BACKGROUND Multiple myeloma(MM)is a terminal differentiated B-cell tumor disease characterized by clonal proliferation of malignant plasma cells and excessive levels of monoclonal immunoglobulins in the bone marrow.Th...BACKGROUND Multiple myeloma(MM)is a terminal differentiated B-cell tumor disease characterized by clonal proliferation of malignant plasma cells and excessive levels of monoclonal immunoglobulins in the bone marrow.The translocation,(t)(4;14),results in high-risk MM with limited treatment alternatives.Thus,there is an urgent need for identification and validation of potential treatments for this MM subtype.Microarray data and sequencing information from public databases could offer opportunities for the discovery of new diagnostic or therapeutic targets.AIM To elucidate the molecular basis and search for potential effective drugs of t(4;14)MM subtype by employing a comprehensive approach.METHODS The transcriptional signature of t(4;14)MM was sourced from the Gene Expression Omnibus.Two datasets,GSE16558 and GSE116294,which included 17 and 15 t(4;14)MM bone marrow samples,and five and four normal bone marrow samples,respectively.After the differentially expressed genes were identified,the Cytohubba tool was used to screen for hub genes.Then,the hub genes were analyzed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis.Using the STRING database and Cytoscape,protein–protein interaction networks and core targets were identified.Potential small-molecule drugs were identified and validated using the Connectivity Map database and molecular docking analysis,respectively.RESULTS In this study,a total of 258 differentially expressed genes with enriched functions in cancer pathways,namely cytokine receptor interactions,nuclear factor(NF)-κB signaling pathway,lipid metabolism,atherosclerosis,and Hippo signaling pathway,were identified.Ten hub genes(cd45,vcam1,ccl3,cd56,app,cd48,btk,ccr2,cybb,and cxcl12)were identified.Nine drugs,including ivermectin,deforolimus,and isoliquiritigenin,were predicted by the Connectivity Map database to have potential therapeutic effects on t(4;14)MM.In molecular docking,ivermectin showed strong binding affinity to all 10 identified targets,especially cd45 and cybb.Ivermectin inhibited t(4;14)MM cell growth via the NF-κB pathway and induced MM cell apoptosis in vitro.Furthermore,ivermectin increased reactive oxygen species accumulation and altered the mitochondrial membrane potential in t(4;14)MM cells.CONCLUSION Collectively,the findings offer valuable molecular insights for biomarker validation and potential drug development in t(4;14)MM diagnosis and treatment,with ivermectin emerging as a potential therapeutic alternative.展开更多
Background Although angiotensin converting enzyme inhibitors （ACEI） and angiotensin receptor blockers （ARB） are equally important in the treatment of hypertension, there is less evidence whether they have equal ca...Background Although angiotensin converting enzyme inhibitors （ACEI） and angiotensin receptor blockers （ARB） are equally important in the treatment of hypertension, there is less evidence whether they have equal cardiovascular and cerebrovascular protective effects, especially in elder hypertensive patients. This study aims to clarify this unresolved issue. Methods This cross-sectional study included clinical data on 933 aged male patients with hypertension who received either an ARB or ACEI for more than two months between January 2007 and May 2011. The primary outcome was the composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. The secondary endpoints were unstable angina, new atrial fibrillation, and transient ischemic attack. Results The median follow-up time was 24 months. Age, drug types, cerebral infarction history, renal dysfunction history were the independent predictors of the primary endpoint. The risk of an occurrence of a primary endpoint event was higher in the ARB group than the ACEI group [P = 0.037, hazard ratios （HR）： 2.124, 95% confidence interval （95% CI）： 1.048-4.306]. The Kaplan-Meier method also suggests that the rate of primary endpoint occurrence was higher in the ARB group than the ACEI group （P = 0.04）. In regard to the secondary endpoints, there were no significant differences between the two treatment arms （P = 0.137, HR： 1.454, 95% CI： 0.888-2.380）. Patient age and coronary heart disease history were independent predictors of the secondary endpoint. Conclusion ACEI were more effective than ARB in reducing cardiovascular and cerebrovascular morbidity and mortality in aged patients with hypertension.展开更多
