Privacy-preserving Copy Number Variation Analysis with Homomorphic Encryption

Innovative pharma-genomics and personalized medicine services are now possible thanks to the availability for processing and analysis of a large amount of genomic data. Operating on such databases, is possible to test for predisposition to diseases by searching for genomic variants on whole genomes as well as on exomes, which are collections of protein coding regions called exons. Genomic data are therefore shared amongst research institutes, public/private operators, and third parties, creating issues of privacy, ethics, and data protection because genome data are strictly personal and identifying. To prevent damages that could follow a data breach—a likely threat nowadays—and to be compliant with current data protection regulations, genomic data files should be encrypted, and the data processing algorithms should be privacy-preserving. Such a migration is not always feasible: not all operations can be implemented straightforwardly to be privacypreserving; a privacy-preserving version of an algorithm may not be as accurate for the purpose of biomedical analysis as the original; or the privacy-preserving version may not scale up when applied to genomic data processing because of inefficiency in computation time. In this work, we demonstrate that at least for a wellknown genomic data procedure for the analysis of copy number variants called copy number variations (CNV) a privacy-preserving analysis is possible and feasible. Our algorithm relies on Homomorphic Encryption, a cryptographic technique to perform calculations directly on the encrypted data. We test our implementation for performance and reliability, giving evidence that it is practical to study copy number variations and preserve genomic data privacy. Our proof-of-concept application successfully and efficiently searches for a patient’s somatic copy number variation changes by comparing the patient gene coverage in the whole exome with a healthy control exome coverage. Since all the genomics data are securely encrypted, the data remain protected even if they are transmitted or shared via an insecure environment like a public cloud. Being this the first study for privacy-preserving copy number variation analysis, we demonstrate the potential of recent Homomorphic Encryption tools in genomic applications

A Novel RFID Distance Bounding Protocol Based on Physically Unclonable Functions

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Radio Frequency Identification (RFID) systems are vulnerable to relay attacks (i.e., mafia, terrorist and distance frauds) when they are used for authentication purposes. Distance bounding protocols are particularly designed as a countermeasure against these attacks. These protocols aim to ensure that the tags are in a distant area by measuring the round-trip delays during a rapid challenge-response exchange of short authenticated messages. Terrorist fraud is the most challenging attack to avoid, because a legitimate user (a tag owner) collaborates with an attacker to defeat the authentication system. Many RFID distance bounding protocols have been proposed recently, with encouraging results. However, none of them provides the ideal security against the terrorist fraud. Motivated by this need, we first introduce a strong adversary model for Physically Unclonable Functions (PUFs) based authentication protocol in which the adversary has access to volatile memory of the tag. We show that the security of Sadeghi et al.’s PUF based authentication protocol is not secure in this model. We provide a new technique to improve the security of their protocol. Namely, in our scheme, even if an adversary has access to volatile memory she cannot obtain all long term keys to clone the tag. Next, we propose a novel RFID distance bounding protocol based on PUFs which satisfies the expected security requirements. Comparing to the previous protocols, the use of PUFs in our protocol enhances the system in terms of security, privacy and tag computational overhead. We also prove that our extended protocol with a final signature provides the ideal security against all those frauds, remarkably the terrorist fraud. Besides that, our protocols enjoy the attractive properties of PUFs, which provide the most cost efficient and reliable means to fingerprint chips based on their physical properties

Cetuximab Concomitant with Second-Line Radiation Therapy in Patients with Locally Advanced Recurrent Squamous Cell Head and Neck Cancer

We presented 9 recurrent head and neck carcinoma patients. Priorly all of them had received radiochemotherapy. We used cetuximab and irradiation concomitantly. Overall survival analysis of the patients was performed using the Kaplan-Meier method on SPSS version 15.0. Based on this calculation, mean follow-up duration is 12.8 months. Mean survival time is 19.8 months and annual mean survival rate is 59.3%

An Analysis of Cholesteric Spherical Reflector Identifiers for Object Authenticity Verification

Arrays of Cholesteric Spherical Reflectors (CSRs), microscopic cholesteric liquid crystals in a spherical shape, have been argued to become a game-changing technology in anti-counterfeiting. Used to build identifiable tags or coating, called CSR IDs, they can supply objects with unclonable fingerprint-like characteristics, making it possible to authenticate objects. In a previous study, we have shown how to extract minutiæ from CSR IDs. In this journal version, we build on that previous research, consolidate the methodology, and test it over CSR IDs obtained by different production processes. We measure the robustness and reliability of our procedure on large and variegate sets of CSR IDs’ images taken with a professional microscope (Laboratory Data set) and with a microscope that could be used in a realistic scenario (Realistic Data set). We measure intra-distance and interdistance, proving that we can distinguish images coming from the same CSR ID from images of different CSR IDs. However, without surprise, images in Laboratory Data set have an intra-distance that on average is less, and with less variance, than the intra-distance between responses from Realistic Data set. With this evidence, we discuss a few requirements for an anti-counterfeiting technology based on CSRs

