Stimulation of primed carbon under climate change corresponds with phosphorus mineralization in the rhizosphere of soybean.

Elevated CO2 and temperature likely alter photosynthetic carbon inputs to soils, which may stimulate soil microbial activity to accelerate the decomposition of soil organic carbon (SOC), liberating more phosphorus (P) into the soil solution. However, this hypothesis on the association of SOC decomposition and P transformation in the plant rhizosphere requires robust soil biochemical evidence, which is critical to nutrient management for the mitigation of soil quality against climate change. This study investigated the microbial functional genes relevant to P mineralization together with priming processes of SOC in the rhizosphere of soybean grown under climate change. Soybean plants were grown under elevated CO2 (eCO2, 700 ppm) combined with warming (+ 2 °C above ambient temperature) in open-top chambers. Photosynthetic carbon flow in the plant-soil continuum was traced with 13CO2 labeling. The eCO2 plus warming treatment increased the primed carbon (C) by 43 % but decreased the NaHCO3-extratable organic P by 33 %. Furthermore, NaHCO3-Po was negatively correlated with phosphatase activity and microbial biomass C. Elevated CO2 increased the abundances of C degradation genes, such as abfA and ManB, and P mineralization genes, such as gcd, phoC and phnK. The results suggested that increased photosynthetic carbon inputs to the rhizosphere of plants under eCO2 plus warming stimulated the microbial population and metabolic functions of both SOC and organic P mineralization. There is a positive relationship between the rhizosphere priming effect and P mineralization. The response of microorganisms to plant-C flow is decisive for coupled C and P cycles, which are likely accelerated under climate change.

Plant phosphorus acquisition links to phosphorus transformation in the rhizospheres of soybean and rice grown under CO2 and temperature co-elevation.

Climate change is likely to influence the reservoir of soil phosphorus (P) as plants adaptably respond to climate change in the perspective of P acquisition capability via root proliferation and mediating biochemical properties in the rhizosphere to access various soil P fractions. It is particularly important in cropping soils where P fertilizer plus soil P is required to synchronize crop P demand for the production sustainability under climate change. However, few studies have examined the effect of CO2 and temperature co-elevation on plant P acquisition, P fractions and relevant functional genes in the rhizosphere of different crops. Thus, the present study investigated the effect of elevated CO2 and warming on P uptake of soybean and rice grown in Mollisols, and soil P fractions and relevant biochemical properties and microbial functions in the rhizosphere with or without P application. Open-top chambers were used to achieve elevated CO2 of 700 ppm combined with warming (+ 2 °C above ambient temperature). CO2 and temperature co-elevation increased P uptake in soybean by 23% and 28% under the no-P and P application treatments, respectively; and in rice, by 34% and 13%, respectively. CO2 and temperature co-elevation depleted organic P in the rhizosphere of soybean, but increased in the rhizosphere of rice. The phosphatase activity negatively correlated with organic P in the highland soil while positively in the paddy soil. The P mineralization likely occurs in soybean-grown soils under climate change, while the P immobilization in paddy soils. CO2 and temperature co-elevation increased the copy numbers of P functional genes including phoD, phoC, pstS and phnX, in soils with P application. These results indicate that the P application would be requested to satisfy the increased P demand in soybean under climate change, but not in rice in paddy soils where soil P availability is sufficient. Therefore, elevated CO2 and temperature facilitated the crop P uptake via biochemical and microbial pathways, and P functional genes played an essential role in the conversion of P.

Random matrix theory for analysing the brain functional network in lower limb motor imagery.

We use random matrix theory (RMT) to investigate the statistical properties of brain functional networks in lower limb motor imagery. Functional connectivity was calculated by Pearson correlation coefficient (PCC), mutual information (MTI) and phase locking value (PLV) extracted from EEG signals. We found that when the measured subjects imagined the movements of their lower limbs the spectral density as well as the level spacings displayed deviations from the random matrix prediction. In particular, a significant difference between the left and right foot imaginary movements was observed in the maximum eigenvalue from the PCC, which can provide a theoretical basis for further study on the classification of unilateral movement of lower limbs.

