ObjectiveStudies have shown that nuciferine has anti-cerebral ischemia effect， but the specific mechanism of action has not been elaborated. Based on the transcriptome results， the pharmacological mechanism of nuciferine against cerebral ischemia was analyzed from multiple dimensions including tissue， cell， pathological process， biological process and signaling pathway. MethodsThirty SD rats were randomly divided into the sham group， model group and nuciferine group（40 mg·kg^-1） according to weight. Except for the sham group， the model of middle cerebral artery occlusion（MCAO） was established by thread embolization method after 30 min of administration in the other two groups. Twenty-four hours after surgery， transcriptome sequencing was used to detect the gene expression profiles in the cortex penumbra of rat cerebral tissue， and gene ontology（GO） and kyoto encyclopedia of genes and genomes（KEGG） pathway enrichment analysis were performed for differentially expressed genes. The mechanismof nuciferine against cerebral ischemia was analyzed from 5 dimensions of tissue， cell， pathological process， biological process and signaling pathway by the transcriptome-based multi-scale network pharmacology platform（TMNP）. ResultsTranscriptome sequencing and gene quantitative analysis showed that 667 genes were significantly reversed by nuciferine. Further enrichment analysis of KEGG and GO suggested that the pathways of nuciferine involved regulating stress response， ion transport， cell proliferation and differentiation， and synaptic function. TMNP research found that at the tissue level， nuciferine could significantly improve the cerebral tissue injury caused by ischemia. At the cellular and pathological levels， nuciferine could play an anti-cerebral ischemia role by improving the state of various nerve cells， mobilizing immune cells， regulating inflammation. And at the level of biological processes and signaling pathways， nuciferine mainly acted on the processes such as vascular remodeling， inflammation-related signaling pathways， and synaptic signaling. ConclusionCombined with the results of transcriptome sequencing， gene quantitative analysis and TMNP， the mechanism of nuciferine against cerebral ischemia may be related to processes such as intervening in stress response and inflammation， affecting vascular remodeling and regulating synaptic function. These results can provide a basis and reference for further study of the pharmacological mechanism of nuciferine against cerebral ischemia.

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

Objective: To review the current development of artificial intelligence (AI) technology in the field of transfusion medicine. Methods: A systematic search was conducted in the Clarivate Web of Science Database from inception to December 2024 for literature related to AI and transfusion. A total of 4 775 publications were identified. Based on inclusion and exclusion criteria, 133 original studies were ultimately included and analyzed using a narrative synthesis approach. Results: Research on AI in transfusion has surged since 2020 (accounting for 77% of all publications), with China ranking second globally in publication volume. Among the included studies, 69.2% focused on predicting individual transfusion needs, followed by inventory management (8.3%), diagnosis and prediction of adverse transfusion reactions (6.0%), factors influencing transfusion outcomes (5.3%), blood group identification (5.3%), blood quality testing (4.5%), and precise blood volume measurement (1.5%). Additionally, 4.5% of the studies were published in journals with an impact factor greater than 10; 19.5% developed software or applications; 31.5% were multi-center studies; 48.1% utilized decision tree methods, while 31.5% employed neural network approaches; and 14.2% conducted external validation of the algorithms. Conclusion: AI demonstrates significant potential in transfusion risk prediction, decision support, and blood management. However, challenges remain, including limited model generalizability, insufficient algorithm interpretability, and barriers to clinical translation. The deep integration of AI with transfusion medicine will accelerate the advent of precision transfusion era, maximizing blood resource utilization, reducing waste, and ensuring transfusion safety.

Objective:To explore the independent association between handgrip strength and chronic kidney disease (CKD) in adult residents in Anhui Province using data from the China Adult Chronic Disease and Risk Factor Surveillance (2023).Methods:A multi-stage stratified cluster random sampling method was used to select residents aged ≥18 years for surveys, physical measurements, and laboratory tests. Relevant covariates were adjusted, and a multivariable logistic regression model was established to infer the association between handgrip strength and CKD, followed by subgroup analysis.Results:A total of 7 295 participants were included in the study, with age of (61.5±13.2) years, and 55.6% of the study participants were women. The results of the multivariate logistic regression analysis showed that with each 1.0 kg increase in handgrip strength, the risk for CKD decreased by 1.3% ( OR=0.987, 95% CI: 0.978-0.997). Compared with those with low handgrip strength, the people with moderate hasdgrip strength ( OR=0.818, 95% CI: 0.694-0.964) and high handgrip strength ( OR=0.729, 95% CI: 0.598-0.989) had lower risk for CKD. In the subgroup analysis, the association between handgrip strength and risk for CKD remained unchanged regardless age, sex, smoking status, and alcohol consumption statuys, and the prevalence of hypertension and hyperlipidemia (interaction P>0.05), except BMI and diabetes. Conclusion:The decline in handgrip strength is associated with an increased risk for CKD in adult residents in Anhui.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To develop and validate a prediction model for medication adherence among patients receiving allergen sublingual immunotherapy (SLIT).Methods:A prospective cross-sectional study was conducted, and a total of 288 patients who received SLIT treatment at an allergy center in the First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital) from December 2023 to July 2024 were assigned to the modeling group. Additionally, 122 patients from August to October 2024 were assigned to the validation group. Data of patients′ general information, medication beliefs, anxiety levels, social support, disease perception, and medication adherence were collected. Single-factor analysis and LASSO regression were utilized to identify potential predictors, and a prediction model for medication adherence was constructed using multifactorial logistic regression. A nomogram was then developed based on the model. The model′s discriminatory ability was evaluated using receiver operating characteristic curve (ROC), the area under curve (AUC), sensitivity, and specificity. The model was then validated in the validation cohort.Results:Single-factor analysis and LASSO regression identified a total of nine predictive factors. Logistic regression revealed that medical belief tendency [ OR (95% CI) =2.420 (1.116-5.248), P=0.025], the somatic control dimension in self-rating anxiety scales [ OR (95% CI)=1.404 (1.241-1.589), P<0.001], the subjective support dimension in social support assessment [ OR (95% CI)=0.784 (0.725-0.847), P<0.001], and the cognitive dimension in illness perception [ OR (95% CI)=0.725 (0.647-0.813), P<0.001] were independent predictors of medication adherence in patients undergoing SLIT. The AUC value of the model was 0.899 (95% CI=0.863-0.934) in the modeling group and 0.882 (95% CI=0.820-0.944) in the validation group, indicating good discriminatory ability. The optimal cutoff value of the model was 0.493, with a sensitivity of 81.1% and specificity of 85.7% in the modeling group, and a sensitivity of 87.3% and specificity of 82.5% in the validation group. Conclusion:The medication adherence prediction model developed in this study for patients undergoing SLIT exhibits good predictive performance and provides valuable guidance for early intervention by clinical healthcare professionals.

