Neutrophils contribute to T cell activation via reactive oxygen species production in HIV infection
Bibliographic record
Abstract
Abstract Neutrophils are the most abundant leukocytes in the human immune system contributing to 50–80% of all the white blood cells in the peripheral blood. Interestingly, the role of neutrophils in HIV infection has been poorly investigated. Previous studies have demonstrated that during HIV infection neutrophils are capable of both activating T cells and suppressing T cells. Our preliminary findings suggest that T cell activation could be modulated by neutrophils through various mechanisms. Galectin-9 has been demonstrated to play an integral role in HIV pathogenesis by suppressing CD8+ T cell function through the engagement with TIM-3. Interestingly, we have observed neutrophils have high expression of galectin-9, which is reduced after prolonged activation. In confirmation with previous studies demonstrating that HIV infected patients have hyperimmune activation, galectin-9 expression is decreased on neutrophils from HIV infected individuals, while the expression of the neutrophil activation marker CD32 is increased. Additionally, galectin-9 expression on neutrophils could be involved in suppressing T cell responses via. galectin-9:TIM-3 engagement. We found that neutrophils from HIV patients enhance T cells activation when co-cultured, whereas this was not the case for healthy controls. Interestingly, these effects could be reversed by inhibiting neutrophil reactive oxygen species (ROS) production. These findings suggest that HIV infection results in hyperimmune activation of neutrophils contributing to T cell activation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".