Retrospective observational study of the association of peak blood glucose during the second 24 hours of admission with hospital-acquired complications in non-critical care admissions to a tertiary referral teaching hospital.

Introduction: Stress hyperglycaemia at hospital presentation is associated with poorer outcomes. Less is known about the risk of poorer outcomes according to achieved glycaemia early in the admission.

Research Design/methods: This was a retrospective observational study of patients admitted to non-critical care wards.

Role of Mutation in the Development of Eleven Different Cancers.

: With the rise in prevalence of diagnostic genetic techniques like RNA sequencing and whole exome sequencing (WES), as well as biological treatment regiments for cancer therapy, several genes have been implicated in carcinogenesis. This review aims to update our understanding of the Neurofibromatosis 2 (NF2) gene and its role in the pathogenesis of various cancers. : A comprehensive search of five online databases yielded 43 studies that highlighted the effect of sporadic NF2 mutations on several cancers, including sporadic meningioma, ependymoma, schwannoma, mesothelioma, breast cancer, hepatocellular carcinoma, prostate cancer, glioblastoma, thyroid cancer, and melanoma.

Molecular logic for cellular specializations that initiate the auditory parallel processing pathways.

The cochlear nuclear complex (CN), the starting point for all central auditory processing, encompasses a suite of neuronal cell types highly specialized for neural coding of acoustic signals. However, the molecular logic governing these specializations remains unknown. By combining single-nucleus RNA sequencing and Patch-seq analysis, we reveal a set of transcriptionally distinct cell populations encompassing all previously observed types and discover multiple hitherto unknown subtypes with anatomical and physiological identity.

Assessing the feasibility and external validity of natural language processing-extracted data for advanced lung cancer patients.

Background: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with advanced lung cancer (aLC). We assessed the external validity of our NLP-extracted data by comparing our findings to those reported in the literature.