28,177 research outputs found

    Next generation sequencing in oncological pathology

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    RESUMEN : La secuenciación de nueva generación (next generation sequencing o NGS) es una técnica molecular de reciente implantación en la práctica clínica diaria capaz de detectar alteraciones moleculares en los tejidos analizados. Su aplicación en Oncología ha supuesto una auténtica revolución en el diagnóstico y tratamiento de los pacientes ya que permite identificar dianas moleculares accionables y el cambio de tratamientos quimioterápicos convencionales al uso de terapias dirigidas contra las mutaciones genéticas detectadas, cambiando así el paradigma del tratamiento y el pronóstico de los pacientes. El uso de NGS, pese a no estar aún extendido en el sistema sanitario debido a la complejidad y coste de la técnica, va adquiriendo cada día mayor relevancia en el desarrollo de terapias dirigidas y la medicina de precisión. Como muestra de ello, cada año progresa el número de medicamentos dirigidos contra dianas moleculares concretas, demostrándose así el interés por individualizar el tratamiento para cada paciente en función de los hallazgos encontrados en las pruebas diagnósticas. Por este motivo, el potencial de la NGS en muy amplio y es previsible que esta técnica acabe por extenderse e implementarse en el arsenal diagnóstico médico del que se dispone hoy en día.ABSTRACT : Next generation sequencing (NGS) is a molecular technique capable to detect molecular alterations in the analyzed samples. It has been recently introduced in the daily clinical practice and its use in Oncology has meant a big revolution in the diagnosis and treatment of patients, thanks to the identification of molecular targets and the shift from conventional chemotherapy to directed therapies against the altered molecular mutations, improving our patient´s prognosis. The cost and the technical difficulties of NGS has meant that this technique has not been spread in the National Healthcare System yet. However, its relevance is increasing nowadays because it allows the development of targeted therapies and precision medicine. As an example of this reality, the number of targeted drugs is against molecular alterations is increasing every year, showing the interest to individualize the treatment for each patient depending on their detected molecular mutations. Therefore, the potential of NGS is wide and it is foreseeable that this technique will be included in the daily and conventional diagnostic tools.Grado en Medicin

    Computational resources for structural and metagenomic characterization of functions in bacteria and bacterial communities. Antimicrobial resistance, pathways for xenobiotic degradation and relationship between gut microbiome and ageing.

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    Prokaryotic organisms are one of the most successful forms of life, they are present in all known ecosystems. The deluge diversity of bacteria reflects their ability to colonise every environment. Also, human beings host trillions of microorganisms in their body districts, including skin, mucosae, and gut. This symbiosis is active for all other terrestrial and marine animals, as well as plants. With the term holobiont we refer, with a single word, to the systems including both the host and its symbiotic microbial species. The coevolution of bacteria within their ecological niches reflects the adaptation of both host and guest species, and it is shaped by complex interactions that are pivotal for determining the host state. Nowadays, thanks to the current sequencing technologies, Next Generation Sequencing, we have unprecedented tools for investigating the bacterial life by studying the prokaryotic genome sequences. NGS revolution has been sustained by the advancements in computational performance, in terms of speed, storage capacity, algorithm development and hardware costs decreasing following the Moore’s Law. Bioinformaticians and computational biologists design and implement ad hoc tools able to analyse high-throughput data and extract valuable biological information. Metagenomics requires the integration of life and computational sciences and it is uncovering the deluge diversity of the bacterial world. The present thesis work focuses mainly on the analysis of prokaryotic genomes under different aspects. Being supervised by two groups at the University of Bologna, the Biocomputing group and the group of Microbial Ecology of Health, I investigated three different topics: i) antimicrobial resistance, particularly with respect to missense point mutations involved in the resistant phenotype, ii) bacterial mechanisms involved in xenobiotic degradation via the computational analysis of metagenomic samples, and iii) the variation of the human gut microbiota through ageing, in elderly and longevous individuals

    Improved GPU implementations of the Pair-HMM forward algorithm for DNA sequence alignment

