Low MAD2 expression levels associate with reduced progression-free survival in patients with high-grade serous epithelial ovarian cancer

Epithelial ovarian cancer (EOC) has an innate susceptibility to become chemoresistant. Up to 30% of patients do not respond to conventional chemotherapy [paclitaxel (Taxol®) in combination with carboplatin] and, of those who have an initial response, many patients relapse. Therefore, an understanding of the molecular mechanisms that regulate cellular chemotherapeutic responses in EOC cells has the potential to impact significantly on patient outcome. The mitotic arrest deficiency protein 2 (MAD2), is a centrally important mediator of the cellular response to paclitaxel. MAD2 immunohistochemical analysis was performed on 82 high-grade serous EOC samples. A multivariate Cox regression analysis of nuclear MAD2 IHC intensity adjusting for stage, tumour grade and optimum surgical debulking revealed that low MAD2 IHC staining intensity was significantly associated with reduced progression-free survival (PFS) (p = 0.0003), with a hazard ratio of 4.689. The in vitro analyses of five ovarian cancer cell lines demonstrated that cells with low MAD2 expression were less sensitive to paclitaxel. Furthermore, paclitaxel-induced activation of the spindle assembly checkpoint (SAC) and apoptotic cell death was abrogated in cells transfected with MAD2 siRNA. In silico analysis identified a miR-433 binding domain in the MAD2 3' UTR, which was verified in a series of experiments. Firstly, MAD2 protein expression levels were down-regulated in pre-miR-433 transfected A2780 cells. Secondly, pre-miR-433 suppressed the activity of a reporter construct containing the 3'-UTR of MAD2. Thirdly, blocking miR-433 binding to the MAD2 3' UTR protected MAD2 from miR-433 induced protein down-regulation. Importantly, reduced MAD2 protein expression in pre-miR-433-transfected A2780 cells rendered these cells less sensitive to paclitaxel. In conclusion, loss of MAD2 protein expression results in increased resistance to paclitaxel in EOC cells. Measuring MAD2 IHC staining intensity may predict paclitaxel responses in women presenting with high-grade serous EOC.

A sequential algorithm for sparse support vector classifiers

Support vector machines (SVMs), though accurate, are not preferred in applications requiring high classification speed or when deployed in systems of limited computational resources, due to the large number of support vectors involved in the model. To overcome this problem we have devised a primal SVM method with the following properties: (1) it solves for the SVM representation without the need to invoke the representer theorem, (2) forward and backward selections are combined to approach the final globally optimal solution, and (3) a criterion is introduced for identification of support vectors leading to a much reduced support vector set. In addition to introducing this method the paper analyzes the complexity of the algorithm and presents test results on three public benchmark problems and a human activity recognition application. These applications demonstrate the effectiveness and efficiency of the proposed algorithm.


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Mitochondrial DNA haplotype analysis of liver fluke in bison from Bialowieza Primaeval Forest indicates domestic cattle as the likely source of infection

We have determined the mitochondrial genotype of liver fluke present in Bison (Bison bonasus) from the herd maintained in the Bialowieza National Park in order to determine the origin of the infection. Our results demonstrated that the infrapopulations present in the bison were genetically diverse and were likely to have been derived from the population present in local cattle. From a consideration of the genetic structure of the liver fluke infrapopulations we conclude that the provision of hay at feeding stations may be implicated in the transmission of this parasite to the bison. This information may be of relevance to the successful management of the herd. © 2012 Elsevier B.V.

