The <i>677C>T</i> variant in <i>methylenetetrahydrofolate reductase</i> causes morphological and functional cerebrovascular deficits in mice
Bibliographic record
Abstract
Abstract Vascular contributions to cognitive impairment and dementia (VCID) particularly Alzheimer’s disease and related dementias (ADRDs) are increasing; however, mechanisms driving cerebrovascular decline are poorly understood. Methylenetetrahydrofolate reductase (MTHFR) is a critical enzyme in the folate and methionine cycles. Variants in MTHFR , notably 677C>T , are associated with dementias, but no mouse model existed to identify mechanisms by which MTHFR 677C>T increases risk. Therefore, MODEL-AD created a novel knock-in (KI) strain carrying the Mthfr 677C>T allele on the C57BL/6J background ( Mthfr 677C>T ) to characterize morphology and function perturbed by the variant. Consistent with human clinical data, Mthfr 677C>T mice have reduced enzyme activity in the liver and elevated plasma homocysteine levels. MTHFR enzyme activity as well as critical metabolites in the folate and methionine cycles are reduced in the Mthfr 677C>T brain. Mice showed reduced tissue perfusion in numerous brain regions by PET/CT as well as significantly reduced vascular density and increased GFAP-expressing astrocytes in frontal cortex. Electron microscopy revealed cerebrovascular damage including endothelial and pericyte apoptosis, reduced luminal size, and increased astrocyte and microglial presence in the microenvironment. Collectively, these data suggest critical perturbations to cerebrovascular function in Mthfr 677C>T mice supporting its use as a model for preclinical studies of VCID.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".