Systemic Polyethylene Glycol Promotes Neurological Recovery and Tissue Sparing in Rats After Cervical Spinal Cord Injury
Bibliographic record
Abstract
Polyethylene glycol (PEG) has been reported to possess fusogenic properties that may confer neuroprotection after spinal cord injury (SCI), but there is uncertainty regarding the mechanisms of PEG in vivo and the robustness of its protective effects. We hypothesized that PEG promotes preservation of cytoskeletal proteins associated with white matter protection and neurobehavioral recovery after SCI. In proof-of-principle experiments using a pin-drop organotypic culture model of SCI, PEG attenuated neural cell death. Adult rats underwent 35-g clip compression SCI at C8 and were randomized postinjury to receive intravenous 30% PEG or sterile Ringer's lactate solution. Confocal microscopy and high-performance liquid chromatography of fluorescein-conjugated PEG permitted in vivo quantification of PEG concentrations in the injured and uninjured spinal cord. Western blot, immunohistochemistry, and terminal deoxynucleotidyl transferase mediated dUTP nick end labeling staining demonstrated that PEG reduced 200-kd neurofilament degradation and apoptotic cell death. Polyethylene glycol also promoted spinal cord tissue sparing based on retrograde axonal Fluoro-Gold tracing and morphometric histological assessment. Polyethylene glycol also promoted significant, although modest, neurobehavioral recovery after SCI. Collectively, these results indicate that PEG protects key axonal cytoskeletal proteins after SCI, and that the protection is associated with axonal preservation. The modest extent of locomotor recovery after treatment with PEG suggests, however, that this compound may notconfer sufficient neuroprotection to be used clinically as a single treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".