Control of brain tumor growth by reactivating myeloid cells with niacin
Bibliographic record
Abstract
Glioblastomas are generally incurable partly because monocytes, macrophages, and microglia in afflicted patients do not function in an antitumor capacity. Medications that reactivate these macrophages/microglia, as well as circulating monocytes that become macrophages, could thus be useful to treat glioblastoma. We have discovered that niacin (vitamin B3) is a potential stimulator of these inefficient myeloid cells. Niacin-exposed monocytes attenuated the growth of brain tumor-initiating cells (BTICs) derived from glioblastoma patients by producing anti-proliferative interferon-α14. Niacin treatment of mice bearing intracranial BTICs increased macrophage/microglia representation within the tumor, reduced tumor size, and prolonged survival. These therapeutic outcomes were negated in mice depleted of circulating monocytes or harboring interferon-α receptor-deleted BTICs. Combination treatment with temozolomide enhanced niacin-promoted survival. Monocytes from glioblastoma patients had increased interferon-α14 upon niacin exposure and were reactivated to reduce BTIC growth in culture. We highlight niacin, a common vitamin that can be quickly translated into clinical application, as an immune stimulator against glioblastomas.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".