Investigating the immunological role of galectin-9 on natural killer (NK) cells in human immunodeficiency virus (HIV)
Bibliographic record
Abstract
Abstract NK cells play an integral role in mediating immune responses to viral infections; however, their function is compromised during chronic diseases such as HIV, partly due to an increase expression of inhibitory receptors. Thus, the reduced immune responses elicited by NK cells in HIV can be the result of the engagement of inhibitory immune checkpoint molecules with their respective ligands. Galectin-9 (Gal-9) is a tandem-repeat type galectin that possess a wide range of immunomodulatory properties such as interacting with Tim-3, which is upregulated on T cells during chronic conditions. Previously, our group has shown that interaction of Gal-9 on regulatory T cells with Tim-3 on CD8+T cells, renders these T cells more permissible to immunosuppression and subsequently leads to their exhaustion. We aimed to further study the role of Gal-9 on NK cell function in HIV patients. As a comparison, we also analyzed another inhibitory receptor known as TIGIT. Our preliminary data indicates upregulation of surface Gal-9 on NK cells in HIV infected individuals when compared to healthy controls. We observed two effector NK cell populations with dichotomous functionality. TIGIT+NK cells expressed more cytotoxic molecules (GzmB and perforin) and less IFNγ. Conversely, Gal-9+NK cells expressed less cytotoxic molecules, but more IFNγ. Additionally, Gal-9+NK cells, in contrast to Gal-9−NK cells, co-express negligible amounts of GzmB and perforin, which is detrimental to their cytotoxic abilities. We believe that understanding the underlying biochemical pathway associated with Gal-9+NK cell dysfunction can pave the way for potential therapeutic strategies.
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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 | 0.000 |
| 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".