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.

Objective: To investigate the impact of milk and egg supplementation on body composition and bone mineral density of rural primary school students in Yunnan Province, so as to provide a reference for developing targeted nutritional intervention strategies. Methods: In December 2023, a cluster sampling method was adopted to select students from grades one to three in four primary schools each from Jinggu and Shidian countys of Yunnan Province, as the intervention group (662 students). Additionally, two boarding primary schools were selected from each county based on the principle of matching scale and student numbers as the control group (455 students). Starting from April 2023, the intervention group received 200 mL milk and 50 g eggs during the break on school days for 8 months, while the control group maintained their usual diet behavior. Body composition was measured by using bioelectrical impedance analysis, and distal radial bone mineral density was assessed via dual energy X-ray absorptiometry in April and December 2023. The intervention effects were analyzed by using a difference in-differences approach. Results: The final measurements of body fat percentage, skeletal muscle mass and fat free mass of the intervention group and the control group of primary school students were significantly higher than the baseline values, and the net effect of milk and egg intervention on these body composition indicators was not statistically significant ( P >0.05, both before and after adjustment). In contrast, bone mineral density increased significantly by 0.02 g/cm 2 in the intervention group. The net intervention effect on bone mineral density was statistically significant ( β=0.02, 95%CI =0.00-0.04), and remained significant after model adjustment ( β=0.02, 95%CI =0.00-0.04) (both P < 0.05). Subgroup analysis showed statistically significant effects of the intervention among girls ( β=0.02, 95%CI =0.00-0.04), day students ( β=0.04, 95%CI =0.01-0.07), and students with normal nutritional status ( β=0.02, 95%CI =0.00-0.04) (all P <0.05). No significant effect of milk and egg supplementation was observed on body composition indicators (all P <0.05). Conclusions Milk and egg supplementation can improve bone mineral density among rural primary school students in Yunnan Province. It is recommended that rural school aged children should increase intake of milk and eggs to support growth and development.

BACKGROUND: T cell dysfunction, which includes exhaustion, anergy, and senescence, is a distinct T cell differentiation state that occurs after antigen exposure. Although T cell dysfunction has been a cornerstone of cancer immunotherapy, its potential in transplant research, while not yet as extensively explored, is attracting growing interest. Interferon regulatory factor 4 (IRF4) has been shown to play a pivotal role in inducing T cell dysfunction. METHODS: A novel ultra-low-dose combination of Trametinib and Rapamycin, targeting IRF4 inhibition, was employed to investigate T cell proliferation, apoptosis, cytokine secretion, expression of T-cell dysfunction-associated molecules, effects of mitogen-activated protein kinase (MAPK) and mammalian target of rapamycin (mTOR) signaling pathways, and allograft survival in both in vitro and BALB/c to C57BL/6 mouse cardiac transplantation models. RESULTS: In vitro , blockade of IRF4 in T cells effectively inhibited T cell proliferation, increased apoptosis, and significantly upregulated the expression of programmed cell death protein 1 (PD-1), Helios, CD160, and cytotoxic T lymphocyte-associated antigen (CTLA-4), markers of T cell dysfunction. Furthermore, it suppressed the secretion of pro-inflammatory cytokines interferon (IFN)-γ and interleukin (IL)-17. Combining ultra-low-dose Trametinib (0.1 mg·kg -1 ·day -1 ) and Rapamycin (0.1 mg·kg -1 ·day -1 ) demonstrably extended graft survival, with 4 out of 5 mice exceeding 100 days post-transplantation. Moreover, analysis of grafts at day 7 confirmed sustained IFN regulatory factor 4 (IRF4) inhibition, enhanced PD-1 expression, and suppressed IFN-γ secretion, reinforcing the in vivo efficacy of this IRF4-targeting approach. The combination of Trametinib and Rapamycin synergistically inhibited the MAPK and mTOR signaling network, leading to a more pronounced suppression of IRF4 expression. CONCLUSIONS Targeting IRF4, a key regulator of T cell dysfunction, presents a promising avenue for inducing transplant immune tolerance. In this study, we demonstrate that a novel ultra-low-dose combination of Trametinib and Rapamycin synergistically suppresses the MAPK and mTOR signaling network, leading to profound IRF4 inhibition, promoting allograft acceptance, and offering a potential new therapeutic strategy for improved transplant outcomes. However, further research is necessary to elucidate the underlying pharmacological mechanisms and facilitate translation to clinical practice.
Animals ; Mice ; Mice, Inbred BALB C ; Mice, Inbred C57BL ; Interferon Regulatory Factors/metabolism* ; Heart Transplantation/methods* ; T-Lymphocytes/immunology* ; Sirolimus/therapeutic use* ; Pyridones/therapeutic use* ; Graft Survival/drug effects* ; Pyrimidinones/therapeutic use* ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Male ; Signal Transduction/drug effects*

