The importance of taking ART appropriately in children and adolescents with HIV-1 to reach the highest capacity of immune function later in life
Bibliographic record
Abstract
Current antiretroviral therapy (ART) guidelines recommend treating all children with HIV-1 infection. This has changed from the broader use of ART to treat children to improve morbidity and minimise mortality. However, prior to current recommendations, not everyone with HIV-1 received timely treatment. What happens to the paediatric immune system when HIV-1 replication is not appropriately supressed remains unclear. 11 samples from adolescents with HIV-1 on ART and uninfected controls in the UK, aged 12–25 years, were examined; overall, adolescents with CD4+counts > 500/μl and a viral load < 50 copies/ml were compared with adolescents with CD4+counts < 500/μl and a viral load > 50 copies/ml at time of sampling. Measurements of thymic output were combined with high throughput next generation sequencing and bioinformatics to systematically organize CD4+and CD8+T cell receptor (TCR) repertoires. TCR repertoire diversity, clonal expansions, TCR sequence sharing, and formation of TCR clusters in HIV-1 infected adolescents with successful HIV-1 suppression were compared to adolescents with ineffective HIV-1 suppression. Thymic output and CD4+T cell numbers were decreased in HIV-1 infected adolescents with poor HIV-1 suppression. A strong homeostatic TCR response, driven by the decreased CD4+T cell compartment and reduced thymic output was observed in the virally uncontrolled HIV-1-infected adolescents. Formation of abundant robust TCR clusters and structurally related TCRs were found in the adolescents with effective HIV-1 suppression. Numerous CD4+T cell numbers in the virally controlled adolescents emphasize the importance of high thymic output and formation of robust TCR clusters in the maintenance of HIV-1 suppression. While the profound capacity for immune recovery in children may allow better opportunity to deal with immunological stress, when ART is taken appropriately, this study demonstrates new insights into the unique paediatric immune system and the immunological changes when HIV-1 replication is ongoing.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".