Abstract 075: The Role of Immunological CD8+ Effector Memory T Cells In Hypertension
Bibliographic record
Abstract
Immunological memory is an important component of adaptive immunity. We have previously shown that T cells are important in hypertension. We therefore hypothesized that memory T cells contribute to long-term and repeated hypertensive challenges. To test this, mice received 2 weeks of angiotensin II, were allowed to recover for 3 weeks and then were received a low dose of ang II (140 ng/kg/min) that minimally raises blood pressure in naïve mice. This low-dose of ang II increased blood pressure to 137±6 mmHg in mice that had previously received a vehicle infusion, but to 172±12 mmHg in mice that had received ang II. In another model we treated mice with L-NAME (0.5mg/ml) in drinking water for two weeks, and then fed a high salt diet (4% NaCl) two weeks after stopping L-NAME. The high salt diet had no effect on blood pressure in naïve mice, but increased blood pressure to 150±6 mmHg in mice that had received L-NAME. In keeping with a memory T cell response, we found that either the ang II or L-NAME and high salt protocols increased CD8+ effector memory cells in the kidney by 4-fold while reducing these effector memory CD8+ T cells in the spleen by 3-fold. CD8+ memory T cells require co-stimulatory signaling between CD70 on macrophages and CD27 on T cells. We found that ang II infusion increased CD70 mRNA in isolated kidney vessels by 5 to 10-fold. Similarly, flow cytometry revealed that ang II increased macrophages expressing CD70 and CD8+ T cells expressing CD27 expression in the kidney. Preliminary results show that anti-CD70 partially blocked memory formation by reducing the hypertensive response to the second low-dose of ang II by about 20 mmHg. Thus, these studies indicate that repeated exposures to ang II promote an immune memory response of CD8+ T cells and markedly enhance the hypertensive response. The role of CD27 and CD70 signaling requires additional study but might serve as a therapeutic target.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".