Hepatocyte gene therapy in a large animal: A neonatal bovine model of citrullinemia

The development of gene-replacement therapy for inborn errors of metabolism has been hindered by the limited number of suitable large-animal models of these diseases and by inadequate methods of assessing the efficacy of treatment. Such methods should provide sensitive detection of expression in vivo and should be unaffected by concurrent pharmacologic and dietary regimens. We present the results of studies in a neonatal bovine model of citrullinemia, an inborn error of urea-cycle metabolism characterized by deficiency of argininosuccinate synthetase and consequent life-threatening hyperammonemia. Measurements of the flux of nitrogen from orally administered 15NH4 to [15N]urea were used to determine urea-cycle activity in vivo. In control animals, these isotopic measurements proved to be unaffected by pharmacologic treatments. Systemic administration of a first-generation E1-deleted adenoviral vector expressing human argininosuccinate synthetase resulted in transduction of hepatocytes and partial correction of the enzyme defect. The isotopic method showed significant restoration of urea synthesis. Moreover, the calves showed clinical improvement and normalization of plasma glutamine levels after treatment. The results show the clinical efficacy of treating a large-animal model of an inborn error of hepatocyte metabolism in conjunction with a method for sensitively measuring correction in vivo. These studies will be applicable to human trials of the treatment of this disorder and other related urea-cycle disorders.

Ultrasensitive detection of pathological prion protein aggregates by dual-color scanning for intensely fluorescent targets

A definite diagnosis of prion diseases such as Creutzfeldt–Jakob disease (CJD) relies on the detection of pathological prion protein (PrPSc). However, no test for PrPSc in cerebrospinal fluid (CSF) has been available thus far. Based on a setup for confocal dual-color fluorescence correlation spectroscopy, a technique suitable for single molecule detection, we developed a highly sensitive detection method for PrPSc. Pathological prion protein aggregates were labeled by specific antibody probes tagged with fluorescent dyes, resulting in intensely fluorescent targets, which were measured by dual-color fluorescence intensity distribution analysis in a confocal scanning setup. In a diagnostic model system, PrPSc aggregates were detected down to a concentration of 2 pM PrPSc, corresponding to an aggregate concentration of approximately 2 fM, which was more than one order of magnitude more sensitive than Western blot analysis. A PrPSc-specific signal could also be detected in a number of CSF samples from patients with CJD but not in control samples, providing the basis for a rapid and specific test for CJD and other prion diseases. Furthermore, this method could be adapted to the sensitive detection of other disease-associated amyloid aggregates such as in Alzheimer's disease.

Cyclin A activates the DNA polymerase δ-dependent elongation machinery in vitro: A parvovirus DNA replication model

Replication of the single-stranded linear DNA genome of parvovirus minute virus of mice (MVM) starts with complementary strand synthesis from the 3′-terminal snap-back telomere, which serves as a primer for the formation of double-stranded replicative form (RF) DNA. This DNA elongation reaction, designated conversion, is exclusively dependent on cellular factors. In cell extracts, we found that complementary strand synthesis was inhibited by the cyclin-dependent kinase inhibitor p21WAF1/CIP1 and rescued by the addition of proliferating cell nuclear antigen, arguing for the involvement of DNA polymerase (Pol) δ in the conversion reaction. In vivo time course analyses using synchronized MVM-infected A9 cells allowed initial detection of MVM RF DNA at the G1/S phase transition, coinciding with the onset of cyclin A expression and cyclin A-associated kinase activity. Under in vitro conditions, formation of RF DNA was efficiently supported by A9 S cell extracts, but only marginally by G1 cell extracts. Addition of recombinant cyclin A stimulated DNA conversion in G1 cell extracts, and correlated with a concomitant increase in cyclin A-associated kinase activity. Conversely, a specific antibody neutralizing cyclin A-dependent kinase activity, abolished the capacity of S cell extracts for DNA conversion. We found no evidence for the involvement of cyclin E in the regulation of the conversion reaction. We conclude that cyclin A is necessary for activation of complementary strand synthesis, which we propose as a model reaction to study the cell cycle regulation of the Pol δ-dependent elongation machinery.

