Is There a Shared Etiology of Olfactory Impairments in Normal Aging and Neurodegenerative Disease?
Bibliographic record
Abstract
As we age, our olfactory function declines. In addition to occurring in normal aging, more rapid decrement of olfactory decline has been associated with several neurodegenerative diseases including Alzheimer's disease (AD) and Parkinson's disease (PD). It has been argued that since olfactory deficits occur less frequently or are absent in diseases such as progressive supranuclear palsy, corticobasal degeneration, and multiple system atrophy, olfactory deficits can be used for differential diagnoses of AD and PD. The purpose of this review is to provide a survey of current knowledge about the molecular bases and differential patterns of olfactory deficits present in normal aging, AD, and PD. As substantial research has been conducted in this area, the majority of the content of this review focuses on articles published in the past decade. We hypothesize that olfactory deficits in normal aging, AD, and PD may have different underlying causes, and propose the use of model organisms with small, tractable nervous systems and/or easy to manipulate genomes to further investigate the cellular mechanisms responsible for these deficits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".