NOD2 Agonism Counter-Regulates Human Type 2 T Cell Functions in Peripheral Blood Mononuclear Cell Cultures: Implications for Atopic Dermatitis
Bibliographic record
Abstract
Atopic dermatitis (AD) is known as a skin disease; however, T cell immunopathology found in blood is associated with its severity. Skin Staphylococcus aureus (S. aureus) and associated host–pathogen dynamics are important to chronic T helper 2 (Th2)-dominated inflammation in AD, yet they remain poorly understood. This study sought to investigate the effects of S. aureus-derived molecules and skin alarmins on human peripheral blood mononuclear cells, specifically testing Th2-type cells, cytokines, and chemokines known to be associated with AD. We first show that six significantly elevated Th2-related chemokine biomarkers distinguish blood from adult AD patients compared to healthy controls ex vivo; in addition, TARC/CCL17, LDH, and PDGF-AA/AB correlated significantly with disease severity. We then demonstrate that these robust AD-associated biomarkers, as well as associated type 2 T cell functions, are readily reproduced from healthy blood mononuclear cells exposed to the alarmin TSLP and the S. aureus superantigen SEB in a human in vitro model, including IL-13, IL-5, and TARC secretion as well as OX-40-expressing activated memory T cells. We further show that the agonism of nucleotide-binding oligomerization domain-containing protein (NOD)2 inhibits this IL-13 secretion and memory Th2 and Tc2 cell functional activation while inducing significantly increased pSTAT3 and IL-6, both critical for Th17 cell responses. These findings identify NOD2 as a potential regulator of type 2 immune responses in humans and highlight its role as an endogenous inhibitor of pathogenic IL-13 that may open avenues for its therapeutic targeting in AD.
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 | 0.000 | 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 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".