Circulating copper and zinc levels and risk of hepatobiliary cancers in Europeans
Bibliographic record
Abstract
Copper and zinc are essential micronutrients and cofactors of many enzymatic reactions that may be involved in liver-cancer development. We aimed to assess pre-diagnostic circulating levels of copper, zinc and their ratio (Cu/Zn) in relation to hepatocellular carcinoma (HCC), intrahepatic bile duct (IHBD) and gall bladder and biliary tract (GBTC) cancers. A nested case–control study was conducted within the European Prospective Investigation into Cancer and Nutrition cohort. Serum zinc and copper levels were measured in baseline blood samples by total reflection X-ray fluorescence in cancer cases (HCC n =106, IHDB n =34, GBTC n =96) and their matched controls (1:1). The Cu/Zn ratio, an indicator of the balance between the micronutrients, was computed. Multivariable adjusted odds ratios and 95% confidence intervals (OR; 95% CI) were used to estimate cancer risk. For HCC, the highest vs lowest tertile showed a strong inverse association for zinc (OR=0.36; 95% CI: 0.13–0.98, P trend =0.0123), but no association for copper (OR=1.06; 95% CI: 0.45–2.46, P trend =0.8878) in multivariable models. The calculated Cu/Zn ratio showed a positive association for HCC (OR=4.63; 95% CI: 1.41–15.27, P trend =0.0135). For IHBC and GBTC, no significant associations were observed. Zinc may have a role in preventing liver-cancer development, but this finding requires further investigation in other settings.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".