Genetic ablation of bone marrow beta-adrenergic receptors in mice modulates miRNA-transcriptome networks of neuroinflammation in the paraventricular nucleus
Bibliographic record
Abstract
Elucidating molecular pathways regulating neuroimmune communication is critical for therapeutic interventions in conditions characterized by overactive immune responses and dysfunctional autonomic nervous system. We generated a bone marrow-specific adrenergic beta 1 and beta 2 knockout mouse chimera (AdrB1.B2 KO) to determine how sympathetic drive to the bone affects transcripts and miRNAs in the hypothalamic paraventricular nucleus (PVN). This model has previously exhibited a dampened systemic immune response and decreased blood pressure compared with control animals. Reduced sympathetic responsiveness of the bone marrow hematopoietic cells of AdrB1.B2 KO chimera led to suppression of transcriptional networks that included leukocyte cell adhesion and migration and T cell-activation and recruitment. Transcriptome responses related to IL-17a signaling and the renin-angiotensin system were also suppressed in the PVN. Based on the transcriptome response, we next computationally predicted miRNAs in the PVN that may underscore the reduced sympathetic responsiveness of the bone marrow cells. These included miR-27b-3p, miR-150, miR-223-3p, and miR-326. Using real-time PCR, we measured a downregulation in the expression of miR-150-5p, miR-205-5p, miR-223-3p, miR-375-5p, miR-499a-5p, miR-27b-3p, let-7a-5p, and miR-21a-5p in the PVN of AdrB1.B2 KO chimera, confirming computational predictions that these miRNAs are associated with reduced neuro-immune responses and the loss of sympathetic responsiveness in the bone marrow. Intriguingly, directional responses of the miRNA corresponded to mRNAs, suggesting complex temporal or circuit-dependent posttranscriptional control of gene expression in the PVN. This study identifies molecular pathways involved in neural-immune interactions that may act as targets of therapeutic intervention for a dysfunctional autonomic nervous system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".