VictorJuiz/thesis huggingface dataset:
Picosecond Infrared Lasers (PIRL): Applications in Biodiagnostics and Towards Quantitative Mass Spectrometry
Keywords: Biodiagnosis
Desorption via Impulsive Vibrational Excitation ablation
Imaging Mass Spectrometry
Laser Ablation Electrospray Ionization
Picosecond Infrared Lasers
Quantitative Mass Spectrometry

A new concept based on the Picosecond Infrared Laser (PIRL) has been introduced to selectively excite water to directly drive ablation of biological tissue faster than any competing energy dissipation process that could damage surrounding tissue. This thesis work showed that this mechanism can be exploited for a new form of spatially resolved mass spectrometry with the prospect of near instant biodiagnostics with mass spectroscopic sensitivity. The ion source for imaging mass spectrometer was based on PIRL ablation with an electrospray pick up source to entrain the ablated species. This hybrid Picosecond Infrared Laser Assisted Electrospray Ionization (PIR-LAESI) showed a limit of detection of 100 nM and a spatial resolution of ~ 100 Îźm, limited only by the current focusing optics. The longitudinal spatial resolution is approximately determined by the absorption depth. At the wavelengths of PIRL pulse, the light is absorbed within a few microns at the ablation threshold, resulting in removal of ~ 4 Îźm thick of material per pulse, which is the size of a single cell. Most importantly no additional treatment was needed as in Matrix Assisted Laser Desorption/Ionization (MALDI). Molecular images using PIR-LAESI for both plant and animal tissues could be collected directly and matched to optical images of the same region. The image quality was compared to nanosecond LAESI versions. Smaller crater size with PIR-LAESI was noted with similar molecular image quality, indicating PIR-LAESI a more sensitive approach with higher spatial resolution. The question is how far the sensitivity can be improved. In principle, single protein detections is possible if there is no thermal fragmentation as shown in this work. New direct in vacuum sample presentation to mass spectrometry should enable this ultimate limit to single molecular detection, using an electric field for ion separation. Molecular dynamics simulation on the ablation process driven by PIRL on ionic polymer water solutions revealed the effect of electric field cannot be observed in the early stage of plume expansion but that the polymers stay intact with shedding of the water solvation layers. These results illustrate that selective excitation of the water provides the desired ablation physics.
Rural Youth within Changing Education, Formal Labour Market and Informal Economic Conditions during Post-Soviet Transition Period in the Kyrgyz Republic
Keywords: Bourdieu
Educational inequalities
International education
Post socialist education
Rural Kyrgyz youth
Youth aspirations and lives

This qualitative case study examines the experiences, expectations and aspirations of education, employment, and future prospects of a group of rural youth growing up in the postsocialist era in southern Kyrgyzstan. Despite popular conceptions that youth are the authors of their life projects with an abundance of choice (Du Bois Reymond, 1995), the socially determining categories of social class, gender, ethnicity, and place still structure these choices and shape the life chances of contemporary youth (Roberts, 2010). This study shows how the postsocialist transformation has increased the burdens and uncertainties of young people and undermined the stability and security of their futures (DeYoung, 2010; Korzh, 2014; Roche, 2014; Walker, 2011). It identifies educational and social inequalities persisting from traditional Kyrgyz and Soviet society, as well as those emerging in the post-Soviet period, and analyzes the effects of these on the experiences and aspirations of rural Kyrgyz youth. Three types of rural Kyrgyz youth emerged from the data set of the study and three illustrative cases were: the trajectory of youth from the rural intelligentsia class with aspirations for a professional future; that of youth from the emerging successful stratum of kommersants (merchants) with aspirations for an entrepreneurial future, and that of youth from the former kolkhoz (Soviet collective farm) working class, who face the precarious future of the migrant worker. These three social trajectories are explained, following Bourdieu, as manifestations of the class and gendered habitus of the rural Kyrgyz youth and their families. The findings of the study reveal the ways that the social resources of kinship-oriented families, specifically their economic, cultural, social, and symbolic forms of capital, determine rural youth experiences and future chances in postsocialist transformation in Kyrgyzstan.
Biophysical Analysis of the C9orf72 Hexanucleotide Repeat Associated with ALS/FTD
Keywords: ALS
C9orf72
CD spectroscopy
G-quadruplex
Methylation
Nucleic acid

