Production of transgenic rice with rice ragged stunt virus synthetic resistance genes

Rice ragged stunt virus (RRSV) is an important pathogen of rice affecting its cultivation in South and South East Asia. An approach based on pathogen derived resistance (PDR) was used to produce RRSV resistant rice cultivars. Sequences from the coding region of RRSV genome segments 7 and 10 (non-structural genes), and 5, 8 and 9 (structural genes) were placed in sense or antisense orientation behind the plant expression promoters CaMV35S, RolC, Ubil, Actl and RBTV. Rice cultivars Taipei 309 and Chinsurah Boro II were transformed by biolistic and/or Agrobacterium-mediated delivery of one or more of these PDR gene constructs. A large number of transgenic lines were produced from calli derived from mature or immature embryos, co-bombarded with the marker gene hph encoding hygromycin resistance and RRSV PDR genes or co-cultivated with strains having the binary vector containing these two genes. Both Mendelian and non-Mendelian segregations were observed in transgenic progeny, especially with transgenic lines produced by biolistics. Preliminary tests conducted in China on selected transgenic lines indicate that plants with RRSV segment 5 antisense PDR gene confer RRSV resistance.

Improved vectors for Agrobacterium tumefaciens-mediated transformation of monocot plants

A series of improved vectors have been constructed that are suitable for use in Agrobacterium tumefaciens-mediated monocot transformation. These binary vectors have several useful features, including the selectable marker genes bar (phosphinothricin resistance) or hph (hygromycin resistance) driven by either the cauliflower mosaic virus (CaMV) 35S promoter or the maize ubiquitin promoter, a high-copy-number replication origin that allows reliable mini-prep DNA isolation from Escherichia coli, and a polylinker sequence into which target genes can be easily inserted. A significant improvement has been made to the hph gene by the introduction of an intron into its coding region. The presence of the intron abolishes hph expression in A. tumefaciens, rendering the bacterium susceptible to the selective agent hygromycin B. The use of such an intron-hph vector thus enables the antibiotic in plant culture media to function as both a selective agent for transformed tissue and as a contraselective agent for A. tumefaciens growth, thus minimising the overgrowth of A. tumefaciens on plant tissues during transformation. Furthermore, the intron appears to be correctly spliced in plant cells and significantly enhances hph expression in transformed rice tissue. In our experiments, the use of the intron-hph vector increased the frequency of rice transformation and has enabled the production of transgenic barley.

Intron-mediated improvement of a selectable marker gene for plant transformation using Agrobacterium tumefaciens

In binary vectors, the antibiotic resistance gene used for selection of transformed plant cells is also usually expressed in the transforming Agrobacterium cells. This expression gives the bacterium antibiotic resistance, an unnecessary advantage on selective medium containing the antibiotic. Insertion of a castor bean catalase-1 (CAT-1) gene intron or a Parasponia andersonii haemoglobin gene intron into the coding region of the selectable marker gene, hph, completely abolished the expression of the gene in Agrobacterium, rendering it susceptible to hygromycin B. Use of these modified binary vectors minimized the overgrowth of Agrobacterium during plant transformation. Both of the introns were correctly spliced in plant cells and significantly enhanced hph gene expression in transformed rice tissue. The presence of these introns in the hph coding sequence not only maintained the selection efficiency of the hph gene, but with the CAT-1 intron also substantially increased the frequency of rice transformation. Transgenic lines with an intron-hph gene generally contained fewer gene copies and produced substantially more mRNA of the predicted size. Our results also indicate that transgenic plants with many copies of the transgene were more likely to show gene silencing than plants with 1-3 copies.

Putative full-length clones of the genomic DNA segments of subterranean clover stunt virus and identification of the segment coding for the viral coat protein

Subterranean clover stunt disease is an economically important aphid-borne virus disease affecting certain pasture and grain legumes in Australia. The virus associated with the disease, subterranean clover stunt virus (SCSV), was previously found to be representative of a new type of single-stranded DNA virus. Analysis of the virion DNA and restriction mapping of double-stranded cDNA synthesized from virion DNA suggested that SCSV has a segmented genome composed of 3 or 4 different species of circular ssDNA each of about 850-880 nucleotides. To further investigate the complexity of the SCSV genome, we have isolated the replicative form DNA from infected pea and from it prepared putative full-length clones representing the SCSV genome segments. Analysis of these clones by restriction mapping indicated that clones representing at least 4 distinct genomic segments were obtained. This method is thus suitable for generating an extensive genomic library of novel ssDNA viruses containing multiple genome segments such as SCSV and banana bunchy top virus. The N-terminal amino acid sequence and amino acid composition of the coat protein of SCSV were determined. Comparison of the amino acid sequence with partial DNA sequence data, and the distinctly different restriction maps obtained for the full-length clones suggested that only one of these clones contained the coat protein gene. The results confirmed that SCSV has a functionally divided genome composed of several distinct ssDNA circles each of about 1 kb.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