Predicting the impacts of climate change on the distribution of threatened forest-restricted birds in Madagascar

The greatest common threat to birds in Madagascar has historically been from anthropogenic deforestation. During recent decades, global climate change is now also regarded as a significant threat to biodiversity. This study uses Maximum Entropy species distribution modeling to explore how potential climate change could affect the distribution of 17 threatened forest endemic bird species, using a range of climate variables from the Hadley Center's HadCM3 climate change model, for IPCC scenario B2a, for 2050. We explore the importance of forest cover as a modeling variable and we test the use of pseudo-presences drawn from extent of occurrence distributions. Inclusion of the forest cover variable improves the models and models derived from real-presence data with forest layer are better predictors than those from pseudo-presence data. Using real-presence data, we analyzed the impacts of climate change on the distribution of nine species. We could not predict the impact of climate change on eight species because of low numbers of occurrences. All nine species were predicted to experience reductions in their total range areas, and their maximum modeled probabilities of occurrence. In general, species range and altitudinal contractions follow the reductive trend of the Maximum presence probability. Only two species (Tyto soumagnei and Newtonia fanovanae) are expected to expand their altitude range. These results indicate that future availability of suitable habitat at different elevations is likely to be critical for species persistence through climate change. Five species (Eutriorchis astur, Neodrepanis hypoxantha, Mesitornis unicolor, Euryceros prevostii, and Oriola bernieri) are probably the most vulnerable to climate change. Four of them (E. astur, M. unicolor, E. prevostii, and O. bernieri) were found vulnerable to the forest fragmentation during previous research. Combination of these two threats in the future could negatively affect these species in a drastic way. Climate change is expected to act differently on each species and it is important to incorporate complex ecological variables into species distribution models.

Glacial to paraglacial history and forest recovery in the Oglio glacier system (Italian Alps) between 26 and 15 ka cal BP

The integrated stratigraphic, radiocarbon and palynological record from an end-moraine system of the Oglio valley glacier (Italian Alps), propagating a lobe upstream in a lateral reach, provided evidence for a complete cycle of glacial advance, culmination and withdrawal during the Last Glacial Maximum and early Lateglacial. The glacier culminated in the end moraine shortly after 25.8 +/- 0.8 ka cal BP, and cleared the valley floor 18.3-17.2 +/- 0.3 ka cal BP. A primary paraglacial phase is then recorded by fast progradation of the valley floor.

As early as 16.7 +/- 0.3 ka cal BP, early stabilization of alluvial fans and lake filling promoted expansion of cembran pine. This is an unprecedented evidence of direct tree response to depletion of paraglacial activity during the early Lateglacial, and also documents the cembran pine survival in the mountain belt of the Italian Alps during the last glaciation. Between 16.1 and 14.6 +/- 0.5 ka cal BP, debris cones emplacement points to a moisture increase favouring tree Betula and Pinus sylvestris-mugo. A climate perturbation renewed paraglacial activity. According to cosmogenic ages on glacial deposits and AMS radiocarbon ages from lake records in South-Eastern Alps such phase compares favourably with the Gschnitz stadial and with the oscillations recorded at lakes Ragogna. Langsee and Jeserzersee, most probably forced by the latest freshening phases of the Heinrich Event 1.

A further sharp pine rise marks the subsequent onset of Bolling interstadial. The chronology of the Oglio glacier compares closely with major piedmont glaciers on the Central and Eastern Alpine forelands. On the other hand, the results of the present study imply a chronostratigraphic re-assessment of the recent geological mapping of the Central Italian Alps. (C) 2012 Elsevier Ltd. All rights reserved.

Sequencing and its consequences:Path dependence and the relationships between genetics and medicalization

Both advocacy for and critiques of the Human Genome Project assume a self-sustaining relationship between genetics and. medicalization. However, this assumption ignores the ways in which the meanings of genetic research are conditional on its position in sequences of events. Based, on analyses of three conditions for which at least one putative gene or genetic marker has been identified, this article argues that critical junctures in the institutional stabilization of phenotypes and the mechanisms that sustain such classifications over time configure the practices and meanings of genetic research. Path dependence is critical to understanding the lack of consistent fit between genetics and medlcalization.

The relationship between spatial planning and economic competitiveness: the ‘path to economic nirvana’ or a ‘dangerous obsession’?

