From art to science: the functional damage due to thumb osteoarthritis finely described by Velazquez 300 years before its clinical description

Velazquez showed to know the entity of thumb osteoarthritis by finely describing it in one of his paintings. The concepts of anatomical damage, loss of strenght, and functional impairment are transmitted to the observer

Translation of tissue-based artificial intelligence into clinical practice: from discovery to adoption.

Digital pathology (DP), or the digitization of pathology images, has transformed oncology research and cancer diagnostics. The application of artificial intelligence (AI) and other forms of machine learning (ML) to these images allows for better interpretation of morphology, improved quantitation of biomarkers, introduction of novel concepts to discovery and diagnostics (such as spatial distribution of cellular elements), and the promise of a new paradigm of cancer biomarkers. The application of AI to tissue analysis can take several conceptual approaches, within the domains of language modelling and image analysis, such as Deep Learning Convolutional Neural Networks, Multiple Instance Learning approaches, or the modelling of risk scores and their application to ML. The use of different approaches solves different problems within pathology workflows, including assistive applications for the detection and grading of tumours, quantification of biomarkers, and the delivery of established and new image-based biomarkers for treatment prediction and prognostic purposes. All these AI formats, applied to digital tissue images, are also beginning to transform our approach to clinical trials. In parallel, the novelty of DP/AI devices and the related computational science pipeline introduces new requirements for manufacturers to build into their design, development, regulatory and post-market processes, which may need to be taken into account when using AI applied to tissues in cancer discovery. Finally, DP/AI represents challenge to the way we accredit new diagnostic tools with clinical applicability, the understanding of which will allow cancer patients to have access to a new generation of complex biomarkers

The hominid thumb and its influence on the employment during evolution

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Strong oviposition preference for Bt over non-Bt maize in Spodoptera frugiperda and its implications for the evolution of resistance

BACKGROUND: Transgenic crops expressing Bt toxins have substantial benefits for growers in terms of reduced synthetic insecticide inputs, area-wide pest management and yield. This valuable technology depends upon delaying the evolution of resistance. The ‘high dose/refuge strategy’, in which a refuge of non-Bt plants is planted in close proximity to the Bt crop, is the foundation of most existing resistance management. Most theoretical analyses of the high dose/refuge strategy assume random oviposition across refugia and Bt crops. RESULTS: In this study we examined oviposition and survival of Spodoptera frugiperda across conventional and Bt maize and explored the impact of oviposition behavior on the evolution of resistance in simulation models. Over six growing seasons oviposition rates per plant were higher in Bt crops than in refugia. The Cry1F Bt maize variety retained largely undamaged leaves, and oviposition preference was correlated with the level of feeding damage in the refuge. In simulation models, damage-avoiding oviposition accelerated the evolution of resistance and either led to requirements for larger refugia or undermined resistance management altogether. Since larval densities affected oviposition preferences, pest population dynamics affected resistance evolution: larger refugia were weakly beneficial for resistance management if they increased pest population sizes and the concomitant degree of leaf damage. CONCLUSIONS: Damaged host plants have reduced attractiveness to many insect pests, and crops expressing Bt toxins are generally less damaged than conventional counterparts. Resistance management strategies should take account of this behavior, as it has the potential to undermine the effectiveness of existing practice, especially in the tropics where many pests are polyvoltinous. Efforts to bring down total pest population sizes and/or increase the attractiveness of damaged conventional plants will have substantial benefits for slowing the evolution of resistance

Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer

Contains fulltext : 206059.pdf (publisher's version ) (Open Access

Plan prospectivo para la implementación de un centro de pensamiento prospectivo en tunja para Boyacá al 2012

Mapas Tablas GraficosRealizar un plan para la implementación de un centro de pensamiento prospectivo en Tunja para Boyacá al 2012. Para el desarrollo del siguiente plan se ha utilizado el método Delphi, el método Micmac, el método Mactor, que permitirán visualizar la ejecución del centro prospectivo.In the following work it is approached, in a general way, the Prospective Plan developed for the implementation of a center of Prospective thought in even Tunja Boyacá at the 2012. For the elaboration of the same one, a series of methods and tools have been used, inside which are: Method Delphi, which allows the gathering of data, to identify the variables and incident actors in the Plan; With the Method Micmac is formed the methodological structure where the data are analyzed obtained previously and assigning the qualification of the same ones, of this analysis is reflected the influence planes between actors and variables; Later on application is given to the Method Mactor, by means of the one which, the game of actors settles down and it is determined the alliance level or conflicts among the same ones

Ianus: an Adpative FPGA Computer

Dedicated machines designed for specific computational algorithms can outperform conventional computers by several orders of magnitude. In this note we describe {\it Ianus}, a new generation FPGA based machine and its basic features: hardware integration and wide reprogrammability. Our goal is to build a machine that can fully exploit the performance potential of new generation FPGA devices. We also plan a software platform which simplifies its programming, in order to extend its intended range of application to a wide class of interesting and computationally demanding problems. The decision to develop a dedicated processor is a complex one, involving careful assessment of its performance lead, during its expected lifetime, over traditional computers, taking into account their performance increase, as predicted by Moore's law. We discuss this point in detail