Association between intercellular adhesion molecule-1 to depression and blood-brain barrier penetration in cerebellar vascular disease
Bibliographic record
Abstract
BACKGROUND Cerebral small vessel disease (CSVD) is a prevalent cerebrovascular disease in clinical practice that is often associated with macrovascular disease. A clear understanding of the underlying causes of CSVD remains elusive. AIM To explore the association between intercellular adhesion molecule-1 (ICAM-1) and blood-brain barrier (BBB) penetration in CSVD. METHODS This study included patients admitted to Fuyang People’s Hospital and Fuyang Community (Anhui, China) between December 2021 and March 2022. The study population comprised 142 patients, including 80 in the CSVD group and 62 in the control group. Depression was present in 53 out of 80 patients with CSVD. Multisequence magnetic resonance imaging (MRI) and dynamic contrast-enhanced MRI were applied in patients to determine the brain volume, cortical thickness, and cortical area of each brain region. Moreover, neuropsychological tests including the Hamilton depression scale, mini-mental state examination, and Montreal cognitive assessment basic scores were performed. RESULTS The multivariable analysis showed that age [P = 0.011; odds ratio (OR) = 0.930, 95% confidence interval (CI): 0.880-0.983] and ICAM-1 levels (P = 0.023; OR = 1.007, 95%CI: 1.001-1.013) were associated with CSVD. Two regions of interest (ROIs; ROI3 and ROI4) in the white matter showed significant (both P < 0.001; 95%CI: 0.419-0.837 and 0.366-0.878) differences between the two groups, whereas only ROI1 in the gray matter showed significant difference (P = 0.046; 95%CI: 0.007-0.680) between the two groups. ICAM-1 was significantly correlated (all P < 0.05) with cortical thickness in multiple brain regions in the CSVD group. CONCLUSION This study revealed that ICAM-1 levels were independently associated with CSVD. ICAM-1 may be associated with cortical thickness in the brain, predominantly in the white matter, and a significant increase in BBB permeability, proposing the involvement of ICAM-1 in BBB destruction.
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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 | 0.001 |
| 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".