GABA exerts anti-inflammatory and immunosuppressive effects (P5175)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Gamma amino-butyric acid (GABA) is an inhibitory neurotransmitter in the CNS, but it also exerts important functions in the immune system and the islets of Langerhans. Thus, functional GABA receptors have been identified on immune cells and islet cells. Previously, we found that in both autoimmune (NOD) and streptozotocin (STZ)-induced diabetes GABA increases islet-cell mass, while exerting anti-apoptotic effects. GABA induced the regeneration of islet beta cells. It also suppressed inflammatory cytokine production, which is likely important in allowing survival of new islet beta cells. In this study, we examine how GABA exerts immunoprotective effects. We report that GABA suppresses both T cells and macrophages. It increases TGF-beta production and regulatory T cells (Tr or Treg). Notably, GABA inhibits NF-kB activation in both lymphocytes and pancreatic islet beta cells. It also protects beta cells from apoptosis induced by various mechanisms, and this may be related to NF-kB inhibition. The mechanisms by which GABA exerts these effects are largely unknown. However, in immune cells it stimulates GABA type A receptors, which act as ligand-gated chloride channels. This may open voltage-dependent calcium channels in the membrane and decrease intra-cellular calcium levels. Conclusion: GABA acts on both T cells and macrophages and exerts potent anti-inflammatory effects, which are protective in models of type 1 diabetes.
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.
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 | 0.001 |
| 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 | 0.001 |
| 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