The relationship between oxidative SOD1 and Abeta production and aggregation
Bibliographic record
Abstract
To determine the relationship between SOD1 oxidation and amyloid beta production and aggregation, we used ELISA to analysis soluble and insoluble Aβ 40 and Aβ 42 in the cortex and spinal cord and used immunofluorescence to test the co‐localization of the oxidative SOD1 aggregation and Aβ aggregation. We found that the insoluble Aβ 40 in cortex was significant higher in 6 month old G37R mice than in non‐transgenic mice. The soluble and insoluble Aβ 42 in cortex and spinal cord were significantly higher in 6 month old G37R mice and G93A mice than in non‐transgenic mice. The mutant SOD1 could influence the production of the soluble or insoluble Aβ 40 and Aβ 42 in the brain and in the spinal cord. The oxidative SOD1 aggregations and Aβ 40 were co‐localized in the G93A and G37R transgenic mice, but not non‐transgenic mice. Meanwhile, the oxidative SOD1 aggregations localized in the senile plaques in the APP/PS1 mice. We speculated that mutant SOD1 was easy to be oxidated, and the oxidative SOD1 could interact with APP. SOD1 oxidation may be the earliest event that triggers SOD1 aggregation and induces Aβ aggregation. We will cross APP transgenic mice with G93A and G37R mice to further prove our conclusions.
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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 | 0.001 | 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 | 0.000 |
| 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".