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    With the rise of Next-Generation Sequencing (NGS), clinical sequencing services have become more accessible but also facing new challenges. As we discovered the closed connection between key DeoxyriboNucleic Acid (DNA) mutation spots and major diseases or conditions, the need for computational genomics has increased significantly. The surging demand motivates developments of more efficient algorithms for genome assembly, error correction, k-mer counting etc. In this thesis, we focus on DNA sequencing analysis, one of the fastest-growing markets in NGS, and its related alignment problems. In recent years, many new hardware technologies and algorithms have been researched for their potential applications in massive parallel sequencing. The emerging hardware includes GPU, FPGA and other ASICs providing parallel processing resources. In this thesis, we choose GPU as our computation platform for its massive parallel processing capabilities. The Forward Algorithm (FA) still remains one of the most commonly used methods in solving sequences alignment problems modeled as Pair-Hidden Markov Model (HMM). The Pair-HMM Forward Algorithm (FA) is not only a computation but data intensive algorithm. Multiple previous works have been done in efforts to accelerate the computation of the FA by applying massive parallelization on the workload, and in this thesis, we bring more optimizations not only by improving the computation concurrency of both initialization process and Pair-HMM FA but also by tackling the communications overhead between the host and devices. We will discuss the general principles of optimizing the Forward Algorithm on GPU and present an improved implementation of the Pair-HMM FA with native CUDA C++. Our design has shown a speedup of 25.10x over the C++ baseline on the GATK HaplotypeCaller Pair-HMM workload with a portion of the real dataset from human genome database, NA12878. This is a major improvement that beats the state-of-the-art implementation with a margin of 60%.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste

    Optimal Control of the Landau-de Gennes Model of Nematic Liquid Crystals

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    We present an analysis and numerical study of an optimal control problem for the Landau-de Gennes (LdG) model of nematic liquid crystals (LCs), which is a crucial component in modern technology. They exhibit long range orientational order in their nematic phase, which is represented by a tensor-valued (spatial) order parameter Q=Q(x)Q = Q(x). Equilibrium LC states correspond to QQ functions that (locally) minimize an LdG energy functional. Thus, we consider an L2L^2-gradient flow of the LdG energy that allows for finding local minimizers and leads to a semi-linear parabolic PDE, for which we develop an optimal control framework. We then derive several a priori estimates for the forward problem, including continuity in space-time, that allow us to prove existence of optimal boundary and external ``force'' controls and to derive optimality conditions through the use of an adjoint equation. Next, we present a simple finite element scheme for the LdG model and a straightforward optimization algorithm. We illustrate optimization of LC states through numerical experiments in two and three dimensions that seek to place LC defects (where Q(x)=0Q(x) = 0) in desired locations, which is desirable in applications.Comment: 26 pages, 9 figure

    Impact of Microstructure of Nanoscale Magnetron Sputtered Ru/Al Multilayers on Thermally Induced Phase Formation

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    In this study, we report on phase formation and microstructure evolution in multiscale magnetron sputtered Ru/Al multilayers upon thermal annealing in vacuum at slow heating rates of 10 K/min. By specifically adjusting the microstructure and design of the as-deposited multilayers, the formation of certain desired phases can be tuned. We demonstrate that the synthesis of single phase RuAl thin films is possible in a very controlled manner in a solid state only via thermal activation without initiating the self-propagating exothermic reactions of Ru/Al multilayers. To investigate phase formation sequences and the resulting microstructures, Ru/Al multilayers were designed via magnetron sputtering with systematic variation of bilayer modulation periods and subsequent vacuum annealing. Thin films samples were characterized by in situ high-temperature XRD, TEM imaging and diffraction. It is shown that different phase sequences appear in strong correlation with the modulation length. Depending on the multilayer design, the phase formation toward single-phase RuAl thin films happens as either a multi-step or single-step event. In particular, below a critical threshold of the modulation period, the multi-step phase formation can be suppressed, and only the desired RuAl target phase is obtained with a pronounced growth in a preferred orientation. This finding may be versatile for the targeted synthesis of intermetallic phases, contributing to further understanding of phase formation in such nanoscale multilayer systems

