Drug Development.

Background: Transcutaneous stimulation of the auricular branch of the vagus nerve (tVNS) was administered to participants diagnosed with mild cognitive impairment (MCI) to improve word-list memory (primary outcome) and other cognitive skills.

Method: A randomized, double-blind, placebo-controlled crossover design was used for this trial. Participants with MCI (n = 59) were sorted into one of two sequences: Sham-tVNS or tVNS-Sham.

Combined endonasal, endo-orbital and transcranial craniofacial resection of invasive anterior skullbase sinonasal carcinoma: 2D endoscopic video.

Background: Sinonasal malignancies, in which squamous cell carcinomas are the most common are rare and difficult to treat given the location and anatomical structures involved. Sinonasal malignancies often present late due to non-specific and benign symptoms. Partial resections are often associated with poorer outcomes [1].

Evaluation of Generative Artificial Intelligence Models in Predicting Pediatric Emergency Severity Index Levels.

Objective: Evaluate the accuracy and reliability of various generative artificial intelligence (AI) models (ChatGPT-3.5, ChatGPT-4.0, T5, Llama-2, Mistral-Large, and Claude-3 Opus) in predicting Emergency Severity Index (ESI) levels for pediatric emergency department patients and assess the impact of medically oriented fine-tuning.

Mapping of high-resolution daily particulate matter (PM) concentration at the city level through a machine learning-based downscaling approach.

PM pollution is a major global concern, especially in Vietnam, due to its harmful effects on health and the environment. Monitoring local PM levels is crucial for assessing air quality. However, Vietnam's state-of-the-art (SOTA) dataset with a 3 km resolution needs to be revised to depict spatial variation in smaller regions accurately.

UniVar: A variant interpretation platform enhancing rare disease diagnosis through robust filtering and unified analysis of SNV, INDEL, CNV and SV.

Background: Interpreting the pathogenicity of genetic variants associated with rare diseases is a laborious and time-consuming endeavour. To streamline the diagnostic process and lighten the burden of variant interpretation, it is crucial to automate variant annotation and prioritization. Unfortunately, currently available variant interpretation tools lack a unified and comprehensive workflow that can collectively assess the clinical significance of these types of variants together: small nucleotide variants (SNVs), small insertions/deletions (INDELs), copy number variants (CNVs) and structural variants (SVs).