White matter microstructure among youth with perinatally acquired HIV is associated with disease severity
Bibliographic record
Abstract
OBJECTIVES: We investigated whether HIV disease severity was associated with alterations in structural brain connectivity, and whether those alterations in turn were associated with cognitive deficits in youth with perinatally acquired HIV (PHIV). DESIGN: PHIV youth (n = 40) from the Pediatric HIV/AIDS Cohort Study (PHACS) (mean age: 16 ± 2 years) were included to evaluate how current and past disease severity measures (recent/nadir CD4%; peak viral load) relate to white matter microstructure within PHIV youth. PHIV youth were compared with 314 controls from the Pediatric Imaging, Neurocognition and Genetics (PING) study. METHODS: Diffusion tensor imaging and tractography were utilized to assess white matter microstructure. Mediation analyses were conducted to examine whether microstructure alterations contributed to relationships between higher disease severity and specific cognitive domains in PHIV youth. RESULTS: Whole brain fractional anisotropy was reduced, but radial and mean diffusivity were increased in PHIV compared with control youth. Within PHIV youth, more severe past HIV disease was associated with reduced fractional anisotropy of the right inferior fronto-occipital (IFO) and left uncinate tracts; elevated mean diffusivity of the F minor; and increased streamlines comprising the left inferior longitudinal fasciculus (ILF). Associations of higher peak viral load with lower working memory performance were partly mediated by reductions in right IFO fractional anisotropy levels. CONCLUSION: Our findings suggest that PHIV youth have a higher risk of alterations in white matter microstructure than typically developing youth, and certain alterations are related to past disease severity. Further, white matter alterations potentially mediate associations between HIV disease and working memory.
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 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) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".