Evidence map›Paper›PMID 33768385›Full record

ArticleCurrent microbiology2021

The Impacts of the Occupants on the Bacterial Communities of Classrooms.

Zhou Feng, He Shen, Yong Nie, Xiao-Lei Wu

Abstract read
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In one paragraph

Article in Current microbiology, 2021. 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
–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

1 citing paper in PubMed.

  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

4 authors.

Zhou FengCollege of Engineering, Peking University, Beijing, 100871, China.
He ShenThe Experimental High School Attached to Beijing Normal University, Beijing, 100032, China.
Yong NieCollege of Engineering, Peking University, Beijing, 100871, China. nieyong@pku.edu.cn.ORCID http://orcid.org/0000-0002-5940-1218
Xiao-Lei WuCollege of Engineering, Peking University, Beijing, 100871, China. xiaolei_wu@pku.edu.cn.ORCID http://orcid.org/0000-0002-9897-6903

Funding

National Key R&D Program of China 2018YFA0902100National Key R&D Program of China 2018YFA0902103National Natural Science Foundation of China 31761133006National Natural Science Foundation of China 31770118National Natural Science Foundation of China 31770120
6 · The paper itself

Abstract

In modern societies, people spend most of their time in the built environment which harbors unique microbial assemblages with the potential to influence human health. However, how the occupants of buildings influence indoor microbial communities remains under-researched. Here, we investigated the diversities of the bacterial communities of a typical Chinese middle school to demonstrate the effects of occupant activities on bacterial communities inside classrooms. The results showed that samples taken from classrooms exhibited higher microbial diversity compared to samples collected from public areas such as gym and restaurant, suggesting the occupant activities could increase the diversities of the indoor microbial communities. Moreover, we also found that the duration of occupation strongly influence the presence/absence of phylogenetic lineages of the bacterial communities, the type of occupants, on the other hand, affect the relative abundances of bacterial taxa. In addition, samples taken from classrooms with longer occupation time exhibited a better fit to the Sloan Neutral Community Model for Prokaryotes, suggesting that room occupation influences the assembly process of microbial communities. In conclusion, our study demonstrates that the duration of occupation and the type of occupants influence the microbiome of the built environment.

Indexed as

Air Pollution, IndoorMicrobiotaBacteriaBuilt EnvironmentHumansPhylogeny

Identifiers

What OpenQuestion holds

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Registered trials

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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.