HIV Impacts CD34+ Progenitors Involved in T-Cell Differentiation During Coculture With Mouse Stromal OP9-DL1 Cells
Bibliographic record
Abstract
HIV-1 causes the loss of CD4+ T cells via depletion or impairment of their production. The latter involves infection of thymocytes, but the involvement of hematopoietic CD34+ cells remains unclear even though HIV-positive patients frequently manifest myelosuppression. In order to have a closer look at the impact of HIV-1 on T-lineage differentiation, this study utilized the OP9-DL1 coculture system, which supports in vitro T-lineage differentiation of human hematopoietic stem/progenitor cells. In the newly developed in vitro OP9-DL1/HIV-1 model, cord-derived CD34+ cells were infected with CXCR4-tropic HIV-1NL4-3 and cocultured. The HIV-infected cocultures exhibited reduced CD4+ T-cell growth at weeks 3–5 post infection compared to autologous uninfected cocultures. Further assays and analyses revealed that CD34+CD7+CXCR4+ cells can be quickly depleted as early as 1 week after infection of the subset, and this was accompanied by the emergence of rare CD34+CD7+CD4+ cells. A subsequent theoretical model analysis suggested potential influence of HIV-1 on the differentiation rate or death rate of lymphoid progenitor cells. These results indicate that CXCR4-tropic HIV-1 strains may impact the dynamics of CD34+CD7+ lymphoid progenitor cell pools, presumably leading to impaired T-cell production potential.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".