15 research outputs found

    3D dendritic spine segmentation using nonparametric shape priors (3B dendritik dikenlerin parametrik olmayan şekil ön bilgisi kullanılarak bölütlenmesi)

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    Analyzing morphological and structural changes of dendritic spines in 2-photon microscopy images in time is important for neuroscience researchers. Correct segmentation of dendritic spines is an important step of developing robust and reliable automatic tools for such analysis. In this paper, we propose an approach for segmentation of 3D dendritic spines using nonparametric shape priors. The proposed method learns the prior distribution of shapes through Parzen density estimation on the training set of shapes. Then, the posterior distribution of shapes is obtained by combining the learned prior distribution with a data term in a Bayesian framework. Finally, the segmentation result that maximizes the posterior is found using active contours. Experimental results demonstrate that using nonparametric shape priors leads to better 3D dendritic spine segmentation results

    Statistical Modeling and Inference for Genomics: Data Integration, Shrinkage and Network Reconstruction

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    Vaart, A.W. van der [Promotor]Wiel, M.A. van de [Promotor

    The Deep Evolution of Ecdysozoa

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    Ecdysozoa (moulting animals) comprises the protostome Phyla Arthropoda, Kinorhyncha, Loricifera, Nematoda, Nematomorpha, Onychophora, Priapulida and Tardigrada, but our precise understanding of the phylogenetic relationships between these is disputed. Ecdysozoa is an extremely ancient clade that originated in the oceans, and ecdysozoans remain major components of modern marine and terrestrial ecosystems, including the most diverse and abundant of all animal Phyla (Arthropoda and Nematoda respectively). In this thesis, I explore the phylogenetic relationships and divergence times of fossil and extant ecdysozoans in order to address several outstanding issues in the early evolutionary history and palaeobiology of Ecdysozoa, employing data from fossils and molecular sequences. First, the phylogenetic relationships of the eight ecdysozoan phyla was tested using Bayesian models from a molecular matrix containing newly sequenced taxa from Nematomorpha, Priapulida and Tardigrada. Analyses retrieved a monophyletic Scalidophora (Kinorhyncha, Loricifera and Priapulida) which in turn is sister-group to a clade comprising Nematoida (Nematoda and Nematomorpha) and Panarthropoda (Arthropoda, Onychophora and Tardigrada) – this is named Cryptovermes nov. An improved set of fossil calibrations was compiled and used to infer the divergence times of ecdysozoans under a range of alternative parameters. Crown-group Ecdysozoa diverged in the Ediacaran Period between 636 – 578 Ma, at least 23 million years before the oldest potential fossil evidence of ecdysozoans in the late Ediacaran (<556 Ma). Arthropods show more precision and less incongruence with the fossil record compared to other ecdysozoan phyla. Several vermiform (worm-like) fossils from the exceptionally preserved Cambrian Stage 3 Chengjiang Biota of Yunnan Province, south-western China were investigated to address the origin of Ecdysozoa and Panarthropoda in a morphological phylogenetic context. Phylogenetic analyses placed Acosmia maotiania in stem-group Ecdysozoa. Ancestral character state reconstructions revealed the similarities and contrasts between the stem-group ecdysozoan A. maotiania and a reconstruction of the common ancestor of crown-group Ecdysozoa. This reveals that pharyngeal teeth and circumoral armament are likely to be derived traits of the ecdysozoan crown-group, and may have 3 influenced the diversification of crown-group ecdysozoans – perhaps facilitating a change in feeding style (e.g. predation). The cycloneuralians Tabelliscolex hexagonus, Cricocosmia jinningensis and Mafangscolex yunnanensis (=Palaeoscolecidomorpha nov.) share several characters in common with lobopodian panarthropods. This includes paired, seriated ventral trunk structures, corresponding (in T. hexagonus and C. jinningensis) to seriated lateral/dorsolateral trunk sclerites with a net-like microstructure. However, phylogenetic analyses did not retrieve a relationship between palaeoscolecidomorphs and panarthropods, indicating that this style of morphological seriation may have multiple origins within Ecdysozoa. The lobopodian Facivermis yunnanicus is rejected as a model system to understand the acquisition a segmental bodyplan with paired appendages in Panarthropoda. Phylogenies generated here indicate that F. yunnanicus’ worm-like appearance is secondarily adapted from more typical lobopodian ancestors, as a result of adaptation to a specialised tube-dwelling suspension-feeding ecology. Finally, the phylogenetic relationships and divergence times of chelicerate arthropod groups were inferred, and interpreted in the context of arthropod terrestrialization. Phylogenetic analysis of a highly complete matrix of slowly evolving genes supports the monophyly of arachnids. Furthermore, it is parsimonious that the common ancestor of scorpions and other air-breathing arachnids was terrestrial – or at least amphibious – if arachnids are a monophyletic group. Molecular clocks estimate that arachnids diverged in the Cambrian or Early Ordovician, though body fossils of these arthropods are absent until the Silurian which supports the hypothesis of paleontologically cryptic early terrestrial biosphere – mirrored by the molecular and fossil records of myriapods and land plants. Scorpions are the oldest extant terrestrial chelicerate lineage in the fossil record, but is unclear whether the earliest Silurian examples were marine, terrestrial, or even secondarily marine in life

    Aspects of Statistical Analysis of Spatial Point Patterns

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    Deep Learning in Medical Image Analysis

