Sequential Monte Carlo with transformations.

This paper examines methodology for performing Bayesian inference sequentially on a sequence of posteriors on spaces of different dimensions. For this, we use sequential Monte Carlo samplers, introducing the innovation of using deterministic transformations to move particles effectively between target distributions with different dimensions. This approach, combined with adaptive methods, yields an extremely flexible and general algorithm for Bayesian model comparison that is suitable for use in applications where the acceptance rate in reversible jump Markov chain Monte Carlo is low. We use this approach on model comparison for mixture models, and for inferring coalescent trees sequentially, as data arrives

Inyecciones locales multipuntuales con corticosteroide para el síndrome de estrés tibial medial: un nuevo enfoque

Medial stress tibial syndrome (MTSS) has been and remains one of the most common pathologic conditions of the lower extremity. The results of conventional therapies for this condition have been inconsistent. Local corticosteroid injection has been shown to have favourable effects in treating musculoskeletal disorders. The effect of local multipunctual injections of a corticosteroid combined with an anaesthetic was studied in 47 patients (29 male and 18 female subjects, with an average age of 23.8 years) with MTSS. Direct consultation and examination was used to assess outcome. Patients were evaluated once a week after first injection for the first 4 weeks, and 3 months after treatment as well. Level of symptoms-free activity was recorded for each patient. The outcomes of the multipunctual injections were determined by comparing preintervention and posintervention level of symptoms-free activity and ability of the athletes to return to presymptom levels of exercise. The results suggest that the treatment reduces the recovery time and improves functional outcomes.El síndrome de estrés medial de la tibia (SEMT) constituye una de las afecciones más comunes del miembro inferior. Los resultados obtenidos con terapias convencionales en esta patología son dispares. La infiltración local de corticoides ha mostrado producir efectos favorables en el tratamiento de diversos problemas musculoesqueléticos. El efecto de la infiltración local multipuntual de un corticoide en combinación con un anestésico se estudió en 47 pacientes (29 hombres y 18 mujeres, con una edad media de 23.8) afectos de SEMT. La consulta directa y el examen físico se emplearon para valorar los resultados. Los pacientes fueron valorados una vez a la semana tras la primera aplicación durante las primeras cuatro semanas y 3 meses después del tratamiento. El nivel de actividad en ausencia de síntomas fue registrado en cada caso. Los resultados de la infiltración multipuntual se determinaron comparando los niveles de actividad en ausencia de síntomas preintervención y posintervención y la capacidad de los deportistas para volver a los niveles de actividad presintomáticos. Los resultados sugieren que este tratamiento reduce el tiempo de recuperación y mejora los resultados funcionales

LOS CONOCIMIENTOS SOBRE EL SUEÑO Y LOS CUIDADOS ENFERMEROS PARA UN BUEN DESCANSO

The patients checked in to the hospital do not sleep well, sometimes due to their pathology, and others times due to their environment. To identify the knowledge of nurses in regards to sleep, as well as putting in place activities that improve it. These aspects are considered in this investigation carried out in the Infanta Elena Hospital in Huelva, Spain. An observational, descriptive, cross-sectional study was carried out, using a survey elaborated by the investigative team, which was given to these professionals. The information was treated through the program SPSS for analysis. As results we emphasize that 75 % of the nurses identify both phases of sleep, but the steps along the NREM and REM are not clear for 55,4 %. A percentage of 57,4 % thinks that a person who wakes up in some phase, when they return to sleep have to begin with phase I of NREM sleep, as if they were initiating rest. Nevertheless 56,9 % affirms that this does not imply that the person could not rest. To assure a number of hours of sufficient sleep is considered to be important for rest. Nevertheless, due to the reasons above mentioned and because the nurses were not clear about whether or not waking often causes that the regeneration of energy cannot be completed, lead us to think that the nurses lack knowledge of sleep. Los pacientes ingresados en el hospital no duermen bien, unas veces por su patología, y otras por causas ambientales. Identificar los conocimientos de enfermería sobre el sueño, así como la puesta en marcha de actividades que lo mejoren, son aspectos abordados en esta investigación efectuada en el Hospital Infanta Elena de Huelva. Se realizó un estudio observacional descriptivo transversal, utilizándose una encuesta elaborada por el equipo investigador, que se pasó a estos profesionales. Los datos fueron tratados con el programa SPSS para su análisis. Como resultados destacamos que el 75% de las enfermeras/os identifican ambas fases del sueño, pero los pasos por la NREM y REM no lo tienen claro un 55,4%. El 57,4% considera que una persona que se despierta en alguna fase, cuando vuelve a dormir ha de comenzar por la fase I de sueño NREM como si iniciara el reposo, sin embargo el 56,9% afirma que esto no implica que la persona no pueda descansar. Asegurar un número de horas de sueño suficiente es considerado importante para el descanso, sin embargo, por todo lo anterior y además de que no parece tenerse claro que si nos despertamos muchas veces ello hace que la reposición de la energía no pueda completarse, nos lleva a pensar en una falta de conocimientos que sobre el sueño tiene el grupo de enfermeras del estudio.

