OBJECTIVE:To evaluate the efficacy and safety of different immunosorbent columns in the treatment of rheumatoid arthritis through a network meta-analysis,and provide evidence-based basis for clinical diagnosis and treatment.METHODS:By computer,the databases of VIP,WanFang,CNKI,PubMed,CBM,CochraneLibrary,and Web of Science were searched for published cohort studies of immunosorbent column for the treatment of rheumatoid arthritis,with a time limit until August 2024.The quality of the included randomized controlled trials was assessed using the Cochrane5.4 manual.The quality of retrospective cohort studies were evaluated via the Newcastle-Ottawa Scale(NOS).Bayesian network meta-analysis was performed using R4.1.1 software.RESULTS:A total of 13 studies were included,with a total sample size of 891 cases,and 4 immunosorbent columns were included.The results of the network meta-analysis showed that the top three orders that reduce C-reactive protein level:HA280 adsorption column+conventional Western medicine＞PH-350 adsorption column+conventional Western medicine＞A protein adsorption column;the top three orders that reduce erythrocyte sedimentation rates:leukocyte adsorption column＞HA280 adsorption column+conventional Western medicine＞PH-350 adsorption column+conventional western medicine;the top three orders that reduce swollen joint count:leukocyte adsorption column＞A protein adsorption column+conventional western medicine＞PH-350 type adsorption column+conventional Western medicine;the top three orders that reduce tenderness joint counts:leukocyte adsorption column＞A protein adsorption column+conventional western medicine＞PH-350 adsorption column+conventional Western medicine;the top three orders that reduce patients' disease activity evaluation:PH-350 adsorption column+conventional western medicine＞leukocyte adsorption column＞A protein adsorption column;the top three orders that reduce visual analogue scale scores:PH-350 adsorption column+conventional Western medicine＞A protein adsorption column＞leukocyte adsorption column;the top three orders that reduce physician's disease activity assessment:PH-350 adsorption column+conventional Western medicine＞leukocyte adsorption column＞conventional Western medicine.CONCLUSION:Based on the 13 articles,in terms of reducing C-reactive protein level,HA280 adsorption column and conventional Western medicine are the preferred choice.In terms of reducing erythrocyte sedimentation rate,swollen joint count,and tender joint count,leukocyte adsorption column is the preferred choice.In terms of reducing patient's disease activity evaluation,physician's disease activity evaluation and visual analogue scale scores,PH-350 adsorption column and conventional Western medicine are the first choice.Different immunosorbent columns can be reasonably and accurately selected according to the patient's specific conditions.

OBJECTIVE:To evaluate the efficacy and safety of different immunosorbent columns in the treatment of rheumatoid arthritis through a network meta-analysis,and provide evidence-based basis for clinical diagnosis and treatment.METHODS:By computer,the databases of VIP,WanFang,CNKI,PubMed,CBM,CochraneLibrary,and Web of Science were searched for published cohort studies of immunosorbent column for the treatment of rheumatoid arthritis,with a time limit until August 2024.The quality of the included randomized controlled trials was assessed using the Cochrane5.4 manual.The quality of retrospective cohort studies were evaluated via the Newcastle-Ottawa Scale(NOS).Bayesian network meta-analysis was performed using R4.1.1 software.RESULTS:A total of 13 studies were included,with a total sample size of 891 cases,and 4 immunosorbent columns were included.The results of the network meta-analysis showed that the top three orders that reduce C-reactive protein level:HA280 adsorption column+conventional Western medicine＞PH-350 adsorption column+conventional Western medicine＞A protein adsorption column;the top three orders that reduce erythrocyte sedimentation rates:leukocyte adsorption column＞HA280 adsorption column+conventional Western medicine＞PH-350 adsorption column+conventional western medicine;the top three orders that reduce swollen joint count:leukocyte adsorption column＞A protein adsorption column+conventional western medicine＞PH-350 type adsorption column+conventional Western medicine;the top three orders that reduce tenderness joint counts:leukocyte adsorption column＞A protein adsorption column+conventional western medicine＞PH-350 adsorption column+conventional Western medicine;the top three orders that reduce patients' disease activity evaluation:PH-350 adsorption column+conventional western medicine＞leukocyte adsorption column＞A protein adsorption column;the top three orders that reduce visual analogue scale scores:PH-350 adsorption column+conventional Western medicine＞A protein adsorption column＞leukocyte adsorption column;the top three orders that reduce physician's disease activity assessment:PH-350 adsorption column+conventional Western medicine＞leukocyte adsorption column＞conventional Western medicine.CONCLUSION:Based on the 13 articles,in terms of reducing C-reactive protein level,HA280 adsorption column and conventional Western medicine are the preferred choice.In terms of reducing erythrocyte sedimentation rate,swollen joint count,and tender joint count,leukocyte adsorption column is the preferred choice.In terms of reducing patient's disease activity evaluation,physician's disease activity evaluation and visual analogue scale scores,PH-350 adsorption column and conventional Western medicine are the first choice.Different immunosorbent columns can be reasonably and accurately selected according to the patient's specific conditions.

