This collection was produced as part of the project, “A ‘Big Data’ Approach to Understanding Neighborhood Effects in Chronic Illness Disparities.” The Investigators for the project are Tiffany Veinot, Veronica Berrocal, Phillipa Clarke, Robert Goodspeed, Daniel Romero, and VG Vinod Vydiswaran from the University of Michigan. The study took place from 2015-2016, with funding from the University of Michigan’s Social Sciences Annual Institute, MCubed, and the Sloan and Moore Foundations.
Contact: Tiffany Veinot, MLS, PhD
Office: 3443 North Quad
Phone: 734/615-8281
Email: tveinot@umich.edu
MCubed project page:
https://mcubed.umich.edu/projects/%E2%80%9Cbig-data%E2%80%9D-approach-understanding-neighborhood-effects-chronic-illness-disparities
Appendix1: Differential expression data for zebrafish regeneration and mouse degeneration models.
Appendix2: Gene ontology data for zebrafish regeneration and mouse degeneration models.
Appendix3: Pathway data for zebrafish regeneration and mouse degeneration models.
Appendix4: Differential expression data and genes within linked peaks for mi2004 mutants.
Appendix5: Gene ontology data for mi2004 mutants.
Appendix6: Pathway data for mi2004 mutants.
Appendix7: Linkage plots for mi2004 mutants.
Appendix8: Inverse PCR and genome-walking data.
Sifuentes, C. J. (2016). Regulation of Müller glial stem cell properties: Insights from a zebrafish model (Doctoral dissertation). Retrieved from http://hdl.handle.net/2027.42/135939
In a broad sense, this project explores morphological and phonological processing in English monolinguals and two bilingual populations, Chinese-English and Spanish-English, using a battery of standardized and self-developed behavioral measures, as well as fNIRS neuroimaging. (T1=NEW PARTICIPANTES -TESTED BEHAVIORAL AND fNIRS-, T2= RETURNING PARTICIPANTS -JUST TESTED WITH BEHAVIORAL ASSESSMENTS)
The outer epithelial layer of zebrafish retinae contains a crystalline array of cone photoreceptors, called the cone mosaic. As this mosaic grows by mitotic addition of new photoreceptors at the rim of the hemispheric retina, topological defects, called “Y-Junctions”, form to maintain approximately constant cell spacing. The generation of topological defects due to growth on a curved surface is a distinct feature of the cone mosaic not seen in other well-studied biological patterns like the R8 photoreceptor array in the _ Drosophila compound eye. Since defects can provide insight into cell-cell interactions responsible for pattern formation, here we characterize the arrangement of cones in individual Y-Junction cores (see Set of images for Figures 1 and 2 and 6 and Supplementary Figure 7) as well as the spatial distribution of Y-junctions across entire retinae (see Dataset for analyzing spatial distribution of Y-junctions in flat-mounted retinae). We find that for individual Y-junctions, the distribution of cones near the core corresponds closely to structures observed in physical crystals (see Set of images for Figures 1 and 2 and 6 and Supplementary Figure 7). In addition, Y-Junctions are organized into lines, called grain boundaries, from the retinal center to the periphery (see Dataset for analyzing spatial distribution of Y-junctions in flat-mounted retinae and Dataset for measuring tendency of Y-junctions to line up into grain boundaries during incorporation into retinae). In physical crystals, regardless of the initial distribution of defects, defects can coalesce into grain boundaries via the mobility of individual particles. By imaging in live fish, we demonstrate that grain boundaries in the cone mosaic instead appear during initial mosaic formation, without requiring defect motion (see Dataset for measuring tendency of Y-junctions to line up into grain boundaries during incorporation into retinae and Dataset for analyzing Y-junction motion in live fish retinae). Motivated by this observation, we show that a computational model of repulsive cell-cell interactions generates a mosaic with grain boundaries (see Code and example simulations of phase-field crystal model (for cone mosaic formation)). In contrast to paradigmatic models of fate specification in mostly motionless cell packings (see Code and accompanying input data for simulating lateral inhibition on motionless cell packing), this finding emphasizes the role of cell motion, guided by cell-cell interactions during differentiation, in forming biological crystals. Such a route to the formation of regular patterns may be especially valuable in situations, like growth on a curved surface, where the resulting long-ranged, elastic, effective interactions between defects can help to group them into grain boundaries.
This collection represents various raw data and analysis of cores extracted during the January 2009 mission of the research vessel Sproul in the Santa Barbara Basin., Cores included: box core SPR0901-04BC, box core SPR0901-unnamed, and Kasten core SPR0901-03KC. Core photos, physical properties and magnetic susceptibility from the multisensor track (MST), and the scanning X-ray fluorescence (XRF) data are included in the collection., and Cruise DOI: 10.7284/901089
This research is funded by NSF-OCE 0752093.
This collection represents various raw data and analysis of cores extracted during the November 2008 mission of R/V Melville in the Santa Barbara Basin., The core included is the jumbo piston core MV0811-14JC. Core photos, physical properties and magnetic susceptibility from the multisensor track (MST), and the scanning X-ray fluorescence (XRF) data are included in the collection., and Cruise DOI: 10.7284/903459
The research is funded by NSF OCE-1304327.
This Collection is a compilation of data measured in the TCC engine at the University of Michigan, Department of Mechanical Engineering, Quantitative Laser Diagnostics Laboratory. The posted Work Deposits are never changed. However, this collection will be expanded with additional Work Deposits as new experimental data become available. The intent of the collection is to provide a comprehensive experimental data set from the TCC-III engine, for fundamental discovery research on in-cylinder flow and spark-ignited combustion. Also, to enable in-depth support for CFD development and validation. The collection includes data files of in-cylinder flowvelocity and flame imaging, as well as engine and system geometry needed to set up 1-D and CFD simulations. and README for TCCIII_Collection: https://umich.box.com/v/Collection-README-rev20180202