Effect of Disulfiram on the Reproductive Capacity of Female Mice.

In the process of assisted reproduction, the high-oxygen in vitro environment can easily cause oxidative damage to oocytes. Disulfiram (DSF) can play an anti-oxidant or pro-oxidant role in different cells, and the effect of DSF on oocytes remains unclear. Moreover, it remains unclear whether the use of DSF in the early stages of pregnancy has a negative impact on the fetus.

Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record?

Background: In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as ​​reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to identify informative patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients.

Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network.

The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use.

Trajectories of Sleep Disturbance and Self-Management of Chronic Conditions during COVID-19 among Middle-aged and Older Adults.

Background: The COVID-19 pandemic has had a widespread impact on sleep quality, yet little is known about the prevalence of sleep disturbance and its impact on self-management of chronic conditions during the ongoing pandemic.

Objective: To evaluate trajectories of sleep disturbance, and their associations with one's capacity to self-manage chronic conditions.

Design: A longitudinal cohort study linked to 3 active clinical trials and 2 cohort studies with 5 time points of sleep data collection (July 15, 2020 - May 23, 2022).

Differential effects of WRAP53 transcript variants on non-small cell lung cancer cell behaviors.

Background: The WD40-encoding RNA antisense to p53 (WRAP53) is an antisense gene of TP53 with three transcriptional start sites producing three transcript variants involved in the progression of non-small cell lung cancer. However, the mechanism by which these different transcript variants regulate non-small cell lung cancer cell behaviors is to be elucidated.

Methods: Two non-small cell lung cancer cell lines, A549 cells with wild-type p53 and H1975 with mutated p53, were transfected with WRAP53-1α and WRAP53-1β siRNA.

Altered Fractional Amplitude of Low-Frequency Fluctuation in Anxious Parkinson's Disease.

Objective: Anxiety symptoms are persistent in Parkinson's disease (PD), but the underlying neural substrates are still unclear. In the current study, we aimed to explore the underlying neural mechanisms in PD patients with anxiety symptoms.

Methods: 42 PD-A patients, 41 PD patients without anxiety symptoms (PD-NA), and 40 healthy controls (HCs) were recruited in the present study.

Augmented Intelligence to Identify Patients With Advanced Heart Failure in an Integrated Health System.

Background: Timely referral for specialist evaluation in patients with advanced heart failure (HF) is a Class 1 recommendation. However, the transition from stage C HF to advanced or stage D HF often goes undetected in routine care, resulting in delayed referral and higher mortality rates.

Objectives: The authors sought to develop an augmented intelligence-enabled workflow using machine learning to identify patients with stage D HF and streamline referral.

Duplicated Flagellins in Pseudomonas Divergently Contribute to Motility and Plant Immune Elicitation.

Flagellins are the main constituents of the flagellar filaments that provide bacterial motility, chemotactic ability, and host immune elicitation ability. Although the functions of flagellins have been extensively studied in bacteria with a single flagellin-encoding gene, the function of multiple flagellin-encoding genes in a single bacterial species is largely unknown. Here, the model plant-growth-promoting bacterium Pseudomonas kilonensis F113 was used to decipher the divergent functions of duplicated flagellins.

Open-set recognition of breast cancer treatments.

Open-set recognition generalizes a classification task by classifying test samples as one of the known classes from training or "unknown." As novel cancer drug cocktails with improved treatment are continually discovered, classifying patients by treatments can naturally be formulated in terms of an open-set recognition problem. Drawbacks, due to modeling unknown samples during training, arise from straightforward implementations of prior work in healthcare open-set learning.

Prediction of left ventricular ejection fraction changes in heart failure patients using machine learning and electronic health records: a multi-site study.

Left ventricular ejection fraction (EF) is a key measure in the diagnosis and treatment of heart failure (HF) and many patients experience changes in EF overtime. Large-scale analysis of longitudinal changes in EF using electronic health records (EHRs) is limited. In a multi-site retrospective study using EHR data from three academic medical centers, we investigated longitudinal changes in EF measurements in patients diagnosed with HF.

Acute respiratory distress syndrome after SARS-CoV-2 infection on young adult population: International observational federated study based on electronic health records through the 4CE consortium.

Purpose: In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population.

Methods: A retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE).

Regional activity alterations in Parkinson's disease patients with anxiety disorders: A resting-state functional magnetic resonance imaging study.

Background: Previous studies have revealed alteration of functional connectivity (FC) in Parkinson's disease patients with anxiety (PD-A), but local brain activities associated with anxiety in Parkinson's disease (PD) patients remain to be elucidated. Regional homogeneity (ReHo) analysis was employed to investigate alterations of regional brain activities in PD-A patients.

Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 42 PD-A patients, 41 PD patients without anxiety (PD-NA), and 40 age-and gender-matched healthy control (HC) subjects.

Genetics of varicose veins reveals polygenic architecture and genetic overlap with arterial and venous disease.

