Breast cancer prognosis risk estimation using integrated gene expression and clinical data

Novel prognostic markers are needed so newly diagnosed breast cancer patients do not undergo any unnecessary therapy. Various microarray gene expression datasets based studies have generated gene signatures to predict the prognosis outcomes, while ignoring the large amount of information contained in established clinical markers. Nevertheless, small sample sizes in individual microarray datasets remain a bottleneck in generating robust gene signatures that show limited predictive power. The aim of this study is to achieve high classification accuracy for the good prognosis group and then achieve high classification accuracy for the poor prognosis group.

RRHGE: a novel approach to classify the estrogen receptor based breast cancer subtypes

Breast cancer is the most common type of cancer among females with a high mortality rate. It is essential to classify the estrogen receptor based breast cancer subtypes into correct subclasses, so that the right treatments can be applied to lower the mortality rate. Using gene signatures derived from gene interaction networks to classify breast cancers has proven to be more reproducible and can achieve higher classification performance. However, the interactions in the gene interaction network usually contain many false-positive interactions that do not have any biological meanings. Therefore, it is a challenge to incorporate the reliability assessment of interactions when deriving gene signatures from gene interaction networks. How to effectively extract gene signatures from available resources is critical to the success of cancer classification.

All signals are not equal: acoustic signalling of individuality, sex and breeding status in a cooperative breeder

Repeated interactions between individuals in socially living animals select for the evolution of signals that convey information identifying individuals or categories of individuals, which may enable the discrimination of familiar versus unfamiliar individuals. Such information may help animals maximize their inclusive fitness by adjusting their own behaviour, allowing them to avoid conflict, preferentially direct help and/or ignore unreliable individuals. Acoustic signals in birds provide the potential to encode individual-specific information. We examined the degree to which individual identity, sex, breeding status, group membership and genetic relatedness were related to variability in six different call types, which occurred across a variety of different behavioural contexts in the apostlebird, Struthidea cinerea, a socially living and cooperatively breeding Australian passerine. We demonstrated that not all calls reflected the same extent of information. Of the six call types, call variation was related to individual identity in three call types, breeding status in two call types and sex and group relatedness in one call type. Finally, variation in two call types was not related to any of the measured variables. Our results suggest that some, but not all, acoustic signals in apostlebirds may be selected for individual distinctiveness between individuals and categories of individuals (male versus female, breeder versus nonbreeder), and these signals may be important in determining levels of cooperation and interaction between individuals in this cooperatively breeding society. © 2014 The Association for the Study of Animal Behaviour.

IPA: Integrated predictive gene signature from gene expression based breast cancer patient samples

Background: Novel predictive markers are needed to accurately diagnose the breast cancer patients so they do not need to undergo any unnecessary aggressive therapies. Various gene expression studies based predictive gene signatureshave generated in the recent past to predict the binary estrogen-receptor subclass or to predict the therapy response subclass. However, the existing algorithms comes with many limitations, including low predictive performances over multiple cohorts of patients and non-significant or limited biological roles associated with thepredictive gene signatures. Therefore, the aim of this study is to develop novel predictive markers with improved performances.Methods: We propose a novel prediction algorithm called IPA to construct a predictive gene signature for performing multiple prediction tasks of predicting estrogen-receptor based binary subclass and predicting chemotherapy response (neoadjuvantly) based binary subclass. The constructed gene signature with considering multiple classification techniques was used to evaluate the algorithm performance on multiple cohorts of breast cancer patients.Results: The evaluation on multiple validation cohorts demonstrated that proposed algorithm achieved stable and high performance to perform prediction tasks, with consideration given to any classification techniques. We show that the predictive gene signature of our proposed algorithm reflects the mechanisms underlying the estrogen-receptors or response to therapy with significant greater biological interpretations, compared with the other existing algorithm.

Control flow-based malware variant detection

Static detection of malware variants plays an important role in system security and control flow has been shown as an effective characteristic that represents polymorphic malware. In our research, we propose a similarity search of malware to detect these variants using novel distance metrics. We describe a malware signature by the set of control flowgraphs the malware contains. We use a distance metric based on the distance between feature vectors of string-based signatures. The feature vector is a decomposition of the set of graphs into either fixed size k-subgraphs, or q-gram strings of the high-level source after decompilation. We use this distance metric to perform pre-filtering. We also propose a more effective but less computationally efficient distance metric based on the minimum matching distance. The minimum matching distance uses the string edit distances between programs' decompiled flowgraphs, and the linear sum assignment problem to construct a minimum sum weight matching between two sets of graphs. We implement the distance metrics in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of a limited false positive rate and our system detects more malware variants when compared to the detection rates of other algorithms. © 2013 IEEE.

