MyD88 Regulates the Expression of SMAD4 and the Iron Regulatory Hormone Hepcidin
Bibliographic record
Abstract
The myeloid differentiation primary response gene 88 (MyD88) is an adaptive protein that is essential for the induction of inflammatory cytokines through almost all the Toll-like receptors (TLRs). TLRs recognize molecular patterns present in microorganisms called pathogen-associated molecular patterns. Therefore, MyD88 plays an important role in innate immunity since its activation triggers the first line of defense against microorganisms. Herein, we describe the first reported role of MyD88 in an interconnection between innate immunity and the iron-sensing pathway (BMP/SMAD4). We found that direct interaction of MyD88 with SMAD4 protein activated hepcidin expression. The iron regulatory hormone hepcidin is indispensable for the intestinal regulation of iron absorption and iron recycling by macrophages. We show that MyD88 induces hepcidin expression in a manner dependent on the proximal BMP responsive element on the hepcidin gene (HAMP) promoter. We identified the Toll/interleukin-1 receptor (TIR) domain of MyD88 as the domain of interaction with SMAD4. Furthermore, we show that BMP6 stimulation, which activates SMAD6 expression, also induces MyD88 proteosomal degradation as a negative feedback mechanism to limit hepcidin induction. Finally, we report that the MyD88 gain-of-function L265P mutation, frequently encountered in B-cell lymphomas such as Waldenström’s macroglobulinemia, enhances hepcidin expression and iron accumulation in B cell lines. Our results reveal a new potential role for MyD88 in the SMAD signaling pathway and iron homeostasis regulation.
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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) | 0.002 | 0.001 |
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".