The association of cholesterol levels with memory and memory change over a 14-year period in a US national cohort.

Introduction: The impact of cholesterol on late-life cognition remains controversial. We investigated the association of high-density lipoprotein cholesterol (HDL-C) and non-HDL-C with memory in a nationally representative cohort.

Methods: Health and Retirement Study (HRS) participants ( = 13,258) aged 50+ (mean age: 67.

Data-driven discovery of cell-type-directed network-correcting combination therapy for Alzheimer's disease.

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by heterogeneous molecular changes across diverse cell types, posing significant challenges for treatment development. To address this, we introduced a cell-type-specific, multi-target drug discovery strategy grounded in human data and real-world evidence. This approach integrates single-cell transcriptomics, drug perturbation databases, and clinical records.

Insights into the Chemical Exposome during Pregnancy: A Non-Targeted Analysis of Preterm and Term Births.

Human-made chemicals are ubiquitous, leading to chronic exposure to complex mixtures of potentially harmful substances. We investigated chemical exposures in pregnant women in New York City by applying a non-targeted analysis (NTA) workflow to 95 paired prenatal urine and serum samples (35 pairs of preterm birth) collected as part of the New York University Children's Health and Environment Study. We analyzed all samples using liquid chromatography coupled with Orbitrap high-resolution mass spectrometry in both positive and negative electrospray ionization modes, employing full scan and data-dependent MS/MS fragmentation scans.

A positive ReceptivaDx result for BCL6 does not correlate with abnormal ERA results or decreased expression of receptivity-associated markers: two sides of the endometrial receptivity coin in fertility evaluation and treatment.

Objective: To investigate if a positive result on ReceptivaDx for evaluation of B-cell lymphoma 6 (BCL6), a proposed marker of progesterone resistance associated with impaired uterine receptivity, correlates with a suboptimal profile of receptivity-associated markers in the window of implantation using the endometrial receptivity array and single-nucleus transcriptomic analysis.

Design: Retrospective clinical cohort study; pilot study of single-nucleus RNA sequencing of prospectively collected window of implantation endometrium undergoing ReceptivaDx BCL6 evaluation.

Setting: Academic center.

VMAP: Vaginal Microbiome Atlas during Pregnancy.

Objectives: To enable interactive visualization of the vaginal microbiome across the pregnancy and facilitate discovery of novel insights and generation of new hypotheses.

Material And Methods: Vaginal Microbiome Atlas during Pregnancy (VMAP) was created with R shiny to generate visualizations of structured vaginal microbiome data from multiple studies.

Results: VMAP (http://vmapapp.

Seeing an apocalyptic post-antibiotic future lowers antibiotics expectations and requests.

Background: Antibiotic resistance is an ongoing pandemic which represents a global public health threat. To encourage the judicious use of antibiotics, public health discourse and campaigns often engage in threat-based messaging depicting an apocalyptic post-antibiotic future. We studied the effectiveness of the strategy because of mixed evidence for its success, and because it is unclear how experiencing the COVID-19 pandemic might have influenced it.

Harnessing EHR data for health research.

With the increasing availability of rich, longitudinal, real-world clinical data recorded in electronic health records (EHRs) for millions of patients, there is a growing interest in leveraging these records to improve the understanding of human health and disease and translate these insights into clinical applications. However, there is also a need to consider the limitations of these data due to various biases and to understand the impact of missing information. Recognizing and addressing these limitations can inform the design and interpretation of EHR-based informatics studies that avoid confusing or incorrect conclusions, particularly when applied to population or precision medicine.

Vaccination invitations sent by warm and competent medical professionals disclosing risks and benefits increase trust and booking intention and reduce inequalities between ethnic groups.

Objective: We aim to identify vaccination invitations that foster trust and improve vaccination uptake overall, especially among ethnic minority groups who are more at risk from coronavirus disease (COVID-19) and less likely to be vaccinated.

Method: In a preregistered 4 × 4 mixed-design experiment, we manipulated how much risk-benefit information the message included within-subjects and the message source between-subjects ( = 4,038 U.K.

Lymphatic Patterns in the Superficial Circumflex Iliac Artery Perforator Flap.

