Ureolytic
microbes play a pivotal role in the maintenance of soil
fertility. Soil aggregates are supposed to provide heterogeneous habitats
for microorganisms, which may result in distinct metabolic functions.
However, limited information is available regarding the distribution
patterns, driving factors, and activity of ureolytic microbiota at
the aggregate scale. In this study, we characterized the ureolytic
microbiota and urease activity of three soil aggregate fractions from
an Inceptisol subjected to 5 years of different fertilization regimes.
Correlations between soil chemical characteristics and ureolytic microbial
communities were analyzed. The results showed that the total abundance
as well as the relative abundance of copiotrophic ureolytic microbes
generally increased with the increasing soil aggregate size. This
trend was in line with the nutrient distribution patterns, including
labile carbon, NH4
+, total carbon, nitrogen,
and phosphorus. Soil urease activity also increased significantly
with the increasing soil aggregate size and was positively correlated
with copiotrophic ureolyric microbes, such as Betaproteobacteria,
Alphaproteobacteria, and Gammaproteobacteria. Thus, we speculated
that larger size soil aggregates with greater availability of labile
carbon support more copiotrophic ureolyric microbes with a high growth
rate, leading to a high density of total ureolytic microbes and higher
urease activity. Smaller aggregates with less available carbon were
associated with more oligotrophs, higher abundances of total ureolytic
microbes, and higher urease activity. Our results suggest that larger
soil aggregates and associated ureolyric microbes play a more important
role in nutrient cycling for crop growth in this Inceptisol ecosystem.
Objective In order to investigate electroencephalogram (EEG) instantaneous activity states related to executed and imagined movement of force of hand clenching (grip force: 4 kg, 10 kg, and 16 kg), we utilized a microstate analysis in which the spatial topographic map of EEG behaves in a certain number of discrete and stable global brain states. Approach Twenty subjects participated in EEG collection; the global field power of EEG and its local maximum were calculated and then clustered using cross validation and statistics; the 4 parameters of each microstate (duration, occurrence, time coverage, and amplitude) were calculated from the clustering results and statistically analyzed by analysis of variance (ANOVA); finally, the relationship between the microstate and frequency band was analyzed. Main Results The experimental results showed that all microstates related to executed and imagined grip force tasks were clustered into 3 microstate classes (A, B, and C); these microstates generally transitioned from A to B and then from B to C. With the increase of the target value of executed and imagined grip force, the duration and time coverage of microstate B gradually decreased, while these parameters of microstate C gradually increased. The occurrence times of microstate B and C related to executed grip force were significantly more than those related to imagined grip force; furthermore, the amplitudes of these 3 microstates related to executed grip force were significantly greater than those related to imagined grip force. The correlation coefficients between the microstates and the frequency bands indicated that the microstates were correlated to mu rhythm and beta frequency bands, which are consistent with event-related desynchronization/synchronization (ERD/ERS) phenomena of sensorimotor rhythm. Significance It is expected that this microstate analysis may be used as a new method for observing EEG instantaneous activity patterns related to variation in executed and imagined grip force and also for extracting EEG features related to these tasks. This study may lay a foundation for the application of executed and imagined grip force training for rehabilitation of hand movement disorders in patients with stroke in the future.
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