6,050 research outputs found

    Converging organoids and extracellular matrix::New insights into liver cancer biology

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    Converging organoids and extracellular matrix::New insights into liver cancer biology

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    Primary liver cancer, consisting primarily of hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), is a heterogeneous malignancy with a dismal prognosis, resulting in the third leading cause of cancer mortality worldwide [1, 2]. It is characterized by unique histological features, late-stage diagnosis, a highly variable mutational landscape, and high levels of heterogeneity in biology and etiology [3-5]. Treatment options are limited, with surgical intervention the main curative option, although not available for the majority of patients which are diagnosed in an advanced stage. Major contributing factors to the complexity and limited treatment options are the interactions between primary tumor cells, non-neoplastic stromal and immune cells, and the extracellular matrix (ECM). ECM dysregulation plays a prominent role in multiple facets of liver cancer, including initiation and progression [6, 7]. HCC often develops in already damaged environments containing large areas of inflammation and fibrosis, while CCA is commonly characterized by significant desmoplasia, extensive formation of connective tissue surrounding the tumor [8, 9]. Thus, to gain a better understanding of liver cancer biology, sophisticated in vitro tumor models need to incorporate comprehensively the various aspects that together dictate liver cancer progression. Therefore, the aim of this thesis is to create in vitro liver cancer models through organoid technology approaches, allowing for novel insights into liver cancer biology and, in turn, providing potential avenues for therapeutic testing. To model primary epithelial liver cancer cells, organoid technology is employed in part I. To study and characterize the role of ECM in liver cancer, decellularization of tumor tissue, adjacent liver tissue, and distant metastatic organs (i.e. lung and lymph node) is described, characterized, and combined with organoid technology to create improved tissue engineered models for liver cancer in part II of this thesis. Chapter 1 provides a brief introduction into the concepts of liver cancer, cellular heterogeneity, decellularization and organoid technology. It also explains the rationale behind the work presented in this thesis. In-depth analysis of organoid technology and contrasting it to different in vitro cell culture systems employed for liver cancer modeling is done in chapter 2. Reliable establishment of liver cancer organoids is crucial for advancing translational applications of organoids, such as personalized medicine. Therefore, as described in chapter 3, a multi-center analysis was performed on establishment of liver cancer organoids. This revealed a global establishment efficiency rate of 28.2% (19.3% for hepatocellular carcinoma organoids (HCCO) and 36% for cholangiocarcinoma organoids (CCAO)). Additionally, potential solutions and future perspectives for increasing establishment are provided. Liver cancer organoids consist of solely primary epithelial tumor cells. To engineer an in vitro tumor model with the possibility of immunotherapy testing, CCAO were combined with immune cells in chapter 4. Co-culture of CCAO with peripheral blood mononuclear cells and/or allogenic T cells revealed an effective anti-tumor immune response, with distinct interpatient heterogeneity. These cytotoxic effects were mediated by cell-cell contact and release of soluble factors, albeit indirect killing through soluble factors was only observed in one organoid line. Thus, this model provided a first step towards developing immunotherapy for CCA on an individual patient level. Personalized medicine success is dependent on an organoids ability to recapitulate patient tissue faithfully. Therefore, in chapter 5 a novel organoid system was created in which branching morphogenesis was induced in cholangiocyte and CCA organoids. Branching cholangiocyte organoids self-organized into tubular structures, with high similarity to primary cholangiocytes, based on single-cell sequencing and functionality. Similarly, branching CCAO obtain a different morphology in vitro more similar to primary tumors. Moreover, these branching CCAO have a higher correlation to the transcriptomic profile of patient-paired tumor tissue and an increased drug resistance to gemcitabine and cisplatin, the standard chemotherapy regimen for CCA patients in the clinic. As discussed, CCAO represent the epithelial compartment of CCA. Proliferation, invasion, and metastasis of epithelial tumor cells is highly influenced by the interaction with their cellular and extracellular environment. The remodeling of various properties of the extracellular matrix (ECM), including stiffness, composition, alignment, and integrity, influences tumor progression. In chapter 6 the alterations of the ECM in solid tumors and the translational impact of our increased understanding of these alterations is discussed. The success of ECM-related cancer therapy development requires an intimate understanding of the malignancy-induced changes to the ECM. This principle was applied to liver cancer in chapter 7, whereby through a integrative molecular and mechanical approach the dysregulation of liver cancer ECM was characterized. An optimized agitation-based decellularization protocol was established for primary liver cancer (HCC and CCA) and paired adjacent tissue (HCC-ADJ and CCA-ADJ). Novel malignancy-related ECM protein signatures were found, which were previously overlooked in liver cancer transcriptomic data. Additionally, the mechanical characteristics were probed, which revealed divergent macro- and micro-scale mechanical properties and a higher alignment of collagen in CCA. This study provided a better understanding of ECM alterations during liver cancer as well as a potential scaffold for culture of organoids. This was applied to CCA in chapter 8 by combining decellularized CCA tumor ECM and tumor-free liver ECM with CCAO to study cell-matrix interactions. Culture of CCAO in tumor ECM resulted in a transcriptome closely resembling in vivo patient tumor tissue, and was accompanied by an increase in chemo resistance. In tumor-free liver ECM, devoid of desmoplasia, CCAO initiated a desmoplastic reaction through increased collagen production. If desmoplasia was already present, distinct ECM proteins were produced by the organoids. These were tumor-related proteins associated with poor patient survival. To extend this method of studying cell-matrix interactions to a metastatic setting, lung and lymph node tissue was decellularized and recellularized with CCAO in chapter 9, as these are common locations of metastasis in CCA. Decellularization resulted in removal of cells while preserving ECM structure and protein composition, linked to tissue-specific functioning hallmarks. Recellularization revealed that lung and lymph node ECM induced different gene expression profiles in the organoids, related to cancer stem cell phenotype, cell-ECM integrin binding, and epithelial-to-mesenchymal transition. Furthermore, the metabolic activity of CCAO in lung and lymph node was significantly influenced by the metastatic location, the original characteristics of the patient tumor, and the donor of the target organ. The previously described in vitro tumor models utilized decellularized scaffolds with native structure. Decellularized ECM can also be used for creation of tissue-specific hydrogels through digestion and gelation procedures. These hydrogels were created from both porcine and human livers in chapter 10. The liver ECM-based hydrogels were used to initiate and culture healthy cholangiocyte organoids, which maintained cholangiocyte marker expression, thus providing an alternative for initiation of organoids in BME. Building upon this, in chapter 11 human liver ECM-based extracts were used in combination with a one-step microfluidic encapsulation method to produce size standardized CCAO. The established system can facilitate the reduction of size variability conventionally seen in organoid culture by providing uniform scaffolding. Encapsulated CCAO retained their stem cell phenotype and were amendable to drug screening, showing the feasibility of scalable production of CCAO for throughput drug screening approaches. Lastly, Chapter 12 provides a global discussion and future outlook on tumor tissue engineering strategies for liver cancer, using organoid technology and decellularization. Combining multiple aspects of liver cancer, both cellular and extracellular, with tissue engineering strategies provides advanced tumor models that can delineate fundamental mechanistic insights as well as provide a platform for drug screening approaches.<br/

