La vía de la insulina y el factor de crecimiento similar a la insulina, una nueva diana terapéutica en oncología

La biología molecular del cáncer ha permitido identificar nuevas dianas para atacar las células tumorales. Recientemente se ha propuesto la vía de señalización de la insulina y el factor de crecimiento similar a la insulina como una de estas dianas. En esta revisión se describe su función biológica, los datos de laboratorio y estudios poblacionales que alertan de su papel en el cáncer y se describen los elementos claves de esta vía de señalización: los ligandos (insulina, IGF1, IGF2), sus receptores y la cascada de señales intracelular que desencadena su activación. Así mismo se revisan las distintas estrategias que se están investigando para bloquearla, algunas de las cuales ya se encuentran en estudios avanzados fase III. Los datos preliminares indican que los fármacos diseñados para bloquear esta vía pueden ser una nueva arma terapéutica para los pacientes oncológicos en un futuro próximo.The molecular biology of cancer has made it possible to identify new targets for attacking tumourous cells. One of these recently proposed targets is the insulin and insulin-like growth factor signaling pathway. This review describes its biological function, laboratory data, population studies that warn of its role in cancer, and the key elements of this signaling pathway: the ligands (insulin, IGF1, IGF2), its receptors and the cascade of intracellular signals that trigger its activation. Also reviewed are the different strategies under investigation for blocking it, some of which are already in phase III advanced studies. The preliminary data indicate that the medicines designed for blocking this pathway might be a new thera

MEBS, a software platform to evaluate large (meta)genomic collections according to their metabolic machinery: Unraveling the sulfur cycle

The increasing number of metagenomic and genomic sequences has dramatically improved our understanding of microbial diversity, yet our ability to infer metabolic capabilities in such datasets remains challenging. We describe the Multigenomic Entropy Based Score pipeline (MEBS), a software platform designed to evaluate, compare, and infer complex metabolic pathways in large "omic" datasets, including entire biogeochemical cycles. MEBS is open source and available through https://github.com/eead-csic-compbio/metagenome Pfam score. To demonstrate its use, we modeled the sulfur cycle by exhaustively curating the molecular and ecological elements involved (compounds, genes, metabolic pathways, and microbial taxa). This information was reduced to a collection of 112 characteristic Pfam protein domains and a list of complete-sequenced sulfur genomes. Using the mathematical framework of relative entropy (H''), we quantitatively measured the enrichment of these domains among sulfur genomes. The entropy of each domain was used both to build up a final score that indicates whether a (meta)genomic sample contains the metabolic machinery of interest and to propose marker domains in metagenomic sequences such as DsrC (PF04358). MEBS was benchmarked with a dataset of 2107 non-redundant microbial genomes from RefSeq and 935 metagenomes from MG-RAST. Its performance, reproducibility, and robustness were evaluated using several approaches, including random sampling, linear regression models, receiver operator characteristic plots, and the area under the curve metric (AUC). Our results support the broad applicability of this algorithm to accurately classify (AUC = 0.985) hard-to-culture genomes (e.g., Candidatus Desulforudis audaxviator), previously characterized ones, and metagenomic environments such as hydrothermal vents, or deep-sea sediment. Our benchmark indicates that an entropy-based score can capture the metabolic machinery of interest and can be used to efficiently classify large genomic and metagenomic datasets, including uncultivated/unexplored taxa

Associations between sole ulcer, white line disease and digital dermatitis and the milk yield of 1824 dairy cows on 30 dairy cow farms in England and Wales from February 2003–November 2004

