Racial disparities in outcomes for extracorporeal membrane oxygenation in the United States

BackgroundRacial disparities in extracorporeal membrane oxygenation (ECMO) outcomes in patients with a broad set of indications are not well documented.MethodsAdults requiring ECMO were identified in the 2016–2019 National Inpatient Sample. Patient and hospital characteristics, including mortality, clinical outcomes, and resource utilization were analyzed using multivariable regressions.ResultsOf 43,190 adult ECMO patients, 67.8% were classified as White, 18.1% Black, and 10.4% Hispanic. Although mortality for Whites declined from 47.5 to 41.0% (P = 0.002), it remained steady for others. Compared to White, Asian/Pacific Islander (PI) race was linked to increased odds of mortalty (AOR = 1.4, 95% CI = 1.1–2.0). Black race was associated with increased odds of acute kidney injury (AOR = 1.4, 95%-CI: 1.2–1.7), while Hispanic race was linked to neurologic complications (AOR 21.6; 95% CI 1.2–2.3). Black and Hispanic race were also associated with increased incremental costs.ConclusionsRace-based disparities in ECMO outcomes persist in the United States. Further work should aim to understand and mitigate the underlying reasons for such findings.     

Comprehensive interrogation of gene lists from genome-scale cancer screens with oncoEnrichR

Genome-scale screening experiments in cancer produce long lists of candidate genes that require extensive interpretation for biological insight and prioritization for follow-up studies. Interrogation of gene lists frequently represents a significant and time-consuming undertaking, in which experimental biologists typically combine results from a variety of bioinformatics resources in an attempt to portray and understand cancer relevance. As a means to simplify and strengthen the support for this endeavor, we have developed oncoEnrichR, a flexible bioinformatics tool that allows cancer researchers to comprehensively interrogate a given gene list along multiple facets of cancer relevance. oncoEnrichR differs from general gene set analysis frameworks through the integration of an extensive set of prior knowledge specifically relevant for cancer, including ranked gene-tumor type associations, literature-supported proto-oncogene and tumor suppressor gene annotations, target druggability data, regulatory interactions, synthetic lethality predictions, as well as prognostic associations, gene aberrations and co-expression patterns across tumor types. The software produces a structured and user-friendly analysis report as its main output, where versions of all underlying data resources are explicitly logged, the latter being a critical component for reproducible science. We demonstrate the usefulness of oncoEnrichR through interrogation of two candidate lists from proteomic and CRISPR screens. oncoEnrichR is freely available as a web-based service hosted by the Galaxy platform ( https://oncotools.elixir.no ), and can also be accessed as a stand-alone R package ( https://github.com/sigven/oncoEnrichR ).     

A prognostic signature based on immune-related genes for cervical squamous cell carcinoma and endocervical adenocarcinoma

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is the fourth commonest female malignancy worldwide. CESC progresses in immune-microenvironment mainly composed of infiltrating immune and stromal cells. Here, we performed an integrated analysis incorporating the expression profiles from the Cancer Genome Atlas (TCGA) database and scores of immune and stromal cells calculated by Estimation of Stromal and Immune cells in Malignant Tumours using Expression data (ESTIMATE) algorithm. A two-gene signature (CD1C and CD6 genes) was established to predict the prognosis of CESC. Based on this signature, patients were divided into the high- and low-risk groups, and this signature showed good prognostic performance according to the results of Kaplan-Meier analysis and receiver operating characteristic (ROC) analysis in train set and two validation sets. A nomogram was built for evaluating the clinical applicability of this signature. In addition, based on Tumor Immune Estimation Resource (TIMER) database, 2 hub genes showed negative correlations with tumor purity and positive correlations with infiltrating levels of immune filtrating cells. What’s more, we propose new treatment strategies for the two prognostic subtypes. Low- risk patients were found presenting with a higher level of immune checkpoint molecules and showing higher immunogenicity in immunophenoscore (IPS) analysis, which indicated a better response for immunotherapy. Meanwhile, estimated by Genomics of Drug Sensitivity in Cancer (GDSC) database, the high-risk patients showed sensitive responses to five chemotherapy drugs. Finally, 10 candidate small-molecule drugs for CESC were defined. In summary, the CD1C-CD6 signature can accurately predict the prognosis of CESC.     

美国新药技术成熟度评价研究

目的研究提出适合我国新药研发和药品安全管理的技术成熟度评价机制。方法借鉴美国新药研发技术成熟度等级(biomedical technology readiness level,BTRL)评价标准与方法,结合我国新药研发、监管和产业化特点,提出我国成熟度评价等级和指标,并在重大新药创制科技重大专项研发管理中开展探索分析。结果与结论探索建立我国化学药和生物制品技术成熟度评价等级标准,将为我国新药研发科研项目和保障药品安全提供管理与评估工具,为其他行业领域提供参考借鉴。     

Brain maturation in the first 3 months of life,measured by electroencephalogram: A comparison between preterm and term-born infants

ObjectivePreterm infants are at risk for altered brain maturation resulting in neurodevelopmental impairments. Topographical analysis of high-density electroencephalogram during sleep matches underlying brain maturation. Using such an EEG mapping approach could identify preterm infants at risk early in life.Methods20 preterm (gestational age < 32 weeks) and 20 term-born infants (gestational age > 37 weeks) were recorded by 18-channel daytime sleep-EEG at term age (GA 40 weeks for preterm and 2–3 days after birth for term infants) and 3 months (corrected age for preterm infants).ResultsPreterm infant’s power spectrum at term age is immature, leveling off with term infants at 3 months of age. Topographical distribution of maximal power density however, reveals qualitative differences between the groups until 3 months of age. Preterm infants exhibit more temporal than central activation at term age and more occipital than central activation at 3 months of age. Moreover, being less mature at term age predicts being less mature at 3 months of age.ConclusionTopographical analysis of sleep EEG reveals changes in brain maturation between term and preterm infants early in life.SignificanceIn future, automated analysis tools using topographical power distribution could help identify preterm infants at risk early in life.     

医疗领域人工智能应用的研究进展＊

人工智能引发了医疗领域的数字革命，在推动行业发展方面具有极大潜力。本研究围绕临床诊疗、医学研究和公共卫生三个基本场景，聚焦人工智能与传统中医药的交叉与融合，并着重介绍人工智能在疾病诊断、决策支持、医学研究以及重大公共卫生事件中的应用。虽然人工智能在诸多方面显示出独特优势，但仍存在透明度不高、缺乏安全性评估和相关法律法规监管等问题需要谨慎解决，以促进人工智能技术在医疗领域的推广。     

BCL2 G quadruplex-binding small molecules: Current status and prospects for the development of next-generation anticancer therapeutics

B cell lymphoma 2 (BCL2) overexpression in a range of human tumors is often related to chemotherapy resistance and poor prognosis. GC-rich regions upstream of the P1 promoter in human BCL2 can form G-quadruplex (G4) structures through the stacking of four Hoogsteen-paired guanine bases. Stabilizing the G4 fold implies the inhibition of BCL2 expression and, thus, small molecules that selectively bind to the G4 are promising anticancer candidates. In this review, we discuss the structural aspects, binding affinity, selectivity, and biological activity of well-characterized BCL2 G4 binding ligands in vitro and in vivo. We also explore future directions in the research and development of G4-based anticancer therapeutics.     

Conserved pan-cancer microenvironment subtypes predict response to immunotherapy

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PARP7 negatively regulates the type I interferon response in cancer cells and its inhibition triggers antitumor immunity

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