Analysis of serious non-AIDS events among HIV-infected adults at Latin American sites

Acquired immune deficiency appears to be associated with serious non-AIDS (SNA)-defining conditions such as cardiovascular disease, liver and renal insufficiency and non-AIDS-related malignancies. We analysed the incidence of, and factors associated with, several SNA events in the LATINA retrospective cohort.

Foxp3 expression in macrophages associated with RENCA tumors in mice.

The transcription factor Foxp3 represents the most specific functional marker of CD4+ regulatory T cells (TRegs). However, previous reports have described Foxp3 expression in other cell types including some subsets of macrophages, although there are conflicting reports and Foxp3 expression in cells other than Treg is not well characterized. We performed detailed investigations into Foxp3 expression in macrophages in the normal tissue and tumor settings. We detected Foxp3 protein in macrophages infiltrating mouse renal cancer tumors injected subcutaneously or in the kidney. Expression was demonstrated using flow cytometry and Western blot with two individual monoclonal antibodies. Further analyses confirmed Foxp3 expression in macrophages by RT PCR, and studies using ribonucleic acid-sequencing (RNAseq) demonstrated a previously unknown Foxp3 messenger (m)RNA transcript in tumor-associated macrophages. In addition, depletion of Foxp3+ cells using diphtheria toxin in Foxp3DTR mice reduced the frequency of type-2 macrophages (M2) in kidney tumors. Collectively, these results indicate that tumor-associated macrophages could express Foxp3.

A novel aggregate gene selection method for microarray data classification

This paper introduces a novel method for gene selection based on a modification of analytic hierarchy process (AHP). The modified AHP (MAHP) is able to deal with quantitative factors that are statistics of five individual gene ranking methods: two-sample t-test, entropy test, receiver operating characteristic curve, Wilcoxon test, and signal to noise ratio. The most prominent discriminant genes serve as inputs to a range of classifiers including linear discriminant analysis, k-nearest neighbors, probabilistic neural network, support vector machine, and multilayer perceptron. Gene subsets selected by MAHP are compared with those of four competing approaches: information gain, symmetrical uncertainty, Bhattacharyya distance and ReliefF. Four benchmark microarray datasets: diffuse large B-cell lymphoma, leukemia cancer, prostate and colon are utilized for experiments. As the number of samples in microarray data datasets are limited, the leave one out cross validation strategy is applied rather than the traditional cross validation. Experimental results demonstrate the significant dominance of the proposed MAHP against the competing methods in terms of both accuracy and stability. With a benefit of inexpensive computational cost, MAHP is useful for cancer diagnosis using DNA gene expression profiles in the real clinical practice.

Sensitivity to MK-801 in phospholipase C-β1 knockout mice reveals a specific NMDA receptor deficit

Phospholipase C-β1 (PLC-β1) is a critical component of multiple signalling pathways downstream of neurotransmitter receptors. Mice lacking this enzyme display a striking behavioural phenotype with relevance to human psychiatric disease. Glutamatergic dysfunction is strongly associated with several abnormal behavioural states and may underlie part of the phenotype of the phospholipase C-β1 knockout (KO) mouse. A heightened response to glutamatergic psychotomimetic drugs is a critical psychosis-related endophenotype, and in this study it was employed as a correlate of glutamatergic dysfunction. Control (n=8) and PLC-β1 KO mice (n=6) were treated with MK-801, a NMDA receptor (NMDAR) antagonist, following either standard housing or environmental enrichment, and the motor function and locomotor activity thus evoked was assessed. In addition, MK-801 binding to the NMDAR was evaluated through radioligand autoradiography in post-mortem tissue (on a drug-naive cohort). We have demonstrated a significantly increased sensitivity to the effects of the NMDA antagonist MK-801 in the PLC-β1 KO mouse. In addition, we found that this mouse line displays reduced hippocampal NMDAR expression, as measured by radioligand binding. We previously documented a reversal of specific phenotypes in this mouse line following housing in an enriched environment. Enrichment did not alter this heightened MK-801 response, nor NMDAR expression, indicating that this therapeutic intervention works on specific pathways only. These findings demonstrate the critical role of the glutamatergic system in the phenotype of the PLC-β1 KO mouse and highlight the role of these interconnected signalling pathways in schizophrenia-like behavioural disruption. These results also shed further light on the capacity of environmental factors to modulate subsets of these phenotypes.

