Nucleosomal asymmetry shapes histone mark binding and promotes poising at bivalent domains.

Promoters of developmental genes in embryonic stem cells (ESCs) are marked by histone H3 lysine 4 trimethylation (H3K4me3) and H3K27me3 in an asymmetric nucleosomal conformation, with each sister histone H3 carrying only one of the two marks. These bivalent domains are thought to poise genes for timely activation upon differentiation. Here, we show that asymmetric bivalent nucleosomes recruit repressive H3K27me3 binders but fail to enrich activating H3K4me3 binders, thereby promoting a poised state.

Evaluating Large Language Models in extracting cognitive exam dates and scores.

Ensuring reliability of Large Language Models (LLMs) in clinical tasks is crucial. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting clinical information, focusing on cognitive tests like MMSE and CDR. Our data consisted of 135,307 clinical notes (Jan 12th, 2010 to May 24th, 2023) mentioning MMSE, CDR, or MoCA.

Health system-wide access to generative artificial intelligence: the New York University Langone Health experience.

Objectives: The study aimed to assess the usage and impact of a private and secure instance of a generative artificial intelligence (GenAI) application in a large academic health center. The goal was to understand how employees interact with this technology and the influence on their perception of skill and work performance.

Materials And Methods: New York University Langone Health (NYULH) established a secure, private, and managed Azure OpenAI service (GenAI Studio) and granted widespread access to employees.

Antibiotic stewardship bundle for uncomplicated gram-negative bacteremia at an academic health system: a quasi-experimental study.

Objective: To evaluate whether an antimicrobial stewardship bundle (ASB) can safely empower frontline providers in the treatment of gram-negative bloodstream infections (GN-BSI).

Intervention And Method: From March 2021 to February 2022, we implemented an ASB intervention for GN-BSI in the electronic medical record (EMR) to guide clinicians at the point of care to optimize their own antibiotic decision-making. We conducted a before-and-after quasi-experimental pre-bundle (preBG) and post-bundle (postBG) study evaluating a composite of in-hospital mortality, infection-related readmission, GN-BSI recurrence, and bundle-related outcomes.

Development and evaluation of an artificial intelligence-based workflow for the prioritization of patient portal messages.

Objectives: Accelerating demand for patient messaging has impacted the practice of many providers. Messages are not recommended for urgent medical issues, but some do require rapid attention. This presents an opportunity for artificial intelligence (AI) methods to prioritize review of messages.

The First Generative AI Prompt-A-Thon in Healthcare: A Novel Approach to Workforce Engagement with a Private Instance of ChatGPT.

Background: Healthcare crowdsourcing events (e.g. hackathons) facilitate interdisciplinary collaboration and encourage innovation.

Large Language Model-Based Responses to Patients' In-Basket Messages.

Importance: Virtual patient-physician communications have increased since 2020 and negatively impacted primary care physician (PCP) well-being. Generative artificial intelligence (GenAI) drafts of patient messages could potentially reduce health care professional (HCP) workload and improve communication quality, but only if the drafts are considered useful.

Objectives: To assess PCPs' perceptions of GenAI drafts and to examine linguistic characteristics associated with equity and perceived empathy.

Evaluation of GPT-4 ability to identify and generate patient instructions for actionable incidental radiology findings.

Objectives: To evaluate the proficiency of a HIPAA-compliant version of GPT-4 in identifying actionable, incidental findings from unstructured radiology reports of Emergency Department patients. To assess appropriateness of artificial intelligence (AI)-generated, patient-facing summaries of these findings.

Materials And Methods: Radiology reports extracted from the electronic health record of a large academic medical center were manually reviewed to identify non-emergent, incidental findings with high likelihood of requiring follow-up, further sub-stratified as "definitely actionable" (DA) or "possibly actionable-clinical correlation" (PA-CC).

Evaluating Large Language Models in Extracting Cognitive Exam Dates and Scores.

Importance: Large language models (LLMs) are crucial for medical tasks. Ensuring their reliability is vital to avoid false results. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting clinical information, focusing on cognitive tests like MMSE and CDR.

Impact of oral vancomycin treatment duration on rate of recurrence in patients requiring concurrent systemic antibiotics.

Background: There is a paucity of data guiding treatment duration of oral vancomycin for infection (CDI) in patients requiring concomitant systemic antibiotics.

Objectives: To evaluate prescribing practices of vancomycin for CDI in patients that required concurrent systemic antibiotics and to determine whether a prolonged duration of vancomycin (>14 days), compared to a standard duration (10-14 days), decreased CDI recurrence.

Methods: In this retrospective cohort study, we evaluated adult hospitalized patients with an initial episode of CDI who were treated with vancomycin and who received overlapping systemic antibiotics for >72 hours.

Chromatin remodeling of histone H3 variants by DDM1 underlies epigenetic inheritance of DNA methylation.

Nucleosomes block access to DNA methyltransferase, unless they are remodeled by DECREASE in DNA METHYLATION 1 (DDM1), a Snf2-like master regulator of epigenetic inheritance. We show that DDM1 promotes replacement of histone variant H3.3 by H3.

Thymic epithelial cell fate and potency in early organogenesis assessed by single cell transcriptional and functional analysis.

