Healthy memory aging - the benefits of regular daily activities increase with age.

As the number of older adults increases, so does the pressure on health care systems due to age-related disorders. Attempts to reduce cognitive decline have focused on individual interventions such as exercise or diet, with limited success. This study adopted a different approach by investigating the impact of combined daily activities on memory decline.

Performance comparison of linear and non-linear feature selection methods for the analysis of large survey datasets.

Large survey databases for aging-related analysis are often examined to discover key factors that affect a dependent variable of interest. Typically, this analysis is performed with methods assuming linear dependencies between variables. Such assumptions however do not hold in many cases, wherein data are linked by way of non-linear dependencies.

Characterization of the Molecular Mechanisms Underlying the Chronic Phase of Stroke in a Cynomolgus Monkey Model of Induced Cerebral Ischemia.

Stroke is one of the main causes of mortality and long-term disability worldwide. The pathophysiological mechanisms underlying this disease are not well understood, particularly in the chronic phase after the initial ischemic episode. In this study, a Macaca fascicularis stroke model consisting of two sample groups, as determined by MRI-quantified infarct volumes as a measure of the stroke severity 28 days after the ischemic episode, was evaluated using qualitative and quantitative proteomics analyses.

Quantitative proteomic analysis reveals potential diagnostic markers and pathways involved in pathogenesis of renal cell carcinoma.

There are no serum biomarkers for the accurate diagnosis of clear cell renal cell carcinoma (ccRCC). Diagnosis and decision of nephrectomy rely on imaging which is not always accurate. Non-invasive diagnostic biomarkers are urgently required.

Role of moesin in hyaluronan induced cell migration in glioblastoma multiforme.

Background: A major barrier to effective treatment of glioblastoma multiforme (GBM) is the invasion of glioma cells into the brain parenchyma rendering local therapies such as surgery and radiation therapy ineffective. GBM patients with such highly invasive and infiltrative tumors have poor prognosis with a median survival time of only about a year. However, the mechanisms leading to increased cell migration, invasion and diffused behavior of glioma cells are still poorly understood.

Exploring age-related changes in dynamical non-stationarity in electroencephalographic signals during early adolescence.

Dynamics of brain signals such as electroencephalogram (EEG) can be characterized as a sequence of quasi-stable patterns. Such patterns in the brain signals can be associated with coordinated neural oscillations, which can be modeled by non-linear systems. Further, these patterns can be quantified through dynamical non-stationarity based on detection of qualitative changes in the state of the systems underlying the observed brain signals.

Confounding effects of phase delays on causality estimation.

Linear and non-linear techniques for inferring causal relations between the brain signals representing the underlying neuronal systems have become a powerful tool to extract the connectivity patterns in the brain. Typically these tools employ the idea of Granger causality, which is ultimately based on the temporal precedence between the signals. At the same time, phase synchronization between coupled neural ensembles is considered a mechanism implemented in the brain to integrate relevant neuronal ensembles to perform a cognitive or perceptual task.

Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance.

Metastatic renal cell carcinoma (RCC) is one of the most treatment-resistant malignancies, and patients have a dismal prognosis, with a <10% five-year survival rate. The identification of markers that can predict the potential for metastases will have a great effect in improving patient outcomes. In this study, we used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify proteins that are differentially expressed in metastatic and primary RCC.

Empirical and theoretical aspects of generation and transfer of information in a neuromagnetic source network.

Variability in source dynamics across the sources in an activated network may be indicative of how the information is processed within a network. Information-theoretic tools allow one not only to characterize local brain dynamics but also to describe interactions between distributed brain activity. This study follows such a framework and explores the relations between signal variability and asymmetry in mutual interdependencies in a data-driven pipeline of non-linear analysis of neuromagnetic sources reconstructed from human magnetoencephalographic (MEG) data collected as a reaction to a face recognition task.

Identification of differentially regulated secretome components during skeletal myogenesis.

Myogenesis is a well-characterized program of cellular differentiation that is exquisitely sensitive to the extracellular milieu. Systematic characterization of the myogenic secretome (i.e.

Identification of novel molecular targets for endometrial cancer using a drill-down LC-MS/MS approach with iTRAQ.

Background: The number of patients with endometrial carcinoma (EmCa) with advanced stage or high histological grade is increasing and prognosis has not improved for over the last decade. There is an urgent need for the discovery of novel molecular targets for diagnosis, prognosis and treatment of EmCa, which will have the potential to improve the clinical strategy and outcome of this disease.

Methodology And Results: We used a "drill-down" proteomics approach to facilitate the identification of novel molecular targets for diagnosis, prognosis and/or therapeutic intervention for EmCa.

The extent and effects of peptide sequence scrambling via formation of macrocyclic B ions in model proteins.

The extent and effects of sequence scrambling in peptide ions during tandem mass spectrometry (MS/MS) have been examined using tryptic peptides from model proteins. Sequence-scrambled b ions appeared in about 35% of 43 tryptic peptides examined under MS/MS conditions. In general, these ions had relatively low abundances with averages of 8% and 16%, depending on the instrumentation used.

mTRAQ-based quantification of potential endometrial carcinoma biomarkers from archived formalin-fixed paraffin-embedded tissues.

Formalin-fixed paraffin-embedded (FFPE) tissues are the primary and preferred medium for archiving patients' samples. Here we demonstrate relative quantifications of protein biomarkers in extracts of laser microdissected epithelial cells from FFPE endometrial carcinoma tissues versus those from normal proliferative endometria by means of targeted proteomic analyses using LC-multiple reaction monitoring (MRM) MS with MRM Tags for Relative and Absolute Quantitation (mTRAQ) labeling. Comparable results of differential expressions for pyruvate kinase isoform M2 (PK-M2) and polymeric Ig receptor were observed between analyses on laser microdissected epithelial cells from FFPE tissues and corresponding homogenates from frozen tissues of the same individuals that had previously been analyzed and reported.

Complexity analysis of source activity underlying the neuromagnetic somatosensory steady-state response.

Using the notion of complexity and synchrony, this study presents a data-driven pipeline of nonlinear analysis of neuromagnetic sources reconstructed from human magnetoencephalographic (MEG) data collected in reaction to vibrostimulation of the right index finger. The dynamics of MEG source activity was reconstructed with synthetic aperture magnetometry (SAM) beam-forming technique. Considering brain as a complex system, we applied complexity-based tools to identify brain areas with dynamic patterns that remain regular across repeated stimulus presentations, and to characterize their synchronized behavior.

Confounding effects of indirect connections on causality estimation.

Addressing the issue of effective connectivity, this study focuses on effects of indirect connections on inferring stable causal relations: partial transfer entropy. We introduce a Granger causality measure based on a multivariate version of transfer entropy. The statistic takes into account the influence of the rest of the network (environment) on observed coupling between two given nodes.

Inferring neural activity from BOLD signals through nonlinear optimization.

The blood oxygen level-dependent (BOLD) fMRI signal does not measure neuronal activity directly. This fact is a key concern for interpreting functional imaging data based on BOLD. Mathematical models describing the path from neural activity to the BOLD response allow us to numerically solve the inverse problem of estimating the timing and amplitude of the neuronal activity underlying the BOLD signal.