The expression of dominant negative TCF7L2 in pancreatic beta cells during the embryonic stage causes impaired glucose homeostasis
Bibliographic record
Abstract
OBJECTIVE: Disruption of TCF7L2 in mouse pancreatic β-cells has generated different outcomes in several investigations. Here we aim to clarify role of β-cell TCF7L2 and Wnt signaling using a functional-knockdown approach. METHODS: Adenovirus-mediated dominant negative TCF7L2 (TCF7L2DN) expression was conducted in Ins-1 cells. The fusion gene in which TCF7L2DN expression is driven by P TRE3G was utilized to generate the transgenic mouse line TCF7L2DN Tet . The double transgenic line was created by mating TCF7L2DN Tet with Ins2-rtTA, designated as βTCFDN. β-cell specific TCF7L2DN expression was induced in βTCFDN by doxycycline feeding. RESULTS: TCF7L2DN expression in Ins-1 cells reduced GSIS, cell proliferation and expression of a battery of genes including incretin receptors and β-cell transcription factors. Inducing TCF7L2DN expression in βTCFDN during adulthood or immediately after weaning generated no or very modest metabolic defect, while its expression during embryonic development by doxycycline feeding in pregnant mothers resulted in significant glucose intolerance associated with altered β-cell gene expression and reduced β-cell mass. CONCLUSIONS: Our observations support a cell autonomous role for TCF7L2 in pancreatic β-cells suggested by most, though not all, investigations. βTCFDN is a novel model for further exploring the role of TCF7L2 in β-cell genesis and metabolic homeostasis.
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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 | 0.000 |
| 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 | 0.001 |
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".