Poly-L-Ornithine Coated Plant Scaffolds Support Motor Recovery in Rats after Traumatic Spinal Cord Injury
Bibliographic record
Abstract
ABSTRACT Spinal cord injury (SCI) is a debilitating neurological condition with far-reaching consequences for patients, including loss of motor function and significant limitations to quality of life. Implantable biomaterials have emerged as a therapeutic strategy to modulate the SCI microenvironment and facilitate regeneration of axons. In this study, plant-derived lignocellulosic scaffolds coated with poly-L-ornithine (PLO) are shown to support locomotor recovery and neural tissue repair in a rat model of spinal cord injury. Upon complete transection of the spinal cord, animals were implanted with a plant-derived scaffold coated in poly-L-ornithine, a positively charged amino acid chain that is known to promote neural stem cell differentiation into neurons and enhance myelin regeneration. Recovery of motor function was evaluated by the Basso, Beattie and Bresnahan (BBB) locomotor scale as well as the Karolinska Institutet Swim Assessment Tool (KSAT). Retrograde tracing of ascending sensory tracts revealed enhanced regeneration in animals that received the PLO-coated scaffold. Numerous β-III tubulin and neurofilament 200 positive fibers may indicate axonal sprouting within the lignocellulosic scaffold and LFB staining highlights myelination around the PLO-coated scaffold. These results demonstrate the potential of plant-based biomaterials in a rat model of acute spinal cord injury and highlight their enhancement after PLO functionalization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".