Identification of Signaling Pathways Targeted by the Food Contaminant FB1: Transcriptome and Kinome Analysis of Samples from Pig Liver and Intestine
Bibliographic record
Abstract
SCOPE: Fumonisin B1 (FB1) is a mycotoxin produced by Fusarium species. In mammals, this toxin causes widespread organ-specific damage; it promotes hepatotoxicity, is immunotoxic, alters intestinal functions etc. Despite its inhibitory effect on de novo ceramide synthesis, its molecular mechanism of action and toxicity is not totally elucidated. METHODS AND RESULTS: To explore the mechanism of FB1 toxicity, we analyzed the transcriptome and the kinome of two organs targeted by FB1: the liver and the jejunum. Pigs were fed for 4 weeks a control diet or a FB1-contaminated diet (10 mg/kg). As expected, FB1-exposed pigs gained less weight and displayed a higher sphinganine/sphingosine ratio. Comparison of the transcriptomes and the kinomes of treated versus control pigs showed striking differences. Among the disrupted pathways in liver and jejunum, we highlight Protein Kinase B (AKT) / Phosphatase and tensin homolog (PTEN) at the intersection of the FB1-modulated pathways. CONCLUSION: Most of the effects of FB1 are mediated by the regulation of ceramide level, which influences protein phosphatase 2 (PP2A) and the phosphoinositide 3-kinase (PI3K)/AKT signaling pathway. This pathway might be a new target to counteract toxic effect of Fumonisin B1, which is one of the most spread food contaminant in the world.
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 | 0.000 | 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) | 0.001 | 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".