Improvement of HIV-Specific Immunity in HIV-Infected Twins Treated with Highly Active Antiretroviral Therapy, Interleukin 2, and Syngeneic Adoptively Transferred Cells
Bibliographic record
Abstract
Five HIV-seropositive twins were treated with HAART and given cycles of treatment consisting of adoptive cellular therapy from their HIV-seronegative identical twins followed by a 5-day course of intravenous IL-2. Changes in absolute and percent CD4(+) and CD8(+) cell count were monitored and compared with changes in these parameters occurring in seven age-, sex-, and disease stage-matched HIV-infected patients treated with HAART alone. Increase in the magnitude and breadth of HIV-specific immune responses was monitored in three twin subjects who received multiple treatment cycles. Absolute and percent CD4(+) cell counts rose dramatically and to significantly higher levels in the recipient twins than in control subjects treated with HAART only. The subjects who received multiple cycles of treatment developed new and increased levels of HIV-specific activated and memory cytotoxic T lymphocyte responses, and interferon gamma-secreting effector cells. Treatment consisting of HAART, adoptive cellular therapy, and IL-2 was superior to treatment with HAART alone for improving absolute and percent CD4(+) cell counts and inducing new, or increasing the magnitude of, HIV-specific immune responses in HIV infected patients.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".