Revisiting the S-matrix approach to the open superstring low energy effective lagrangian

The conventional S-matrix approach to the (tree level) open string low energy effective lagrangian assumes that, in order to obtain all its bosonic ${\alpha'}^N$ order terms, it is necessary to know the open string (tree level) $(N+2)$-point amplitude of massless bosons, at least expanded at that order in $\alpha'$. In this work we clarify that the previous claim is indeed valid for the bosonic open string, but for the supersymmetric one the situation is much more better than that: there are constraints in the kinematical bosonic terms of the amplitude (probably due to Spacetime Supersymmetry) such that a much lower open superstring $n$-point amplitude is needed to find all the ${\alpha'}^N$ order terms. In this `revisited' S-matrix approach we have checked that, at least up to ${\alpha'}^4$ order, using these kinematical constraints and only the known open superstring 4-point amplitude, it is possible to determine all the bosonic terms of the low energy effective lagrangian. The sort of results that we obtain seem to agree completely with the ones achieved by the method of BPS configurations, proposed about ten years ago. By means of the KLT relations, our results can be mapped to the NS-NS sector of the low energy effective lagrangian of the type II string theories implying that there one can also find kinematical constraints in the $N$-point amplitudes and that important informations can be inferred, at least up to ${\alpha'}^4$ order, by only using the (tree level) 4-point amplitude.Comment: 34 pages, 3 figure, Submitted on Aug 4, 2012, Published on Oct 15, 201

An accurate test for homogeneity of odds ratios based on Cochran's Q-statistic

Background: A frequently used statistic for testing homogeneity in a meta-analysis of K independent studies is Cochran's Q. For a standard test of homogeneity the Q statistic is referred to a chi-square distribution with K - 1 degrees of freedom. For the situation in which the effects of the studies are logarithms of odds ratios, the chi-square distribution is much too conservative for moderate size studies, although it may be asymptotically correct as the individual studies become large. Methods: Using a mixture of theoretical results and simulations, we provide formulas to estimate the shape and scale parameters of a gamma distribution to t the distribution of Q. Results: Simulation studies show that the gamma distribution is a good approximation to the distribution for Q. Conclusions: : Use of the gamma distribution instead of the chi-square distribution for Q should eliminate inaccurate inferences in assessing homogeneity in a meta-analysis. (A computer program for implementing this test is provided.) This hypothesis test is competitive with the Breslow-Day test both in accuracy of level and in power

Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control

It is widely accepted that the complex dynamics characteristic of recurrent neural circuits contributes in a fundamental manner to brain function. Progress has been slow in understanding and exploiting the computational power of recurrent dynamics for two main reasons: nonlinear recurrent networks often exhibit chaotic behavior and most known learning rules do not work in robust fashion in recurrent networks. Here we address both these problems by demonstrating how random recurrent networks (RRN) that initially exhibit chaotic dynamics can be tuned through a supervised learning rule to generate locally stable neural patterns of activity that are both complex and robust to noise. The outcome is a novel neural network regime that exhibits both transiently stable and chaotic trajectories. We further show that the recurrent learning rule dramatically increases the ability of RRNs to generate complex spatiotemporal motor patterns, and accounts for recent experimental data showing a decrease in neural variability in response to stimulus onset

DNA barcoding reveals the coral “laboratory-rat”, Stylophora pistillata encompasses multiple identities

Stylophora pistillata is a widely used coral “lab-rat” species with highly variable morphology and a broad biogeographic range (Red Sea to western central Pacific). Here we show, by analysing Cytochorme Oxidase I sequences, from 241 samples across this range, that this taxon in fact comprises four deeply divergent clades corresponding to the Pacific-Western Australia, Chagos-Madagascar-South Africa, Gulf of Aden-Zanzibar-Madagascar, and Red Sea-Persian/Arabian Gulf-Kenya. On the basis of the fossil record of Stylophora, these four clades diverged from one another 51.5-29.6 Mya, i.e., long before the closure of the Tethyan connection between the tropical Indo-West Pacific and Atlantic in the early Miocene (16–24 Mya) and should be recognised as four distinct species. These findings have implications for comparative ecological and/or physiological studies carried out using Stylophora pistillata as a model species, and highlight the fact that phenotypic plasticity, thought to be common in scleractinian corals, can mask significant genetic variation

Hormone-induced protection of mammary tumorigenesis in genetically engineered mouse models

INTRODUCTION: The experiments reported here address the question of whether a short-term hormone treatment can prevent mammary tumorigenesis in two different genetically engineered mouse models. METHODS: Two mouse models, the p53-null mammary epithelial transplant and the c-neu mouse, were exposed to estrogen and progesterone for 2 and 3 weeks, respectively, and followed for development of mammary tumors. RESULTS: In the p53-null mammary transplant model, a 2-week exposure to estrogen and progesterone during the immediate post-pubertal stage (2 to 4 weeks after transplantation) of mammary development decreased mammary tumorigenesis by 70 to 88%. At 45 weeks after transplantation, analysis of whole mounts of the mammary outgrowths demonstrated the presence of premalignant hyperplasias in both control and hormone-treated glands, indicating that the hormone treatment strongly affects the rate of premalignant progression. One possible mechanism for the decrease in mammary tumorigenesis may be an altered proliferation activity as the bromodeoxyuridine labeling index was decreased by 85% in the mammary glands of hormone-treated mice. The same short-term exposure administered to mature mice at a time of premalignant development also decreased mammary tumorigenesis by 60%. A role for stroma and/or systemic mediated changes induced by the short-term hormone (estrogen/progesterone) treatment was demonstrated by an experiment in which the p53-null mammary epithelial cells were transplanted into the cleared mammary fat pads of previously treated mice. In such mice, the tumor-producing capabilities of the mammary cells were also decreased by 60% compared with the same cells transplanted into unexposed mice. In the second set of experiments using the activated Her-2/neu transgenic mouse model, short-term estradiol or estradiol plus progesterone treatment decreased mammary tumor incidence by 67% and 63%, and tumor multiplicity by 91% and 88%, respectively. The growth rate of tumors arising in the hormone-treated activated Her-2/neu mice was significantly lower than tumors arising in non-hormone treated mice. CONCLUSION: Because these experiments were performed in model systems that mimic many essential elements of human breast cancer, the results strengthen the rationale for translating this prevention strategy to humans at high risk for developing breast cancer

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks