Selective Reduction of Blood Flow to White Matter During Hypercapnia Corresponds With Leukoaraiosis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Age-related white matter disease (leukoaraiosis) clusters in bands in the centrum semiovale, about the occipital and frontal horns of the lateral ventricles, in the corpus callosum, and internal capsule. Cerebrovascular anatomy suggests that some of these locations represent border zones between arterial supply territories. We hypothesized that there are zones of reduced cerebrovascular reserve (susceptible to selective reductions in blood flow, ie, steal phenomenon) in the white matter of young, healthy subjects, the physiological correlate of these anatomically defined border zones. Furthermore, we hypothesized that these zones spatially correspond with the regions where the elderly develop leukoaraiosis. METHODS: Twenty-eight healthy volunteers underwent functional MR mapping of the cerebrovascular response to hypercapnia. We studied 18 subjects by blood oxygen level-dependent MRI and 10 subjects by arterial spin labeling MRI. We controlled both end-tidal pCO(2) and pO(2). All functional data was registered in Montreal Neurological Institute space and generated composite blood oxygen level-dependent MR and arterial spin labeling MR maps of cerebrovascular reserve. We compared these maps with frequency maps of leukoaraiosis published previously. RESULTS: Composite maps demonstrated significant (90% CI excluding the value zero) steal phenomenon in the white matter. This steal was induced by relatively small changes in end-tidal pCO(2). It occurred precisely in those locations where elderly patients develop leukoaraiosis. CONCLUSIONS: This steal phenomenon likely represents the physiological correlate of the previously anatomically defined internal border zones. Spatial concordance with white matter changes in the elderly raises the possibility that this steal phenomenon may have a pathogenetic role.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".