Dexamethasone in glioblastoma multiforme therapy : mechanisms and controversies

Glioblastoma multiforme (GBM) is the most common and malignant of the glial tumors. The world-wide estimates of new cases and deaths annually are remarkable, making GBM a crucial public health issue. Despite the combination of radical surgery, radio and chemotherapy prognosis is extremely poor (median survival is approximately 1 year). Thus, current therapeutic interventions are highly unsatisfactory. For many years, GBM-induced brain oedema and inflammation have been widely treated with dexamethasone (DEX), a synthetic glucocorticoid (GC). A number of studies have reported that DEX also inhibits GBM cell proliferation and migration. Nevertheless, recent controversial results provided by different laboratories have challenged the widely accepted dogma concerning DEX therapy for GBM. Here, we have reviewed the main clinical features and genetic and epigenetic abnormalities underlying GBM. Finally, we analyzed current notions and concerns related to DEX effects on cerebral oedema, cancer cell proliferation and migration and clinical outcome.peer-reviewe

A three-term recurrence relation for accurate evaluation of transition probabilities of the simple birth-and-death process

The simple (linear) birth-and-death process is a widely used stochastic model for describing the dynamics of a population. When the process is observed discretely over time, despite the large amount of literature on the subject, little is known about formal estimator properties. Here we will show that its application to observed data is further complicated by the fact that numerical evaluation of the well-known transition probability is an ill-conditioned problem. To overcome this difficulty we will rewrite the transition probability in terms of a Gaussian hypergeometric function and subsequently obtain a three-term recurrence relation for its accurate evaluation. We will also study the properties of the hypergeometric function as a solution to the three-term recurrence relation. We will then provide formulas for the gradient and Hessian of the log-likelihood function and conclude the article by applying our methods for numerically computing maximum likelihood estimates in both simulated and real dataset.Peer reviewe

Kpax3 : Bayesian bi-clustering of large sequence datasets

Motivation: Estimation of the hidden population structure is an important step in many genetic studies. Often the aim is also to identify which sequence locations are the most discriminative between groups of samples for a given data partition. Automated discovery of interesting patterns that are present in the data can help to generate new biological hypotheses. Results: We introduce Kpax3, a Bayesian method for bi-clustering multiple sequence alignments. Influence of individual sites will be determined in a supervised manner by using informative prior distributions for the model parameters. Our inference method uses an implementation of both split-merge and Gibbs sampler type MCMC algorithms to traverse the joint posterior of partitions of samples and variables. We use a large Rotavirus sequence dataset to demonstrate the ability of Kpax3 to generate biologically important hypotheses about differential selective pressures across a virus protein.Peer reviewe

The emerging role of the inwardly rectifying K+ channels in autism spectrum disorders and epilepsy

Autism is a complex behavioral disorder that develops prior to age three years and is distinguished by high heritability. Many genes predisposing to autism spectrum disorders (ASDs) have been identified. These findings have demonstrated that ASDs are etiologically heterogeneous; although, the mutations underlying ASDs are identifiable only in a minority of patients. Indeed, the causes of ASDs are unknown in more than 70% of patients. Recently, we have described two unrelated families whose affected individuals display a characteristic triad of symptoms of autism; such as impairments in social interaction, impairments in communication, restricted interests and repetitive behavior. They also displayed other symptoms commonly observed in autistic individuals; such as gait imbalance, clumsiness, mental retardation and epilepsy. The genetic analysis of these families resulted in the identification of new heterozygous point mutations in the KCNJ10 gene that encodes the inwardly-rectifying K+ channel Kir4.1 expressed predominantly, but not exclusively, in astrocytes. Functionally, the mutated channels exhibited a phenotype consistent with gain-of-function defects. These new findings highlight the emerging role of inwardly-rectifying K+ channels and astrocyte dysfunction in autism spectrum disorders associated with epilepsy.peer-reviewe

Bayesian cluster analysis with applications to pathogen population genomics

Identifying similarity patterns in heterogeneous observations is a very common problem in many branches of science. When the similarities and dissimilarities are encoded by a group structure, the task of dividing the observed sample into an unknown number of homogeneous groups is known as cluster analysis. Among the many types of statistical data analyses, it is one of the most widely applied. In evolutionary biology, for example, the population structure plays an important role. Groups naturally arise as the result of evolutionary processes and depending on the resolution of the study, clusters might represent similar molecules, organisms, or even species. With the huge amount of genetic data now freely available in on-line databases, cluster analysis is a valuable technique to better understand the evolution of organisms. In this dissertation we focus our attention on Bayesian approaches to model-based clustering. We review the mathematical formalization of the two most common methods, finite mixture models and product partition models, together with algorithms needed to draw inferences. We then introduce a novel Bayesian model which has been specifically designed to partition categorical data matrices. Finally, we show how cluster analysis is a very effective method for understanding the evolution of pathogens, and how this information is relevant to public health

Redox sensitivity of tyrosine hydroxylase activity and expression in dopaminergic dysfunction

