Multiomics Blood-Based Biomarkers Predict Alzheimer's Predementia with High Specificity in a Multicentric Cohort Study.

Background: The primary criteria for diagnosing mild cognitive impairment (MCI) due to Alzheimer's Disease (AD) or probable mild AD dementia rely partly on cognitive assessments and the presence of amyloid plaques. Although these criteria exhibit high sensitivity in predicting AD among cognitively impaired patients, their specificity remains limited. Notably, up to 25% of non-demented patients with amyloid plaques may be misdiagnosed with MCI due to AD, when in fact they suffer from a different brain disorder.

Notch activation shifts the fate decision of senescent progenitors toward myofibrogenesis in human adipose tissue.

Senescence is a key event in the impairment of adipose tissue (AT) function with obesity and aging but the underlying molecular and cellular players remain to be fully defined, particularly with respect to the human AT progenitors. We have found distinct profiles of senescent progenitors based on AT location between stroma from visceral versus subcutaneous AT. In addition to flow cytometry, we characterized the location differences with transcriptomic and proteomic approaches, uncovering the genes and developmental pathways that are underlying replicative senescence.

Ramadan and gestational diabetes: maternal and neonatal outcomes.

Aims: The impact of Ramadan exposure to Gestational Diabetes Mellitus (GDM) pregnancies is not known. We therefore aimed to assess the association of Ramadan with maternal and neonatal outcomes among pregnant women with GDM.

Methods: Retrospective cohort study of 345 Muslim women with singleton pregnancies who attended a major Sydney teaching hospital during the period 1989-2010, was undertaken.

COVID-19 Medical Vulnerability Indicators: A Predictive, Local Data Model for Equity in Public Health Decision Making.

This article reports the outcome of a project to develop and assess a predictive model of vulnerability indicators for COVID-19 infection in Los Angeles County. Multiple data sources were used to construct four indicators for zip code tabulation areas: (1) pre-existing health condition, (2) barriers to accessing health care, (3) built environment risk, and (4) the CDC's social vulnerability. The assessment of the indicators finds that the most vulnerable neighborhoods are characterized by significant clustering of racial minorities.