Stanniocalcin 2 alters PERK signalling and reduces cellular injury during cerulein induced pancreatitis in mice
Bibliographic record
Abstract
BACKGROUND: Stanniocalcin 2 (STC2) is a secreted protein activated by (PKR)-like Endoplasmic Reticulum Kinase (PERK) signalling under conditions of ER stress in vitro. Over-expression of STC2 in mice leads to a growth-restricted phenotype; however, the physiological function for STC2 has remained elusive. Given the relationship of STC2 to PERK signalling, the objective of this study was to examine the role of STC2 in PERK signalling in vivo. RESULTS: Since PERK signalling has both physiological and pathological roles in the pancreas, STC2 expression was assessed in mouse pancreata before and after induction of injury using a cerulein-induced pancreatitis (CIP) model. Increased Stc2 expression was identified within four hours of initiating pancreatic injury and correlated to increased activation of PERK signalling. To determine the effect of STC2 over-expression on PERK, mice systemically expressing human STC2 (STC2Tg) were examined. STC2Tg pancreatic tissue exhibited normal pancreatic morphology, but altered activation of PERK signalling, including increases in Activating Transcription Factor (ATF) 4 accumulation and autophagy. Upon induction of pancreatic injury, STC2Tg mice exhibited limited increases in circulating amylase levels and increased maintenance of cellular junctions. CONCLUSIONS: This study links STC2 to the pathological activation of PERK in vivo, and suggests involvement of STC2 in responding to pancreatic acinar cell injury.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".