Molecular and Clinical Epidemiology of CXCR4-Using HIV-1 in a Large Population
Bibliographic record
Abstract
Objective. We wished to characterize the epidemiological and clinical correlates of CXCR4-using human immunodeficiency virus type 1 (HIV-1) (“X4 variants”) in a cross-sectional analysis of a large population of anti-retroviral-naive individuals. Methods. HIV-1 coreceptor use was determined in the last pretherapy plasma sample for 1191 individuals initiating triple-combination therapy in British Columbia, Canada. Baseline variables investigated included so-ciodemographic characteristics, plasma viral load (pVL), CD4 cell count, AIDS diagnosis, HIV-1 V3 loop sequence, and human CCR5 D32 genotype. Results. Individuals harboring X4 variants ( of 979 phenotyped samples; 18.2%) displayed a poorernp 178 baseline clinical profile than individuals harboring exclusively CCR5-using HIV-1 (“R5 variants”) (median pVL, 175,000 vs. 120,000 copies of HIV-1 RNA/mL []; median CD4 cell count, 110 vs. 290 cells/mm3 [Pp.0006 P!]). Individuals heterozygous for the CCR5 D32 deletion ( of 967; 13.2%) were at 2.5 times higher.0001 np 128 risk of harboring X4 variants, compared with those without the deletion (multivariate). The presencePp.0005 of basic amino acids at codon 11 and/or codon 25 of HIV-1 V3 ( of 955; 11.4%) was associated with anp 109 9.1 times higher risk of harboring X4 variants (multivariate), regardless of CCR5 D32 genotype. In mul-P!.0001 tivariate analyses adjusting for baseline parameters, HIV-1 coreceptor use was not found to be a significant predictor of survival or treatment response.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".