3,279 research outputs found
Developing Multimodal Spectroscopic Imaging Techniques to Study Metal Dyshomeostasis and Altered Brain Biochemistry During Ageing
Cognitive decline and neurodegenerative diseases such as Alzheimer’s disease, pose significant concerns for the ageing population. Increased understanding of the biochemical processes that occur during ageing, may help to reveal pathways for prevention or treatment. There has been interest in the potential role that metal dis-homeostasis plays during ageing and cognitive decline, so this thesis has focussed on developing and applying spectroscopic methods to study metal dis-homeostasis and concomitant biochemical changes during ageing
An automated high-content screening image analysis pipeline for the identification of selective autophagic inducers in human cancer cell lines.
Automated image processing is a critical and often rate-limiting step in high-content screening (HCS) workflows. The authors describe an open-source imaging-statistical framework with emphasis on segmentation to identify novel selective pharmacological inducers of autophagy. They screened a human alveolar cancer cell line and evaluated images by both local adaptive and global segmentation. At an individual cell level, region-growing segmentation was compared with histogram-derived segmentation. The histogram approach allowed segmentation of a sporadic-pattern foreground and hence the attainment of pixel-level precision. Single-cell phenotypic features were measured and reduced after assessing assay quality control. Hit compounds selected by machine learning corresponded well to the subjective threshold-based hits determined by expert analysis. Histogram-derived segmentation displayed robustness against image noise, a factor adversely affecting region growing segmentation
Biophysical Characteristics of Lipid-Induced Aβ Oligomers Correlate to Distinctive Phenotypes In Transgenic Mice
Alzheimer\u27s disease (AD) is a progressive neurodegenerative disorder that affects cognition and memory. Recent advances have helped identify many clinical sub-types in AD. Mounting evidence point toward structural polymorphism among fibrillar aggregates of amyloid-β (Aβ) to being responsible for the phenotypes and clinical manifestations. In the emerging paradigm of polymorphism and prion-like propagation of aggregates in AD, the role of low molecular weight soluble oligomers, which are long known to be the primary toxic agents, in effecting phenotypes remains inconspicuous. In this study, we present the characterization of three soluble oligomers of Aβ42, namely 14LPOs, 16LPOs, and GM1Os with discreet biophysical and biochemical properties generated using lysophosphatidyl glycerols and GM1 gangliosides. The results indicate that the oligomers share some biophysical similarities but display distinctive differences with GM1Os. Unlike the other two, GM1Os were observed to be complexed with the lipid upon isolation. It also differs mainly in detection by conformation-sensitive dyes and conformation-specific antibodies, temperature and enzymatic stability, and in the ability to propagate morphologically-distinct fibrils. GM1Os also show distinguishable biochemical behavior with pronounced neuronal toxicity. Furthermore, all the oligomers induce cerebral amyloid angiopathy (CAA) and plaque burden in transgenic AD mice, which seems to be a consistent feature among all lipid-derived oligomers, but 16LPOs and GM1Os displayed significantly higher effect than the others. These results establish a correlation between molecular features of Aβ42 oligomers and their distinguishable effects in transgenic AD mice attuned by lipid characteristics, and therefore help bridge the knowledge gap in understanding how oligomer conformers could elicit AD phenotypes
The impact of aerobic exercise on brain's white matter integrity in the Alzheimer's disease and the aging population
The brain is the most complex organ in the body. Currently, its complicated functionality has not been fully understood. However, in the last decades an exponential growth on research publications emerged thanks to the use of in-vivo brain imaging techniques. One of these techniques pioneered for medical use in the early 1970s was known as nuclear magnetic resonance imaging based (now called magnetic resonance imaging [MRI]). Nowadays, the advances of MRI technology not only allowed us to characterize volumetric changes in specific brain structures but now we could identify different patterns of activation (e.g. functional MRI) or changes in structural brain connectivity (e.g. diffusion MRI). One of the benefits of using these techniques is that we could investigate changes that occur in disease-specific cohorts such as in the case of Alzheimer’s disease (AD), a neurodegenerative disease that affects mainly older populations. This disease has been known for over a century and even though great advances in technology and pharmacology have occurred, currently there is no cure for the disease. Hence, in this work I decided to investigate whether aerobic exercise, an emerging alternative method to pharmacological treatments, might provide neuroprotective effects to slow down the evident brain deterioration of AD using novel in-vivo diffusion imaging techniques. Previous reports in animal and human studies have supported these exercise-related neuro-protective mechanisms. Concurrently in AD participants, increased brain volumes have been positively associated with higher cardiorespiratory fitness levels, a direct marker of sustained physical activity and increased exercise. Thus, the goal of this work is to investigate further whether exercise influences the brain using structural connectivity analyses and novel diffusion imaging techniques that go beyond volumetric characterization. The approach I chose to present this work combined two important aspects of the investigation. First, I introduced important concepts based on the neuro-scientific work in relation to Alzheimer’s diseases, in-vivo imaging, and exercise physiology (Chapter 1). Secondly, I tried to describe in simple mathematics the physics of this novel diffusion imaging technique (Chapter 2) and supported a tract-specific diffusion imaging processing methodology (Chapter 3 and 4). Consequently, the later chapters combined both aspects of this investigation in a manuscript format (Chapter 5-8). Finally, I summarized my findings, include recommendations for similar studies, described future work, and stated a final conclusion of this work (Chapter 9)
AAV-mediated expression of secreted and transmembrane αKlotho isoforms rescues relevant aging hallmarks in senescent SAMP8 mice
