Clinical Validation of ELISA Assays for Insulin-Like Growth Factor-II (IGF-II)
Bibliographic record
Abstract
Background : Insulin-like growth factor-II (IGF-II) is known to be dysregulated in malnutrition and in non-islet cell tumour hypoglycaemia (NICTH). Its measurement may be used diagnostically in the latter condition but little information is available on its utility as a nutritional marker. The aims of this study were to clinically validate two ELISAs for measurement of IGF-II in these conditions and to provide further information relevant to their use in nutritional contexts. Methods : IGF-II concentrations were measured by extraction and non-extraction ELISA and RIA in 20 malnourished patients referred for nutrition support. IGF-II concentrations were also measured by both ELISAs in 10 subjects with clinical features of NICTH. Results : Baseline IGF-II measured by both ELISAs correlated with body weight in patients referred for parenteral nutrition (PN) (P Conclusions : IGF-II may have a place in monitoring of nutrition support and merits further study of its utility as a nutritional marker. Whilst the ELISAs investigated can sensitively detect IGF-II and are valid for the measurement of IGF-II in nutritional contexts they are unlikely to replace RIA for the purpose of investigating NICTH. doi:10.4021/jem82w
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".