Evidence map›Paper›PMID 25384384›Full record

ArticleEnvironmental health and toxicology2014

Toxic detection in mine water based on proteomic analysis of lysosomal enzymes in Saccharomyces cerevisiae.

Ngoc-Tu Nguyen, Yang-Hoon Kim, Seung Hyuck Bang, Ji Hye Hong, Soon Dong Kwon, Jiho Min

Open access · goldAbstract read
In one paragraph

Article in Environmental health and toxicology, 2014. 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
0.9field-weighted citation impact, top 28% 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

1 citing paper in PubMed, 9 citations in OpenAlex.

  1. Article
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

6 authors at 2 institutions in 1 country.

Ngoc-Tu NguyenDepartment of Bioprocess Engineering, Chonbuk National University, Jeonju, Korea.
Yang-Hoon KimDepartment of Microbiology, Chungbuk National University, Cheongju, Korea.
Seung Hyuck BangDepartment of Bioprocess Engineering, Chonbuk National University, Jeonju, Korea.
Ji Hye HongMine Reclamation Corporation, Coal Center, Seoul, Korea.
Soon Dong KwonMine Reclamation Corporation, Coal Center, Seoul, Korea.
Jiho MinDepartment of Bioprocess Engineering, Chonbuk National University, Jeonju, Korea.
Jeonbuk National University · KRChungbuk National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesLysosome is the cell-organelle which is commonly used as biomonitoring tool in environmental pollution. In this study, the lysosomal proteomic of the yeast Saccharomyces cerevisiae was analyzed for utilization in the detection of toxic substances in mine water samples.

methodsThis work informs the expression of lysosomal proteomic in yeast in response with toxic chemicals, such as sodium meta-arsenite and tetracycline, for screening specific biomarkers. After that, a recombinant yeast contained this biomarker were constructed for toxic detection in pure toxic chemicals and mine water samples.

resultsEach chemical had an optimal dose at which the fluorescent protein intensity reached the peak. In the case of water samples, the yeast showed the response with sample 1, 3, 4, and 5; whereas there is no response with sample 2, 6, and 7.

conclusionsThe recombinant yeast showed a high ability of toxic detection in response with several chemicals such as heavy metals and pharmaceuticals. In the case of mine water samples, the response varied depending on the sample content.

Indexed as

Heavy metalsLysosomal proteomicLysosomal responseMine waterPharmaceuticals

Identifiers

PMID25384384
PMCPMC4243728
OpenAlexW2118428999

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.