TrAp: a Tree Approach for Fingerprinting Subclonal Tumor Composition

Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide an overview of an aggregate of numerous cells, rather than subclonal-specific quantification of aberrations such as single nucleotide variants (SNVs). Computational approaches to de-mix a single collective signal from the mixed cell population of a tumor sample into its individual components are currently not available. Herein we propose a framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. The method is based on the plausible biological assumption that tumor progression is an evolutionary process where each individual aberration event stems from a unique subclone and is present in all its descendants subclones. We have developed an efficient algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation datasets. We applied TrAp to SNV frequency profile from Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of twenty single cells of the same tumor. Despite the large experimental noise, specific co-occurring mutations found in clones inferred by TrAp are also present in some of these single cells. Finally, we deconvolve Exome-Seq data from three distinct metastases from different body compartments of one melanoma patient and exhibit the evolutionary relationships of their subpopulations

From Planning to Mature: on the Determinants of Open Source Take-Off

Thanks to a recent and vast empirical literature, we know in details how the most popular open source projects are organized and why they succeed. However open source is not only Linux: in this paper we use a large data-set obtained from SourceForge.net to estimate the main determinants of the progress in the development of a stable and mature code of an open source software. We show that projects geared towards sophisticated users (i.e. system administrators) or projects aimed at developing tools for the Internet, multimedia and software have greater chances to reach an advanced development stage. On the contrary, projects devoted to the production of applications for games and telecommunication as well as projects distributed under highly restrictive licensing terms (GPL) have a significantly smaller probability to advance. Interestingly, we find that the size of the "community of developers" increases the chances of progress but this effect decreases as the community gets larger, a signal of possible coordination problems. Finally, we show that the determinants of projects' development stage change with the age of the project in many dimensions thus supporting the common perception of open source as an extremely dynamic phenomenon.software market, open source software, development status, intended audience, license

The Big Roof for a Theory of Design through the Permutation of the Big Formal and Structural Types

The topic of the large centrally planned hall is one of the oldest ones in Building History; with different techniques and since Pre-Christian times, builders have always aimed at imagining and realizing a centrally-planned space surmounted by a big roof. Such ambition has never disappeared and today the projects focusing on this topic are innumerable also thanks to the advancements in the construction techniques and to better materials. Do all of these buildings, both the recent and the less recent ones, share features and rules that make them belong to a same family of structural forms? The work we carried out is not meant only to prove that the “genealogical lines” that unite different planning experiences do exist, it aims for something more. Indeed we suppose and then prove that entire families of architectures are referable to formal and structural geometry rules from which we can abstract planning codes that allow modern planners to operate through the permutation of such original types

Video analysis in youth volleyball team

The aim of the study was to use video analysis in training to improve the performance of young athletes. Participants will be divided in two teams that will play the same “Under-21 championship”, but with a different average age (Team A: average age 14,41±1,66; Team B average age 18,94±1,59). Twelve matches (in 4 months) of both teams will be videotaped. Statistical data for each team will be extrapolated from them, and compared among them in order to take in correlations skills data. Only team A, the “young team”, will be given the opportunity to review errors and strong points of each match, so as to prepare for the successive match, according to the errors made in the matches. The videos will be analyzed by “Kinovea” software, while statistics analysed with “SoloStats123”. It is expected that there will be a performance improvement in young team A, around the same average level of “expert” team B. These results will be used as a starting point to analyze the differences between two teams with different average age, in a higher championship quality

The serve in under 12-13 Italian volleyball team

The serve is the technical skill with which a rally of a game of volleyball begins, and it can be performed by underhand, by a high float or drive and by a high jump. At the request of the coaches of national youth teams, the Italian Volleyball Federation (FIPAV) has adopted the mandatory underhand serve only for Under-12 and under 13 championships in order to favor the continuity of the game movement and passes of the ball over the net, which would be compromised in the event of a volleyball athlete who is particularly good at high jump serves. Although the abutment from the bottom appears to be more easily learned, not having the characteristics of offensiveness, must be abandoned as soon as it is able to perform the services more insidious. The increase in strength up to 11 years is very low and no difference between the sexes, he observes a slight increase up to 15 years, then intervenes when the phase of maximum development that leads to the peak at age 18. In this period there is also a progressive differentiation between females and males with a surge in favor of males estimated at strength of about 40% greater than that of peers. The aim of this preliminary study was to see if an experimental study can be implemented, preceded by a pilot study in order to verify the hypothesis for the accuracy of the mandatory rule for the Under-12 and Under-13

Pro-Resolving FPR2 Agonists Regulate NADPH Oxidase-Dependent Phosphorylation of HSP27, OSR1, and MARCKS and Activation of the Respective Upstream Kinases

Formyl peptide receptor 2 (FPR2) is involved in the pathogenesis of chronic inflammatory diseases, being activated either by pro-resolving or proinflammatory ligands. FPR2-associated signal transduction pathways result in phosphorylation of several proteins and in NADPH oxidase activation. We, herein, investigated molecular mechanisms underlying phosphorylation of heat shock protein 27 (HSP27), oxidative stress responsive kinase 1 (OSR1), and myristolated alanine-rich C-kinase substrate (MARCKS) elicited by the pro-resolving FPR2 agonists WKYMVm and annexin A1 (ANXA1)

