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A human‐origin probiotics cocktail exhibit cardio‐protective effects independent of GLP‐1 receptor signaling

2019· article· en· W3174356798 on OpenAlexaboutno aff
Ravinder Nagpal, Sidharth P. Mishra, Shaohua Wang, Ann Tallant, Jasmina Varagić, Dalane W. Kitzman, Hariom Yadav

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institutes of Health
KeywordsButyrateEndocrinologyInternal medicineProbioticGlucagon-like peptide-1Ejection fractionType 2 diabetesDiet-induced obeseVentricleReceptorBiologyMicrobiomeGut floraDiabetes mellitusMedicineInsulin resistanceHeart failureBiochemistryBioinformaticsBacteria

Abstract

fetched live from OpenAlex

The emerging role of the gut microbiome in cardiovascular diseases is posited to be mediated by the microbial metabolites, some of which yield beneficial effects while others may accelerate the heart diseases. The beneficial metabolites like short‐chain fatty acids, particularly butyrate, exhibit several beneficial effects on metabolic diseases including cardiovascular functions. We have previously demonstrated that butyrate promotes the production of glucagon‐like protein‐1 (GLP‐1). GLP‐1 and its therapeutic agonists are known to promote cardiovascular functions. Herein, we investigated the role of systemic deletion of GLP‐1 receptor (using GLP1R KO) on cardiac functions in 16 weeks high‐fat diet (HFD)‐fed obese mice and assessed the impact of feeding a butyrate‐producing probiotic cocktail (consisting 5 Lactobacillus and 5 Enterococcus strains isolated from infant's gut) on cardiac functions, using the non‐invasive high‐frequency ultrasound echocardiography system (VEVO, VisualSonics, Toronto, Ontario, Canada). GLP1R‐KO mice show reduced cardiac output and stroke volume, and higher ejection fraction and fractional shortening of the left ventricle compared GLP1R‐WT mice. In addition, the GLP1R‐KO mice also exhibited significantly reduced systolic and diastolic diameter and volume, along with higher ratio of aortic acceleration and ejection time. Interestingly, feeding of probiotic cocktail protected from such dysfunctions in GLP‐KO mice, and also all these measures remain unchanged in GLP‐WT mice with and without probiotics treatments. No significant differences in body weight and diet intake was observed, however, glucose and insulin tolerance tests were improved in both probiotic‐fed groups. Results indicate that GLP1‐receptor depletion causes cardiovascular dysfunctions and feeding of the human‐origin probiotic cocktail ameliorates such dysfunctions, and probiotics effects are independent of GLP‐1 receptor signaling. Further analyses to better understand the mechanisms of actions of probiotics cocktail contributing these effects, are directed to establish a new cardioprotective probiotic biotherapy in obesity and type 2 diabetes. Support or Funding Information We thank the support provide by Center of Cardiovascular Sciences Center, Wake Forest School of Medicine, and the Department of Defense funding PR170446, as well funds and services provided from Center for Diabetes, Obesity and Metabolism, Wake Forest Baptist Medical Center and National Center for Advancing Translational Sciences (NCATS), National Institutes of Health funded Wake Forest Clinical and Translational Science Institute (WF CTSI) through Grant Award Number UL1TR001420. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 score0.006

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 communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.249
Teacher spread0.235 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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