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two extremes of a spectrum of neurodegenerative disorders. Recently, it was shown that expansion of (GGGGCC)n. (GGCCCC)n in the C9orf72 gene is the main cause of ALS/FTD. Being G-rich on one strand, and C-rich on the other strand, the C9orf72 repeat is a great candidate for secondary structure formation. To date, it has been shown that different repeats of the G-rich DNA and RNA, can form G-quadruplexes in-vitro. Our studies have been mainly focused on biophysically characterizing G-rich RNA and DNA strands, and C-rich DNA strands by using CD and UV spectroscopy and gel electrophoresis. We have shown that G-rich RNA forms parallel G-quadruplexes and C-rich DNA can form an array of secondary structures including i-motifs at acidic pH, monomolecular hairpins at basic pH and G-quadruplexes at neutral pH. This range of structure is due to the ability of cytosines to get hemiprotonated. Non-canonical structures have long been known to act as mutagenic intermediates leading to genetic instability. Therefore, biophysically assessing these structures not only may provide a basis for mechanistic pathways leading to the disease, but may help find ways to prevent the disease. One of the proposed disease mechanisms is through toxic gain-of-function where neurodegeneration is caused by formation of nuclear RNA aggregates which sequester proteins. Based on this, we also identified two proteins which exhibit structure-specific binding to the RNA G-quadruplexes. Subsequently, we offered proof-of-principle of a ligand-based therapeutic approach where TMPyP4, a G-quadruplex binding ligand, was shown to disrupt the interaction between the RNA G-quadruplexes and ASF/SF2 and hnRNPA1. Lastly, we studied the effect of methylation on the secondary structures formed by the repeat. Recently, it was shown that the repeat itself is methylated in ALS patients, which also rationalized the observed 50% transcription reduction seen in expansion carriers. We have shown that while methylation at CpG sites stabilizes the structures on both G-rich and C-rich DNA strands, hydroxymethylation destabilizes them.
DNA-mediated Gold Nanoparticle Assembly: a Universal Platform for Therapeutic and Diagnostic Applications
Keywords: Cancer therapy
Diagnostics
Gold nanoparticle
Nanoparticle
Nanoparticle assembly
Nanotechnology

Unique physicochemical properties of nanomaterials offer novel methodologies for disease treatment and diagnosis. Dynamic nanoparticle assemblies are adding an additional level of functionality and flexibility by combining multiple nanoparticle types into structures with stimuli-responsive size and surface chemistry. DNA-mediated gold nanoparticles assemblies are offering the most functional and versatile platform, which combines DNA addressability with large surface area, monodispersity, and easy functionalization of gold nanoparticles. Assembly size determines their application, with smaller nanoassemblies particularly suitable for drug delivery, and larger microassemblies used for biosensing. Despite a number of published studies, no in vivo examples or clinically ready biosensors have been reported. Therefore, the goal of this thesis was to identify the barriers for translation in both fields and to develop methods to overcome these limitations. To this end core-satellite nanoassemblies were designed for in vivo delivery, which efficiently protected loaded cargo and minimized macrophage recognition. Their controllable serum stability could be used as the mechanism of cargo release. In vivo nanoassemblies showed longer circulation half-life, improved tumour targeting, and renal bioelimination. In parallel, larger microassembly structures were combined with DNA enzyme signal amplification to generate a novel infectious pathogen biosensor. The assay was particularly suited for point-of-care setting with cheap and stable components and simple, fast, and specific colourimetric readout that could assay multiple targets in parallel. To demonstrate its clinical readiness, the assay was adapted for detection of a panel of five urinary tract infection bacteria. All targets were successfully identified in parallel at clinically relevant concentrations. Preliminary tests with E. coli patient samples confirmed clinical detection with good sensitivity and excellent specificity. This work presents a novel DNA-mediated gold nanoparticle assembly platform that is ready for in vivo translation and clinical in vitro diagnostics.
Genetics of Obsessive-compulsive Disorder: From Phenotypes to Pharmacogenetics
Keywords: Candidate genes
Genome-wide association study
Molecular genetics
Obsessive-compulsive disorder
Pharmacogenetics

