Proportion of HIV-1 Infected CD8+CD4- T Lymphocytes In Vivo
Bibliographic record
Abstract
The proportion and significance of HIV-1 infection of CD8+ T-cells was examined in a patient cohort of HIV-1 seropositive (n=28) and seronegative individuals (n=4). It was hypothesized that irrespective of the clinical status of the patients, productively HIV-1 infected CD8+ T-cells would be found and these cells would contribute to the plasma viral load in vivo. Flow cytometric analysis using fluorochrome-conjugated antibodies, RT-PCR analysis using HIV-1(pol) specific primers, and quantification of HIV-1 viral transcripts by ex vivo culture of isolated CD8+ T-cells were employed. In 22 of the 28 patient samples analyzed, a significantly higher proportion of cells with expression of CD8+HIV-1(gag)+ than of CD4+HIV-1(gag)+ T-cells was observed (36.9% +/- 10.0% vs 26.4% +/- 13.1% respectively, p< 0.01). No correlation was observed between absolute CD4 counts, CD8 counts, plasma viral load and CD8+ T cell infection. RT-PCR analysis indicated the presence of HIV-1 transcripts in the ex vivo isolated CD8+ T-cell population. Ex vivo isolated CD8+ T-cells demonstrated productive infection over time. We conclude, with three lines of evidence detecting and measuring HIV-1 infection of CD8+ T-lymphocytes, that this cellular target and reservoir may be central to HIV-1 pathogenesis.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".