Washington University School of Medicine in St. Louis Showcase

The Knight Alzheimer Disease Research Center (ADRC) Data Freeze Ending 2025-09-30 is a longitudinal compilation of harmonized, processed research data collected from August 1, 1979 through September 30, 2025. This Data Freeze represents a fixed, versioned snapshot of curated datasets maintained by the ADRC and is intended to support reproducible secondary analyses under approved data use agreements. The Data Freeze includes data contributed by multiple ADRC Cores, including clinical assessments, cognitive testing, neuropsychological measures, neuroimaging data summaries, fluid biomarker data, neuropathology variables, and related research measures. Modules are compiled, quality controlled, and integrated according to ADRC Data Management and Sharing procedures prior to freeze finalization. This dataset reflects the full longitudinal structure of ADRC participant data available as of the official cutoff date (September 30, 2025). No data collected after this date are included in this release. Each subsequent Data Freeze constitutes a new versioned dataset with its own DOI. The purpose of this Data Freeze is to: 1. Provide a stable, citable dataset snapshot for approved secondary analyses 2. Support NIH Data Management and Sharing (DMS) policy compliance 3. Enable transparency, reproducibility, and longitudinal tracking of dataset versions This repository record provides metadata describing the Data Freeze and assigns a persistent DOI to this version. The underlying human subject data are stored in a secure Research Infrastructure Services (RIS) environment and are not publicly downloadable. Access to this dataset is controlled and requires submission of a formal data request through the Knight ADRC Request Center. Approved investigators must complete the appropriate Data Use Agreement prior to receiving access. Upon approval, access to the static dataset corresponding to this DOI will be granted through ADRC-managed secure infrastructure. Investigators using this Data Freeze must cite this dataset DOI in all resulting publications and acknowledge Knight ADRC funding as specified in the Data Use Agreement. This dataset was generated and curated by the Knight ADRC Data Management and Statistics Core in collaboration with contributing ADRC Cores. For information about submitting a data request, please visit: https://knightadrc.wustl.edu/professionals-clinicians/request-center-resources/submit-a-request/

Poststroke sleep disruption is a major determinant of recovery, yet how lesion location shapes hyper-acute and acute changes in sleep architecture remains poorly understood. To address this gap, we developed real-time photothrombosis (RT-PT) in a mouse model that enables spatially targeted focal ischemia with continuous EEG/EMG monitoring from the moment of stroke induction without the confounding effects of anesthesia. This dataset provides real-time electrophysiological recordings (EEG/EMG) from 18 mice undergoing focal ischemia via RT-PT. By delivering laser light through implanted optical fibers, we induced titratable ischemic strokes in the forelimb somatosensory cortex (SSC), intralaminar thalamus (IT), or CA1 region of the hippocampus (CA1) while animals remained awake and freely behaving. The dataset captures neural dynamics across the hyper-acute (0–24 hr) and acute (1–4 days) phases of stroke, comprising 18 raw EDF recordings and 270 manually corrected AccuSleep scoring files. The shared dataset is organized into a hierarchical structure indexed by target infarct region and Mouse ID. Root Directory: RT-PT Dataset (AccuSleep Files: Divided into target region subfolders (SSC, IT, and CA1). Each folder contains the raw, continuous 5-day EDF recording for each mouse, alongside 15 AccuSleep files (signal, label, and calibration) split into 24-hour intervals.; Codes: Contains 13 scripts and notebooks organized into three functional subfolders: Vigilance State\, \Fragmentation\, and \Spectra\, with each subfolder housing the respective code files for that analysis.; Analysis (Master Directory): Contains the consolidated "Sleep Macrostructure Analysis.csv" master spreadsheet, which aggregates all vigilance and fragmentation values from the individual AccuSleep labels. This directory also includes individual infarct images and composite PDF figures for histological validation.; GraphPad Prism Files: Contains four files that directly visualize the data from the master CSV, illustrating both raw and normalized longitudinal trends.; Additional Information: Supplemental materials, including the conference poster (.pptx and .pdf) detailing the RT-PT methodology and the guideline for AccuSleep scoring and EDF analysis with the codes provided. Additional information is in the Manuscript.docx file.

This dataset contains the raw data supporting main Figures 1-5 and Extended Data Figures 1-10 used in the manuscript "Intranasal boosting induces variant-specific responses in SARS-CoV-2 vaccine-imprinted mice" submitted to Nature Communications. The dataset includes antibody titers in the serum and bronchoalveolar lavage fluid of mice immunized with SARS-CoV-2 mRNA or chimpanzee adenoviral-vectored vaccines at various regimens. The dataset also includes pseudovirus neutralization results and flow cytometry analysis of vaccinated mice. Vaccinations were conducted in wild-type C57BL/6J mice or animals expressing human ACE2 (K18-hACE2 mice). Neutralization assays were performed using Vero cells overexpressing TMPRSS2.

The Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) study is a large, prospective, multi-center case-control study focused on identifying genetic and epidemiological risk factors for intracerebral hemorrhage (ICH), with an emphasis on enrolling participants from underrepresented racial and ethnic groups. The study was designed to address known disparities in ICH incidence, location, and outcomes among non-Hispanic white, Black, and Hispanic populations. The published dataset includes DICOM and NIFTI images from 2,942 subjects. Cases were identified through a rapid “hot-pursuit” enrollment strategy at clinical sites, while controls were selected through random digit dialing and matched to cases by age, sex, race/ethnicity, and geographic region. The imaging component of the dataset includes 7,988 CT sessions and 1,472 MR sessions, collected using standardized protocols across participating centers. This dataset provides a valuable resource for studying the radiographic features of ICH and supports analyses of hemorrhage patterns, severity, and outcomes in a racially and ethnically diverse population. This dataset is hosted on the Imaging Cerebrovascular Disease Knowledge Portal (iCDKP), which is supported in part by the National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), under Grant No. 1U24NS132940-01. Imaging data has been de-identified and refaced. Users are required to acknowledge both iCDKP and its federal funding source in any presentations or publications that utilize the dataset, following the citation guidelines provided on the dataset’s iCDKP page. To request access, users must register for an account and complete a Data Request License Agreement available via the iCDKP request portal: https://sites.wustl.edu/icdkp/request_data/.

