Altered levels of insulin‐like growth factor binding protein proteases in preeclampsia and intrauterine growth restriction
Bibliographic record
Abstract
Intrauterine growth restriction (IUGR) and preeclampsia (PE) are leading causes of perinatal and maternal morbidity and mortality. Many studies have found association between low levels of insulin-like growth factor binding protein (IGFBP) proteases in the first trimester maternal circulation and the risk of subsequent development of PE and/or IUGR. These results are generally interpreted to reflect decreased production of the proteases by the placenta, leading to reduced proteolysis of IGFBPs and lower free levels of insulin-like growth factor (IGF), resulting in diminished feto-placental development. However, the association between low circulating levels of placental proteins early in pregnancy and the subsequent development of IUGR and/or PE could be due to low exchange in the placenta and not due to reduced production. In contrast, late in pregnancy, the circulating levels of these proteins and their expression in the placenta are often elevated in PE, which may reflect upregulation to compensate for abnormal placental development, that is an adaptive mechanism to increase IGFBP proteolysis, increase local IGF levels and promote feto-placental growth. Further research into the biological mechanisms underlying these associations will aid the identification of high-risk pregnancies and the development of therapeutic targets for diseases for which there are presently no preventative measures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".