Investigating KLP-20-Dependent miRNA regulation in Caenorhabditis elegans: Mechanisms of neuronal-epidermal cell non-autonomous signaling
Bibliographic record
Abstract
Kinesins are microtubule-associated motors essential for intracellular transport, yet their roles in RNA regulation are still not well understood. Our lab previously identified KLP-20 as a novel interactor of the RISC complex (unpublished), with loss of KLP-20 disrupting miRNA-mediated gene silencing. Although KLP-20 expression is restricted to neurons, KLP-20 mutants display characteristic bumpy epidermal phenotype, suggesting a role in neuronal-epidermal communication. We hypothesize that KLP-20 may facilitate the transport of miRNA-RISC complexes from neurons to the epidermis, enabling non-autonomous signaling. Using the nematode C. elegans, we aim to define the role of KLP-20 in miRNA regulation and neuronal to epidermal communication.To address this, I generated numerous RNAi constructs to test candidate genes for suppression of the KLP-20 dependant bumpy epidermal phenotype, expressed miRNAs under an epidermal promoter to assess tissue-specific rescue, and investigated whether KLP-20 mediated miRNA regulation is dependant on miRNA regulatory machinery. This work will advance the understanding of kinesins in miRNA regulation, with implications for neurodegenerative diseases linked to disrupted miRNA pathways.
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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 | 0.000 | 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) | 0.000 | 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".