Control of β-Site Amyloid Precursor Protein-Cleaving Enzyme-1 Expressionby Protein Kinase C-λ/ι and Nuclear Factor κ-B
Bibliographic record
Abstract
Βackground: β-Amyloid precursor protein-cleaving enzyme-1 (BACE1) initiates the production of Aβ-peptides that form Aβ-plaque in Alzheimer’s disease. Methods: Reportedly, acute insulin treatment in normal mice, and hyperinsulinemia in high-fat-fed (HFF) obese/diabetic mice, increase BACE1 activity and levels of Aβ-peptides and phospho- -thr-231-tau in the brain; moreover, these effects are blocked by PKC-λ/ι inhibitors. However, as chemical inhibitors may affect unsuspected targets, we presently used knockout methodology to further examine PKC-λ/ι requirements. We found that total-body heterozygous PKC-λ knockout reduced acute stimulatory effects of insulin and chronic effects of hyperinsulinemia in HFF/obese/diabetic mice, on brain PKC-λ activity and production of Aβ1-40/42 and phospho-thr-231-tau. This protection in HFF mice may reflect that hepatic PKC-λ haploinsufficiency prevents the development of glucose intolerance and hyperinsulinemia. Results: On the other hand, heterozygous knockout of PKC-λ markedly reduced brain levels of BACE1 protein and mRNA, and this may reflect diminished activation of nuclear factor kappa-B (NFκB), which is activated by PKC-λ and increases BACE1 and proinflammatory cytokine transcription. Accordingly, whereas intravenous administration of aPKC inhibitor diminished aPKC activity and BACE1 levels by 50% in the brain and 90% in the liver, nasally-administered inhibitor reduced aPKC activity and BACE1 mRNA and protein levels by 50-70% in the brain while sparing the liver. Additionally, 24-hour insulin treatment in cultured human-derived neurons increased NFκB activity and BACE1 levels, and these effects were blocked by various PKC-λ/ι inhibitors. Conclusion: PKC-λ/ι controls NFκB activity and BACE1 expression; PKC-λ/ι inhibitors may be used nasally to target brain PKC-λ/ι or systemically to block both liver and brain PKC-λ/ι, to regulate NFκB-dependent BACE1 and proinflammatory cytokine expression.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".