Long non coding RNAs (lncRNAs) are dysregulated in Malignant Pleural Mesothelioma (MPM)

Malignant Pleural Mesothelioma (MPM) is an aggressive cancer that is often diagnosed at an advanced stage and is characterized by a long latency period (20-40 years between initial exposure and diagnosis) and prior exposure to asbestos. Currently accurate diagnosis of MPM is difficult due to the lack of sensitive biomarkers and despite minor improvements in treatment, median survival rates do not exceed 12 months. Accumulating evidence suggests that aberrant expression of long non-coding RNAs (lncRNAs) play an important functional role in cancer biology. LncRNAs are a class of recently discovered non-protein coding RNAs >200 nucleotides in length with a role in regulating transcription. Here we used NCode long noncoding microarrays to identify differentially expressed lncRNAs potentially involved in MPM pathogenesis. High priority candidate lncRNAs were selected on the basis of statistical (P<0.05) and biological significance (>3-fold difference). Expression levels of 9 candidate lncRNAs were technically validated using RT-qPCR, and biologically validated in three independent test sets: (1) 57 archived MPM tissues obtained from extrapleural pneumonectomy patients, (2) 15 cryopreserved MPM and 3 benign pleura, and (3) an extended panel of 10 MPM cell lines. RT-qPCR analysis demonstrated consistent up-regulation of these lncRNAs in independent datasets. ROC curve analysis showed that two candidates were able to separate benign pleura and MPM with high sensitivity and specificity, and were associated with nodal metastases and survival following induction chemotherapy. These results suggest that lncRNAs have potential to serve as biomarkers in MPM.

Identification of a long non-coding RNA gene, GHSROS (growth hormone secretagogue receptor opposite strand), which stimulates cell migration in non-small cell lung cancer cell lines

The molecular mechanisms involved in non‑small cell lung cancer tumourigenesis are largely unknown; however, recent studies have suggested that long non-coding RNAs (lncRNAs) are likely to play a role. In this study, we used public databases to identify an mRNA-like, candidate long non-coding RNA, GHSROS (GHSR opposite strand), transcribed from the antisense strand of the ghrelin receptor gene, growth hormone secretagogue receptor (GHSR). Quantitative real-time RT-PCR revealed higher expression of GHSROS in lung cancer tissue compared to adjacent, non-tumour lung tissue. In common with many long non-coding RNAs, GHSROS is 5' capped and 3' polyadenylated (mRNA-like), lacks an extensive open reading frame and harbours a transposable element. Engineered overexpression of GHSROS stimulated cell migration in the A549 and NCI-H1299 non-small cell lung cancer cell lines, but suppressed cell migration in the Beas-2B normal lung-derived bronchoepithelial cell line. This suggests that GHSROS function may be dependent on the oncogenic context. The identification of GHSROS, which is expressed in lung cancer and stimulates cell migration in lung cancer cell lines, contributes to the growing number of non-coding RNAs that play a role in the regulation of tumourigenesis and metastatic cancer progression.

Preventing pollution attacks in multi-source network coding

Network coding is a method for achieving channel capacity in networks. The key idea is to allow network routers to linearly mix packets as they traverse the network so that recipients receive linear combinations of packets. Network coded systems are vulnerable to pollution attacks where a single malicious node floods the network with bad packets and prevents the receiver from decoding correctly. Cryptographic defenses to these problems are based on homomorphic signatures and MACs. These proposals, however, cannot handle mixing of packets from multiple sources, which is needed to achieve the full benefits of network coding. In this paper we address integrity of multi-source mixing. We propose a security model for this setting and provide a generic construction.

