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Alzheimer's disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/.

This data set includes the data for Experiment 1 and 2 of the study 'Speech Fine Structure Contains Critical Temporal Cues to Support Speech Segmentation'. The stimuli and related MATLAB scripts for processing the stimuli are also included.

Population structure on Aedes albopictus samples from all Connecticut samples (no temporal series) based on 15 microsatellite markers

Repository for simulations of passive diffusion through the nuclear pore complex, associated with the manuscript: Simple rules for passive diffusion through the nuclear pore complex. Timney B, Raveh B, Mironska R, Trivedi JM, Kim SJ, Russel D, Wente SR, Sali A, and Rout MP Journal of Cell Biology (2016) DOI: 10.1083/jcb.201601004

This upload is a supplementary dataset for the following preprint: N. Trebesch and E. Tajkhorshid. "Structure Reveals Homology in Elevator Transporters." bioRxiv. (2023). DOI: 10.1101/2023.06.14.544989. Please see the preprint for the methods, analysis, and discussion associated with this dataset.

The immortalized human ReNcell VM cell line represents a reproducible and easy-to-propagate cell culture system for studying the differentiation of neural progenitors. To better characterize the starting line and its subsequent differentiation, we assessed protein and phospho-protein levels and cell morphology over a 15-day period during which ReNcell progenitors differentiated into neurons, astrocytes and oligodendrocytes. Five of the resulting datasets measured protein levels or states of phosphorylation based on tandem-mass-tag (TMT) mass spectrometry and four datasets characterized cellular phenotypes using high-content microscopy. Proteomic analysis revealed reproducible changes in pathways responsible for cytoskeletal rearrangement, cell phase transitions, neuronal migration, glial differentiation, neurotrophic signalling and extracellular matrix regulation. Proteomic and imaging data revealed accelerated differentiation in cells treated with the poly-selective CDK and GSK3 inhibitor kenpaullone or the HMG-CoA reductase inhibitor mevastatin, both of which have previously been reported to promote neural differentiation. These data provide in-depth information on the ReNcell progenitor state and on neural differentiation in the presence and absence of drugs, setting the stage for functional studies.

Files and metadata associated with the EMDataBank/Unified Data Resource for 3DEM 2015/2016 Map Challenge hosted at challenges.emdatabank.org are deposited. All members of the Scientific Community--at all levels of experience--were invited to participate as Challengers, and/or as Assessors. Seven benchmark raw image datasets were selected for the challenge. Six are selected from recently described single particle structure determinations with image data collected as multi-frame movies; one is based on simulated (in silico) images. All of the raw image datasets are archived at pdbe.org/empiar. 27 Challengers created 66 single particle reconstructions from the targets, and then uploaded their results with associated details. 15 of the reconstructions were calculated using the SDSC Gordon supercomputer. This map challenge was one of two community-wide challenges sponsored by EMDataBank in 2015/2016 to critically evaluate 3DEM methods that are coming into use, with the ultimate goal of developing validation criteria associated with every 3DEM map and map-derived model. {"references": ["Henderson et al (2012) Outcome of the first electron microscopy validation task force meeting. doi:10.1016/j.str.2011.12.014", "Lawson et al (2016) EMDataBank unified data resource for 3DEM. doi:10.1093/nar/gkv1126", "Marabini et al (2016) The Electron Microscopy Exchange (EMX) Iniitiative doi:10.1016/j.jsb.2016.02.008"]} The 2015/2016 Map Challenge was supported by the US National Institutes of Health / National Institute for General Medical Sciences (NIH/NIGMS) Under Grant Number R01 GM079429 to Wah Chiu (PI). A Directors Award from the UCSD Supercomputer Center provided supercomputer access that was used in 15 of the 66 submitted entries.

The associated data are images of gels associated with the figures throughout the paper. The label of each of gel describes which figure/panel the gel is directly related too. All of the gels are uncropped and unlabeled, but gels that are replicates for the same experiment with proper and same labeling are located in the main body or supplemental of the manuscript. Therefore, please reference the name of the file to figure out what lanes to view as well as the manuscript for the labeling. Do not hesitate to contact Ryan Clarke with any questions. Thanks you!