Transforming growth factor β-2 is rhythmically expressed in both WT and BMAL1-deficient hypothalamic neurons and regulates neuropeptide Y: Disruption by palmitate
Bibliographic record
Abstract
The hypothalamus contains neuropeptide Y (NPY)-expressing neurons that control food intake and regulate energy homeostasis. During the development of obesity, neuroinflammation occurs in the hypothalamus before peripheral tissues, but the cytokines involved have not been thoroughly studied. Among them is the transforming growth factor beta (TGF-β) family of cytokines. Herein, we demonstrate that Tgfb 1-3, as well as its receptors Tgfbr1 and Tgfbr2, exhibit high levels of expression in the whole hypothalamus, primary hypothalamic culture, and immortalized hypothalamic neurons. Of interest, only Tgfb2 mRNA displays circadian expression in the immortalized hypothalamic neurons and maintains this rhythmicity in BMAL1-KO-derived hypothalamic neurons that are deficient of inherent clock gene rhythmicity. Although BMAL2 may serve as an alternative rhythm generation mechanism in the absence of BMAL1, its knockdown did not affect Tgfb2 expression. Treatment of immortalized NPY-expressing neurons with TGF-β2 upregulates the core circadian oscillators Bmal1 and Nr1d1, and importantly, also Npy mRNA expression. With obesity, the hypothalamus is exposed to elevated levels of palmitate, a saturated fatty acid that promotes neuroinflammation by upregulating pro-inflammatory cytokines. Palmitate treatment disrupts the expression of TGF-β signaling components, increases BMAL1 binding to the Tgfb2 5' regulatory region, and upregulates Npy mRNA, whereas antagonizing TGFBRI attenuates the upregulation of Npy. These results suggest that hypothalamic neuronal TGF-β2 lies at the intersection of circadian rhythms, feeding neuropeptide control, and neuroinflammation. A better understanding of the underlying mechanisms that link nutrient excess to hypothalamic dysfunction is critical for the development of effective prevention and treatment strategies.
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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) | 0.000 | 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) | 0.002 | 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".