The milk yields of 1824 cows were used to investigate the effect of lesion-specific causes of lameness, based on farmer treatment and diagnosis of lame cows, on milk yield. A three level hierarchical model of repeated test day yields within cows within herds was used to investigate the impact of lesion-specific causes of lameness (sole ulcer, white line disease, digital dermatitis and other causes) on milk yield before and after treatment compared with unaffected cows. Cattle which developed sole ulcer (SU) and white line disease (WLD) were higher yielding cattle before they were diagnosed. Their milk production fell to below that of the mean of unaffected cows before diagnosis and remained low after diagnosis. In cattle which developed digital dermatitis (DD) there was no significant difference in milk yield before treatment and a slightly raised milk yield immediately after treatment. The estimated milk loss attributable to SU and WLD was approximately 570kg and 370kg respectively. These results highlight that specific types of lameness vary by herds and within herds they are associated with higher yielding cattle. Consequently lesion-specific lameness reduction programmes targeting the cow and farm specific causes of lameness might be more effective than generic recommendations. They also highlight the importance of milk loss when estimating the economic impact of SU and WLD on the farms profitability

Milk production of lacaune sheep with different degrees of crossing with manchega sheep in a commercial flock in Spain

The objective of the present study was to evaluate the effect of the grade of crossbreeding (Lacaune x Manchega) and environmental factors on milk production in a commercial flock in Spain. A total of 5769 milk production records of sheep with different degrees of purity of the Lacaune breed crossed with Manchega were used as follows: 100% Lacaune (n = 2960), 7/8 Lacaune (n = 502), 13/16 Lacaune (n = 306), 3/4 (n = 1288), 5/8 Lacaune (n = 441) and 1/2 Lacaune: Manchega (n = 272). Additional available information included the number of parity (1 to 8), litter size (single or multiple), and the season of the year of lambing (spring, summer, autumn and winter). A mixed model was used to evaluate the level of crossbreeding and environmental factors on milk production. The 100% Lacaune sheep presented the highest milk production with respect to the F1 Lacaune x Manchega sheep (p < 0.01), showing that as the degree of gene absorption increases with the Manchega breed, it presents lower milk yield. The 100%, 13/16, and 3/4 Lacaune genotypes had the highest milk yields with respect to the 1/2 Lacaune/Manchega breed (p < 0.001). The Lacaune registered on average 181.1 L in a period adjusted to 160 days of lactation (1.13 L/ day). Likewise, the parity number, litter size, and season of lambing effects showed significant differences (p < 0.01). It was concluded that 13/16 and 3/4 Lacaune/Manchega ewes presented the highest milk yields with respect to the other crosses

Diagnóstico estratégico da produção de carne de cabrito da raça serrana

Este trabalho pretende realizar um diagnóstico estratégico do setor de carnes de cabrito Serrana. Os dados baseiam-se numa amostra de 70 criadores da região Norte de Trás-os-Montes. Os resultados do estudo revelam algumas debilidades estruturais no setor, como a reduzida escolaridade dos produtores, a ancianidade, o abandono da atividade, o baixo preço ao produtor ou mesmo as oscilações da procura. Efetivamente, de acordo com os indivíduos da nossa amostra, se agruparmos o envelhecimento dos produtores à diminuição do efetivo e ao abandono da atividade, a fragilidade do setor é enorme. Acresce alguma carência de visão e inovação, por parte dos agentes, nos diferentes elos do sistema de comercialização. Nenhum criador vende a carne através da internet, a retalho ou pré-embalada, não retendo para si o valor acrescentado da transformação. Assim, o escoamento do produto é praticamente assegurado pela qualidade da carne, que se tem apresentado como uma potencialidade irrefutável.This paper intends to perform a strategic diagnostic of the meat sector of Serrana goat kid. The data is based on a sample of 70 breeders, members of the Association for the Serrana goats (ANCRAS), from the Northern region of Trás-os-Montes. The study findings reveal some structural weaknesses in the sector, such as low schooling of farmers, old age, cessation of goat farming activity, low producer prices or demand fluctuations. Indeed, according to our sample goat breeders, if we add the “goat breeders aging” with “herd goat decrease” and “abandonment of the goat farming activity”, the sector’s fragility is huge. Moreover, there are some lack of vision and innovation, by the actors in different links of the marketing chain. No one of the farmers sells the meat over the internet, retail or prepacked, so do not appropriate themselves of the added value of processing. Indeed, the product marketing is essentially based on meat quality, which has been presented as the sector main strength.Este trabalho foi financiado por: Projeto OPEN2PRESERVE - Modelo de gestión sostenible para la preservación de paisajes abiertos de montaña (SOE2/P5/E0804). Os autores agradecem à Fundação para a Ciência e a Tecnologia (FCT, Portugal) e ao FEDER no âmbito do programa PT2020 pelo apoio financeiro ao CIMO (UID/AGR/00690/2013).info:eu-repo/semantics/publishedVersio

