Least square projection: A fast high-precision multidimensional projection technique and its application to document mapping

The problem of projecting multidimensional data into lower dimensions has been pursued by many researchers due to its potential application to data analyses of various kinds. This paper presents a novel multidimensional projection technique based on least square approximations. The approximations compute the coordinates of a set of projected points based on the coordinates of a reduced number of control points with defined geometry. We name the technique Least Square Projections ( LSP). From an initial projection of the control points, LSP defines the positioning of their neighboring points through a numerical solution that aims at preserving a similarity relationship between the points given by a metric in mD. In order to perform the projection, a small number of distance calculations are necessary, and no repositioning of the points is required to obtain a final solution with satisfactory precision. The results show the capability of the technique to form groups of points by degree of similarity in 2D. We illustrate that capability through its application to mapping collections of textual documents from varied sources, a strategic yet difficult application. LSP is faster and more accurate than other existing high-quality methods, particularly where it was mostly tested, that is, for mapping text sets.

A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data

Background: The genome-wide identification of both morbid genes, i.e., those genes whose mutations cause hereditary human diseases, and druggable genes, i.e., genes coding for proteins whose modulation by small molecules elicits phenotypic effects, requires experimental approaches that are time-consuming and laborious. Thus, a computational approach which could accurately predict such genes on a genome-wide scale would be invaluable for accelerating the pace of discovery of causal relationships between genes and diseases as well as the determination of druggability of gene products.Results: In this paper we propose a machine learning-based computational approach to predict morbid and druggable genes on a genome-wide scale. For this purpose, we constructed a decision tree-based meta-classifier and trained it on datasets containing, for each morbid and druggable gene, network topological features, tissue expression profile and subcellular localization data as learning attributes. This meta-classifier correctly recovered 65% of known morbid genes with a precision of 66% and correctly recovered 78% of known druggable genes with a precision of 75%. It was than used to assign morbidity and druggability scores to genes not known to be morbid and druggable and we showed a good match between these scores and literature data. Finally, we generated decision trees by training the J48 algorithm on the morbidity and druggability datasets to discover cellular rules for morbidity and druggability and, among the rules, we found that the number of regulating transcription factors and plasma membrane localization are the most important factors to morbidity and druggability, respectively.Conclusions: We were able to demonstrate that network topological features along with tissue expression profile and subcellular localization can reliably predict human morbid and druggable genes on a genome-wide scale. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing morbidity and druggability.

High tech garbage can help engineering colleges to improve hands-on education

This paper presents a discussion on the potential use of high tech garbage, including electronic waste (e-waste), as a source of mechanisms, sensors and actuators, that can be adapted to improve the reality of microprocessor systems labs, at low cost. By means of some examples, it is shown that entire subsystems withdrawn of high tech equipments can be easily integrated into existing laboratory infrastructure. As examples, first a precision positioning mechanism is presented, which was taken from a discarded commercial ink jet printer and interfaced with a microprocessor board used in the laboratory classes. Secondly, a read/write head and its positioning mechanism has been withdrawn of a retired CD/DVD drive and again interfaced with the microprocessor board. Students who have been using these new experiments strongly approve their inclusion in the lab schedules. © 2011 IEEE.

Isolamento e caracterização de promotores órgão-específicos a partir de informações do Banco FORESTs (Eucalyptus Genome Sequencing Project Consortium)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Precision of distances and ordering of microsatellite markers in consensus linkage maps of chromosomes 1, 3 and 4 from two reciprocal chicken populations using bootstrap sampling

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The humankind genome: from genetic diversity to the origin of human diseases

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease’s etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