Sensitive detection of DNA polymorphisms by the serial invasive signal amplification reaction

The invasive signal amplification reaction has been previously developed for quantitative detection of nucleic acids and discrimination of single-nucleotide polymorphisms. Here we describe a method that couples two invasive reactions into a serial isothermal homogeneous assay using fluorescence resonance energy transfer detection. The serial version of the assay generates more than 107 reporter molecules for each molecule of target DNA in a 4-h reaction; this sensitivity, coupled with the exquisite specificity of the reaction, is sufficient for direct detection of less than 1,000 target molecules with no prior target amplification. Here we present a kinetic analysis of the parameters affecting signal and background generation in the serial invasive signal amplification reaction and describe a simple kinetic model of the assay. We demonstrate the ability of the assay to detect as few as 600 copies of the methylene tetrahydrofolate reductase gene in samples of human genomic DNA. We also demonstrate the ability of the assay to discriminate single base differences in this gene by using 20 ng of human genomic DNA.

A distribution of tumor size at detection and its limiting form.

A distribution of tumor size at detection is derived within the framework of a mechanistic model of carcinogenesis with the object of estimating biologically meaningful parameters of tumor latency. Its limiting form appears to be a generalization of the distribution that arises in the length-biased sampling from stationary point processes. The model renders the associated estimation problems tractable. The usefulness of the proposed approach is illustrated with an application to clinical data on premenopausal breast cancer.

On the nucleation and growth of amyloid beta-protein fibrils: detection of nuclei and quantitation of rate constants.

We have studied the fibrillogenesis of synthetic amyloid beta-protein-(1-40) fragment (A beta) in 0.1 M HCl. At low pH, A beta formed fibrils at a rate amenable to detailed monitoring by quasi-elastic light-scattering spectroscopy. Examination of the fibrils with circular dichroism spectroscopy and electron microscopy showed them to be highly similar to those found in amyloid plaques. We determined the hydrodynamic radii of A beta aggregates during the entire process of fibril nucleation and growth. Above an A beta concentration of approximately 0.1 mM, the initial rate of elongation and the final size of fibrils were independent of A beta concentration. Below an A beta concentration of 0.1 mM, the initial elongation rate was proportional to the peptide concentration, and the resulting fibrils were significantly longer than those formed at higher concentration. We also found that the surfactant n-dodecylhexaoxyethylene glycol monoether (C12E6) slowed nucleation and elongation of fibrils in a concentration-dependent manner. Our observations are consistent with a model of A beta fibrillogenesis that includes the following key steps: (i) peptide micelles form above a certain critical A beta concentration, (ii) fibrils nucleate within these micelles or on heterogeneous nuclei (seeds), and (iii) fibrils grow by irreversible binding of monomers to fibril ends. Interpretation of our data enabled us to determine the sizes of fibril nuclei and A beta micelles and the rates of fibril nucleation (from micelles) and fibril elongation. Our approach provides a powerful means for the quantitative assay of A beta fibrillogenesis.

Early p53 alterations in mouse skin carcinogenesis by UVB radiation: immunohistochemical detection of mutant p53 protein in clusters of preneoplastic epidermal cells.

High levels of the p53 protein are immunohistochemically detectable in a majority of human nonmelanoma skin cancers and UVB-induced murine skin tumors. These increased protein levels are often associated with mutations in the conserved domains of the p53 gene. To investigate the timing of the p53 alterations in the process of UVB carcinogenesis, we used a well defined murine model (SKH:HR1 hairless mice) in which the time that tumors appear is predictable from the UVB exposures. The mice were subjected to a series of daily UVB exposures, either for 17 days or for 30 days, which would cause skin tumors to appear around 80 or 30 weeks, respectively. In the epidermis of these mice, we detected clusters of cells showing a strong immunostaining of the p53 protein, as measured with the CM-5 polyclonal antiserum. This cannot be explained by transient accumulation of the normal p53 protein as a physiological response to UVB-induced DNA damage. In single exposure experiments the observed transient CM-5 immunoreactivity lasted for only 3 days and was not clustered, whereas these clusters were still detectable as long as 56 days after 17 days of UVB exposure. In addition, approximately 70% of these patches reacted with the mutant-specific monoclonal antibody PAb240, whereas transiently induced p53-positive cells did not. In line with indicative human data, these experimental results in the hairless mouse model unambiguously demonstrate that constitutive p53 alterations are causally related to chronic UVB exposure and that they are a very early event in the induction of skin cancer by UVB radiation.

EmotiBlog: a model to learn subjective information detection in the new textual genres of the Web 2.0 -a multilingual and multi-genre approach-

Tesis doctoral con mención europea en procesamiento del lenguaje natural realizada en la Universidad de Alicante por Ester Boldrini bajo la dirección del Dr. Patricio Martínez-Barco. El acto de defensa de la tesis tuvo lugar en la Universidad de Alicante el 23 de enero de 2012 ante el tribunal formado por los doctores Manuel Palomar (Universidad de Alicante), Dr. Paloma Moreda (UA), Dr. Mariona Taulé (Universidad de Barcelona), Dr. Horacio Saggion (Universitat Pompeu Fabra) y Dr. Mike Thelwall (University of Wolverhampton). Calificación: Sobresaliente Cum Laude por unanimidad.

