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«Strengthening the Nation through Diversity, Innovation & Leadership in STEM San Antonio,Texas · October 3-6, 2013 Get Connected! Connect with the ...»

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The human voltage-gated proton channel (Hv1) is a 4 transmembrane domain proton-selective channel which causes efflux of protons. It is gated by membrane depolarization, lacks a traditional pore domain, and is sensitive to pH gradients. This channel plays a role in male fertility, stroke, respiratory burst, and breast cancer cell proliferation and migration. Although similar to voltage sensing domains with solved 3-dimensional structures, the Hv1 proton channel structure remains elusive. Determining the structure of Hv1 channel will serve as a template for designing new therapeutic strategies. Here, we present our progress toward solving the 3-dimensional structure of the Hv1 proton channel. We have generated a carboxy-terminal polyhistidine-tagged Hv1 channel protein which we verified by western blots. Small scale expression experiments for detergent screen and a time course study have been performed to find suitable conditions for stabilizing the Hv1 channel protein outside the cell membrane. We are analyzing the stability of protein during metal affinity chromatography and size exclusion chromatography and have begun with the crystallization trials. Furthermore, whole-cell patch-clamp electrophysiology is used as a guide for solving the structure of a functional channel. Our data demonstrates that Hv1 proton channel forms a dimer at day 2 of culture. We anticipate that purified protein, in milligram quantities, will be isolated and subjected to crystallization trials. Future experiments will focus on generating protein on a larger scale to determine the optimal conditions for crystallization and to determine the Hv1 proton channel’s 3-dimensional crystal structure.

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CRYSTALLIZATION SCREENING OF A GAMMA-AMINOBUTRYIC ACID-SENSITIVE ION CHANNEL

Heather Snell, Eric B. Gonzales.

University of North Texas Health Science Center, Fort Worth, TX.

Gamma-aminobutryic acid (GABA) is the major inhibitory neurotransmitter in the vertebrate brain, and targets include membrane proteins. The GABAA-rho receptor, a member of the Cys-loop super family of ion channels, is one of GABA’s targets and has been implicated in various retinal disorders, and, specifically, a mutation in GABAArho1 has been implicated in increased susceptibility for bipolar schizoaffective disorder. Although the 3-dimensional structure of homologues of this receptor have been solved, the GABAA-rho receptor structure remains elusive. We have identified a GABAA-rho construct that can be used to generate purified and intact protein that leads to the growth of protein crystals, a critical step toward solving the protein’s structure. GABAA-rho1 was subcloned into a baculovirus expression vector using blunt-end PCR and transfected into SF9 insect cells. Cells were harvested, and protein was isolated using metal affinity and size exclusion chromatography. A phosphate buffered saline (PBS)based running buffer was used to stabilize the purified protein. Protein crystallization trials were performed using the lipidic cubic phase technique and observed weekly for crystal formation using a stereomicroscope. GABAA-rho was isolated using metal affinity chromatography. Our size exclusion chromatography studies reveal that using a PBSbased running buffer stabilizes the pentameric arrangement of purified GABAA-rho receptor. Subsequent lipidic cubic phase crystallization trials revealed three conditions yielding birefringent protein crystals. Based on preliminary data, we have identified optimal buffer and detergent conditions to isolate and solubilize the protein and optimal crystal conditions for protein crystal formation.

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PLANT SCIENCES

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PLANT SELECTABLE-MARKER GENE DELETION USING BXB1 SITE-SPECIFIC RECOMBINATION SYSTEM

Mona Easterling, Kevin Wang, Frank Yau.

Northeastern State University, Broken Arrow, OK.

An important tool for the production of genetically modified (GM) crops is the selectable marker gene (SMG), which allows for the identification of transformed cells. Following selection, transformed plant cells can multiply and generate stably transformed plants. The SMG, usually an antibiotic or herbicide-resistance gene, will remain in the genome of GM crops. Both regulatory agencies and the public have raised food safety and environmental concerns about the presence of SMGs. The most controversial concern involves horizontal transfer of the SMG coding for antibiotic resistance, which could possibly reduce the clinical effectiveness of antibiotic drugs. Mycobacteriophage Bxb1 sitespecific recombination system can be used in plant transgenesis to excise the SMG coding for antibiotic resistance.