Objective:To explore the spatial correlation between gray matter volume (GMV) changes and neurotransmitter receptors/transporters in patients with first-episode schizophrenia (FES) .Methods:Fifty-four FES patients(FES group) and fifty-nine healthy controls (HC group) were selected from June 2014 to May 2020 in the Psychiatry Department of Renmin Hospital of Wuhan University. Structural magnetic resonance imaging (sMRI) was conducted on all subjects. Differences of GMV were compared across 400 cortical regions and 32 subcortical regions. Based on the positron emission tomography(PET) data from Neuromaps, which provides the density of 19 different neurotransmitter receptors and transporters, Spearman correlation analysis was performed to evaluate the spatial correlation between GMV changes and neurotransmitter systems.Results:Compared to the HC group, FES group exhibited significant GMV reductions in widespread cortical (90/400) and subcortical (6/32) regions (all FDR-corrected P<0.05). The effect size of GMV reduction (Cohen’s d) showed significant positive correlations with the density of 5-hydroxytryptamine 1a(5HT1a) ( r=0.400, Pspin=0.002), γ-aminobutyric acid type A receptor(GABA A)( r=0.307, Pspin=0.002), and metabotropic glutamate receptor 5(mGluR5) ( r=0.275, Pspin=0.020) receptors (all FDR-corrected P<0.05). Conclusion:GMV reductions in a wide range of brain regions existed in patients with FES. There are significant correlations between 5HT1a, GABA A and mGluR5 receptors and gray matter reduction in patients with FES. The disorder of these neurotransmitter receptors may be the potential neurobiological mechanism of gray matter structural abnormalities in the early stage of schizophrenia.

Objective To explore the mechanism of action of mitochondrial DNA(mtDNA)of alveolar epithelial type Ⅱ cells(AECⅡ)in silicotic fibrosis.Methods This study was divided into the animal experiment and cell experiment.Animal experiment:twenty-eight C57BL/6 mice were randomly divided into the saline group(n=14)and the silicosis model group(n=14),which were given 50 μL of sterile saline and 50 μL of 50 mg/mL of SiO2 suspension by tracheal perfusion respectively.HE staining and Masson staining were performed to observe the histopathological changes of mouse lung tissues after sampling with the exposure of 28 days and 56 days,and Western blot was used to detect the expression levels of functional proteins of pulmonary surfactant protein-D(SP-D),and Krebs von den Lungen-6(KL-6),and fibrotic protein of transforming growth factor-β1(TGF-β1)in mouse lung tissues.Cell experiment:AECⅡ cell line of A549 was exposed to different concentrations of SiO2 suspension.CCK-8 was used to detect cell viability,DAPI staining was used to observe cell apoptosis,Western blot was used to detect related protein expression,JC-1 was used to detect the changes of mitochondrial membrane potential,and RT-qPCR was used to detect mtDNA levels in whole cells,mitochondria,cytoplasm and supernatant.The expression levels of related proteins in AECⅡ were detected by Western blot after cleared mtDNA by DnaseⅠ.Results Histopathological examination of lung tissues showed that SiO2 exposure led to damage in mice lung tissues,with infiltration of inflammatory cell,silica nodules,and a significant increase of collagen fibers.After SiO2 exposure,the protein expressions of SP-D,KL-6 and TGF-β1 in lung tissues were up-regulated(P<0.05).DAPI staining and CCK-8 results showed a reduced activity and impaired apoptosis of AECⅡ after treated with 400 and 800 μg/mL SiO2.JC-1 assay results demonstrated that exposure to 800 μg/mL SiO2 caused a decrease of mitochondrial membrane potential in AECⅡ(P<0.05).RT-qPCR results showed that 800 μg/mL SiO2 exposure led to increased mtDNA levels in the cytoplasm and supernatant of AECⅡ(P<0.05).Western blot results showed that 800 μg/mL SiO2 exposure caused an increase in the levels of SP-D,KL-6,and TGF-β1 proteins,while which were ameliorated by Dnase Ⅰ treatment.Conclusion SiO2 exposure results in the escape and release of AECⅡ mtDNA and dysfunction of AECⅡ,thereby leading to the development of pulmonary fibrosis.