Renal Cryoablation: Investigation of Periprocedural Visualization Tools and Treatment Response Quantification

Cryoablation for small renal tumors has demonstrated sufficient clinical efficacy over the past decade as a non-surgical nephron-sparing approach for treating renal masses for patients who are not surgical candidates. Minimally invasive percutaneous cryoablations have been performed with image guidance from CT, ultrasound, and MRI. During the MRI-guided cryoablation procedure, the interventional radiologist visually compares the iceball size on monitoring images with respect to the original tumor on separate planning images. The comparisons made during the monitoring step are time consuming, inefficient and sometimes lack the precision needed for decision making, requiring the radiologist to make further changes later in the procedure. This study sought to mitigate uncertainty in these visual comparisons by quantifying tissue response to cryoablation and providing visualization of the response during the procedure. Based on retrospective analysis of MR-guided cryoablation patient data, registration and segmentation algorithms were investigated and implemented for periprocedural visualization to deliver iceball position/size with respect to planning images registered within 3.3mm with at least 70% overlap and a quantitative logit model was developed to relate perfusion deficit in renal parenchyma visualized in verification images as a result of iceball size visualized in monitoring images. Through retrospective study of 20 patient cases, the relationship between likelihood of perfusion loss in renal parenchyma and distance within iceball was quantified and iteratively fit to a logit curve. Using the parameters from the logit fit, the margin for 95% perfusion loss likelihood was found to be 4.28 mm within the iceball. The observed margin corresponds well with the clinically accepted margin of 3-5mm within the iceball. In order to display the iceball position and perfusion loss likelihood to the radiologist, algorithms were implemented to create a fast segmentation and registration module which executed in under 2 minutes, within the clinically-relevant 3 minute monitoring period. Using 16 patient cases, the average Hausdorff distance was reduced from 10.1mm to 3.21 mm with average DSC increased from 46.6% to 82.6% before and after registration.

General descriptions, organic contents and ratios of geolipid components at DSDP Holes 75-530B and 75-532

Distributions of free and bound n-alkanes, n-alkanoic acids, and n-alkanols were determined in order to compare the character of organic matter contained in organic-carbon-rich sediments from two sites sampled by the hydraulic piston corer. Two diatomaceous debris-flow samples of Pleistocene age were obtained from Hole 530B in the Angola Basin. A sample of bioturbated Pleistocene diatomaceous clay and another of bioturbated late Miocene nannofossil clay were collected from Hole 532 on the Walvis Ridge. Geolipid distributions of all samples contain large terrigenous contributions and lesser amounts of marine components. Similarities in organic matter contents of Hole 530B and Hole 532 sediments suggest that a common depositional setting, probably on the Walvis Ridge, was the original source of these sediments through Quaternary, and possibly late Neogene, times and that downslope relocation of these biogenic deposits has frequently occurred.

Lithology, stage, organic carbon, d13C, hydrocarbons and fatty acids at DSDP Hole 93-603B

Organic-matter-rich Upper Cretaceous claystones from DSDP Hole 603B, lower continental rise, had organic carbon values ranging from 1.7 to 13.7%, C/N ratios from 32 to 72, and d13C values from -23.5 to -27.1 per mil. Lipid class maxima for the unbound alkanes (C29 and C31), unbound fatty acids (C28 and C30), and bound fatty acids (C24, C26 , and C28) and the strong odd-carbon and even-carbon preferences, respectively, suggested that the organic matter in these sediments was partially the result of input from continental plant waxes. Transport of the organic-matter-rich sediments to the deep sea from the near-shore environment probably resulted from turbiditic flow under oxygen-stressed conditions.

