Evidence map›Paper›PMID 37623901›Full record

ArticleMetabolites2023

The Metabolomics Changes in Luria-Bertani Broth Medium under Different Sterilization Methods and Their Effects on

Haifeng Wang, Juan Guo, Xing Chen, Hongxuan He

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
6.7field-weighted citation impact, top 3% 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

15 citing papers in PubMed, 27 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 2 institutions in 1 country.

Haifeng WangSchool of Environmental Engineering, Yellow River Conservancy Technical Institute, Kaifeng Key Laboratory of Food Composition and Quality Assessment, Kaifeng 475004, China.ORCID 0000-0003-2720-0283
Juan GuoSchool of Environmental Engineering, Yellow River Conservancy Technical Institute, Kaifeng Key Laboratory of Food Composition and Quality Assessment, Kaifeng 475004, China.
Xing ChenSchool of Environmental Engineering, Yellow River Conservancy Technical Institute, Kaifeng Key Laboratory of Food Composition and Quality Assessment, Kaifeng 475004, China.
Hongxuan HeNational Research Center for Wildlife-Borne Diseases, Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.
Yellow River Conservancy Technical Institute · CNChinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Luria-Bertani broth (LB) culture medium is a commonly used bacterial culture medium in the laboratory. The nutrient composition, concentration, and culture conditions of LB medium can influence the growth of microbial strains. The purpose of this article is to demonstrate the impact of LB liquid culture medium on microbial growth under different sterilization conditions. In this study, LB medium with four different treatments was used, as follows: A, LB medium without treatments; B, LB medium with filtration; C, LB medium with autoclaving; and D, LB medium with autoclaving and cultured for 12 h. Subsequently, the protein levels and antioxidant capacity of the medium with different treatments were measured, and the effects of the different LB medium treatments on the growth of microorganisms and metabolites were determined via 16s rRNA gene sequencing and metabolomics analysis, respectively.

Indexed as

16s rRNA gene sequencingdifferential metabolitesLuria–Bertani broth mediummicrobial growth

Identifiers

PMID37623901
PMCPMC10456909
OpenAlexW4385994935

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.