Genetic ablation of bone marrow beta‐adrenergic receptors alters miRNA‐transcriptome networks for microglia activation and inflammation in the paraventricular nucleus of the hypothalamus
Bibliographic record
Abstract
Hypertension (HTN) is a preventable condition with complex etiology. Neurogenic origins of HTN such as aberrant signaling in the paraventricular nucleus (PVN) of the hypothalamus remain a high priority for therapeutic interventions, as most anti‐HTN treatments remain ineffective in a significant portion of patients. Discerning the molecular mechanisms underlying neurogenic HTN is critical for understanding how an overactive sympathetic drive contributes to high blood pressure. We generated a novel bone marrow‐specific adrenergic beta 1 and beta 2 knockout mouse chimera (AdrB1.B2 KO mouse) to study how sympathetic drive to the bone, or lack thereof, affects the molecular responses in the PVN. These mice have previously been characterized by dampened systemic immune responses and decreased blood pressure during the active period. Here, loss of sympathetic drive in the AdrB1.B2 KO chimera lead to an overwhelming suppression of transcriptional networks in the PVN that included leukocyte cell adhesion and migration as well as lymphocyte activation and adhesion, and T cell‐ activation and recruitment. Furthermore, transcriptome networks associated with astroglia, microglial, and neuronal function were suppressed in the PVN of AdrB1.B2 KO chimera. Transcriptional networks related to IL‐17a signaling and the renin‐angiotensin system related genes were also suppressed in the PVN of the AdrB1.B2 KO chimera. Using computational predictive tools, we identified a number of miRNAs expected to regulate global transcriptome responses in the PVN. These included miR‐27b3p, miR‐150, miR‐223, and miR‐326, some of which have been implicated in HTN. In addition, using qPCR, we observed a downregulation in the relative expression of miR‐150, miR‐205, miR‐223, miR‐375, miR‐499a, and miR‐27b3p in the PVN of AdrB1.B2 KO chimera, thus in part confirming the results of computational predictive tools. This study identifies novel molecular mechanisms involved in neural‐immune interactions that underlie neurogenic HTN and elucidate new pathways for therapeutic intervention. Support or Funding Information Supported by AHA grant 14SDG18300010 to JZ and NIH R21AT010192 Award AWD05242 P0104932 to CJM and JZ.
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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".