Plasma sCD14 Is a Biomarker Associated With Impaired Neurocognitive Test Performance in Attention and Learning Domains in HIV Infection
Bibliographic record
Abstract
OBJECTIVE: Mild forms of HIV-associated neurocognitive disorders (HAND) remain prevalent in the era of combination antiretroviral therapy (cART). Although elevated lipopolysaccharide (LPS) and immune activation are implicated in HAND pathogenesis, relationships of LPS and inflammatory markers to mild forms of HAND or impairment in specific cognitive domains are unknown. To examine these relationships, we compared plasma soluble CD14 (sCD14), CCL2, and LPS levels with neurocognitive test scores in a cART era cohort. METHODS: We analyzed plasma from HIV+ subjects (n = 97) with nadir CD4 counts <300 and high frequency of hepatitis C virus coinfection and illicit drug use for relationships between sCD14, CCL2, and LPS levels and neurocognitive test scores. RESULTS: Plasma sCD14 levels were higher in subjects with test scores indicating global impairment (P = 0.007), particularly in attention and learning domains (P = 0.015 and P = 0.03, respectively), regardless of HAND diagnosis. Plasma sCD14 levels correlated inversely with global, attention, and learning T scores (P = 0.036, 0.047, and 0.007, respectively) and yielded higher area under receiver operating characteristic values for predicting impaired scores than single-marker models based on plasma or cerebrospinal fluid viral load or CD4 count (area under receiver operating characteristic values = 0.71, 0.81, and 0.71, respectively) and in 4-marker models based on plasma sCD14 and 3 conventional markers compared with the 3-marker models. CONCLUSIONS: Plasma sCD14 is a biomarker associated with impaired neurocognitive testing in attention and learning domains in HIV-infected individuals with advanced disease, suggesting involvement of cortical and limbic pathways by inflammatory processes in the cART era. Plasma sCD14 is a potential biomarker to monitor HAND progression and therapeutic responses.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".