Synergistic control of axon regeneration and functional recovery by <i>let-7</i> miRNA and Insulin signalling (IIs) pathways
Bibliographic record
Abstract
Abstract The capability of neurons to regenerate after injury becomes poor in adulthood. Previous studies indicated that loss of either let-7 miRNA or components of Insulin signalling (IIs) can overcome the age-related decline in axon regeneration in C. elegans . In this study, we wanted to understand the relationship between these two pathways in axon regeneration. We found that the simultaneous removal of let-7 and the gene for insulin receptor daf-2 synergistically increased the functional recovery involving posterior touch sensation following axotomy of PLM neuron in adulthood. Conversely, the loss of let-7 could bypass the regeneration block due to the loss of DAF-16, a transcriptional target of DAF-2. Similarly, the loss of daf-2 could bypass the requirement of LIN-41, a transcriptional co-factor of the let-7 pathway. Our analysis revealed that these two pathways synergistically control targeting of the regenerating axon to the ventral nerve cord, which leads to functional recovery. The computational analysis of the gene expression data revealed a large number of genes, their interacting modules, and hub genes under let-7 and IIs pathway are exclusive in nature. Our study highlights a potential to promote neurite regeneration by harnessing the independent gene expression program involving the let-7 and Insulin signalling pathways.
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 | 0.000 |
| 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".