Experimentally induced puromycine aminonucleoside nephrosis (PAN) in rats: evaluation of angiogenic protein platelet-derived endothelial cell growth factor (PD-ECGF) expression in glomeruli

<p>Abstract</p> <p>Background</p> <p>In experimentally induced puromycine aminonucleoside nephrosis (PAN) animal models, nephrotic syndrome with minimal change disease and focal and segmental sclerosis-like nephritis similar to that in human is demonstrated; however, the real mechanism of PAN is not yet elucidated. Platelet derived endothelial cell growth factor (PD-ECGF), an endothelial mitogen protein, is believed to take part in microvessel formation and in stimulation of angiogenesis and its expression has not been totally demonstrated in PAN rats yet. In this study, we aimed to examine PD-ECGF expression in acute and chronic PAN induced in rats and find out the association between its expression and the stages of angiogenesis in kidney.</p> <p>Methods</p> <p>For the experiment, twenty-four Male Wistar Albino rats were used and divided into four groups; control group (n = 6), pre-proteinuria group (n = 6), acute group (n = 6) and chronic group (n = 6). We compared statistically all data by One-way ANOVA Test followed by Dunn Multiple Comparison Test.</p> <p>Results</p> <p>Proteinurea levels in control and pre-proteinuria groups were not statistically different; however, it was remarkably higher in the acute nephrosis group and significantly greater in the chronic nephrosis group than control group (<it>p </it>< 0.0025). In pre-proteinuria group, the serum albumin and creatinine clearances also did not significantly differ from the control group. On the other hand, in the acute and chronic nephrosis groups, serum albumin and creatinine clearances progressively decreased (<it>p </it>< 0.05). In our immunohistochemical studies, we showed elevated PD-ECGF expression in glomeruli of acute and chronic PAN rats. Microscopic and ultrastructural appearances of the glomeruli of acute and chronic PAN showed various sequential steps of angiogenesis, macrophages and immature capillaries with primitive lumens and apoptotic endothelial cells in the increased mesangial matrix.</p> <p>Conclusions</p> <p>It is reported that acute and chronic PAN progressively increase PD-ECGF expression and following induction of angiogenesis in the affected glomeruli.</p

Estimation of bremsstrahlung photon fluence from aluminum by artificial neural network

Background: As bremsstrahlung photon beam fluence is important parameter to be known in a photonuclear reaction experiment as the number of produced particle is strongly depends on photon fluence. Materials and Methods: Photon production yield from different thickness of aluminum target has been estimated using artificial neural network (ANN) model. Target thickness and incoming electron energy has been used as input in ANN model and the photon fluence was output. Results: The results were estimated using ANN model for three different thickness and compared with the results obtained by EGS (Electron Gamma Shower) simulation. Conclusion: It can be concluded from this work that the bremsstrahlung photon fluence can be obtained using ANN model

Approximation Algorithms for Capacitated k-Median and Scheduling with Resource and Precedence Constraints

This thesis proposes approximation algorithms for two combinatorial optimization problems: 1) Capacitated k-Median, and 2) Scheduling with Resource and Precedence Constraints. In the first problem, we are given a set of clients and a set of facilities in a metric space such that a set of k facilities need to be opened and each client needs to be assigned to an open facility (clustered around) to minimize the sum of client-facility distances. In addition, we have capacity constraints associated with each facility in the input to indicate the maximum number of clients that can be assigned to that facility. We give a constant-factor approximation algorithm for this problem by rounding a linear programming relaxation. In line with the previous approximation algorithms for the same problem, this is a pseudo-approximation algorithm that violates the capacities by at most a factor of (1+ epsilon). In the second problem, we have a set of jobs to be scheduled on a set of machines to minimize either the makespan of the schedule or the more general total weighted completion time. Jobs have precedence constraints between them. Each job also have a resource requirement and the total resource use of jobs running concurrently at any point in a feasible schedule should not exceed the global resource cap given in the input. We initially use a divide-and-conquer approach to obtain a O(log n)-approximation for the minimum makespan objective on identical machines. Then, we generalize the result to weighted completion time objective and uniformly related machines by combining the initial divide-and-conquer method with linear programming relaxations for these variations. Furthermore, we adapt our algorithm as a solution to an emerging problem in High Performance Computing (HPC): scheduling precedence constrained jobs under a power cap. We implement our algorithm and compare it to state-of-the-art greedy methods in a simulation environment on a variety of precedence relationships and power/performance data collected from real HPC applications. We find that our divide-and-conquer method improves performance by up to 75% compared to greedy scheduling algorithms

Local long-distance spin transport in single layer graphene spin filter

Spin transport through single layer graphene grown by chemical vapor deposition has been measured in the local measurement configuration using aluminum oxide tunnel barriers and Co electrodes. Unlike the case of non-local measurements we report positive magnetoresistance for graphene channels as long as 10 microns at room temperature. Our analysis shows that the spin diffusion length in graphene is 14 ±4 microns at room temperature, bringing us a step closer to spintronic applications based on graphene spin filters