Cholinergic basal forebrain circuit degeneration in Alzheimer's disease
Bibliographic record
Abstract
Alzheimer's disease is characterized by loss of synapses and neurons in specific areas of the brain, leading to loss of learning, memory and cognitive function. Among the most vulnerable neurons in Alzheimer's disease are basal forebrain cholinergic neurons. Degeneration of cholinergic projections to cortex and hippocampus is responsible for learning and memory deficits. Basal forebrain cholinergic neurons rely on two target‐derived neurotrophic factors, nerve growth factor (NGF) and brain‐derived neurotrophic factor (BDNF), to maintain survival, differentiation, connectivity and function. NGF and BDNF are dysregulated in Alzheimer's disease by very different mechanisms. NGF is found in the brain in its precursor form, proNGF, which accumulates in Alzheimer's disease and becomes toxic to basal forebrain cholinergic neurons. BDNF, on the other hand, is decreased in Alzheimer's disease at the transcriptional level, causing cholinergic dysfunction and synapse loss. The molecular pathways for BDNF down‐regulation have been partially elucidated, and recent work demonstrates that lifestyle changes can raise BDNF levels and rescue age‐related cognitive impairment. Nevertheless, a full understanding of the causes and mechanisms of basal forebrain cholinergic neuron degeneration in Alzheimer's disease remains a challenge.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".