Oxidative stress does not differ in primary dermal fibroblasts isolated from fast-growing and control-growing Japanese Quail (<i>Coturnix japonica</i>)
Bibliographic record
Abstract
Growth rate is a key life-history trait that influences fitness and shapes the physiology of organisms. Additionally, faster growing individuals of the same species seem to be burdened with higher whole-animal metabolism and higher cellular turnover rates, which may lead to increases in oxidative stress, though this fact remains controversial within the literature. Aerobic organisms are subjected to metabolic by-products known as reactive oxygen species (ROS), which can wreak havoc on macromolecules, such as structurally altering proteins and inducing mutations in DNA, among others. To combat accumulating damage, organisms have evolved endogenous antioxidants and can consume exogenous antioxidants to sequester ROS before they cause cellular damage. We used primary fibroblast cells isolated from control-growing and fast-growing Japanese Quail (Coturnix japonica Temminck and Schlegel, 1849) as a study model for the effects of differing growth rates on oxidative stress. We measured reduced glutathione (GSH) concentration, ROS production, mitochondrial content, and lipid peroxidation (LPO) damage. We found no significant differences in the four parameters measured between control-growing and fast-growing Quail. However, we found that in fast-growing Quail, GSH correlated with LPO damage and mitochondrial content, and LPO damage positively correlated with mitochondrial content, whereas control-growing Quail only showed positive relationships between LPO damage and ROS production.
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".