Mycotoxin exposure and human cancer risk: A systematic review of epidemiological studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In recent years, there has been an increasing interest in investigating the carcinogenicity of mycotoxins in humans. This systematic review aims to provide an overview of data linking exposure to different mycotoxins with human cancer risk. Publications (2019 and earlier) of case-control or longitudinal cohort studies were identified in PubMed and EMBASE. These articles were then screened by independent reviewers and their quality was assessed according to the Newcastle-Ottawa scale. Animal, cross-sectional, and molecular studies satisfied criteria for exclusion. In total, 14 articles were included: 13 case-control studies and 1 longitudinal cohort study. Included articles focused on associations of mycotoxin exposure with primary liver, breast, and cervical cancer. Overall, a positive association between the consumption of aflatoxin-contaminated foods and primary liver cancer risk was verified. Two case-control studies in Africa investigated the relationship between zearalenone and its metabolites and breast cancer risk, though conflicting results were reported. Two case-control studies investigated the association between hepatocellular carcinoma and fumonisin B1 exposure, but no significant associations were observed. This systematic review incorporates several clear observations of dose-dependent associations between aflatoxins and liver cancer risk, in keeping with IARC Monograph conclusions. Only few human epidemiological studies investigated the associations between mycotoxin exposures and cancer risk. To close this gap, more in-depth research is needed to unravel evidence for other common mycotoxins, such as deoxynivalenol and ochratoxin A. The link between mycotoxin exposures and cancer risk has mainly been established in experimental studies, and needs to be confirmed in human epidemiological studies to support the evidence-based public health strategies.
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.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it