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Record W4404956735 · doi:10.1016/j.celrep.2026.117491

Prophage induction contributes to alterations in the gut phageome during intestinal inflammation

2024· preprint· en· W4404956735 on OpenAlexafffund
Anshul Sinha, Amy Qian, Tommy Boutin, Corinne F. Maurice

Bibliographic record

VenueCell Reports · 2024
Typepreprint
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of TorontoMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchKenneth Rainin Foundation
KeywordsProphageLysogenic cycleLytic cycleBiologyInflammationDysbiosisTemperatenessMicrobiologyImmunologyMicrobiomeGut floraBacteriophageGeneticsVirusGeneEscherichia coli

Abstract

fetched live from OpenAlex

Bacteriophages (phages) are abundant members of the gut microbiota and regulators of bacterial communities. During homeostasis, gut phage communities are longitudinally stable and lysogenic replication is dominant. In chronic gut inflammatory disorders, such as inflammatory bowel diseases (IBDs), there are alterations in phage diversity, which may result from changes in phage replication cycles. Here, we use a combination of in vitro, simplified community, and whole-community bioinformatics approaches to investigate whether prophage induction contributes to these alterations. We identify several compounds associated with gut inflammation that induce prophages from commensal gut bacterial isolates. Analyzing data from two mouse models of colitis, we observe that shifts in the composition of temperate phages occur over the course of inflammation, supporting a switch from lysogenic to lytic replication. Collectively, our observations support the idea that prophage induction contributes to alterations in the phageome associated with intestinal inflammation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

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

Citations1
Published2024
Admission routes2
Has abstractyes

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