GET: a foundation model of transcription across human cell types.

Transcriptional regulation, involving the complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate in unseen cell types and conditions. Here, we introduce GET, an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types.

Statins as a risk factor for diabetic retinopathy: a Mendelian randomization and cross-sectional observational study.

Background: Diabetic retinopathy (DR) is the foremost cause of vision loss among the global working-age population, and statins are among the most frequently prescribed drugs for lipid management in patients with DR. The exact relationship between statins and DR has not been determined. This study sought to validate the causal association between statins usage and diabetic retinopathy.

Harnessing the potential of large language models in medical education: promise and pitfalls.

Objectives: To provide balanced consideration of the opportunities and challenges associated with integrating Large Language Models (LLMs) throughout the medical school continuum.

Process: Narrative review of published literature contextualized by current reports of LLM application in medical education.

Conclusions: LLMs like OpenAI's ChatGPT can potentially revolutionize traditional teaching methodologies.

Artificial intelligence education: An evidence-based medicine approach for consumers, translators, and developers.

Current and future healthcare professionals are generally not trained to cope with the proliferation of artificial intelligence (AI) technology in healthcare. To design a curriculum that caters to variable baseline knowledge and skills, clinicians may be conceptualized as "consumers", "translators", or "developers". The changes required of medical education because of AI innovation are linked to those brought about by evidence-based medicine (EBM).

Anti-VEGF combined with ocular corticosteroids therapy versus anti-VEGF monotherapy for diabetic macular edema focusing on drugs injection times and confounding factors of pseudophakic eyes: A systematic review and meta-analysis.

Purpose: To assess the effectiveness and safety of combining intravitreal endothelial growth factor inhibitor (anti-VEGF) and ocular corticosteroids for diabetic macular edema (DME).

Methods: Articles concentrating on the efficacy and safety of combining anti-VEGF and ocular corticosteroids therapy for DME versus anti-VEGF monotherapy was screened systematically. Meta-analysis was conducted on the basis of a protocol registered in the PROSPERO (CRD42023408338) and performed on the extracted continuous variables and dichotomous variables.

Pharmacological roles of lncRNAs in diabetic retinopathy with a focus on oxidative stress and inflammation.

Diabetic retinopathy (DR) is a complication caused by abnormal glucose metabolism, which affects the vision and quality of life of patients and severely impacts the society at large.DR has a complex pathogenic process. Evidence from multiple studies have shown that oxidative stress and inflammation play pivotal roles in DR.

Visual Reasoning: From State to Transformation.

Most existing visual reasoning tasks, such as CLEVR in VQA, ignore an important factor, i.e., transformation.

Effect of wheat straw pretreated with liquid fraction of digestate from different substrates on anaerobic digestion performance and microbial community characteristics.

The effects of liquid fraction of digestate (LFD) pretreatment on anaerobic digestion (AD) performance and microbial community characteristics were estimated. Prior to AD, LFD (LFD, LFD, and LFD) collected separately from three continuously stirred tank reactors (CSTRs) using swine manure (SM), food waste (FW), and wheat straw (WS) as the mono-substrate was applied to pretreat WS. The results showed that AD with LFD pretreatment resulted in biomethane yields of 240.