BACKGROUND: Macrophage polarization anomalies and dysfunction play a crucial role in the pathogenesis of immune thrombocytopenia (ITP). Itaconate is a Krebs cycle-derived immunometabolite synthesized by myeloid cells to modulate cellular metabolism and inflammatory responses. This study aimed to evaluate the immunoregulatory effects of an itaconate derivative on macrophages in patients with ITP. METHODS: Peripheral blood-derived macrophages from patients with ITP and healthy controls were treated with 4-octyl itaconate (4-OI), a derivative of itaconate that can penetrate the cell membrane. Macrophage polarization, antigen-presenting functions, and phagocytic capability were measured via flow cytometry and enzyme-linked immunosorbent assay (ELISA). Macrophage glycolysis in patients with ITP and the metabolic regulatory effect of 4-OI were detected using a Seahorse XFe96 Analyzer. An active murine model of ITP was used to evaluate the therapeutic effects of 4-OI in vivo . RESULTS: 4-OI reduced the levels of CD80 and CD86 in M1 macrophages and suppressed the release of tumor necrosis factor-α (TNF-α) and interleukin (IL)-6 pro-inflammatory cytokines, suggesting that 4-OI could hinder the polarization of macrophages toward an M1 phenotype. We found that 4-OI pretreated M1 macrophages reduced the proliferation of CD4 + T cells and promoted the differentiation of regulatory T cells. In addition, after 4-OI treatment, the phagocytic capacity of M1 macrophages toward antibody-coated platelets decreased significantly in patients with ITP. In addition, the glycolytic function of M1 macrophages was elevated in individuals with ITP compared to those in healthy controls. 4-OI treatment downregulated glycolysis in M1 macrophages. The glycolysis inhibitor 2-deoxy-d-glucose (2-DG) also inhibited the polarization of M1 macrophages and restored their functions. In vivo , 4-OI treatment significantly increased platelet counts in the active ITP murine model. CONCLUSIONS Itaconate derivative 4-OI inhibited M1 macrophage polarization and restored impaired functions through metabolic reprogramming. This study provides a novel therapeutic option for ITP.
Macrophages/metabolism* ; Humans ; Animals ; Succinates/pharmacology* ; Mice ; Male ; Female ; Adult ; Middle Aged ; Flow Cytometry ; Tumor Necrosis Factor-alpha/metabolism* ; Enzyme-Linked Immunosorbent Assay ; Purpura, Thrombocytopenic, Idiopathic/metabolism* ; Glycolysis/drug effects* ; Metabolic Reprogramming

OBJECTIVES: To analyze the multimorbidity patterns and core diseases among hospitalized patients in different age groups and to explore the impacts of multimorbidity patterns on hospitalization costs. METHODS: Electronic medical records of adult inpatients (aged ≥18 years) from Ningbo Medical Center Lihuili Hospital between January 1, 2018, and June 30, 2023 were collected. The multimorbidity status involving 53 specific diseases was analyzed across different age groups. Association rule mining was used to identify common multimorbidity patterns. Complex network analysis was used to identify core diseases within the multimorbidity networks. Generalized estimating equations (GEE) were used to analyze the impact of different multimorbidity patterns on hospitalization costs. RESULTS: The prevalence of multimorbidity among the 359 402 adult inpatients was 38.51%, with higher rates observed in males (43.60%) and elderly patients (58.29%). Association rule mining identified 15 common multimorbidity patterns, which exhibited differences across age groups. The most prevalent multimorbidity pattern overall was "diabetes→hypertension" (support=7.04%, confidence=62.17%, lift=2.17). In the young adult group, the most prevalent pattern was "dyslipidemia→chronic liver disease" (support=1.19%, confidence=53.17%, lift=6.04). In the middle-aged group, it was "diabetes→hypertension" (support=4.84%, confidence=50.28%, lift=2.15). In the elderly group, it was "coronary heart disease, diabetes→hypertension" (support=2.38%, confidence=77.43%, lift=1.63). Complex network analysis revealed that the core diseases within multimorbidity networks differed across age groups. The core disease identified in the young adult group was chronic liver disease (degree centrality=50, betweenness centrality=0.055, closeness centrality=0.963). Core diseases in the middle-aged group included hypertension, chronic liver disease, and diabetes (all with degree centrality=52, betweenness centrality=0.022, closeness centrality=1.000). Core diseases in the elderly group comprised hypertension, diabetes, malignant tumors, chronic liver disease, thyroid disease, anemia, and arrhythmia (all with degree centrality=52, betweenness centrality=0.009, closeness centrality=1.000). Generalized estimating equations analysis indicated that, most multimorbidity patterns were significantly associated with increased hospitalization costs. However, the magnitude of cost increase varied across different multimorbidity patterns. Specifically, hospitalization costs for patients with patterns such as "heart failure→hypertension", "stroke→hypertension", "malignant tumor, diabetes→hypertension", "stroke, diabetes→hypertension", and "diabetes, heart failure→hypertension" were more than double those of patients without any target diseases. CONCLUSIONS Multimorbidity patterns and core diseases among hospitalized patients differ significantly across age groups, and different patterns exert varying impacts on hospitalization costs. These findings underscore the necessity for age-stratified and multimorbidity pattern specific management strategies.
Humans ; Multimorbidity ; Male ; Hospitalization/economics* ; Female ; Aged ; Middle Aged ; Adult ; Age Factors ; Young Adult ; Adolescent ; Diabetes Mellitus/epidemiology* ; Electronic Health Records ; Aged, 80 and over ; Hospital Costs ; China/epidemiology* ; Hypertension/economics* ; Liver Diseases/epidemiology*