Nonparametric Message Passing Methods for Cooperative Localization and Tracking

The objective of this thesis is the development of cooperative localization and tracking algorithms using nonparametric message passing techniques. In contrast to the most well-known techniques, the goal is to estimate the posterior probability density function (PDF) of the position of each sensor. This problem can be solved using Bayesian approach, but it is intractable in general case. Nevertheless, the particle-based approximation (via nonparametric representation), and an appropriate factorization of the joint PDFs (using message passing methods), make Bayesian approach acceptable for inference in sensor networks. The well-known method for this problem, nonparametric belief propagation (NBP), can lead to inaccurate beliefs and possible non-convergence in loopy networks. Therefore, we propose four novel algorithms which alleviate these problems: nonparametric generalized belief propagation (NGBP) based on junction tree (NGBP-JT), NGBP based on pseudo-junction tree (NGBP-PJT), NBP based on spanning trees (NBP-ST), and uniformly-reweighted NBP (URW-NBP). We also extend NBP for cooperative localization in mobile networks. In contrast to the previous methods, we use an optional smoothing, provide a novel communication protocol, and increase the efficiency of the sampling techniques. Moreover, we propose novel algorithms for distributed tracking, in which the goal is to track the passive object which cannot locate itself. In particular, we develop distributed particle filtering (DPF) based on three asynchronous belief consensus (BC) algorithms: standard belief consensus (SBC), broadcast gossip (BG), and belief propagation (BP). Finally, the last part of this thesis includes the experimental analysis of some of the proposed algorithms, in which we found that the results based on real measurements are very similar with the results based on theoretical models.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Artificial Neural Networks still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning ANN parameters. In recent years the use of hybrid technologies, combining Artificial Neural Networks and Genetic Algorithms, has been utilized to. In this work, several ANN topologies were trained and tested using Artificial Neural Networks and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out.

Present and Future of Photovoltaic Solar Electricity

Ponencia Invitada presentada en el IEEE Region 8 Student Branch and GOLD Congress

A Ground-Truth Video Dataset for the Development and Evaluation of Vision-based Sense-and-Avoid systems

The importance of vision-based systems for Sense-and-Avoid is increasing nowadays as remotely piloted and autonomous UAVs become part of the non-segregated airspace. The development and evaluation of these systems demand flight scenario images which are expensive and risky to obtain. Currently Augmented Reality techniques allow the compositing of real flight scenario images with 3D aircraft models to produce useful realistic images for system development and benchmarking purposes at a much lower cost and risk. With the techniques presented in this paper, 3D aircraft models are positioned firstly in a simulated 3D scene with controlled illumination and rendering parameters. Realistic simulated images are then obtained using an image processing algorithm which fuses the images obtained from the 3D scene with images from real UAV flights taking into account on board camera vibrations. Since the intruder and camera poses are user-defined, ground truth data is available. These ground truth annotations allow to develop and quantitatively evaluate aircraft detection and tracking algorithms. This paper presents the software developed to create a public dataset of 24 videos together with their annotations and some tracking application results.

