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P: 82 Genetically Engineered E. coli Nissle Attenuates Hyperammonemia and Improves Memory in an Experimental Model of Cirrhosis and Hepatic Encephalopathy

2019· article· en· W2971729742 on OpenAlexaff
Rafael Ochoa‐Sanchez, Alexis Monnet‐Aimard, Farzaneh Tamnanloo, Mariana M. Oliveira, Mélanie Tremblay, Mylène Perreault, Bill Querbes, Caroline Kurtz, Christopher F. Rose

Bibliographic record

VenueThe American Journal of Gastroenterology · 2019
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHepatic encephalopathyHyperammonemiaCirrhosisEncephalopathyGenetically engineeredMedicineNeuroscienceInternal medicineBiologyBiochemistryGene

Abstract

fetched live from OpenAlex

BACKGROUND: Hyperammonemia associated with chronic liver disease (CLD) is implicated in the pathogenesis of hepatic encephalopathy (HE). The gut is a major source of ammonia production that contributes to systemic hyperammonemia in CLD and HE and remains the primary therapeutic target for lowering circulating ammonia. As a therapeutic strategy, Escherichia coli Nissle 1917 bacterium (EcN), a well characterized probiotic, was genetically modified to consume and convert ammonia to arginine (SYNARG), and its administration to thioacetamide-treated mice resulted in a significant reduction of ammonia levels. 1 SYNARG was further modified to synthesize butyrate (SYNARG+BUT), a short-chain fatty acid with anti-inflammatory/anti-oxidant properties, and both strains were tested in an experimental model of cirrhosis and HE, the bile duct ligation (BDL). METHODS: One week post surgery, BDL rats were gavaged with SYNARG, SYNARG+BUT (3 × 10 11 CFU/day, BID) or vehicle until they were sacrificed at 3- or 5-weeks along with respective sham controls. Plasma ammonia and live markers were measured at 3 and 5 weeks. Recognition-memory, motor-coordination, muscle-strength, locomotion and anxiety were assessed in the 5-week BDL groups. RESULTS: BDL significantly increased ammonia over time, with levels of 109.1 ± 9.2 µM (Shams 56.7 ± 3.5 µM, P < 0.001) and 150.2 ± 25.6 µM (Shams 58.3 ± 3.0µM, P < 0.001) at 3- and 5-weeks, respectively. In addition, plasma liver markers alanine-transaminase, aspartate-transaminase, bilirubin, and gamma-glutamyl transferase were significantly increased in BDL rats at both timepoints while albumin was significantly lowered. As compared to BDL-Veh rats, hyperammonemia was attenuated by SYNARG (103.9 ± 12.3 µM) and SYNARG+BUT (110.8 ± 8.5 µM) at 5, but not 3 weeks post-surgery, while liver fibrosis (hydroxyproline content) was attenuated at 3, but not 5 weeks post-surgery. None of the circulating liver markers were changed by the treatments at any timepoint. Motor-coordination, muscle-strength, locomotion and anxiety were affected in all BDL groups without protective effect of treatments. Short-term memory (STM) was impaired in BDL-Veh ( P < 0.001) and BDL-SYNARG ( P < 0.05) versus Shams, while STM was resolved in BDL-SYNARG+BUT ( P < 0.05 vs BDL-Veh). Long-term memory (LTM) was impaired in BDL-Veh vs Shams ( P < 0.05), but BDL-SYNARG and BDL-SYNARG+BUT were protected. CONCLUSIONS: EcN, engineered to consume ammonia in the gut and synthesize butyrate, is an effective approach to lower plasma ammonia in a model of cirrhosis and HE. Moreover, the attenuation of hyperammonemia in cirrhotic rats is associated with a protective effect on memory in this model. The therapeutic potential of these engineered EcN strains should be further evaluated in patients with CLD and HE.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.245
Teacher spread0.236 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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