Cigarette smoking is associated with reduced neuroinflammation and better cognitive control in people living with HIV
Bibliographic record
Abstract
People living with HIV (HIV+) are roughly twice as likely to smoke cigarettes (Smok+) as the general population. With the advent of effective antiretroviral therapies, it is increasingly important to understand the effects of chronic HIV infection and cigarette smoking on brain function and cognition since HIV+ individuals have heightened neuroinflammation and cognitive deficits even with such therapies. Based on prior studies demonstrating that smoking reduces a marker for neuroinflammation in HIV- individuals, we hypothesized that HIV+/Smok+ individuals would have less neuroinflammation and better cognitive control than HIV+/Smok- individuals. Fifty-nine participants (HIV-/Smok- [n = 16], HIV-/Smok+ [n=14], HIV+/Smok- [n = 18], and HIV+/Smok+ [n = 11]) underwent baseline eligibility tests, positron emission tomography (PET) scanning to determine levels of a marker for neuroinflammation, and assessment of cognitive control with the reverse-translated 5-choice continuous performance test (5C-CPT), with smokers having smoked to satiety prior to testing. For the PET data, a significant effect of smoking status on whole brain (WB) standardized uptake value (SUV) was found between HIV+/Smok+ and HIV+/Smok- participants (due to 18.8% lower WB SUV in the HIV+/Smok+ group). HIV+/Smok- participants exhibited a mean 13.5% higher WB SUV than HIV-/Smok- participants. For the 5C-CPT, HIV+/Smok+ participants performed significantly better than HIV+/Smok- participants (d prime), and HIV+/Smok- participants performed worse than HIV-/Smok- participants. Thus, HIV+/Smok+ individuals demonstrated lower levels of the neuroinflammation marker and better cognitive control than HIV+/Smok- individuals. Given that HIV+ individuals whose HIV is well-controlled can still have chronic neurocognitive complications, study results suggest possible paths for future research into nicotine-related treatments to prevent such complications.
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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 | 0.001 | 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".