EEG-based Classification of Lower Limb Motor Imagery with Brain Network Analysis.

This study aims to investigate the difference in cortical signal characteristics between the left and right foot imaginary movements and to improve the classification accuracy of the experimental tasks. Raw signals were gathered from 64-channel scalp electroencephalograms of 11 healthy participants. Firstly, the cortical source model was defined with 62 regions of interest over the sensorimotor cortex (nine Brodmann areas). Secondly, functional connectivity was calculated by phase lock value for α and ß rhythm networks. Thirdly, network-based statistics were applied to identify whether there existed stable and significant subnetworks that formed between the two types of motor imagery tasks. Meanwhile, ten graph theory indices were investigated for each network by t-test to determine statistical significance between tasks. Finally, sparse multinomial logistic regression (SMLR)-support vector machine (SVM), as a feature selection and classification model, was used to analyze the graph theory features. The specific time-frequency (α event-related desynchronization and ß event-related synchronization) difference network between the two tasks was congregated at the midline and demonstrated significant connections in the premotor areas and primary somatosensory cortex. A few of statistically significant differences in the network properties were observed between tasks in the α and ß rhythm. The SMLR-SVM classification model achieved fair discrimination accuracy between imaginary movements of the two feet (maximum 75% accuracy rate in single-trial analyses). This study reveals the network mechanism of the discrimination of the left and right foot motor imagery, which can provide a novel avenue for the BCI system by unilateral lower limb motor imagery.

[Preliminary exploration on accurately preoperative evaluation of colonic lesions in slow transit constipation complicated with adult megacolon].

OBJECTIVE: To investigate the application value of colonic transit test (CTT) combined with anorectal manometry (ARM), barium enema (BE) and defecography (DFG) in accurately evaluating colonic lesions of slow transit constipation complicated with adult megacolon. METHODS: Clinical data of 47 above patients admitted between October 2007 and February 2015 in the People's Hospital of Hunan Province were analyzed retrospectively. All the patients were examined with≥2 times of CTT combined with ARM and BE, and 42 cases received additional DFG at the same time, to evaluate colonic lesions before operation. Operative biopsy pathology was used as the standard. The sensitivity, specificity, positive predictive value(PPV) and negative predictive value(NPV) of positioning in the ascending colon and caecum, transverse colon and descending colon were calculated, and the consistency was represented by Kappa test(Kappa value≥0.75 indicates good consistency, meanwhile higher Kappa value indicates better consistency). The Heikkinen score was used to evaluate defecation function at postoperative 6 months. RESULTS: The age of 47 patients was from 18 to 56 years old. Compared with intraoperative findings and biopsy pathology, the diagnostic coincidence rate was 89.4% by CTT combined with BE and DFG positioning, which suggested pathology-changed colonic segment locating in the ascending colon and cecum (n=12), transverse colon (n=26) and descending colon (n=9), while intraoperative findings and biopsy pathology suggested pathology-changed colonic segment locating in the ascending colon and cecum (n=11), transverse colon (n=23) and descending colon (n=13). The sensitivity was 88.3%, specificity 93.5%, PPV 92.1%, NPV 94.9% and Kappa value was 0.827(P<0.001). Procedures performed included segmental colectomy (n=8), subtotal colectomy (n=29), total colectomy (n=10). There was no serious complication during and after operation. Defecatory function was excellent in 24 cases (60.0%), good in 10 (25.0%), and moderate in 6 (15.0%) evaluated by Heikkinen score at postoperative 6 months. A total of 40 patients were followed up from 1 to 7 years (median 3 years) and there was no long-term diarrhea and recurrence of constipation or giant colon after operation. CONCLUSION: Preoperative detection of CTT combined with ARM, BE and DFG in patients with slow transit constipation complicated with adult megacolon can make a more precise assessment of the extent of colonic lesions in advance, which has a good clinical predictive value.