Caenorhabditis elegans Model to Test the Effect of Pharmacological Drugs on IGF-1/insulin Signalling Pathway
Bibliographic record
Abstract
Many pharmacological drugs have been reported to alter insulin signalling in the body resulting in altered blood glucose levels.Drug induced hypoglycaemic or hyperglycaemic effect may lead to adverse effects especially in diabetic patients.Treating ailments of diabetic patients has always remained challenging for the clinicians due to unexplored effect of many drugs on insulin signalling.Insulin/insulin like growth factor-1 signalling (IIS) pathway is highly conserved between Caenorhabditis elegans and humans.In both C. elegans and humans IIS pathway is involved in regulating fat storage.C. elegans dauer formation is regulated primarily via IIS pathway and is triggered by adverse environmental conditions.In this paper we proposed the use of C. elegans dauer formation as a vital strategy to check the drug interaction with IIS.Activity of DAF-2 and DAF-16 are the key regulators of IIS in C. elegans.Aspirin, silymarin and pravastatin drugs have been reported to alter blood glucose levels using animal models and clinical reports.To test the efficacy of our model we tested the effect of these drugs on IIS by using dauer formation as a read-out.Our results report that aspirin and silymarin decreased dauer formation whereas pravastatin enhanced it; the effect was mediated through daf-16 signalling.Our results thus report that C. elegans dauer formation can be used as an effective readout for drug and IIS pathway interaction. Caenorhabditis elegans Model to Test the Effect of Pharmacological Drugs on IGF-1/insulin Signalling 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".