Coupling in silico and in vitro analysis of peptide-MHC binding:a bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes

The ability to define and manipulate the interaction of peptides with MHC molecules has immense immunological utility, with applications in epitope identification, vaccine design, and immunomodulation. However, the methods currently available for prediction of peptide-MHC binding are far from ideal. We recently described the application of a bioinformatic prediction method based on quantitative structure-affinity relationship methods to peptide-MHC binding. In this study we demonstrate the predictivity and utility of this approach. We determined the binding affinities of a set of 90 nonamer peptides for the MHC class I allele HLA-A*0201 using an in-house, FACS-based, MHC stabilization assay, and from these data we derived an additive quantitative structure-affinity relationship model for peptide interaction with the HLA-A*0201 molecule. Using this model we then designed a series of high affinity HLA-A2-binding peptides. Experimental analysis revealed that all these peptides showed high binding affinities to the HLA-A*0201 molecule, significantly higher than the highest previously recorded. In addition, by the use of systematic substitution at principal anchor positions 2 and 9, we showed that high binding peptides are tolerant to a wide range of nonpreferred amino acids. Our results support a model in which the affinity of peptide binding to MHC is determined by the interactions of amino acids at multiple positions with the MHC molecule and may be enhanced by enthalpic cooperativity between these component interactions.

Analysis of Spatial-temporal Dynamics in the System of Economic Security of Different Subjects of Economic Management

The importance to solve the problem of spatial-temporal dynamics analysis in the system of economic security of different subjects of economic management is substantiated. Various methods and approaches for carrying out analysis of spatial-temporal dynamics in the system of economic security are considered. The basis of the generalized analysis of spatial-temporal dynamics in economic systems is offered.

Quantitative pathological changes in the cerebellum of multiple system atrophy

Multiple system atrophy (MSA) is a rare neurodegenerative disorder associated with parkinsonism, ataxia, and autonomic dysfunction. Its pathology is primarily subcortical comprising vacuolation, neuronal loss, gliosis, and α-synuclein-immunoreactive glial cytoplasmic inclusions (GO). To quantify cerebellar pathology in MSA, the density and spatial pattern of the pathological changes were studied in α-synuclein-immunolabelled sections of the cerebellar hemisphere in 10 MSA and 10 control cases. In MSA, densities of Purkinje cells (PC) were decreased and vacuoles in the granule cell layer (GL) increased compared with controls. In six MSA cases, GCI were present in cerebellar white matter. In the molecular layer (ML) and GL of MSA, vacuoles were clustered, the clusters exhibiting a regular distribution parallel to the edge of the folia. Purkinje cells were randomly or regularly distributed with large gaps between surviving cells. Densities of glial cells and surviving neurons in the ML and surviving cells and vacuoles in the GL were negatively correlated consistent with gliosis and vacuolation in response to neuronal loss. Principal components analysis (PCA) suggested vacuole densities in the ML and vacuole density and cell losses in the GL were the main source of neuropathological variation among cases. The data suggest that: (1) cell losses and vacuolation of the GCL and loss of PC were the most significant pathological changes in the cases studied, (2) pathological changes were topographically distributed, and (3) cerebellar pathology could influence cerebral function in MSA via the cerebello-dentato-thalamic tract.

Cross-country and inter-temporal analysis of Supply Chain Integration (SCI): China, Hungary and the Netherlands - changes in SCI from 1996 to 2008

Using plant level data from a global survey with multiple time frames, one begun in the late 1990s, this paper introduces measures of supply chain integration and discusses the dynamic relationship between the level of integration and a set of internal and external performance measurements. Specifically, data from Hungary, The Netherlands and The People’s Republic of China are used in the analyses. The time frames considered range from the late 1990s till 2009, encompassing major changes and transitions. Our results seem to indicate that SCI has an underlying structure of four sets of indicators, namely: (1) delivery frequency from the supplier or to the customer; (2) sharing internal processes with suppliers; (3) sharing internal processes with buyers and (4) joint facility location with partners. The differences between groups in terms of several performance measures proved to be small, being mostly statistically insignificant - but looking at the ANOVA table we can conclude that in this sample of companies those having joint location with their partners seem to outperform others.