BACKGROUND: Pulmonary arterial hypertension (PAH) presents a significant health burden in Asia and remains a critical challenge. This study aims to delineate the PAH burden in Asia from 1990 to 2021. METHODS: Using the latest data from the Global Burden of Disease 2021, we evaluated and analyzed the distributions and patterns of PAH disease burden among various age groups, sexes, regions, and countries in Asia. Additionally, we examined the associations between PAH disease burden and key health system indicators, including the socio-demographic index (SDI) and the universal health coverage (UHC) index. RESULTS: In 2021, there were 25,989 new PAH cases, 103,382 existing cases, 13,909 PAH-associated deaths, and 385,755 DALYs attributed to PAH in Asia, which accounted for approximately 60% of global PAH cases. The age-standardized rates (ASRs) for prevalence and deaths were 2.05 (95% uncertainty interval [UI]: 1.66-2.52) per 100,000 population and 0.31 (95% UI: 0.23-0.38) per 100,000 population, respectively. From 1990 to 2021, Asia reported the lowest ASRs for PAH prevalence but the highest ASRs for deaths compared to other continents. While the ASRs for prevalence increased slightly, ASRs for mortality and DALYs decreased over time. This increasing burden of PAH was primarily driven by population growth and aging. The burden was especially pronounced among individuals aged ≥60 years and <9 years, who collectively accounted for the majority of deaths and DALYs. Moreover, higher SDI and UHC levels were linked to reduced incidence, but higher prevalence rates. CONCLUSIONS Although progress has been made in reducing PAH-related mortality and DALYs, the disease continues to impose a substantial burden in Asia, particularly among older adults and young children. Region-specific health policies should focus on improving early diagnosis, expanding access to treatment, and effectively addressing the growing PAH burden in the region.
Humans ; Global Burden of Disease ; Male ; Female ; Middle Aged ; Adult ; Asia/epidemiology* ; Prevalence ; Aged ; Pulmonary Arterial Hypertension/mortality* ; Adolescent ; Young Adult ; Child ; Child, Preschool ; Infant ; Hypertension, Pulmonary/epidemiology*

BACKGROUND: While emotional distress, encompassing anxiety and depression, has been associated with negative clinical outcomes, its impact across various clinical departments and general hospitals has been less explored. Previous studies with limited sample sizes have examined the effectiveness of specific treatments (e.g., antidepressants) rather than a systemic management strategy for outcome improvement in non-psychiatric inpatients. To enhance the understanding of the importance of addressing mental health care needs among non-psychiatric patients in general hospitals, this study retrospectively investigated the impacts of emotional distress and the effects of early detection and management of depression and anxiety on hospital length of stay (LOS) and rate of long LOS (LLOS, i.e., LOS >30 days) in a large sample of non-psychiatric inpatients. METHODS: This retrospective cohort study included 487,871 inpatients from 20 non-psychiatric departments of a general hospital. They were divided, according to whether they underwent a novel strategy to manage emotional distress which deployed the Huaxi Emotional Distress Index (HEI) for brief screening with grading psychological services (BS-GPS), into BS-GPS ( n = 178,883) and non-BS-GPS ( n = 308,988) cohorts. The LOS and rate of LLOS between the BS-GPS and non-BS-GPS cohorts and between subcohorts with and without clinically significant anxiety and/or depression (CSAD, i.e., HEI score ≥11 on admission to the hospital) in the BS-GPS cohort were compared using univariable analyses, multilevel analyses, and/or propensity score-matched analyses, respectively. RESULTS: The detection rate of CSAD in the BS-GPS cohort varied from 2.64% (95% confidence interval [CI]: 2.49%-2.81%) to 20.50% (95% CI: 19.43%-21.62%) across the 20 departments, with a average rate of 5.36%. Significant differences were observed in both the LOS and LLOS rates between the subcohorts with CSAD (12.7 days, 535/9590) and without CSAD (9.5 days, 3800/169,293) and between the BS-GPS (9.6 days, 4335/178,883) and non-BS-GPS (10.8 days, 11,483/308,988) cohorts. These differences remained significant after controlling for confounders using propensity score-matched comparisons. A multilevel analysis indicated that BS-GPS was negatively associated with both LOS and LLOS after controlling for sociodemographics and the departments of patient discharge and remained negatively associated with LLOS after controlling additionally for the year of patient discharge. CONCLUSION Emotional distress significantly prolonged the LOS and increased the LLOS of non-psychiatric inpatients across most departments and general hospitals. These impacts were moderated by the implementation of BS-GPS. Thus, BS-GPS has the potential as an effective, resource-saving strategy for enhancing mental health care and optimizing medical resources in general hospitals.
Humans ; Retrospective Studies ; Male ; Length of Stay/statistics & numerical data* ; Female ; Middle Aged ; Adult ; Psychological Distress ; Inpatients/psychology* ; Aged ; Anxiety/diagnosis* ; Depression/diagnosis*

