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Record W4407794682 · doi:10.7717/peerj.18860

Changes in bacterial viability after preparation and storage of fecal microbiota transplantation solution using equine feces

2025· article· en· W4407794682 on OpenAlexaff
Júlia de Assis Arantes, Rebecca Di Pietro, Mélanie Ratté, Luis G. Arroyo, Mathilde Leclère, Márcio Costa

Bibliographic record

VenuePeerJ · 2025
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsUniversity of GuelphUniversité de Montréal
Fundersnot available
KeywordsFecesFecal bacteriotherapyTransplantationBiologyMicrobiologyMedicineClostridium difficileInternal medicineAntibiotics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.327
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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