The application of genome-wide CRISPR-Cas9 screens to dissect the molecular mechanisms of toxins
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
Many toxins are life-threatening to both animals and humans. However, specific antidotes are not available for most of those toxins. The molecular mechanisms underlying the toxicology of well-known toxins are not yet fully characterized. Recently, the advance in CRISPR-Cas9 technologies has greatly accelerated the process of revealing the toxic mechanisms of some common toxins on hosts from a genome-wide perspective. The high-throughput CRISPR screen has made it feasible to untangle complicated interactions between a particular toxin and its corresponding targeting tissue(s). In this review, we present an overview of recent advances in molecular dissection of toxins' cytotoxicity by using genome-wide CRISPR screens, summarize the components essential for toxin-specific CRISPR screens, and propose new strategies for future research.
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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 | 0.000 | 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) | 0.000 | 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