Evidence map›Paper›PMID 38733426›Full record

ReviewBiodegradation2024

Study on microbial diversity of washing machines.

Yunyi Cao, Shuai Yuan, Lingling Pang, Jiuyan Xie, Yi Gao, Jian Zhang, Zhenyao Zhao, Su Yao

Abstract readReview
PubMed Publisher
In one paragraph

Review in Biodegradation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. The State-of-the-Art ofHealthcare (Basel, Switzerland) · 2024
    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

8 authors.

Yunyi Cao *Wuxi Little Swan Electric Co., Ltd., Wuxi, China.
Shuai Yuan *China Standardization Technology Service (Qingdao) Co., Ltd., Qingdao, China.
Lingling Pang *China Standardization Technology Service (Qingdao) Co., Ltd., Qingdao, China. pangll@csc.org.cn.
Jiuyan XieChina Center of Industrial Culture Collection (CICC), China National Research Institute of Food and Fermentation Industries, Beijing, China.
Yi GaoChina Center of Industrial Culture Collection (CICC), China National Research Institute of Food and Fermentation Industries, Beijing, China.
Jian ZhangChina Center of Industrial Culture Collection (CICC), China National Research Institute of Food and Fermentation Industries, Beijing, China.
Zhenyao ZhaoChina Center of Industrial Culture Collection (CICC), China National Research Institute of Food and Fermentation Industries, Beijing, China.
Su YaoChina Center of Industrial Culture Collection (CICC), China National Research Institute of Food and Fermentation Industries, Beijing, China. milly@china-cicc.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health and environmental protection are the development trend of household appliances, coupled with the impact of the COVID-19 epidemic in the past few years. Consumers have unprecedented concerns and expectations about the sterilization and disinfection functions of household appliances. As a washing and nursing equipment for household clothes, the anti-bacterial technology of washing machine has developed rapidly. The new models of washing machines in the market have basically added the function of sterilization. In order to thoroughly solve the problem of sterilization and bacteriostasis of washing machines from the source, the distribution of microbial contamination in washing machines should be fully investigated. At present, there is almost no systematic study on the microbial community structure in washing machines in China. Therefore, the purpose of this study is to analyze the bacterial community structure in Chinese household washing machines. To explore the key factors affecting the bacterial community structure of washing machines. Bacterial communities were comprehensively analyzed by high throughput sequencing. Using chao and shannon indexes as indicators, one-way ANOVA was used to explore the key factors affecting the bacterial community structure of washing machines. A total of 2,882,778 tags and 21,265 OTUs from 522 genera were sequenced from 56 washing machine samples. Genus Mycobacterium, Pseudomonas, Brevundimonas, Sphingomonas, Sphingobium, Enhydrobacter, Methylobacterium, Pseudoxanthomonas, Stenotrophomonas and Sphingopyxis were the top ten bacteria genera in abundance. The effects of sources, types, frequency of utilization, sampling locations and service life of washing machines on bacterial diversity in washing machine were systematically analyzed. The statistical analysis showed that service life was an important factor affecting bacterial diversity in washing machine. Our study lays a foundation for directional screening of characteristic microorganisms with targeted characters including malodor-producing, fouling, pathogenic and stress-resistance, the antibacterial evaluation, metabolic mechanism of key characteristic microorganisms as well as antibacterial materials development. At present, the sterilization technology of washing machines has not been fully in combination with the distribution survey of microorganisms in washing machines. According to the specific microorganism distribution condition of the washing machine, the key distribution positions and the types of specific microorganisms contained in different positions, conduct more targeted sterilization treatment. This will help to completely solve the problem of microbial growth in washing machines from the source.

Indexed as

BacteriaChinaCOVID-19High-Throughput Nucleotide SequencingHousehold ArticlesLaunderingMicrobiotaBacterial community structureChinese householdsHigh throughput sequencingWashing machine

Identifiers

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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.