Changes in bacterial viability after preparation and storage of fecal microbiota transplantation solution using equine feces
Bibliographic record
Abstract
Background Fecal microbiota transplantation (FMT) has been used as a treatment option for horses (Equus caballus) with gastrointestinal diseases. Several preparation and conservation protocols to improve bacterial survival have been studied in other species. Methods This study aimed to evaluate the impact of oxygen exposure and different protectant solutions on bacterial viability before and after freezing using horse feces. Fecal samples from 10 healthy horses were aliquoted and diluted in cryoprotectant solutions containing antioxidants (n = 40) or 10% glycerol (n = 40). Half of the aliquots from each dilution condition were prepared inside an anaerobic chamber, while the other half were prepared under ambient air conditions. Each sample was also analyzed fresh and after freezing at −20 °C for 90 days. Bacterial viability was assessed using flow cytometry. A mixed linear model and the Friedman and Wilcoxon tests were used depending on data distribution. Results Freeze-thawing decreased bacterial viability by 47% (mean ± SD: 51 ± 27% before, 27 ± 8% after; p < 0.001). Glycerol was superior to the cryoprotectant after freezing (32 ± 8% glycerol, 24 ± 8% cryoprotectant; p < 0.001). Oxygen exposure did not affect viability (p = 0.13). There was no statistical difference between protectant solutions in fresh samples (p = 0.16). Conclusions Fresh FMT solutions may be better for treating horses with dysbiosis, but if freezing cannot be avoided, glycerol should be used to dilute feces.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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) | 0.000 | 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) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".