Detection of Neu1 Sialidase Activity in Regulating TOLL-like Receptor Activation
Bibliographic record
Abstract
Mammalian Toll-like receptors (TLRs) are a family of receptors that recognize pathogen-associated molecular patterns. Not only are TLRs crucial sensors of microbial (e.g., viruses, bacteria and parasite) infections, they also play an important role in the pathophysiology of infectious diseases, inflammatory diseases, and possibly in autoimmune diseases. Thus, the intensity and duration of TLR responses against infectious diseases must be tightly controlled. It follows that understanding the structural integrity of sensor receptors, their ligand interactions and signaling components is essential for subsequent immunological protection. It would also provide important opportunities for disease modification through sensor manipulation. Although the signaling pathways of TLR sensors are well characterized, the parameters controlling interactions between the sensors and their ligands still remain poorly defined. We have recently identified a novel mechanism of TLR activation by its natural ligand, which has not been previously observed 1,2. It suggests that ligand-induced TLR activation is tightly controlled by Neu1 sialidase activation. We have also reported that Neu1 tightly regulates neurotrophin receptors like TrkA and TrkB 3, which involve Neu1 and matrix metalloproteinase-9 (MMP-9) cross-talk in complex with the receptors 4. The sialidase assay has been initially use to find a novel ligand, thymoquinone, in the activation of Neu4 sialidase on the cell surface of macrophages, dendritic cells and fibroblast cells via GPCR Gαi proteins and MMP-9 5. For TLR receptors, our data indicate that Neu1 sialidase is already in complex with TLR-2, -3 and -4 receptors, and is induced upon ligand binding to either receptor. Activated Neu1 sialidase hydrolyzes sialyl α-2,3-linked β-galactosyl residues distant from ligand binding to remove steric hinderance to TLR-4 dimerization, MyD88/TLR4 complex recruitment, NFkB activation and pro-inflammatory cell responses. In a collaborative report, Neu1 sialidase has been shown to regulate phagocytosis in macrophage cells 6. Taken together, the sialidase assay has provided us with powerful insights to the molecular mechanisms of ligand-induced receptor activation. Although the precise relationship between Neu1 sialidase and the activation of TLR, Trk receptors has yet to be fully elucidated, it would represent a new or pioneering approach to cell regulation pathways.
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 | 0.001 | 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".