Hidden Markov models for cancer classification using gene expression profiles

This paper introduces an approach to cancer classification through gene expression profiles by designing supervised learning hidden Markov models (HMMs). Gene expression of each tumor type is modelled by an HMM, which maximizes the likelihood of the data. Prominent discriminant genes are selected by a novel method based on a modification of the analytic hierarchy process (AHP). Unlike conventional AHP, the modified AHP allows to process quantitative factors that are ranking outcomes of individual gene selection methods including t-test, entropy, receiver operating characteristic curve, Wilcoxon test and signal to noise ratio. The modified AHP aggregates ranking results of individual gene selection methods to form stable and robust gene subsets. Experimental results demonstrate the performance dominance of the HMM approach against six comparable classifiers. Results also show that gene subsets generated by modified AHP lead to greater accuracy and stability compared to competing gene selection methods, i.e. information gain, symmetrical uncertainty, Bhattacharyya distance, and ReliefF. The modified AHP improves the classification performance not only of the HMM but also of all other classifiers. Accordingly, the proposed combination between the modified AHP and HMM is a powerful tool for cancer classification and useful as a real clinical decision support system for medical practitioners.

Cover, not caging, influences chronic physiological stress in a ground-nesting bird

Predator exclosures ('nest cages') around nests are increasingly used to enhance hatching success of declining ground-nesting birds. However, such exclosures are contentious and have been suggested to have detrimental effects on the species which they aim to protect. This study examines whether exclosures increase physiological stress of incubating birds, a hitherto unrecognised and untested potential drawback of exclosures. Red-capped plover Charadrius ruficapillus hatching success was radically altered and significantly higher for nests with exclosures (96.2%) compared with those without (6.8%). Chronic physiological stress in parents (as measured by the heterophil/lymphocyte [H/L] ratio in blood) did not vary between nests with and without exclosures, or between the sexes. However the absence of vegetative cover at the nest site was associated with a 62.7% elevation in H/L ratio, indicating that incubating birds which place their nests in the open are subject to increased levels of chronic stress. The results from this study demonstrate the fundamental importance of predation for the nesting success of this species and confirm that chronic stress levels are not a detrimental side effect of exclosure use.

The construction of a subset of ICNP® for patients with dementia: a Delphi consensus and a group interview study

BACKGROUND: The International Classification for Nursing Practice (ICNP®) 2013 includes over 4000 concepts for global nursing diagnoses, outcomes and interventions and is a large and complex set of standardised nursing concepts and expressions. Nurses may use subsets from the ICNP as concepts and expressions for research, education and clinical practice. The objective of this study was to identify and validate concepts for an ICNP subset to guide observations and documentation of nursing care for patients with dementia.

METHOD: The process model for developing ICNP subsets was followed, according to the guidelines adopted by the International Council of Nursing (ICN). To identify relevant and useful concepts for the subset, a modified form of the Delphi method was used. Six nurses working in healthcare services in three municipalities in Norway with postgraduate education in geriatric psychiatry and dementia care participated in two Delphi sessions. The participants reviewed and scored the concepts included in the suggested subset and had an opportunity to rewrite them and offer alternatives. To validate the subset after the Delphi study, a group interview was conducted with six other nurses with postgraduate education in geriatric psychiatry and dementia care. The group interview was recorded and transcribed, and summative content analysis was used.

RESULTS: Suitable concepts for an ICNP subset to guide observations and documentation of nursing care for patients with dementia were identified. In total, 301 concepts were identified, including 77 nursing diagnoses, 78 outcomes and 146 nursing interventions. An increased focus on concepts to describe basic psychosocial needs such as identity, comfort, connection, inclusion and engagement was recommended by nurses in the validation process.

CONCLUSIONS: Relevant and pre-formulated nursing diagnoses, goals and interventions were identified, which can be used to develop care plans and facilitate accuracy in the documentation of individuals with dementia. The participants believed that it may be difficult to find formulations for all steps of the nursing process. In particular, nursing diagnoses and psychosocial needs are often inadequately documented. The participants highlighted the need for the subset to contain essential information about psychosocial needs and communication.

