Thyroid‐Stimulating Hormone Stimulates Interleukin‐6 Release from 3T3‐L1 Adipocytes through a cAMP‐Protein Kinase A Pathway
Bibliographic record
Abstract
OBJECTIVE: Thyroid-stimulating hormone (TSH) is a novel modulator of adipokine release from human and mouse adipocytes. The aim of our study was to identify the signal transduction pathways activated by TSH that stimulate interleukin (IL)-6 production. RESEARCH METHODS AND PROCEDURES: Mouse 3T3-L1 preadipocyte and differentiated adipocyte cell cultures were studied. The effect of 0 to 1 microM TSH on IL-6 protein release into the medium over 0 to 24 hours was assessed. TSH signaling pathways responsible for regulating IL-6 were studied through the use of 1 muM forskolin, 100 microM 8-pCPT-2'-O-Me-cAMP, 10 microM H89, 50 microM PD98059, and 2 mug/mL actinomycin D. RESULTS: TSH stimulated IL-6 release by 2.6-fold from 3T3-L1 adipocytes at concentrations as low as 0.01 microM but did not alter IL-6 production of corresponding preadipocytes. Forskolin (elevates intracellular cAMP) stimulated IL-6 release from 3T3-L1 adipocytes (n = 3, p < 0.005), and H89, an inhibitor of cAMP-dependent protein kinase A (PKA), reduced TSH-stimulated IL-6 release by 66% (n = 3, p < 0.01), indicating a requirement for cAMP-dependent PKA. Inhibition of the mitogen-activated protein kinase pathway with PD98059 did not affect TSH-stimulated IL-6 release. Activation of an alternate cAMP target, the exchange protein of cAMP, with 8-pCPT-2'-O-Me-cAMP, had no effect on IL-6 release. TSH raised the level of IL-6 mRNA, and blockade of transcription with actinomycin D abrogated IL-6 protein release by TSH (n = 3, p < 0.05). DISCUSSION: TSH stimulates IL-6 release from differentiated 3T3-L1 adipocytes, but not preadipocytes, by signaling through cAMP-PKA to activate IL-6 gene transcription.
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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 | 0.001 |
| 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 | 0.001 |
| 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".