Downregulation of Fas activity rescues early onset of diabetes in<i>c-Kit</i><sup><i>Wv/+</i></sup>mice
Bibliographic record
Abstract
c-Kit and its ligand stem cell factor (SCF) are important for β-cell survival and maturation; meanwhile, interactions between the Fas receptor (Fas) and Fas ligand are capable of triggering β-cell apoptosis. Disruption of c-Kit signaling leads to severe loss of β-cell mass and function with upregulation of Fas expression in c-Kit(Wv/+) mouse islets, suggesting that there is a critical balance between c-Kit and Fas activation in β-cells. In the present study, we investigated the interrelationship between c-Kit and Fas activation that mediates β-cell survival and function. We generated double mutant, c-Kit(Wv/+);Fas(lpr/lpr) (Wv(-/-)), mice to study the physiological and functional role of Fas with respect to β-cell function in c-Kit(Wv/+) mice. Isolated islets from these mice and the INS-1 cell line were used. We observed that islets in c-Kit(Wv/+) mice showed a significant increase in β-cell apoptosis along with upregulated p53 and Fas expression. These results were verified in vitro in INS-1 cells treated with SCF or c-Kit siRNA combined with a p53 inhibitor and Fas siRNA. In vivo, Wv(-/-) mice displayed improved β-cell function, with significantly enhanced insulin secretion and increased β-cell mass and proliferation compared with Wv(+/+) mice. This improvement was associated with downregulation of the Fas-mediated caspase-dependent apoptotic pathway and upregulation of the cFlip/NF-κB pathway. These findings demonstrate that a balance between the c-Kit and Fas signaling pathways is critical in the regulation of β-cell survival and function.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".