Innate adaptation: the influence of human cytomegalovirus on natural killer cells
Bibliographic record
Abstract
During their lifetime, over half the world’s population will experience chronic viral infection or cancer, both of which involve evasion of host immunity. We have within us immune cells called natural killer (NK) cells that constantly survey our tissues to detect and eliminate transformed and infected cells. Thus, they have a critical role in preventing cancer and containing virus infection. Although most viruses only disrupt our lives transiently, if at all, some viruses establish life-long persistent infection. Human cytomegalovirus (HCMV) is a common herpesvirus infecting most of the adult population and although relatively innocuous in healthy individuals, HCMV infection or reactivation has an enormous impact on the human immune system, poses serious health risks to the immunocompromised, and is an important cofactor driving ongoing immune activation in people living with HIV (PLWH). One outcome of HCMV infection is emergence of a stable differentiated population of phenotypically and functionally adapted NK cells exhibiting a form of memory. While mechanisms that create adapted NK cells in vivo remain enigmatic, exposure to HCMV is the one common factor underlying their presence. Exploring basic molecular mechanisms governing NK cell-mediated immunity can inform cell-based treatment strategies against virus infection or cancer. As chronic HIV-1 infection amplifies HCMV-driven accumulation of adaptive NK cells, we studied whether NK cell adaptation to HCMV infection functionally impacts their natural and antibody-dependent cytotoxic functions in this setting. Although factors present during HCMV infection augmented NK cell activity, we found no evidence that NK cells acquire superior cytotoxic function or capacity for interferon-γ secretion in response to target cells following adaptation to HCMV infection. However, HCMV-driven NK cell adaptation in HIV-1 infection paralleled increased expression of TIGIT, an inhibitory immune checkpoint receptor, on NK cells. As chronic virus infection contributes to effector cell dysfunction, punctuated by increased expression of inhibitory immune checkpoint receptors, it is important to unravel the mechanisms by which viruses affect regular NK cell functions to either prevent dysfunction or introduce disease-appropriate mediators to invigorate NK cell responses. Understanding basic molecular mechanisms governing NK cell-mediated immunity will inform new strategies to optimize our immune system capacities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".