NAD <sup>+</sup> repletion with niacin counteracts cancer cachexia
Bibliographic record
Abstract
SUMMARY Cachexia is a debilitating wasting syndrome and highly prevalent comorbidity in cancer patients. It manifests especially with energy and mitochondrial metabolism aberrations that promote tissue wasting. We recently identified nicotinamide adenine dinucleotide (NAD + ) loss to associate with muscle mitochondrial dysfunction in cancer hosts. In this study we confirmed that depletion of NAD + and downregulation of Nrk2 , an NAD + biosynthetic enzyme, are common features of different mouse models and cachectic cancer patients. Testing NAD + repletion therapy in cachectic mice revealed that NAD + precursor, vitamin B3 niacin, efficiently corrected tissue NAD + levels, improved mitochondrial metabolism and ameliorated cancer- and chemotherapy-induced cachexia. To examine NAD + metabolism in a clinical setting, we showed that the low expression of NRK2 in cancer patients correlated with metabolic abnormalities underscoring the significance of NAD + in the pathophysiology of human cancer cachexia. Overall, our results propose a novel therapy target, NAD + metabolism, for cachectic cancer patients.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".