Association between serum albumin levels and disease severity in adult patients with dengue: A 7-year retrospective cohort study in China's Mainland

Objective:To identify the association between serum albumin levels and disease severity among adult patients with dengue in China's Mainland.Methods:This retrospective cohort study analyzed the data of adult patients(aged≥18 years)hospitalized with laboratory-confirmed dengue in a tertiary center for infectious diseases from 2013 to 2019 in China's Mainland.Serum albumin levels were estimated and compared between patients with severe dengue and non-severe dengue.Additionally,the association between serum albumin levels and severe dengue was evaluated using a generalized linear model[relative risks(RR)].Multivariate logistic regression analysis was performed to identify the potential predictors of severe dengue.Results:Overall,1568 patients were included in this study.Of these patients,34(2.17%)developed severe dengue.The median serum albumin levels were significantly lower in patients with severe dengue than that in those with non-severe dengue(33 g/L vs.37 g/L,P<0.001).After adjustment for age,sex,and comorbidities,hypoalbuminemia(RR 4.877,95%CI 2.193-11.461,P<0.001)was found to be a predictor of severe dengue.Serum albumin levels(OR 1.303,95%CI 1.161-1.462,P<0.001)and age(OR 1.038,95%CI 1.017-1.061,P<0.001)were significant risk factors for severe dengue.The area under the curve for serum albumin levels to distinguish severe dengue was 0.787.Conclusions:Lower serum albumin levels were significantly associated with disease severity in adult patients with dengue.Hypoalbuminemia on admission resulted in at least a four-fold increased risk of severe dengue.

Molecular phylogenomic analysis reveals a single origin of monkeypox virus transmission in Guangzhou,China in June 2023

The monkeypox(mpox)virus has caused worldwide transmission since its initial report in England in early May 2022.Available data from the World Health Organization(WHO)show that Europe and the Americas experienced a huge wave of mpox virus infection.Now the number of infected cases is on the rise in Asia.Several sporadic infections have been reported in China.In this study,we obtained high‐quality whole viral genomic sequences using a mpox virus‐specific amplicon‐based sequencing strategy.Our analysis of the phylogenomic characteristics indicated that all eight mpox virus sequences from Guangzhou belonged to the clade IIb lineage B.1.3 cluster.However,we could not locate the exact origins where the virus was imported,based on all the available mpox virus sequences from the Global Initiative on Sharing Avian Influenza Data(GISAID)database(https://gisaid.org/),except for their closest sequence similarity to that was reported from Japan.Novel amino acid mutations were found among the eight cases,suggesting that a local transmission may have occurred in Guangzhou,China.

Engineering a fumaric acid-responsive two-component biosensor for dynamic range improvement in Escherichia coli

Due to the selective permeability of the cytomembrane,high-yield fumaric acid strains form a steep difference between intra-and extracellular concentrations.Intracellular biosensors cannot detect the real concentration change of extracellular fumaric acid.To overcome this limitation,a two-component biosensor(TCB)that could respond to extracellular fumaric acid was designed based on the DcuS-DcuR two-component system.The two-component system consists of a histidine kinase(SK)and response regulator.SK is a transmembrane histidine kinase sensor that can detect concentration changes in extracellular compounds.To improve the dynamic range of the constructed fumaric acid TCB,we optimized the expression ratio and expression intensity of dcuS and dcuR.We found that the optimum expression ratio of dcuS:dcuR was 46:54.Under this ratio,the higher was the expression level,the greater the dynamic range.In addition,we modified the ATP-binding site on the DcuS,and the final dynamic range of the TCB reached 6.6-fold.Overall,the obtained fumaric acid-responsive TCB with a high dynamic range is reported for the first time,providing a synthetic biology tool for high-throughput screening and dynamic metabolic regulation of fumaric acid cell factories.

Genetic and pathogenicity diversity of dengue virus type 2 strains circulating in Guangdong,China

Dengue fever is a mosquito-borne viral disease spread in tropical and subtropical regions caused by the dengue virus(DENV).DENV causes a febrile illness,severe forms including hemorrhagic fevers and shock with fatalities in humans.DENV-2 is frequently associated with severe dengue infections and epidemics.DENV-2 strains from Guangdong,China,have not been characterized to compare the phylogenetics and pathogenicity of different DENV-2 subgenotype strains in both vitro and vivo.A total of 22 patients tested to be DENV-2 positive and were enrolled in this study,22 complete genomes were obtained by virus isolation and high-throughput sequencing.Phylogenetic and single amino polymorphism(SAP)analysis indicated that two major subgenotypes(A and C)of DENV-2 Cosmopolitan were prevalent in Guangdong in 2018.The apparent change of major subgenotypes of DENV-2 circulating in Guangdong indicated the diversity of DENV-2 strains,including endemic genotype and imported genotype.It alerted the risk of cross-border transmission of DENV.A significant difference in replication rate was observed in C6/36 between different DENV-2 strains,although growth kinetics comparison of different DENV-2 Cosmopolitan subgenotypes showed similar profiles.DENV-2 subgenotypes(A and C)replicated efficiently in IFNAR−/−C57BL/6 mice,and subgenotype A of Cosmopolitan infected mice showed increased weight loss and delayed viral clearance compared with the subgenotype C group.DENV-2 prevalent in Guangdong in 2018 showed apparent genetic and pathogenicity diversity in both vitro and vivo,indicating the necessity of molecular surveillance and exploration of the relationship between its pathogenicity and clinical characteristics.

Machine-learning-based models assist the prediction of pulmonary embolism in autoimmune diseases:A retrospective,multicenter study

Background:Pulmonary embolism(PE)is a severe and acute cardiovascular syndrome with high mortality among patients with autoimmune inflammatory rheumatic diseases(AIIRDs).Accurate prediction and timely intervention play a pivotal role in enhancing survival rates.However,there is a notable scarcity of practical early prediction and risk assessment systems of PE in patients with AIIRD.Methods:In the training cohort,60 AIIRD with PE cases and 180 age-,gender-,and disease-matched AIIRD non-PE cases were identified from 7254 AIIRD cases in Tongji Hospital from 2014 to 2022.Univariable logistic regression(LR)and least absolute shrinkage and selection operator(LASSO)were used to select the clinical features for further training with machine learning(ML)methods,including random forest(RF),support vector machines(SVM),neural network(NN),logistic regression(LR),gradient boosted decision tree(GBDT),classification and regression trees(CART),and C5.0 models.The performances of these models were subsequently validated using a multicenter validation cohort.Results:In the training cohort,24 and 13 clinical features were selected by univariable LR and LASSO strategies,respectively.The five ML models(RF,SVM,NN,LR,and GBDT)showed promising performances,with an area under the receiver operating characteristic(ROC)curve(AUC)of 0.962-1.000 in the training cohort and 0.969-0.999 in the validation cohort.CART and C5.0 models achieved AUCs of 0.850 and 0.932,respectively,in the training cohort.Using D-dimer as a pre-screening index,the refined C5.0 model achieved an AUC exceeding 0.948 in the training cohort and an AUC above 0.925 in the validation cohort.These results markedly outperformed the use of D-dimer levels alone.Conclusion:ML-based models are proven to be precise for predicting the onset of PE in patients with AIIRD exhibiting clinical suspicion of PE.Trial Registration:Chictr.org.cn:ChiCTR2200059599.