Bxb1 is a uni-directional, site-specific recombination system. This means that once the SMG is excised, it is no longer able to reinsert into the genome. A Bxb1 site-specific, recombinase expressing, autoexcision vector containing the kanamycin resistant gene nptll was created in our lab, electroporated into Agrobacterium strain LBA4404, and used in tobacco leaf disc transformation. Activation of the seed-specific promoter allowed for autoexcision of the gene cassette containing nptII and the recombinase. The cultured tissue was screened on kanamycin selection medium.

Molecular analysis including genomic DNA isolation, GUS analysis, PCR, and sequencing has been conducted.





Sequencing demonstrated successful autoexcision in first-generation seeds. Further analysis will be completed to test the effectiveness of this Bxb1 system in homozygous deletion of the antibiotic-resistance marker gene nptll in secondgeneration tissues.

COMPUTER/INFORMATION SCIENCES

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AN EFFICIENT FPGA IMPLEMENTATION FOR ELLIPTIC CURVE POINT MULTIPLICATION

Einstein Morales Sr., Dorothy Bollman.

University of Puerto Rico at Mayagüez, Mayagüez, PR.

Efficient elliptic curve cryptography (ECC) depends on efficient finite field arithmetic for speed and a sufficiently large finite field for security. The most widely studied ECC systems to date have been those over binary fields (i.e., GF(2m)) and prime fields (i.e., GF(p) where p is prime). Binary fields have the advantage that arithmetic in the ground field GF(2) is very simple, but reduction modulo of an irreducible polynomial can be costly. Prime fields have the advantage that there is no need for reduction modulo an irreducible polynomial; however, arithmetic modulo p using the standard method of division by p can be costly. In this work, we implement elliptic curve point multiplication on an FPGA over a prime field GF(p) where p is a pseudo Mersenne prime having the same number of bits as the NIST-recommended field GF(2233). We use an improved method for multiplication modulo p, and we compare performance to recent results for an FPGA implementation of elliptic curve point multiplication over a GF(2233).

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University of Texas at El Paso, El Paso, TX.

In multi-criteria decision making, decisions are made based on multiple criteria that can be conflicting and nonhomogenously satisfied. By using fuzzy (non-additive) measures, it is possible to create a model that incorporates the preference relations of all possible subsets of criteria. In practice, identifying fuzzy measures is a difficult task. It is necessary to have an automated process that can extract the fuzzy measures from previous decisions by human experts. A hybrid optimization approach has been proposed, using bees algorithm and an interval constraint solver. In this work, we present 3 versions of this approach, with each version representing variations on the order and number of times both the bees algorithm and the constraint solver are called. We also test each of these versions with both toy examples and a real-world scenario: software quality assessment (SQA). The results showed that this approach

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helps predict software quality consistently with over 60% accuracy, which is as accurate as previous approaches to SQA using machine learning.

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MULTIEXPERT, MULTICRITERIA DECISION MAKING

Joel Henderson1, Martine Ceberio1, Stefano Bistarelli2.

University of Texas at El Paso, El Paso, TX, 2University of Perugia, Perugia, IT.

1 Expert analysis and decisions are highly valued assets in a wide variety of fields, from social services to grant funding committees. However, the use of experts can be prohibitive due to either lack of availability or cost. As such, it is desirable to be able to replicate such decisions. There are many obstacles that impede an accurate simulation of expert decisions. For example, despite looking at the same information, 2 experts may disagree on the decisions. Moreover, a single expert may make inconsistent decisions across similar scenarios. In this work, we focus on multicriteria decision making in the case of multiple experts. We examine how multicriteria decision making techniques can address the multiexperts dimension of the problem, as well as how argumentation networks can inform us about how to aggregate the multiple experts’ decisions. Questions that we consider include how to predict best decisions based on multiexperts’ prior decision data and how to use that knowledge to be able to predict and diffuse disagreements in group decision making. We look at experts’ decision data in the area of software quality assessment, and we analyze automated decisions that result from using nondiscriminatory techniques, i.e., techniques that take all decisions, even conflicting, into account with the same importance. We reconsider these data, explore the use of argumentation networks, and reflect on the relevance of such an approach. We report the results of our preliminary observations and we propose directions for future work.

