Bystander CD4 T-cell death is inhibited by broadly neutralizing anti-HIV antibodies only at levels blocking cell-to-cell viral transmission
Bibliographic record
Abstract
The progressive loss of CD4+ T cells during HIV infection of lymphoid tissues involves both the apoptotic death of activated and productively infected CD4 T cells and the pyroptotic death of large numbers of resting and abortively infected bystander CD4 T cells. HIV spreads both through cellular release of virions and cell-to-cell transmission involving the formation of virological synapses. Cell-to-cell transmission results in high-level transfer of large quantities of virions to the target cell exceeding that achieved with cell-free virions. Broadly neutralizing anti-HIV antibodies (bNAbs) binding to HIV envelope protein capably block cell-free virus spread, and when added at higher concentrations can also interdict cell-to-cell transmission. Exploiting these distinct dose-response differences, we now show that four different bNAbs block the pyroptotic death of bystander cells, but only when added at concentrations sufficient to block cell-to-cell transmission. These findings further support the conclusion that HIV killing of abortively infected bystander CD4 T cells requires cell-to-cell transfer of virions. As bNAbs attract more interest as potential therapeutics, it will be important to consider the higher concentrations of these antibodies required to block the inflammatory death of bystander CD4 T cells.
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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) | 0.002 | 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".