Based on proteomics to explore the mechanism of mecobalamin promoting the repair of injured peripheral nerves
Bibliographic record
Abstract
Mecobalamin is commonly used in the adjuvant intervention of various peripheral nerve injuries. Actin cytoskeleton plays a role in the regeneration of myelin and axon. Therefore, the purpose of this study was to explore the possibility of mecobalamin regulating actin cytoskeleton in repairing nerve injury. In this study, a crush injury on the right sciatic nerve of two groups of rats (12 in each group) was established. The control group was only given normal saline (i.g.), and the intervention group was given mecobalamin 1 mg/kg (i.g.). The rats were sacrificed on 28th day and the injured nerves were collected for proteomics. The result shows that regulation of actin cytoskeleton pathway changed significantly. The expression of protein Vav1 was verified by Western blot and immunofluorescence. In the intervention group, the nerve fiber structure was complete, the axons were dense and symmetrical, and the myelin sheath was compact and uniform in thickness. The positive rate of myelin basic protein and βⅢ-tubulin was higher than that in the control group. The findings of the study show that mecobalamin regulates the actin cytoskeleton in the repair of nerve damage and upregulates Vav1 in the regulation of actin cytoskeleton pathway.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".