Accurate prediction of drug responses in cancer cell lines (CCLs) and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine. Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response (CDR) prediction, challenges remain regarding the generalization of new drugs that are unseen in the training set. Herein, we propose a multimodal fusion deep learning (DL) model called drug-target and single-cell language based CDR (DTLCDR) to predict preclinical and clinical CDRs. The model integrates chemical descriptors, molecular graph representations, predicted protein target profiles of drugs, and cell line expression profiles with general knowledge from single cells. Among these features, a well-trained drug-target interaction (DTI) prediction model is used to generate target profiles of drugs, and a pretrained single-cell language model is integrated to provide general genomic knowledge. Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods. Further ablation studies verified the effectiveness of each component of our model, highlighting the significant contribution of target information to generalizability. Subsequently, the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments, demonstrating its potential for real-world applications. Moreover, DTLCDR was transferred to the clinical datasets, demonstrating satisfactory performance in the clinical data, regardless of whether the drugs were included in the cell line dataset. Overall, our results suggest that the DTLCDR is a promising tool for personalized drug discovery.

Objective:To explore the application of a scenario-based onsite first-aid skills station in objective structured clinical examination (OSCE).Methods:Based on common scenarios and cases in medical practice, an evaluation framework of the OSCE onsite first-aid skills station—containing assessment indicators, exam room setting, examiner training, and assessment process—was designed to evaluate the onsite first-aid competencies of medical graduates of the five-year program for three consecutive years. SPSS 24.0 was used to perform the Kruskal-Wallis test and Pearson correlation analysis to calculate the correlation between course examination scores and OSCE onsite first-aid skills station assessment scores. Excel was used to calculate the difficulty index and discrimination index of test items.Results:The graduates' OSCE onsite first-aid skills station assessment scores were improved year by year, with a mean score of about 80 points. The station assessment items showed a moderate difficulty level (0.7-0.8), a good discrimination level (>0.4), and good internal consistency (Cronbach's α>0.7). The examiners and examinees had a high recognition of the design and effectiveness of this station assessment method. There was a positive correlation between the OSCE scores and corresponding course scores (2016, r=0.245, P=0.001; 2017, r=0.108, P=0.026; 2018, r=0.198, P=0.006). Conclusions:Through scientific scoring and strict examination management, the OSCE scenario-based onsite first-aid skills station can effectively evaluate examinees' injury treatment competencies in different situations, which can provide a reference for course teaching.