Ranking and combining multiple predictors without labeled data

In a broad range of classification and decision making problems, one is given the advice or predictions of several classifiers, of unknown reliability, over multiple questions or queries. This scenario is different from the standard supervised setting, where each classifier accuracy can be assessed using available labeled data, and raises two questions: given only the predictions of several classifiers over a large set of unlabeled test data, is it possible to a) reliably rank them; and b) construct a meta-classifier more accurate than most classifiers in the ensemble? Here we present a novel spectral approach to address these questions. First, assuming conditional independence between classifiers, we show that the off-diagonal entries of their covariance matrix correspond to a rank-one matrix. Moreover, the classifiers can be ranked using the leading eigenvector of this covariance matrix, as its entries are proportional to their balanced accuracies. Second, via a linear approximation to the maximum likelihood estimator, we derive the Spectral Meta-Learner (SML), a novel ensemble classifier whose weights are equal to this eigenvector entries. On both simulated and real data, SML typically achieves a higher accuracy than most classifiers in the ensemble and can provide a better starting point than majority voting, for estimating the maximum likelihood solution. Furthermore, SML is robust to the presence of small malicious groups of classifiers designed to veer the ensemble prediction away from the (unknown) ground truth.Comment: Supplementary Information is included at the end of the manuscript. This is a revision of our original submission of the manuscript entitled "The student's dilemma: ranking and improving prediction at test time without access to training data", which is now entitled "Ranking and combining multiple predictors without labeled data

LIFE Project: Implementing a modelling framework for emergency vehicles advanced priority strategies

Given the aging demographics and rapid urbanisation, cities need to be equipped to respond to emergency (eg. 999 calls) more quickly. By 2050, over 25% of the UK’s population will be over 65. This has implications on the overall health services as well as the NHS Trust to cope with anticipated rise in ambulance call outs amidst worsening urban congestion. Ambulance services are required to reach 75% of emergency calls within 8 minutes. For this reason, there is a growing need to develop new and innovative applications for an even more intelligent use of the existing transport system that will support in real-time emergency vehicles to reach life threatening emergency cases quicker. this paper will discuss the methodology and the preliminary results of the modelling framework implementation of a “Life First Emergency Traffic Control” or “LiFE” system, a ITS implementation seeking to identify the best solution to reduce the time to respond to emergency calls, whilst operating a resilient service with a cost and fuelefficient fleet. Results of the application of a microsimulation model to replicate the behaviour of ambulances in urban area and how different reactions of general traffic can impact on the travel time of an ambulance are presented. The proposed microsimulation modelling framework has been developed with the final aim to understand and evaluate the impacts and the best scenarios to improve ambulance (or any Emergency vehicle) response time and gains in cost-saving, whilst assessing mitigation strategies to reduce other impacts such as residual congestion. The work is part of an Innovate UK collaborative funded project, namely Life First Emergency Traffic Control (LiFE) with the aim to develop an innovative application for an intelligent transport system that operates in realtime to enable ambulances to reach life threatening emergency cases quicker by integrating ambulance route finder applications with traffic management systems

Forest stand structure and coarse woody debris determine the biodiversity of beetle communities in Mediterranean mountain beech forests

Abstract The relationships between structural complexity, deadwood abundance, microhabitat type and species-diversity indicators are excellent tools to monitor biodiversity in forest ecosystems. In spite of their importance, correlations between structural traits and Coleoptera communities in Mediterranean mountain forests have only rarely been investigated. Consequently, the magnitude and direction of the relationships between forest traits and biodiversity indicators remain poorly understood. In this study, we analyzed whether biodiversity indices of saproxylic and non-saproxylic beetle communities could be influenced by stand structure, microhabitat type, and deadwood abundance in two protected beech forests located in the central and southern Apennines (namely Gran Sasso e Monti della Laga National Park, GSML, and Cilento, Vallo di Diano e Alburni National Park, CVDA). Standard measurements of forest structural traits and quantitative assessment of tree microhabitats and deadwood were carried out. Adult beetles were collected using window flight traps and emergence traps on decaying deadwood. The two beech forests were different in terms of both beetle communities and structural traits. A two-block partial least squares analysis 2B-PLS highlighted differences in biodiversity indices and structural traits between the two forest ecosystems. In GSML, we observed that biodiversity indices were positively correlated with the volume of coarse woody debris and the presence fungal infections, clefts into the sapwood, and woodpecker cavities, while more dominant beetle communities were found under denser canopy cover. In CVDA, Coleoptera abundance was positively correlated with the basal area and crown broken microhabitats. Our results point toward the relevance of ecological attributes in tracking changes in beetle biodiversity in specific forest contexts. In these protected Mediterranean mountain beech stands, in which the main forest management strategies have the primary objective of biodiversity conservation, we suggest to progressively increase the structural diversity and canopy dynamics, as well as the volume of coarse woody debris

Intranuclear Signaling Cascades Triggered by Nuclear GPCRs

G protein-couped receptors (GPCRs) play a key role on cellular membranes, where they respond to a broad array of extracellular signals such as lipids, peptides, proteins and sensory agents. Intracellular biological responses triggered by these receptors include hormone secretion, muscle contraction, cellular metabolism a tyrosine kinase receptors transactivation. Recent results indicate that GPCRs localize to and signal also at nuclear level, thus regulating distinct signaling pathways which can also result from the integration of extracellular and intracellular stimuli. Nuclear GPCRs play a central role in many cellular processes, including regulation of gene transcription, cellular proliferation, neovascularization and RNA synthesis. On nuclear membranes and in nucleoplasm are present all the downstream signal transduction components of GPCRs, including G proteins, adenylyl cyclase, and second messengers such as Ca++, ERKs, p38MAPK and other protein kinases. Nuclear GPCRs may be constitutively active or may be activated by ligands internalized from the extracellular space or synthesized within the cell. The translocation of membrane receptors to the nucleus could be attributed to the presence of a Nuclear Localization Signal, which is present in the eighth helix or in the third intracellular loop of a limited number of GPCRs. However, several sequence motifs that do not resemble classical Nuclear Localization Signals can promote import of GPCRs. In this review we discuss the most recent results on nuclear localization and signaling of several GPCRS