Abstract P2011: Chronic Systemic Administration of Pro-Inflammatory Cytokines Causes Cardiovascular Dysfunction and Downregulates Brain Expression of Regulator of G-Protein Signaling-10 in Rats
Bibliographic record
Abstract
Systemic pro-inflammatory cytokines (PICs) promote central oxidative stress and neuroinflammation that contribute to sympathetic excitation and cardiovascular dysfunction in hypertension and heart failure. However, the key molecular regulators of neuroinflammatory responses in the brain remain unclear. Regulator of G-protein Signaling-10 (RGS10), a GTPase-accelerating protein that is expressed predominantly in the brain, has recently emerged as an important counter regulator of PICs-induced downstream signaling in the central nervous system. RGS10 negatively regulates NF-kB-mediated inflammatory responses in microglia and antagonizes neurotoxic effects of peripheral inflammation. The present study examined whether peripherally administered PICs alter RGS10 expression in cardiovascular/autonomic brain regions like subfornical organ (SFO) and hypothalamic paraventricular nucleus (PVN). Male SD rats received a 2-week subcutaneous infusion of vehicle, interleukin (IL)-1β (400 ng/day) and tumor necrosis factor (TNF)-α (600 ng/day). Rats treated with IL-1β (n=6) or TNF-α (n=6) had significantly (*P<0.05) reduced mRNA level (fold change) of RGS10 in SFO (0.60±0.15* or 0.69±0.16* vs 1.03±0.28; IL-1β or TNF-α, vs vehicle treatment) and PVN (0.72±0.15* or 0.71±0.19* vs 1.02±0.24), and lessoned mRNA level of NF-kB inhibitor IkB-α (SFO: 0.60±0.21* or 0.55±0.16* vs 1.07±0.46; PVN: 0.70±0.31* or 0.82±0.16* vs 1.00±0.07). Treatments with IL-1β or TNF-α increased mRNA level of NADPH oxidase 2 (SFO: 1.96±0.91* or 1.62±0.47* vs 1.03±0.28; PVN: 2.00±0.82* or 1.74±0.70* vs 1.00±0.15) and cyclooxygenase-2 (SFO: 1.78±0.76* or 1.98±1.04* vs 1.00±0.13; PVN: 1.68±0.34* or 1.62±0.57* vs 1.02±0.24). Rats treated with IL-1β or TNF-α had elevated mean blood pressure (98±11* or 100±9* vs 84±5 mmHg) and increased sympathetic activity as indicated by pressure response to ganglionic blockade (38±7 * or 36±6* vs 28±4 mmHg). Additionally, IL-1β or TNF-α-treated rats had increased cardiac fibrotic markers and impaired cardiac diastolic function. These results suggest that circulating PICs reduce RGS10 expression in the brain, which may contribute to sympathetic excitation and cardiovascular dysfunction in inflammatory conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".