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    The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis

    Serotonergic modulation of the ventral pallidum by 5HT1A, 5HT5A, 5HT7 AND 5HT2C receptors

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    Introduction: Serotonin's involvement in reward processing is controversial. The large number of serotonin receptor sub-types and their individual and unique contributions have been difficult to dissect out, yet understanding how specific serotonin receptor sub-types contribute to its effects on areas associated with reward processing is an essential step. Methods: The current study used multi-electrode arrays and acute slice preparations to examine the effects of serotonin on ventral pallidum (VP) neurons. Approach for statistical analysis: extracellular recordings were spike sorted using template matching and principal components analysis, Consecutive inter-spike intervals were then compared over periods of 1200 seconds for each treatment condition using a student’s t test. Results and conclusions: Our data suggests that excitatory responses to serotonin application are pre-synaptic in origin as blocking synaptic transmission with low-calcium aCSF abolished these responses. Our data also suggests that 5HT1a, 5HT5a and 5HT7 receptors contribute to this effect, potentially forming an oligomeric complex, as 5HT1a antagonists completely abolished excitatory responses to serotonin application, while 5HT5a and 5HT7 only reduced the magnitude of excitatory responses to serotonin. 5HT2c receptors were the only serotonin receptor sub-type tested that elicited inhibitory responses to serotonin application in the VP. These findings, combined with our previous data outlining the mechanisms underpinning dopamine's effects in the VP, provide key information, which will allow future research to fully examine the interplay between serotonin and dopamine in the VP. Investigation of dopamine and serotonins interaction may provide vital insights into our understanding of the VP's involvement in reward processing. It may also contribute to our understanding of how drugs of abuse, such as cocaine, may hijack these mechanisms in the VP resulting in sensitization to drugs of abuse

    Investigating cerebrovascular health and functional plasticity using quantitative FMRI

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    A healthy cerebrovasculature is necessary to maintain optimal levels of blood flow and oxygen metabolism required for overall brain health. Cerebrovascular health also promotes functional plasticity which facilitates lifelong adaptation with experience and recovery following injury. In diseases such as Multiple Sclerosis (MS), there is known vascular and metabolic dysfunction, however, patients retain variable levels of functional plasticity which aids recovery following acute bouts of inflammation. Physical exercise interventions, aimed at improving cerebral blood flow and oxygen metabolism, present a potential avenue for improving patient outcomes and slowing the progression of disability. However, there is a lack of mechanistic understanding of i) brain energetic processes underlying plasticity and ii) how aerobic fitness (AF), which is linked to increased brain plasticity, benefits brain vascular and metabolic function. The work presented in this thesis uses arterial spin labelling (ASL) functional magnetic resonance imaging (fMRI) to quantitatively characterise the vascular and metabolic processes associated with functional brain plasticity, and the effects of AF on the brain’s functional capacity in healthy adults. This thesis begins with an overview of the neurobiological processes of interest and fMRI techniques that can quantify these processes. Next, a comparison of common ASL acquisition and analysis procedures is made to establish the most appropriate methods for subsequent experimental work. Chapters 4 and 5 investigate the effects of AF on cerebrovascular function in healthy adults. Chapter 6 then gives an overview of existing functional motor plasticity work, before Chapters 7 and 8 which quantify vascular and metabolic adaptations following motor training in the healthy brain. Chapter 9, presents preliminary work in an MS cohort, applying methods from previous chapters to quantify vascular and metabolic differences between patients and controls. The general discussion in Chapter 10 summarises the main findings and contributions of this work and key areas for future research are outlined

    Effects of Diversity and Neuropsychological Performance in an NFL Cohort

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    Objective: The aim of this study was to examine the effect of ethnicity on neuropsychological test performance by comparing scores of white and black former NFL athletes on each subtest of the WMS. Participants and Methods: Data was derived from a de-identified database in South Florida consisting of 63 former NFL white (n=28, 44.4%) and black (n=35, 55.6%) athletes (Mage= 50.38; SD= 11.57). Participants completed the following subtests of the WMS: Logical Memory I and II, Verbal Paired Associates I and II, and Visual Reproduction I and II. Results: A One-Way ANOVA yielded significant effect between ethnicity and performance on several subtests from the WMS-IV. Black athletes had significantly lower scores compared to white athletes on Logical Memory II: F(1,61) = 4.667, p= .035, Verbal Paired Associates I: F(1,61) = 4.536, p = .037, Verbal Paired Associates: II F(1,61) = 4.677, p = .034, and Visual Reproduction I: F(1,61) = 6.562, p = .013. Conclusions: Results suggest significant differences exist between white and black athletes on neuropsychological test performance, necessitating the need for proper normative samples for each ethnic group. It is possible the differences found can be explained by the psychometric properties of the assessment and possibility of a non-representative sample for minorities, or simply individual differences. Previous literature has found white individuals to outperform African-Americans on verbal and non-verbal cognitive tasks after controlling for socioeconomic and other demographic variables (Manly & Jacobs, 2002). This highlights the need for future investigators to identify cultural factors and evaluate how ethnicity specifically plays a role on neuropsychological test performance. Notably, differences between ethnic groups can have significant implications when evaluating a sample of former athletes for cognitive impairment, as these results suggest retired NFL minorities may be more impaired compared to retired NFL white athletes
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