Evidence map›Paper›PMID 40735648›Full record

ArticleInfection and drug resistance2025

Investigation into the Efficacy of Formic Acid Fumigation for Inactivating Clinically Isolated Filamentous Fungi.

Kaixuan Yuan, Benshun Tian, Annan Zhan, Zhuoxi Chen, Long Ye, Yong Ling, Suiling Liu, Xuejiao Bai, Yunhu Zhao

Abstract read
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Article in Infection and drug resistance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Kaixuan Yuan *Department of Clinical Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, People's Republic of China.ORCID 0009-0004-9815-7846
Benshun Tian *Faculty of Materials & Manufacturing, Beijing University of Technology, Beijing, People's Republic of China.
Annan Zhan *KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, Guangdong, People's Republic of China.
Zhuoxi ChenDepartment of Clinical Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Long YeDepartment of Clinical Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, People's Republic of China.ORCID 0009-0002-9740-9357
Yong LingDepartment of Clinical Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, People's Republic of China.ORCID 0009-0004-2013-4417
Suiling LiuDepartment of Clinical Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Xuejiao BaiAdministration Department of Nosocomial Infection, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Yunhu ZhaoDepartment of Clinical Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, People's Republic of China.ORCID 0000-0002-3745-014X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Inactivating filamentous fungi (molds) reduce toxin production and transmission. This study evaluated the efficacy of formic acid (FA) fumigation to identify optimal conditions and its effects on fungal morphology. We aim to develop an efficient inactivation protocol for molds and provide valuable insights into laboratory techniques for fungal inactivation. Methods: Initially, 238 clinical isolates from 23 species of molds were evaluated for the inactivation efficacy of formic acid, formaldehyde, and peracetic acid. After identifying the optimal sterilizing agent, 188 isolates from 16 clinically significant species were tested. Four concentrations (30%, 50%, 70%, and 100%) and six-time intervals (4 to 14 hours) were tested to optimize fumigation conditions. Morphological changes were analyzed using Results: The inactivation rates of 238 molds fumigated with formic acid, formaldehyde, and peracetic acid for 24 hours were 99.16%, 89.08%, and 90.35% ( Conclusion: Formic acid demonstrated superior inactivation efficacy compared to formaldehyde and peracetic acid. At a concentration of 70% and a fumigation duration of 12 hours, the inactivation of molds was most effective.

Indexed as

filamentous fungiformaldehydeformic acidfumigationinactivationperacetic acid

Identifiers

PMID40735648
PMCPMC12306555

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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.