INT6/EIF3E interacts with ATM and is required for proper execution of the DNA damage response in human cells

Altered expression of the INT6 gene, encoding the e subunit of the translational initiation factor eIF3, occurs in human breast cancers, but how INT6 relates to carcinogenesis remains unestablished. Here, we show that INT6 is involved in the DNA damage response. INT6 was required for cell survival following γ-irradiation and G(2)-M checkpoint control. RNA interference-mediated silencing of INT6 reduced phosphorylation of the checkpoint kinases CHK1 and CHK2 after DNA damage. In addition, INT6 silencing prevented sustained accumulation of ataxia telangiectasia mutated (ATM) at DNA damage sites in cells treated with γ-radiation or the radiomimetic drug neocarzinostatin. Mechanistically, this result could be explained by interaction of INT6 with ATM, which together with INT6 was recruited to the sites of DNA damage. Finally, INT6 silencing also reduced ubiquitylation events that promote retention of repair proteins at DNA lesions. Accordingly, accumulation of the repair factor BRCA1 was defective in the absence of INT6. Our findings reveal unexpected and striking connections of INT6 with ATM and BRCA1 and suggest that the protective action of INT6 in the onset of breast cancers relies on its involvement in the DNA damage response.

Empirical analysis of the effect of dimension reduction and word order on semantic vectors

The aim of this paper is to provide a comparison of various algorithms and parameters to build reduced semantic spaces. The effect of dimension reduction, the stability of the representation and the effect of word order are examined in the context of the five algorithms bearing on semantic vectors: Random projection (RP), singular value decom- position (SVD), non-negative matrix factorization (NMF), permutations and holographic reduced representations (HRR). The quality of semantic representation was tested by means of synonym finding task using the TOEFL test on the TASA corpus. Dimension reduction was found to improve the quality of semantic representation but it is hard to find the optimal parameter settings. Even though dimension reduction by RP was found to be more generally applicable than SVD, the semantic vectors produced by RP are somewhat unstable. The effect of encoding word order into the semantic vector representation via HRR did not lead to any increase in scores over vectors constructed from word co-occurrence in context information. In this regard, very small context windows resulted in better semantic vectors for the TOEFL test.

A study on the effects of routing symbol design on process model comprehension

Process modeling grammars are used to create models of business processes. In this paper, we discuss how different routing symbol designs affect an individual's ability to comprehend process models. We conduct an experiment with 154 students to ascertain which visual design principles influence process model comprehension. Our findings suggest that design principles related to perceptual discriminability and pop out improve comprehension accuracy. Furthermore, semantic transparency and aesthetic design of symbols lower the perceived difficulty of comprehension. Our results inform important principles about notational design of process modeling grammars and the effective use of process modeling in practice.

BSTA Promotes mTORC2-Mediated Phosphorylation of Akt1 to Suppress Expression of FoxC2 and Stimulate Adipocyte Differentiation

Phosphorylation and activation of Akt1 is a crucial signaling event that promotes adipogenesis. However, neither the complex multistep process that leads to activation of Akt1 through phosphorylation at Thr308 and Ser473 nor the mechanism by which Akt1 stimulates adipogenesis is fully understood. We found that the BSD domain–containing signal transducer and Akt interactor (BSTA) promoted phosphorylation of Akt1 at Ser473 in various human and murine cells, and we uncovered a function for the BSD domain in BSTA-Akt1 complex formation. The mammalian target of rapamycin complex 2 (mTORC2) facilitated the phosphorylation of BSTA and its association with Akt1, and the BSTA-Akt1 interaction promoted the association of mTORC2 with Akt1 and phosphorylation of Akt1 at Ser473 in response to growth factor stimulation. Furthermore, analyses of bsta gene-trap murine embryonic stem cells revealed an essential function for BSTA and phosphorylation of Akt1 at Ser473 in promoting adipocyte differentiation, which required suppression of the expression of the gene encoding the transcription factor FoxC2. These findings indicate that BSTA is a molecular switch that promotes phosphorylation of Akt1 at Ser473 and reveal an mTORC2-BSTA-Akt1-FoxC2–mediated signaling mechanism that is critical for adipocyte differentiation.