This phase 3 double-blind, placebo-controlled randomized clinical trial, Starting a Testosterone and Exercise Program After Hip Injury (STEP-HI), was conducted at 8 US sites between December 2018 and August 2023. Participants were women aged 65 years or older with a recent surgical repair of a nonpathologic femur fracture, met objective criteria for mobility impairment, and were community dwelling after discharge from rehabilitation. During the first 14 months of the trial, participants were randomly assigned to 1 of 3 treatment groups: exercise plus topical testosterone gel, exercise plus placebo gel, or enhanced usual care. Statistical analysis, using a modified intention-to-treat approach, was performed from November 2023 to November 2024.

The Knight Alzheimer Disease Research Center (ADRC) Data Freeze Ending 2025-03-31 is a longitudinal compilation of harmonized, processed research data collected from August 1, 1979 through March 31, 2025. This Data Freeze represents a fixed, versioned snapshot of curated datasets maintained by the ADRC and is intended to support reproducible secondary analyses under approved data use agreements. The Data Freeze includes data contributed by multiple ADRC Cores, including clinical assessments, cognitive testing, neuropsychological measures, neuroimaging data summaries, fluid biomarker data, neuropathology variables, and related research measures. Modules are compiled, quality controlled, and integrated according to ADRC Data Management and Sharing procedures prior to freeze finalization. This dataset reflects the full longitudinal structure of ADRC participant data available as of the official cutoff date (March 31, 2025). No data collected after this date are included in this release. Each subsequent Data Freeze constitutes a new versioned dataset with its own DOI. The purpose of this Data Freeze is to: 1. Provide a stable, citable dataset snapshot for approved secondary analyses 2. Support NIH Data Management and Sharing (DMS) policy compliance 3. Enable transparency, reproducibility, and longitudinal tracking of dataset versions This repository record provides metadata describing the Data Freeze and assigns a persistent DOI to this version. The underlying human subject data are stored in a secure Research Infrastructure Services (RIS) environment and are not publicly downloadable. Access to this dataset is controlled and requires submission of a formal data request through the Knight ADRC Request Center. Approved investigators must complete the appropriate Data Use Agreement prior to receiving access. Upon approval, access to the static dataset corresponding to this DOI will be granted through ADRC-managed secure infrastructure. Investigators using this Data Freeze must cite this dataset DOI in all resulting publications and acknowledge Knight ADRC funding as specified in the Data Use Agreement. This dataset was generated and curated by the Knight ADRC Data Management and Statistics Core in collaboration with contributing ADRC Cores. For information about submitting a data request, please visit: https://knightadrc.wustl.edu/professionals-clinicians/request-center-resources/submit-a-request/

Using qPCR and targeted LC–MS/MS, we profiled S1P metabolic enzymes, receptors, and metabolites in human gestational tissues across pregnancy. These findings reveal tissue-specific regulation of S1P metabolism and signaling in human gestational tissues, suggesting a therapeutic role of S1P in modulating myometrial contractility. The collection of this data was conducted with the approval of the Washington University in St. Louis Institutional Review Board (ID# 202205099).

Trust can be defined as “a willingness to be vulnerable to another for a given set of tasks” and thus, trust and public health are inextricably linked. State actors are key participants in population health, organizing, among other things, mandates and guidelines that target health behaviors and encourage the uptake of medicines, screenings, diagnostics, and control of health conditions. Effective implementation of these crucial, government-sponsored health efforts is conditional on the public’s belief that the state is trustworthy and has one's best interest in mind – positioning trust in government as a central determinant of public health. Trusting relationships between patients, health systems, and health care providers are also essential, as high-quality, safe care and adherence with healthcare professionals’ recommendations heavily depend upon trust. In many countries, trust in government and health care providers are inseparable, as governments are the primary providers of healthcare. Despite these critical relationships, existing studies that link trust and public health outcomes often focus on contemporaneous factors, many of which are endogenous to public health outcomes (e.g., support for the incumbent political party). For example, Sopory and colleagues reported a comprehensive examination of the phenomenon of trust during public health emergency events among 68 studies from 28 countries that included individuals who were directly affected by a public health emergency. Importantly, no studies from South America or Africa were included. The shortage of research on the sociostructural, historical, economic, and political sources of low trust limits our understanding of how trust deficits might be remedied so as to improve population health. Understanding why trust is low as well as how to repair trust are thus of critical importance.

This dataset contains deidentified information from 33 adolescent girls with (n=21) and without (n=12) type 1 diabetes from 12 to 18 years of age. Parameters in the dataset include general demographics and fracture history, general health information, body composition bone mineral density by DXA, bone microarchitecture and strength by HR-pQCT, blood labs, circulating bone turnover biomarkers, and presence of peripheral neuropathy based on the Michigan Neuropathy Screening Instrument. Full details can be found in the associated files. The collection of this data was conducted with the approval of the Washington University in St. Louis Institutional Review Board (ID# 201908120). Participants provided informed consent for the sharing of de-identified data.