Parallel Implementation of Efficient Search Schemes for the Inference of Cancer Progression Models

The emergence and development of cancer is a consequence of the accumulation over time of genomic mutations involving a specific set of genes, which provides the cancer clones with a functional selective advantage. In this work, we model the order of accumulation of such mutations during the progression, which eventually leads to the disease, by means of probabilistic graphic models, i.e., Bayesian Networks (BNs). We investigate how to perform the task of learning the structure of such BNs, according to experimental evidence, adopting a global optimization meta-heuristics. In particular, in this work we rely on Genetic Algorithms, and to strongly reduce the execution time of the inference -- which can also involve multiple repetitions to collect statistically significant assessments of the data -- we distribute the calculations using both multi-threading and a multi-node architecture. The results show that our approach is characterized by good accuracy and specificity; we also demonstrate its feasibility, thanks to a 84x reduction of the overall execution time with respect to a traditional sequential implementation

Hyaluronic acid gel fillers in the management of facial aging

Time affects facial aging by producing cellular and anatomical changes resulting in the consequential loss of soft tissue volume. With the advent of new technologies, the physician has the opportunity of addressing these changes with the utilization of dermal fillers. Hyaluronic acid (HA) dermal fillers are the most popular, non-permanent injectable materials available to physicians today for the correction of soft tissue defects of the face. This material provides an effective, non invasive, non surgical alternative for correction of the contour defects of the face due to its enormous ability to bind water and easiness of implantation. HA dermal fillers are safe and effective. The baby-boomer generation, and their desire of turning back the clock while enjoying an active lifestyle, has expanded the popularity of these fillers. In the US, there are currently eight HA dermal fillers approved for commercialization by the Food and Drug Administration (FDA). This article reviews the innate properties of FDA-approved HA fillers and provides an insight on future HA products and their utilization for the management of the aging face

Multi-objective optimization to explicitly account for model complexity when learning Bayesian Networks

Bayesian Networks have been widely used in the last decades in many fields, to describe statistical dependencies among random variables. In general, learning the structure of such models is a problem with considerable theoretical interest that still poses many challenges. On the one hand, this is a well-known NP-complete problem, which is practically hardened by the huge search space of possible solutions. On the other hand, the phenomenon of I-equivalence, i.e., different graphical structures underpinning the same set of statistical dependencies, may lead to multimodal fitness landscapes further hindering maximum likelihood approaches to solve the task. Despite all these difficulties, greedy search methods based on a likelihood score coupled with a regularization term to account for model complexity, have been shown to be surprisingly effective in practice. In this paper, we consider the formulation of the task of learning the structure of Bayesian Networks as an optimization problem based on a likelihood score. Nevertheless, our approach do not adjust this score by means of any of the complexity terms proposed in the literature; instead, it accounts directly for the complexity of the discovered solutions by exploiting a multi-objective optimization procedure. To this extent, we adopt NSGA-II and define the first objective function to be the likelihood of a solution and the second to be the number of selected arcs. We thoroughly analyze the behavior of our method on a wide set of simulated data, and we discuss the performance considering the goodness of the inferred solutions both in terms of their objective functions and with respect to the retrieved structure. Our results show that NSGA-II can converge to solutions characterized by better likelihood and less arcs than classic approaches, although paradoxically frequently characterized by a lower similarity to the target network

Transverse momentum dependent parton distributions in a light-cone quark model

The leading twist transverse momentum dependent parton distributions (TMDs) are studied in a light-cone description of the nucleon where the Fock expansion is truncated to consider only valence quarks. General analytic expressions are derived in terms of the six amplitudes needed to describe the three-quark sector of the nucleon light-cone wave function. Numerical calculations for the T-even TMDs are presented in a light-cone constituent quark model, and the role of the so-called pretzelosity is investigated to produce a nonspherical shape of the nucleon.Comment: references added and typos corrected; version to appear in Phys. Rev.

Redescription of Ventania avellanedae (Stylommatophora: Odontostomidae), a land snail endemic to the Ventania Mountain System, Argentina

Although the presence of apertural folds and lamellae is the most recognizable character of the Odontostomidae, some species lack them, mostly in Anctus Martens, 1860, Bahiensis Jousseaume, 1877 and Moricandia Pilsbry & Vanatta, 1898. Eudioptus avellanedae Doering, 1881 - a slender odontostomid species that lacks even the slightest trace of folds or lamellae in its shell aperture - was however transferred to Odontostomus by Pilsbry in 1902 on the basis of its building forward of the aperture-margins. It is currently placed in its own monotypic subgenus, Cyclodontina (Ventania) Parodiz, 1940, on the basis of about the same argument. In this paper we redescribe its shell morphology and, for the first time, describe the internal anatomy of the pallial complex and the reproductive and digestive systems. The presence of a spongy gland in the pallial complex; of a short penis sheath with no retractor muscle; of a bursa copulatrix duct longer than spermoviduct, and of an epiphallic gland strongly support the inclusion of this unusual species in Odontostomidae. The species is diagnosable by the sculpture of the protoconch, which is not smooth as previously described, but has waved axial ribs crossed by spiral lines in young specimens; the distinctive external and internal shape of the bursa copulatrix duct; the internal penis wall divided in three regions of different sculpture; the smooth inner wall of the vagina; the long and cylindrical epiphallus with a distal widening indicating the presence of an epiphallic gland, and the penis retractor muscle inserted in the distal end of a short flagellum. These characters support the validity of Ventania Parodiz, 1940, different from Cyclodontina Beck, 1837.Fil: Piza, Julia. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; ArgentinaFil: Cazzaniga, Néstor Jorge. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentin

Burning magnesium, a sparkle in acute inflammation: gleams from experimental models

Magnesium contributes to the regulation of inflammatory responses. Here, we focus on the role of magnesium in acute inflammation. Although present knowledge is incomplete to delineate an accurate scenario and a schedule of the events occurring under magnesium deficiency, it emerges that low magnesium status favors the induction of acute inflammation by sensitizing sentinel cells to the noxious agent, and then by participating to the orchestration of the vascular and cellular events that characterize the process

Shaping and Dilating the Fitness Landscape for Parameter Estimation in Stochastic Biochemical Models

The parameter estimation (PE) of biochemical reactions is one of the most challenging tasks in systems biology given the pivotal role of these kinetic constants in driving the behavior of biochemical systems. PE is a non-convex, multi-modal, and non-separable optimization problem with an unknown fitness landscape; moreover, the quantities of the biochemical species appearing in the system can be low, making biological noise a non-negligible phenomenon and mandating the use of stochastic simulation. Finally, the values of the kinetic parameters typically follow a log-uniform distribution; thus, the optimal solutions are situated in the lowest orders of magnitude of the search space. In this work, we further elaborate on a novel approach to address the PE problem based on a combination of adaptive swarm intelligence and dilation functions (DFs). DFs require prior knowledge of the characteristics of the fitness landscape; therefore, we leverage an alternative solution to evolve optimal DFs. On top of this approach, we introduce surrogate Fourier modeling to simplify the PE, by producing a smoother version of the fitness landscape that excludes the high frequency components of the fitness function. Our results show that the PE exploiting evolved DFs has a performance comparable with that of the PE run with a custom DF. Moreover, surrogate Fourier modeling allows for improving the convergence speed. Finally, we discuss some open problems related to the scalability of our methodology

Mitophagy contributes to endothelial adaptation to simulated microgravity

Exposure to real or simulated microgravity is sensed as a stress by mammalian cells, which activate a complex adaptive response. In human primary endothelial cells, we have recently shown the sequential intervention of various stress proteins which are crucial to prevent apoptosis and maintain cell function. We here demonstrate that mitophagy contributes to endothelial adaptation to gravitational unloading. After 4 and 10 d of exposure to simulated microgravity in the rotating wall vessel, the amount of BCL2 interacting protein 3, a marker of mitophagy, is increased and, in parallel, mitochondrial content, oxygen consumption, and maximal respiratory capacity are reduced, suggesting the acquisition of a thrifty phenotype to meet the novel metabolic challenges generated by gravitational unloading. Moreover, we suggest that microgravity induced-disorganization of the actin cytoskeleton triggers mitophagy, thus creating a connection between cytoskeletal dynamics and mitochondrial content upon gravitational unloading

High carotenoid mutants of Chlorella vulgaris show enhanced biomass yield under high irradiance

Microalgae represent a carbon-neutral source of bulk biomass, for extraction of high-value compounds and production of renewable fuels. Due to their high metabolic activity and reproduction rates, species of the genus Chlorella are highly productive when cultivated in photo-bioreactors. However, wild-type strains show biological limitations making algal bioproducts ex-pensive compared to those extracted from other feedstocks. Such constraints include inhomoge-neous light distribution due to high optical density of the culture, and photoinhibition of the sur-face-exposed cells. Thus, the domestication of algal strains for industry makes it increasingly important to select traits aimed at enhancing light-use efficiency while withstanding excess light stress. Carotenoids have a crucial role in protecting against photooxidative damage and, thus, represent a promising target for algal domestication. We applied chemical mutagenesis to Chlorella vulgaris and selected for enhanced tolerance to the carotenoid biosynthesis inhibitor norflurazon. The NFR (norflurazon-resistant) strains showed an increased carotenoid pool size and enhanced tolerance towards photooxidative stress. Growth under excess light revealed an improved carbon assimilation rate of NFR strains with respect to WT. We conclude that domestication of Chlorella vulgaris, by optimizing both carotenoid/chlorophyll ratio and resistance to photooxidative stress, boosted light-to-biomass conversion efficiency under high light conditions typical of photobiore-actors. Comparison with strains previously reported for enhanced tolerance to singlet oxygen, reveals that ROS resistance in Chlorella is promoted by at least two independent mechanisms, only one of which is carotenoid-dependent