Time-Course Analysis of Protein and Lipid Oxidation in the Brains of Yac128 Huntington's Disease Transgenic Mice
Bibliographic record
Abstract
Huntington's disease (HD) is caused by an expansion of cytosine-adenine-guanine (CAG) repeats within the coding region of the HD gene, which expresses the protein huntingtin and is characterized by selective degeneration of specific neuronal populations, mainly in the striatum and the cortex. The mechanisms that account for this selective neuronal death are multifaceted, but oxidative stress might play an important role in this process. To determine whether changes in the intracellular redox state will result in oxidative damage to cellular macromolecules with disease progression, we analyzed levels of lipid peroxidation (with the thiobarbituric acid reactive substances [TBARS] assay) and protein carbonyl formation (using the 2,4-dinitrophenylhydrazine reaction) in the cerebellum, cerebral cortex, prefrontal cortex, striatum, and hippocampus of the YAC128 HD mouse model at 3, 6, and 12 months of age. With the exception of a transient increase in protein carbonyl levels in the YAC128 prefrontal cortex at 6 months of age, levels of lipid peroxidation and protein oxidation were not significantly different between YAC128 mice and their age-matched wild-type counterparts in any of the brain regions analyzed up to 12 months of age. However, age-related increases in oxidative stress were observed in various brain regions. These results suggest that lipid and protein oxidative damage is not a major contributor to neurodegeneration in the YAC128 brain up to 12 months of age.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".