    Type 2 Diabetes Mellitus and its comorbidity, Alzheimer’s disease: Identifying critical microRNA using machine learning

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    MicroRNAs (miRNAs) are critical regulators of gene expression in healthy and diseased states, and numerous studies have established their tremendous potential as a tool for improving the diagnosis of Type 2 Diabetes Mellitus (T2D) and its comorbidities. In this regard, we computationally identify novel top-ranked hub miRNAs that might be involved in T2D. We accomplish this via two strategies: 1) by ranking miRNAs based on the number of T2D differentially expressed genes (DEGs) they target, and 2) using only the common DEGs between T2D and its comorbidity, Alzheimer’s disease (AD) to predict and rank miRNA. Then classifier models are built using the DEGs targeted by each miRNA as features. Here, we show the T2D DEGs targeted by hsa-mir-1-3p, hsa-mir-16-5p, hsa-mir-124-3p, hsa-mir-34a-5p, hsa-let-7b-5p, hsa-mir-155-5p, hsa-mir-107, hsa-mir-27a-3p, hsa-mir-129-2-3p, and hsa-mir-146a-5p are capable of distinguishing T2D samples from the controls, which serves as a measure of confidence in the miRNAs’ potential role in T2D progression. Moreover, for the second strategy, we show other critical miRNAs can be made apparent through the disease’s comorbidities, and in this case, overall, the hsa-mir-103a-3p models work well for all the datasets, especially in T2D, while the hsa-mir-124-3p models achieved the best scores for the AD datasets. To the best of our knowledge, this is the first study that used predicted miRNAs to determine the features that can separate the diseased samples (T2D or AD) from the normal ones, instead of using conventional non-biology-based feature selection methods

    Metavirome Analysis Reveals a High Prevalence of Porcine Hemagglutination Encephalomyelitis Virus in Clinically Healthy Pigs in China

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    Six swine coronaviruses (SCoVs), which include porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), porcine hemagglutination encephalomyelitis virus (PHEV), porcine respiratory coronavirus (PRCV), swine acute diarrhea syndrome coronavirus (SADS-CoV), and porcine delta coronavirus (PDCoV), have been reported as infecting and causing serious diseases in pigs. To investigate the genetic diversity and spatial distribution of SCoVs in clinically healthy pigs in China, we collected 6400 nasal swabs and 1245 serum samples from clinically healthy pigs at slaughterhouses in 13 provinces in 2017 and pooled them into 17 libraries by type and region for next-generation sequencing (NGS) and metavirome analyses. In total, we identified five species of SCoVs, including PEDV, PDCoV, PHEV, PRCV, and TGEV. Strikingly, PHEV was detected from all the samples in high abundance and its genome sequences accounted for 75.28% of all coronaviruses, while those belonging to TGEV (including PRCV), PEDV, and PDCoV were 20.4%, 2.66%, and 2.37%, respectively. The phylogenetic analysis showed that two lineages of PHEV have been circulating in pig populations in China. We also recognized two PRCVs which lack 672 nucleotides at the N-terminus of the S gene compared with that of TGEV. Together, we disclose preliminarily the genetic diversities of SCoVs in clinically healthy pigs in China and provide new insights into two SCoVs, PHEV and PRCV, that have been somewhat overlooked in previous studies in China

    Robotic Bronchoscopy: Review of Three Systems

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    Robotic bronchoscopy (RB) has been shown to improve access to smaller and more peripheral lung lesions, while simultaneously staging the mediastinum. Pre-clinical studies demonstrated extremely high diagnostic yields, but real-world RB yields have yet to fully matched up in prospective studies. Despite this, RB technology has rapidly evolved and has great potential for lung-cancer diagnosis and even treatment. In this article, we review the historical and present challenges with RB in order to compare three RB systems

    Identifizierung prädiktiver und prognostischer Biomarker in unterschiedlichen Tumorkompartimenten des ösophagealen Adenokarzinoms

