Matching Items (171)
Description
One of the major challenges that were yet to be solved for solid phase peptide synthesis was the lack of an efficient peptide sequencing technique that was less hazardous, easier to perform , and was more cost-effective. Sequencing peptides were held important in the field of Chemistry and Biochemistry because it aided in drug discovery, finding ligands that bind to a specific target protein and finding alternative agents in transporting molecules to its desired location. Therefore, the overall purpose of this experiment was to develop a method of solid phase sequencing technique that was more environmental friendly, sequences at a faster rate, and was more cost-effective.
ContributorsCordovez, Lalaine Anne Ordiz (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Legutki, Joseph Barten (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2014-05
Description
AMPylation is a post-translation modification that has an important role in the survival of many bacterial pathogens by affecting the host cell's molecular signaling. In the course of studying this intercellular manipulation, there has only been modest progression in the identification of the enzymes with AMPylation capabilities (AMPylators) and their respective targets. The reason for these minimal developments is the inability to analyze a large subset of these proteins. Therefore, to increase the efficiency of the identification and characterization of the proteins, Yu et al developed a high-throughput non-radioactive discovery platform using Human Nucleic Acid Programmable Protein Arrays (NAPPA) and a validation platform using bead-based assays. The large-scale unbiased screening of potential substrates for two bacterial AMPylators containing Fic domain, VopS and IbpAFic2, had been performed and dozens of novel substrates were identified and confirmed. With the efficiency of this method, the platform was extended to the identification of novel substrates for a Legionella virulence factor, SidM, containing a different adenylyl transferase domain. The screening was performed using NAPPA arrays comprising of 10,000 human proteins, the active AMPylator SidM, and its inactive D110/112A mutant as a negative control. Many potential substrates of SidM were found, including Rab GTPases and non-GTPase proteins. Several of which have been confirmed with the bead-based AMPylation assays.
ContributorsGraves, Morgan C. (Author) / LaBaer, Joshua (Thesis director) / Qiu, Ji (Committee member) / Yu, Xiaobo (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2013-05
Description
We, a team of students and faculty in the life sciences at Arizona State University (ASU), currently teach an Introduction to Biology course in a Level 5, or maximum-security unit with the support of the Arizona Department of Corrections and the Prison Education Program at ASU. This course aims to enhance current programs at the unit by offering inmates an opportunity to practice literacy and math skills, while also providing exposure to a new academic field (science, and specifically biology). Numerous studies, including a 2005 study from the Arizona Department of Corrections (ADC), have found that vocational programs, including prison education programs, reduce recidivism rates (ADC 2005, Esperian 2010, Jancic 1988, Steurer et al. 2001, Ubic 2002) and may provide additional benefits such as engagement with a world outside the justice system (Duguid 1992), the opportunity for inmates to revise personal patterns of rejecting education that they may regret, and the ability of inmate parents to deliberately set a good example for their children (Hall and Killacky 2008). Teaching in a maximum security prison unit poses special challenges, which include a prohibition on most outside materials (except paper), severe restrictions on student-teacher and student-student interactions, and the inability to perform any lab exercises except limited computer simulations. Lack of literature discussing theoretical and practical aspects of teaching science in such environment has prompted us to conduct an ongoing study to generate notes and recommendations from this class through the use of surveys, academic evaluation of students' work and ongoing feedback from both teachers and students to inform teaching practices in future science classes in high-security prison units.