Background The global spread of coronavirus disease 2019(COVID-19)continues to threaten human health security,exerting considerable pressure on healthcare systems worldwide.While prognostic models for COVID-19 hospita...Background The global spread of coronavirus disease 2019(COVID-19)continues to threaten human health security,exerting considerable pressure on healthcare systems worldwide.While prognostic models for COVID-19 hospitalized or intensive care patients are currently available,prognostic models developed for large cohorts of thousands of individuals are still lacking.Methods Between February 4 and April 16,2020,we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital,Hubei Province,China.(1)Screening of key prognostic factors:A univariate Cox regression analysis was performed on 2,649 patients in the training set,and factors affecting prognosis were initially screened.Subsequently,a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis.Finally,multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis.(2)Establishment of a scoring system:The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors,calculated the C index,drew calibration curves and drew training set patient survival curves.(3)Verification of the scoring system:The scoring system assessed 1,325 patients in the test set,splitting them into high-and low-risk groups,calculated the C-index,and drew calibration and survival curves.Results The cross-sectional study found that age,clinical classification,sex,pulmonary insufficiency,hypoproteinemia,and four other factors(underlying diseases:blood diseases,malignant tumor;complications:digestive tract bleeding,heart dysfunction)have important significance for the prognosis of the enrolled patients with COVID-19.Herein,we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19.Meanwhile,the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high-and low-risk groups(using a scoring threshold of 117.77,a score below which is considered low risk).The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines(C indexes,0.95 vs.0.89).Conclusions Age,clinical typing,sex,pulmonary insufficiency,hypoproteinemia,and four other factors were important for COVID-19 survival.Compared with general statistical methods,this method can quickly and accurately screen out the relevant factors affecting prognosis,provide an order of importance,and establish a scoring system based on the nomogram model,which is of great clinical significance.展开更多
基金National Key Research and Development Program of China,No.2021YFC2701704the National Clinical Medical Research Center for Geriatric Diseases,"Multicenter RCT"Research Project,No.NCRCG-PLAGH-20230010the Military Logistics Independent Research Project,No.2022HQZZ06.
文摘BACKGROUND Multiple myeloma(MM)is a terminal differentiated B-cell tumor disease characterized by clonal proliferation of malignant plasma cells and excessive levels of monoclonal immunoglobulins in the bone marrow.The translocation,(t)(4;14),results in high-risk MM with limited treatment alternatives.Thus,there is an urgent need for identification and validation of potential treatments for this MM subtype.Microarray data and sequencing information from public databases could offer opportunities for the discovery of new diagnostic or therapeutic targets.AIM To elucidate the molecular basis and search for potential effective drugs of t(4;14)MM subtype by employing a comprehensive approach.METHODS The transcriptional signature of t(4;14)MM was sourced from the Gene Expression Omnibus.Two datasets,GSE16558 and GSE116294,which included 17 and 15 t(4;14)MM bone marrow samples,and five and four normal bone marrow samples,respectively.After the differentially expressed genes were identified,the Cytohubba tool was used to screen for hub genes.Then,the hub genes were analyzed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis.Using the STRING database and Cytoscape,protein–protein interaction networks and core targets were identified.Potential small-molecule drugs were identified and validated using the Connectivity Map database and molecular docking analysis,respectively.RESULTS In this study,a total of 258 differentially expressed genes with enriched functions in cancer pathways,namely cytokine receptor interactions,nuclear factor(NF)-κB signaling pathway,lipid metabolism,atherosclerosis,and Hippo signaling pathway,were identified.Ten hub genes(cd45,vcam1,ccl3,cd56,app,cd48,btk,ccr2,cybb,and cxcl12)were identified.Nine drugs,including ivermectin,deforolimus,and isoliquiritigenin,were predicted by the Connectivity Map database to have potential therapeutic effects on t(4;14)MM.In molecular docking,ivermectin showed strong binding affinity to all 10 identified targets,especially cd45 and cybb.Ivermectin inhibited t(4;14)MM cell growth via the NF-κB pathway and induced MM cell apoptosis in vitro.Furthermore,ivermectin increased reactive oxygen species accumulation and altered the mitochondrial membrane potential in t(4;14)MM cells.CONCLUSION Collectively,the findings offer valuable molecular insights for biomarker validation and potential drug development in t(4;14)MM diagnosis and treatment,with ivermectin emerging as a potential therapeutic alternative.
