Evidence map›Paper›PMID 31143306›Full record

ArticleJournal of clinical medicine research2019

Characteristics of Gut Microbiota in Patients With Diabetes Determined by Data Mining Analysis of Terminal Restriction Fragment Length Polymorphisms.

Yuta Nakamura, Yoshio Nagai, Toshio Kobayashi, Kentaro Furukawa, Yoichi Oikawa, Akira Shimada, Yasushi Tanaka

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical medicine research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Yuta NakamuraDivision of Metabolism and Endocrinology, Department of Internal Medicine, St. Marianna University School of Medicine, 2-16-1, Sugao, Miyamae-ku, Kawasaki, Kanagawa 216-8511, Japan.
Yoshio NagaiDivision of Metabolism and Endocrinology, Department of Internal Medicine, St. Marianna University School of Medicine, 2-16-1, Sugao, Miyamae-ku, Kawasaki, Kanagawa 216-8511, Japan.
Toshio KobayashiMiyagi University, Sendai, Miyagi 982-0215, Japan.
Kentaro FurukawaFurukawa Hospital, Yokohama, Kanagawa 221-0021, Japan.
Yoichi OikawaDepartment of Internal Medicine, Tokyo Saiseikai Central Hospital, Tokyo 108-0073, Japan.
Akira ShimadaDepartment of Endocrinology and Diabetes, Saitama Medical University, Iruma-gun, Saitama 350-0495, Japan.
Yasushi TanakaDivision of Metabolism and Endocrinology, Department of Internal Medicine, St. Marianna University School of Medicine, 2-16-1, Sugao, Miyamae-ku, Kawasaki, Kanagawa 216-8511, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study was performed to clarify whether gut microbiota obtained from fecal samples could identify the type of diabetes in patients of each gender by using a combination of terminal restriction fragment length polymorphism (T-RFLP) analysis and data mining.

methodsA cross-sectional study was performed at three centers. Fecal samples were collected from 12 Japanese patients with type 1 diabetes mellitus (T1D), 18 patients with type 2 diabetes mellitus (T2D), and 31 subjects without diabetes mellitus (non-DM). Amplification of fecal 16S rRNA was carried out. After digestion of the amplification products with restriction enzymes (

resultsAmong men, the error rate was 2.4% with

conclusionsWe were able to classify the 16SrRNA gene amplification products obtained from fecal samples of T1D patients, T2D patients, and non-DM subjects with a high level of precision by combining T-RFLP analysis and data mining. Specific gut microbiota patterns were found for T1D and T2D patients, as well as a sex difference of the patterns.

Indexed as

Data miningDiabetesGut microbiotaT-RFLP analysis

Identifiers

PMID31143306
PMCPMC6522229

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.