Perturbation of host cell cytoskeleton by cranberry proanthocyanidin and its effect on enteric infections
Bibliographic record
Abstract
Cranberry-derived compounds, including a fraction known as proanthocyanidins (PACs) exhibit anti-microbial, anti-infective, and anti-adhesive properties against a number of disease-causing organisms.This thesis illustrates the effect of cranberry proanthocyanidins (CPACs) on t he infection of epithelial cells by two enteric bacterial pathogens, enteropathogenic Escherichia coli (EPEC) and Salmonella Typhimurium.Immunofluorescence data showed that actin pedestal formation, required for infection by enteropathogenic Escherichia coli (EPEC), was disrupted in the presence of CPACs.In addition, invasion of HeLa cells by Salmonella Typhimurium was significantly reduced.CPACs had no e ffect on ba cterial growth, on the production of bacterial virulence proteins or the viability of host cells.Interestingly, we found that CPACs had a potent and dose-dependent effect on t he host cell cytoskeleton that was evident even in uninfected cells.C PACs inhibited the phagocytosis of inert particles by a macrophage I would first like to thank my supervisors, Professor Nathalie Tufenkji as well as Professor Samantha Gruenheid for their continuous support, guidance and encouragement along the way.I will always be grateful for their patience and dedication throughout the many different directions this project has taken.To the many mentors, teachers, and coaches serving as role models throughout my life; I wouldn't be the person I am today without your teachings and influences.To my labmates in the Complex Traits Group, in particular Ajitha Thanabalasuriar, Sarah Teatero, Lei Zhu, Mark Mime, Yonatan Lipsitz, you made each day worthwhile.
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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 | 0.000 |
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".