Dietary vitamin B12 deficiency impairs motor function and changes neuronal survival and choline metabolism after ischemic stroke in middle aged male and female mice
Bibliographic record
Abstract
Abstract Nutrition is a modifiable risk factor for ischemic stroke. As people age their ability to absorb some nutrients decreases, a primary example is vitamin B12. Older individuals with a vitamin B12 deficiency are at a higher risk for ischemic stroke and have worse stroke outcome. However, the mechanisms through which these occur remain unknown. The aim of the study was to investigate the role of vitamin B12 deficiency in ischemic stroke outcome and mechanistic changes in a mouse model. Ten-month-old male and female mice were put on control or vitamin B12 deficient diets for 4-weeks prior to and after ischemic stroke to the sensorimotor cortex. Motor function was measured, and tissues were collected to assess potential mechanisms. All deficient mice had increased levels of total homocysteine in plasma and liver tissues. After ischemic stroke, deficient mice had impaired motor function compared to control mice. There was no difference between groups in lesion volume, however, there was an increase in total apoptosis within the ischemic region of brain tissue in male deficient mice. More neuronal survival was present in ischemic brain tissue of the deficient mice compared to controls. Additionally, there were changes in choline metabolites in ischemic brain tissue because of a vitamin B12 deficiency. The data presented in this study confirms that a vitamin B12 deficiency worsens stroke outcome in male and female mice. The mechanisms driving this change may be a result of neuronal survival and compensation in choline metabolism within the damaged brain tissue.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".