Browse the latest research summaries in the field of bioinformatics for spinal cord injury patients and caregivers.
Showing 81-90 of 334 results
Int. J. Mol. Sci., 2023 • July 5, 2023
This research evaluates the feasibility of a multimodal pain assessment protocol during rehabilitation following spinal cord injury (SCI). The protocol amalgamates clinical workup (CW), quantitative s...
KEY FINDING: The SCI Pain Instrument (SCIPI) was efficient in distinguishing between nociceptive and neuropathic pain, showing a progressive increase in severity over time.
eLife, 2023 • July 18, 2023
The study conducts a meta-analysis of genome-wide association studies (GWASs) using 22,016 Japanese individuals and identifies 14 significant loci, 8 of which were previously unreported. A Mendelian r...
KEY FINDING: Identified 14 significant loci associated with OPLL, including 8 previously unreported loci.
Journal of Translational Medicine, 2023 • July 20, 2023
This study comprehensively maps transcriptional changes in young and old DRGs after injury, identifying hub genes and related drugs affecting axon regeneration. The research pioneers the construction ...
KEY FINDING: Identified 693 and 885 DEGs in old and young mice, respectively, after peripheral nerve injury, with shared DEGs involved in inflammatory and immune responses.
The Journal of Spinal Cord Medicine, 2024 • January 1, 2024
This study used principal component analysis (PCA) to identify how cardiometabolic (CM) risk factors cluster in individuals with spinal cord injury (SCI) compared to non-SCI controls, revealing a six-...
KEY FINDING: Principal component analysis (PCA) identified six factor components (FC) explaining 77% and 82% of the total variance in the SCI and non-SCI cohorts, respectively.
ADV SKIN WOUND CARE, 2023 • October 1, 2023
The study aimed to identify genetic biomarkers predisposing individuals with spinal cord injury (SCI) to recurrent pressure injuries (PIs) through repeated measures of the transcriptome profile. Resul...
KEY FINDING: Whole genome sequencing identified 260 genes with increased single-nucleotide variations in exonic regions among individuals with high intramuscular adipose tissue levels and recurrent PIs.
Frontiers in Neurology, 2023 • October 12, 2023
This study used cluster analysis to identify five clinically similar subgroups of tSCI patients based on demographics and injury characteristics at baseline. These subgroups showed statistically signi...
KEY FINDING: The study identified five distinct subgroups of tSCI patients based on baseline variables such as age, BMI, injury severity (AIS grade), primary location of injury (PLI), and baseline FIM motor score.
Translational Neuroscience, 2023 • October 7, 2023
This study evaluated the effectiveness of lower limb rehabilitation robots (LLRRs) in improving the walking ability of spinal cord injury (SCI) patients, comparing it to conventional rehabilitation tr...
KEY FINDING: Patients in the LLRR group (Group B) showed significantly higher FAC (functional ambulation category) scores after 10 weeks of training compared to the conventional RT group (Group A).
Frontiers in Neuroscience, 2023 • December 13, 2023
This study introduces a novel spatial filter paradigm, adaptive spatial pattern (ASP), which differentiates itself from traditional CSP methods by emphasizing the optimization of energy distribution w...
KEY FINDING: The classification accuracy of the proposed method has reached 74.61 and 81.19% on datasets 2a and 2b, respectively.
Healthcare, 2024 • December 19, 2023
This study developed an AI‑based real‑time motion feedback system for patients with spinal cord injury (SCI) during rehabilitation, aiming to enhance their interest and motivation. The effectiveness o...
KEY FINDING: The experimental group (using the AI system) showed increased strength in all measured variables, whereas the control group showed constant or reduced results.
Sensors, 2024 • January 19, 2024
The study investigates the use of mechanomyography (MMG) and machine learning (ML) to simplify transcutaneous spinal cord stimulation (tSCS) calibration. It proposes using accelerometers to measure mu...
KEY FINDING: The acceleration-based calibration procedure achieved a mean accuracy of up to 87% relative to the classical EMG approach as ground truth on a combined cohort of 11 healthy subjects and 11 patients.