Activation of Endoproteolytic Processing of Insulin-Like Growth Factor-II in Fetal, Early Postnatal, and Pregnant Rats and Persistence of Circulating Levels in Postnatal Life
Bibliographic record
Abstract
The process of posttranslational modifications of IGF-II likely has important physiological consequences. In addition to mature IGF-II, glycosylated proIGF-II(156-amino acid peptide) and two glycosylated big IGF-II forms, IGF-II(1-104) and IGF-II(1-87), have been identified in the human circulation. Due to lack of an appropriate methodology, different IGF-II isoforms have not been demonstrated and characterized in the rat circulation, thus preventing a better understanding of the physiological and pathological roles of IGF-II. In the present study, we characterized each IGF-II form and assessed its content in the rat circulation throughout life time by using a highly sensitive Western blot analysis, which is void of the IGF binding protein interference and distinguished all IGF-II forms. For the first time, we demonstrated the presence of IGF-II variants, including proIGF-II, IGF-II(1-87), and mature IGF-II, in the rat circulation during postnatal life, challenging the current impression that IGF-II is absent from sera of adult rats. ProIGF-II is glycosylated and is the predominant form in the rat circulation. Endoproteolytic processing of proIGF-II was clearly activated in fetal, neonatal, and pregnant rats, likely reflecting its involvement in fetal development through the generation of specific forms of IGF-II (e.g. mature IGF-II) that are required for their distinct biological functions. Taken together, our data also suggest that serum IGF-II profiles may reflect underlying physiological conditions.
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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 | 0.000 |
| 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 | 0.000 |
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".