Computational methods for genome screening

Motivation An actual issue of great interest, both under a theoretical and an applicative perspective, is the analysis of biological sequences for disclosing the information that they encode. The development of new technologies for genome sequencing in the last years, opened new fundamental problems since huge amounts of biological data still deserve an interpretation. Indeed, the sequencing is only the first step of the genome annotation process that consists in the assignment of biological information to each sequence. Hence given the large amount of available data, in silico methods became useful and necessary in order to extract relevant information from sequences. The availability of data from Genome Projects gave rise to new strategies for tackling the basic problems of computational biology such as the determination of the tridimensional structures of proteins, their biological function and their reciprocal interactions. Results The aim of this work has been the implementation of predictive methods that allow the extraction of information on the properties of genomes and proteins starting from the nucleotide and aminoacidic sequences, by taking advantage of the information provided by the comparison of the genome sequences from different species. In the first part of the work a comprehensive large scale genome comparison of 599 organisms is described. 2,6 million of sequences coming from 551 prokaryotic and 48 eukaryotic genomes were aligned and clustered on the basis of their sequence identity. This procedure led to the identification of classes of proteins that are peculiar to the different groups of organisms. Moreover the adopted similarity threshold produced clusters that are homogeneous on the structural point of view and that can be used for structural annotation of uncharacterized sequences. The second part of the work focuses on the characterization of thermostable proteins and on the development of tools able to predict the thermostability of a protein starting from its sequence. By means of Principal Component Analysis the codon composition of a non redundant database comprising 116 prokaryotic genomes has been analyzed and it has been showed that a cross genomic approach can allow the extraction of common determinants of thermostability at the genome level, leading to an overall accuracy in discriminating thermophilic coding sequences equal to 95%. This result outperform those obtained in previous studies. Moreover, we investigated the effect of multiple mutations on protein thermostability. This issue is of great importance in the field of protein engineering, since thermostable proteins are generally more suitable than their mesostable counterparts in technological applications. A Support Vector Machine based method has been trained to predict if a set of mutations can enhance the thermostability of a given protein sequence. The developed predictor achieves 88% accuracy.

Genetic engineering and preclinical evaluation of oncolytic herpes simplex viruses retargeted to cancer-specific receptors

Oncolytic virotherapy exploits the ability of viruses to infect and kill cells. It is suitable as treatment for tumors that are not accessible by surgery and/or respond poorly to the current therapeutic approach. HSV is a promising oncolytic agent. It has a large genome size able to accommodate large transgenes and some attenuated oncolytic HSVs (oHSV) are already in clinical trials phase I and II. The aim of this thesis was the generation of HSV-1 retargeted to tumor-specific receptors and detargeted from HSV natural receptors, HVEM and Nectin-1. The retargeting was achieved by inserting a specific single chain antibody (scFv) for the tumor receptor selected inside the HSV glycoprotein gD. In this research three tumor receptors were considered: epidermal growth factor receptor 2 (HER2) overexpressed in 25-30% of breast and ovarian cancers and gliomas, prostate specific membrane antigen (PSMA) expressed in prostate carcinomas and in neovascolature of solid tumors; and epidermal growth factor receptor variant III (EGFRvIII). In vivo studies on HER2 retargeted viruses R-LM113 and R-LM249 have demonstrated their high safety profile. For R-LM249 the antitumor efficacy has been highlighted by target-specific inhibition of the growth of human tumors in models of HER2-positive breast and ovarian cancer in nude mice. In a murine model of HER2-positive glioma in nude mice, R-LM113 was able to significantly increase the survival time of treated mice compared to control. Up to now, PSMA and EGFRvIII viruses (R-LM593 and R-LM613) are only characterized in vitro, confirming the specific retargeting to selected targets. This strategy has proved to be generally applicable to a broad spectrum of receptors for which a single chain antibody is available.

Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

Design methods and geometric modelling of scaffolds for bone tissue engineering

Every year, thousand of surgical treatments are performed in order to fix up or completely substitute, where possible, organs or tissues affected by degenerative diseases. Patients with these kind of illnesses stay long times waiting for a donor that could replace, in a short time, the damaged organ or the tissue. The lack of biological alternates, related to conventional surgical treatments as autografts, allografts, e xenografts, led the researchers belonging to different areas to collaborate to find out innovative solutions. This research brought to a new discipline able to merge molecular biology, biomaterial, engineering, biomechanics and, recently, design and architecture knowledges. This discipline is named Tissue Engineering (TE) and it represents a step forward towards the substitutive or regenerative medicine. One of the major challenge of the TE is to design and develop, using a biomimetic approach, an artificial 3D anatomy scaffold, suitable for cells adhesion that are able to proliferate and differentiate themselves as consequence of the biological and biophysical stimulus offered by the specific tissue to be replaced. Nowadays, powerful instruments allow to perform analysis day by day more accurateand defined on patients that need more precise diagnosis and treatments.Starting from patient specific information provided by TC (Computed Tomography) microCT and MRI(Magnetic Resonance Imaging), an image-based approach can be performed in order to reconstruct the site to be replaced. With the aid of the recent Additive Manufacturing techniques that allow to print tridimensional objects with sub millimetric precision, it is now possible to practice an almost complete control of the parametrical characteristics of the scaffold: this is the way to achieve a correct cellular regeneration. In this work, we focalize the attention on a branch of TE known as Bone TE, whose the bone is main subject. Bone TE combines osteoconductive and morphological aspects of the scaffold, whose main properties are pore diameter, structure porosity and interconnectivity. The realization of the ideal values of these parameters represents the main goal of this work: here we'll a create simple and interactive biomimetic design process based on 3D CAD modeling and generative algorithmsthat provide a way to control the main properties and to create a structure morphologically similar to the cancellous bone. Two different typologies of scaffold will be compared: the first is based on Triply Periodic MinimalSurface (T.P.M.S.) whose basic crystalline geometries are nowadays used for Bone TE scaffolding; the second is based on using Voronoi's diagrams and they are more often used in the design of decorations and jewellery for their capacity to decompose and tasselate a volumetric space using an heterogeneous spatial distribution (often frequent in nature). In this work, we will show how to manipulate the main properties (pore diameter, structure porosity and interconnectivity) of the design TE oriented scaffolding using the implementation of generative algorithms: "bringing back the nature to the nature".

High precision range estimation techniques for multi-path wireless environments

Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic assumptions in practical systems. The performance and complexity of the proposed technique is investigated as well. This study’s results show that selecting bandwidth, center frequency, and SNR levels for each sub-band can adapt positioning accuracy.

Genetic Engineering of Induced Pluripotent Stem Cells and Reprogramming to Motor Neurons to Elucidate Selective Motor Neuron Death in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease, fatal within 1 to 5 years after onset of symptoms. About 3 out of 100’000 persons are diagnosed with ALS and there is still no cure available [1, 2]. 95% of all cases occur sporadically and the aetiology remains largely unknown [XXXX]. However, up to now 16 genes were identified to play a role in the development of familial ALS. One of these genes is FUS that encodes for the protein fused in sarcoma/translocated in liposarcoma (FUS/TLS). Mutations in this gene are responsible for some cases of sporadic as well as of inherited ALS [3]. FUS belongs to the family of heterogeneous nuclear ribonucleoproteins and is predicted to be involved in several cellular functions like transcription regulation [4], RNA splicing [5, 6], mRNA transport in neurons [7] and microRNA processing [8]. Aberrant accumulation of mutated FUS has been found in the cytoplasm of motor neurons from ALS patients [9]. The mislocalization of FUS is based on a mutation in the nuclear localization signal of FUS [10]. However, it is still unclear if the cytoplasmic localization of FUS leads to a toxic gain of cytoplasmic function and/or a loss of nuclear function that might be crucial in the course of ALS. The goal of this project is to characterize the impact of ALS-associated FUS mutations on in vitro differentiated motor neurons. To this end, we edit the genome of induced pluripotent stem cells (iPSC) using transcription activator-like effector nucleases (TALENs) [11,12] to create three isogenic cell lines, each carrying an ALS-associated FUS mutation (G156E, R244C and P525L). These iPSC’s will then be differentiated to motor neurons according to a recently establishe protocol (Ref Wichterle) and serve to study alterations in the transcriptome, proteome and metabolome upon the expression of ALS-associated FUS. With this approach, we hope to unravel the molecular mechanism leading to FUS-associated ALS and to provide new insight into the emerging connection between misregulation of RNA metabolism and neurodegeneration, a connection that is currently implied in a variety of additional neurological diseases, including spinocerebellar ataxia 2 (SCA-2), spinal muscular atrophy (SMA), fragile X syndrome, and myotonic dystrophy.

