A clinical prognostic model for the identification of low-risk patients with acute symptomatic pulmonary embolism and active cancer.

BACKGROUND: Physicians need a specific risk-stratification tool to facilitate safe and cost-effective approaches to the management of patients with cancer and acute pulmonary embolism (PE). The objective of this study was to develop a simple risk score for predicting 30-day mortality in patients with PE and cancer by using measures readily obtained at the time of PE diagnosis. METHODS: Investigators randomly allocated 1,556 consecutive patients with cancer and acute PE from the international multicenter Registro Informatizado de la Enfermedad TromboEmbólica to derivation (67%) and internal validation (33%) samples. The external validation cohort for this study consisted of 261 patients with cancer and acute PE. Investigators compared 30-day all-cause mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. RESULTS: In the derivation sample, multivariable analyses produced the risk score, which contained six variables: age > 80 years, heart rate ≥ 110/min, systolic BP < 100 mm Hg, body weight < 60 kg, recent immobility, and presence of metastases. In the internal validation cohort (n = 508), the 22.2% of patients (113 of 508) classified as low risk by the prognostic model had a 30-day mortality of 4.4% (95% CI, 0.6%-8.2%) compared with 29.9% (95% CI, 25.4%-34.4%) in the high-risk group. In the external validation cohort, the 18% of patients (47 of 261) classified as low risk by the prognostic model had a 30-day mortality of 0%, compared with 19.6% (95% CI, 14.3%-25.0%) in the high-risk group. CONCLUSIONS: The developed clinical prediction rule accurately identifies low-risk patients with cancer and acute PE.

Constructing brain functional networks from EEG: partial and unpartial correlations.

We consider electroencephalograms (EEGs) of healthy individuals and compare the properties of the brain functional networks found through two methods: unpartialized and partialized cross-correlations. The networks obtained by partial correlations are fundamentally different from those constructed through unpartial correlations in terms of graph metrics. In particular, they have completely different connection efficiency, clustering coefficient, assortativity, degree variability, and synchronization properties. Unpartial correlations are simple to compute and they can be easily applied to large-scale systems, yet they cannot prevent the prediction of non-direct edges. In contrast, partial correlations, which are often expensive to compute, reduce predicting such edges. We suggest combining these alternative methods in order to have complementary information on brain functional networks.

A-8a 2003 Summary of Food Stamp Errors - Active and Negative Cases, April 2003 - September 2003

Summary of food stamp errors.

Europe’s experience in countering radicalization: approaches and challenges

For the last decade Europe has perceived itself to be under a constant threat from jihadistinspired terrorism. Terrorist organizations motivated by other ideologies are still active throughout the European Union, but the 2010 Europol annual report clearly states that “Islamist terrorism is still perceived as the biggest threat to most Member States,” and statements from the highest-ranking officials in most European countries confirm this observation (EUROPOL, 2010, p. 6). Authorities base their assessment on the extensive intelligence and investigative activities directed against jihadist networks taking place in virtually every European country. On average, in fact, European authorities arrest some 200 individuals and thwart a handful of plots of jihadist inspiration every year (EUROPOL, 2009). Keeping the global scenario in mind, European authorities deem this dynamic likely to continue in the foreseeable future.

Connectivity differences in brain networks.

The scenario considered here is one where brain connectivity is represented as a network and an experimenter wishes to assess the evidence for an experimental effect at each of the typically thousands of connections comprising the network. To do this, a univariate model is independently fitted to each connection. It would be unwise to declare significance based on an uncorrected threshold of α=0.05, since the expected number of false positives for a network comprising N=90 nodes and N(N-1)/2=4005 connections would be 200. Control of Type I errors over all connections is therefore necessary. The network-based statistic (NBS) and spatial pairwise clustering (SPC) are two distinct methods that have been used to control family-wise errors when assessing the evidence for an experimental effect with mass univariate testing. The basic principle of the NBS and SPC is the same as supra-threshold voxel clustering. Unlike voxel clustering, where the definition of a voxel cluster is unambiguous, 'clusters' formed among supra-threshold connections can be defined in different ways. The NBS defines clusters using the graph theoretical concept of connected components. SPC on the other hand uses a more stringent pairwise clustering concept. The purpose of this article is to compare the pros and cons of the NBS and SPC, provide some guidelines on their practical use and demonstrate their utility using a case study involving neuroimaging data.

