Soluble Arctic amyloid β protein inhibits hippocampal long‐term potentiation <i>in vivo</i>
Bibliographic record
Abstract
Mutations in the amyloid precursor protein that result in substitutions of glutamic acid at residue 22 of the amyloid beta protein (A beta) with glutamine (Q22, Dutch) or glycine (G22, Arctic) cause aggressive familial neurological diseases characterized by cerebrovascular haemorrhages or Alzheimer's-type dementia, respectively. The present study compared the ability of these peptides to block long-term potentiation (LTP) of glutamatergic transmission in the hippocampus in vivo. The effects of intracerebroventricular injection of wild-type, Q22 and G22 A beta(1-40) peptides were examined in the CA1 area of urethane-anaesthetized rats. Both mutant peptides were approximately 100-fold more potent than wild-type A beta at inhibiting LTP induced by high-frequency stimulation when solutions of A beta were freshly prepared. Fibrillar material, as determined by electron microscopy, was obvious in all these peptide solutions and exhibited appreciable Congo Red binding, particularly for A beta(1-40)G22 and A beta(1-40)Q22. A soluble fraction of A beta(1-40)G22, obtained following high-speed centrifugation, retained full activity of the peptide solution to inhibit LTP, providing strong evidence that in the case of the Arctic disease a soluble nonfibrillar form of A beta may represent the primary mediator of A beta-related cognitive deficits, particularly early in the disease. In contrast, nonfibrillar soluble A beta(1-40)Q22 supernatant solution was approximately 10-fold less potent at inhibiting LTP than A beta(1-40)G22, a finding consistent with fibrillar A beta contributing to the inhibition of LTP by the Dutch peptide.
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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 | 0.000 | 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".