ContributorsLarson, Anika Jade (Author) / Mor, Tsafrir (Thesis director) / Brownell, Sara (Committee member) / Lockard, Joe (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
The purpose of this project was to identify proteins associated with the migration and invasion of non-transformed MCF10A mammary epithelial cells with ectopically expressed missense mutations in p53. Because of the prevalence of TP53 missense mutations in basal-like and triple-negative breast cancer tumors, understanding the effect of TP53 mutations on the phenotypic expression of human mammary epithelial cells may offer new therapeutic targets for those currently lacking in treatment options. As such, MCF10A mammary epithelial cells ectopically overexpressing structural mutations (G245S, H179R, R175H, Y163C, Y220C, and Y234C) and DNA-binding mutations (R248Q, R248W, R273C, and R273H) in the DNA-binding domain were selected for use in this project. Overexpression of p53 in the mutant cell lines was confirmed by western blot and q-PCR analysis targeting the V5 epitope tag present in the pLenti4 vector used to transduce TP53 into the mutant cell lines. Characterization of the invasion and migration phenotypes resulting from the overexpression of p53 in the mutant cell lines was achieved using transwell invasion and migration assays with Boyden chambers. Statistical analysis showed that three cell lines—DNA-contact mutants R248W and R273C and structural mutant Y220C—were consistently more migratory and invasive and demonstrated a relationship between the migration and invasion properties of the mutant cell lines. Two families of proteins were then explored: those involved in the Epithelial-Mesenchymal Transition (EMT) and matrix metalloproteinases (MMPs). Results of q-PCR and immunofluorescence analysis of epithelial marker E-cadherin and mesenchymal proteins Slug and Vimentin did not show a clear relationship between mRNA and protein expression levels with the migration and invasiveness phenotypes observed in the transwell studies. Results of western blotting, q-PCR, and zymography of MMP-2 and MMP-9 also did not show any consistent results indicating a definite relationship between MMPs and the overall invasiveness of the cells. Finally, two drugs were tested as possible treatments inhibiting invasiveness: ebselen and SBI-183. These drugs were tested on only the most invasive of the MCF10A p53 mutant cell lines (R248W, R273C, and Y220C). Results of invasion assay following 30 μM treatment with ebselen and SBI-183 showed that ebselen does not inhibit invasiveness; SBI-183, however, did inhibit invasiveness in all three cell lines tested. As such, SBI-183 will be an important compound to study in the future as a treatment that could potentially serve to benefit triple-negative or basal-like breast cancer patients who currently lack therapeutic treatment options.
ContributorsZhang, Kathie Q (Author) / LaBaer, Joshua (Thesis director) / Anderson, Karen (Committee member) / Gonzalez, Laura (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as “economic epidemiology” or “epidemiological economics,” the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.
ContributorsPerrings, Charles (Author) / Castillo-Chavez, Carlos (Author) / Chowell-Puente, Gerardo (Author) / Daszak, Peter (Author) / Fenichel, Eli P. (Author) / Finnoff, David (Author) / Horan, Richard D. (Author) / Kilpatrick, A. Marm (Author) / Kinzig, Ann (Author) / Kuminoff, Nicolai (Author) / Levin, Simon (Author) / Morin, Benjamin (Author) / Smith, Katherine F. (Author) / Springborn, Michael (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / W.P. Carey School of Business (Contributor) / Economics (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2015-12-01
Description
Preserving a system’s viability in the presence of diversity erosion is critical if the goal is to sustainably support biodiversity. Reduction in population heterogeneity, whether inter- or intraspecies, may increase population fragility, either decreasing its ability to adapt effectively to environmental changes or facilitating the survival and success of ordinarily rare phenotypes. The latter may result in over-representation of individuals who may participate in resource utilization patterns that can lead to over-exploitation, exhaustion, and, ultimately, collapse of both the resource and the population that depends on it. Here, we aim to identify regimes that can signal whether a consumer–resource system is capable of supporting viable degrees of heterogeneity. The framework used here is an expansion of a previously introduced consumer–resource type system of a population of individuals classified by their resource consumption. Application of the Reduction Theorem to the system enables us to evaluate the health of the system through tracking both the mean value of the parameter of resource (over)consumption, and the population variance, as both change over time. The article concludes with a discussion that highlights applicability of the proposed system to investigation of systems that are affected by particularly devastating overly adapted populations, namely cancerous cells. Potential intervention approaches for system management are discussed in the context of cancer therapies.
ContributorsKareva, Irina (Author) / Morin, Benjamin (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2015-02-01
Description
Background
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.
Methodology
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.
Methodology
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.