Objective:To investigate the influence of curative-intent resection with textbook outcomes of liver surgery (TOLS) on long-term prognosis of gallbladder carcinoma (GBC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 824 patients with GBC in the national multicenter database of Biliary Surgery Group of Elite Group of Chinese Journal of Digestive Surgery, who were admitted to 15 medical centers from January 2014 to January 2021, were collected. There were 285 males and 539 females, aged (62±11)years. According to the evalua-tion criteria of TOLS, patients were divided into those who achieved TOLS and those who did not achieve TOLS. Measurement data with normal distribution were represented as Mean± SD, and com-parison between groups was conducted using the independent sample t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. Comparison of ordinal data were conduc-ted using the Mann-Whitney U test. The Kaplan-Meier method was used to calculate survival rate and draw survival curve, and the Log-rank test was used for survival analysis. The COX stepwise regression model with backward Wald method was used for univariate and multivariate analyses. Results:(1) Achievement of TOLS. Of the 824 patients undergoing curative-intent resection for GBC, there were 510 cases achieving TOLS and 314 cases not achieving TOLS. (2) Follow-up. Of the 824 patients undergoing curative-intent resection for GBC, after excluding 112 deaths within 90 days after discharge, 712 cases were included for the survival analysis. The median follow-up time, median overall survival time and 5-year overall survival rate of the 510 patients achieving TOLS were 22.1(11.4,30.1)months, 47.6(30.6,64.6)months and 47.5%. The median follow-up time, median overall survival time and 5-year overall survival rate of the 202 patients not achieving TOLS were 14.0(6.8,25.5)months, 24.3(20.0,28.6)months and 21.0%. There was a significant difference in overall survival between patients achieving TOLS and patients not achieving TOLS ( χ2=58.491, P<0.05). (3) Analysis of factors influencing prognosis of patients. Results of multivariate analysis showed that TOLS, carcinoembryonic antigen (CEA), CA19-9, poorly differentiation of tumor, T2 stage of eighth edition of American Joint Committee on Cancer (AJCC) staging, T3 and T4 stage of eighth edition of AJCC staging, N1 stage of the eighth edition of AJCC staging, N2 stage of the eighth edition of AJCC staging, adjuvant therapy were independent factors influencing overall survival time of patients undergoing curative-intent resection for GBC ( hazard ratio=0.452, 1.479, 1.373, 1.612, 1.455, 1.481, 1.835, 1.978, 0.538, 95% c onfidence interval as 0.352-0.581, 1.141-1.964, 1.052-1.791, 1.259-2.063, 1.102-1.920, 1.022-2.147, 1.380-2.441, 1.342-2.915, 0.382-0.758, P<0.05). Conclusion:Patients under-going curative-intent resection for GBC with TOLS can achieve better long-term prognosis.

Objective Using the weighted gene co-expression network analysis(WGCNA)to explore the key genes of aging associated with Alzheimer's disease(AD).Methods GSE132903 was selected from GEO database as the analysis dataset.The differential expressed genes(DEGs)of AD were screened,and visualized with volcano and heat map.Aging and senescence-associated genes(ASAGs)were downloaded from MsigDB,Aging Altas and CellAge databases.WGCNA screened the gene modules with the highest correlation with AD,and genes of key modules subsequently performed with gene ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.AD age-related differential expressed genes(ARDEGs)were obtained by taking intersection genes of DEGs,key module genes of WGCNA and ASAGs.Protein-protein interaction(PPI)network analysis was performed using the STRING database to find key node genes.The co-expression networks and associated functions of key genes were analyzed using the GeneMANIA database.The key genes were validated in Alzdata database.Results 226 DEGs,606 ASAGs and 8 ARDEGs were obtained.The top 5 key genes selected by PPI were SYP,STXBP1,VAMP2,CPLX1 and STX1A.Alzdata database verified that the expressions of 5 key genes in other brain regions of AD were down-regulated,except for no significant changes of VAMP2 in hippocampus and STXBP1 in frontal cortex,as well as no expression of CPLX1 in frontal cortex.The differential expression of VAMP2,STXBP1 and STX1A appeared in the early stage of AD,and CPLX1 was related to the pathological process of Tau.SYP and STXBP1 were related to the pathological processes of amyloid β-protein and Tau.Conclusion SYP,STXBP1,VAMP2,CPLX1 and STX1A are ARDEGs,which are expected to be potential diagnostic and therapeutic targets for AD.

