Cholinergic signalling in the forebrain controls microglial phenotype and responses to systemic inflammation
Bibliographic record
Abstract
Abstract(250) Loss of basal forebrain cholinergic projections occurs in Alzheimer’s disease, frontotemporal dementia and in aging. Moreover, nicotinic stimulation is anti-inflammatory in macrophages and microglia but how loss of basal forebrain acetylcholine impacts on microglial phenotype is poorly understood. Here we hypothesized that endogenous ACh maintains homeostatic microglial phenotype and that neurodegeneration-evoked loss of ACh tone, triggers microglial activation. Using the specific immunotoxin, mu-p75 NTR -saporin, we performed partial lesions of the basal forebrain cholinergic nuclei, medial septum and ventral diagonal band. We examined microglial phenotype in the hippocampus, the major projection area for these nuclei, using bulk RNA preparations, Flow cytometry-sorted microglial cells, immunohistochemistry and ELISA to examine responses to cholinergic withdrawal and acute responses to subsequent systemic inflammation with LPS. Basal forebrain cholinergic degeneration elicited lasting activation of microglia in the hippocampus, showing suppression of Sall1 and persistent elevation of Trem2, Clec7a, Itgax and complement genes proportionate to Chat loss. These primed microglia showed exaggerated IL-1β responses to systemic LPS challenge. In normal animals LPS evoked acute increases in extracellular choline, a proxy for ACh release, and this response was lost in lesioned animals. Restoration of basal cholinergic signalling via serial treatments with the nicotinic agonist PNU282,987 resulted in reversion to the homeostatic microglial phenotype and prevented exaggerated responses to acute systemic inflammation. The data indicate that neurodegeneration-evoked loss of cholinergic tone, triggers microglial activation via impaired microglial nicotinic signalling and leaves these microglia more vulnerable to secondary inflammatory insults. The data have implications for neuroinflammation during aging and neurodegeneration and for responses to sepsis and systemic inflammation.
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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".