Evidence map›Paper›PMID 42350404›Full record

ArticleNPJ microgravity2026

Simulated microgravity weakens wheat root microbial network against pathogens.

Jingjing Cui, Zhenyu Chen, Shaocheng Yan, Liting Zhao, A G Degermendzhi, Hong Liu, Yuming Fu

Abstract read
In one paragraph

Article in NPJ microgravity, 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

7 authors.

Jingjing Cui *Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education; Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology; National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering); School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
Zhenyu Chen *Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education; Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology; National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering); School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
Shaocheng Yan *Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education; Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology; National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering); School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
Liting ZhaoKey Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education; Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology; National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering); School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
A G DegermendzhiInstitute of Biophysics, Department of Federal Research Center "Krasnoyarsk Science Center of the Siberian Branch of the Russian Academy of Sciences", Krasnoyarsk, Russia.
Hong LiuKey Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education; Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology; National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering); School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
Yuming FuKey Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education; Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology; National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering); School of Biological Science and Medical Engineering, Beihang University, Beijing, China. fuyuming@buaa.edu.cn.

Funding

International Cooperation and Exchange of the National Natural Science Foundation of China 32261133528National Natural Science Foundation of China 32471289Russian Science Foundation No. 23-44-00059Space Utilization System of the China Manned Space Program KJZ-YY-NSM0603
6 · The paper itself

Abstract

Fungal pathogens are well-recognized biotic stressors for plants under terrestrial gravity and also pose risks to space crop production, but their effects on root-associated microbial networks under microgravity conditions remain poorly understood. Here, we profiled bacterial and fungal communities in wheat seedlings with or without Fusarium graminearum infection under normal gravity and simulated microgravity, and linked network properties to plant growth and hormone profiles. Although bacterial and fungal α-diversity showed no significant differences among treatments and Bray-Curtis β-diversity showed limited separation, co-occurrence networks revealed that infection disrupted bacterial-bacterial and bacterial-fungal networks more strongly under simulated microgravity than under normal gravity, whereas fungal-fungal networks were largely unchanged. Bacterial network characteristics explained more variation in plant performance than bacterial-fungal network characteristics. Structural equation modeling showed that simulated microgravity reduced endosphere bacterial network stability, which was positively associated with plant performance, especially jasmonic acid and cytokinin levels. Random forest analysis identified Paenibacillus and Microbacteriaceae-related taxa as key predictors of bacterial network stability. These findings support microbiome-based strategies to enhance plant resilience in space systems.

Identifiers

PMID42350404
PMCPMC13662163

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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.