[This corrects the article DOI: 10.1016/j.jpha.2023.08.006.].

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

Workplace psychosocial hazards may be related to job content or work schedule, specific characteristics of the workplace or opportunities for career development. They can lead to significant losses and harm to workplace relationships, labor participation, productivity and quality within the workplace. This article introduces the definition, types and occupational hazards of workplace psychosocial hazards, as well as the theoretical source, main features and update of the version of the assessment tool Copenhagen Psychosocial Questionnaire, and provides suggestions for the assessment, monitoring, and future scientific research on workplace psychosocial hazards in China.

Objective:Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease.However,we still don't fully understand how certain immune-related genes contribute to the disease's development and progression.This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis(WGCNA)and machine learning. Methods:This study downloaded the gene chip data from the Gene Expression Omnibus(GEO)database,and used WGCNA to screen out important gene modules related to Parkinson's disease.Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease.Gene ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)were used to analyze the the functions of immune-related genes and signaling pathways involved.Immune cell infiltration analysis was performed using the CIBERSORT package of R language.Using bioinformatics method and 3 machine learning methods[least absolute shrinkage and selection operator(LASSO)regression,random forest(RF),and support vector machine(SVM)],the immune-related genes of Parkinson's disease were further screened.A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes(hub)gene.The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. Results:A total of 218 immune genes related to Parkinson's disease were identified,including 45 upregulated genes and 50 downregulated genes.Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways.The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells,NK cells,CD8+ T cells,and B cells were higher in the samples of Parkinson's disease patients,while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients.ANK1 was screened out as the hub gene.The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction,iron homeostasis regulation,and immune system activation. Conclusion:This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods,suggesting its potential as a candidate therapeutic target for Parkinson's disease.

Objective To investigate the protective effect of total saponins of Panax japonicus(TSPJ)against CCl4-induced acute liver injury(ALI)in rats and explore the underlying pharmacological mechanisms.Methods Male SD rat models of CCl4-induced ALI were given intraperitoneal injections of distilled water,100 mg/kg biphenyl bisabololol,or 50,100,and 200 mg/kg TSPJ during modeling(n=8).Liver functions(AST,ALT,TBil and ALP)of the rats were assessed and liver pathologies were observed with HE staining.Immunohistochemistry was used to detect the expressions of PI3K/Akt/NF-κB signaling pathway molecules in liver tissue;ELISA was used to determine the levels of T-SOD,GSH-Px,and MDA.Western blotting was performed to detect the expression levels of PI3K-Akt and SIRT6-NF-κB pathways in the liver tissue.Results Network pharmacological analysis indicated that the key pathways including PI3K/Akt mediated the therapeutic effect of TSPJ on ALI.In the rat models of ALI,treatments with biphenyl bisabololol and TSPJ significantly ameliorated CCl4-induced increase of serum levels AST,ALT,ALP,TBil and MDA and decrease of T-SOD and GSH-Px levels(all P<0.01).The rat models of ALI showed significantly increased expression of p-NF-κB(P<0.01),decreased expressions of PI3K,p-Akt and SIRT6 proteins,and elevated expression levels of p-NF-κB,TNF-α and IL-6 proteins in the liver,which were all significantly improved in the treatment groups(P<0.05 or 0.01).Conclusion TSPJ can effectively alleviate CCl4-induced ALI in rats by suppressing inflammatory responses and oxidative stress in the liver viaregulating the PI3K/Akt and SIRT6/NF-κB pathways.

Objective To investigate immunogenic and toxic effects of graphene oxide (GO) nanoparticles in mouse skeletal muscles and in human blood in vitro. Methods GO nanoparticles prepared using a probe sonicator were supended in deionized H2O or PBS, and particle size and surface charge of the nanoparticles were measured with dynamic light scattering (DLS). Different concentrations (0.5, 1.0 and 2.0 mg/mL) of GO suspension or PBS were injected at multiple sites in the gastrocnemius muscle (GN) of C57BL/6 mice, and inflammatory response and immune cell infiltrations were detected with HE and immunofluorescence staining. We also examined the effects of GO nanoparticles on human red blood cell (RBC) morphology, hemolysis and blood coagulation using scanning electron microscope (SEM), spectrophotometry, and thromboelastography (TEG). Results GO nanoparticles suspended in PBS exhibited better colloidal dispersity, stability and surface charge effects than those in deionized H2O. In mouse GNs, injection of GO suspensions dose- and time-dependently resulted in sustained muscular inflammation and myofiber degeneration at the injection sites, which lasted till 8 weeks after the injection; immunofluorescence staining revealed obvious infiltration of monocytes, macrophages, dendritic cells and CD4+T cells around the injection sites in mouse GNs. In human RBCs, incubation with GO suspensions at 0.2, 2.0 and 20 mg/mL, but not at 0.002 or 0.02 mg/mL, caused significant alterations of cell morphology and hemolysis. TEG analysis showed significant abnormalities of blood coagulation parameters following treatment with high concentrations of GO. Conclusion GO nanoparticles can induce sustained inflammatory and immunological responses in mouse GNs and cause RBC hemolysis and blood coagulation impairment, suggesting its muscular toxicity and hematotoxicity at high concentrations.

Workplace psychosocial hazards may be related to job content or work schedule, specific characteristics of the workplace or opportunities for career development. They can lead to significant losses and harm to workplace relationships, labor participation, productivity and quality within the workplace. This article introduces the definition, types and occupational hazards of workplace psychosocial hazards, as well as the theoretical source, main features and update of the version of the assessment tool Copenhagen Psychosocial Questionnaire, and provides suggestions for the assessment, monitoring, and future scientific research on workplace psychosocial hazards in China.

Objective To investigate the protective effect of total saponins of Panax japonicus(TSPJ)against CCl4-induced acute liver injury(ALI)in rats and explore the underlying pharmacological mechanisms.Methods Male SD rat models of CCl4-induced ALI were given intraperitoneal injections of distilled water,100 mg/kg biphenyl bisabololol,or 50,100,and 200 mg/kg TSPJ during modeling(n=8).Liver functions(AST,ALT,TBil and ALP)of the rats were assessed and liver pathologies were observed with HE staining.Immunohistochemistry was used to detect the expressions of PI3K/Akt/NF-κB signaling pathway molecules in liver tissue;ELISA was used to determine the levels of T-SOD,GSH-Px,and MDA.Western blotting was performed to detect the expression levels of PI3K-Akt and SIRT6-NF-κB pathways in the liver tissue.Results Network pharmacological analysis indicated that the key pathways including PI3K/Akt mediated the therapeutic effect of TSPJ on ALI.In the rat models of ALI,treatments with biphenyl bisabololol and TSPJ significantly ameliorated CCl4-induced increase of serum levels AST,ALT,ALP,TBil and MDA and decrease of T-SOD and GSH-Px levels(all P<0.01).The rat models of ALI showed significantly increased expression of p-NF-κB(P<0.01),decreased expressions of PI3K,p-Akt and SIRT6 proteins,and elevated expression levels of p-NF-κB,TNF-α and IL-6 proteins in the liver,which were all significantly improved in the treatment groups(P<0.05 or 0.01).Conclusion TSPJ can effectively alleviate CCl4-induced ALI in rats by suppressing inflammatory responses and oxidative stress in the liver viaregulating the PI3K/Akt and SIRT6/NF-κB pathways.