Interleukin‐7 levels may predict virological response in advanced HIV‐1‐infected patients receiving lopinavir/ritonavir‐based therapy
Bibliographic record
Abstract
OBJECTIVES: To examine the relationship between levels of the T-cell regulatory cytokine interleukin-7 (IL-7) and CD4 cell counts during immune reconstitution and to assess its prognostic value in advanced HIV-1-infected patients receiving lopinavir/ritonavir-based therapy. METHODS: Thirty-six HIV-1-infected adults who completed 48 weeks of follow-up visits were included in this prospective study. Patients having failed two or more antiretroviral therapy regimens were treated with lopinavir/ritonavir-based therapy. An enzyme-linked immunosorbent assay was used to determine IL-7 plasma levels, flow cytometry was used to analyse cell surface antigens, and polymerase chain reaction was used to quantify plasma HIV-1. RESULTS: Pretreatment IL-7 levels were elevated in all patients (mean 11.0 pg/mL) and were negatively correlated with CD4 cell counts and age (r=-0.59, P<0.001 and r=-0.57, P<0.001, respectively). During the course of treatment, IL-7 levels decreased by 34% while CD4 cell numbers progressively increased by 88%. Multivariate regression analysis showed that only pretreatment IL-7 levels predicted viral load at 48 weeks when controlling for baseline CD4 cell counts, viral load and patient demographics. CONCLUSIONS: These findings are consistent with regulation of T-cell recovery by IL-7, and suggest that IL-7 measurements might be used to predict virological response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".