Modelling human preferences for ranking and collaborative filtering: a probabilistic ordered partition approach

Learning preference models from human generated data is an important task in modern information processing systems. Its popular setting consists of simple input ratings, assigned with numerical values to indicate their relevancy with respect to a specific query. Since ratings are often specified within a small range, several objects may have the same ratings, thus creating ties among objects for a given query. Dealing with this phenomena presents a general problem of modelling preferences in the presence of ties and being query-specific. To this end, we present in this paper a novel approach by constructing probabilistic models directly on the collection of objects exploiting the combinatorial structure induced by the ties among them. The proposed probabilistic setting allows exploration of a super-exponential combinatorial state-space with unknown numbers of partitions and unknown order among them. Learning and inference in such a large state-space are challenging, and yet we present in this paper efficient algorithms to perform these tasks. Our approach exploits discrete choice theory, imposing generative process such that the finite set of objects is partitioned into subsets in a stagewise procedure, and thus reducing the state-space at each stage significantly. Efficient Markov chain Monte Carlo algorithms are then presented for the proposed models. We demonstrate that the model can potentially be trained in a large-scale setting of hundreds of thousands objects using an ordinary computer. In fact, in some special cases with appropriate model specification, our models can be learned in linear time. We evaluate the models on two application areas: (i) document ranking with the data from the Yahoo! challenge and (ii) collaborative filtering with movie data. We demonstrate that the models are competitive against state-of-the-arts.

What shall i share and with whom? A multi-task learning formulation using multi-faceted task relationships

Multi-task learning is a learning paradigm that improves the performance of "related" tasks through their joint learning. To do this each task answers the question "Which other task should I share with"? This task relatedness can be complex - a task may be related to one set of tasks based on one subset of features and to other tasks based on other subsets. Existing multi-task learning methods do not explicitly model this reality, learning a single-faceted task relationship over all the features. This degrades performance by forcing a task to become similar to other tasks even on their unrelated features. Addressing this gap, we propose a novel multi-task learning model that leams multi-faceted task relationship, allowing tasks to collaborate differentially on different feature subsets. This is achieved by simultaneously learning a low dimensional sub-space for task parameters and inducing task groups over each latent subspace basis using a novel combination of L1 and pairwise L∞ norms. Further, our model can induce grouping across both positively and negatively related tasks, which helps towards exploiting knowledge from all types of related tasks. We validate our model on two synthetic and five real datasets, and show significant performance improvements over several state-of-the-art multi-task learning techniques. Thus our model effectively answers for each task: What shall I share and with whom?

Ativação linfocitária durante a cirurgia de revascularização miocárdica : papel da circulação extracorpórea

Introdução: Sabe-se que a cirurgia de revascularização miocárdica está associada com alteração dos mediadores inflamatórios e da função imunitária, com ativação precoce dos linfócitos que poderia ser responsável pela linfopenia e diminuição da atividade dos linfócitos no pós-operatório. A elevação enzimática está diminuída na cirurgia sem circulação extracorpórea mas este achado não está associado a melhor evolução clínica. Nesta tese, testamos a hipótese de que a cirurgia de revascularização miocárdica realizada sem circulação extracorpórea pode levar a uma ativação linfocitária de menor intensidade do que a cirurgia com circulação extracorpórea. Métodos: A resposta da ativação linfocitária foi estudada durante o período trans e pósoperatório em 28 pacientes randomizados para cirurgia de coronária sem circulação extracorpórea (n=13) ou cirurgia convencional com circulação extracorpórea (n=15), utilizando citometria de fluxo para determinar a expressão de CD25, CD26, CD69 e DR em linfócitos T (CD3+) e B (CD19+), em sangue periférico. No mesmo período foram realizadas dosagens de troponina I por quimioluminescência e realizado ecocardiograma uni-bidimensional antes e após a cirurgia. Resultados: Não houve diferença estatisticamente significativa para nenhum dos marcadores de ativação linfocitária quando comparados os grupos operados sem ou com circulação extracorpórea (ANOVA bicaudal para medidas repetidas, p>0,05). Considerando todos os pacientes estudados, houve uma elevação da expressão proporcional de CD25 e CD69 em linfócitos T (CD3+) e B (CD19+). Nos linfócitos T, o valor proporcional médio mais elevado (+ EP) de CD69 foi observado 6 horas após terem sido completadas as anastomoses (+75 + 476%) e CD25 teve uma elevação mais gradual, com o pico de seu valor médio (+48 + 24 %) ocorrendo 24 horas após a revascularização. Em linfócitos B, o pico do valor médio de CD69 (+104 + 269 %) ocorreu também após o fim das anastomoses. CD25 teve seu pico de valor médio (+150 + 773 %) 112 horas após a revascularização e seu último valor medido ainda estava elevado. A expressão de CD26 em linfócitos T teve um aparente declínio nos seus valores proporcionais médios (-42 + 32 %) 12 horas após o fim das anastomoses. Não houve diferença significativa na elevação enzimática entre os dois grupos (teste estatístico >0,05). No ecocardiograma, o grupo operado sem circulação extracorpórea apresentou diminuição do volume diastólico (p=0,001) de da fração de ejeção (P=0,012), enquanto no grupo com circulação extracorpórea, diminuíram os volumes diastólico (p=0,006) e sistólico (p=0,01). Conclusões: 1) Comparando a cirurgia de revascularização miocárdica com circulação extracorpórea, a cirurgia sem circulação extracorpórea não reduz a ativação dos linfócitos. 2) A cirurgia de revascularização miocárdica produz uma ativação precoce dos linfócitos, com aumento da expressão de CD69 e CD25 em linfócitos T (CD3+) e B (CD19+), em sangue periférico. A elevação precoce de CD69, e elevação mais tardia de CD25, pode indicar duas partes de uma seqüência de ativação linfocitária. 3) O comportamento das enzimas cardíacas e dos achados ecocardiográficos não sugere benefício da cirurgia sem circulação extracorpórea sobre o dano miocárdio.

