Reciprocal modulation of helper Th1 and Th17 cells by the β2‐adrenergic receptor agonist drug terbutaline
Bibliographic record
Abstract
Catecholamine hormones are powerful regulators of the immune system produced by the sympathetic nervous system (SNS). They regulate the adaptive immune system by altering T‐cell differentiation into T helper (Th) 1 and Th2 cell subsets, but the effect on Th17 cells is not known. Th17 cells, defined, in part, by chemokine receptor CCR 6 and cytokine interleukin ( IL )‐17A, are crucial for mediating certain pathogen‐specific responses and are linked with several autoimmune diseases. We demonstrated that a proportion of human Th17 cells express beta 2‐adrenergic receptor (β2AR), a G protein‐coupled receptor that responds to catecholamines. Activation of peripheral blood mononuclear cells, which were obtained from venous blood drawn from healthy volunteers, with anti‐cluster of differentiation 3 (CD3) and anti‐ CD 28 and with a β2‐agonist drug, terbutaline (TERB), augmented IL ‐17A levels ( P < 0.01) in the majority of samples. TERB reduced interferon gamma (IFNγ) indicating that IL ‐17A and IFN γ are reciprocally regulated. Similar reciprocal regulation was observed with dbc AMP . Proliferation of Th cells was monitored by carboxyfluorescein diacetate N ‐succinimidyl ester labeling and flow cytometry with antibody staining for CD 3 and CD 4. TERB increased proliferation by a small but significant margin ( P < 0.001). Next, Th17 cells ( CD 4 + CXCR 3 − CCR 6 + ) were purified using an immunomagnetic positive selection kit, which removes all other mononuclear cells. TERB increased IL ‐17A from purified Th17 cells, which argues that TERB acts directly on Th17 cells. Thus, hormone signals from the SNS maintain a balance of Th cells subtypes through the β2AR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".