Varicose veins represent a common cause of cardiovascular morbidity, with limited available medical therapies. Although varicose veins are heritable and epidemiologic studies have identified several candidate varicose vein risk factors, the molecular and genetic basis remains uncertain. Here we analyzed the contribution of common genetic variants to varicose veins using data from the Veterans Affairs Million Veteran Program and four other large biobanks.

Atorvastatin remodels lipid distribution between liver and adipose tissues through blocking lipoprotein efflux in fish.

The regulation of cholesterol metabolism in fish is still unclear. Statins play important roles in promoting cholesterol metabolism development in mammals. However, studies on the role of statins in cholesterol metabolism in fish are currently limited.

An in vitro nerve agent brain poisoning transwell model for convenient and accurate antidote evaluation.

Nerve agent (NA) can inhibit acetylcholinesterase (AChE) causing seriously injury at extremely low doses. However, the cruel reality is that the lack of effective cerebral antidotes for treatment of NA poisoning. There is an urgent requirement for the large-scale evaluation and screening of antidotes.

Network pharmacology and molecular docking analysis on molecular targets and mechanisms of Blume in the treatment of ischemic stroke.

Blume (GEB) is widely used to treat cardio-cerebrovascular disease in China and in traditional Chinese medicine it is considered to be a dispelling wind and dredging collateral. However, the mechanism and active components of the plant in treating ischemic stroke (IS) remain unclear. The present study aimed to identify the active components and mechanism of GEB in treating IS using network pharmacology and molecular docking technology.

Hospitalizations Associated With Mental Health Conditions Among Adolescents in the US and France During the COVID-19 Pandemic.

Importance: The COVID-19 pandemic has been associated with an increase in mental health diagnoses among adolescents, though the extent of the increase, particularly for severe cases requiring hospitalization, has not been well characterized. Large-scale federated informatics approaches provide the ability to efficiently and securely query health care data sets to assess and monitor hospitalization patterns for mental health conditions among adolescents.

Objective: To estimate changes in the proportion of hospitalizations associated with mental health conditions among adolescents following onset of the COVID-19 pandemic.

Preserving the woody plant tree of life in China under future climate and land-cover changes.

The tree of life (TOL) is severely threatened by climate and land-cover changes. Preserving the TOL is urgent, but has not been included in the post-2020 global biodiversity framework. Protected areas (PAs) are fundamental for biological conservation.

Characterizing variability of electronic health record-driven phenotype definitions.

Objective: The aim of this study was to analyze a publicly available sample of rule-based phenotype definitions to characterize and evaluate the variability of logical constructs used.

Materials And Methods: A sample of 33 preexisting phenotype definitions used in research that are represented using Fast Healthcare Interoperability Resources and Clinical Quality Language (CQL) was analyzed using automated analysis of the computable representation of the CQL libraries.

Results: Most of the phenotype definitions include narrative descriptions and flowcharts, while few provide pseudocode or executable artifacts.

[Effect of ethanol extract of Gastrodiae Rhizoma on mitochondrial dysfunction in cerebral ischemia-reperfusion injury].

This study observed the effects of ethanol extract of Gastrodiae Rhizoma(GE) on multiple aspects of mitochondrial dysfunction by investigating the mitochondria isolated from rat brains subjected to focal middle cerebral artery occlusion/reperfusion(MCAO/R). SD rats were randomly divided into a sham operation group(Sham), a model group(MCAO/R), low-and high-dose ethanol extract of GE groups(262.3 and 524.

Machine Learning for Lung Cancer Diagnosis, Treatment, and Prognosis.

The recent development of imaging and sequencing technologies enables systematic advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in effectively handling and fully utilizing the accumulation of such enormous amounts of data. Machine learning-based approaches play a critical role in integrating and analyzing these large and complex datasets, which have extensively characterized lung cancer through the use of different perspectives from these accrued data.

A comparative study of pretrained language models for long clinical text.

Objective: Clinical knowledge-enriched transformer models (eg, ClinicalBERT) have state-of-the-art results on clinical natural language processing (NLP) tasks. One of the core limitations of these transformer models is the substantial memory consumption due to their full self-attention mechanism, which leads to the performance degradation in long clinical texts. To overcome this, we propose to leverage long-sequence transformer models (eg, Longformer and BigBird), which extend the maximum input sequence length from 512 to 4096, to enhance the ability to model long-term dependencies in long clinical texts.

Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease.

Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease (AD). We present a network topology-based deep learning framework to identify disease-associated genes (NETTAG). We leverage non-coding GWAS loci effects on quantitative trait loci, enhancers and CpG islands, promoter regions, open chromatin, and promoter flanking regions under the protein-protein interactome.

Erratum: MUC3A promotes non-small cell lung cancer progression via activating the NFκB pathway and attenuates radiosensitivity.

[This corrects the article DOI: 10.7150/ijbs.59430.