Cerebral blood flow in relation to peripheral endothelial function in youth bipolar disorder
Bibliographic record
Abstract
INTRODUCTION: Anomalous cerebral blood flow (CBF) is evident in bipolar disorder (BD), however the extent to which CBF reflects peripheral vascular function in BD is unknown. This study investigated endothelial function, an index of early atherosclerosis and cardiovascular disease risk, in relation to CBF among youth with BD. METHODS: Participants included 113 youth, 13-20 years old (66 BD; 47 healthy controls [HC]). CBF was measured using arterial spin labeling with 3T MRI. Region of interest analyses (ROI; global grey matter, middle frontal gyrus, anterior cingulate cortex, temporal cortex, caudate) were undertaken alongside voxel-wise analyses. Reactive hyperemia index (RHI), a measure of endothelial function, was assessed non-invasively via pulse amplitude tonometry. General linear models were used to examine RHI and RHI-by-diagnosis associations with CBF, controlling for age, sex, and body mass index. Bonferroni correction for multiple comparisons was used for ROI analyses, such that the significance level was divided by the number of ROIs (α = 0.05/5 = 0.01). Cluster-extent thresholding was used to correct for multiple comparisons for voxel-wise analyses. RESULTS: ROI findings were not significant after correction. Voxel-wise analyses found that higher RHI was associated with lower left thalamus CBF in the whole group (p < 0.001). Additionally, significant RHI-by-diagnosis associations with CBF were found in three clusters: left intracalcarine cortex (p < 0.001), left thalamus (p < 0.001), and right frontal pole (p = 0.006). Post-hoc analyses showed that in each cluster, higher RHI was associated with lower CBF in BD, but higher CBF in HC. CONCLUSION: We found that RHI was differentially associated with CBF in youth with BD versus HC. The unanticipated association of higher RHI with lower CBF in BD could potentially reflect a compensatory mechanism. Future research, including prospective studies and experimental designs are warranted to build on the current findings.
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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 | 0.001 |
| 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) | 0.002 | 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".