Background: Obsessive-compulsive disorder (OCD) is a debilitating neuropsychiatric disorder that is characterized by a diverse clinical presentation. Evidence suggests genetic involvement in the etiology of OCD; however, genetic association studies have yielded mixed results partly due to clinical heterogeneity. Aims: We therefore investigated the genetics of OCD subphenotypes: age at onset (AAO), Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) severity score and symptom dimensions, family history of obsessive-compulsive and related disorders (OCRDs), psychiatric comorbidities, and drug response. We first examined these subphenotypes to ascertain clinically homogeneous dimensions of OCD. We then analyzed these subphenotypes and antidepressant response for genetic association to identify marker(s) for each subphenotype. Methods: The sample consists of 560 OCD individuals. For the subphenotypic analyses, admixture analysis (STATA) was performed to analyze AAO and factor analysis (SPSS) was applied to reduce the Y-BOCS symptom checklist. Family history and psychiatric comorbidity were obtained using the modified Family History Index and SCID-IV interviews respectively. The candidate gene study investigated markers, mostly in the remote regulatory regions, of 17 candidates for association with subphenotypes in 497 OCD participants. Genome-wide association study was conducted in a subset of this sample to examine AAO and Y-BOCS severity. Retrospective antidepressant response data was available in 222 OCD individuals. Statistical analyses were performed using SPSS, PLINK, and R programs, comparing genotype frequencies between different subphenotype groups. Results: We identified early (
Stabilization, Extension and Unification of the Lattice Boltzmann Method Using Information Theory
Keywords: Cavity Flow
Entropy
Information Theory
Kullback-Leibler Divergence
Lattice Boltzmann Method
Stability

A novel Lattice Boltzmann method is derived using the Principle of Minimum Discrimination Information (MinxEnt) via the minimization of Kullback-Leibler Divergence (KLD). Approximations of this method yield the single relaxation time (SRT-LBM), two relaxation time (TRT-LBM), multiple relaxation time (MRT-LBM) Lattice Boltzmann methods as well as Entropic Lattice Boltzmann Method (ELBM) and Ehrenfest Step LBM (EF-LBM). Specically it is shown that these methods can be understood as approximations of a method for constrained KLD minimization. By carrying out the actual single step Newton-Raphson minimization (MinxEnt-LBM) a more accurate and stable Lattice Boltzmann Method can be implemented. To demonstrate this, 2D Poiseulle flow, 1D shock tube and lid-driven cavity ow simulations are carried out and compared to SRT-LBM, TRT-LBM MRT-LBM and EF-LBM.
School Function In Children After Traumatic Brain Injury: Developing A New Outcome Measure
Keywords: Measurement
Pediatric
Qualitative research
Questionnaire
School function
Traumatic brain injury