Senescence represents a stage in life associated with elevated incidence of morbidity and increased risk of mortality due to the accumulation of molecular alterations and tissue dysfunction, promoting a decrease in the organism's protective systems. Thus, aging presents molecular and biological hallmarks, which include chronic inflammation, epigenetic alterations, neuronal dysfunction, and worsening of physical status. In this context, we explored the AAV9-mediated expression of the two main isoforms of the aging-protective factor Klotho (KL) as a strategy to prevent these general age-related features using the senescence-accelerated mouse prone 8 (SAMP8) model. Both secreted and transmembrane KL isoforms improved cognitive performance, physical state parameters, and different molecular variables associated with aging. Epigenetic landscape was recovered for the analyzed global markers DNA methylation (5-mC), hydroxymethylation (5-hmC), and restoration occurred in the acetylation levels of H3 and H4. Gene expression of pro- and anti-inflammatory mediators in central nervous system such as TNF-α and IL-10, respectively, had improved levels, which were comparable to the senescence-accelerated-mouse resistant 1 (SAMR1) healthy control. Additionally, this improvement in neuroinflammation was supported by changes in the histological markers Iba1, GFAP, and SA β-gal. Furthermore, bone tissue structural variables, especially altered during senescence, recovered in SAMP8 mice to SAMR1 control values after treatment with both KL isoforms. This work presents evidence of the beneficial pleiotropic role of Klotho as an anti-aging therapy as well as new specific functions of the KL isoforms for the epigenetic regulation and aged bone structure alteration in an aging mouse model. Intraventricular administration of AAV vectors expressing secreted and transmembrane Klotho isoforms, rescued accelerated aging phenotype of SAMP8 mice. An improvement in cognitive and physical performance, recovery of epigenetic, inflammatory and senescence markers, as well as structural changes in long bones of these mice was detected
AAV-mediated expression of secreted and transmembrane αKlotho isoforms rescues relevant aging hallmarks in senescent SAMP8 mice
Senescence represents a stage in life associated with elevated incidence of morbidity and increased risk of mortality due to the accumulation of molecular alterations and tissue dysfunction, promoting a decrease in the organism's protective systems. Thus, aging presents molecular and biological hallmarks, which include chronic inflammation, epigenetic alterations, neuronal dysfunction, and worsening of physical status. In this context, we explored the AAV9-mediated expression of the two main isoforms of the aging-protective factor Klotho (KL) as a strategy to prevent these general age-related features using the senescence-accelerated mouse prone 8 (SAMP8) model. Both secreted and transmembrane KL isoforms improved cognitive performance, physical state parameters, and different molecular variables associated with aging. Epigenetic landscape was recovered for the analyzed global markers DNA methylation (5-mC), hydroxymethylation (5-hmC), and restoration occurred in the acetylation levels of H3 and H4. Gene expression of pro- and anti-inflammatory mediators in central nervous system such as TNF-α and IL-10, respectively, had improved levels, which were comparable to the senescence-accelerated-mouse resistant 1 (SAMR1) healthy control. Additionally, this improvement in neuroinflammation was supported by changes in the histological markers Iba1, GFAP, and SA β-gal. Furthermore, bone tissue structural variables, especially altered during senescence, recovered in SAMP8 mice to SAMR1 control values after treatment with both KL isoforms. This work presents evidence of the beneficial pleiotropic role of Klotho as an anti-aging therapy as well as new specific functions of the KL isoforms for the epigenetic regulation and aged bone structure alteration in an aging mouse model
Evaluation of machine learning algorithms for treatment outcome prediction in patients with epilepsy based on structural connectome data
The objective of this study is to evaluate machine learning algorithms aimed at predicting surgical treatment outcomes in groups of patients with temporal lobe epilepsy (TLE) using only the structural brain connectome. Specifically, the brain connectome is reconstructed using white matter fiber tracts from presurgical diffusion tensor imaging. To achieve our objective, a two-stage connectome-based prediction framework is developed that gradually selects a small number of abnormal network connections that contribute to the surgical treatment outcome, and in each stage a linear kernel operation is used to further improve the accuracy of the learned classifier. Using a 10-fold cross validation strategy, the first stage in the connectome-based framework is able to separate patients with TLE from normal controls with 80% accuracy, and second stage in the connectome-based framework is able to correctly predict the surgical treatment outcome of patients with TLE with 70% accuracy. Compared to existing state-of-the-art methods that use VBM data, the proposed two-stage connectome-based prediction framework is a suitable alternative with comparable prediction performance. Our results additionally show that machine learning algorithms that exclusively use structural connectome data can predict treatment outcomes in epilepsy with similar accuracy compared with "expert-based" clinical decision. In summary, using the unprecedented information provided in the brain connectome, machine learning algorithms may uncover pathological changes in brain network organization and improve outcome forecasting in the context of epilepsy
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Foreign body responses in central nervous system mimic natural wound responses and alter biomaterial functions
Biomaterials hold promise for diverse therapeutic applications in the central nervous system (CNS). Little is known about molecular factors that determine CNS foreign body responses (FBRs) in vivo , or about how such responses influence biomaterial function. Here, we probed these factors using a platform of injectable hydrogels readily modified to present interfaces with different representative physiochemical properties to host cells. We show that biomaterial FBRs mimic specialized multicellular CNS wound responses not present in peripheral tissues, which serve to isolate damaged neural tissue and restore barrier functions. Moreover, we found that the nature and intensity of CNS FBRs are determined by definable properties. For example, cationic, anionic or nonionic interfaces with CNS cells elicit quantifiably different levels of stromal cell infiltration, inflammation, neural damage and amyloid production. The nature and intensity of FBRs significantly influenced hydrogel resorption and molecular delivery functions. These results characterize specific molecular mechanisms that drive FBRs in the CNS and have important implications for developing effective biomaterials for CNS applications
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