246-LB: Stimulation of Hepatic Lipid Secretion by Glucocorticoid Action in the Nucleus of the Solitary Tract
Bibliographic record
Abstract
Dysregulated lipid metabolism is a characteristic of diabetes, insulin resistance, and obesity. Increased glucocorticoid (GC) levels and/or action is associated with elevated levels of circulating triglyceride (TG)-rich very low-density lipoproteins (VLDL-TGs). Lipid metabolism is heavily affected by GCs via its direct actions on peripheral organs, e.g. liver, adipose tissue. However, how GCs modulate hepatic VLDL-TG secretion via their actions in the brain is less known. The nucleus of the solitary tract (NTS) in the hindbrain is responsive to various hormones and is an important region involved in whole-body metabolism. Here, we aimed to assess how GC action in the NTS affects hepatic TG secretion and hypothesized that GC receptor (GR) agonism in the NTS stimulates hepatic TG secretion. Sprague-Dawley rats underwent stereotaxic NTS bilateral cannulation and vascular catheterizations to enable simultaneous direct NTS infusions, intravenous injections, and blood sampling. Hepatic TG secretion rates were measured in 10h-fasted rats after intravenous poloxamer injection with concurrent NTS infusions. NTS GC infusion stimulated TG secretion compared to NTS vehicle controls, but this effect was negated with pharmacological and genetic GR antagonism, suggesting that NTS GCs are mediated via its receptor. The NTS GC-induced increase in VLDL-TG was not associated with changes in liver lipogenic gene expression and protein levels or plasma ApoB48/100. However, plasma FFAs were increased in NTS GC infused rats, and this was associated with increased pHSL:HSL protein levels in white adipose tissue. We herein provide evidence that acute GC action in the NTS stimulates hepatic VLDL-TG secretion and affects adipose tissue lipid metabolism. Increased circulating FFA availability may contribute to the hyperlipidemic effects of NTS GCs. Future studies to assess the role of NTS GC action in diabetic and obesity-related metabolic disease dyslipidemic models are warranted. Disclosure B. Vasilev: None. M. S. Grewal: None. B. Lum: None. J. T. Yue: None. Funding Natural Sciences and Engineering Research Council of Canada (RGPIN-2016-06657); Canada Foundation for Innovation (37267); Canada Research Chairs Tier 2 in Brain Regulation of Metabolism
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".