Bibliographic record
Abstract
In vitro gut models provide several advantages over in vivo models for the study of the human gut microbiota. However, because communities developed in these models are inevitably simplified simulations of the in vivo environment, it is necessary to broadly define the differences between in vitro consortia and the communities from which they are derived. In this study we characterized microbial community development in a twin-vessel single-stage chemostat model of the human distal gut ecosystem using both gel (Denaturing Gradient Gel Electrophoresis) and phylogenetic microarray (Human Intestinal Tract Chip) based techniques. Five different sets of twin-vessels were inoculated with feces from three different healthy adult donors and allowed to reach steady state compositions. We found that twin-vessel single-stage chemostats could develop and maintain stable, diverse, and reproducible communities that reach steady state compositions in all five runs by at most 36 days post-inoculation. As noted in other in vitro studies, steady state communities were enriched in Bacteroidetes but not Clostridium cluster XIVa, Bacilli or other Firmicutes relative to the fecal inocula. Communities developed within this model had higher within-run reproducibility than between-run repeatability when using consecutive fecal donations. Both fecal inocula and steady state chemostat communities seeded with feces from different donors had distinct compositions. We conclude that twin-vessel single-stage chemostat models represent a valid simulation of the human distal gut environment and can support complex, representative microbial communities ideal for experimental manipulation.
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
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".