Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis

Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.

A multi-center,double-blind,randomized,placebo-and positive-controlled phase II clinical study of benvitimod for the treatment of atopic dermatitis

To the Editor:Atopic dermatitis(AD)is a chronic,recurrent,and inflammatory skin disease that can be accompanied by asthma,allergic rhinitis,conjunctivitis,and other diseases.[1]Topical corticosteroids are mostly used in patients with AD.Considering the side effects of the long-term use of corticosteroids,additional topical treatments could be useful.

Epidemiology of urticaria in China:a population-based study

Background:Urticaria is a common skin disease characterized by episodes of wheals,and it has a negative effect on patients’quality of life.Large-scale population-based epidemiological studies of urticaria are scarce in China.The aim of this survey was to determine the prevalence,clinical forms,and risk factors of urticaria in the Chinese population.Methods:This survey was conducted in 35 cities from 31 provinces,autonomous regions,and municipalities of China.Two to three communities in each city were selected in this investigation.Participants completed questionnaires and received dermatological examinations.We analyzed the prevalence,clinical forms,and risk factors of urticaria.Results:In total,44,875 questionnaires were distributed and 41,041 valid questionnaires were collected(17,563 male and 23,478 female participants).The lifetime prevalence of urticaria was 7.30%,with 8.26%in female and 6.34%in male individuals(P<0.05).The point prevalence of urticaria was 0.75%,with 0.79%in female and 0.71%in male individuals(P<0.05).Concomitant angioedema was found in 6.16%of patients.Adults had a higher prevalence of urticaria than adolescents and children.Living in urban areas,exposure to pollutants,an anxious or depressed psychological status,a personal and family history of allergy,thyroid diseases,and Helicobacter pylori infection were associated with a higher prevalence of urticaria.Smoking was correlated with a reduced risk of urticaria.Conclusion:This study demonstrated that the lifetime prevalence of urticaria was 7.30%and the point prevalence was 0.75%in the Chinese population;women had a higher prevalence of urticaria than men.Various factors were correlated with urticaria.

Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information

Proteases are enzymes that cleave and hydrolyse the peptide bonds between two specific amino acid residues of target substrate proteins.Protease-controlled proteolysis plays a key role in the degradation and recycling of proteins,which is essential for various physiological processes.Thus,solving the substrate identification problem will have important implications for the precise understanding of functions and physiological roles of proteases,as well as for therapeutic target identification and pharmaceutical applicability.Consequently,there is a great demand for bioinformatics methods that can predict novel substrate cleavage events with high accuracy by utilizing both sequence and structural information.In this study,we present Procleave,a novel bioinformatics approach for predicting protease-specific substrates and specific cleavage sites by taking into account both their sequence and 3D structural information.Structural features of known cleavage sites were represented by discrete values using a LOWESS data-smoothing optimization method,which turned out to be critical for the performance of Procleave.The optimal approximations of all structural parameter values were encoded in a conditional random field(CRF)computational framework,alongside sequence and chemical group-based features.Here,we demonstrate the outstanding performance of Procleave through extensive benchmarking and independent tests.Procleave is capable of correctly identifying most cleavage sites in the case study.Importantly,when applied to the human structural proteome encompassing 17,628 protein structures,Procleave suggests a number of potential novel target substrates and their corresponding cleavage sites of different proteases.Procleave is implemented as a webserver and is freely accessible at http://procleave.erc.monash.edu/.