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Record W4308459163 · doi:10.1136/gutjnl-2022-328403

Longitudinal transkingdom gut microbial approach towards decompensation in outpatients with cirrhosis

2022· article· en· W4308459163 on OpenAlexfundno aff
Jasmohan S. Bajaj, Marcela Peña‐Rodríguez, Alex La Reau, Wendy Phillips, Michael Fuchs, Brian Davis, Richard K. Sterling, Masoumeh Sikaroodi, Andrew Fagan, Amirhossein Shamsaddini, Zachariah M. Henseler, Tonya Ward, Hannah Lee, Patrick M. Gillevet

Bibliographic record

VenueGut · 2022
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute on Alcohol Abuse and AlcoholismAgency for Healthcare Research and QualityBausch HealthOffice of Research and DevelopmentU.S. Department of Veterans Affairs
KeywordsDecompensationArchaeaGut floraCrenarchaeotaBiologyEubacteriumMicrobiologyCirrhosisInternal medicineGastroenterologyMedicineBacteriaImmunologyGenetics

Abstract

fetched live from OpenAlex

Objective First decompensation development is a critical milestone that needs to be predicted. Transkingdom gut microbial interactions, including archaeal methanogens, may be important targets and predictors but a longitudinal approach is needed. Design Cirrhosis outpatients who provided stool twice were included. Group 1: compensated, group 2: 1 decompensation (decomp), group 3: >1 decompensationwere followed and divided into those who remained stable or decompensated. Bacteria, viral and archaeal presence, α/β diversity and taxa changes over time adjusted for clinical variables were analysed. Correlation networks between kingdoms were analysed. Results 157 outpatients (72 group 1, 33 group 2 and 52 group 3) were followed and 28%–47% developed outcomes. Baseline between those who remained stable/developed outcome: While no α/β diversity differences were seen, commensals were lower and pathobionts were higher in those who decompensated. After decompensation: those experiencing their first decompensation showed greater decrease in α/β-diversity, bacterial change (↑Lactobacillusspp,Streptococcus parasanguinisand ↓beneficial LachnospiraceaeandEubacterium hallii) and viral change (↑Siphoviridae, ↓ Myoviridae) versus those with further decompensation. Archaea: 19% hadMethanobacter brevii, which wassimilar between/within groups. Correlation networks: Baseline archaeal-viral-bacterial networks were denser and more homogeneous in those who decompensated versus the rest. Archaea-bacterial correlations collapsed post first decompensation.Lactobacillusphage Lc Nu and C2-like viruses were negatively linked with beneficial bacteria. Conclusion In this longitudinal study of cirrhosis outpatients, the greatest transkingdom gut microbial changes were seen in those reaching the first decompensation, compared with subsequent decompensating events. A transkingdom approach may refine prediction and provide therapeutic targets to prevent cirrhosis progression.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.246
Teacher spread0.223 · 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 designObservational
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

Citations19
Published2022
Admission routes1
Has abstractyes

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