ContributorsTowers, Sherry (Author) / Afzal, Shehzad (Author) / Bernal, Gilbert (Author) / Bliss, Nadya (Author) / Brown, Shala (Author) / Espinoza, Baltazar (Author) / Jackson, Jasmine (Author) / Judson-Garcia, Julia (Author) / Khan, Maryam (Author) / Lin, Michael (Author) / Mamada, Robert (Author) / Moreno, Victor (Author) / Nazari, Fereshteh (Author) / Okuneye, Kamaldeen (Author) / Ross, Mary (Author) / Rodriguez, Claudia (Author) / Medlock, Jan (Author) / Ebert, David (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / Mary Lou Fulton Teachers College (Contributor) / Educational Leadership and Innovation (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Global Security Initiative (Contributor)
Created2015-06-11
Description
Background
Seroepidemiological studies before and after the epidemic wave of H1N1-2009 are useful for estimating population attack rates with a potential to validate early estimates of the reproduction number, R, in modeling studies.
Methodology/Principal Findings
Since the final epidemic size, the proportion of individuals in a population who become infected during an epidemic, is not the result of a binomial sampling process because infection events are not independent of each other, we propose the use of an asymptotic distribution of the final size to compute approximate 95% confidence intervals of the observed final size. This allows the comparison of the observed final sizes against predictions based on the modeling study (R = 1.15, 1.40 and 1.90), which also yields simple formulae for determining sample sizes for future seroepidemiological studies. We examine a total of eleven published seroepidemiological studies of H1N1-2009 that took place after observing the peak incidence in a number of countries. Observed seropositive proportions in six studies appear to be smaller than that predicted from R = 1.40; four of the six studies sampled serum less than one month after the reported peak incidence. The comparison of the observed final sizes against R = 1.15 and 1.90 reveals that all eleven studies appear not to be significantly deviating from the prediction with R = 1.15, but final sizes in nine studies indicate overestimation if the value R = 1.90 is used.
Conclusions
Sample sizes of published seroepidemiological studies were too small to assess the validity of model predictions except when R = 1.90 was used. We recommend the use of the proposed approach in determining the sample size of post-epidemic seroepidemiological studies, calculating the 95% confidence interval of observed final size, and conducting relevant hypothesis testing instead of the use of methods that rely on a binomial proportion.
Seroepidemiological studies before and after the epidemic wave of H1N1-2009 are useful for estimating population attack rates with a potential to validate early estimates of the reproduction number, R, in modeling studies.
Methodology/Principal Findings
Since the final epidemic size, the proportion of individuals in a population who become infected during an epidemic, is not the result of a binomial sampling process because infection events are not independent of each other, we propose the use of an asymptotic distribution of the final size to compute approximate 95% confidence intervals of the observed final size. This allows the comparison of the observed final sizes against predictions based on the modeling study (R = 1.15, 1.40 and 1.90), which also yields simple formulae for determining sample sizes for future seroepidemiological studies. We examine a total of eleven published seroepidemiological studies of H1N1-2009 that took place after observing the peak incidence in a number of countries. Observed seropositive proportions in six studies appear to be smaller than that predicted from R = 1.40; four of the six studies sampled serum less than one month after the reported peak incidence. The comparison of the observed final sizes against R = 1.15 and 1.90 reveals that all eleven studies appear not to be significantly deviating from the prediction with R = 1.15, but final sizes in nine studies indicate overestimation if the value R = 1.90 is used.
Conclusions
Sample sizes of published seroepidemiological studies were too small to assess the validity of model predictions except when R = 1.90 was used. We recommend the use of the proposed approach in determining the sample size of post-epidemic seroepidemiological studies, calculating the 95% confidence interval of observed final size, and conducting relevant hypothesis testing instead of the use of methods that rely on a binomial proportion.
ContributorsNishiura, Hiroshi (Author) / Chowell-Puente, Gerardo (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2011-03-24
Description
Background
Several past studies have found that media reports of suicides and homicides appear to subsequently increase the incidence of similar events in the community, apparently due to the coverage planting the seeds of ideation in at-risk individuals to commit similar acts.
Methods
Here we explore whether or not contagion is evident in more high-profile incidents, such as school shootings and mass killings (incidents with four or more people killed). We fit a contagion model to recent data sets related to such incidents in the US, with terms that take into account the fact that a school shooting or mass murder may temporarily increase the probability of a similar event in the immediate future, by assuming an exponential decay in contagiousness after an event.