Utilization of organic matter by invertebrates along an estuarine gradient in an intermittently open estuary

In intermittently open estuaries, the sources of organic matter sustaining benthic invertebrates are likely to vary seasonally, particularly between periods of connection and disconnection with the ocean and higher and lower freshwater flows. This study investigated the contribution of allochthonous and autochthonous primary production to the diet of representative invertebrate species using stable isotope analysis (SIA) during the austral summer and winter (2008, 2009) in an intermittently open estuary on the south-eastern coast of Australia. As the study was conducted towards the end of a prolonged period of drought, a reduced influence of freshwater/terrestrial organic matter was expected. Sampling was conducted along an estuarine gradient, including upper, middle and lower reaches and showed that the majority of assimilated organic matter was derived from autochthonous estuarine food sources. Additionally, there was an input of allochthonous organic matter, which varied along the length of the estuary, indicated by distinct longitudinal trends in carbon and nitrogen stable isotope signatures along the estuarine gradient. Marine seaweed contributed to invertebrate diets in the lower reaches of the estuary, while freshwater/terrestrial organic matter had increased influence in the upper reaches. Suspension-feeding invertebrates derived large parts of their diet from freshwater/terrestrial material, despite flows being greatly reduced in comparison with non-drought years.

Cameras and body memory create new blends of performance with visual art practice

I propose that a learnt somatic experience of dance can translate into another discipline such as visual art. In my visual art practice I combine both photography, which is traditionally seen as a still medium, and performance in order to create a new form of embodiment. I have developed two series of art works of prints and video made in response to the Australian landscape. By analyzing my method of movement and photography I will describe how an embodied dance language can result in a material outcome – a series of drawings of light and movement, a body signature made possible through old and new technology. I have activated a performative state while capturing images discovering new ways of using technology reliant upon my knowledge of dance, performance and photography. Making a human size camera to make analogue prints I gained an intuitive knowledge of light – a skill that has become foundational in performance and photography. In response to space and light in the Australian landscape I then built a custom made camera that allows for the longest possible time to capture an image. I move while taking the image and use the camera as if an eye at the end of my arm. In this way I activate dance skills and embodied knowledge of space, timing and light, opening up a radical space for new thinking, making and performing.Furthermore this process engages memory and sentiment embodied through age. Many artists have responded to the unique qualities of the Australian landscape and by using a performative/photographic approach I have engaged with my own body memory. Being brought up in the landscape and training in ballet my body has acquired memories at a cellular level. My method has given memory a voice. In doing these works I have become conscious of how unconscious memories of the space and light in the landscape is a movement vocabulary activated in a way that ‘feels’ like dancing. As an ageing person this experience is profound and the resultant materialisation of the photographs and videos leave a material record of the event. The sentiments evoked through my process bridge the past with the present, the body with the mind, memory with body and space connecting disciplines in a new way.The materialisation of artworks itself continues cross-disciplinary processes using a technique that is a continuum of the performative. Through using technology I release memory of the landscape and pixel by pixel build imagery that relies on and is a part of the performative process. It is a photographic performance dance manifesting as pigment on paper exhibited a gallery context. The exhibition allows a space for the viewer to respond - re-membering the universal the act of moving. The works titled ‘body signatures’ and ‘Fly Rhythm’ become a communicative device in the gallery context.My paper through an analysis of process and methods used in making the two series will talk to several of the subjects listed and reveal a new way of connecting performance and visual art and old and new technologies.

Using otolith microchemistry and shape to assess the habitat value of oil structures for reef fish

Over 7500 oil and gas structures (e.g. oil platforms) are installed in offshore waters worldwide and many will require decommissioning within the next two decades. The decision to remove such structures or turn them into reefs (i.e. 'rigs-to-reefs') hinges on the habitat value they provide, yet this can rarely be determined because the residency of mobile species is difficult to establish. Here, we test a novel solution to this problem for reef fishes; the use of otolith (earstone) properties to identify oil structures of residence. We compare the otolith microchemistry and otolith shape of a site-attached coral reef fish (Pseudanthias rubrizonatus) among four oil structures (depth 82-135 m, separated by 9.7-84.2 km) on Australia's North West Shelf to determine if populations developed distinct otolith properties during their residency. Microchemical signatures obtained from the otolith edge using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) differed among oil structures, driven by elements Sr, Ba and Mn, and to a lesser extent Mg and Fe. A combination of microchemical data from the otolith edge and elliptical Fourier (shape) descriptors allowed allocation of individuals to their 'home' structure with moderate accuracy (overall allocation accuracy: 63.3%, range: 45.5-78.1%), despite lower allocation accuracies for each otolith property in isolation (microchemistry: 47.5%, otolith shape: 45%). Site-specific microchemical signatures were also stable enough through time to distinguish populations during 3 separate time periods, suggesting that residence histories could be recreated by targeting previous growth zones in the otolith. Our results indicate that reef fish can develop unique otolith properties during their residency on oil structures which may be useful for assessing the habitat value of individual structures. The approach outlined here may also be useful for determining the residency of reef fish on artificial reefs, which would assist productivity assessments of these habitats.

Spectral unmixing based on nonnegative matrix factorization with local smoothness constraint

Spectral unmixing (SU) is an emerging problem in the remote sensing image processing. Since both the endmember signatures and their abundances have nonnegative values, it is a natural choice to employ the attractive nonnegative matrix factorization (NMF) methods to solve this problem. Motivated by that the abundances are sparse, the NMF with local smoothness constraint (NMF-LSC) is proposed in this paper. In the proposed method, the smoothness constraint is utilized to impose the sparseness, instead of the traditional L1-norm which is restricted by the underlying column-sum-to-one requirement of the to the abundance matrix. Simulations show the advantages of our algorithm over the compared methods.

