Browse the latest research summaries in the field of bioinformatics for spinal cord injury patients and caregivers.
Showing 281-290 of 296 results
Curr Protoc Essent Lab Tech, 2013 • January 1, 2013
Quantification of immunohistochemistry (IHC) and immunofluorescence (IF) using image intensity depends on a number of variables. These variables add a subjective complexity in keeping a standard withi...
KEY FINDING: FFT allows for an objective quantification of photomicrographs based on morphology, which reduces the subjectivity associated with pixel-intensity methods.
Frontiers in Bioengineering and Biotechnology, 2022 • December 5, 2022
The study aimed to explore a new microRNA (miRNA) which can bind to combining engineered exosomes for treatment of older OS patients. MiR-449a is down-regulated in osteosarcoma and suppresses cell pro...
KEY FINDING: MiR-449a is down-regulated in osteosarcoma and suppresses cell proliferation by targeting CCNB1.
Journal of Orthopaedic Surgery and Research, 2016 • September 5, 2016
This study aimed to identify key molecular pathways involved in spinal cord injury (SCI) by analyzing gene expression profiles in rats at different time points after injury. The analysis revealed 416 ...
KEY FINDING: A total of 416 genes showed significant differential expression at all time points after SCI, suggesting their consistent involvement in the injury response.
J Cell Physiol, 2015 • July 1, 2015
This study investigates the migration of Schwann cells in electric fields (EFs), finding that they migrate towards the anode, with increased directedness and displacement at higher EF strengths. RNA s...
KEY FINDING: Schwann cells migrate towards the anode in an applied electric field, and the directedness and displacement of migration increase with the strength of the electric field.
Computational and Mathematical Methods in Medicine, 2016 • March 28, 2016
This study presents a mathematical model to investigate axon regeneration around glial scars after spinal cord injury, focusing on the impact of inhibitory factors and scar size. The model, based on S...
KEY FINDING: The level of inhibitory factors on the surface of glial scar significantly impacts axon elongation.
Biol Bull, 2011 • August 1, 2011
This paper discusses the use of functional genomics and gene network analysis to study regeneration, focusing on the central nervous system. It proposes using the lamprey as a model system due to its ...
KEY FINDING: Functional genomics can be used to elucidate gene regulatory networks (GRNs) in developing tissues, which, like regeneration, are complex systems, therefore, can also be applied to study the molecular mechanisms underlying the complex functions of regeneration.
J Mol Neurosci, 2015 • May 30, 2015
The study aimed to identify reliable markers for avulsion-injured spinal motoneurons, as traditional markers like ChAT are not detectable early after injury. The researchers investigated the expressio...
KEY FINDING: ATF-3 is a marker for avulsion-injured motoneurons. It was rapidly induced and sustained in the nuclei of injured motoneurons.
Computational and Mathematical Methods in Medicine, 2022 • October 1, 2022
This study explores the role of TRIM28 in LIHC, finding that its expression is upregulated in tumors and associated with poor prognosis. The research identifies correlations between TRIM28 expression ...
KEY FINDING: High TRIM28 expression level was associated with T classification, pathologic stage, histologic grade, and serum AFP levels.
Scientific Reports, 2015 • November 10, 2015
The study aimed to characterize the large genome of the Mexican axolotl salamander (Ambystoma mexicanum) using shotgun and laser capture chromosome sequencing. Researchers generated 600 Gb of shotgun ...
KEY FINDING: The A. mexicanum genome is estimated to be ~32 Gb.
Computational and Mathematical Methods in Medicine, 2016 • December 7, 2016
This study introduces a novel nonlinear trimodal regression analysis methodology for quantifying muscle degeneration using radiodensitometric distributions from CT scans. The method was tested on a ra...
KEY FINDING: The study found significant qualitative differences in the shapes of HU distributions among healthy, elderly, and pathological subjects. The healthy subject had a high-amplitude muscle peak, while the elderly subject had a more pronounced fat peak.