Magyar egyetemi hallgatók vállalkozási attitűdjei és az attitűdöket befolyásoló tényezők elemzése a GUESSS-felmérés adatai alapján - Kik is akarnak ténylegesen vállalkozni? (Entrepreneurial attitudes of the Hungarian students and the analysis of the factors influencing attitudes based on the datas of GUESSS survey – Who want to undertake really?)

A vállalkozóvá válás meghatározó tényezőinek kutatása szakmai berkekben leginkább a Szent Grál keresésére emlékeztet: már lassan azt sem tudjuk, hogy egyáltalán léteznek-e ilyen tényezők. A kutatást nehezítik a többnyire önbevallásos kérdésekre adott torzított válaszok, a szóba jöhető tényezők számossága és a vállalkozói motivációk heterogenitása a különböző demográfiai karakterisztikákkal rendelkező népesség körében. Az egyetemi hallgatók körében némileg egyszerűbb a vizsgálat, hiszen ez egy relatíve homogén minta. Ugyanakkor itt a leginkább áttételesek a hatások, és ráadásul nem a tényleges vállalkozóvá válás, hanem többnyire csak a szándékok tesztelhetők. A vállalkozóvá válás szándékát Bandura társadalmi megismerés-elmélete, Shapero elmozduláselmélete és az Ajzen-féle tervezett magatartás elmélet alapján felállított koncepcionális modell keretén belül vizsgálják és elemzik a szerzők. Arra keresik a választ, hogy az egyes vállalkozói tulajdonságok, az egyetemi környezeti tényezők és a családi háttér hogyan hatnak a vállalkozóvá válásra. A teszteléshez a 21 országra kiterjedő 2011-es GUESSS-felmérésből a magyar egyetemi/ főiskolai hallgatók 5224-es erősségű mintáját használták fel. A multimoniális regressziós vizsgálat eredményei megerősítik, hogy a vállalkozói tulajdonságok és a családban levő vállalkozó megléte mellett a vállalkozói oktatás is pozitívan befolyásolják a vállalkozásindítási szándékot. A klaszterelemzés rámutatott arra, hogy a vállalkozói szándékok, az erre ható tényezők, továbbá a választott szak és más demográfiai tényezők szempontjából a hallgatók meglehetősen heterogének. _______ The search for the determining factors to become an entrepreneur is something like searching for the Holy Grail: After many decades we do not even know if these factors exist or not. The research is difficult because the questionnaires are self esteem, the potential influential factors are numerous, and the motivations do vary across the different cohorts of population. It is easier to conduct a survey amongst university students since this sample is relatively homogenous. At the same times, the determining factors to become an entrepreneur cannot be really tested; the authors can examine mostly the attitudes and the intentions. The conceptual model of entrepreneurial intentions, developed in the paper, based on Bandura, Shaper and Ajzen. The paper is testing eight hypotheses about the influential factors of entrepreneurial intentions such as entrepreneurial traits, the university environment, and the family background. For testing the hypothesis they use a sample of 5224 Hungarian students from the GUESSS 2011 survey. According to the multinomial regression, entrepreneurial intentions are positively influenced by certain entrepreneurial traits, entrepreneur in the family, and entrepreneurship courses at the higher education institutions. The cluster analysis results underline the heterogeneity of the students in terms of entrepreneurial intentions, gender, and the major field of studies

A frame analysis of the leadership styles of dental and medical school deans

The purpose of this study was to determine how dental and medical school deans perceived their own leadership styles and how many management/leadership perspectives they used when approaching a problem. A descriptive and correlational study was conducted which examined the leadership orientations or "frames" utilized by these deans. Four frames--the structural, the human resource, the political, and the symbolic--emerged from leadership studies which described the behavior of leaders in organizational actions and problem solving.^ Employing the repeated measures ANCOVA, it was found that there were no significant interactions between type of dean and perceptions or perspectives. However, the main effects of both leadership style perceptions and the use of perspectives were significant. This indicated that over the total sample of deans, both perceptions and perspectives were used differently; the deans perceived themselves and used perspectives the highest for the human resource frame and the lowest for the political frame. Also, dental deans' mean use overall of the four perspective frames was higher than the medical deans. In addition to the ANCOVA, t-tests performed on perceptions revealed that the deans perceived the frames differently in three human resource items. Pearson's correlations indicated that for the combined sample of deans, significant negative correlations existed when the human resource or symbolic frame was compared to the structural frame. All of the deans used multiple frames, allowing them to re-frame or combine frames according to the situation. ^

