Comparison of plasma levels of nutrient-related biomarkers among Japanese populations in Tokyo, Japan, São Paulo, Brazil, and Hawaii, USA
Bibliographic record
Abstract
Although Japanese in Japan and the USA are high-risk populations for colorectal cancer, the prevalence of obesity, one of the established risk factors for this disease, is low in these populations compared with other high-risk populations. To understand this inconsistency, we compared plasma obesity-related biomarkers in cross-sectional studies carried out in Tokyo, São Paulo, and Hawaii. We measured plasma levels of insulin-like growth factor-I (IGF-I), insulin-like growth factor-binding protein (IGFBP)-1, IGFBP-3, C-peptide, adiponectin, leptin, tumor necrosis factor-α, and interleukin-6 by immunoassay and total C-reactive protein, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides using a clinical chemistry autoanalyzer. A total of 299 participants were included in the present analysis, comprising 142 Japanese in Tokyo, 79 Japanese Brazilians in São Paulo, and 78 Japanese Americans in Hawaii. We found significantly lower plasma levels of C-peptide and IGF-I in Japanese in Tokyo than in Japanese Americans, and lower levels of leptin and triglycerides and higher levels of adiponectin, IGFBP-3, and high-density lipoprotein cholesterol in Japanese in Tokyo than in the other two populations. We also observed a significantly higher plasma IGFBP-1 level in Japanese Brazilians, and lower plasma levels of total cholesterol and low-density lipoprotein in Japanese Americans than in the other two populations. We observed significant differences in obesity-related biomarkers between the three Japanese populations. If our results are confirmed, the risk of colorectal cancer predicted on the basis of these biomarkers would be lowest for Japanese in Tokyo, followed by Japanese Brazilians and Japanese Americans.
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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 | 0.001 | 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) | 0.000 | 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".