Trauma remains the leading cause of morbidity and mortality for children. Traumatic brain injury (TBI) is responsible for large population-level costs, and protracted burden on family and caregivers. TBI can significantly impact a child's ability to learn and attain important educational and social milestones. Coordinated reintegration into the school environment is paramount in order to achieve optimal outcome. To date, no validated instrument exists for teachers to be able assess the function of children in school after suffering TBI. By using Food and Drug Administration guidelines on Patient Reported Outcomes (PRO), and National Institutes of Health guidelines on mixed methods research, this thesis aims to develop a validated measure of school function in children after TBI, as assessed by the educational professional most closely involved with that child's education. There are multiple intended uses of this instrument. It will serve as a means for teachers to assess the function of their injured students in the classroom. It will also serve as a vehicle to provide tailored rehabilitation services to injured students. Clinicians will be able to assess the recovery of their patients who have returned to school using this outcome measure. Finally, it will serve as a validated outcome measure for clinical trials in pediatric TBI. This work was carried out in three phases. First, qualitative research methodology was used to develop a measurement concept of school function after TBI. School function was defined as the observable traits and behavioural manifestations of multiple cognitive, psychosocial, and neurologic processes, as well as performance on in-classroom academic tasks that represent a child's ability to achieve expected academic and social milestones. The qualitative data informed the second phase of instrument development, in which items were generated and reduced to form a 95-item prototype questionnaire. In the third phase, field testing was performed in order to validate the concept of school function and further reduce items. Only 58 questionnaires were completed; much further work is necessary to achieve the goal of generating a valid and reliable instrument. When complete, it will fill a large gap in the outcome assessment of this vulnerable population.
177Lu-labeled Gold Nanoparticles for Radiation Therapy of Locally Advanced Breast Cancer
Keywords: 177Lu
Brachytherapy
Epidermal growth factor receptor (EGFR)
Gold nanoparticles
Locally advanced breast cancer (LABC)

Locally advanced breast cancer (LABC) occurs in about 10-15% of patients diagnosed with breast cancer (BC) and 30% of these patients have triple negative breast cancer (TNBC) that are often epidermal growth factor receptor (EGFR)-positive. The goal of the proposed research was design and evaluate preclinically a novel radiation nanomedicine for LABC composed of EGFR-targeted gold nanoparticles (AuNP) by covalently conjugating panitumumab and 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) complexing 177Lu incorporated into a metal-chelating polymer (MCP) (177Lu-T-AuNP) which could be used as a neoadjuvant treatment to improve the outcome of patients with LABC. 177Lu-T-AuNP were efficiently internalized by EGFR-positive BC cells and were significantly more effective than 177Lu-labeled and non-targeted (NT)-AuNP for killing these cells. For radiation treatment of EGFR-positive tumours, both 177Lu-T-AuNP and 177Lu-NT-AuNP were intratumourally (i.t.) injected into athymic mice with MDA-MB-468 BC xenografts for comparison. Biodistribution studies showed that 177Lu-T-AuNPs exhibited 2-fold higher tumour retention than 177Lu-NT-AuNPs following i.t. injection at 48 h p.i. Both forms of radiolabeled AuNP were highly effective for inhibiting tumour growth without normal organ toxicity due to local tumour retention of both form of AuNP. To minimize the displacement of 177Lu-labeled MCP from AuNP, polyethylene glycol (PEG) ligands presenting a disulfide [177Lu-DOTA-PEG-ortho-pyridyl disulfide (OPSS)], a lipoic acid (LA) [177Lu-DOTA-PEG-lipoic acid (LA)] or multi-LA [PEG-pGlu(177Lu-DOTA)8-LA4] for multivalent binding were synthesized and the stability of MCP-AuNP complexes determined. In vitro challenge study with thiol-containing molecules or human plasma, PEG-pGlu(DOTA)8-LA4-AuNP were most stable. In whole body elimination study, elimination of radioactivity due to displacement of 177Lu-MCP from AuNP in mice injected with 177Lu-DOTA-PEG-OPSS-AuNP was more rapid, indicating that 177Lu-DOTA-PEG-OPSS-AuNP was less stable than two other forms of 177Lu-MCP-AuNP. Since MCP presenting a terminal multi-LA group provides the greatest stability, this conjugation chemistry is the most promising for construction of 177Lu-labeled and antibody-targeted AuNP for neoadjuvant treatment of LABC.
Applications of Pascal Mixture Models to Insurance and Risk Management
Keywords: Cox Process
Expectation-Maximization Algorithm
Finite Mixture of Pascal Distribution
Hidden Markov Models
Loss Reserving
Multivariate Frequencies

