Targeted Killing of Virally Infected Cells by Radiolabeled Antibodies to Viral Proteins
Bibliographic record
Abstract
BACKGROUND: The HIV epidemic is a major threat to health in the developing and western worlds. A modality that targets and kills HIV-1-infected cells could have a major impact on the treatment of acute exposure and the elimination of persistent reservoirs of infected cells. The aim of this proof-of-principle study was to demonstrate the efficacy of a therapeutic strategy of targeting and eliminating HIV-1-infected cells with radiolabeled antibodies specific to viral proteins in vitro and in vivo. METHODS AND FINDINGS: Antibodies to HIV-1 envelope glycoproteins gp120 and gp41 labeled with radioisotopes bismuth 213 ((213)Bi) and rhenium 188 ((188)Re) selectively killed chronically HIV-1-infected human T cells and acutely HIV-1-infected human peripheral blood mononuclear cells (hPBMCs) in vitro. Treatment of severe combined immunodeficiency (SCID) mice harboring HIV-1-infected hPBMCs in their spleens with a (213)Bi- or (188)Re-labeled monoclonal antibody (mAb) to gp41 resulted in a 57% injected dose per gram uptake of radiolabeled mAb in the infected spleens and in a greater than 99% elimination of HIV-1-infected cells in a dose-dependent manner. The number of HIV-1-infected thymocytes decreased 2.5-fold in the human thymic implant grafts of SCID mice treated with the (188)Re-labeled antibody to gp41 compared with those treated with the (188)Re-control mAb. The treatment did not cause acute hematologic toxicity in the treated mice. CONCLUSIONS: The current study demonstrates the effectiveness of HIV-targeted radioimmunotherapy and may provide a novel treatment option in combination with highly active antiretroviral therapy for the eradication of HIV.
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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".