Evidence map›Paper›PMID 36699582›Full record

ArticleFrontiers in microbiology2022

Quantitative metaproteomics reveals composition and metabolism characteristics of microbial communities in Chinese liquor fermentation starters.

Jinzhi Zhao, Yi Yang, Liangqiang Chen, Jianxujie Zheng, Xibin Lv, Dandan Li, Ziyu Fang, Chengpin Shen, Vijini Mallawaarachchi, Yu Lin and 4 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

14 authors.

Jinzhi ZhaoDepartment of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China.
Yi YangDepartment of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China.
Liangqiang ChenKweichow Moutai Group, Renhuai, Guizhou, China.
Jianxujie ZhengDepartment of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China.
Xibin LvKweichow Moutai Group, Renhuai, Guizhou, China.
Dandan LiDepartment of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China.
Ziyu FangDepartment of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY, United States.
Chengpin ShenShanghai Omicsolution Co., Ltd., Shanghai, China.
Vijini MallawaarachchiCollege of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia.
Yu LinCollege of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia.
Shaoning YuZhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, China.
Fan YangKweichow Moutai Group, Renhuai, Guizhou, China.
Li WangKweichow Moutai Group, Renhuai, Guizhou, China.
Liang QiaoDepartment of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Methods: Herein, we used quantitative metaproteomics based on data-independent acquisition (DIA) mass spectrometry to analyze a total of 90 samples of white, yellow, and black Results: Taxonomic composition differences were explored across types of Discussion: We expect that this study will facilitate the understanding of the key microbes and their metabolism in the traditional fermentation process of Chinese liquor production.

Indexed as

Chinese liquorDaqudata-independent acquisitionmicrobial communityquantitative metaproteomics

Identifiers

PMID36699582
PMCPMC9868298

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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 OpenQuestion graph.