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*

Objective:To understand the incidence trend of brucellosis over time in Shandong Province from 2004 to 2023, and provide evidence for the prevention and control of brucellosis.Methods:The incidence data of brucellosis in Shandong from 2004 to 2023 were collected from China Disease Prevention and Control Information System. The annual change percentage (APC) and annual average change percentage (AAPC) of the incidence rate were calculated by using Joinpoint regression model. A age-period-cohort model was used to analyze changes in brucellosis incidence with age, period, and birth cohort.Results:The average annual incidence of brucellosis was 1.76/100 000 in Shandong from 2004 to 2023. The Joinpoint regression analysis results showed that the reported incidence of brucellosis increased by an average of 92.0% and 18.9% each year from 2004 to 2010 and from 2010 to 2014, respectively, and decreased by an average of 0.2% each year from 2014 to 2023. The results of APC model showed that the incidence of brucellosis increased first and then decreased with age ( χ2=176.92, P<0.001), and incidence of brucellosis showed slow increase and rapid increase first, then decrease ( χ2=2 921.03, P<0.001) over time. The risk for brucellosis reached peak in 2016 ( RR=5.29, 95% CI: 4.96-5.65) and became the lowest in 2006 ( RR=0.24, 95% CI: 0.21-0.28). The incidence increased in later birth cohort ( χ2=348.88, P<0.001), the AAPCs of all the age groups were between 15.0% and 40.0%, and the older the age, the greater the risk ( χ2=348.77, P<0.001). Conclusions:From 2004 to 2023, the reported incidence of brucellosis in Shandong showed a significant age-period-cohort effect, which increased first and then decreased, first increased and then decreased with age, increased slowly and rapidly first, then decreased over time, and increased in later birth cohort. It is necessary to conduct targeted prevention and control, health education to reduce the risk for brucellosis.

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.

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,chal-lenges 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,mo-lecular 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 understand the incidence trend of brucellosis over time in Shandong Province from 2004 to 2023, and provide evidence for the prevention and control of brucellosis.Methods:The incidence data of brucellosis in Shandong from 2004 to 2023 were collected from China Disease Prevention and Control Information System. The annual change percentage (APC) and annual average change percentage (AAPC) of the incidence rate were calculated by using Joinpoint regression model. A age-period-cohort model was used to analyze changes in brucellosis incidence with age, period, and birth cohort.Results:The average annual incidence of brucellosis was 1.76/100 000 in Shandong from 2004 to 2023. The Joinpoint regression analysis results showed that the reported incidence of brucellosis increased by an average of 92.0% and 18.9% each year from 2004 to 2010 and from 2010 to 2014, respectively, and decreased by an average of 0.2% each year from 2014 to 2023. The results of APC model showed that the incidence of brucellosis increased first and then decreased with age ( χ2=176.92, P<0.001), and incidence of brucellosis showed slow increase and rapid increase first, then decrease ( χ2=2 921.03, P<0.001) over time. The risk for brucellosis reached peak in 2016 ( RR=5.29, 95% CI: 4.96-5.65) and became the lowest in 2006 ( RR=0.24, 95% CI: 0.21-0.28). The incidence increased in later birth cohort ( χ2=348.88, P<0.001), the AAPCs of all the age groups were between 15.0% and 40.0%, and the older the age, the greater the risk ( χ2=348.77, P<0.001). Conclusions:From 2004 to 2023, the reported incidence of brucellosis in Shandong showed a significant age-period-cohort effect, which increased first and then decreased, first increased and then decreased with age, increased slowly and rapidly first, then decreased over time, and increased in later birth cohort. It is necessary to conduct targeted prevention and control, health education to reduce the risk for brucellosis.

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.

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.