Search

The distribution of boron (B) in leaves is far from uniform, and tolerance to B toxicity should be varied in different portions of an entire leaf. Here, according to the order and degree of leaf chlorosis, a whole leaf blade of trifoliate orange [Poncirus trifoliata (L.) Raf.] rootstock was divided into two segments-leaf tip and leaf center, and transmission electron microscope (TEM) and fourier transform infrared spectroscopy (FTIR) were used to obtain more detailed information on the cell ultrastructure and component architecture of the two leaf segments under B toxicity. Results revealed that B toxicity led to alterations in pectin network crosslinking structure of leaf tip and destruction of cell wall integrity. Moreover, B toxicity altered protein structure and decreased protein content, while increased carbohydrate content in the two leaf segments, especially in leaf tip. Excess B supply reduced the cellulose content in leaf tip but increased in leaf center. TEM micrographs exhibited chloroplast disintegration and plastoglobulus accumulation in cells of two different leaf sections of B-toxicity plants, with less pronounced changes in leaf center. Furthermore, B toxicity only induced accumulation of starch grains in cells of leaf center. Overall results indicated that the B-toxic-induced biochemical changes of the cell ultrastructure and component architecture greatly differed in leaf tip and center. This study facilitates a better understanding of structural changes in different leaf portions of P. trifoliata under B toxicity stress and provides new ideas for further research on other elements in different plant leaf portions.

Trifoliate orange and citrange are two important rootstock resources to citrus, and citrange has a stronger tolerance to boron (B) deficiency and toxicity than trifoliate orange. In this study, we described how B deficiency and toxicity depressed the variations of cell wall B location, subcellular structure, cell wall components and structure of the two citrus rootstocks, to evaluate the mechanisms of different B tolerance of rootstocks on the cellular and structural levels. The results showed that citrange had better growth and lower symptoms of B stresses than trifoliate orange. What is more, citrange had a stronger ability to allocate more B to cell walls than trifoliate orange at deficient-B level. Under B deficiency and excessive conditions, severe damages in subcellular structure with obvious irregular thickening of cell walls and higher accumulation of plastoglobulus were observed in leaf cells of both two rootstocks. Additionally, it also showed obvious variations in the mode of hydrogen bonding, and more accumulation of cellulose, phenols and carbonhydrates in cell walls of trifoliate orange leaf under B starvation, while lighter changes on cell wall components were observed in citrange. As for B toxicity, comparing to trifoliate orange, citrange showed a lighter damage on pectin crosslinking structure in cell walls of leaf tissue. These results gained some novel mechanisms of different citrus rootstocks to B stress tolerance, and provide a theoretical basis for cultivating improved citrus rootstocks.

Boron (B) is an essential microelement for higher plants, and plays a role in cell wall formation. Citrange seedlings with different amounts of B were studied through Fourier-transform infrared spectroscopy (FTIR) analyses. The results showed that the growth and development of new roots were evidently inhibited by B deficiency. Boron-deficiency significantly increased cell wall biomass (CWB) as a percentage of root fresh weight and the ratio of B concentration in cell wall to the total B in roots. The findings from CWB FTIR spectra showed the band at 3429 cm−1 under control condition was shifted to 3442 cm−1 after being B deprived, suggesting that the mode of hydrogen bonding was changed by B deficiency. Boron deficiency clearly decreased the peak height of carboxylic ester band around 1741 cm−1, but increased that of COO− stretching band around 1400 cm−1, suggesting that the relative amount and degree of esterification of carboxylic groups was decreased and pectin content and structure was altere...

Boron (B) is a microelement required for higher plants, and B deficiency has serious negative effect on metabolic processes. We concentrated on the changes in metabolite profiles of trifoliate orange leaves and roots as a consequence of B deficiency at the initial stage of growth by gas chromatography-mass spectrometry (GC-MS)-based metabolomics. Enlargement and browning of root tips were observed in B-deficient plants, while any obvious symptom was not recorded in the leaves after 30 days of B deprivation. The distinct patterns of alterations in metabolites observed in leaves and roots due to B deficiency suggest the presence of specific organ responses to B starvation. The accumulation of soluble sugars was occurred in leaves, which may be attributed to down-regulated pentose phosphate pathway (PPP) and amino acid biosynthesis under B deficiency, while the amount of most amino acids in roots was increased, indicating that the effects of B deficiency on amino acids metabolism in trifoliate orange may be a consequence of disruptions in root tissues and decreased protein biosynthesis. Several important products of shikimate pathway were also significantly affected by B deficiency, which may be related to abnormal growth of roots induced by B deficiency. Conclusively, our results revealed a global perspective of the discriminative metabolism responses appearing between B-deprived leaves and roots and provided new insight into the relationship between B deficiency symptom in roots and the altered amino acids profiling and shikimate pathway induced by B deficiency during seedling establishment.

