A probabilistic examplar based model

A central problem in case based reasoning (CBR) is how to store and retrievecases. One approach to this problem is to use exemplar based models, where onlythe prototypical cases are stored. However, the development of an exemplar basedmodel (EBM) requires the solution of several problems: (i) how can a EBM berepresented? (ii) given a new case, how can a suitable exemplar be retrieved? (iii)what makes a good exemplar? (iv) how can an EBM be learned incrementally?This thesis develops a new model, called a probabilistic exemplar based model,that addresses these research questions. The model utilizes Bayesian networksto develop a suitable representation and uses probability theory to develop thefoundations of the developed model. A probability propagation method is usedto retrieve exemplars when a new case is presented and for assessing the prototypicalityof an exemplar.The model learns incrementally by revising the exemplars retained and byupdating the conditional probabilities required by the Bayesian network. Theproblem of ignorance, encountered when only a few cases have been observed,is tackled by introducing the concept of a virtual exemplar to represent all theunseen cases.The model is implemented in C and evaluated on three datasets. It is alsocontrasted with related work in CBR and machine learning (ML)

The neuropsychiatry of Parkinson's disease: advances and challenges

In people with Parkinson's disease, neuropsychiatric signs and symptoms are common throughout the disease course. These symptoms can be disabling and as clinically relevant as motor symptoms, and their presentation can be similar to, or distinct from, their counterparts in the general population. Correlates and risk factors for developing neuropsychiatric signs and symptoms include demographic, clinical, and psychosocial characteristics. The underlying neurobiology of these presentations is complex and not well understood, with the strongest evidence for neuropathological changes associated with Parkinson's disease, mechanisms linked to dopaminergic therapy, and effects not specific to Parkinson's disease. Assessment instruments and formal diagnostic criteria exist, but there is little routine screening of these signs and symptoms in clinical practice. Mounting evidence supports a range of pharmacological and non-pharmacological interventions, but relatively few efficacious treatment options exist. Optimising the management of neuropsychiatric presentations in people with Parkinson's disease will require additional research, raised awareness, specialised training, and development of innovative models of care

Subarachnoid Space: New Tricks by an Old Dog

PURPOSE: The purpose of the study was to: (1) evaluate the subarachnoid space (SAS) width and pial artery pulsation in both hemispheres, and (2) directly compare magnetic resonance imaging (MRI) to near-infrared transillumination/backscattering sounding (NIR-T/BSS) measurements of SAS width changes in healthy volunteers. METHODS: The study was performed on three separate groups of volunteers, consisting in total of 62 subjects (33 women and 29 men) aged from 16 to 39 years. SAS width was assessed by MRI and NIR-T/BSS, and pial artery pulsation by NIR-T/BSS. RESULTS: In NIR-T/BSS, the right frontal SAS was 9.1% wider than the left (p<0.01). The SAS was wider in men (p<0.01), while the pial artery pulsation was higher in women (p<0.01). Correlation and regression analysis of SAS width changes between the back- and abdominal-lying positions measured with MRI and NIRT-B/SS demonstrated high interdependence between both methods (r = 0.81, p<0.001). CONCLUSIONS: NIR-T/BSS and MRI were comparable and gave equivalent modalities for the SAS width change measurements. The SAS width and pial artery pulsation results obtained with NIR-T/BSS are consistent with the MRI data in the literature related to sexual dimorphism and morphological asymmetries between the hemispheres. NIR-T/BSS is a potentially cheap and easy-to-use method for early screening in patients with brain tumours, increased intracranial pressures and other abnormalities. Further studies in patients with intracranial pathologies are warranted

Structure of PbTe(SiO2)/SiO2 multilayers deposited on Si(111)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)The structure of thin films composed of a multilayer of PbTe nanocrystals embedded in SiO2, named as PbTe(SiO2), between homogeneous layers of amorphous SiO2 deposited on a single-crystal Si( 111) substrate was studied by grazing-incidence small-angle X-ray scattering (GISAXS) as a function of PbTe content. PbTe(SiO2)/SiO2 multilayers were produced by alternately applying plasma-enhanced chemical vapour deposition and pulsed laser deposition techniques. From the analysis of the experimental GISAXS patterns, the average radius and radius dispersion of PbTe nanocrystals were determined. With increasing deposition dose the size of the PbTe nanocrystals progressively increases while their number density decreases. Analysis of the GISAXS intensity profiles along the normal to the sample surface allowed the determination of the period parameter of the layers and a structure parameter that characterizes the disorder in the distances between PbTe layers. (C) 2010 International Union of Crystallography Printed in Singapore - all rights reserved433385393Brazilian Synchrotron Light Laboratory (LNLS)PRONEXConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Active wetting of epithelial tissues