Sequence analysis of complementary DNAs encoding C3 in the nurse shark ({\it Ginglymostoma cirratum\/})

Mammalian C3 is a pivotal complement protein, encoded for by a single gene. In some vertebrate species multiple C3 isoforms are products of different C3 genes. The goal of this study was to determine whether multiple genes encode for shark C3. A protocol was developed for the isolation of mRNA from shark blood for the isolation of C3 cDNA clones. RT-PCR amplification of mRNA, using sense (GCGEQNM) and antisense (TWLTAYV) primers encoding conserved regions of human C3, yielded 21 clones. The C3-like clones isolated shared 97% similarity with each other and 40% similarity to human C3. RACE-PCR amplification of shark liver RNA, using gene specific primers, yielded products ranging from 1800bp to 3000bp. Deduced amino acid sequence, corresponding to 408bp of the 1800bp fragment, was obtained which showed 51% similarity to human C3. These results suggest that nurse shark C3 might be encoded for by more than one gene. ^

Comparative analysis of a moderating and mediating model of stress, appraisal, and coping in Hispanic and non-Hispanic Alzheimer's disease caregivers

This dissertation utilizes a cross-sectional study to examine the phenomenon of caregiving within a theoretically grounded stress, appraisal, and coping model. Hispanic and non-Hispanic caregivers were studied to examine the factors associated with variance in caregiver appraisal, coping, and outcomes of caregiving strain (depression and somatic complaints) and caregiving gain (life satisfaction, mastery, and personal gain). A purposive sampling strategy was used to recruit 204 Alzheimer's disease caregivers in South Florida. A self-report questionnaire was used to collect demographic data, and to measure stress, appraisal, coping, and psychological well-being of caregivers. Regression equations were developed to compare moderating and mediating models of appraisal and coping. Emotion-focused coping skills were found to significantly moderate the effects of stress (F [1,195] = 4.62, p < .05), explaining approximately 21% of the variance in satisfaction was found to moderate the effects of stress (F [1,195] = 7.09; p < .05), explaining approximately 27% of the variance in personal gain and approximately 8% of the variance in life satisfaction (F [1,195] = 4.14; p < .05). Appraisal of Burden was found to significantly mediate the effects of stress, explaining approximately 30% of the variance in somatic complaints (F [1,196] = 31.60; p < .001) and 32% of the variance in depression (F [1,196] = 38.18; p < .001). The results of the analyses indicate that appraisal and coping skills are important variables in the stress process. The results of this study underscore the importance of accounting for positive and negative outcomes in providing a fuller understanding of the stress, appraisal and coping process of Alzheimer's Disease caregivers. ^

Fiscal and organizational determinants of transportation outcomes: A quantitative and qualitative analysis of sustainability factors

Federal transportation legislation in effect since 1991 was examined to determine outcomes in two areas: (1) The effect of organizational and fiscal structures on the implementation of multimodal transportation infrastructure, and (2) The effect of multimodal transportation infrastructure on sustainability. Triangulation of methods was employed through qualitative analysis (including key informant interviews, focus groups and case studies), as well as quantitative analysis (including one-sample t-tests, regression analysis and factor analysis). ^ Four hypotheses were directly tested: (1) Regions with consolidated government structures will build more multimodal transportation miles: The results of the qualitative analysis do not lend support while the results of the quantitative findings support this hypothesis, possibly due to differences in the definitions of agencies/jurisdictions between the two methods. (2) Regions in which more locally dedicated or flexed funding is applied to the transportation system will build a greater number of multimodal transportation miles: Both quantitative and qualitative research clearly support this hypothesis. (3) Cooperation and coordination, or, conversely, competition will determine the number of multimodal transportation miles: Participants tended to agree that cooperation, coordination and leadership are imperative to achieving transportation goals and objectives, including targeted multimodal miles, but also stressed the importance of political and financial elements in determining what ultimately will be funded and implemented. (4) The modal outcomes of transportation systems will affect the overall health of a region in terms of sustainability/quality of life indicators: Both the qualitative and the quantitative analyses provide evidence that they do. ^ This study finds that federal legislation has had an effect on the modal outcomes of transportation infrastructure and that there are links between these modal outcomes and the sustainability of a region. It is recommended that agencies further consider consolidation and strengthen cooperation efforts and that fiscal regulations are modified to reflect the problems cited in qualitative analysis. Limitations of this legislation especially include the inability to measure sustainability; several measures are recommended. ^

