<i>In vivo</i> effects of insulin‐like growth factor‐I (IGF‐I) on prenatal and early postnatal development of the central nervous system
Bibliographic record
Abstract
The in vivo actions of insulin-like growth factor-I (IGF-I) on prenatal and early postnatal brain development were investigated in transgenic (Tg) mice that overexpress IGF-I prenatally under the control of regulatory sequences from the nestin gene. Tg mice demonstrated increases in brain weight of 6% by embryonic day (E) 18 and 27% by postnatal day (P) 12. In Tg embryos at E16, the volume of the cortical plate was significantly increased by 52% and total cell number was increased by 54%. S-phase labeling with 5-bromo-2'-deoxyuridine revealed a 13-15% increase in the proportion of labeled neuroepithelial cells in Tg embryos at E14. In Tg mice at P12, significant increases in regional tissue volumes were detected in the cerebral cortex (29%), subcortical white matter (52%), caudate-putamen (37%), hippocampus (49%), dentate gyrus (71%) and habenular complex (48%). Tg mice exhibited significant increases in the total number of neurons in the cerebral cortex (27%), caudate-putamen (27%), dentate gyrus (69%), medial habenular nucleus (61%) and lateral habenular nucleus (36%). In the cerebral cortex and subcortical white matter of Tg mice, the total numbers of glial cells were significantly increased by 37% and 42%, respectively. The numerical density of apoptotic cells in the cerebral cortex, labeled by antibodies against active caspase-3, was reduced by 26% in Tg mice at P7. Our results demonstrate that IGF-I can both promote proliferation of neural cells in the embryonic central nervous system in vivo and inhibit their apoptosis during postnatal 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) | 0.001 | 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) | 0.002 | 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".