These data were produced from a study that assessed mitochondrial metabolic function by measuring two metabolites, l-carnitine and acetylcarnitine, to determine their effectiveness as candidate clinical biomarkers for age-related, drug-induced alterations in mitochondrial metabolism. To study age and medication-related changes in mitochondrial metabolism, we administered the FDA-approved mitochondriotropic drug, clofazimine (CFZ), or vehicle for to young and old mice. These findings are described in our manuscript: Clofazimine-Mediated, Age-Related Changes in Skeletal Muscle Mitochondrial Metabolites. Data reported was supported by funding from the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health (NIH) under award numbers R01GM127787 (GRR), R35GM136312 (KAS), P30AR069620 (K Jepsen), and T32GM140223 (L Isom).
These are datasets released from our manuscript "A Comparison of Lossless Compression Methods in Microscopy Data Storage Applications".
Included in this data release are: `noise16.tif`: a file containing background noise collected from a 1000-frame acquisition of a ORCA-Fusion camera; `noise8.tif`: a file containing the 16-bit data collective above converted into a 8-bit form; `brainbow.tif`: This is a mouse Brainbow image originally published and described in Roossien, et al. Bioinformatics 2019; `bead.tif`: This is a 3D image of 100nm Invitrogen TetraSpeck fluorescent microspheres imaged in a blue channel using a custom microscope; `fly.tif`: This is a 3D image of a fly Bitbow brain collected as described in Li, et al. Front. Neural Circuits 2021; and `neurite.tif`: This is a 3D image of DiD-labeled mouse V1 tissue, collected using a custom microscope.
Untargeted lipidomics (Data S1) and targeted metabolomics (Data S2) analysis from in vitro culture of a murine macrophage cell line expressing shRNA targeted to Cardiolipin synthase (CRLS1), referred to as CRLS1 knockdown (KD), or a paired non-target shRNA-expressing (NT-Control). CRLS1 KD and NT-Control macrophages were either directly analyzed (untargeted lipidomics) or stimulated with lipopolysaccharide for a variety of timepoints and then analyzed (targeted metabolomics). Datasets are available as .csv files.
Reynolds M.B. et al. (2023). Cardiolipin coordinates inflammatory metabolic reprogramming through regulation of Complex II disassembly and degradation. Science Advances, 9(5). DOI: 10.1126/sciadv.ade8701
The data and scripts are meant to show how burster dynamics determine response to a single biphasic stimulus. The files include data which show trends in the propensity of termination for different burster types and the MATLAB scripts used to generate this data. The MATLAB scripts also allow the user to generate their own data sets for alternative bursting paths and stimulus parameter combinations. Furthermore, they allow the user to visually examine the effects of single stimuli in the voltage timeseries and in state space. How the user can access these features of the script is described in the file "ReadMe.pdf."
The characterization of HFO networks through functional connectivity analysis and network centrality. Details of the code repository can be found in the README.txt file.
Ionizing radiation acoustic imaging (iRAI) allows online monitoring of radiation’s interactions with tissues during radiation therapy, providing real-time, adaptive feedback for cancer treatments.
Using the data set presented here, this study demonstrated iRAI can image the temporal dose accumulation of a radiaiton treatment plan. Clincial standard treatment plan with both rabbit and patient in vivo were first real-time volumetric visulized by iRAI.
This data set is the rawdata for our paper published in Nature Biotechnology entitled "Real-time, volumetric imaging of radiation dose delivery deep into the liver during cancer treatment ".
An individual participant data meta-analysis was conducted to examine 1) the degree to which bedtime, wake time, and chronotype correlate with posttraumatic stress disorder (PTSD) severity among individuals diagnosed with PTSD, 2) the standardized mean difference in bedtime, wake time, and chronotype for those with and without a PTSD diagnosis, and 3) moderators of these relationships. This deposit includes the full dataset used for data analyses.
No proprietary software is required to open any of these files.
Zalta, A. K., Vanderboll, K., Dent, A. L., Contreras, I. M., Malek, N., Lascano, X. N., Zellner, K. L., Grandhi, J., Araujo, P. J., Straka, K., Liang, C. Z., Czarny, J. E., Martinez, J., & Burgess, H. J. (2023). Sleep timing, chronotype, and posttraumatic stress disorder: An individual participant data meta-analysis. Psychiatry research, 321, 115061. Advance online publication. https://doi.org/10.1016/j.psychres.2023.115061
Data comparing the Simplified Endoscopic Mucosal Assessment for Crohn's Disease (SEMA-CD) from video recordings of colonoscopies to SEMA-CD scoring of their corresponding colonoscopy reports from pediatric patients with Crohn's disease.
The search data supports a literature review project on Psychological Functioning in Pediatric Patients with Single Ventricle Congenital Heart Disease. The data included are the reproducible search strategies (txt file) and the exported results of all citations from all databases (txt, ris, and.nbib files). Both the original search files and updated search files have been included in the deposit.
Research Overview: This dataset is clinical consent forms, collected as part of Dr. Elizabeth Umberfield's dissertation research of at the University of Michigan. 134 consent forms are used in the analysis, 102 of which are shared here (not all are shared due to data protection agreements with participating sites). The research aimed to enable representation of clinical consent forms and their permissions within the Informed Consent Ontology. These efforts were supported by the Rackham Graduate Student Research Grant, and Dr. Umberfield's doctoral training was supported by the Robert Wood Johnson Foundation Future of Nursing Scholars Program.
Umberfield, E., Jiang, Y., Fenton, S., Stansbury, C., Ford, K., Crist, K., Kardia, S., Thomer, A., & Harris, M. R. (In Press). Lessons Learned for Identifying and Annotating Permissions in Clinical Consents. Applied Clinical Informatics. and Umberfield, E., Stansbury, C., Ford, K., Jiang, Y., Kardia, S. L. R., Thomer, A., & Harris, M. R. (Under Review). Evaluating and Extending the Informed Consent Ontology for Representing Permissions from the Clinical Domain.