Genetic polymorphisms in the human tissue kallikrein (KLK) locus and their implication in various malignant and non-malignant diseases

The Kallikrein (KLK) gene locus encodes a family of serine proteases and is the largest contiguous cluster of protease-encoding genes attributed an evolutionary age of 330 million years. The KLK locus has been implicated as a high susceptibility risk loci in numerous cancer studies through the last decade. The KLK3 gene already has established clinical relevance as a biomarker in prostate cancer prognosis through its encoded protein, prostate-specific antigen. Data mined through genome-wide association studies (GWAS) and next-generation sequencing point to many important candidate single nucleotide polymorphisms (SNPs) in KLK3 and other KLK genes. SNPs in the KLK locus have been found to be associated with several diseases including cancer, hypertension, cardiovascular disease and atopic dermatitis. Moreover, introducing a model incorporating SNPs to improve the efficiency of prostate-specific antigen in detecting malignant states of prostate cancer has been recently suggested. Establishing the functional relevance of these newly-discovered SNPs, and their interactions with each other, through in silico investigations followed by experimental validation, can accelerate the discovery of diagnostic and prognostic biomarkers. In this review, we discuss the various genetic association studies on the KLK loci identified either through candidate gene association studies or at the GWAS and post-GWAS front to aid researchers in streamlining their search for the most significant, relevant and therapeutically promising candidate KLK gene and/or SNP for future investigations.

QUT_Para at TREC 2012 Web Track : word associations for retrieving web documents

Many existing information retrieval models do not explicitly take into account in- formation about word associations. Our approach makes use of rst and second order relationships found in natural language, known as syntagmatic and paradigmatic associ- ations, respectively. This is achieved by using a formal model of word meaning within the query expansion process. On ad hoc retrieval, our approach achieves statistically sig- ni cant improvements in MAP (0.158) and P@20 (0.396) over our baseline model. The ERR@20 and nDCG@20 of our system was 0.249 and 0.192 respectively. Our results and discussion suggest that information about both syntagamtic and paradigmatic associa- tions can assist with improving retrieval eectiveness on ad hoc retrieval.

The human tissue kallikrein and kallikrein-related peptidase family

The human kallikrein-related peptidases are a subgroup of trypsin and chymotrypsin-like serine peptidases that are characterized by their homology to tissue kallikrein or kallikrein 1 (KLK1) encoded by the KLK1 gene (reviewed in[1-4]). The human KLK locus spans an approximately 320 kb region on chromosome 19q13.3-13.4 and contains fifteen genes encoding KLK1 and fourteen other kallikrein-related peptidases, KLK2-KLK15, which have been named contiguously in the locus in the order of their discovery [5-8] (Figure 606.1). It is the largest contiguous cluster of serine protease encoding genes in the human genome which has evolved from gene duplication of KLK1 and then subsequent reduplication of the newly evolved KLK genes [2]. The high conservation noted for KLK1-KLK3 (62-77%) reflects the proposed duplication of the KLK1 gene that produced the KLK2 gene which further generated the KLK3 gene. In contrast, the newer KLK4-KLK15 proteases share much less similarity, from 24-66%, although strong homology between KLK4 and KLK5, KLK9 and KLK11, and KLK10 and KLK12 suggests these genes are duplications of each other [2]...

How activation, entanglement, and searching a semantic network contribute to event memory

Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.

The complete mitochondrial genome of the flesh fly, Sarcophaga impatiens Walker (Diptera: Sarcophagidae)

Approximately 2500 fly species comprise the Sarcophagidae family worldwide. The complete mitochondrial genome of the carrion-breeding, forensically important Sarcophaga impatiens Walker (Diptera: Sarcophagidae) from Australia was sequenced. The 15,169 bp circular genome contains the 37 genes found in a typical Metazoan genome: 13 protein-coding genes, 2 ribosomal RNA genes and 22 transfer RNA genes. It also contains one non-coding A+T-rich region. The arrangement of the genes was the same as that found in the ancestral insect. All the protein initiation codons are ATN, except for cox1 that begins with TCG (encoding S). The 22 tRNA anticodons of S. impatiens are consistent with those observed in Drosophila yakuba, and all form the typical cloverleaf structure, except for tRNA-Ser(AGN) that lacks the DHU arm. The mitochondrial genome of Sarcophaga presented will be valuable for resolving phylogenetic relationships within the family Sarcophagidae and the order Diptera, and could be used to identify favourable genetic markers for species identifications for forensic purposes.

