Analysis of circulating insulin-like growth factor-1 (IGF-1) and IGF binding protein-3 (IGFBP-3) in tobacco smokers and non-smokers
Bibliographic record
Abstract
BACKGROUND: IGF-1 and the major serum IGF-1 binding protein, IGFBP-3, are under extensive investigation as potential prognostic markers of specific malignancies and vascular diseases. However, there is conflicting evidence that tobacco smoking may influence systemic concentrations of IGF-1 and IGFBP-3. SUBJECTS AND METHODS: Serum concentrations of IGF-1 and IGFBP-3 were measured in 20 smokers and 20 non-smokers, matched for age and gender. Serum concentrations of cotinine, the major metabolite of nicotine, and ICAM-1, known to exhibit a dose-dependent relationship with cotinine, were also assayed. RESULTS: There was no difference between the systemic concentrations of IGF-1 or IGFBP-3 found in smokers and non-smokers (IGF-1: mean [s.d]; 104 29 vs 101 24 ng ml-1, respectively; and IGFBP-3: 2562 [522] vs 2447 [570] ng ml-1, respectively). Similarly, there was no correlation between serum cotinine and IGF-1 or IGFBP-3 concentrations in smokers. Soluble ICAM-1 concentrations were significantly increased in smokers, compared to non-smokers (mean [s.d]; 258 [60] vs 194 [50] ng ml-1, respectively; p = 0.002). CONCLUSION: There was no relationship noted between tobacco smoking and either IGF-1 or IGFBP-3. These data suggest that smoking would not appear to be a major confounder of the reported clinical associations between IGF-1, IGFBP-3, or IGF-1/IGFBP-3 ratios and specific disease entities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".