A quantitative method for clopidogrel using online-SPE tandem LC–MS/MS was developed and fully validated according to the well-established FDA guidelines. The method achieves adequate sensitivity for pharmacokinetic studies, with lower limit of quantifications (LLOQs) as low as 10 pg/mL. Chromatographic separations were performed on reversed phase columns Kromasil Eternity-2.5-C18-UHPLC for both methods. Positive electrospray ionization in multiple reaction monitoring (MRM) mode was employed for signal detection and a deuterated analogue (clopidogrel-d4) was used as internal standard (IS). Adjustments in sample preparation, including introduction of an online-SPE system proved to be the most effective method to solve the analyte back-conversion in clinical samples. Pooled clinical samples (two levels) were prepared and successfully used as real-sample quality control (QC) in the validation of back-conversion testing under different conditions. The result showed that the real samples were stable in room temperature for 24 h. Linearity, precision, extraction recovery, matrix effect on spiked QC samples and stability tests on both spiked QCs and real sample QCs stored in different conditions met the acceptance criteria. This online-SPE method was successfully applied to a bioequivalence study of 75 mg single dose clopidogrel tablets in 48 healthy male subjects., Graphical abstract A quantitative method for clopidogrel using online-SPE tandem LC–MS/MS was developed and fully validated according to the well-established FDA guidelines. The method achieves adequate sensitivity for pharmacokinetic studies, with lower limit of quantifications (LLOQs) as low as 10 pg/mL. Adjustments in sample preparation, including introduction of an online-SPE system proved to be the most effective method to solve the analyte back-conversion in clinical samples. fx1

In order to provide reliable date delivery and system management for large scale wireless sensor networks (WSNs), tracing the route path of packets in a lightweight manner is crucial and critical. Real-time path tracing technology enables us to observe every data transmission and analyze network dynamics in a fine-grained fashion. Due to resource constraints of WSNs, however, it is difficult, if not impossible, to integrate into each packet with its full path information. We attempt to capture such information with inserting a small and constant overhead into each packet. This design, PathZip, let each sensor node performs lightweight hash-based computations to passively label every packet forwarded. Meanwhile, the sink extracts the label information so as to leverage the pre-knowledge on the network to compute the full packet path. Both topology-aware and geometry-assistant techniques are utilized by PathZip in order to exploit different network knowledge and reduce the computation and storage overhead greatly. We conduct theoretical analysis and extensive simulations to evaluate the performance of our design. The results show that our method is effective to trace the full route path in large-scale WSNs, and outperforms the state-of-the-art methods.

Land monitoring is a critical task to ensure the quality of agricultural production. Traditional precision agriculture techniques require intensive computation and expensive hardware devices. This paper explores the techniques of deploying sensor networks in the field for practical land monitoring. As an example, we accurately measure the dark-area/light-area ratios in agriculture fields based on the Monte Carlo theory. We formulate the minimum sensor deployment problem, whose aim is to minimize the number of sensor nodes needed to achieve measurement precision requirements while satisfying size limitation requirements. Size limitation requirements are specified so that manual treatments can be carried on sub-regions that have an extraordinary dark/light ratio. We propose an incremental deployment solution - INCOME - to solve the problem, which does not require any prior knowledge of the dark/light distribution of the field. A split/merge algorithm is designed in INCOME to divide the monitored field into sub-regions satisfying both requirements. We formally prove that the sensor number needed in INCOME is less than that of regular division, and analyze the sensors needed in the ideal case and worst case. Comprehensive simulation studies demonstrate that the performance of INCOME is close to the optimal solution.

An assay based on protein precipitation and liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been developed and validated for the quantitative analysis of Sodium Tanshinone IIA Sulfonate (STS) in human plasma. After the addition of dehydroepiandrosterone-D5-3-sulfate sodium salt (DHEAS-D5) as internal standard (IS) and formic acid, plasma samples were prepared by one-step protein precipitation with a mixture of acetonitrile and methanol. Isocratic mobile phase consisted of 0.4 mmol/L ammonium formate buffer (16 ppm formic acid)/acetonitrile (40/60, v/v) on a XSELECT™ HSS T3 column. Detection was performed on a triple-quadrupole mass spectrometer utilizing an electrospray ionization (ESI) interface operating in positive ion and selected reaction monitoring (SRM) mode with the precursor to product ion transitions m/z 373.3→357.1 for STS and m/z 373.0→97.8 for the IS. Calibration curves of STS in human plasma were linear (r=0.9957-0.9998) over the concentration range of 2-1000 ng/mL with acceptable accuracy and precision. The lower limit of quantification in human plasma was 2 ng/mL. The validated LC-MS/MS method has been successfully applied to a pharmacokinetic study of STS in Chinese healthy male volunteers.

