Evidence map›Paper›PMID 42382349›Full record

ArticleFrontiers in microbiology2026

Study on disinfection using wet wipes and UV irradiation for areas prone to condensate accumulation in the Chinese Space Station.

Ying Zhang, Jiangchuan Zhou, Jinglin Ma, Lili Ren

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ying ZhangSchool of Life Science, Beijing Institute of Technology, Beijing, China.
Jiangchuan ZhouSchool of Life Science, Beijing Institute of Technology, Beijing, China.
Jinglin MaSchool of Life Science, Beijing Institute of Technology, Beijing, China.
Lili RenDepartment of Otolaryngology Head and Neck Surgery, The 6th Medical Center of Chinese PLA General Hospital, Chinese PLA Medical School, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Condensate water is one of the environmental niches aboard space stations that is most prone to microbial growth. This study reports one of the first applications of a detailed characterization of the microbial composition of condensate water collected from inside the China Space Station during flight, as well as an evaluation of effective cleaning and disinfection strategies for microbial control. Methods: To maximize the recovery of microorganisms from the condensate-water environment, we developed a custom high-throughput microbial isolation and cultivation device (cChip) based on the isolation chip method (iChip) and used it for high-throughput cultivation of microorganisms from onboard areas of the China Space Station that are susceptible to microbial proliferation. In addition, to evaluate on the ground the decontamination efficacy of four disinfection methods already used in orbit (wiping with pure-water wipes, 75% alcohol wipes, quaternary ammonium salt wipes, and ultraviolet irradiation), we constructed a microbial contamination model on authentic textile flight materials using the isolated strains in proportions determined from high-throughput sequencing data. The efficacy of these four disinfection approaches against the contamination model was then assessed using contact plates, PMA-qPCR, and qPCR. Results: In total, 14 bacterial strains and 9 fungal strains were obtained. Notably, members of the genera

Indexed as

China Space Stationcondensate waterhigh-throughput microbial cultivation chipon-orbit microbial disinfection measuresspace station microbial contamination model

Identifiers

PMID42382349
PMCPMC13314837

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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.