This paper offers a contribution to contemporary studies of spatial planning. In particular, it problematises the relationship between neoliberal competitiveness and spatial planning. Neoliberal competitiveness is a hegemonic discourse in public policy as it (allegedly) provides the ‘path to economic nirvana’. However, commentators have critiqued its theoretical underpinnings and labelled it a ‘dangerous obsession’ for policy makers. Another set of literatures argues that spatial planning can be understood as a form of ‘neoliberal spatial governance’ and read in a ‘postpolitical’ framework that ‘privileges competitiveness’. Synthesising these debates this paper critically analyses the application and operationalisation of neoliberal competitiveness in Northern Ireland and Belfast. In focusing on this unique case study—a deeply divided society with a turbulent history—the paper takes the debate forward in arguing that rather than offering the ‘path to economic nirvana’ neoliberal competitiveness is a ‘postpolitical strategy’ and represents a ‘dangerous obsession’ for spatial planning.

Is a single item stress measure independently associated with subsequent severe injury: a prospective cohort study of 16,385 forest industry employees

Background: A previous review showed that high stress increases the risk of occupational injury by three- to five-fold. However, most of the prior studies have relied on short follow-ups. In this prospective cohort study we examined the effect of stress on recorded hospitalised injuries in an 8-year follow-up.
Methods: A total of 16,385 employees of a Finnish forest company responded to the questionnaire. Perceived stress was measured with a validated single-item measure, and analysed in relation recorded hospitalised injuries from 1986 to 2008. We used Cox proportional hazard regression models to examine the prospective associations between work stress, injuries and confounding factors.
Results: Highly stressed participants were approximately 40% more likely to be hospitalised due to injury over the follow-up period than participants with low stress. This association remained significant after adjustment for age, gender, marital status, occupational status, educational level, and physical work environment.
Conclusions: High stress is associated with an increased risk of severe injury.

Android Malware Detection Using Parallel Machine Learning Classifiers

Mobile malware has continued to grow at an alarming rate despite on-going mitigation efforts. This has been much more prevalent on Android due to being an open platform that is rapidly overtaking other competing platforms in the mobile smart devices market. Recently, a new generation of Android malware families has emerged with advanced evasion capabilities which make them much more difficult to detect using conventional methods. This paper proposes and investigates a parallel machine learning based classification approach for early detection of Android malware. Using real malware samples and benign applications, a composite classification model is developed from parallel combination of heterogeneous classifiers. The empirical evaluation of the model under different combination schemes demonstrates its efficacy and potential to improve detection accuracy. More importantly, by utilizing several classifiers with diverse characteristics, their strengths can be harnessed not only for enhanced Android malware detection but also quicker white box analysis by means of the more interpretable constituent classifiers.

Machine Learning for Predictive Maintenance: A Multiple Classifiers Approach

In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

Polarisation independent resistively loaded frequency selective surface absorber with optimum oblique incidence performance

This study presents the design of a thin electromagnetic absorber which exhibits radar backscatter suppression that is independent of the wave polarisation at large incidence angles. The structure consists of a metal backed printed frequency selective surface (FSS), with resistors placed across narrow gaps inserted in the middle of each of the four sides of the conductor loops. The geometry of the periodic array and the value of the vertical and horizontal resistor pairs are carefully chosen to present a real impedance of 377 Ω at the centre operating frequency for both TE and TM polarised waves. Angular sensitivity and reflectivity bandwidth have been investigated for FSS absorber designs with thicknesses of 1, 2 and 3 mm. Each of the three structures was optimised to work at a centre frequency of 10 GHz and an incident angle of 45°. The design methodology is verified by measuring the radar backscatter suppression from a 3 mm (l / 10) thick screen in the frequency range 8–12 GHz. The absorber construction was simplified by filling the four metal gaps in each unit cell with shielding paint, and selecting the ink thickness to give the two required surface resistance values.