Nodal induces apoptosis through activation of the ALK7 signaling pathway in pancreatic INS-1 β-cells
Bibliographic record
Abstract
We demonstrated previously that the activation of ALK7 (activin receptor-like kinase-7), a member of the type I receptor serine/threonine kinases of the TGF-β superfamily, resulted in increased apoptosis and reduced proliferation through suppression of Akt signaling and the activation of Smad2-dependent signaling pathway in pancreatic β-cells. Here, we show that Nodal activates ALK7 signaling and regulates β-cell apoptosis. We detected Nodal expression in the clonal β-cell lines and rodent islet β-cells. Induction of β-cell apoptosis by treatment with high glucose, palmitate, or cytokines significantly increased Nodal expression in clonal INS-1 β-cells and isolated rat islets. The stimuli induced upregulation of Nodal expression levels were associated with elevation of ALK7 protein and enhanced phosphorylated Smad3 protein. Nodal treatment or overexpression of Nodal dose- or time-dependently increased active caspase-3 levels in INS-1 cells. Nodal-induced apoptosis was associated with decreased Akt phosphorylation and reduced expression level of X-linked inhibitor of apoptosis (XIAP). Remarkably, overexpression of XIAP or constitutively active Akt, or ablation of Smad2/3 activity partially blocked Nodal-induced apoptosis. Furthermore, siRNA-mediated ALK7 knockdown significantly attenuated Nodal-induced apoptosis of INS-1 cells. We suggest that Nodal-induced apoptosis in β-cells is mediated through ALK7 signaling involving the activation of Smad2/3-caspase-3 and the suppression of Akt and XIAP pathways and that Nodal may exert its biological effects on the modulation of β-cell survival and β-cell mass in an autocrine fashion.
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".