Cost-effective authentic and anonymous data sharing with forward security

Data sharing has never been easier with the advances of cloud computing, and an accurate analysis on the shared data provides an array of benefits to both the society and individuals. Data sharing with a large number of participants must take into account several issues, including efficiency, data integrity and privacy of data owner. Ring signature is a promising candidate to construct an anonymous and authentic data sharing system. It allows a data owner to anonymously authenticate his data which can be put into the cloud for storage or analysis purpose. Yet the costly certificate verification in the traditional public key infrastructure (PKI) setting becomes a bottleneck for this solution to be scalable. Identity-based (ID-based) ring signature, which eliminates the process of certificate verification, can be used instead. In this paper, we further enhance the security of ID-based ring signature by providing forward security: If a secret key of any user has been compromised, all previous generated signatures that include this user still remain valid. This property is especially important to any large scale data sharing system, as it is impossible to ask all data owners to re-authenticate their data even if a secret key of one single user has been compromised. We provide a concrete and efficient instantiation of our scheme, prove its security and provide an implementation to show its practicality.

Can mud (silt and clay) concentration be used to predict soil organic carbon content within seagrass ecosystems?

The emerging field of blue carbon science is seeking cost-effective ways to estimate the organic carbon content of soils that are bound by coastal vegetated ecosystems. Organic carbon (Corg) content in terrestrial soils and marine sediments has been correlated with mud content (i.e. silt and clay), however, empirical tests of this theory are lacking for coastal vegetated ecosystems. Here, we compiled data (n = 1345) on the relationship between Corg and mud (i.e. silt and clay, particle sizes <63 μm) contents in seagrass ecosystems (79 cores) and adjacent bare sediments (21 cores) to address whether mud can be used to predict soil Corg content. We also combined these data with the δ13C signatures of the soil Corg to understand the sources of Corg stores. The results showed that mud is positively correlated with soil Corg content only when the contribution of seagrass-derived Corg to the sedimentary Corg pool is relatively low, such as in small and fast growing meadows of the genera Zostera, Halodule and Halophila, and in bare sediments adjacent to seagrass ecosystems. In large and long-living seagrass meadows of the genera Posidonia and Amphibolis there was a lack of, or poor relationship between mud and soil Corg content, related to a higher contribution of seagrass-derived Corg to the sedimentary Corg pool in these meadows. The relative high soil Corg contents with relatively low mud contents (i.e. mud-Corg saturation) together with significant allochthonous inputs of terrestrial organic matter could overall disrupt the correlation expected between soil Corg and mud contents. This study shows that mud (i.e. silt and clay content) is not a universal proxy for blue carbon content in seagrass ecosystems, and therefore should not be applied generally across all seagrass habitats. Mud content can only be used as a proxy to estimate soil Corg content for scaling up purposes when opportunistic and/or low biomass seagrass species (i.e. Zostera, Halodule and Halophila) are present (explaining 34 to 91% of variability), and in bare sediments (explaining 78% of the variability).

Comparison of marine macrophytes for their contributions to blue carbon sequestration

Many marine ecosystems have the capacity for long-term storage of organic carbon (C) in what are termed "blue carbon" systems. While blue carbon systems (saltmarsh, mangrove, and seagrass) are efficient at long-term sequestration of organic carbon (C), much of their sequestered C may originate from other (allochthonous) habitats. Macroalgae, due to their high rates of production, fragmentation, and ability to be transported, would also appear to be able to make a significant contribution as C donors to blue C habitats. In order to assess the stability of macroalgal tissues and their likely contribution to long-term pools of C, we applied thermogravimetric analysis (TGA) to 14 taxa of marine macroalgae and coastal vascular plants. We assessed the structural complexity of multiple lineages of plant and tissue types with differing cell wall structures and found that decomposition dynamics varied significantly according to differences in cell wall structure and composition among taxonomic groups and tissue function (photosynthetic vs. attachment). Vascular plant tissues generally exhibited greater stability with a greater proportion of mass loss at temperatures > 300 degrees C (peak mass loss -320 degrees C) than macroalgae (peak mass loss between 175-300 degrees C), consistent with the lignocellulose matrix of vascular plants. Greater variation in thermogravimetric signatures within and among macroalgal taxa, relative to vascular plants, was also consistent with the diversity of cell wall structure and composition among groups. Significant degradation above 600 degrees C for some macroalgae, as well as some belowground seagrass tissues, is likely due to the presence of taxon-specific compounds. The results of this study highlight the importance of the lignocellulose matrix to the stability of vascular plant sources and the potentially significant role of refractory, taxon-specific compounds (carbonates, long-chain lipids, alginates, xylans, and sulfated polysaccharides) from macroalgae and seagrasses for their long-term sedimentary C storage. This study shows that marine macroalgae do contain refractory compounds and thus may be more valuable to long-term carbon sequestration than we previously have considered.