Estrogen-related receptor-α is a metabolic regulator of effector T-cell activation and differentiation
Why this work is in the frame
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Bibliographic record
Abstract
Stimulation of resting CD4(+) T lymphocytes leads to rapid proliferation and differentiation into effector (Teff) or inducible regulatory (Treg) subsets with specific functions to promote or suppress immunity. Importantly, Teff and Treg use distinct metabolic programs to support subset specification, survival, and function. Here, we describe that the orphan nuclear receptor estrogen-related receptor-α (ERRα) regulates metabolic pathways critical for Teff. Resting CD4(+) T cells expressed low levels of ERRα protein that increased on activation. ERRα deficiency reduced activated T-cell numbers in vivo and cytokine production in vitro but did not seem to modulate immunity through inhibition of activating signals or viability. Rather, ERRα broadly affected metabolic gene expression and glucose metabolism essential for Teff. In particular, up-regulation of Glut1 protein, glucose uptake, and mitochondrial processes were suppressed in activated ERRα(-/-) T cells and T cells treated with two chemically independent ERRα inhibitors or by shRNAi. Acute ERRα inhibition also blocked T-cell growth and proliferation. This defect appeared as a result of inadequate glucose metabolism, because provision of lipids, but not increased glucose uptake or pyruvate, rescued ATP levels and cell division. Additionally, we have shown that Treg requires lipid oxidation, whereas Teff uses glucose metabolism, and lipid addition selectively restored Treg--but not Teff--generation after acute ERRα inhibition. Furthermore, in vivo inhibition of ERRα reduced T-cell proliferation and Teff generation in both immunization and experimental autoimmune encephalomyelitis models. Thus, ERRα is a selective transcriptional regulator of Teff metabolism that may provide a metabolic means to modulate immunity.
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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 it