New definitions of margin for multi-class Boosting algorithms

La familia de algoritmos de Boosting son un tipo de técnicas de clasificación y regresión que han demostrado ser muy eficaces en problemas de Visión Computacional. Tal es el caso de los problemas de detección, de seguimiento o bien de reconocimiento de caras, personas, objetos deformables y acciones. El primer y más popular algoritmo de Boosting, AdaBoost, fue concebido para problemas binarios. Desde entonces, muchas han sido las propuestas que han aparecido con objeto de trasladarlo a otros dominios más generales: multiclase, multilabel, con costes, etc. Nuestro interés se centra en extender AdaBoost al terreno de la clasificación multiclase, considerándolo como un primer paso para posteriores ampliaciones. En la presente tesis proponemos dos algoritmos de Boosting para problemas multiclase basados en nuevas derivaciones del concepto margen. El primero de ellos, PIBoost, está concebido para abordar el problema descomponiéndolo en subproblemas binarios. Por un lado, usamos una codificación vectorial para representar etiquetas y, por otro, utilizamos la función de pérdida exponencial multiclase para evaluar las respuestas. Esta codificación produce un conjunto de valores margen que conllevan un rango de penalizaciones en caso de fallo y recompensas en caso de acierto. La optimización iterativa del modelo genera un proceso de Boosting asimétrico cuyos costes dependen del número de etiquetas separadas por cada clasificador débil. De este modo nuestro algoritmo de Boosting tiene en cuenta el desbalanceo debido a las clases a la hora de construir el clasificador. El resultado es un método bien fundamentado que extiende de manera canónica al AdaBoost original. El segundo algoritmo propuesto, BAdaCost, está concebido para problemas multiclase dotados de una matriz de costes. Motivados por los escasos trabajos dedicados a generalizar AdaBoost al terreno multiclase con costes, hemos propuesto un nuevo concepto de margen que, a su vez, permite derivar una función de pérdida adecuada para evaluar costes. Consideramos nuestro algoritmo como la extensión más canónica de AdaBoost para este tipo de problemas, ya que generaliza a los algoritmos SAMME, Cost-Sensitive AdaBoost y PIBoost. Por otro lado, sugerimos un simple procedimiento para calcular matrices de coste adecuadas para mejorar el rendimiento de Boosting a la hora de abordar problemas estándar y problemas con datos desbalanceados. Una serie de experimentos nos sirven para demostrar la efectividad de ambos métodos frente a otros conocidos algoritmos de Boosting multiclase en sus respectivas áreas. En dichos experimentos se usan bases de datos de referencia en el área de Machine Learning, en primer lugar para minimizar errores y en segundo lugar para minimizar costes. Además, hemos podido aplicar BAdaCost con éxito a un proceso de segmentación, un caso particular de problema con datos desbalanceados. Concluimos justificando el horizonte de futuro que encierra el marco de trabajo que presentamos, tanto por su aplicabilidad como por su flexibilidad teórica. Abstract The family of Boosting algorithms represents a type of classification and regression approach that has shown to be very effective in Computer Vision problems. Such is the case of detection, tracking and recognition of faces, people, deformable objects and actions. The first and most popular algorithm, AdaBoost, was introduced in the context of binary classification. Since then, many works have been proposed to extend it to the more general multi-class, multi-label, costsensitive, etc... domains. Our interest is centered in extending AdaBoost to two problems in the multi-class field, considering it a first step for upcoming generalizations. In this dissertation we propose two Boosting algorithms for multi-class classification based on new generalizations of the concept of margin. The first of them, PIBoost, is conceived to tackle the multi-class problem by solving many binary sub-problems. We use a vectorial codification to represent class labels and a multi-class exponential loss function to evaluate classifier responses. This representation produces a set of margin values that provide a range of penalties for failures and rewards for successes. The stagewise optimization of this model introduces an asymmetric Boosting procedure whose costs depend on the number of classes separated by each weak-learner. In this way the Boosting procedure takes into account class imbalances when building the ensemble. The resulting algorithm is a well grounded method that canonically extends the original AdaBoost. The second algorithm proposed, BAdaCost, is conceived for multi-class problems endowed with a cost matrix. Motivated by the few cost-sensitive extensions of AdaBoost to the multi-class field, we propose a new margin that, in turn, yields a new loss function appropriate for evaluating costs. Since BAdaCost generalizes SAMME, Cost-Sensitive AdaBoost and PIBoost algorithms, we consider our algorithm as a canonical extension of AdaBoost to this kind of problems. We additionally suggest a simple procedure to compute cost matrices that improve the performance of Boosting in standard and unbalanced problems. A set of experiments is carried out to demonstrate the effectiveness of both methods against other relevant Boosting algorithms in their respective areas. In the experiments we resort to benchmark data sets used in the Machine Learning community, firstly for minimizing classification errors and secondly for minimizing costs. In addition, we successfully applied BAdaCost to a segmentation task, a particular problem in presence of imbalanced data. We conclude the thesis justifying the horizon of future improvements encompassed in our framework, due to its applicability and theoretical flexibility.

Uncoupling of transfer of the presequence and unfolding of the mature domain in precursor translocation across the mitochondrial outer membrane

Translocation of mitochondrial precursor proteins across the mitochondrial outer membrane is facilitated by the translocase of the outer membrane (TOM) complex. By using site-specific photocrosslinking, we have mapped interactions between TOM proteins and a mitochondrial precursor protein arrested at two distinct stages, stage A (accumulated at 0°C) and stage B (accumulated at 30°C), in the translocation across the outer membrane at high resolution not achieved previously. Although the stage A and stage B intermediates were assigned previously to the forms bound to the cis site and the trans site of the TOM complex, respectively, the results of crosslinking indicate that the presequence of the intermediates at both stage A and stage B is already on the trans side of the outer membrane. The mature domain is unfolded and bound to Tom40 at stage B whereas it remains folded at stage A. After dissociation from the TOM complex, translocation of the stage B intermediate, but not of the stage A intermediate, across the inner membrane was promoted by the intermembrane-space domain of Tom22. We propose a new model for protein translocation across the outer membrane, where translocation of the presequence and unfolding of the mature domain are not necessarily coupled.