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

An exergy based engineering and economic analysis of sustainable building

To achieve the goal of sustainable development, the building energy system was evaluated from both the first and second law of thermodynamics point of view. The relationship between exergy destruction and sustainable development were discussed at first, followed by the description of the resource abundance model, the life cycle analysis model and the economic investment effectiveness model. By combining the forgoing models, a new sustainable index was proposed. Several green building case studies in U.S. and China were presented. The influences of building function, geographic location, climate pattern, the regional energy structure, and the technology improvement potential of renewable energy in the future were discussed. The building’s envelope, HVAC system, on-site renewable energy system life cycle analysis from energy, exergy, environmental and economic perspective were compared. It was found that climate pattern had a dramatic influence on the life cycle investment effectiveness of the building envelope. The building HVAC system energy performance was much better than its exergy performance. To further increase the exergy efficiency, renewable energy rather than fossil fuel should be used as the primary energy. A building life cycle cost and exergy consumption regression model was set up. The optimal building insulation level could be affected by either cost minimization or exergy consumption minimization approach. The exergy approach would cause better insulation than cost approach. The influence of energy price on the system selection strategy was discussed. Two photovoltaics (PV) systems—stand alone and grid tied system were compared by the life cycle assessment method. The superiority of the latter one was quite obvious. The analysis also showed that during its life span PV technology was less attractive economically because the electricity price in U.S. and China did not fully reflect the environmental burden associated with it. However if future energy price surges and PV system cost reductions were considered, the technology could be very promising for sustainable buildings in the future.

An investigation of multiple pathways of developmental intervention change

Convergence among treatment, prevention, and developmental intervention approaches has led to the recognition of the need for evaluation models and research designs that employ a full range of evaluation information to provide an empirical basis for enhancing the efficiency, efficacy, and effectiveness of prevention and positive development interventions. This study reports an investigation of a positive youth development program using an Outcome Mediation Cascade (OMC) evaluation model, an integrated model for evaluating the empirical intersection between intervention and developmental processes. The Changing Lives Program (CLP) is a community supported positive youth development intervention implemented in a practice setting as a selective/indicated program for multi-ethnic, multi-problem at risk youth in urban alternative high schools. This study used a Relational Data Analysis integration of quantitative and qualitative data analysis strategies, including the use of both fixed and free response measures and a structural equation modeling approach, to construct and evaluate the hypothesized OMC model. Findings indicated that the hypothesized model fit the data (χ2 (7) = 6.991, p = .43; RMSEA = .00; CFI = 1.00; WRMR = .459). Findings also provided preliminary evidence consistent with the hypothesis that in addition to having effects on targeted positive outcomes, PYD interventions are likely to have progressive cascading effects on untargeted problem outcomes that operate through effects on positive outcomes. Furthermore, the general pattern of findings suggested the need to use methods capable of capturing both quantitative and qualitative change in order to increase the likelihood of identifying more complete theory informed empirically supported models of developmental intervention change processes.