Objective:To estimate the longitudinal association between serum lipid biomarkers and the development of cardiometabolic multimorbidity (CMM) in middle-aged and old adults (≥45) in China, while examining effect differences among degree of dyslipidemia aggregation and various dyslipidemia combination patterns.Methods:Based on data from the China Health and Retirement Longitudinal Study (2011-2018), logistic regression analysis was used to evaluate the associations of TC, LDL-C, HDL-C, TG (4 forms of dyslipidemias), degree and pattern of dyslipidemia combination with CMM. We also used restricted cubic splines to show the dose-response associations between 4 lipid biomarkers and CMM development.Results:Of the 6 522 participants included, 590 (9.05%) developed CMM. After adjusting for covariates, all 4 forms of dyslipidemias were positively associated with CMM development (high TC: OR=1.33, 95% CI: 1.03-1.71; high LDL-C: OR=1.35, 95% CI: 1.05-1.75; low HDL-C: OR=1.45, 95% CI: 1.19-1.77; high TG: OR=1.50, 95% CI: 1.20-1.88). The U-shaped dose-response relationship between LDL-C and CMM development was observed ( P for non-linear =0.022). The odds of CMM increased with the increase of dyslipidemias forms, which was highest in those with ≥3 forms of dyslipidemias ( OR=2.02, 95% CI: 1.33-3.06). In various dyslipidemia form combinations, the possibility of CMM development was highest in those with high TC, high LDL-C and low HDL-C ( OR=3.54, 95% CI: 1.40-8.67). High TC and high LDL-C were significantly associated with CMM development in people without cardiometabolic diseases. Low HDL-C was positively associated with diabetes and CMM development in participants without cardiometabolic diseases, cardiovascular disease (CVD) followed by diabetes, and diabetes followed by CVD. High TG was positively associated with diabetes and CMM in participants without cardiometabolic diseases, and diabetes followed by CVD. Conclusions:A total of 4 forms of dyslipidemia were all independently associated with CMM development in middle-aged and old adults in China. The dose-response relationship between LDL-C level and CMM development was U-shaped. The aggregation of 4 forms of dyslipidemia were associated with the development of CMM. Low HDL-C and high TG were significantly associated with multiple patterns of cardiometabolic diseases development.

The article presents the diagnosis and treatment of an imported case with severe Plasmodium falciparum malaria, and the effect of plasma exchange combined with continuous renal replacement therapy. Severe P. falciparum malaria is characterized by complex clinical symptoms and multiple complications, and plasma exchange combined with continuous renal replacement therapy has a satisfactory therapeutic efficacy for severe P. falciparum malaria.

Existing neuroregulatory techniques can achieve precise stimulation of the whole brain or cortex, but high-focus deep brain stimulation has been a technical bottleneck in this field. In this paper, based on the theory of negative permeability emerged in recent years, a simulation model of magnetic replicator is established to study the distribution of the induced electric field in the deep brain and explore the possibility of deep focusing, which is compared with the traditional magnetic stimulation method. Simulation results show that a single magnetic replicator realized remote magnetic source. Under the condition of the same position and compared with the traditional method of stimulating, the former generated smaller induced electric field which sharply reduced with distance. By superposition of the magnetic field replicator, the induced electric field intensity could be increased and the focus could be improved, reducing the number of peripheral wires while guaranteeing good focus. The magnetic replicator model established in this paper provides a new idea for precise deep brain stimulation, which can be combined with neuroregulatory techniques in the future to lay a foundation for clinical application.
Brain ; Cerebral Cortex ; Computer Simulation ; Electricity ; Magnetic Fields

Transcranial electric stimulation (TES) is a non-invasive, economical, and well-tolerated neuromodulation technique. However, traditional TES is a whole-brain stimulation with a small current, which cannot satisfy the need for effectively focused stimulation of deep brain areas in clinical treatment. With the deepening of the clinical application of TES, researchers have constantly investigated new methods for deeper, more intense, and more focused stimulation, especially multi-electrode stimulation represented by high-precision TES and temporal interference stimulation. This paper reviews the stimulation optimization schemes of TES in recent years and further analyzes the characteristics and limitations of existing stimulation methods, aiming to provide a reference for related clinical applications and guide the following research on TES. In addition, this paper proposes the viewpoint of the development direction of TES, especially the direction of optimizing TES for deep brain stimulation, aiming to provide new ideas for subsequent research and application.
Transcranial Direct Current Stimulation/methods* ; Deep Brain Stimulation ; Brain/physiology* ; Head ; Electric Stimulation/methods*