文摘Background Although angiotensin converting enzyme inhibitors （ACEI） and angiotensin receptor blockers （ARB） are equally important in the treatment of hypertension, there is less evidence whether they have equal cardiovascular and cerebrovascular protective effects, especially in elder hypertensive patients. This study aims to clarify this unresolved issue. Methods This cross-sectional study included clinical data on 933 aged male patients with hypertension who received either an ARB or ACEI for more than two months between January 2007 and May 2011. The primary outcome was the composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. The secondary endpoints were unstable angina, new atrial fibrillation, and transient ischemic attack. Results The median follow-up time was 24 months. Age, drug types, cerebral infarction history, renal dysfunction history were the independent predictors of the primary endpoint. The risk of an occurrence of a primary endpoint event was higher in the ARB group than the ACEI group [P = 0.037, hazard ratios （HR）： 2.124, 95% confidence interval （95% CI）： 1.048-4.306]. The Kaplan-Meier method also suggests that the rate of primary endpoint occurrence was higher in the ARB group than the ACEI group （P = 0.04）. In regard to the secondary endpoints, there were no significant differences between the two treatment arms （P = 0.137, HR： 1.454, 95% CI： 0.888-2.380）. Patient age and coronary heart disease history were independent predictors of the secondary endpoint. Conclusion ACEI were more effective than ARB in reducing cardiovascular and cerebrovascular morbidity and mortality in aged patients with hypertension.
基金supported by National Key Research and Development Program of China(2020YFC2002706).
文摘Background The global spread of coronavirus disease 2019(COVID-19)continues to threaten human health security,exerting considerable pressure on healthcare systems worldwide.While prognostic models for COVID-19 hospitalized or intensive care patients are currently available,prognostic models developed for large cohorts of thousands of individuals are still lacking.Methods Between February 4 and April 16,2020,we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital,Hubei Province,China.(1)Screening of key prognostic factors:A univariate Cox regression analysis was performed on 2,649 patients in the training set,and factors affecting prognosis were initially screened.Subsequently,a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis.Finally,multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis.(2)Establishment of a scoring system:The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors,calculated the C index,drew calibration curves and drew training set patient survival curves.(3)Verification of the scoring system:The scoring system assessed 1,325 patients in the test set,splitting them into high-and low-risk groups,calculated the C-index,and drew calibration and survival curves.Results The cross-sectional study found that age,clinical classification,sex,pulmonary insufficiency,hypoproteinemia,and four other factors(underlying diseases:blood diseases,malignant tumor;complications:digestive tract bleeding,heart dysfunction)have important significance for the prognosis of the enrolled patients with COVID-19.Herein,we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19.Meanwhile,the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high-and low-risk groups(using a scoring threshold of 117.77,a score below which is considered low risk).The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines(C indexes,0.95 vs.0.89).Conclusions Age,clinical typing,sex,pulmonary insufficiency,hypoproteinemia,and four other factors were important for COVID-19 survival.Compared with general statistical methods,this method can quickly and accurately screen out the relevant factors affecting prognosis,provide an order of importance,and establish a scoring system based on the nomogram model,which is of great clinical significance.
