Psychosocial determinants of oral health outcomes in young children.

Objective: To examine the social determinants of early childhood caries (ECC), one of the greatest public health risks affecting children, and examine alternative pathways of influence.

Methods: A physically healthy, socio-demographically high-risk sample of initially caries-free children, aged 1-4 years, was prospectively studied for 2 years. At 6-month intervals, assessments were made of caries presence from a standard dental exam; oral microbiology was assayed from saliva samples; oral hygiene behaviors and psychological and psychosocial risk exposure were derived from interviews and questionnaires.

A conserved role for ALG10/ALG10B and the -glycosylation pathway in the sleep-epilepsy axis.

Congenital disorders of glycosylation (CDG) comprise a class of inborn errors of metabolism resulting from pathogenic variants in genes coding for enzymes involved in the asparagine-linked glycosylation of proteins. Unexpectedly to date, no CDG has been described for , encoding the alpha-1,2-glucosyltransferase catalyzing the final step of lipid-linked oligosaccharide biosynthesis. Genome-wide association studies (GWAS) of human traits in the UK Biobank revealed significant SNP associations with short sleep duration, reduced napping frequency, later sleep timing and evening diurnal preference as well as cardiac traits at a genomic locus containing a pair of paralogous enzymes and .

Artificial intelligence in risk prediction and diagnosis of vertebral fractures.

With the increasing prevalence of vertebral fractures, accurate diagnosis and prognostication are essential. This study assesses the effectiveness of AI in diagnosing and predicting vertebral fractures through a systematic review and meta-analysis. A comprehensive search across major databases selected studies utilizing AI for vertebral fracture diagnosis or prognosis.

'QuickDASH' to find unique genes and biological processes associated with shoulder osteoarthritis: a prospective case-control study.

Objective: Osteoarthritis (OA) is a disease impacting the synovial joint complex, yet transcriptional changes specific to shoulder OA remain underexplored. This study aims to profile transcriptomic changes in periarticular tissues from patients undergoing shoulder replacement for OA. By correlating these profiles with QuickDASH scores-a validated measure of worsening shoulder function-this research seeks to understand the gene expression changes associated with clinical decline.