The study aimed to construct the second and third generation chimeric antigen receptor T cells (CAR-T) targeting the c-mesenchymal-epithelial transition factor (c-Met) protein, and observe their killing effect on human serous ovarian cancer cell SKOV-3. The expression of MET gene in ovarian serous cystadenocarcinoma, the correlation between MET gene expression and the abundance of immune cell infiltration, and the effect of MET gene expression on the tissue function of ovarian serous cystadenocarcinoma were analyzed by bioinformatics. The expression of c-Met in ovarian cancer tissues and adjacent tissues was detected by immunohistochemical staining. The second and third generation c-Met CAR-T cells, namely c-Met CAR-T(2G/3G), were prepared by lentivirus infection, and the cell subsets and infection efficiency were detected by flow cytometry. Using CD19 CAR-T and activated T cells as control groups and A2780 cells with c-Met negative expression as Non target groups, the kill efficiency on SKOV-3 cells with c-Met positive expression, cytokine release and cell proliferation of c-Met CAR-T(2G/3G) were explored by lactate dehydrogenase (LDH) release, ELISA and CCK-8 respectively. The results showed that MET gene expression was significantly up-regulated in ovarian cancer tissues compared with normal tissues, which was consistent with the immunohistochemistry results. However, in all pathological stages, there was no obvious difference in MET expression and no correlation between MET gene expression and the race and age of ovarian cancer patients. The second generation and third generation c-Met CAR-T cells were successfully constructed. After lentivirus infection, the proportion of CD8⁺ T cells in c-Met CAR-T(2G) was upregulated, while there was no significant change in the cell subsets of c-Met CAR-T(3G). The LDH release experiment showed that the kill efficiency of c-Met CAR-T(2G/3G) on SKOV-3 increased with the increase of effect-target ratio. When the effect-target ratio was 20:1, the kill efficiency of c-Met CAR-T(2G) reached (42.02 ± 5.17)% (P < 0.05), and the kill efficiency of c-Met CAR-T(3G) reached (51.40 ± 2.71)% (P < 0.05). ELISA results showed that c-Met CAR-T released more cytokine compared to CD19 CAR-T and activated T cells (P < 0.05). Moreover, the cytokine release of c-Met CAR-T(3G) was higher than c-Met CAR-T(2G) (P < 0.01). The CCK-8 results showed that after 48 h, the cell number of c-Met CAR-T(2G) was higher than that of c-Met CAR-T(3G) (P < 0.01). In conclusion, both the second and third generation c-Met CAR-T can target and kill c-Met-positive SKOV-3 cells, with no significant difference. c-Met CAR-T(2G) has stronger proliferative ability, and c-Met CAR-T(3G) releases more cytokines.
Humans ; Female ; Ovarian Neoplasms/immunology* ; Proto-Oncogene Proteins c-met/metabolism* ; Receptors, Chimeric Antigen/immunology* ; Cell Line, Tumor ; Cystadenocarcinoma, Serous/immunology* ; T-Lymphocytes/immunology*

This study identified 8 members including NjBIN2 of the GSK3 family in Nardostachys jatamansi by bioinformatics analysis. Moreover, the phylogenetic tree revealed that the GKS3 family members of N. jatamansi had a close relationship with those of Arabidopsis. RT-qPCR results showed that NjBIN2 presented a tissue-specific expression pattern with the highest expression in roots, suggesting that NjBIN2 played a role in root growth and development. In addition, the application of epibrassinolide or the brassinosteroid(BR) synthesis inhibitor(brassinazole) altered the expression pattern of NjBIN2 and influenced the photomorphogenesis(cotyledon opening) and root development of N. jatamansi, which provided direct evidence about the functions of NjBIN2. In conclusion, this study highlights the roles of BIN2 in regulating the growth and development of N. jatamansi by analyzing the expression pattern and biological function of NjBIN2. It not only enriches the understanding about the regulatory mechanism of the growth and development of N. jatamansi but also provides a theoretical basis and potential gene targets for molecular breeding of N. jatamansi with improved quality in the future.
Brassinosteroids/metabolism* ; Steroids, Heterocyclic/metabolism* ; Gene Expression Regulation, Plant/drug effects* ; Plant Proteins/metabolism* ; Phylogeny ; Nardostachys/metabolism* ; Plant Growth Regulators/pharmacology* ; Plant Roots/drug effects*