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.

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 explore the mechanism of Shen Hong capsule in preventing and treating acute mountain sickness based on biological information platform and in vitro experiment. Methods Traditional Chinese Medicine Systems Pharmacology （TCMSP） and Traditional Chinese Medicine Information Database （TCMID） were used to obtain the active components and predicted targets of Shen Hong capsule. Therapeutic Target Database （TTD）, Disease Gene Network （DisGeNET） database and GeneCards database were used to search for the targets of acute mountain sickness related diseases, and the potential therapeutic targets were obtained. The protein-protein interaction （PPI） was analyzed by Search Tool for the Retrieval of Interacting Genes/Proteins （STRING）, the Database for Annotation, Visualization, and Integrated Discovery （DAVID） online platform was used to analyse the Gene Ontology （GO） and the Kyoto Encyclopedia of Genes and Genomes （KEGG） signal pathway enrichment. The network information was visualized by Cytoscape software, the key targets in PPI network were obtained according to the topology data, and the binding ability of main active components and key therapeutic targets were analyzed by molecular docking. The validation of the main active components was performed by liquid chromatography-mass spectrometry （LC-MS）. The hypoxia model was created by H9c2 cells, apoptosis was visualized by Hoechst33342 staining, and key target proteins were verified by Western blot. Results 91 active components, 3 main active components and 150 predicted targets were selected from Shen Hong capsule. 515 targets of altitude sickness-related diseases and 37 targets of Shen Hong capsule regulating altitude sickness-related diseases were screened out. 44 related signal pathways, such as HIF-1 signal pathway, PPAR signal pathway, drug metabolism - cytochrome P450, were enriched and analyzed. TNF, IL1B, VEGFA, NOS3, EGFR, ESR1, PPARG, NR3C1, HMOX1 and IFNG were 10 key targets. The molecular docking results showed that the docking conformations between the main active components and the key targets were stable. The three main active components of quercetin, luteolin and kaempferol were identified by LC-MS, and in vitro experiments proved that Shen Hong capsule could relieve acute hypoxia injury by regulating the expression of HIF-1α, PPARG, NOS3, and TNF. Conclusion Shen Hong capsule could regulate the body’s hypoxia response and metabolism through multi-component, multi-target and multi-channel ways, so as to prevent and treat acute mountain sickness. This study provided a direction for further exploring the mechanism of Shen Hong capsule, and also provided a theoretical basis for further development and clinical application.

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.

Medical device related infections caused by bacteria are common complications in clinical practice,and preventing bacterial colonization on the surface of medical materials is one of the important challenges in the medical field.Therefore,there is an urgent need to construct medical coatings that combine antibacterial properties and biocompatibility.In this study,a γ-polyglutamic acid(γ-PGA)complex with long-chain alkyl quaternary ammonium salts formed by electrostatic and hydrophobic interactions was prepared,which was insoluble in water but soluble in organic solvents(e.g.,ethanol),and was capable of constructing antimicrobial coatings on the surfaces of medical materials in a simple and efficient manner.The bactericidal effect of the coating was verified using viable bacteria counting experiments,and the results showed that the bactericidal rate of the coated thermoplastic polyurethane(TPU)membrane against Staphylococcus aureus was greater than 99.9%compared with that of the uncoated TPU membrane.In addition,a cytotoxicity assay was performed using the L929 fibroblast and cell proliferation detection kit(CCK-8),which showed that the survival rate of L929 fibroblasts on coated TPU was greater than 90%.Meanwhile,the hemolysis rate of coated erythrocytes was tested using fresh rabbit red blood cells(RBCs),and the hemolysis rate on the coated TPU surface was 1.5%.The above results indicated that the coating had good biocompatibility.The preparation method of medical antibacterial coating reported in this study provided a new idea for preventing bacterial infections related to implantable/interventional medical devices.

