Xenogeneic β2-Microglobulin Substitution Alters NK Cell Function
Bibliographic record
Abstract
Recently, it has been shown that human beta(2)-microglobulin (h-beta(2)m) blocks the association between the NK cell inhibitory receptor Ly49C and H-2K(b). Given this finding, we therefore sought to assess the immunobiology of NK cells derived from C57BL/6 (H-2(b)) mice expressing exclusively h-beta(2)m. Initial analysis revealed that the Ly49C expression profile of NK cells from h-beta(2)m(+) mice was modified, despite the fact that H-2K(b) expression was normal in these mice. Moreover, the NK cells were not anergic in that IL-2 treatment of h-beta(2)m(+) NK cells in vitro enabled efficient lysis of prototypic tumor cell lines as well as of syngeneic h-beta(2)m(+) lymphoblasts. This loss of self-tolerance appeared to correlate with the activation status of h-beta(2)m(+) NK cells because quiescent h-beta(2)m(+) transplant recipients maintained h-beta(2)m(+) grafts but polyinosine:polycytidylic acid-treated recipients acutely rejected h-beta(2)m(+) grafts. NK cell reactivity toward h-beta(2)m(+) targets was attributed to defective Ly49C interactions with h-beta(2)m:H-2K(b) molecules. With regard to NK cell regulatory mechanisms, we observed that h-beta(2)m:H-2K(b) complexes in the cis-configuration were inefficient at regulating Ly49C and, furthermore, that receptor-mediated uptake of h-beta(2)m:H-2K(b) by Ly49C was impaired compared with uptake of mouse beta(2)m:H-2K(b). Thus, we conclude that transgenic expression of h-beta(2)m alters self-MHC class I in such a way that it modulates the NK cell phenotype and interferes with regulatory mechanisms, which in turn causes in vitro-expanded and polyinosine:polycytidylic acid-activated NK cells to be partially self-reactive similar to what is seen with NK cells derived from MHC class I-deficient mice.
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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".