Approaches to designing for older adults' intuitive interaction with complex devices

Many older people have difficulties using modern consumer products due to increased product complexity both in terms of functionality and interface design. Previous research has shown that older people have more difficulty in using complex devices intuitively when compared to the younger. Furthermore, increased life expectancy and a falling birth rate have been catalysts for changes in world demographics over the past two decades. This trend also suggests a proportional increase of older people in the work-force. This realisation has led to research on the effective use of technology by older populations in an effort to engage them more productively and to assist them in leading independent lives. Ironically, not enough attention has been paid to the development of interaction design strategies that would actually enable older users to better exploit new technologies. Previous research suggests that if products are designed to reflect people's prior knowledge, they will appear intuitive to use. Since intuitive interfaces utilise domain-specific prior knowledge of users, they require minimal learning for effective interaction. However, older people are very diverse in their capabilities and domain-specific prior knowledge. In addition, ageing also slows down the process of acquiring new knowledge. Keeping these suggestions and limitations in view, the aim of this study was set to investigate possible approaches to developing interfaces that facilitate their intuitive use by older people. In this quest to develop intuitive interfaces for older people, two experiments were conducted that systematically investigated redundancy (the use of both text and icons) in interface design, complexity of interface structure (nested versus flat), and personal user factors such as cognitive abilities, perceived self-efficacy and technology anxiety. All of these factors could interfere with intuitive use. The results from the first experiment suggest that, contrary to what was hypothesised, older people (65+ years) completed the tasks on the text only based interface design faster than on the redundant interface design. The outcome of the second experiment showed that, as expected, older people took more time on a nested interface. However, they did not make significantly more errors compared with younger age groups. Contrary to what was expected, older age groups also did better under anxious conditions. The findings of this study also suggest that older age groups are more heterogeneous in their capabilities and their intuitive use of contemporary technological devices is mediated more by domain-specific technology prior knowledge and by their cognitive abilities, than chronological age. This makes it extremely difficult to develop product interfaces that are entirely intuitive to use. However, by keeping in view the cognitive limitations of older people when interfaces are developed, and using simple text-based interfaces with flat interface structure, would help them intuitively learn and use complex technological products successfully during early encounter with a product. These findings indicate that it might be more pragmatic if interfaces are designed for intuitive learning rather than for intuitive use. Based on this research and the existing literature, a model for adaptable interface design as a strategy for developing intuitively learnable product interfaces was proposed. An adaptable interface can initially use a simple text only interface to help older users to learn and successfully use the new system. Over time, this can be progressively changed to a symbols-based nested interface for more efficient and intuitive use.

User-driven quality of experience modelling for mobile video optimisation

The increasing demand for mobile video has attracted much attention from both industry and researchers. To satisfy users and to facilitate the usage of mobile video, providing optimal quality to the users is necessary. As a result, quality of experience (QoE) becomes an important focus in measuring the overall quality perceived by the end-users, from the aspects of both objective system performance and subjective experience. However, due to the complexity of user experience and diversity of resources (such as videos, networks and mobile devices), it is still challenging to develop QoE models for mobile video that can represent how user-perceived value varies with changing conditions. Previous QoE modelling research has two main limitations: aspects influencing QoE are insufficiently considered; and acceptability as the user value is seldom studied. Focusing on the QoE modelling issues, two aims are defined in this thesis: (i) investigating the key influencing factors of mobile video QoE; and (ii) establishing QoE prediction models based on the relationships between user acceptability and the influencing factors, in order to help provide optimal mobile video quality. To achieve the first goal, a comprehensive user study was conducted. It investigated the main impacts on user acceptance: video encoding parameters such as quantization parameter, spatial resolution, frame rate, and encoding bitrate; video content type; mobile device display resolution; and user profiles including gender, preference for video content, and prior viewing experience. Results from both quantitative and qualitative analysis revealed the significance of these factors, as well as how and why they influenced user acceptance of mobile video quality. Based on the results of the user study, statistical techniques were used to generate a set of QoE models that predict the subjective acceptability of mobile video quality by using a group of the measurable influencing factors, including encoding parameters and bitrate, content type, and mobile device display resolution. Applying the proposed QoE models into a mobile video delivery system, optimal decisions can be made for determining proper video coding parameters and for delivering most suitable quality to users. This would lead to consistent user experience on different mobile video content and efficient resource allocation. The findings in this research enhance the understanding of user experience in the field of mobile video, which will benefit mobile video design and research. This thesis presents a way of modelling QoE by emphasising user acceptability of mobile video quality, which provides a strong connection between technical parameters and user-desired quality. Managing QoE based on acceptability promises the potential for adapting to the resource limitations and achieving an optimal QoE in the provision of mobile video content.