Genetic Engineering of Induced Pluripotent Stem Cells and Reprogramming to Motor Neurons to Elucidate Selective Motor Neuron Death in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease, fatal within 1 to 5 years after onset of symptoms. About 3 out of 100’000 persons are diagnosed with ALS and there is still no cure available [1, 2]. 95% of all cases occur sporadically and the aetiology remains largely unknown [3]. However, up to now 16 genes were identified to play a role in the development of familial ALS. One of these genes is FUS that encodes for the protein fused in sarcoma (FUS). Mutations in this gene are responsible for some cases of sporadic as well as of inherited ALS [4]. FUS belongs to the family of heterogeneous nuclear ribonucleoproteins and is predicted to be involved in several cellular functions like transcription regulation, RNA splicing, mRNA transport in neurons and microRNA processing [5] Aberrant accumulation of mutated FUS has been found in the cytoplasm of motor neurons from ALS patients [6]. The mislocalization of FUS is based on a mutation in the nuclear localization signal of FUS [7]. However, it is still unclear if the cytoplasmic localization of FUS leads to a toxic gain of cytoplasmic function and/or a loss of nuclear function that might be crucial in the course of ALS. The goal of this project is to characterize the impact of ALS-associated FUS mutations on in vitro differentiated motor neurons. To this end, we edit the genome of induced pluripotent stem cells (iPSC) using transcription activator-like effector nucleases (TALENs) [8,9] to create three isogenic cell lines, each carrying an ALS-associated FUS mutation (G156E, R244C and P525L). These iPSC’s will then be differentiated to motor neurons according to a recently established protocol [10] and serve to study alterations in the transcriptome, proteome and metabolome upon the expression of ALS-associated FUS. With this approach, we hope to unravel the molecular mechanism leading to FUS-associated ALS and to provide new insight into the emerging connection between misregulation of RNA metabolism and neurodegeneration, a connection that is currently implied in a variety of additional neurological diseases, including spinocerebellar ataxia 2 (SCA-2), spinal muscular atrophy (SMA), fragile X syndrome, and myotonic dystrophy. [1] Cleveland, D.W. et al. (2001) Nat Rev Neurosci 2(11): 806-819 [2] Sathasivam, S. (2010) Singapore Med J 51(5): 367-372 [3] Schymick, J.C. et al. (2007) Hum Mol Genet Vol 16: 233-242 [4] Pratt, A.J. et al. (2012). Degener Neurol Neuromuscul Dis 2012(2): 1-14 [5] Lagier-Tourenne, C. Hum Mol Genet, 2010. 19(R1): p. R46-64 [6] Mochizuki, Y. et al. (2012) J Neurol Sci 323(1-2): 85-92 [7] Dormann, D. et al. (2010) EMBO J 29(16): 2841-2857 [8] Hockemeyer, D. et al. (2011) Nat Biotech 29(8): 731-734 [9] Joung, J.K. and J.D. Sander (2013) Nat Rev Mol Cell Biol 14(1): 49-55 [10]Amoroso, M.W. et al. (2013) J Neurosci 33(2): 574-586.

CHEOPS: a space telescope for ultra-high precision photometry of exoplanet transits

The CHaracterising ExOPlanet Satellite (CHEOPS) is a joint ESA-Switzerland space mission (expected to launch in 2017) dedicated to search for exoplanet transits by means of ultra-high precision photometry. CHEOPS will provide accurate radii for planets down to Earth size. Targets will mainly come from radial velocity surveys. The CHEOPS instrument is an optical space telescope of 30 cm clear aperture with a single focal plane CCD detector. The tube assembly is passively cooled and thermally controlled to support high precision, low noise photometry. The telescope feeds a re-imaging optic, which supports the straylight suppression concept to achieve the required Signal to Noise. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.