The optimization principle in phylogenetic analysis tends to give incorrect topologies when the number of nucleotides or amino acids used is small

In the maximum parsimony (MP) and minimum evolution (ME) methods of phylogenetic inference, evolutionary trees are constructed by searching for the topology that shows the minimum number of mutational changes required (M) and the smallest sum of branch lengths (S), respectively, whereas in the maximum likelihood (ML) method the topology showing the highest maximum likelihood (A) of observing a given data set is chosen. However, the theoretical basis of the optimization principle remains unclear. We therefore examined the relationships of M, S, and A for the MP, ME, and ML trees with those for the true tree by using computer simulation. The results show that M and S are generally greater for the true tree than for the MP and ME trees when the number of nucleotides examined (n) is relatively small, whereas A is generally lower for the true tree than for the ML tree. This finding indicates that the optimization principle tends to give incorrect topologies when n is small. To deal with this disturbing property of the optimization principle, we suggest that more attention should be given to testing the statistical reliability of an estimated tree rather than to finding the optimal tree with excessive efforts. When a reliability test is conducted, simplified MP, ME, and ML algorithms such as the neighbor-joining method generally give conclusions about phylogenetic inference very similar to those obtained by the more extensive tree search algorithms.

Structural details of an interaction between cardiolipin and an integral membrane protein

Anionic lipids play a variety of key roles in biomembrane function, including providing the immediate environment for the integral membrane proteins that catalyze photosynthetic and respiratory energy transduction. Little is known about the molecular basis of these lipid–protein interactions. In this study, x-ray crystallography has been used to examine the structural details of an interaction between cardiolipin and the photoreaction center, a key light-driven electron transfer protein complex found in the cytoplasmic membrane of photosynthetic bacteria. X-ray diffraction data collected over the resolution range 30.0–2.1 Å show that binding of the lipid to the protein involves a combination of ionic interactions between the protein and the lipid headgroup and van der Waals interactions between the lipid tails and the electroneutral intramembrane surface of the protein. In the headgroup region, ionic interactions involve polar groups of a number of residues, the protein backbone, and bound water molecules. The lipid tails sit along largely hydrophobic grooves in the irregular surface of the protein. In addition to providing new information on the immediate lipid environment of a key integral membrane protein, this study provides the first, to our knowledge, high-resolution x-ray crystal structure for cardiolipin. The possible significance of this interaction between an integral membrane protein and cardiolipin is considered.

Reciprocal regulation of Gsα by palmitate and the βγ subunit

Hormonal activation of Gs, the stimulatory regulator of adenylyl cyclase, promotes dissociation of αs from Gβγ, accelerates removal of covalently attached palmitate from the Gα subunit, and triggers release of a fraction of αs from the plasma membrane into the cytosol. To elucidate relations among these three events, we assessed biochemical effects in vitro of attached palmitate on recombinant αs prepared from Sf9 cells. In comparison to the unpalmitoylated protein (obtained from cytosol of Sf9 cells, treated with a palmitoyl esterase, or expressed as a mutant protein lacking the site for palmitoylation), palmitoylated αs (from Sf9 membranes, 50% palmitoylated) was more hydrophobic, as indicated by partitioning into TX-114, and bound βγ with 5-fold higher affinity. βγ protected GDP-bound αs, but not αs· GTP[γS], from depalmitoylation by a recombinant esterase. We conclude that βγ binding and palmitoylation reciprocally potentiate each other in promoting membrane attachment of αs and that dissociation of αs·GTP from βγ is likely to mediate receptor-induced αs depalmitoylation and translocation of the protein to cytosol in intact cells.

