The plasma membrane H+-ATPase plays an important role in the plant response to nutrient and environmental stresses. However, the involvement of plant root plasma membrane H+-ATPase in adaptation to phosphate (P) starvation is not yet fully elucidated. In this study, experiments were performed with soybean roots in low-P nutrient solution (10 microM). Treatment with fusicoccin, an activator of the plasma membrane H+-ATPase, increased P uptake by 35%, while vanadate, an inhibitor of plasma membrane H+-ATPase, severely suppressed it. These results suggested that P uptake might be regulated via the modulation of the activity of plasma membrane H+-ATPase under P starvation. The relationship between P uptake and the activity of plasma membrane H+-ATPase was examined further by using plasma membrane H+-ATPase transgenic Arabidopsis thaliana under low-P conditions. Transgenic plants absorbed more P compared with wild-type Arabidopsis. Results from real-time RT-PCR, western-blotting and immunolocalization analysis indicated that the increase in activity of the plasma membrane H+-ATPase by P starvation was caused by its transcriptional and translational regulation. A higher expression was observed at the translational level than at the transcriptional level. P starvation could induce a transient increase of endogenous indole-3-acetic acid (IAA) in soybean roots. The exogenous application of IAA stimulated the activity of plasma membrane H+-ATPase and P uptake, while naphthylphthalamic acid (NPA), an IAA transport inhibitor, blocked IAA effects. Taken together, these results suggested an involvement of root plasma membrane H+-ATPase in the adaptation of soybean to P starvation. IAA might be involved in signal transduction of P starvation by activating the plasma membrane H+-ATPase in soybean roots.
Hollow metal oxide fibers (TiO2 and Fe2O3) have been prepared by using activated carbon fibers (ACFs) as the templates, through a simple impregnation and heat treatment. The resulting products, as compared to ACFs, possessed not only a similar morphological feature upward to the micrometer scale but also different surface nanostructures with unique morphology. The TiO2 fibers displayed overlapped “wormlike” surface and a hierarchical structure with two distinguishable layers, the inner layer and the outer layer, which were composed of the particles of 7 and 15 nm, respectively. It was also found that the reaction temperature had a significant effect on the TiO2 surface morphology. The Fe2O3 fibers exhibited a rough and crinkle-like surface and were also composed of hierarchical particles. Both TiO2 and Fe2O3 fibers possessed the hierarchical pore structure with mesopores in the walls of the large hollow channel. Such porous architecture favored the resultant TiO2 with better apparent photoactivity than P25 titania for degradation of gaseous acetone and would also make the materials useful for further application in other fields.
Affinity measure is a key factor that determines the quality of the analysis of a complex network. Here, we introduce a type of statistics, activation forces, to weight the links of a complex network and thereby develop a desired affinity measure. We show that the approach is superior in facilitating the analysis through experiments on a large-scale word network and a protein-protein interaction (PPI) network consisting of ∼5,000 human proteins. The experiment on the word network verifies that the measured word affinities are highly consistent with human knowledge. Further, the experiment on the PPI network verifies the measure and presents a general method for the identification of functionally similar proteins based on PPIs. Most strikingly, we find an affinity network that compactly connects the cancer-associated proteins to each other, which may reveal novel information for cancer study; this includes likely protein interactions and key proteins in cancer-related signal transduction pathways.
The temporal order of cancer gene mutations in tumors is essential for understanding and treating the disease. Existing methods are unable to infer the order of mutations that are identified at the same time in individual tumor samples, leaving the heterogeneity of the order unknown. Here, we show that through a complex network-based approach, which is based on the newly defined statistic –carcinogenesis information conductivity (CIC), the temporal order in individual samples can be effectively inferred. The results suggest that tumor-suppressor genes might more frequently initiate the order of mutations than oncogenes, and every type of cancer might have its own unique order of mutations. The initial mutations appear to be dedicated to acquiring the function of evading apoptosis, and some order constraints might reflect potential regularities. Our approach is completely data-driven without any parameter settings and can be expected to become more effective as more data will become available.
Atmogenic sulfur (S) deposition loading by acid rain is one of the biggest environmental problems in China. It is important to know the accumulated S stored in soil, because eventually the size (and also the "desorption" rate) determines how rapidly the soil water pH responds to decrease in S deposition. The S fractions and the ratio of total carbon/total sulfur (C/S) of forest soil in 9 catchments were investigated by comparing soils at the rural and urban sites in China. The S fractions included water-soluble sulfate-S (SO(4)-S), adsorbed SO(4)-S, insoluble SO(4)-S and organic S. The ratio of C/S in soil at the rural site was significantly (p < 0.05) greater than that at the urban site. C/S of soil in the A horizon was significantly (p < 0.05) and negatively correlated with the wet S-deposition rate. The ratio of C/S presents a better indicator for atmogenic S loading. Organic S was the dominant form in soils at rural sites; contributing more than 69% of the total S in the uppermost 30 cm soil. Organic S and adsorbed SO(4)-S were the main forms of S in soil at urban sites. High contents of water-soluble SO(4)-S and adsorbed SO(4)-S were found in uppermost 30 cm soils at urban sites but not at rural sites. Decades of acid rain have caused accumulation of inorganic SO(4)-S in Chinese forest soil especially at the urban sites. The soil at urban sites had been firstly acidified, and the impacts on the forest ecosystem in these areas should be noticed.
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