Neurometabolite Alterations Associated With Cognitive Performance in Perinatally HIV-Infected Children
Bibliographic record
Abstract
Despite treatment with combination antiretroviral therapy (cART), cognitive impairment is still observed in perinatally HIV-infected children. We aimed to evaluate potential underlying cerebral injury by comparing neurometabolite levels between perinatally HIV-infected children and healthy controls. This cross-sectional study evaluated neurometabolites, as measured by Magnetic Resonance Spectroscopy (MRS), in perinatally HIV-infected children stable on cART (n = 26) and healthy controls (n = 36).Participants were included from a cohort of perinatally HIV-infected children and healthy controls, matched group-wise for age, gender, ethnicity, and socio-economic status. N-acetylaspartate (NAA), glutamate (Glu), myo-inositol (mI), and choline (Cho) levels were studied as ratios over creatine (Cre). Group differences and associations with HIV-related parameters, cognitive functioning, and neuronal damage markers (neurofilament and total Tau proteins) were determined using age-adjusted linear regression analyses.HIV-infected children had increased Cho:Cre in white matter (HIV-infected = 0.29 ± 0.03; controls = 0.27 ± 0.03; P value = 0.045). Lower nadir CD4+ T-cell Z-scores were associated with reduced neuronal integrity markers NAA:Cre and Glu:Cre. A Centers for Disease Control and Prevention (CDC) stage C diagnosis was associated with higher glial markers Cho:Cre and mI:Cre. Poorer cognitive performance was mainly associated with higher Cho:Cre in HIV-infected children, and with lower NAA:Cre and Glu:Cre in healthy controls. There were no associations between neurometabolites and neuronal damage markers in blood or CSF.Compared to controls, perinatally HIV-infected children had increased Cho:Cre in white matter, suggestive of ongoing glial proliferation. Levels of several neurometabolites were associated with cognitive performance, suggesting that MRS may be a useful method to assess cerebral changes potentially linked to cognitive outcomes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".