hPepT1 selectively transports muramyl dipeptide but not Nod1-activating muramyl peptides
Bibliographic record
Abstract
Muramyl peptides derived from bacterial peptidoglycan are detected intracellularly by Nod1 and Nod2, 2 members of the newly characterized nod-like receptor (NLR) family of pattern recognition molecules. In the absence of bacterial invasion into the host cytosolic compartment, it remains unclear whether muramyl peptides can cross the plasma membrane and localize into the cytosol. We have recently demonstrated that the plasma membrane transporter, hPepT1, was able to efficiently translocate muramyl dipeptide (MDP), a specific Nod2-activating molecule, into host cells. We aimed to characterize the transport properties of hPepT1 towards a spectrum of muramyl peptides, including Nod1-activating molecules. To do so, we designed an original procedure based on the ectopic expression of hPepT1 in oocytes from Xenopus laevis. Our results demonstrated that hPepT1 transports MDP but no other Nod2-activating molecule. Moreover, we observed that Nod1-stimulating muramyl peptides were not transported by hPepT1. Since hPepT1 expression is strongly associated with intestinal epithelial cells, where Nod1 and Nod2 have been shown to play a key role, these observations suggest a distinct contribution of Nod1 and Nod2 in mucosal homeostasis following the cellular uptake of muramyl peptides by hPepT1.
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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) | 0.001 | 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 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".