCL2 and COL1A1 was downregulated(P＜0.05)in the model group compared with the control group.However,Masson's trichrome staining and F4/80 immunohistochemical analysis showed no significant changes in hepatic fibrosis or macrophage infiltration.Conclusion Subcutaneous administration of letrozole sustained-release pellets combined with a high-fat diet successfully establishes a mouse model of PCOS.The model mice exhibited significant changes in hepatic gene expression.Liver may contribute to PCOS pathogenesis through regulating cholesterol and steroid metabolism.

AIM To investigate effects of petroleum ether fraction from Derris eriocarpa How on glucose and lipid metabolism in a mouse model of metabolic syndrome(MS).METHODS KM mice were fed a high-fat diet and administered streptozotocin intraperitoneally to establish MS models.The MS mice were then randomly assigned to the model group,the metformin hydrochloride group,the lovastatin group,the ursolic acid group,and the high-,medium-and low-dose D.eriocarpa petroleum ether fraction groups,with 10 mice in each group.Ten additional mice maitained on a normal diet served as the normal control group.After 4 weeks of intragastric administration,glucose and lipid metabolism indicators were measured.Hepatic pathological changes were assessed using HE staining and oil red O staining.Liver tissue mRNA expressions of ATF3,PEPCK,FXR,CYP7A1,HNF4ɑ,CYP8B1 and SRB1 were quantified by RT-qPCR.Hepatic protein expressions of ATF3,HNF4ɑ,PEPCK,FXR and CYP7A1 was analyzed by Western blot in MS mice.RESULTS Compared to the model group,the high-dose D.eriocarpa petroleum ether fraction group exhibited significant glucose tolerance improvement(reduced OGTT-AUC,P＜0.01);favorable serum lipid modulation in terms of increased HDL-C levels(P＜0.01)and decreased TG,TC,LDL-C(P＜0.01);reduced renal biomarkers(BUN,SCR)and hepatotoxic indicators of TBA,AST and ALT activities(P＜0.01);alleviated hepatic lipid accumulation and histopathological damage;downregulated mRNA and protein expressions of ATF3,HNF4ɑ and PEPCK,as well as CYP8B1 mRNA expression(P＜0.01);and upregulated mRNA and protein expressions of FXR and CYP7A1,along with SRB1 mRNA expression(P＜0.01).CONCLUSION D.eriocarpa petroleum ether fraction ameliorates glucose and lipid metabolism dysregulation in MS mice by modulating the ATF3/HNF4ɑ/CYP7A1 signaling pathway,consequently eliciting hypoglycemic,hypolipidemic,hepatoprotective and nephroprotective effects.