Tracheal intubation is the most commonly used way to establish artificial airway in intensive care unit patients, and it is the premise of respiratory support and treatment, the success of extubation is an important basis to measure the prognosis of patients. Influenced by many factors, extubation of patients may fail, resulting in prolonged hospitalization, increased medical expenses and increased incidence of complications. This article reviews the literature at home and abroad, and summarizes the main mechanism, risk factors and prevention strategies of extubation failure in intensive care unit patients, aiming at improving the recognition ability of clinical medical staff for extubation failure and providing reference for clinical management and follow-up research.

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.

Dental implantology has developed rapidly for over half a century,since pure titanium(99.7％)dental cylindrical threaded implants were exploited and osseointegration was introduced in 1960s by Prof.Br?nemark.The long term retention rates of 10 years or more are over 95％.However,the biological complications jeopardize the long term effects of dental implant treatment seriously.The prevalence of dental implant biological complications varies greatly among different reports resulting from the disparities on the defini-tions of dental implant biological complications.After analyzing and summarizing the major opinions proposed internationally in recent years,the consensus for the definition of dental implant biological complications has been reached.Generally the dental implant biologi-cal implications can be classified into early stage(before restoration)biological complications and late stage(after restoration)biological complications.The early stage biological complications include acute and chronic infections,pain,soft tissue deficiency,and osseointegration failure,etc.The late stage complications include peri-implant diseases(peri-implant mucositis and peri-implantitis),soft tissue deficiency around implant,implant loosening and dropping off,etc.The various risk factors related to different dental implant biological complications,the strategies of the prevention and treatment for the dental implant biological complications have been discussed comprehensively,and the consensus has been reached.It is aimed to advocate the dentist to pay more attention to the early prevention of the biological implant complications,to promote more researches on the implant biological complications,and to help elevate the level of dental implantology in our country.

In continuation of research aimed at identifying anti-inflammatory agents from natural sesquiterpenoids, an activity-guided fractionation approach utilizing lipopolysaccharide (LPS)-mediated RAW264.7 cells was employed to investigate chemical constituents from Inula Britannica (I. britannica). Seven novel sesquiterpenoid dimers inulabritanoids A-G (1-7) and two novel sesquiterpenoid monomers inulabritanoids H (8) and I (9) were isolated from I. britannica together with eighteen known compounds (10-27). The structural elucidation was accomplished through comprehensive analysis of 1D and 2D nuclear magnetic resonance (NMR), high-resolution mass spectrometry (HR-MS), and electronic circular dichroism (ECD) spectra, complemented by quantum chemical calculations. Compounds 1, 2, 12, 16, 19, and 26 demonstrated inhibitory effects on NO production, with IC₅₀ values of 3.65, 5.48, 3.29, 6.91, 3.12, and 5.67 μmol·L^-1, respectively. Mechanistic studies revealed that compound 1 inhibited IκB kinase β (IKKβ) phosphorylation, thereby blocking nuclear factor κB (NF-κB) nuclear translocation, and activated the kelch-like ECH-associated protein 1 (Keap1)/nuclear factor erythroid 2-related factor 2 (Nrf2) signal pathway, leading to decreased expression of NADPH oxidase 2 (NOX-2), inducible nitric oxide synthase (iNOS), tumor necrosis factor α (TNF-α), interleukin-6 (IL-6), monocyte chemotactic protein-1 (MCP-1), IL-1β, and IL-1α and increased expression of NAD(P)H: quinone oxidoreductase 1 (NQO-1) and heme oxygenase-1 (HO-1), thus exhibiting anti-inflammatory effects in vitro. These results indicate that dimeric sesquiterpenoids may serve as promising candidates for anti-inflammatory drug development.
Mice ; Animals ; Sesquiterpenes/isolation & purification* ; Anti-Inflammatory Agents/isolation & purification* ; Inula/chemistry* ; RAW 264.7 Cells ; Nitric Oxide ; Molecular Structure ; NF-kappa B/immunology* ; NF-E2-Related Factor 2/immunology* ; Macrophages/immunology* ; Nitric Oxide Synthase Type II/immunology* ; Plant Extracts/pharmacology* ; Lipopolysaccharides ; Tumor Necrosis Factor-alpha/immunology* ; I-kappa B Kinase/genetics*