Influence of RANTES, SDF‐1 and TGF‐β levels on the value of interleukin‐7 as a predictor of virological response in HIV‐1‐infected patients receiving double boosted protease inhibitor‐based therapy
Bibliographic record
Abstract
OBJECTIVES: Interleukin-7 (IL-7), RANTES (regulated on activation, normal T cell expressed and secreted), stromal cell-derived factor-1 (SDF-1) and transforming growth factor-beta (TGF-beta) appear to share certain biological properties in vitro and all are involved in HIV-1 disease progression. Our earlier observations indicated that IL-7 levels decrease upon CD4 T-cell recovery and represent a new, independent predictor of virological response. Here, we examine associations among circulating levels of IL-7, RANTES, SDF-1 and TGF-beta in hopes of gaining insight into their contribution to the predictive value of IL-7. METHODS: Levels of IL-7, RANTES, SDF-1 and TGF-beta, and immune and viral parameters were assessed in HIV-1-infected patients. RESULTS: Cross-sectional (n=148) and longitudinal (n=36) analyses showed that levels of IL-7, but not RANTES, SDF-1 or TGF-beta, were increased in HIV-1-infected adults compared with those of healthy controls. In the cross-sectional study, levels of IL-7 were correlated with RANTES (r=0.31, P=0.002) and TGF-beta (r=0.53, P<0.001) but not with SDF-1 (r=0.12, P=0.22), and these associations were more pronounced in patients with CD4 T-cell counts >200 cells/microL. In contrast to IL-7, levels of RANTES, SDF-1 and TGF-beta were not correlated with CD4 T-cell counts. Longitudinal analysis revealed a marked decline in IL-7 levels accompanied by an increase in CD4 T-cell count following antiretroviral therapy (ART), but no changes in RANTES, SDF-1 or TGF-beta levels. Multivariate regression analysis showed no influence of baseline RANTES, SDF-1 or TGF-beta levels on the value of IL-7 as a predictor of virological response at 48 weeks. CONCLUSIONS: Collectively, these results indicate that changes in IL-7 levels did not induce changes in RANTES, SDF-1 or TGF-beta. Furthermore, they indicate that RANTES, SDF-1 or TGF-beta levels do not explain the predictor value of IL-7 in patients receiving ART.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".