Developing multidimensional metrics for evaluating paediatric neurodevelopmental disorders

Healthy brain functioning depends on efficient communication of information between brain regions, forming complex networks. By quantifying synchronisation between brain regions, a functionally connected brain network can be articulated. In neurodevelopmental disorders, where diagnosis is based on measures of behaviour and tasks, a measure of the underlying biological mechanisms holds promise as a potential clinical tool. Graph theory provides a tool for investigating the neural correlates of neuropsychiatric disorders, where there is disruption of efficient communication within and between brain networks. This research aimed to use recent conceptualisation of graph theory, along with measures of behaviour and cognitive functioning, to increase understanding of the neurobiological risk factors of atypical development. Using magnetoencephalography to investigate frequency-specific temporal dynamics at rest, the research aimed to identify potential biological markers derived from sensor-level whole-brain functional connectivity. Whilst graph theory has proved valuable for insight into network efficiency, its application is hampered by two limitations. First, its measures have hardly been validated in MEG studies, and second, graph measures have been shown to depend on methodological assumptions that restrict direct network comparisons. The first experimental study (Chapter 3) addressed the first limitation by examining the reproducibility of graph-based functional connectivity and network parameters in healthy adult volunteers. Subsequent chapters addressed the second limitation through adapted minimum spanning tree (a network analysis approach that allows for unbiased group comparisons) along with graph network tools that had been shown in Chapter 3 to be highly reproducible. Network topologies were modelled in healthy development (Chapter 4), and atypical neurodevelopment (Chapters 5 and 6). The results provided support to the proposition that measures of network organisation, derived from sensor-space MEG data, offer insights helping to unravel the biological basis of typical brain maturation and neurodevelopmental conditions, with the possibility of future clinical utility.

Facial affect processing inbipolar disorder:a magnetoencephalography study

Background: Identifying biological markers to aid diagnosis of bipolar disorder (BD) is critically important. To be considered a possible biological marker, neural patterns in BD should be discriminant from those in healthy individuals (HI). We examined patterns of neuromagnetic responses revealed by magnetoencephalography (MEG) during implicit emotion-processing using emotional (happy, fearful, sad) and neutral facial expressions, in sixteen BD and sixteen age- and gender-matched healthy individuals. Methods: Neuromagnetic data were recorded using a 306-channel whole-head MEG ELEKTA Neuromag System, and preprocessed using Signal Space Separation as implemented in MaxFilter (ELEKTA). Custom Matlab programs removed EOG and ECG signals from filtered MEG data, and computed means of epoched data (0-250ms, 250-500ms, 500-750ms). A generalized linear model with three factors (individual, emotion intensity and time) compared BD and HI. A principal component analysis of normalized mean channel data in selected brain regions identified principal components that explained 95% of data variation. These components were used in a quadratic support vector machine (SVM) pattern classifier. SVM classifier performance was assessed using the leave-one-out approach. Results: BD and HI showed significantly different patterns of activation for 0-250ms within both left occipital and temporal regions, specifically for neutral facial expressions. PCA analysis revealed significant differences between BD and HI for mild fearful, happy, and sad facial expressions within 250-500ms. SVM quadratic classifier showed greatest accuracy (84%) and sensitivity (92%) for neutral faces, in left occipital regions within 500-750ms. Conclusions: MEG responses may be used in the search for disease specific neural markers.

Protemic characterization of peripheral blood mononuclear cells

Peripheral blood mononuclear cells (PBMCs) play quite diverse and important roles in monitoring immune homeostasis. Thus, these subset of blood cells may provide access to potential physiological relevant biomolecules, namely proteins. For this reason, PBMCs represent a promising biological sample in scientific research, particularly as a source of potential biological markers discovery of the most diverse diseases. Prior studies of proteomic characterization of PBMCs from healthy individuals lack either the identification of a large number of proteins or its quantification in a way that is compatible with the search of potential biomarker candidates. Therefore, this study aimed to provide a comprehensive PBMCs proteome characterisation as well as to create a SWATH library. It was also evaluated if by using the BD Vacutainer® CPT™ tubes for PBMCs isolation, it would be possible to identify a larger number of immunologically relevant proteins in comparison to plasma samples. The enrichment test assay revealed that it is possible to identify more immune-related proteins from isolated PBMCs than from plasma. Moreover, the majority of the quantified proteins with an “immune system” GO term assigned is present in higher amounts in PBMCs samples. 2D LC-MS/MS proved to be the best approach to use in qualitative analysis of PBMCs and in the construction of a SWATH library, since it resulted in an increase of both identified and quantified proteins (66.3% and 16.9%, respectively) in comparison to 1D LC-MS/MS. A total of 2071 proteins were identified and it was possible to quantify 922 different proteins among six distinct samples. From these proteins, 445 were commom between all individuals. In conclusion, this work provides a comprehensive PBMCs proteome dataset that will be useful in further studies that focus on the search for potential biological markers of various pathologies in these cells. Additionally, SWATH-MS proved to be a reproducible and effective acquisition method to quantify PBMCs proteins.