The implications of cross-regional differences for the design of In-vehicle Information Systems : a comparison of Australian and Chinese drivers

The increasing global distribution of automobiles necessitates that the design of In-vehicle Information Systems (IVIS) is appropriate for the regions to which they are being exported. Differences between regions such as culture, environment and traffic context can influence the needs, usability and acceptance of IVIS. This paper describes two studies aimed at identifying regional differences in IVIS design needs and preferences across drivers from Australia and China to determine the impact of any differences on IVIS design. Using a questionnaire and interaction clinics, the influence of cultural values and driving patterns on drivers' preferences for, and comprehension of, surface- and interaction-level aspects of IVIS interfaces was explored. Similarities and differences were found between the two regional groups in terms of preferences for IVIS input control types and labels and in the comprehension of IVIS functions. Specifically, Chinese drivers preferred symbols and Chinese characters over English words and were less successful (compared to Australians) at comprehending English abbreviations, particularly for complex IVIS functions. Implications in terms of the current trend to introduce Western-styled interfaces into other regions with little or no adaptation are discussed.

We still don’t know how much BPMN is enough – but we are getting closer

Process models expressed in BPMN typically rely on a small subset of all available symbols. In our 2008 study, we examined the composition of these subsets, and found that the distribution of BPMN symbols in practice closely resembles the frequency distribution of words in natural language. We offered some suggestions based on our findings, how to make the use of BPMN more manageable and also outlined ideas for further development of BPMN. Since this paper was published it has provoked spirited debate in the BPM practitioner community, prompted the definition of a modeling standard in US government, and helped shape the next generation of the BPMN standard.

Robust image hash functions using higher order spectra

Robust hashing is an emerging field that can be used to hash certain data types in applications unsuitable for traditional cryptographic hashing methods. Traditional hashing functions have been used extensively for data/message integrity, data/message authentication, efficient file identification and password verification. These applications are possible because the hashing process is compressive, allowing for efficient comparisons in the hash domain but non-invertible meaning hashes can be used without revealing the original data. These techniques were developed with deterministic (non-changing) inputs such as files and passwords. For such data types a 1-bit or one character change can be significant, as a result the hashing process is sensitive to any change in the input. Unfortunately, there are certain applications where input data are not perfectly deterministic and minor changes cannot be avoided. Digital images and biometric features are two types of data where such changes exist but do not alter the meaning or appearance of the input. For such data types cryptographic hash functions cannot be usefully applied. In light of this, robust hashing has been developed as an alternative to cryptographic hashing and is designed to be robust to minor changes in the input. Although similar in name, robust hashing is fundamentally different from cryptographic hashing. Current robust hashing techniques are not based on cryptographic methods, but instead on pattern recognition techniques. Modern robust hashing algorithms consist of feature extraction followed by a randomization stage that introduces non-invertibility and compression, followed by quantization and binary encoding to produce a binary hash output. In order to preserve robustness of the extracted features, most randomization methods are linear and this is detrimental to the security aspects required of hash functions. Furthermore, the quantization and encoding stages used to binarize real-valued features requires the learning of appropriate quantization thresholds. How these thresholds are learnt has an important effect on hashing accuracy and the mere presence of such thresholds are a source of information leakage that can reduce hashing security. This dissertation outlines a systematic investigation of the quantization and encoding stages of robust hash functions. While existing literature has focused on the importance of quantization scheme, this research is the first to emphasise the importance of the quantizer training on both hashing accuracy and hashing security. The quantizer training process is presented in a statistical framework which allows a theoretical analysis of the effects of quantizer training on hashing performance. This is experimentally verified using a number of baseline robust image hashing algorithms over a large database of real world images. This dissertation also proposes a new randomization method for robust image hashing based on Higher Order Spectra (HOS) and Radon projections. The method is non-linear and this is an essential requirement for non-invertibility. The method is also designed to produce features more suited for quantization and encoding. The system can operate without the need for quantizer training, is more easily encoded and displays improved hashing performance when compared to existing robust image hashing algorithms. The dissertation also shows how the HOS method can be adapted to work with biometric features obtained from 2D and 3D face images.

Automatic query expansion : a structural linguistic perspective

A user’s query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques ignore information about the dependencies that exist between words in natural language. However, more recent approaches have demonstrated that by explicitly modeling associations between terms significant improvements in retrieval effectiveness can be achieved over those that ignore these dependencies. State-of-the-art dependency-based approaches have been shown to primarily model syntagmatic associations. Syntagmatic associations infer a likelihood that two terms co-occur more often than by chance. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process will improve retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.