EmotiBlog: a fine-grained model for emotion detection in non-traditional textual genres

This paper presents the first version of EmotiBlog, an annotation scheme for emotions in non-traditional textual genres such as blogs or forums. We collected a corpus composed by blog posts in three languages: English, Spanish and Italian and about three topics of interest. Subsequently, we annotated our collection and carried out the inter-annotator agreement and a ten-fold cross-validation evaluation, obtaining promising results. The main aim of this research is to provide a finer-grained annotation scheme and annotated data that are essential to perform evaluation focused on checking the quality of the created resources.

Multigradient field-active contour model for multilayer boundary detection of ultrasound rectal wall image

Extraction and reconstruction of rectal wall structures from an ultrasound image is helpful for surgeons in rectal clinical diagnosis and 3-D reconstruction of rectal structures from ultrasound images. The primary task is to extract the boundary of the muscular layers on the rectal wall. However, due to the low SNR from ultrasound imaging and the thin muscular layer structure of the rectum, this boundary detection task remains a challenge. An active contour model is an effective high-level model, which has been used successfully to aid the tasks of object representation and recognition in many image-processing applications. We present a novel multigradient field active contour algorithm with an extended ability for multiple-object detection, which overcomes some limitations of ordinary active contour models—"snakes." The core part in the algorithm is the proposal of multigradient vector fields, which are used to replace image forces in kinetic function for alternative constraints on the deformation of active contour, thereby partially solving the initialization limitation of active contour for rectal wall boundary detection. An adaptive expanding force is also added to the model to help the active contour go through the homogenous region in the image. The efficacy of the model is explained and tested on the boundary detection of a ring-shaped image, a synthetic image, and an ultrasound image. The experimental results show that the proposed multigradient field-active contour is feasible for multilayer boundary detection of rectal wall

Mach edges: a critical test of the nonlinear 3rd derivative model for edge-detection

Feature detection is a crucial stage of visual processing. In previous feature-marking experiments we found that peaks in the 3rd derivative of the luminance profile can signify edges where there are no 1st derivative peaks nor 2nd derivative zero-crossings (Wallis and George 'Mach edges' (the edges of Mach bands) were nicely predicted by a new nonlinear model based on 3rd derivative filtering. As a critical test of the model, we now use a new class of stimuli, formed by adding a linear luminance ramp to the blurred triangle waves used previously. The ramp has no effect on the second or higher derivatives, but the nonlinear model predicts a shift from seeing two edges to seeing only one edge as the added ramp gradient increases. In experiment 1, subjects judged whether one or two edges were visible on each trial. In experiment 2, subjects used a cursor to mark perceived edges and bars. The position and polarity of the marked edges were close to model predictions. Both experiments produced the predicted shift from two to one Mach edge, but the shift was less complete than predicted. We conclude that the model is a useful predictor of edge perception, but needs some modification.

Feature LDA:a supervised topic model for automatic detection of web API documentations from the web

Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models.

Probabilistic multiple model neural network based leak detection system:experimental study

This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.

A template model predicts detection of sparse stimul

Contemporary models of contrast integration across space assume that pooling operates uniformly over the target region. For sparse stimuli, where high contrast regions are separated by areas containing no signal, this strategy may be sub-optimal because it pools more noise than signal as area increases. Little is known about the behaviour of human observers for detecting such stimuli. We performed an experiment in which three observers detected regular textures of various areas, and six levels of sparseness. Stimuli were regular grids of horizontal grating micropatches, each 1 cycle wide. We varied the ratio of signals (marks) to gaps (spaces), with mark:space ratios ranging from 1 : 0 (a dense texture with no spaces) to 1 : 24. To compensate for the decline in sensitivity with increasing distance from fixation, we adjusted the stimulus contrast as a function of eccentricity based on previous measurements [Baldwin, Meese & Baker, 2012, J Vis, 12(11):23]. We used the resulting area summation functions and psychometric slopes to test several filter-based models of signal combination. A MAX model failed to predict the thresholds, but did a good job on the slopes. Blanket summation of stimulus energy improved the threshold fit, but did not predict an observed slope increase with mark:space ratio. Our best model used a template matched to the sparseness of the stimulus, and pooled the squared contrast signal over space. Templates for regular patterns have also recently been proposed to explain the regular appearance of slightly irregular textures (Morgan et al, 2012, Proc R Soc B, 279, 2754–2760)