A Q factor analysis of college undergraduate students' study behaviors

The purpose of this study was to better understand the study behaviors and habits of university undergraduate students. It was designed to determine whether undergraduate students could be grouped based on their self-reported study behaviors and if any grouping system could be determined, whether group membership was related to students’ academic achievement. A total of 152 undergraduate students voluntarily participated in the current study by completing the Study Behavior Inventory instrument. All participants were enrolled in fall semester of 2010 at Florida International University. The Q factor analysis technique using principal components extraction and a varimax rotation was used in order to examine the participants in relation to each other and to detect a pattern of intercorrelations among participants based on their self-reported study behaviors. The Q factor analysis yielded a two factor structure representing two distinct student types among participants regarding their study behaviors. The first student type (i.e., Factor 1) describes proactive learners who organize both their study materials and study time well. Type 1 students are labeled “Proactive Learners with Well-Organized Study Behaviors”. The second type (i.e., Factor 2) represents students who are poorly organized as well as being very likely to procrastinate. Type 2 students are labeled Disorganized Procrastinators. Hierarchical linear regression was employed to examine the relationship between student type and academic achievement as measured by current grade point averages (GPAs). The results showed significant differences in GPAs between Type 1 and Type 2 students at the .05 significance level. Furthermore, student type was found to be a significant predictor of academic achievement beyond and above students’ attribute variables including sex, age, major, and enrollment status. The study has several implications for educational researchers, practitioners, and policy makers in terms of improving college students' learning behaviors and outcomes.

Fiscal decentralization and development: An analysis of city governments in Argentina and Mexico, 1980--2010

This dissertation examines local governments' efforts to promote economic development in Latin America. The research uses a mixed method to explore how cities make decisions to innovate, develop, and finance economic development programs. First, this study provides a comparative analysis of decentralization policies in Argentina and Mexico as a means to gain a better understanding of the degree of autonomy exercised by local governments. Then, it analyzes three local governments each within the province of Santa Fe, Argentina and the State of Guanajuato, Mexico. The principal hypothesis of this dissertation is that if local governments collect more own-source tax revenue, they are more likely to promote economic development and thus, in turn, promote growth for their region. ^ By examining six cities, three of which are in Santa Fe—Rosario, Santa Fe (capital) and Rafaela—and three in Guanajuato—Leon, Guanajuato (capital) and San Miguel de Allende, this dissertation provides a better understanding of public finances and tax collection efforts of local governments in Latin America. Specific attention is paid to each city's budget authority to raise new revenue and efforts to promote economic development. The research also includes a large statistical dataset of Mexico's 2,454 municipalities and a regression analysis that evaluates local tax efforts on economic growth, controlling for population, territorial size, and the professional development. In order to generalize these results, the research tests these discoveries by using statistical data gathered from a survey administered to Latin American municipal officials. ^ The dissertation demonstrates that cities, which experience greater fiscal autonomy measured by the collection of more own-source revenue, are better able to stimulate effective economic development programs, and ultimately, create jobs within their communities. The results are bolstered by a large number of interviews, which were conducted with over 100 finance specialists, municipal presidents, and local authorities. The dissertation also includes an in-depth literature review on fiscal federalism, decentralization, debt financing and local development. It concludes with a discussion of the findings of the study and applications for the practice of public administration.^

Combination of 16S rRNA variable regions provides a detailed analysis of bacterial community dynamics in the lungs of cystic fibrosis patients

Chronic bronchopulmonary bacterial infections remain the most common cause of morbidity and mortality among patients with cystic fibrosis (CF). Recent community sequencing work has now shown that the bacterial community in the CF lung is polymicrobial. Identifying bacteria in the CF lung through sequencing can be costly and is not practical for many laboratories. Molecular techniques such as terminal restriction fragment length polymorphism or amplicon length heterogeneity-polymerase chain reaction (LH-PCR) can provide many laboratories with the ability to study CF bacterial communities without costly sequencing. The aim of this study was to determine if the use of LH-PCR with multiple hypervariable regions of the 16S rRNA gene could be used to identify organisms found in sputum DNA. This work also determined if LH-PCR could be used to observe the dynamics of lung infections over a period of time. Nineteen samples were analysed with the V1 and the V1_V2 region of the 16S rRNA gene. Based on the amplicon size present in the V1_V2 region, Pseudomonas aeruginosa was confirmed to be in all 19 samples obtained from the patients. The V1 region provided a higher power of discrimination between bacterial profiles of patients. Both regions were able to identify trends in the bacterial population over a period of time. LH profiles showed that the CF lung community is dynamic and that changes in the community may in part be driven by the patient's antibiotic treatment. LH-PCR is a tool that is well suited for studying bacterial communities and their dynamics.