Graphical constraints: a graphical user interface for constraint problems

A constraint satisfaction problem is a classical artificial intelligence paradigm characterized by a set of variables (each variable with an associated domain of possible values), and a set of constraints that specify relations among subsets of these variables. Solutions are assignments of values to all variables that satisfy all the constraints. Many real world problems may be modelled by means of constraints. The range of problems that can use this representation is very diverse and embraces areas like resource allocation, scheduling, timetabling or vehicle routing. Constraint programming is a form of declarative programming in the sense that instead of specifying a sequence of steps to execute, it relies on properties of the solutions to be found, which are explicitly defined by constraints. The idea of constraint programming is to solve problems by stating constraints which must be satisfied by the solutions. Constraint programming is based on specialized constraint solvers that take advantage of constraints to search for solutions. The success and popularity of complex problem solving tools can be greatly enhanced by the availability of friendly user interfaces. User interfaces cover two fundamental areas: receiving information from the user and communicating it to the system; and getting information from the system and deliver it to the user. Despite its potential impact, adequate user interfaces are uncommon in constraint programming in general. The main goal of this project is to develop a graphical user interface that allows to, intuitively, represent constraint satisfaction problems. The idea is to visually represent the variables of the problem, their domains and the problem constraints and enable the user to interact with an adequate constraint solver to process the constraints and compute the solutions. Moreover, the graphical interface should be capable of configure the solver’s parameters and present solutions in an appealing interactive way. As a proof of concept, the developed application – GraphicalConstraints – focus on continuous constraint programming, which deals with real valued variables and numerical constraints (equations and inequalities). RealPaver, a state-of-the-art solver in continuous domains, was used in the application. The graphical interface supports all stages of constraint processing, from the design of the constraint network to the presentation of the end feasible space solutions as 2D or 3D boxes.

Detecting cell assemblies in large neuronal populations

Recent progress in the technology for single unit recordings has given the neuroscientific community theopportunity to record the spiking activity of large neuronal populations. At the same pace, statistical andmathematical tools were developed to deal with high-dimensional datasets typical of such recordings.A major line of research investigates the functional role of subsets of neurons with significant co-firingbehavior: the Hebbian cell assemblies. Here we review three linear methods for the detection of cellassemblies in large neuronal populations that rely on principal and independent component analysis.Based on their performance in spike train simulations, we propose a modified framework that incorpo-rates multiple features of these previous methods. We apply the new framework to actual single unitrecordings and show the existence of cell assemblies in the rat hippocampus, which typically oscillate attheta frequencies and couple to different phases of the underlying field rhythm

Evaluation of the Genotoxicity of Chitosan Nanoparticles for Use in Food Packaging Films

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)