An exploration strategy for non-stationary opponents

The success or failure of any learning algorithm is partially due to the exploration strategy it exerts. However, most exploration strategies assume that the environment is stationary and non-strategic. In this work we shed light on how to design exploration strategies in non-stationary and adversarial environments. Our proposed adversarial drift exploration (DE) is able to efficiently explore the state space while keeping track of regions of the environment that have changed. This proposed exploration is general enough to be applied in single agent non-stationary environments as well as in multiagent settings where the opponent changes its strategy in time. We use a two agent strategic interaction setting to test this new type of exploration, where the opponent switches between different behavioral patterns to emulate a non-deterministic, stochastic and adversarial environment. The agent’s objective is to learn a model of the opponent’s strategy to act optimally. Our contribution is twofold. First, we present DE as a strategy for switch detection. Second, we propose a new algorithm called R-max# for learning and planning against non-stationary opponent. To handle such opponents, R-max# reasons and acts in terms of two objectives: (1) to maximize utilities in the short term while learning and (2) eventually explore opponent behavioral changes. We provide theoretical results showing that R-max# is guaranteed to detect the opponent’s switch and learn a new model in terms of finite sample complexity. R-max# makes efficient use of exploration experiences, which results in rapid adaptation and efficient DE, to deal with the non-stationary nature of the opponent. We show experimentally how using DE outperforms the state of the art algorithms that were explicitly designed for modeling opponents (in terms average rewards) in two complimentary domains

Microstructure Architecture Development in Metals and Alloys By Additive Manufacturing Using Electron Beam Melting

The concept of materials with controlled microstructural architecture (MCMA) to develop and fabricate structural materials with novel and possibly superior properties and performance characteristics is a new paradigm or paradigm extension for materials science and engineering. In the conventional materials science and engineering paradigm, structure (microstructure), properties, processing, and performance features are linked in the development of desirable materials properties and performance through processing methodologies which manipulate microstructures. For many metal or alloy systems, thermomechanical treatment combining controlled amounts of plastic deformation with heat treatment or aging cycles can achieve improved mechanical properties beyond those attainable by conventional processing alone (such as rolling or forging for example) through controlled microstructure development. In this paper we illustrate a new concept involving the fabrication of microstructural architectures by the process development and selective manipulation of these microstructures ideally defining material design space. This allows for the additional or independent manipulation of material properties by additive manufacturing (AM) using electron beam melting (EBM). Specifically we demonstrate the novel development of a carbide (M23C6) architecture in the AM of a Co-base alloy and an oxide (Cu2O) precipitate-dislocation architecture in the AM of an oxygen-containing Cu. While more conventional processing can produce various precipitate microstructures in these materials, EBM produces spatial arrays of precipitate columns or columnar-like features often oriented in the build direction. These microstructural architectures are observed by optical microscopy and scanning and transmission electron microscopy. Prospects for EBM architecture development in precipitation-hardenable Al alloys is also discussed. In the EBM build process using precursor powders, the electron beam parameters (including beam focus, scan speed and sequencing) produce localized, requisite thermodynamic regimes which create or organize the precipitate-related spatial arrays. This feature demonstrates the utility of AM not only in the fabrication of complex components, but also prospects for selective property design using CAD for MCMA development: a new or extended processing-microstructure-property-performance paradigm for materials science and engineering in advanced manufacturing involving solid free-form fabrication (SFF).Mechanical Engineerin

Efficiently detecting switches against non-stationary opponents

Interactions in multiagent systems are generally more complicated than single agent ones. Game theory provides solutions on how to act in multiagent scenarios; however, it assumes that all agents will act rationally. Moreover, some works also assume the opponent will use a stationary strategy. These assumptions usually do not hold in real world scenarios where agents have limited capacities and may deviate from a perfect rational response. Our goal is still to act optimally in these cases by learning the appropriate response and without any prior policies on how to act. Thus, we focus on the problem when another agent in the environment uses different stationary strategies over time. This will turn the problem into learning in a non-stationary environment, posing a problem for most learning algorithms. This paper introduces DriftER, an algorithm that (1) learns a model of the opponent, (2) uses that to obtain an optimal policy and then (3) determines when it must re-learn due to an opponent strategy change. We provide theoretical results showing that DriftER guarantees to detect switches with high probability. Also, we provide empirical results showing that our approach outperforms state of the art algorithms, in normal form games such as prisoner’s dilemma and then in a more realistic scenario, the Power TAC simulator

Effect of Build Parameters and Build Geometries on Residual Microstructures and Mechanical Properties of Ti-6Al-4V Components Built by Electron Beam Melting (EBM)

In this study, involving additive manufacturing (AM) using electron beam melting (EBM), we have examined build defects which result from beam tripping, porosities (including unmelted or unsintered zones) due to excursions from optimal build parameters (especially variations in melt scan beam current and scan speed), and gas bubbles trapped in atomized Ti-6Al-4V starting powder as well as recycled powder, and retained in the build. At optimized build conditions we have also examined microstructure-mechanical property (hardness, tensile strength, and elongation) variations for multiple rake building and multiple melt scans using optical metallography and scanning and transmission electron microscopy (SEM and TEM). These build variances cause cooling rate variances which promote α-phase growth and variations in dislocation density, as well as α-to-α' (martensite) phase changes, all of which produce some degree of mechanical property variations. These features (especially α-to-α' phase changes) are notable on comparing solid builds in comparison with a variety of mesh arrays where strut dimension and build-element complexities alter the cooling rates in a significant way. We illustrate these microstructure variations with corresponding variations in microindentation hardness measurements made directly on fine mesh (strut) structures. Finally, we have examined Ti-6Al-4V powder chemistries and solid build chemistries which for single-pass melt scans at optimized build conditions are shown to be relatively constant up to 40 cycles of powder reuse with the exception of Al content which was reduced by 10 to 15% in solid builds at optimized conditions. However, Al loss in solid builds approached 25% for multiple (2 and 3) melt scans, while no changes in Ar gas-bubble density were observed with changes in α-phase (grain) width which increased from 3 µm for a single melt scan to 4.5 and 6 µm for 2 and 3 melt scans, respectively. Corresponding Rockwell C-scale (HRC) hardness varied from 37, 36, and 35, respectively; with ultimate tensile strengths exceeding 1.2 GPa at elongations of 12% or higher for this melt scan sequence.Mechanical Engineerin

Hidden variables with nonlocal time

To relax the apparent tension between nonlocal hidden variables and relativity, we propose that the observable proper time is not the same quantity as the usual proper-time parameter appearing in local relativistic equations. Instead, the two proper times are related by a nonlocal rescaling parameter proportional to |psi|^2, so that they coincide in the classical limit. In this way particle trajectories may obey local relativistic equations of motion in a manner consistent with the appearance of nonlocal quantum correlations. To illustrate the main idea, we first present two simple toy models of local particle trajectories with nonlocal time, which reproduce some nonlocal quantum phenomena. After that, we present a realistic theory with a capacity to reproduce all predictions of quantum theory.Comment: 16 pages, accepted for publication in Found. Phys., misprints corrected, references update