Cultural self-identification(s) and personal social networks among first and second-generation immigrants

L’estudi examina les relacions entre (1) les xarxes socials personals de la població immigrant resident a Barcelona i (2) les seves identitats culturals múltiples. L’objectiu principal de l’estudi és entendre com el contingut i l’estructura de les relacions socials dels immigrants facilita o dificulta (1) tenir un sentiment de pertinença a les noves cultures d’acollida, la catalana i la espanyola, i (2) la integració d’aquestes noves identitats socioculturals amb la seva identitat d’origen en una nova identitat bicultural cohesiva. El nostre plantejament inicial era que els immigrants amb xarxes socials més diverses des del punt de vista de la seva composició cultural tindrien més recursos socials i experiències cognitives més diverses , factors que afavoreixen les identificacions múltiples i la participació cívica. Els resultats de l’estudi mostren que el grau d’identificació dels participants amb la seva cultura ètnica o d’origen és força alt i, en certa mesura, més alt en comparació amb les cultures d’acollida ( catalana, cívica i espanyola). Tanmateix, el vincle dels participants amb les cultures d’acollida (p. ex., la cultura catalana) és prou rellevant per a indicar una orientació bicultural (catalana i ètnica). Les anàlisis de correlacions revelen que sentir-se català no impedeix sentir-se part de la comunitat etnocultural d’origen. A més, existeix una interrelació entre l'orientació cultural catalana i la identificació amb les comunitats cíviques locals. De la mateixa manera, tenir competències en llengua catalana no va en detriment de les competències en llengua castellana. Les anàlisis també mostren que factors com l’orientació cultural catalana, l’ús del català i la identificació amb la cultura catalana tenen una correlació positiva amb el grau de chohesio de la indentitat bicultural, afavoreixen el benestar psicològic i disminueixen l’estrès aculturatiu. L’anàlisi de les xarxes socials mostra que la identificació amb la cultura catalana, l’orientació cultural catalana i la integració de la identitat són factors clau per tenir xarxes socials més diverses des del punt de vista ètnic i lingüístic, amb menys membres del col•lectiu d’origen, i amb subgrups o “cliques” culturalment més heterogenis. La identificació espanyola també prediu, en mesura més reduïda, la diversitat de les xarxes. Els nostres resultats contribueixen a la recerca actual i les teories sobre interculturalitat i identitat cultural.

A new efficient approach to the direct restricted active space self-consistent field method

An implicitly parallel method for integral-block driven restricted active space self-consistent field (RASSCF) algorithms is presented. The approach is based on a model space representation of the RAS active orbitals with an efficient expansion of the model subspaces. The applicability of the method is demonstrated with a RASSCF investigation of the first two excited states of indole

Automatic generation of active coordinates for quantum dynamics calculations: application to the dynamics of benzene photochemistry

A new practical method to generate a subspace of active coordinates for quantum dynamics calculations is presented. These reduced coordinates are obtained as the normal modes of an analytical quadratic representation of the energy difference between excited and ground states within the complete active space self-consistent field method. At the Franck-Condon point, the largest negative eigenvalues of this Hessian correspond to the photoactive modes: those that reduce the energy difference and lead to the conical intersection; eigenvalues close to 0 correspond to bath modes, while modes with large positive eigenvalues are photoinactive vibrations, which increase the energy difference. The efficacy of quantum dynamics run in the subspace of the photoactive modes is illustrated with the photochemistry of benzene, where theoretical simulations are designed to assist optimal control experiments

A8a Summary of Food Stamp Errors-Active and Negative cases, July 2004

A-8A summary of food stamp errors active and negative cases

A-8a 2003 Summary of Food Stamp Errors - Active and Negative Cases, April 2001 - September 2001

Summary of food stamp errors.

Hypotensive effect of human factor XII active fragment in conscious normotensive rats: role of bradykinin.