This thesis studies the applications of Pascal mixture models in three closely related topics in insurance and risk management. The first topic is on the modeling of correlated frequencies of operational risk (OR) losses from financial institutions. We propose a copula-free approach for modeling correlated frequencies using an Erlang-based multivariate mixed Poisson distribution. Many properties possessed by this class of distributions are investigated and a tailor-made generalized expectation-maximization (EM) algorithm is derived for fitting purposes. The applicability of the proposed distribution is illustrated in an OR management context, where this class is used to model the OR loss. The accuracy of the proposed approach is analyzed using a modified real operational loss data set. The second topic is about multivariate count regression with application in modeling correlated claim frequencies. We propose a multivariate Pascal mixture regression model as an alternative to understand the association between multivariate count response variables and their covariates. We examine the many properties possessed by this class of regression. A generalized EM algorithm is derived for fitting purposes, which also provides the standard errors of the regression coefficients which are useful for inference. Its applicability is demonstrated by fitting an automobile insurance claim count data set. The third topic is about modeling and predicting the number of incurred but not reported (IBNR) claims in Property Casualty (P) insurance. We model the claim arrival process together with the reporting delays as a marked Cox process whose intensity function is governed by a hidden Markov chain. The associated reported claim process and IBNR claim process remain to be marked Cox processes with easily convertible intensity functions and marking distributions. Closed-form expressions for both the autocorrelation function (ACF) and the distributions of the numbers of reported claims and IBNR claims are derived. A generalized EM algorithm is obtained to estimate the model parameters. The proposed model is examined through simulation studies and is also applied to a real insurance claim data set. We compare the predictive distributions of our model with those of the over-dispersed Poisson model (ODP), a stochastic model that underpins the widely used chain-ladder method.
Lagrangian Relaxation Approaches to Cardinality Constrained Portfolio Selection
Keywords: Index Tracking
Lagrangian Relaxation
Portfolio Optimization
Risk Management

Portfolio selection with cardinality constraint is a process that creates a strict subset of assets from a large selection pool. The advantage of cardinality constraint is that fewer assets can reduce transaction costs and complexity of asset management. Also, this type of constraint can be used to mimic a benchmark portfolio (index) such as S 500. In this dissertation we study two different cardinality constrained portfolio selection problems, known as Index Tracking and Financial Planning. Index Tracking is a typical application of the cardinality constrained portfolio selection process and has attracted much attention from portfolio managers. However, replicating unpredictable market indices using limited available resource requires advanced modelling and optimization techniques in practice. This thesis aims to qualitatively investigate and analyze different types of index tracking problems and the associated optimal strategies. Firstly, we construct the tracking portfolio via a constrained clustering approach which considers various practical aspects such as transaction costs, turnover, and sector limits constraints. We show that the portfolio allocation can diversify between different sectors and reduce the portfolio risk fairly well. Next we address a cardinality constrained Financial Planning problem through Stochastic Mixed Integer Programming and extend the network flow structured framework to index tracking problem. Finally, we incorporate the cardinality restriction to a classical mean-variance based tracking model and build the robust counterpart via Robust Optimization. All developed models demand problem solvability due to the rapid increase in the number of variables and constraints for tracking real indices such as S 500. We design three dual decomposition algorithms, which allow different specific heuristics to be embedded, to quickly obtain high quality solutions for associated models. For example, Tabu Search was applied to solve the scenario sub-problems to speed up the Progressive Hedging algorithm for cardinality constrained financial planning problems. Our designed models are general enough to extend to many other management applications, and our accompanied decomposition algorithms are efficient enough to handle the cardinality constraint in these problems. The generated portfolios illustrate the effectiveness of our selection technologies and designed algorithms in terms of different performance metrics with respect to the market.