Early loss of locus coeruleus innervation promotes cognitive and neuropathological changes before amyloid plaque deposition in a transgenic rat model of Alzheimer's disease
Bibliographic record
Abstract
AIMS: The locus coeruleus (LC) is the main source of noradrenaline (NA) in the mammalian brain and has been found to degenerate during the initial stages of Alzheimer's disease (AD). Recent studies indicate that at late stages of the amyloid pathology, LC-pathological alterations accelerate AD-like pathology progression by interfering with the neuromodulatory and anti-inflammatory properties of NA. However, the impact of LC degeneration at the earliest stages of amyloidosis on the AD-like pathology is not well understood. METHODS: The LC was lesioned in wild-type and McGill-R-Thy1-APP transgenic (APP tg) rats by administering N-(2-chloroethyl)-N-ethyl-bromo-benzylamine before amyloid plaque deposition. Cognitive deficits and AD-like neuropathological changes were measured after the LC lesion. RESULTS: Four months post-treatment, rats displayed a decrease in brain noradrenergic innervation. The LC lesion in APP tg-treated rats enhanced cognitive deficits and decreased hippocampal cholinergic innervation and neurotrophin expression. In addition, the APP tg-treated rats displayed an increased microglial and astroglial cell number in close vicinity to hippocampal amyloid-beta burdened neurons. The recruited microglia showed cellular alterations indicative of an intermediate activation state. CONCLUSIONS: Our results indicate that early LC demise aggravates the early neuroinflammatory process, cognitive impairments, cholinergic deficits and neurotrophin deregulation at the earliest stages of the human-like brain amyloidosis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".