Linfócitos T : uma análise do perfil diferencial da expressão gênica na imunorregulação

Tese (doutorado)—Universidade de Brasília, Faculdade de Medicina, Pós-Graduação em Patologia Molecular, 2016.

Procalcitonin Biomarker Kinetics to Predict Multiorgan Dysfunction Syndrome in Children With Sepsis and Systemic Inflammatory Response Syndrome

Background: Procalcitonin (PCT) kinetics is a good prognosis marker in infectious diseases, but few studies of children sepsis have been performed. Objectives: The aim of our study was to examine kinetics of procalcitonin, to evaluate its relationship with severity and to analyze its usefulness in the prediction of multiorgan dysfunction syndrome (MODS). Patients and Methods: Prospective observational study in an 8-bed pediatric intensive care unit of a university hospital. Sixty-two children aged 0-19 years with systemic inflammatory response syndrome or septic states. The degree of severity was evaluated according pediatric logistic organ dysfunction (PELOD) score. Blood tests to determine levels of PCT were taken if the patients had the criteria of systemic inflammatory response syndrome or sepsis. The serum to determine levels of PCT in control group has been taken from patients undergoing elective surgery. Results: Higher values of PCT were identified in patients with PELOD score 12 and more compared to those with PELOD < 12 (P = 0.016). Similarly, higher PCT values were found in patients who developed MODS in contrast to those without MODS (P = 0.011). According to ROC analysis cut-off value of 4.05 ng/mL was found to best discriminate patients with PELOD < 12 and PELOD ≥ 12 with AUC = 0.675 (P = 0.035). Effect of procalcitonin levels on mortality was not demonstrated. Conclusions: Levels of procalcitonin from day 1 to day 5 are related to the severity and multiorgan dysfunction syndrome in children.

Integrated Proteomics Identified Up-regulated Focal Adhesion-mediated Proteins In Human Squamous Cell Carcinoma In An Orthotopic Murine Model.

Understanding the molecular mechanisms of oral carcinogenesis will yield important advances in diagnostics, prognostics, effective treatment, and outcome of oral cancer. Hence, in this study we have investigated the proteomic and peptidomic profiles by combining an orthotopic murine model of oral squamous cell carcinoma (OSCC), mass spectrometry-based proteomics and biological network analysis. Our results indicated the up-regulation of proteins involved in actin cytoskeleton organization and cell-cell junction assembly events and their expression was validated in human OSCC tissues. In addition, the functional relevance of talin-1 in OSCC adhesion, migration and invasion was demonstrated. Taken together, this study identified specific processes deregulated in oral cancer and provided novel refined OSCC-targeting molecules.

Whole Cortical And Default Mode Network Mean Functional Connectivity As Potential Biomarkers For Mild Alzheimer's Disease.

The search for an Alzheimer's disease (AD) biomarker is one of the most relevant contemporary research topics due to the high prevalence and social costs of the disease. Functional connectivity (FC) of the default mode network (DMN) is a plausible candidate for such a biomarker. We evaluated 22 patients with mild AD and 26 age- and gender-matched healthy controls. All subjects underwent resting functional magnetic resonance imaging (fMRI) in a 3.0 T scanner. To identify the DMN, seed-based FC of the posterior cingulate was calculated. We also measured the sensitivity/specificity of the method, and verified a correlation with cognitive performance. We found a significant difference between patients with mild AD and controls in average z-scores: DMN, whole cortical positive (WCP) and absolute values. DMN individual values showed a sensitivity of 77.3% and specificity of 70%. DMN and WCP values were correlated to global cognition and episodic memory performance. We showed that individual measures of DMN connectivity could be considered a promising method to differentiate AD, even at an early phase, from normal aging. Further studies with larger numbers of participants, as well as validation of normal values, are needed for more definitive conclusions.

Microfluidic Paper-based Devices For Bioanalytical Applications.

Paper has become increasingly recognized as a very interesting substrate for the construction of microfluidic devices, with potential application in a variety of areas, including health diagnosis, environmental monitoring, immunoassays and food safety. The aim of this review is to present a short history of analytical systems constructed from paper, summarize the main advantages and disadvantages of fabrication techniques, exploit alternative methods of detection such as colorimetric, electrochemical, photoelectrochemical, chemiluminescence and electrochemiluminescence, as well as to take a closer look at the novel achievements in the field of bioanalysis published during the last 2 years. Finally, the future trends for production of such devices are discussed.

PAH biomarkers for human health risk assessment: a review of the state-of-the-art

Polycyclic aromatic hydrocarbons (PAH) are widely distributed in the environment, and some are carcinogenic to human beings. The study of biomarkers has helped clarify the nature and magnitude of the human health risks posed by such substances. This article provides a review of the state-of-the-art on PAH biomarkers for human health risk assessment and also discusses their applicability within the context of environmental management in Brazil. The article discusses the methodologies for determination of some biomarkers such as 1-hydroxypyrene and PAH-DNA adducts. Cytogenetic markers, frequency of chromosomal aberrations, and micronucleus induction were considered for the evaluation of cancer risk. The current stage of studies on validation of such biomarkers was also approached.