Evidence map›Paper›PMID 25719268›Full record

ArticleNature protocols2015

Surgical models of Roux-en-Y gastric bypass surgery and sleeve gastrectomy in rats and mice.

Bote G Bruinsma, Korkut Uygun, Martin L Yarmush, Nima Saeidi

Open access · greenAbstract read
In one paragraph

Article in Nature protocols, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed
7.4field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

55 citing papers in PubMed, 79 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Bote G BruinsmaCenter for Engineering in Medicine, Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts, USA.
Korkut UygunCenter for Engineering in Medicine, Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts, USA.
Martin L YarmushCenter for Engineering in Medicine, Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts, USA.
Nima SaeidiCenter for Engineering in Medicine, Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts, USA.
Massachusetts General Hospital · US

Funding

The Role of Adipose Tissue Remodeling in Surgically-Induced Weight LossF32DK095558 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI SAEIDI, NIMA · 2012 to 2014
$163k
NIDDK NIH HHS DK095558NIDDK NIH HHS F32 DK095558
6 · The paper itself

Abstract

Bariatric surgery is the only definitive solution currently available for the present obesity pandemic. These operations typically involve reconfiguration of gastrointestinal tract anatomy and impose profound metabolic and physiological benefits, such as substantially reducing body weight and ameliorating type II diabetes. Therefore, animal models of these surgeries offer unique and exciting opportunities to delineate the underlying mechanisms that contribute to the resolution of obesity and diabetes. Here we describe a standardized procedure for mouse and rat models of Roux-en-Y gastric bypass (80-90 min operative time) and sleeve gastrectomy (30-45 min operative time), which, to a high degree, resembles operations in humans. We also provide detailed protocols for both pre- and postoperative techniques that ensure a high success rate in the operations. These protocols provide the opportunity to mechanistically investigate the systemic effects of the surgical interventions, such as regulation of body weight, glucose homeostasis and gut microbiome.

Indexed as

Models, AnimalAnimalsGastrectomyGastric BypassMiceRats

Identifiers

PMID25719268
PMCPMC4476550
OpenAlexW2054032713

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.