Greedy geographic routing is widely adopted in practical wireless networks due to its simplicity. However, greedy geographic routing alone cannot guarantee the delivery of packets due to the existence of local minima. A number of solutions have been proposed to address this issue, such as face routing, landmark-based routing, network segmentation or virtual coordinate based methods, etc. However, these solutions either have various limitations, such as depending on exact node locations, requiring costly preprocessing of the global network topology, or have obvious performance shortcomings, such as severe load-imbalance, large path stretch factors, etc. In this work, we attempt to combine the advantages of existing solutions, and present a hierarchical greedy geographic routing scheme. This design, FLYER, neither depends on exact node locations, nor needs to store any global state information in each node, which makes it applicable and scalable in large-scale practical systems. Moreover, our routing scheme is able to produce route paths with lower stretch factors and more load-balancing property than existing solutions. The algorithm works in a completely localized fashion, and the additional storage and computation complexity is extremely low. Extensive simulations are conducted, and the results demonstrate the superior performance of our approach against the state-of-the-art methods.

Wormhole attack is a severe threat to wireless ad hoc and sensor networks. Most of previous countermeasures either require specialized hardware devices or make strong assumptions on the network in order to capture the specific symptom induced by wormholes. Those requirements and assumptions limit the applicability of those approaches. Recently, some approaches based on topological or graph theoretical techniques are proposed to recognize wormholes using only connectivity information, shedding light on the challenging issue of connectivity-based wormhole detections. Unfortunately, those state-of-the-art connectivity-based countermeasures either present the principle of tracing wormholes in continuous domain, which makes it costly to transform them into protocols in discrete networks, or only explore localized (unstable) symptom of wormholes, accordingly incurring high false positive or negative rate. In this work, we make the first attempt towards establishing a graph theoretical method, called Worm Planar, that merely utilizes localized connectivity information and is able to capture the global essential symptoms of wormholes directly in the discrete networks. Worm Planar exploits location free network planarization technique to perform connectivity-based wormhole detection. Our new insights into the symptoms of wormholes make Worm Planar orthogonal to existing connectivity-based methods. We formally prove the correctness and evaluate the effectiveness of our approach through extensive simulations and comparisons with the state-of-the-art approaches. Simulation results demonstrate that Worm Planar is able to accurately identify and isolate wormholes for a large class of network instances.

In order to provide reliable data delivery and system management for large-scale wireless sensor networks (WSNs), tracing the route paths of packets in a lightweight manner is crucial and critical. Real-time path tracing technology enables us to observe every data transmission and analyze network dynamics in a fine-grained fashion. Due to resource constraints of WSNs, however, it is difficult, if not impossible, to integrate into each packet with its full path information. We attempt to capture such information with inserting a small and constant overhead into each packet. In this design, PathZip, each sensor node performs lightweight hash-based computations to passively label every packet forwarded. Meanwhile, the sink extracts the label information so as to leverage the pre-knowledge on the network to compute the full packet path. Both topology-aware and geometry-assistant techniques are utilized by PathZip in order to exploit different network knowledge and reduce the computation and storage overhead greatly. We conduct theoretical analysis and extensive simulations to evaluate the performance of our design. The results show that our method is effective to trace the full route path in large-scale WSNs, and outperforms the state-of-the-art methods.

Wormhole attack is a severe threat to wireless sensor networks (WSNs), which has received considerable attentions in the literature. However, most of the previous approaches either require special hardware devices or depend on rigorous assumptions on the network settings, which greatly limit their applicability. In this work, we attempt to relax the limitations in prior work, and propose a novel approach to detect wormhole attacks by only local topology information in WSNs. The basic idea is as follows. Each node locally collects its neighborhood information and reconstructs the neighborhood subgraph by multidimensional scaling (MDS). Potential wormhole nodes are detected by validating the legality of the reconstruction. Then, a refinement process is introduced to filter the suspect nodes and to remove false positives. Our approach solely relies on the local connectivity information and is extremely simple and lightweight, which makes it applicable in practical systems. Extensive simulations are conducted, and the results demonstrate the effectiveness and superior performance of our approach.