Immune regulation and vascular inflammation in genetic hypertension
Bibliographic record
Abstract
Immune cells have been implicated in the pathogenesis of hypertension. We hypothesized that under the influence of chromosome (chr)2, T lymphocytes contribute to vascular inflammation in genetic salt-sensitive hypertension. Normotensive (Brown Norway), hypertensive (Dahl salt-sensitive), and consomic rats (SSBN2; in which chr2 has been transferred from Brown Norway to Dahl rats) were studied. Systolic blood pressure, measured by tail cuff, and aortic preproendothelin mRNA, measured by quantitative RT-PCR, were elevated in Dahl rats compared with Brown Norway rats and were reduced in SSBN2 rats compared with Dahl rats (P < 0.01). Compared with Brown Norway rats, Dahl rats exhibited increased inflammatory markers and mediators such as nuclear translocation of the aortic p65 subunit of NF-kappaB as well as VCAM-1, ICAM-1, chemokine (C-C motif) receptor 5, and CD4 mRNA, all of which were reduced in SSBN2 rats. Aortic CD8 mRNA was equally increased in Dahl and SSBN2 rats relative to Brown Norway rats. CD4(+) T cell infiltration in the aorta of SSBN2 rats was reduced compared with Dahl rats, whereas the aortic protein expression of Foxp3b and immunosuppressors transforming growth factor (TGF)-beta(1) and IL-10, the three markers associated with the regulatory T cell lineage, were enhanced in SSBN2 rats. Activation in vitro of T cells demonstrated that CD4(+)CD25(+) and CD8(+)CD25(+) cells (Tregs) produce IL-10 in SSBN2 rats. Thus, increased vascular inflammatory responses and hypertension in a genetic salt-sensitive hypertensive rodent model are reduced by transfer of chr2 from a normotensive strain, and this is associated with enhanced levels of immunosuppressive mediators.
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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".