Vitamin D and Brain Imaging in the Elderly: Should we Expect Some Lesions Specifically Related to Hypovitaminosis D?
Bibliographic record
Abstract
Hypovitaminosis D is associated with cognitive decline in the elderly, but the issue of causality remains unresolved. Definitive evidence would include the visualization of brain lesions resulting from hypovitaminosis D. The aim of the present article is to determine, through a literature review, the location and nature of possible brain disorders in hypovitaminosis D. We found limited brain-imaging data, which reported ischemic infarcts and white matter hyperintensities in hypovitaminosis D, though did not provide their specific location or report any focal atrophy. Based on the finding of executive dysfunctions (i.e., mental shifting and information updating impairments) in the presence of hypovitaminosis D, we suggest that hypovitaminosis D is associated with a dysfunction of the frontal-subcortical neuronal circuits, particularly the dorsolateral circuit. Further imaging studies are required to corroborate this assumption and to determine whether hypovitaminosis D results in degenerative and / or vascular lesions.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 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".