Frequência da Anafilaxia Induzida pelo Exercício numa Consulta de Imunoalergologia

Introdução: A anafilaxia induzida pelo exercício (AIE) é uma forma rara de alergia física que ocorre na sequência de esforços físicos. A verdadeira incidência e prevalência da AIE permanecem por esclarecer, não existindo até à data dados publicados a nível nacional. Objectivos: Estimar a frequência da AIE no ambulatório de um serviço de Imunoalergologia e incrementar o conhecimento em relação a esta patologia. Métodos: De 7699 doentes observados na consulta de Imunoalergologia durante o período de um ano, incluímos os correspondentes a quadros de anafilaxia notificados pelo corpo clínico (“pelo menos um episódio de reacção sistémica grave”). Resultados: A AIE foi reportada em 5 de 103 doentes com história de anafilaxia; correspondendo a uma frequência de 0,06% na população observada na consulta. A média etária destes doentes era de 20,2 ± 10,3 anos (entre 10 e 37 anos) e a distribuição por sexo masculino/feminino de 4:1. Todos tinham história pessoal de atopia e de rinite alérgica; dois doentes (40%) tinham asma. As actividades desencadeantes das crises foram a corrida, o futebol, a natação e a dança. Todos os doentes tinham sintomas com o exercício dependente da ingestão prévia de alimentos: cereais em três doentes (trigo – dois, cevada – um), leguminosas em dois (amendoim – um, feijão -frade e feijão -verde – um); com teste cutâneo por picada positivo para os referidos alimentos. Conclusões: A AIE representa 5% dos casos de anafi laxia reportados. Todos os casos identifi cados apresentavam AIE dependente de alimentos, encontrando-se os doentes controlados com a evicção dos alimentos referidos 6 horas antes da prática de exercício e sendo portadores de dispositivo para autoadministração de adrenalina

Copy number variants prioritization after array-CGH analysis - a cohort of 1000 patients

Array-based comparative genomic hybridization has been assumed to be the first genetic test offered to detect genomic imbalances in patients with unexplained intellectual disability with or without dysmorphisms, multiple congenital anomalies, learning difficulties and autism spectrum disorders. Our study contributes to the genotype/phenotype correlation with the delineation of laboratory criteria which help to classify the different copy number variants (CNVs) detected. We clustered our findings into five classes ranging from an imbalance detected in a microdeletion/duplication syndrome region (class I) to imbalances that had previously been reported in normal subjects in the Database of Genomic Variants (DGV) and thus considered common variants (class IV).info:eu-repo/semantics/publishedVersio

Nursing Diagnosis Risk for falls: prevalence and clinical profile of hospitalized patients

Objectives: to identify the prevalence of the Nursing Diagnosis (ND) Risk for falls in the hospitalizations of adult patients in clinical and surgical units, to characterize the clinical profile and to identify the risk factors of the patients with this ND. Method: a cross-sectional study with 174 patients. The data was collected from the computerized nursing care prescriptions system and on-line hospital records, and analyzed statistically. Results: the prevalence of the ND Risk for falls was 4%. The patients’ profile indicated older adults, males (57%), those hospitalized in the clinical units (63.2%), with a median length of hospitalization of 20 (10-24) days, with neurological illnesses (26%), cardio-vascular illnesses (74.1%) and various co-morbidities (3±1.8). The prevalent risk factors were neurological alterations (43.1%), impaired mobility (35.6%) and extremes of age (10.3%). Conclusion: the findings contributed to evidencing the profile of the patients with a risk of falling hospitalized in clinical and surgical wards, which favors the planning of interventions for preventing this adverse event

A Dynamical Systems Model for Combinatorial Cancer Therapy Enhances Oncolytic Adenovirus Efficacy by MEK-Inhibition

Oncolytic adenoviruses, such as ONYX-015, have been tested in clinical trials for currently untreatable tumors, but have yet to demonstrate adequate therapeutic efficacy. The extent to which viruses infect targeted cells determines the efficacy of this approach but many tumors down-regulate the Coxsackievirus and Adenovirus Receptor (CAR), rendering them less susceptible to infection. Disrupting MAPK pathway signaling by pharmacological inhibition of MEK up-regulates CAR expression, offering possible enhanced adenovirus infection. MEK inhibition, however, interferes with adenovirus replication due to resulting G1-phase cell cycle arrest. Therefore, enhanced efficacy will depend on treatment protocols that productively balance these competing effects. Predictive understanding of how to attain and enhance therapeutic efficacy of combinatorial treatment is difficult since the effects of MEK inhibitors, in conjunction with adenovirus/cell interactions, are complex nonlinear dynamic processes. We investigated combinatorial treatment strategies using a mathematical model that predicts the impact of MEK inhibition on tumor cell proliferation, ONYX-015 infection, and oncolysis. Specifically, we fit a nonlinear differential equation system to dedicated experimental data and analyzed the resulting simulations for favorable treatment strategies. Simulations predicted enhanced combinatorial therapy when both treatments were applied simultaneously; we successfully validated these predictions in an ensuing explicit test study. Further analysis revealed that a CAR-independent mechanism may be responsible for amplified virus production and cell death. We conclude that integrated computational and experimental analysis of combinatorial therapy provides a useful means to identify treatment/infection protocols that yield clinically significant oncolysis. Enhanced oncolytic therapy has the potential to dramatically improve non-surgical cancer treatment, especially in locally advanced or metastatic cases where treatment options remain limited.National Institutes of Health (U.S.) (Grant R01 CA118545)National Institutes of Health (U.S.) (Grant R01 CA095701)National Institutes of Health (U.S.) (Grant U54 CA11297)National Institutes of Health (U.S.) (Grant U54-CA112967