S6K1 controls pancreatic β cell size independently of intrauterine growth restriction
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) is a worldwide heath problem that is characterized by insulin resistance and the eventual loss of β cell function. As recent studies have shown that loss of ribosomal protein (RP) S6 kinase 1 (S6K1) increases systemic insulin sensitivity, S6K1 inhibitors are being pursued as potential agents for improving insulin resistance. Here we found that S6K1 deficiency in mice also leads to decreased β cell growth, intrauterine growth restriction (IUGR), and impaired placental development. IUGR is a common complication of human pregnancy that limits the supply of oxygen and nutrients to the developing fetus, leading to diminished embryonic β cell growth and the onset of T2DM later in life. However, restoration of placental development and the rescue of IUGR by tetraploid embryo complementation did not restore β cell size or insulin levels in S6K1-/- embryos, suggesting that loss of S6K1 leads to an intrinsic β cell lesion. Consistent with this hypothesis, reexpression of S6K1 in β cells of S6K1-/- mice restored embryonic β cell size, insulin levels, glucose tolerance, and RPS6 phosphorylation, without rescuing IUGR. Together, these data suggest that a nutrient-mediated reduction in intrinsic β cell S6K1 signaling, rather than IUGR, during fetal development may underlie reduced β cell growth and eventual development of T2DM later in life.
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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 | 0.001 |
| 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".