Bibliographic record
Abstract
Chemotherapy often causes damage to hematopoietic tissues, leading to acute bone marrow suppression and the long term development of leukemias. Niacin deficiency, which is common in cancer patients, causes dramatic genomic instability in bone marrow cells in an in vivo rat model. From a mechanistic perspective, niacin deficiency delays excision repair and causes double strand break accumulation, which in turn favors chromosome breaks and translocations. Niacin deficiency also impairs cell cycle arrest and apoptosis in response to DNA damage, which combine to encourage the survival of cells with leukemogenic potential. Conversely, pharmacological supplementation of rats with niacin increases bone marrow poly(ADP-ribose) formation and apoptosis. Improvement of niacin status in rats significantly decreased nitrosourea-induced leukemia incidence. The data from our rat model suggest that niacin supplementation of cancer patients may decrease the severity of short- and long-term side effects of chemotherapy, and could improve tumor cell killing through activation of poly(ADP-ribose)-dependent apoptosis pathways.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".