Transcriptomic profiling of chemical exposure reveals roles of Yap1 in protecting yeast cells from oxidative and other types of stresses
Bibliographic record
Abstract
Transcriptomic profiles are generated by comparing wild-type and the yeast yap1 mutant to various chemicals in an attempt to establish a correlation between this gene mutation and chemical exposure. Test chemicals include ClonNAT as a non-genotoxic agent, methyl methanesulphonate (MMS) as an alkylating agent, tert-butyl hydroperoxide (t-BHP) as an oxidative agent and the mixture of t-BHP and MMS to reflect complex natural exposure. Differentially expressed genes (DEGs) were identified and specific DEGs were obtained by excluding overlapping DEGs with the control group. In the MMS exposure group, deoxyribonucleotide biosynthetic processes were upregulated, while oxidation-reduction processes were downregulated. In the t-BHP exposure group, metabolic processes were upregulated while peroxisome and ion transport pathways were downregulated. In the mixture exposure group, the proteasome pathway was upregulated, while the aerobic respiration was downregulated. Homologue analysis of DEGs related to human diseases showed that many of DEGs were linked to cancer, ageing and neuronal degeneration. These observations confirm that the yap1 mutant is more sensitive to chemicals than wild-type cells and that the susceptible individuals carrying the YAP1-like gene defect may enhance risk to chemical exposure. Hence, this study offers a novel approach to environmental risk assessment, based on the genetic backgrounds of susceptible individuals.
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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".