MétaCan
Menu
Back to cohort
Record W4366818270 · doi:10.1002/cpz1.737

The Robogut: A Bioreactor Model of the Human Colon for Evaluation of Gut Microbial Community Ecology and Function

2023· article· en· W4366818270 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Protocols · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Guelph
FundersBreakthrough T1D CanadaCanadian Institutes of Health ResearchCanada Foundation for InnovationCanada Research Chairs
KeywordsProtocol (science)BioreactorMicrobiomeBiochemical engineeringMicrobial population biologyBiologyMicrobial ecologyFunction (biology)BiotechnologyComputer scienceEcologyBioinformaticsBacteriaMedicinePathologyEngineeringCell biology

Abstract

fetched live from OpenAlex

The human colon is inhabited by a complex community of microbes. These microbes are integral to host health and physiology. Understanding how and when the microbiome causally influences host health will require microbiome models that can be tightly controlled and manipulated. While in vivo models are unrivalled in their ability to study host-microbial interplay, in vitro models are gaining in popularity as methods to study the ecology and function of the gut microbiota, and benefit from tight controllability and reproducibility, as well as reduced ethical constraints. In this set of protocols, we describe the Robogut, a single-stage bioreactor system designed to replicate the conditions of the distal human colon, to culture whole microbial communities derived from stool and/or colonic biopsy samples, with consideration of methods to create culture medium formulations and to build, run, and sample the bioreactor apparatus. Cleaning and maintenance of the bioreactor system are also described. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Growth medium preparation Support Protocol 1: Preparing medium supplements Basic Protocol 2: Preparing the bioreactor vessels Support Protocol 2: Making acid and base bottles Support Protocol 3: Preparing the effluent bottles Support Protocol 4: Making acid solution Support Protocol 5: Making base solution Basic Protocol 3: Preparing inoculum and inoculating bioreactors Alternate Protocol 1: Preparing inoculum less than 0.5% (w/v) of vessel volume Alternate Protocol 2: Preparing synthetic community aliquots and inoculation via the septum Alternate Protocol 3: Preparing inoculum from a tissue sample Basic Protocol 4: Sampling the bioreactor vessel Basic Protocol 5: Harvesting bioreactor vessel contents at end of experiment Support Protocol 6: Cleaning and sterilizing sampling needles Basic Protocol 6: Cleaning the bioreactor vessel Support Protocol 7: Cleaning bioreactor support bottles.

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.

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)0.001
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 score0.319
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.139
GPT teacher head0.419
Teacher spread0.280 · 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