The quorum-sensing transcriptional regulator TraR requires its cognate signaling ligand for protein folding, protease resistance, and dimerization

Complexes between the quorum-sensing regulator TraR and its inducing ligand autoinducer (AAI) are soluble in Escherichia coli, whereas apo-TraR is almost completely insoluble. Here we show that the lack of soluble TraR is due in large part to rapid proteolysis, inasmuch as apo-TraR accumulated to high levels in an E. coli strain deficient in Clp and Lon proteases. In pulse labeling experiments, AAI protected TraR against proteolysis only when it was added before the radiolabel. This observation indicates that TraR proteins can productively bind AAI only during their own synthesis on polysomes, whereas fully synthesized apo-TraR proteins are not functional AAI receptors. Purified apo-TraR was rapidly degraded by trypsin to oligopeptides, whereas TraR–AAI complexes were more resistant to trypsin and were cleaved at discrete interdomain linkers, indicating that TraR requires AAI to attain its mature tertiary structure. TraR–AAI complexes eluted from a gel filtration column as dimers and bound DNA as dimers. In contrast, apo-TraR was monomeric, and incubation with AAI under a variety of conditions did not cause dimerization. We conclude that AAI is critical for the folding of nascent TraR protein into its mature tertiary structure and that full-length apo-TraR cannot productively bind AAI and is consequently targeted for rapid proteolysis.

Switch from Myc/Max to Mad1/Max binding and decrease in histone acetylation at the telomerase reverse transcriptase promoter during differentiation of HL60 cells

Recent evidence suggests that the Myc and Mad1 proteins are implicated in the regulation of the gene encoding the human telomerase reverse transcriptase (hTERT), the catalytic subunit of telomerase. We have analyzed the in vivo interaction between endogenous c-Myc and Mad1 proteins and the hTERT promoter in HL60 cells with the use of the chromatin immunoprecipitation assay. The E-boxes at the hTERT proximal promoter were occupied in vivo by c-Myc in exponentially proliferating HL60 cells but not in cells induced to differentiate by DMSO. In contrast, Mad1 protein was induced and bound to the hTERT promoter in differentiated HL60 cells. Concomitantly, the acetylation of the histones at the promoter was significantly reduced. These data suggest that the reciprocal E-box occupancy by c-Myc and Mad1 is responsible for activation and repression of the hTERT gene in proliferating and differentiated HL60 cells, respectively. Furthermore, the histone deacetylase inhibitor trichostatin A inhibited deacetylation of histones at the hTERT promoter and attenuated the repression of hTERT transcription during HL60 cell differentiation. In addition, trichostatin A treatment activated hTERT transcription in resting human lymphocytes and fibroblasts. Taken together, these results indicate that acetylation/deacetylation of histones is operative in the regulation of hTERT expression.

Accumulation rates and composition of organic matter in sediments off Peru

Deep-sea sediment samples from three Ocean Drilling Program (ODP) Leg 112 sites on the Peru continental margin were investigated, using a number of organic geochemical and organic petrographic techniques, for amounts and compositions of the organic matter preserved. Preliminary results include mass accumulation rates of organic carbon at Site 679 and characteristics of the organic facies for sediments from Sites 679, 681, and 684. Organic-carbon contents are high, with few exceptions. Particularly high values were determined in the Pliocene interval at Site 684 (4%-7.5%) and in the early Pliocene to Quaternary section of Hole 679D (2%-9%). Older sediments at this site have distinctively lower organic-carbon contents (0.2%-2.5%). Mass accumulation rates of organic matter at Site 679 are 0.02 to 0.07 g carbon/cm**2/k.y. for late Miocene to early Pliocene sediments and higher by a factor of 5 to 10 in the Quaternary sediments. The organic matter in all samples has a predominantly marine planktonic and bacterial origin, with minor terrigenous contribution. Organic particle sizes are strikingly small, so that only a minor portion is covered by visual maceral analysis. Molecular organic-geochemical data were obtained for nonaromatic hydrocarbons, aromatic hydrocarbons (including sulfur compounds), alcohols, ketones, esters, and carboxylic acids. Among the total extractable lipids, long-chain unsaturated ketones from Prymnesiophyte algae strongly predominate among the gas chromatography (GC) amenable components. Steroids are major constituents of the ketone and free- and bound-alcohol fractions. Perylene is the most abundant aromatic hydrocarbon, whereas in the nonaromatic hydrocarbon fractions, long-chain n-alkanes from higher land plants predominate, although the total terrigenous organic matter proportion in the sediments is small.