The active fragment derived from factor XII (factor XIIf) was purified from human plasma and administered intravenously to normotensive conscious rats. Factor XIIf-mediated hypotension was dose-dependent and augmented by pretreatment with captopril, an inhibitor of the bradykinin-processing enzyme kininase II. These results therefore suggest that factor XIIf-mediated hypotension is due to the formation of bradykinin.

Orthotropic active strain models for the numerical simulation of cardiac biomechanics

An active strain formulation for orthotropic constitutive laws arising in cardiac mechanics modeling is introduced and studied. The passive mechanical properties of the tissue are described by the Holzapfel-Ogden relation. In the active strain formulation, the Euler-Lagrange equations for minimizing the total energy are written in terms of active and passive deformation factors, where the active part is assumed to depend, at the cell level, on the electrodynamics and on the specific orientation of the cardiac cells. The well-posedness of the linear system derived from a generic Newton iteration of the original problem is analyzed and different mechanical activation functions are considered. In addition, the active strain formulation is compared with the classical active stress formulation from both numerical and modeling perspectives. Taylor-Hood and MINI finite elements are employed to discretize the mechanical problem. The results of several numerical experiments show that the proposed formulation is mathematically consistent and is able to represent the main key features of the phenomenon, while allowing savings in computational costs.

Monitoring of illicit pill distribution networks using an image collection exploration framework

This paper proposes a novel approach for the analysis of illicit tablets based on their visual characteristics. In particular, the paper concentrates on the problem of ecstasy pill seizure profiling and monitoring. The presented method extracts the visual information from pill images and builds a representation of it, i.e. it builds a pill profile based on the pill visual appearance. Different visual features are used to build different image similarity measures, which are the basis for a pill monitoring strategy based on both discriminative and clustering models. The discriminative model permits to infer whether two pills come from the same seizure, while the clustering models groups of pills that share similar visual characteristics. The resulting clustering structure allows to perform a visual identification of the relationships between different seizures. The proposed approach was evaluated using a data set of 621 Ecstasy pill pictures. The results demonstrate that this is a feasible and cost effective method for performing pill profiling and monitoring.

A targeted association study of immunity genes and networks suggests novel associations with placental malaria infection

A large proportion of the death toll associated with malaria is a consequence of malaria infection during pregnancy, causing up to 200,000 infant deaths annually. We previously published the first extensive genetic association study of placental malaria infection, and here we extend this analysis considerably, investigating genetic variation in over 9,000 SNPs in more than 1,000 genes involved in immunity and inflammation for their involvement in susceptibility to placental malaria infection. We applied a new approach incorporating results from both single gene analysis as well as gene-gene interactionson a protein-protein interaction network. We found suggestive associations of variants in the gene KLRK1 in the single geneanalysis, as well as evidence for associations of multiple members of the IL-7/IL-7R signalling cascade in the combined analysis. To our knowledge, this is the first large-scale genetic study on placental malaria infection to date, opening the door for follow-up studies trying to elucidate the genetic basis of this neglected form of malaria.

Minimizing recombinations in consensus networks for phylogeographic studies

Background: We address the problem of studying recombinational variations in (human) populations. In this paper, our focus is on one computational aspect of the general task: Given two networks G1 and G2, with both mutation and recombination events, defined on overlapping sets of extant units the objective is to compute a consensus network G3 with minimum number of additional recombinations. We describe a polynomial time algorithm with a guarantee that the number of computed new recombination events is within ϵ = sz(G1, G2) (function sz is a well-behaved function of the sizes and topologies of G1 and G2) of the optimal number of recombinations. To date, this is the best known result for a network consensus problem.Results: Although the network consensus problem can be applied to a variety of domains, here we focus on structure of human populations. With our preliminary analysis on a segment of the human Chromosome X data we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. These results have been verified independently using traditional manual procedures. To the best of our knowledge, this is the first recombinations-based characterization of human populations. Conclusion: We show that our mathematical model identifies recombination spots in the individual haplotypes; the aggregate of these spots over a set of haplotypes defines a recombinational landscape that has enough signal to detect continental as well as population divide based on a short segment of Chromosome X. In particular, we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. The agreement with mutation-based analysis can be viewed as an indirect validation of our results and the model. Since the model in principle gives us more information embedded in the networks, in our future work, we plan to investigate more non-traditional questions via these structures computed by our methodology.