During development, cortical (c) and medullary (m) thymic epithelial cells (TEC) arise from the third pharyngeal pouch endoderm. Current models suggest that within the thymic primordium most TEC exist in a bipotent/common thymic epithelial progenitor cell (TEPC) state able to generate both cTEC and mTEC, at least until embryonic day 12.5 (E12.

Chromatin remodeling of histone H3 variants underlies epigenetic inheritance of DNA methylation.

Epigenetic inheritance refers to the faithful replication of DNA methylation and histone modification independent of DNA sequence. Nucleosomes block access to DNA methyltransferases, unless they are remodeled by DECREASE IN DNA METHYLATION1 (DDM1 ), a Snf2-like master regulator of epigenetic inheritance. We show that DDM1 activity results in replacement of the transcriptional histone variant H3.

Improving Information Extraction from Pathology Reports using Named Entity Recognition.

Pathology reports are considered the gold standard in medical research due to their comprehensive and accurate diagnostic information. Natural language processing (NLP) techniques have been developed to automate information extraction from pathology reports. However, existing studies suffer from two significant limitations.

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial.

Background: We previously developed and validated a predictive model to help clinicians identify hospitalized adults with coronavirus disease 2019 (COVID-19) who may be ready for discharge given their low risk of adverse events. Whether this algorithm can prompt more timely discharge for stable patients in practice is unknown.

Objectives: The aim of the study is to estimate the effect of displaying risk scores on length of stay (LOS).

Quantification of Sepsis Model Alerts in 24 US Hospitals Before and During the COVID-19 Pandemic.

This descriptive study evaluates the association between nursing reports of sepsis overalerting and alert volume by quantifying the number of alerts generated by the Epic Sepsis Model at 24 US hospitals before and during the COVID-19 pandemic.

Influence of dietary Chlorella vulgaris and carbohydrate-active enzymes on growth performance, meat quality and lipid composition of broiler chickens.

Herein, we investigated the effect of Chlorella vulgaris as ingredient (10% of incorporation) in broiler diets, supplemented or not with 2 formulations of Carbohydrate-Active enZymes (CAZymes; Rovabio Excel AP and a mixture of recombinant CAZymes, composed by an exo-β-glucosaminidase, an alginate lyase, a peptidoglycan N-acetylmuramic acid deacetylase and a lysozyme), on growth performance, meat quality, fatty acid composition, oxidative stability, and sensory traits. One hundred twenty 1-day-old Ross 308 male birds were randomly assigned to one of the 4 experimental diets (n = 30): corn-soybean meal-basal diet (control), basal diet with 10% C. vulgaris (CV), CV supplemented with 0.

A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients.

The COVID-19 pandemic has challenged front-line clinical decision-making, leading to numerous published prognostic tools. However, few models have been prospectively validated and none report implementation in practice. Here, we use 3345 retrospective and 474 prospective hospitalizations to develop and validate a parsimonious model to identify patients with favorable outcomes within 96 h of a prediction, based on real-time lab values, vital signs, and oxygen support variables.

Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites.

Background: Automated systems that use machine learning to estimate a patient's risk of death are being developed to influence care. There remains sparse transparent reporting of model generalizability in different subpopulations especially for implemented systems.

Methods: A prognostic study included adult admissions at a multi-site, academic medical center between 2015 and 2017.

Estimating real-world performance of a predictive model: a case-study in predicting mortality.

Objective: One primary consideration when developing predictive models is downstream effects on future model performance. We conduct experiments to quantify the effects of experimental design choices, namely cohort selection and internal validation methods, on (estimated) real-world model performance.

Materials And Methods: Four years of hospitalizations are used to develop a 1-year mortality prediction model (composite of death or initiation of hospice care).

Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research.

Conventional text classification models make a bag-of-words assumption reducing text into word occurrence counts per document. Recent algorithms such as word2vec are capable of learning semantic meaning and similarity between words in an entirely unsupervised manner using a contextual window and doing so much faster than previous methods. Each word is projected into vector space such that similar meaning words such as "strong" and "powerful" are projected into the same general Euclidean space.

Biomedical engineer's guide to the clinical aspects of intensive care mechanical ventilation.

Background: Mechanical ventilation is an essential therapy to support critically ill respiratory failure patients. Current standards of care consist of generalised approaches, such as the use of positive end expiratory pressure to inspired oxygen fraction (PEEP-FiO) tables, which fail to account for the inter- and intra-patient variability between and within patients. The benefits of higher or lower tidal volume, PEEP, and other settings are highly debated and no consensus has been reached.

Diagnostic accuracy of Magnetic Resonance Imaging using liver tissue specific contrast agents and contrast enhanced Multi Detector Computed Tomography: A systematic review of diagnostic test in Hepatocellular Carcinoma (HCC).

Objectives: The aim of this systematic review is to investigate diagnostic accuracy of Magnetic Resonance Imaging (MRI) scans using liver specific tissue contrast media over contrast enhanced Multi Detector CT (MDCT) in diagnoses of Hepatocellular Carcinoma (HCC) in patients with chronic liver disease.

Key Findings: A total of 8 diagnostic studies were identified and generally considered of high quality. The studies reported sufficient evidence on sensitivity and specificity, which was synthesised and summarised providing an overview of the evidence.