A mass spectrometry‐based proteomics approach to identify novel host proteins in enteropathogenic <i>E. coli</i> pedestals (214.3)
Bibliographic record
Abstract
The human intestinal pathogen enteropathogenic Escherichia coli (EPEC) is a major cause of infantile diarrhea and early childhood mortality, particularly in developing countries. A hallmark of these infections is the formation of pedestal‐like morphological structures at sites where EPEC attaches to the host cell surface. Despite their known presence during these infections, their precise role in the disease process remains uncertain. Protein components that have been confirmed at pedestals are limited. Consequently, we hypothesize that undiscovered host proteins are present within EPEC pedestals and that some may play crucial roles in the pathogenesis of EPEC. To test our hypothesis, we developed a novel technique that can separate and concentrate EPEC pedestals from epithelial cells. We then utilized mass spectrometry (proteomics) to identify the protein constituents within these structures. From our screen, we identified 68 proteins with high confidence scores. Among these proteins, 24 corresponded to known and 44 are considered novel pedestal proteins. We have confirmed 9 novel pedestal proteins and have demonstrated the underlying molecular mechanisms in which they are hijacked by EPEC. Grant Funding Source : NSERC
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".