Soluble CD14 through GABA production by monocytes promotes Th17 differentiation and innate lymphoid cells 3740
Bibliographic record
Abstract
Abstract Description Soluble CD14 (sCD14) plays a pivotal role in immunity, with elevated levels linked to numerous acute and chronic conditions, including COVID-19, HIV, and cardiovascular diseases. Studies highlight monocytes as the primary source of sCD14, particularly under endotoxin or LPS stimulation. sCD14 enhances inflammatory responses, amplifying macrophage and neutrophil activation, yet can suppress LPS-stimulated monocyte responses in whole blood. It also modulates B cell activity, increasing IgG1 and IL-6 production, while inhibiting T cell proliferation and cytokine release (e.g., IL-2, IFN-γ, TNF-a). Our studies reveal that sCD14 indirectly promotes Th17 differentiation by reducing Th1 responses and upregulating Th17-related cytokines (e.g., IL-17A, IL-17F). This mechanism expands Th17 cells and polarizes naïve CD4+ and CD8+ T cells toward Th17 phenotypes, implicated in inflammatory diseases like psoriasis and multiple sclerosis. Additionally, sCD14-treated T cells secrete unique chemokines, including IP-10 and TARC, enhancing inflammation. We found that sCD14 through GABA production by monocytes promote IL-17 and innate lymphoid cells (ILCs), which express Th17-associated markers. GABA further drives Th17 differentiation through mTOR signaling. These findings underscore sCD14’s multifaceted role in shaping immune responses, especially in promoting Th17-mediated inflammation and related pathologies. Funding Sources This study was supported by a CIHR grant to SE and a CIHR-REDI award to S.S. Topic Categories Immune Response Regulation: Cellular Mechanisms (IRC)
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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 | 0.000 |
| 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) | 0.007 | 0.002 |
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".