Background:  Lymphedema is a chronic condition, characterized by fluid buildup and tissue swelling and is caused by impairment of the lymphatic system. The lymph interpositional flap transfer technique, in which lymph flow is restored with a flap that includes subdermal lymphatic channels, is an option for surgical reconstruction. The superficial circumflex iliac artery perforator (SCIP) flap can be used for this purpose.

Alzheimer's disease as a women's health challenge: a call for action on integrative precision medicine approaches.

Alzheimer's Disease (AD) is marked by pronounced sex differences in pathophysiology and progression. However, the field has yet to fully recognize AD as a women's health issue, delaying the development of targeted preventative strategies and treatments. This perspective explores the elements impacting AD in women, identifying sex specificity in risk factors, highlighting new diagnostic approaches with electronic health records, and reviewing key molecular studies to underscore the need for integrative precision medicine approaches.

Data-driven insights can transform women's reproductive health.

This perspective explores the transformative potential of data-driven insights to understand and address women's reproductive health conditions. Historically, clinical studies often excluded women, hindering comprehensive research into conditions such as adverse pregnancy outcomes and endometriosis. Recent advances in technology (e.

Exposure to autoimmune disorders increases Alzheimer's disease risk in a multi-site electronic health record analysis.

Molecular studies of Alzheimer's disease (AD) implicate potential links between autoimmunity and AD, but the underlying clinical relationships between these conditions remain poorly understood. Electronic health records (EHRs) provide an opportunity to determine the clinical risk relationship between autoimmune disorders and AD and understand whether specific disorders and disorder subtypes affect AD risk at the phenotypic level in human populations. We evaluated relationships between 26 autoimmune disorders and AD across retrospective observational case-control and cohort study designs in the EHR systems at UCSF and Stanford.

Making inroads to precision medicine for the treatment of autoimmune diseases: Harnessing genomic studies to better diagnose and treat complex disorders.

Precision Medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle. Autoimmune diseases are those in which the body's natural defense system loses discriminating power between its own cells and foreign cells, causing the body to mistakenly attack healthy tissues. These conditions are very heterogeneous in their presentation and therefore difficult to diagnose and treat.

Identifying therapeutic candidates for endometriosis through a transcriptomics-based drug repositioning approach.

Existing medical treatments for endometriosis-related pain are often ineffective, underscoring the need for new therapeutic strategies. In this study, we applied a computational drug repurposing pipeline to stratified and unstratified disease signatures based on endometrial gene expression data to identify potential therapeutics from existing drugs, based on expression reversal. Of 3,131 unique genes differentially expressed by at least one of six endometriosis signatures, only 308 (9.

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights.

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.

Gene expression meta-analysis reveals aging and cellular senescence signatures in scleroderma-associated interstitial lung disease.

Aging and cellular senescence are increasingly recognized as key contributors to pulmonary fibrosis. However, our understanding in the context of scleroderma-associated interstitial lung disease (SSc-ILD) is limited. To investigate, we leveraged previously established lung aging- and cell-specific senescence signatures to determine their presence and potential relevance to SSc-ILD.

Should we stop referring to the pandemic of antimicrobial resistance as silent?

Background: Referring to the ongoing antimicrobial resistance crisis as a 'silent' pandemic has gained popularity, but there are mixed views on whether such a phrase should be used in public health communication. Some researchers have argued that using the term 'silent pandemic' may lower the perceived threat and hinder mobilization efforts to tackle the problem.

Objectives: I investigated the impact of the phrase 'silent pandemic' on perceived threat levels and mobilization intentions.

When intuitive Bayesians need to be good readers: The problem-wording effect on Bayesian reasoning.

Are humans intuitive Bayesians? It depends. People seem to be Bayesians when updating probabilities from experience but not when acquiring probabilities from descriptions (i.e.

Miscarriage risk assessment: a bioinformatic approach to identifying candidate lethal genes and variants.

Purpose: Miscarriage, often resulting from a variety of genetic factors, is a common pregnancy outcome. Preconception genetic carrier screening (PGCS) identifies at-risk partners for newborn genetic disorders; however, PGCS panels currently lack miscarriage-related genes. In this study, we evaluated the potential impact of both known and candidate genes on prenatal lethality and the effectiveness of PGCS in diverse populations.

Discovery of sparse, reliable omic biomarkers with Stabl.

Adoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facilitate this process, we introduce Stabl, a general machine learning method that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling.