Search Constraints
Filtering by:
Language
English
Remove constraint Language: English
Discipline
Health Sciences
Remove constraint Discipline: Health Sciences
Number of results to display per page
View results as:
Search Results
-
- Creator:
- Bautista-Arredondo, Luis F., Muñoz-Rocha, T. Verenice, Figueroa, José L., Téllez-Rojo, Martha M., Torres-Olascoaga, Libni A., Cantoral, Alejandra, Arboleda-Merino, Laura C., Leung, Cindy, Peterson, Karen E., and Lamadrid-Figueroa, Héctor
- Description:
- Data was collected from participants of the Early Life Exposures in Mexico to ENvironmental Toxicants (ELEMENT) study, which consists of three sequentially-enrolled birth cohorts of pregnant women. Research protocols of this study were approved by the Institutional Review Board at University of Michigan and the Mexico National Institute of Public Health. We obtained informed consent from study participants prior to enrollment.
- Keyword:
- Food Insecurity, COVID-19 Pandemic, Mexico, Cohort
- Citation to related publication:
- Bautista-Arredondo LF, Verenice Muñoz-Rocha T, Figueroa JL, Téllez-Rojo MM, Torres-Olascoaga LA, Cantoral A, Arboleda-Merino L, Leung L, Peterson KE, and Lamadrid-Figueroa H. A surge in food insecurity during the COVID-19 pandemic in a cohort in Mexico City. 2022. Article in process of publication.
- Discipline:
- Health Sciences
-
- Creator:
- Dariya, Malyarenko, Tariq, Humera, Kushwaha, Aman, Mourad, Rami, Heist, Kevin, Chenevert, Thomas L, Ross, Brian D, Chen, Heang-Ping, and Hadjiiski, Lubomir
- Description:
- The 3D GRE MRI data for murine model of myelofbifrosis with expert segmentations of mouse tibia was used to train Attention UNET model to automate bone marrow segmentation for measurements of imaging biomarkers. This dataset consists of three archives: (1) containing the source MRI images in Meta-image-header (MHD) format with resulting segmentation labels by two experts and four UNET models with different training scenarios; (2) corresponding training models; and (3) deep-learning (DL)-based segmentation tools for application to future murine tibia MRI data. and The MHD images are an ITK compatible format that can be viewed in standard image viewer, like 3D Slicer. The image archive is structured with a directory tree that contains \"mouseID"\"scan-date"\"segmentaion-scenario"\. The "training model" archive containes DL-model labeled by the data subset, and "deployment" archive containes the DL-segmentation software.
- Keyword:
- deep-learning segmentation, preclinical MRI, murine tibia, and mouse model of myelofibrosis
- Citation to related publication:
- Kushwaha A, Mourad RF, Heist K, Tariq H, Chan HP, Ross BD, Chenevert TL, Malyarenko D, Hadjiiski LM. Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning. Tomography. 2023 Mar 7;9(2):589-602. doi: 10.3390/tomography9020048. PMID: 36961007; PMCID: PMC10037585. and https://github.com/dumichgh/MFJK1_Segmentation_MHDs
- Discipline:
- Health Sciences
-
- Creator:
- Malyarenko, Dariya, Chenevert, Thomas L, Heist, Kevin, Bonham, Christopher, and Ross, Brian
- Description:
- The imaging data was used to measure repeatability and temporal trends of quantitative imaging biomarkers of myelofibrosis in bone marrow based on apparent diffusion coefficient, fat fraction and magnetization transfer ratio. The dataset consists of time series of the MRI Meta-image-header (MHD) images of wild type and diseased mice combined by the imaging time point. The MHD images are an ITK compatible format that can be viewed in standard image viewer, like 3D Slicer. Each time point image archive is structured with a directory tree that contains ./././"mouseID"/"scan-date"/"acquisition type"/
- Keyword:
- murine tibia MRI, bone marrow imaging, apparent diffusion coefficient (ADC), proton density fat fraction (PDFF), magnetization transfer ratio (MTR), and pre-clinical model of myelofibrosis
- Citation to related publication:
- Ross BD, Malyarenko D, Heist K, Amouzandeh G, Jang Y, Bonham CA, Amirfazli C, Luker GD, Chenevert TL. Repeatability of Quantitative Magnetic Resonance Imaging Biomarkers in the Tibia Bone Marrow of a Murine Myelofibrosis Model. Tomography. 2023 Feb 28;9(2):552-566. doi: 10.3390/tomography9020045. PMID: 36961004; PMCID: PMC10037563.
- Discipline:
- Health Sciences
-
- Creator:
- Samuel, Sara M, Wilson, Diane L, and Fleming, Emily K
- Description:
- The International Committee of Medical Journal Editors (ICMJE) requires researchers to post individual participant data (IPD) plans for interventional clinical trials with registration in order to be eligible for publication in its member journals. This study looked at how researchers interpret the ICMJE requirements and the related prompts for information used by ClinicalTrials.gov. This data consists of the analyzed contents of the IPD plans that researchers at the University of Michigan (U-M) submitted with trial registrations for the first 27 months that the 2019 requirement was in effect.
- Keyword:
- research data sharing, research data policy, research data, clinical trials, ClinicalTrials.gov, individual participant data, IPD, data sharing plan, and compliance
- Citation to related publication:
- Samuel, S. M. & Wilson, D. L. & Fleming, E., (2023) “Evaluating individual participant data plans for ICMJE compliance: A case study at University of Michigan”, Journal of the Society for Clinical Data Management 3(4). doi: https://doi.org/10.47912/jscdm.257
- Discipline:
- Health Sciences, Social Sciences, and General Information Sources
-
- Creator:
- Lumeng, Julie C
- Description:
- Infant eating behavior is likely driven not only by hunger and satiety reflective of caloric need, but also by the reward value of food. The reward value of food can be understood in terms of wanting, liking, and salience. Little is understood about infant response to the reward value of food, or its predictors, particularly prenatally. This project sought to understand whether prenatal factors during pregnancy predict infant reward response to food, as measured by questionnaires in early infancy.
- Keyword:
- wanting, liking, salience, infancy, eating, growth, and prenatal
- Discipline:
- Health Sciences
-
- Creator:
- Lori, Jody R., Moyer, Cheryl, Lockhart, Nancy, Zielinski, Ruth E., Kukula, Vida, Apetorgbor, Veronica, Awini, Elizabeth, Badu-Gyan, Georgina, and Williams, John
- Description:
- GRAND is a five-year, cluster randomized controlled trial. The study is registered on ClinicalTrials.gov, [ID#: NCT04033003] and is a collaboration between University of Michigan in the United States and the Dodowa Health Research Center in Ghana. , The study setting for GRAND is four districts (Akwapim North, Yilo Krobo, Nsawam-Adoagyiri, and Lower Manya Krobo) within the Eastern Region of Ghana. Health facilities were selected based the number ANC registrants per month and average gestational age of women at registration in each facility., and Facilities were then matched based on facility type, district, and number of monthly ANC registrants. A cluster randomized controlled trial was conducted in 14 facilities in four districts of the Eastern Region of Ghana. Health facilities were randomized using a matched pairs design; each pair was similar in the number of deliveries and average gestational age of the women at enrollment in antenatal care. The locations of the facilities were far enough apart to avoid cross-group contamination. In each pair of facilities, one was randomly assigned to the intervention (G-ANC) and the other to the control (I-ANC). Recruitment began July 2019 and ended when enrollment targets were met. Data collection ended July 2023 when data collection was complete.
- Keyword:
- Antenatal care, Ghana, and Maternal health
- Citation to related publication:
- Lori, J., Kukula, V., Liu, L. et al. Improving health literacy through group antenatal care: results from a cluster randomized controlled trial in Ghana. BMC Pregnancy Childbirth 24, 37 (2024). https://doi.org/10.1186/s12884-023-06224-x
- Discipline:
- International Studies and Health Sciences
-
- Creator:
- Rana, Gurpreet K., Reynolds, Christopher W., Rha, Jennifer Y., Lenselink, Allison M., Asokumar, Dhanya, Zebib, Laura, Giacona, Francesca L. , Islam, Nowshin N., Kannikeswaran, Sanjana, Manuel, Kara, Cheung, Allison, Marzoughi, Maedeh , and Heisler, Michele
- Description:
- The search data supports a literature review project on "Innovative strategies and implementation science approaches for health delivery among migrants in humanitarian settings". The data included in the dataset are the complete search strategies (rtf file) and the exported results of all citations from all databases (ris file) after removal of duplicate citations.
- Keyword:
- humanitarian setting, migrant, forced displacement , health delivery, implementation science, and scoping review
- Discipline:
- Health Sciences
-
- Creator:
- Zielinski, Ruth E, Kukula, Vida, Apetorgbor, Veronica, Awini, Elizabeth, Moyer, Cheryl, Badu-Gyan, Georgina, Williams, John, Lockhart, Nancy, and Lori, Jody R
- Description:
- This is a process evaluation of the RCT, Group Antenatal Care and Delivery project (GRAND) to identify and document patient, provider, and system barriers and facilitators to program implementation. Using both quantitative and qualitative methods, potential and actual influences on the quality and conduct of the program's operations, implementation, and service delivery were identified. Only the seven (7) sites randomized to the Group ANC (G-ANC) intervention were included for collection of process evaluation data since the evaluation was of G-ANC implementation. Data were collected from August 2019 to November 2020 and included both quantitative and qualitative data sources.
- Keyword:
- Group Antenatal Care, Ghana, and Process Evaluation
- Citation to related publication:
- Zielinski R, Kukula V, Apetorgbor V, Awini E, Moyer C, Badu-Gyan G, et al. (2023) “With group antenatal care, pregnant women know they are not alone”: The process evaluation of a group antenatal care intervention in Ghana. PLoS ONE 18(11): e0291855. https://doi.org/10.1371/journal.pone.0291855
- Discipline:
- International Studies and Health Sciences
-
- Creator:
- Chen, Kevin S, Noureldein, Mohamed H, McGinley, Lisa M, Hayes, John M, Rigan, Diana M, Kwentus, Jaquelin F, Mason, Shayna N, Mendelson, Faye E, Savelieff, Masha G, and Feldman, Eva L
- Description:
- Therapeutic mechanisms of human neural stem cells (hNSCs) were studied in an Alzheimer's disease mouse model (5XFAD). hNSCs restored spatial memory abilities in 5XFAD animals; however, amyloid beta levels were unchanged. Spatial transcriptomics was used to probe mechanisms of hNSCs. Focusing on a subset of plaque-induced genes, gene normalization was seen particularly in microglia, confirmed by PROGENy and Cell Chat analyses. and The spatial transcriptomics data from this publication have been deposited in NCBI Gene Expression Omnibus (16) and are accessible through GEO Series accession number GSE209583 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE209583 and enter token gzglogqkvjqrhmt). Additional supporting data are available from the corresponding author upon reasonable request.
- Citation to related publication:
- Chen KS, Noureldein MH, McGinley LM, Hayes JM, Rigan DM, Kwentus JF, Mason SN, Mendelson FE, Savelieffd MG, Feldman EL. Human neural stem cells restore spatial memory in a transgenic Alzheimer's disease mouse model by an immunomodulating mechanism. bioRxiv [Preprint]. 2023 Nov 4:2023.11.01.565161. doi: 10.1101/2023.11.01.565161. PMID: 37961246; PMCID: PMC10635057.
- Discipline:
- Health Sciences
-
- Creator:
- Wallace, Dylan M, Benyamini, Miri, Nason-Tomaszewski, Samuel R, Costello, Joseph T, Cubillos, Luis H, Mender, Matthew J, Temmar, Hisham, Willsey, Matthew S, Patil, Parag P, Chestek, Cynthia A, and Zacksenhouse, Miriam
- Description:
- This is data from Wallace, Benyamini et al., 2023, Journal of Neural Engineering. There are two sets of data included: 1. Neural features and error labels used to train error classifiers for each day used in the study 2. Trial data from an example experiment day (Monkey N, Day 6), with runs for offline calibration, online brain control, error monitoring, and error correction. The purpose of this study was to investigate the use of error signals in motor cortex to improve brain-machine interface (BMI) performance for control of two finger groups. All data is contained in .mat files, which can be opened using MATLAB or the Python SciPy library.
- Keyword:
- Brain-machine interface (BMI), Error detection, and Neural recording
- Citation to related publication:
- Wallace, D. M., Benyamini, M., Nason-Tomaszewski, S. R., Costello, J. T., Cubillos, L. H., Mender, M. J., Temmar, H., Willsey, M. S., Patil, P. G., Chestek, C. A., & Zacksenhouse, M. (2023). Error detection and correction in intracortical brain–machine interfaces controlling two finger groups. Journal of Neural Engineering, 20(4), 046037. https://doi.org/10.1088/1741-2552/acef95
- Discipline:
- Engineering, Science, and Health Sciences