Functional and Complementary Phosphorylation State Attributes of Human Insulin-like Growth Factor-Binding Protein-1 (IGFBP-1) Isoforms Resolved by Free Flow Electrophoresis
Bibliographic record
Abstract
Fetal growth restriction (FGR) is a common disorder in which a fetus is unable to achieve its genetically determined potential size. High concentrations of insulin-like growth factor-binding protein-1 (IGFBP-1) have been associated with FGR. Phosphorylation of IGFBP-1 is a mechanism by which insulin-like growth factor-I (IGF-I) bioavailability can be modulated in FGR. In this study a novel strategy was designed to determine a link between IGF-I affinity and the concomitant phosphorylation state characteristics of IGFBP-1 phosphoisoforms. Using free flow electrophoresis (FFE), multiple IGFBP-1 phosphoisoforms in amniotic fluid were resolved within pH 4.43-5.09. The binding of IGFBP-1 for IGF-I in each FFE fraction was determined with BIAcore biosensor analysis. The IGF-I affinity (K(D)) for different IGFBP-1 isoforms ranged between 1.12e-08 and 4.59e-07. LC-MS/MS characterization revealed four phosphorylation sites, Ser(P)(98), Ser(P)(101), Ser(P)(119), and Ser(P)(169), of which Ser(P)(98) was new. Although the IGF-I binding affinity for IGFBP-1 phosphoisoforms across the FFE fractions did not correlate with phosphopeptide intensities for Ser(P)(101), Ser(P)(98), and Ser(P)(169) sites, a clear association was recorded with Ser(P)(119). Our data demonstrate that phosphorylation at Ser(119) plays a significant role in modulating affinity of IGFBP-1 for IGF-I. In addition, an altered profile of IGFBP-1 phosphoisoforms was revealed between FGR and healthy pregnancies that may result from potential site-specific phosphorylation. This study provides a strong basis for use of this novel approach in establishing the linkage between phosphorylation of IGFBP-1 and FGR. This overall strategy will also be broadly applicable to other phosphoproteins with clinical and functional significance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".