Conclusions
We find significant evidence that mass killings involving firearms are incented by similar events in the immediate past. On average, this temporary increase in probability lasts 13 days, and each incident incites at least 0.30 new incidents (p = 0.0015). We also find significant evidence of contagion in school shootings, for which an incident is contagious for an average of 13 days, and incites an average of at least 0.22 new incidents (p = 0.0001). All p-values are assessed based on a likelihood ratio test comparing the likelihood of a contagion model to that of a null model with no contagion. On average, mass killings involving firearms occur approximately every two weeks in the US, while school shootings occur on average monthly. We find that state prevalence of firearm ownership is significantly associated with the state incidence of mass killings with firearms, school shootings, and mass shootings.
Several past studies have found that media reports of suicides and homicides appear to subsequently increase the incidence of similar events in the community, apparently due to the coverage planting the seeds of ideation in at-risk individuals to commit similar acts.
Methods
Here we explore whether or not contagion is evident in more high-profile incidents, such as school shootings and mass killings (incidents with four or more people killed). We fit a contagion model to recent data sets related to such incidents in the US, with terms that take into account the fact that a school shooting or mass murder may temporarily increase the probability of a similar event in the immediate future, by assuming an exponential decay in contagiousness after an event.
Conclusions
We find significant evidence that mass killings involving firearms are incented by similar events in the immediate past. On average, this temporary increase in probability lasts 13 days, and each incident incites at least 0.30 new incidents (p = 0.0015). We also find significant evidence of contagion in school shootings, for which an incident is contagious for an average of 13 days, and incites an average of at least 0.22 new incidents (p = 0.0001). All p-values are assessed based on a likelihood ratio test comparing the likelihood of a contagion model to that of a null model with no contagion. On average, mass killings involving firearms occur approximately every two weeks in the US, while school shootings occur on average monthly. We find that state prevalence of firearm ownership is significantly associated with the state incidence of mass killings with firearms, school shootings, and mass shootings.
ContributorsTowers, Sherry (Author) / Gomez-Lievano, Andres (Author) / Khan, Maryam (Author) / Mubayi, Anuj (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2015-07-02
Description
The membrane proximal region (MPR, residues 649–683) and transmembrane domain (TMD, residues 684–705) of the gp41 subunit of HIV-1’s envelope protein are highly conserved and are important in viral mucosal transmission, virus attachment and membrane fusion with target cells. Several structures of the trimeric membrane proximal external region (residues 662–683) of MPR have been reported at the atomic level; however, the atomic structure of the TMD still remains unknown. To elucidate the structure of both MPR and TMD, we expressed the region spanning both domains, MPR-TM (residues 649–705), in Escherichia coli as a fusion protein with maltose binding protein (MBP). MPR-TM was initially fused to the C-terminus of MBP via a 42 aa-long linker containing a TEV protease recognition site (MBP-linker-MPR-TM).
Biophysical characterization indicated that the purified MBP-linker-MPR-TM protein was a monodisperse and stable candidate for crystallization. However, crystals of the MBP-linker-MPR-TM protein could not be obtained in extensive crystallization screens. It is possible that the 42 residue-long linker between MBP and MPR-TM was interfering with crystal formation. To test this hypothesis, the 42 residue-long linker was replaced with three alanine residues. The fusion protein, MBP-AAA-MPR-TM, was similarly purified and characterized. Significantly, both the MBP-linker-MPR-TM and MBP-AAA-MPR-TM proteins strongly interacted with broadly neutralizing monoclonal antibodies 2F5 and 4E10. With epitopes accessible to the broadly neutralizing antibodies, these MBP/MPR-TM recombinant proteins may be in immunologically relevant conformations that mimic a pre-hairpin intermediate of gp41.
ContributorsGong, Zhen (Author) / Martin Garcia, Jose Manuel (Author) / Daskalova, Sasha (Author) / Craciunescu, Felicia (Author) / Song, Lusheng (Author) / Dorner, Katerina (Author) / Hansen, Debra (Author) / Yang, Jay-How (Author) / LaBaer, Joshua (Author) / Hogue, Brenda (Author) / Mor, Tsafrir (Author) / Fromme, Petra (Author) / Department of Chemistry and Biochemistry (Contributor) / Biodesign Institute (Contributor) / Applied Structural Discovery (Contributor) / Infectious Diseases and Vaccinology (Contributor) / Innovations in Medicine (Contributor) / Personalized Diagnostics (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2015-08-21