Precise control of miR-125b is required to create a regeneration-permissive environment after spinal cord injury
Bibliographic record
Abstract
Most spinal cord injuries lead to permanent paralysis in mammals. By contrast, the remarkable regenerative abilities of salamanders enable full functional recovery even from complete spinal cord transections. The molecular differences underlying this evolutionary divergence between mammals and amphibians are poorly understood. We focused on upstream regulators of gene expression as primary entry points into this question. We identified a group of microRNAs (miRNAs) that are conserved between the Mexican axolotl salamander (Ambystoma mexicanum) and mammals but show marked cross-species differences in regulation patterns following spinal cord injury. We found that precise post-injury levels of one of these miRNAs (miR-125b) is essential for functional recovery, and guides correct regeneration of axons through the lesion site in a process involving the direct downstream target Sema4D in axolotls. Translating these results to a mammalian model, we increased miR-125b levels in the rat through mimic treatments following spinal cord transection. These treatments downregulated Sema4D and other glial-scar-related genes, and enhanced the animal's functional recovery. Our study identifies a key regulatory molecule conserved between salamander and mammal, and shows that the expression of miR-125b and Sema4D must be carefully controlled in the right cells at the correct level to promote regeneration. We also show that these molecular components of the salamander's regeneration-permissive environment can be experimentally harnessed to improve treatment outcomes for mammalian spinal cord injuries.
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) | 0.000 | 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".