Cytoprotective and anticancer properties of coenzyme Q versus capsaicin
Bibliographic record
Abstract
Coenzyme Q (CoQ) is an essential component of the mitochondrial electron transport chain and serves as an electron donor and acceptor in mitochondrial energy-linked respiration. CoQ1 was shown to prevent ROS formation and cell death in complex 1 inhibited cells. Low concentrations of capsaicin like CoQ1 inhibited ROS formation but CoQ1 was more effective at restoring the mitochondrial membrane potential collapse caused by complex 1 inhibitors such as rotenone. At low concentrations, capsaicin acts as a CoQ mimic by protecting against rotenone induced ROS formation and mitochondrial membrane potential collapse. Lipid peroxidation in isolated rat hepatocytes induced by cumene hydroperoxide and chloroacetaldehyde was also prevented. At higher concentrations, capsaicin and CoQ1 became cytotoxic. Hep G2 cells were more susceptible than hepatocytes. The cytotoxic mechanism for both capsaicin and CoQ1 was shown to involve a collapse of the mitochondrial membrane potential, however, only capsaicin caused ROS formation. The capsaicin side chain was required for capsaicin induced cytotoxicity. The anticancer properties of CoQ1 and capsaicin should prove useful for inducing tumor cell apoptosis.
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".