Malnutrition coding shortfalls in Australian and New Zealand hospitals

Aim The International Classification of Diseases, version 10, Australian modification (ICD-10-AM) is used to classify diseases in hospital patients in Australia and New Zealand. ICD-10-AM defines malnutrition as ‘[body mass index] BMI <18.5 kg/m2 or unintentional weight loss of ≥5% with evidence of suboptimal intake resulting in subcutaneous fat loss and/or muscle wasting’. The Australasian Nutrition Care Day Survey (ANCDS) is the most comprehensive survey to evaluate malnutrition prevalence in acute care patients from Australian and New Zealand hospitals. This study determined if malnourished participants were assigned malnutrition-related codes according to ICD-10-AM. Methods The ANCDS recruited acute care patients from 56 hospitals. Hospital-based dietitians evaluated participants' nutritional status using BMI and Subjective Global Assessment (SGA). In keeping with the ICD-10-AM definition, malnutrition was defined as BMI <18.5 kg/m2, SGA-B (moderately malnourished) or SGA-C (severely malnourished). After 3 months, in this prospective cohort study, staff members from each hospital's health information/medical records department provided coding results for malnourished participants. Results Malnutrition was prevalent in 30% (n = 869) of the cohort (n = 2976) and a significantly small number of malnourished patients were coded for malnutrition (n = 162, 19%, P < 0.001). In 21 hospitals, none of the malnourished participants were coded. Conclusions This is the largest study to provide a snapshot of malnutrition coding in Australian and New Zealand hospitals. Findings highlight gaps in malnutrition documentation and/or subsequent coding, which could potentially result in significant loss of casemix-related revenue for hospitals. Dietitians must lead the way in developing structured processes for malnutrition identification, documentation and coding.

A coding approach to the multicast stream authentication problem

We study the multicast stream authentication problem when an opponent can drop, reorder and introduce data packets into the communication channel. In such a model, packet overhead and computing efficiency are two parameters to be taken into account when designing a multicast stream protocol. In this paper, we propose to use two families of erasure codes to deal with this problem, namely, rateless codes and maximum distance separable codes. Our constructions will have the following advantages. First, our packet overhead will be small. Second, the number of signature verifications to be performed at the receiver is O(1). Third, every receiver will be able to recover all the original data packets emitted by the sender despite losses and injection occurred during the transmission of information.

Identifying steganographic payload location in binary image

In this paper, we propose a steganalysis method that is able to identify the locations of stego bearing pixels in the binary image. In order to do that, our proposed method will calculate the residual between a given stego image and its estimated cover image. After that, we will compute the local entropy difference between these two versions of images as well. Finally, we will compute the mean of residual and mean of local entropy difference across multiple stego images. From these two means, the locations of stego bearing pixels can be identified. The presented empirical results demonstrate that our proposed method can identify the stego bearing locations of near perfect accuracy when sufficient stego images are supplied. Hence, our proposed method can be used to reveal which pixels in the binary image have been used to carry the secret message.

Binary image steganographic techniques classification based on multi-class steganalysis

In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography.

Blind steganalysis : a countermeasure for binary image steganography

In this paper, we propose a new blind steganalytic method to detect the presence of secret messages embedded in black and white images using the steganographic techniques. We start by extracting several sets of matrix, such as run length matrix, gap length matrix and pixel difference. We also apply characteristic function on these matrices to enhance their discriminative capabilities. Then we calculate the statistics which include mean, variance, kurtosis and skewness to form our feature sets. The presented empirical works demonstrate our proposed method can effectively detect three different types of steganography. This proves the universality of our proposed method as a blind steganalysis. In addition, the experimental results show our proposed method is capable of detecting small amount of the embedded message.

Estimating hidden message length in binary image embedded by using boundary pixels steganography

In this paper, we propose a new steganalytic method to detect the message hidden in a black and white image using the steganographic technique developed by Liang, Wang and Zhang. Our detection method estimates the length of hidden message embedded in a binary image. Although the hidden message embedded is visually imperceptible, it changes some image statistic (such as inter-pixels correlation). Based on this observation, we first derive the 512 patterns histogram from the boundary pixels as the distinguishing statistic, then we compute the histogram difference to determine the changes of the 512 patterns histogram induced by the embedding operation. Finally we propose histogram quotient to estimate the length of the embedded message. Experimental results confirm that the proposed method can effectively and reliably detect the length of the embedded message.

pGreen : a versatile and flexible binary Ti vector for Agrobacterium-mediated plant transformation

Binary Ti vectors are the plasmid vectors of choice in Agrobacterium-mediated plant transformation protocols. The pGreen series of binary Ti vectors are configured for ease-of-use and to meet the demands of a wide range of transformation procedures for many plant species. This plasmid system allows any arrangement of selectable marker and reporter gene at the right and left T-DNA borders without compromising the choice of restriction sites for cloning, since the pGreen cloning sites are based on the well-known pBluescript general vector plasmids. Its size and copy number in Escherichia coli offers increased efficiencies in routine in vitro recombination procedures. pGreen can replicate in Agrobacterium only if another plasmid, pSoup, is co-resident in the same strain. pSoup provides replication functions in trans for pGreen. The removal of RepA and Mob functions has enabled the size of pGreen to be kept to a minimum. Versions of pGreen have been used to transform several plant species with the same efficiencies as other binary Ti vectors. Information on the pGreen plasmid system is supplemented by an Internet site (http://www.pgreen.ac.uk) through which comprehensive information, protocols, order forms and lists of different pGreen marker gene permutations can be found.