Soybean, as a major oil crop, is one of the most widely planted crops in the world. Fusarium oxysporum causes soybean root rot, leading to great economic losses to soybean planting every year globally. Chemical fungicide for controlling soybean F. oxysporum diseases may cause environmental problems and have human health risks. Biological control methods avoid these shortcomings, however, few studies have focused on biocontrol of soybean diseases caused by F. oxysporum. Aiming at this problem, we obtained biocontrol bacteria against soybean F. oxysporum by plate confrontation method. The type of the strain with the highest biocontrol activity was identified by molecular biological methods, and then verified it biocontrol effects through greenhouse experiments. One of our isolated strain named BS06 strain had the highest activity, which was identified as Bacillus subtilis. Our study showed that BS06 strain could effectively control soybean F. oxysporum disease and significantly reduce F. oxysporum to infect soybean roots. Compared with control and carbendazim treatments, BS06 treatment had higher root biomass, plant height, leaf chlorophyll content, stem base diameter and control efficiency. Our results indicated that BS06 could effectively protect soybean root, that might BS06 strain produce substances to inhibit F. oxysporum, which was potentially useful for soybean planting.
Recent research on Parkinson's disease (PD) has demonstrated the topological abnormalities of structural covariance networks (SCNs) using various morphometric features from structural magnetic resonance images (sMRI). However, the sulcal depth (SD)-based SCNs have not been investigated. In this study, we used SD to investigate the topological alterations of SCNs in 60 PD patients and 56 age- and gender-matched healthy controls (HC). SCNs were constructed by thresholding SD correlation matrices of 68 regions and analyzed using graph theoretical approaches. Compared with HC, PD patients showed increased normalized clustering coefficient and normalized path length, as well as a reorganization of degree-based and betweenness-based hubs (i.e., less frontal hubs). Moreover, the degree distribution analysis showed more high-degree nodes in PD patients. In addition, we also found the increased assortativity and reduced robustness under a random attack in PD patients compared to HC. Taken together, these findings indicated an abnormal topological organization of SD-based SCNs in PD patients, which may contribute in understanding the pathophysiology of PD at the network level.
This study aimed to investigate the cortical complexity and gyrification patterns in Parkinson’s disease (PD) using local fractional dimension (LFD) and local gyrification index (LGI), respectively. In a cross-sectional study, LFD and LGI in 60 PD patients without dementia and 56 healthy controls (HC) were investigated using brain structural MRI data. LFD and LGI were estimated using the Computational Anatomy Toolbox (CAT12) and statistically analyzed between groups on a vertex level using statistical parametric mapping 12 (SPM12). Additionally, correlations between structural changes and clinical indices were further examined. PD patients showed widespread LFD reductions mainly in the left pre- and postcentral cortex, the left superior frontal cortex, the left caudal middle frontal cortex, the bilaterally superior parietal cortex and the right superior temporal cortex compared to HC. For LGI, there was no significant difference between PD and HC. In PD patients group, a significant negative correlation was found between LFD of the left postcentral cortex and duration of illness (DOI). Our results of widespread LFD reductions, but not LGI, indicate that LFD may provide a more sensitive diagnostic biomarker and encode specific information of PD. The significant negative correlation between LFD of the left postcentral cortex and DOI suggests that LFD may be a biomarker to monitor disease progression in PD.
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