Oxidant molecules generated during neuronal metabolism appear to play a significant role in the processes of aging and neurodegeneration. Increasing experimental evidence suggests the noteworthy relevance of the intracellular reduction-oxidation (redox) balance for the dopaminergic (DA-ergic) neurons of the substantia nigra pars compacta. These cells possess a distinct physiology intrinsically associated with elevated reactive oxygen species production, conferring on them a high vulnerability to free radical damage, one of the major causes of selective DA-ergic neuron dysfunction and degeneration related to neurological disorders such as Parkinson’s disease. Tyrosine hydroxylase (tyrosine 3-monooxygenase; E.C. 1.14.16.2; TH) activity represents the rate-limiting biochemical event in DA synthesis. TH activity, metabolism and expression are finely tuned by several regulatory systems in order to maintain a crucial physiological condition in which DA synthesis is closely coupled to its secretion. Alterations of these regulatory systems of TH functions have indeed been thought to be key events in the DA-ergic degeneration. TH has seven cysteine residues presenting thiols. Depending on the oxido-reductive (redox) status of the cellular environment, thiols exist either in the reduced form of free thiols or oxidized to disulfides. The formation of disulfides in proteins exerts critical regulatory functions both in physiological and in pathological conditions when oxidative stress is sustained. Several reports have recently shown that redox state changes of thiol residues, as consequence of an oxidative injury, can directly or indirectly affect the TH activity, metabolism and expression. The major focus of this review, therefore, is to report recent evidence on the redox modulation of TH activity and expression, and to provide an overview of a cellular phenomenon that might represent a target for new therapeutic strategies against the DA-ergic neurodegenerative disorders.peer-reviewe

Power amplification via compliant layer interdigitation and dielectrophoretic structuring of PZT particle composites

Nonunion occurs in up to 10% of all fractures, with about 8% of all femoral fractures ending in nonunion, or failed healing with current fixation methods1,2. These failure rates can be caused by factors such as diabetes, osteoporosis, tobacco use, and severe tissue damage3,4. According to the FDA, it takes a minimum of nine moths to declare nonunion after trauma, with no progress in healing for three months5,6. Some adjunct therapy methods are being used to combat these failure rates such as the OsteoGen¬TM direct current bone growth stimulator. However, these devices require an implanted battery that will eventually need removed. The evolution of portable electronics has led to recent popularity of piezoelectric materials for energy harvesting, especially for devices deployed remotely or in vivo. Intramedullary nails could utilize the energy harvesting capabilities of piezoelectric materials to provide electrical stimulation at the fracture site without an implanted battery. However, the efficiency of piezoelectric generators harvesting energy from the human body is lacking due to off-resonance loading7. In addition, piezoelectric ceramics are expensive to manufacture, dense, brittle, and difficult to use in high strain environments. Piezoelectric composites composed of ferroelectric particles distributed in a polymer matrix are desirable due to low cost and tunable properties. In this study, Compliant Layer Adaptive Composite Stacks (CLACS) made with thin piezoelectric composite layers structured by dielectrophoresis (DEP) were investigated to increase the energy harvesting efficiency at low frequencies. To predict power generation capabilities, a theoretical model was developed by using established particle composite models in conjunction with a shear lag structural mechanics model for CLACS. Granular composite discs of lead zirconate titanate particles in an epoxy matrix were manufactured at a 50% volume fraction and structured by DEP, if applicable. CLACS were manufactured using ten composite discs and two compliant layer thicknesses. The stacks were electromechanically tested by varying load, frequency, and resistance. Experimental results showed an increase in power amplification with DEP structured discs and compliant layers. In addition, the theoretical model accurately predicts power production for both 0-3 and 1-3 CLACS at low frequencies. DEP structured particle composite CLACS can provide a method of energy harvesting for devices in remote locations, especially in low frequency high strain environments. Future work could continue the development of piezoelectric particle composite CLACS for use in intramedullary nails. Such studies would evaluate the performance of ring shaped piezoelectric composites, develop theoretical understanding for ring shaped CLACS, investigate fatigue strength of piezoelectric particle composites, and evaluate impact strength of particle composite CLACS as compared to ceramic CLACS. Lastly, overall improvements to particle composite manufacturing methods to reduce variability could be investigated

THE DEVELOPMENT OF NORMAL PREHENSION

O presente trabalho apresenta alguns aspectos importantes do desenvolvimento sensório-motor normal da preensão relacionados com a evolução desta,  partir do bebê recém-nascido. São dadas idéias de como desenvolver a preensão através de vários tipos de objetos, na sequência do amadurecimento neurológico da criança até 12 meses de idade.This article shows some important aspects of lhe normal sensory-motor development of prehension related lo lhe prehensive evo~ution, starting with newborn babies. Some ideas of how lo develop prehension using different kin~s of objects aredescribed, respecting the neurological maturation of the child until 12 months of age

Autism spectrum disorder

Background: Autism spectrum disorder is a complex heterogeneous condition that is characterized by impairments in social interaction, communication, and behavior which mostly co-exists with several comorbidities. The current prevalence of autism spectrum disorder in the general population is estimated to be 1 in 68 children. Despite significant advances in research and multiple treatment options, the management of the disease remains poor. Although there are governmental services and few non-governmental organizations working for individuals with autism, there is no official data available regarding the incidence and prevalence of autism in Malta Methods: This study focuses on the need of increasing awareness for autism spectrum disorder in Malta among the general public and health care professionals which would benefit a better understanding of the disorder for early diagnosis and more effective treatments. This was best provided through questionnaires. Results: Our survey revealed that only a limited percentage of the Maltese population had some knowledge about the symptoms, age of onset, potential causes of the disease and treatment options for autism. Conclusion: There is an immense need for improvement regarding the awareness of autism in Malta to estimate the exact burden of the disorder and make the latest diagnostic and treatment options available to the people living with this disease on the island