Spontaneous pulmonary hypertension in genetic mouse models of natural killer cell deficiency
Bibliographic record
Abstract
Natural killer (NK) cells are cytotoxic innate lymphoid cells with an established role in the regulation of vascular structure in pregnancy and cancer. Impaired NK cell function has been identified in patients with pulmonary arterial hypertension (PAH), a disease of obstructive vascular remodeling in the lungs, as well as in multiple rodent models of disease. However, the precise contribution of NK cell impairment to the initiation and progression of PAH remains unknown. Here, we report the development of spontaneous pulmonary hypertension in two independent genetic models of NK cell dysfunction, including Nfil3−/− mice, which are deficient in NK cells due to the absence of the NFIL3 transcription factor, and Ncr1-Gfp mice, which lack the NK activating receptor NKp46. Mouse models of NK insufficiency exhibited increased right ventricular systolic pressure and muscularization of the pulmonary arteries in the absence of elevated left ventricular end-diastolic pressure, indicating that the development of pulmonary hypertension was not secondary to left heart dysfunction. In cases of severe NK cell impairment or loss, a subset of mice failed to develop pulmonary hypertension and instead exhibited reduced systemic blood pressure, demonstrating an extension of vascular abnormalities beyond the pulmonary circulation into the systemic vasculature. In both mouse models, the development of PAH was linked to elevated interleukin-23 production, whereas systemic hypotension in Ncr1-Gfp mice was accompanied by a loss of angiopoietin-2. Together, these results support an important role for NK cells in the regulation of pulmonary and systemic vascular function and the pathogenesis of PAH.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".