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GENETIC ALGORITHM FOR CRYPTANALYSIS ON SUBSTITUTION CIPHERS

Jose Nieves Jr., Aldredo Cruz.

Polytechnic University of Puerto Rico, San Juan, PR.

A genetic algorithm (GA) is a search method based on natural selection and genetic inheritance. Cryptology encompasses cryptography and cryptanalysis. Cryptography is the process of protecting information by encrypting it into an unreadable format. Cryptanalysis is the process of obtaining the original message from an encrypted message without knowledge of the key. Here, the use of genetic algorithms to solve classical problems that arise in cryptology is investigated to determine its benefits. More specifically, how the use of genetic algorithms may lead to efficient cryptanalysis of substitution ciphers, which may be present in modern symmetric cryptographic systems. Frequency analysis is used in the fitness function to measure the performance of each key generated by the genetic algorithm.

Different parameters and techniques for the cross-over, mutation, and parent selection are explored. If the GA-based approach proves successful, it could lead to faster, more automated cryptanalysis techniques.

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PRIVACY PRESERVATION CONSTRUCTS FOR JSON IN THE CONTEXT OF HEALTH INFORMATION SYSTEMS

Hiva Samadian, Amirhossein Chinaei.

University of Puerto Rico at Mayagüez, Mayagüez, PR.

JavaScript Object Notation (JSON), a data-interchange language used for transmitting structured data over a network connection between a server and web application, is an alternative to XML, which underlies many Internet applications, including electronic healthcare information systems. JSON suffers from the lack of mechanisms to support user-centered privacy preservation. This paper introduces an enhancement to JSON to support privacy preservation corresponding to discretionary access control in health information systems. A mechanism has been introduced by which one can define privacy policies as JSON tree structure nodes. Obviously, any mechanism to define privacy policies in JSON needs to be supported by the query language. Hence, we have also proposed a simple extension onto Javs Query Language (JaQL). We will implement a prototype of this solution. Our extensive experiments will prove that our privacy preservation approach does not impose a significant overhead with respect to query execution time in JaQL.

304 GRADUATE POSTER ABSTRACTS

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PEDIGREE EVALUATOR

Mario Zuniga, Andres Figueroa.

University of Texas-Pan American, Edinburg, TX.

Collecting family history to find inherited traits is a fundamental procedure in human genetics. A pedigree is a genealogical graph or table that represents relationships between individuals. Pedigrees can be used in a clinical setting, such as genetic counseling sessions or genetic evaluations, and in genetic research. This includes risk information for future pregnancies or relatives who are currently unaffected but who are at risk for developing a disorder based on family history information. Pedigrees are essential to identify and discover genes that are involved in the development of genetic disorders. Pedigrees are also essential to genetic counseling. Genetic counselors usually draw pedigrees by hand or with the assistance of general drawing software such as Microsoft PowerPoint.

This handwriting procedure is usually time-consuming and may lead to a mess when pedigrees are later modified.

We are introducing Pedigree Evaluator. Pedigree Evaluator is a user-friendly, Java-based application for pedigree data analysis. Similar commercial products are expensive and do not execute on different platforms. Pedigree Evaluator provides automatic pedigree drawing tools. Pedigree Evaluator is not only a tool to draw pedigrees but also a complete database package for pedigree management, clinical data management, import/export pedigree modules, and user configurable pedigree views. (The authors acknowledge the National Science Foundation (grants CNSand CNS-0940575) for its support.) EDUCATION

OTHER EDUCATION

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META ANALYSIS OF STUDENT IDENTITY AND AGENCY IN CRITICAL MATHEMATICS EDUCATION

Gabriela Vargas, Rochelle Gutierrez.

University of Illinois at Urbana-Champaign, Champaign, IL.



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