Variation in HIV-1 Tat and Vpr protein amino acid sequences and its association with vascular health measures in a South African cohort: an exploratory study
Bibliographic record
Abstract
OBJECTIVES: Human immunodeficiency virus (HIV)-1 is associated with adverse cardiovascular-related outcomes. Subtype-specific variations in the amino acid sequences of Tat and Vpr HIV-1 proteins are associated with differential clinical outcomes in people living with HIV (PLHIV). Given the diverse clinical outcomes related to different HIV subtypes, it is crucial to evaluate the variations in the sequence of Tat and Vpr amino acids in geographical regions where subtype C predominates, such as South Africa. This study aimed to determine whether specific Tat and Vpr protein amino acid variants (alone or in combination) are associated with vascular health measures and predict incident hypertension and all-cause mortality over a five-year period. METHODS: A cohort of n = 60 treatment-naïve PLHIV at baseline and n = 35 at a five-year follow-up was investigated. Standardized vascular health measures, including carotid intima-media thickness (cIMT), cross-sectional wall area (CSWA) and carotid-radial pulse wave velocity (crPWV), as well as Sanger sequencing for Tat/Vpr analysis, were performed. The associations of vascular health measures with Tat and Vpr amino acid variants were investigated. RESULTS: We found that the variation in amino acid sequence in Tat only (p = 0.039) and Tat/Vpr (p < 0.001) were associated with crPWV at baseline. Variation in the Tat and Vpr amino acid sequence did not predict incident hypertension in five years or all-cause mortality. CONCLUSION: The variants of the Tat and Vpr amino acid sequence were associated with arterial stiffness, which may be an underlying mechanism for cardiovascular disease development in PLHIV.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".