Development, regeneration and cancer involve drastic transitions in tissue morphology. In analogy with the behavior of inert fluids, some of these transitions have been interpreted as wetting transitions. The validity and scope of this analogy are unclear, however, because the active cellular forces that drive tissue wetting have been neither measured nor theoretically accounted for. Here we show that the transition between 2D epithelial monolayers and 3D spheroidal aggregates can be understood as an active wetting transition whose physics differs fundamentally from that of passive wetting phenomena. By combining an active polar fluid model with measurements of physical forces as a function of tissue size, contractility, cell-cell and cell-substrate adhesion, and substrate stiffness, we show that the wetting transition results from the competition between traction forces and contractile intercellular stresses. This competition defines a new intrinsic lengthscale that gives rise to a critical size for the wetting transition in tissues, a striking feature that has no counterpart in classical wetting. Finally, we show that active shape fluctuations are dynamically amplified during tissue dewetting. Overall, we conclude that tissue spreading constitutes a prominent example of active wetting --- a novel physical scenario that may explain morphological transitions during tissue morphogenesis and tumor progression

Using molecular data for epidemiological inference: assessing the prevalence of Trypanosoma brucei rhodesiense in Tsetse in Serengeti, Tanzania

Background: Measuring the prevalence of transmissible Trypanosoma brucei rhodesiense in tsetse populations is essential for understanding transmission dynamics, assessing human disease risk and monitoring spatio-temporal trends and the impact of control interventions. Although an important epidemiological variable, identifying flies which carry transmissible infections is difficult, with challenges including low prevalence, presence of other trypanosome species in the same fly, and concurrent detection of immature non-transmissible infections. Diagnostic tests to measure the prevalence of T. b. rhodesiense in tsetse are applied and interpreted inconsistently, and discrepancies between studies suggest this value is not consistently estimated even to within an order of magnitude. Methodology/Principal Findings: Three approaches were used to estimate the prevalence of transmissible Trypanosoma brucei s.l. and T. b. rhodesiense in Glossina swynnertoni and G. pallidipes in Serengeti National Park, Tanzania: (i) dissection/microscopy; (ii) PCR on infected tsetse midguts; and (iii) inference from a mathematical model. Using dissection/microscopy the prevalence of transmissible T. brucei s.l. was 0% (95% CI 0–0.085) for G. swynnertoni and 0% (0–0.18) G. pallidipes; using PCR the prevalence of transmissible T. b. rhodesiense was 0.010% (0–0.054) and 0.0089% (0–0.059) respectively, and by model inference 0.0064% and 0.00085% respectively. Conclusions/Significance: The zero prevalence result by dissection/microscopy (likely really greater than zero given the results of other approaches) is not unusual by this technique, often ascribed to poor sensitivity. The application of additional techniques confirmed the very low prevalence of T. brucei suggesting the zero prevalence result was attributable to insufficient sample size (despite examination of 6000 tsetse). Given the prohibitively high sample sizes required to obtain meaningful results by dissection/microscopy, PCR-based approaches offer the current best option for assessing trypanosome prevalence in tsetse but inconsistencies in relating PCR results to transmissibility highlight the need for a consensus approach to generate meaningful and comparable data

A Metric Framework for quantifying Data Concentration

Poor performance of artificial neural nets when applied to credit-related classification problems is investigated and contrasted with logistic regression classification. We propose that artificial neural nets are less successful because of the inherent structure of credit data rather than any particular aspect of the neural net structure. Three metrics are developed to rationalise the result with such data. The metrics exploit the distributional properties of the data to rationalise neural net results. They are used in conjunction with a variant of an established concentration measure that differentiates between class characteristics. The results are contrasted with those obtained using random data, and are compared with results obtained using logistic regression. We find, in general agreement with previous studies, that logistic regressions out-perform neural nets in the majority of cases. An approximate decision criterion is developed in order to explain adverse results

Bright ligand-activatable fluorescent protein for high-quality multicolor live-cell super-resolution microscopy

We introduce UnaG as a green-to-dark photoswitching fluorescent protein capable of high-quality super-resolution imaging with photon numbers equivalent to the brightest photoswitchable red protein. UnaG only fluoresces upon binding of a fluorogenic metabolite, bilirubin, enabling UV-free reversible photoswitching with easily controllable kinetics and low background under Epi illumination. The on- and off-switching rates are controlled by the concentration of the ligand and the excitation light intensity, respectively, where the dissolved oxygen also promotes the off-switching. The photo-oxidation reaction mechanism of bilirubin in UnaG suggests that the lack of ligand-protein covalent bond allows the oxidized ligand to detach from the protein, emptying the binding cavity for rebinding to a fresh ligand molecule. We demonstrate super-resolution single-molecule localization imaging of various subcellular structures genetically encoded with UnaG, which enables facile labeling and simultaneous multicolor imaging of live cells. UnaG has the promise of becoming a default protein for high-performance super-resolution imaging. Photoconvertible proteins occupy two color channels thereby limiting multicolour localisation microscopy applications. Here the authors present UnaG, a new green-to-dark photoswitching fluorescent protein for super-resolution imaging, whose activation is based on a noncovalent binding with bilirubin