Caffeine yields aneuploidy through asymmetrical cell division caused by misalignment of chromosomes
Bibliographic record
Abstract
Aneuploidy has been implicated as an important step leading to various neoplasias. Although genetic factors that block aneuploidy have been the subject of intense interest, the impact of pharmacological and environmental substances on the development of aneuploidy has not been studied. Here, we show that caffeine induces aneuploidy through asymmetrical cell division. Mitotic exits of HeLa, U2OS, and primary fibroblast cells were significantly delayed by 10 mmol/L caffeine. Most caffeine-treated mitotic cells showed misalignment of chromosomes at the metaphase plates, and were arrested at prometaphase. Mitoticarrest deficient 2 (MAD2) depletion rescued the caffeine-induced delay of mitotic exit, indicating that caffeine-induced prolongation of mitosis was caused by activation of a MAD2-dependent spindle checkpoint. Enumeration of centromeres by fluorescence in situ hybridization revealed that cell division in the presence of caffeine was not symmetrical and resulted in aneuploid cell production. Most of these cells survived and underwent DNA synthesis. Our findings reveal a novel pharmacological effect of a high concentration of caffeine on genomic stability in dividing cells.
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".