Biomarkers and neurodevelopment in perinatally HIV-infected or exposed youth
Bibliographic record
Abstract
OBJECTIVE: To examine the relationship between markers of vascular dysfunction and neurodevelopmental outcomes in perinatally HIV-infected (PHIV+) and perinatally HIV-exposed but uninfected (PHEU) youth. DESIGN: Cross-sectional design within a prospective, 15-site US-based cohort study. METHODS: Neurodevelopmental outcomes were evaluated in relation to nine selected vascular biomarkers in 342 youth (212 PHIV+, 130 PHEU). Serum levels were assessed for adiponectin, C-reactive protein (CRP), fibrinogen, interleukin-6 (IL-6), soluble vascular cell adhesion molecule-1 (sVCAM-1), E-selectin (sE-selectin), monocyte chemoattractant protein (sMCP-1), intercellular adhesion molecule-1 (sICAM-1), and P-selectin (sP-selectin). The Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) was administered at entry, yielding a Full-Scale IQ score, and four index scores. Factor analysis was conducted to reduce the biomarkers to fewer factors with related biological roles. Structural equation models (SEMs) were used to measure associations between resulting factors and WISC-IV scores. RESULTS: Mean participant age was 11.4 years, 54% were female, 70% black. The nine biomarkers were clustered into three factor groups: F1 (fibrinogen, CRP, and IL-6); F2 (sICAM-1 and sVCAM-1); and F3 (MCP-1, sP-selectin, and sE-selectin). Adiponectin showed little correlation with any factor. SEMs revealed significant negative association of F1 with WISC-IV processing speed score in the total cohort. This effect remained significant after adjusting for HIV status and other potential confounders. A similar association was observed when restricted to PHIV+ participants in both unadjusted and adjusted SEMs. CONCLUSION: Aggregate measures of fibrinogen, CRP, and IL-6 may serve as a latent biomarker associated with relatively decreased processing speed in both PHIV+ and PHEU youth.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".