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Making Spinal Cord Injury (SCI) Research Accessible to Everyone. Simplified summaries of the latest research, designed for patients, caregivers and anybody who's interested.

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Bioinformatics Research

Browse the latest research summaries in the field of bioinformatics for spinal cord injury patients and caregivers.

Showing 161-170 of 334 results

NeurologyBioinformaticsRehabilitation

Shaping Exploration: How Does the Constraint-Induced Movement Therapy Helps Patients Finding a New Movement Solution

J. Funct. Morphol. Kinesiol., 2023 • December 22, 2022

This study investigates how constraint-induced movement therapy (CIMT) helps patients with spinal cord injuries find new movement solutions using a dynamical systems approach. The researchers analyzed...

KEY FINDING: Individuals modulated foot height to accomplish the task.

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BioinformaticsBiomedicalBiomechanics

Machine-Learning-Based Methodology for Estimation of Shoulder Load in Wheelchair-Related Activities Using Wearables

Sensors, 2023 • February 1, 2023

This study developed a machine-learning-based methodology to estimate shoulder load in wheelchair-related activities using wearable sensors. The approach involved collecting data from participants per...

KEY FINDING: A subject-specific biLSTM model trained on a sparse sensor setup (upper arm IMU, WC IMUs, and EMG) yielded the most promising results, with a mean correlation coefficient of 0.74 ± 0.14 and a relative root-mean-squared error of 8.93% ± 2.49%.

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Spinal Cord InjuryGastroenterologyBioinformatics

The gut microbiota and metabolite profiles are altered in patients with spinal cord injury

Molecular Brain, 2023 • February 5, 2023

This study examined the gut microbiota and serum metabolites in SCI patients compared to healthy individuals to understand their interaction in SCI pathogenesis. We present a comprehensive landscape o...

KEY FINDING: SCI patients have different gut bacteria compared to healthy people, with increases in some bacteria (UBA1819, Anaerostignum, Eggerthella, Enterococcus) and decreases in others (Faecalibacterium, Blautia, Escherichia–Shigella, Agathobacter, Collinsella, Dorea, Ruminococcus, Fusicatenibacter, and Eubacterium).

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Cardiovascular ScienceBioinformatics

Sample, Fuzzy and Distribution Entropies of Heart Rate Variability: What Do They Tell Us on Cardiovascular Complexity?

Entropy, 2023 • February 2, 2023

This study explores the nature of information on heart rate variability (HRV) provided by Distribution Entropy (DistEn) compared to Sample Entropy (SampEn) and Fuzzy Entropy (FuzzyEn) over multiple sc...

KEY FINDING: DistEn is affected by spinal cord lesions but not by postural changes, suggesting it measures cardiovascular complexity.

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Assistive TechnologyBioinformatics

Integration of Task-Based Exoskeleton with an Assist-as-Needed Algorithm for Patient-Centered Elbow Rehabilitation

Sensors, 2023 • February 23, 2023

This paper presents an Assist-as-Needed (AAN) algorithm for controlling an exoskeleton designed for elbow rehabilitation. The algorithm uses FSR sensors and machine learning to personalize assistance....

KEY FINDING: The study provides patients with real-time, visual feedback on their progress by combining range of motion and FSR data to quantify disability levels.

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Assistive TechnologyBioinformaticsTelehealth & Digital Health

An algorithm to reduce human–robot interface compliance errors in posture estimation in wearable robots

Wearable Technologies, 2022 • December 1, 2022

The study addresses the problem of posture estimation errors in wearable robots due to the compliance of the human-robot interface. A novel algorithm is presented that uses machine learning to correct...

KEY FINDING: The algorithm reduced the estimated thigh segment’s angle RMS error from 6.3° to 2.5°.

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Regenerative MedicineBioinformatics

Deep learning-based predictive identification of neural stem cell differentiation

Nature Communications, 2021 • May 6, 2021

This study introduces a deep learning-based platform for identifying the differentiation of neural stem cells (NSCs) into specific cell types, particularly neurons, astrocytes, and oligodendrocytes. T...

KEY FINDING: A deep learning-based model can accurately identify differentiated cell types from brightfield images of NSCs as early as 1 day of culture.

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Regenerative MedicineNeurologyBioinformatics

Transcriptomic Approaches to Neural Repair

The Journal of Neuroscience, 2015 • October 14, 2015

Transcriptomic approaches are used to identify molecular mechanisms for neural repair. RNA-Seq technology improves the ability to understand gene expression network regulation. Activation of a core tr...

KEY FINDING: RNA-Seq technology improves the ability to understand gene expression network regulation, because it can identify isoform-specific gene regulators. This allows defining precise transcription start sites and 3' untranslated regions for each differentially expressed isoform.

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Spinal Cord InjuryNeurologyBioinformatics

Identification of four differentially expressed genes associated with acute and chronic spinal cord injury based on bioinformatics data

Neural Regeneration Research, 2021 • May 1, 2021

This study aimed to identify differentially expressed genes (DEGs) associated with both acute and chronic phases of spinal cord injury (SCI) using bioinformatics analysis of gene expression profiles. ...

KEY FINDING: Approximately 66 DEGs were identified in GSE45550 between 3–14 days after SCI, whereas 2418 DEGs were identified in GSE45006 1–56 days after SCI.

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Spinal Cord InjuryNeurologyBioinformatics

Cortical transcriptome analysis after spinal cord injury reveals the regenerative mechanism of central nervous system in CRMP2 knock-in mice

Neural Regen Res, 2021 • December 12, 2020

This study aimed to reveal the intracellular mechanism in axotomized neurons in the CRMP2 knock-in (CRMP2KI) mouse model by performing transcriptome analysis in mouse sensorimotor cortex using micro-d...

KEY FINDING: CRMP2KI suppresses somatic atrophy in sensorimotor cortex after spinal cord injury

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