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    Das ösophageale Adenokarzinom zeigt eine global steigende Inzidenz und hat mit einer 5-Jahres-Überlebensrate von weniger als 25% eine schlechte Prognose. Personalisierte Therapieansätze sind selten und prognostische/prädiktive Biomarker des Tumormikromilieus sind unzureichend charakterisiert. Die kumulative Promotion nähert sich dieser Problematik in drei unterschiedlichen Schwerpunkten. 1. Zur Identifizierung Kompartiment-spezifischer Biomarker wurde eine Methode entwickelt, welche als kostengünstige Alternative zum sc-Seq Expressionsprofile individueller Zelltypen generiert. Dabei erfolgt die Extraktion der RNA nicht aus Einzelzellen, sondern aus flowzytometrisch-getrennten Zellkompartimenten. Die Separation der Proben in Epithelzellen, Immunzellen und Fibroblasten wurde durch verschiedene Verfahren validiert und eine suffiziente Ausbeute an RNA auch für kleine Gewebemengen gezeigt. 2. Biomarker des Immunzellkompartiments als therapeutische Angriffspunkte wurden in einem Patientenkollektiv von bis zu 551 Patienten auf ihre Bedeutung beim EAC überprüft. Es zeigte sich eine Expression der Immuncheckpoints LAG3, VISTA und IDO auf TILs durch IHC und RNA-Sonden basierte Verfahren in einem relevanten Anteil (LAG3: 11,4%, VISTA: 29%, IDO: 52,6%). Es konnte eine prognostisch günstige Bedeutung der VISTA, LAG3 und IDO Expression gezeigt werden. Durch den Vergleich von Genexpressionsprofilen aus therapienaiven und vorbehandelten Tumoren konnte zudem ein immunsuppressiver Effekt von neoadjuvanten Therapiekonzepten auf das Tumormikromilieu des EACs gezeigt werden. Dabei kam es zur verminderten Expression von Checkpoints und Anzahl TILs nach (Radio-) Chemotherapie. 3. Im Tumorzellkompartiment wurde die Rolle von Amplifikationen in ErbB-Rezeptor abhängigen Signalwegen durch FISH-Technik und Immunhistochemie evaluiert. Es fanden sich KRAS Amplifikationen in 17,1%, PIK3CA Amplifikationen in 5% sowie eine HER2/neu-Überexpression in 14,9% der untersuchten Tumore

    A circulating microRNA panel as a novel dynamic monitor for oral squamous cell carcinoma

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    Abstract Oral squamous cell carcinoma (OSCC) has high recurrence and mortality rates despite advances in diagnosis and treatment. Therefore, it is necessary to identify new biomarkers for early detection, efficient monitoring, and prognosis prediction. Since microRNA (miRNA) is stable and detectable in serum, it has been reported to inform the diagnosis and monitor disease progression through liquid biopsy. In this study, a circulating specific miRNA panel in OSCC patients was developed, and its usefulness as a dynamic monitor was validated. Small RNAs were extracted from the serum of OSCC patients (n = 4) and normal controls (n = 6) and profiled using next-generation sequencing. NGS identified 42 differentially expressed miRNAs (DEmiRNAs) in serum between patients with OSCC and healthy controls, with threefold differences (p < 0.05). Combining the 42 DEmiRNAs and The Cancer Genome Atlas (TCGA) databases OSCC cohort, 9 overlapping DEmiRNAs were screened out. Finally, 4 significantly up-regulated miRNAs (miR-92a-3p, miR-92b-3p, miR-320c and miR-629-5p) were identified from OSCC patients via validation in the Chungnam National University Hospital cohort. Application of the specific miRNA panel for distinguishing OSCC patients from healthy controls produced specificity and sensitivity of 97.8 and 74%, respectively. In addition, the serum levels of these 4 miRNAs significantly decreased after complete surgical resection and increased after recurrence. We suggest that circulating 4-miRNA panel might be promising non-invasive predictors for diagnosing and monitoring the progression of patients with OSCC
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