The Effects of Gut Dysbiosis via Bacteriophages and its Role in Parkinson's Disease
Bibliographic record
Abstract
Parkinson's disease (PD) is chronic age-dependent neurodegenerative disorder that has both motor and non-motor symptoms.A "multi-hit" hypothesis for PD suggests that a combination of risk factors (i.e., genetic and/or environmental) may lead to the disease.Increasing evidence is suggesting a link between the gut and PD.Phage-936 is a Lactococcal bacteriophage that targets lactic acid bacteria and may be associated with gut microbiome dysbiosis and inflammation.In this thesis, we sought to determine whether the phage-936 virus exacerbates the impact of inflammatory or neurotoxic stimuli (LPS, paraquat).We assessed changes in bacterial population by constructing a microbiome profile for both control and treated groups.Our results showed that L. lactis alone has an impact on the gut microbiome, but no significant changes were observed in neuronal dopaminergic cell counts with the treatments.I would also like to extend my appreciation to Teresa Fortin, our dedicated lab technician.Her expertise in laboratory techniques and willingness to assist at every step of my research have been invaluable.I would like to acknowledge the support of my friends and family who have stood by me throughout this academic journey.Your encouragement and understanding have been a constant source of motivation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".