A Comparison of Methods to Maintain the Equine Cecal Microbial Environment In Vitro Utilizing Cecal and Fecal Material
Bibliographic record
Abstract
The equine gastrointestinal (GI) microbiota is intimately related to the horse. The objective of the current study was to evaluate the microbiome and metabolome of cecal inoculum maintained in an anaerobic chamber or chemostat batch fermenter, as well as the fecal slurry maintained in an anaerobic chamber over 48 h. Cecal and fecal content were collected from healthy adult horses immediately upon death. Cecal fluid was used to inoculate chemostat vessels (chemostat cecal, n = 11) and vessels containing cecal fluid (anaerobic cecal, n = 15) or 5% fecal slurry (anaerobic fecal, n = 6) were maintained in an anaerobic chamber. Sampling for microbiome and metabolome analysis was performed at vessel establishment (0 h), and after 24 h and 48 h of fermentation. Illumina sequencing was performed, and metabolites were identified via nuclear magnetic resonance (NMR). Alpha and beta diversity indices, as well as individual metabolite concentrations and metabolite regression equations, were analyzed and compared between groups and over time. No differences were evident between alpha or beta diversity in cecal fluid maintained in either an anaerobic chamber or chemostat. The microbiome of the fecal inoculum maintained anaerobically shifted over 48 h and was not comparable to that of the cecal inoculum. Metabolite concentrations were consistently highest in chemostat vessels and lowest in anaerobic fecal vessels. Interestingly, the rate of metabolite change in anaerobic cecal and chemostat cecal vessels was comparable. In conclusion, maintaining an equine cecal inoculum in either an anaerobic chamber or chemostat vessel for 48 h is comparable in terms of the microbiome. However, the microbiome and metabolome of fecal material is not comparable with a cecal inoculum. Future research is required to better understand the factors that influence the level of microbial activity in vitro, particularly when microbiome data identify analogous communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".