Seasonal Variation in Copper-mediated Low-density Lipoprotein Oxidation In Vitro is Related to Varying Plasma Concentration of Oxidised Lipids in Summer and Winter
Bibliographic record
Abstract
The seasonal variation of CuCl2-mediated low density lipoprotein (LDL) oxidation (10 microM Cu2+, lag phase, rate of oxidation and maximum absorbance at 234 nm) were measured in 43 men and women on 4-6 occasions (mean 5.7 +/- 0.5) over a 12-month period. The lag phase averaged 52.7 +/- 0.6 min and did not differ by gender. Lag phase and rate of the rapid propagation phase of LDL oxidation showed a sinusoidal pattern over the year (increased and reduced oxidative susceptibility during January and June-July, respectively; both p < 0.001). Changes in plasma alpha-tocopherol, ascorbic acid, lycopene or beta-carotene concentrations did not explain seasonal differences in oxidative susceptibility of LDL in vitro. Nor did plasma lipid content of linoleic acid, the main substrate of lipid peroxidation, vary. However, the amount of hydroperoxy- plus hydroxy-fatty acids in plasma lipids varied according to season (p < 0.024) and was related to the lag phase (r = -0.26, p < 0.001). Seasonal variation in oxidative susceptibility was not significant after adjusting for hydroperoxy- plus hydroxy-fatty acids (p = 0.506). Isolated LDL is more vulnerable to Cu2+-induced lipid peroxidation during the winter and this may be due to the higher amount of oxidised lipids during that period.
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 | 0.001 |
| 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".