    Monitoring tools for DevOps and microservices: A systematic grey literature review

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    Microservice-based systems are usually developed according to agile practices like DevOps, which enables rapid and frequent releases to promptly react and adapt to changes. Monitoring is a key enabler for these systems, as they allow to continuously get feedback from the field and support timely and tailored decisions for a quality-driven evolution. In the realm of monitoring tools available for microservices in the DevOps-driven development practice, each with different features, assumptions, and performance, selecting a suitable tool is an as much difficult as impactful task. This article presents the results of a systematic study of the grey literature we performed to identify, classify and analyze the available monitoring tools for DevOps and microservices. We selected and examined a list of 71 monitoring tools, drawing a map of their characteristics, limitations, assumptions, and open challenges, meant to be useful to both researchers and practitioners working in this area. Results are publicly available and replicable

    Breaking Virtual Barriers : Investigating Virtual Reality for Enhanced Educational Engagement

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    Virtual reality (VR) is an innovative technology that has regained popularity in recent years. In the field of education, VR has been introduced as a tool to enhance learning experiences. This thesis presents an exploration of how VR is used from the context of educators and learners. The research employed a mixed-methods approach, including surveying and interviewing educators, and conducting empirical studies to examine engagement, usability, and user behaviour within VR. The results revealed educators are interested in using VR for a wide range of scenarios, including thought exercises, virtual field trips, and simulations. However, they face several barriers to incorporating VR into their practice, such as cost, lack of training, and technical challenges. A subsequent study found that virtual reality can no longer be assumed to be more engaging than desktop equivalents. This empirical study showed that engagement levels were similar in both VR and non-VR environments, suggesting that the novelty effect of VR may be less pronounced than previously assumed. A study against a VR mind mapping artifact, VERITAS, demonstrated that complex interactions are possible on low-cost VR devices, making VR accessible to educators and students. The analysis of user behaviour within this VR artifact showed that quantifiable strategies emerge, contributing to the understanding of how to design for collaborative VR experiences. This thesis provides insights into how the end-users in the education space perceive and use VR. The findings suggest that while educators are interested in using VR, they face barriers to adoption. The research highlights the need to design VR experiences, with understanding of existing pedagogy, that are engaging with careful thought applied to complex interactions, particularly for collaborative experiences. This research contributes to the understanding of the potential of VR in education and provides recommendations for educators and designers to enhance learning experiences using VR

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    SeeChart: Enabling Accessible Visualizations Through Interactive Natural Language Interface For People with Visual Impairments

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    Web-based data visualizations have become very popular for exploring data and communicating insights. Newspapers, journals, and reports regularly publish visualizations to tell compelling stories with data. Unfortunately, most visualizations are inaccessible to readers with visual impairments. For many charts on the web, there are no accompanying alternative (alt) texts, and even if such texts exist they do not adequately describe important insights from charts. To address the problem, we first interviewed 15 blind users to understand their challenges and requirements for reading data visualizations. Based on the insights from these interviews, we developed SeeChart, an interactive tool that automatically deconstructs charts from web pages and then converts them to accessible visualizations for blind people by enabling them to hear the chart summary as well as to interact through data points using the keyboard. Our evaluation with 14 blind participants suggests the efficacy of SeeChart in understanding key insights from charts and fulfilling their information needs while reducing their required time and cognitive burden.Comment: 28 pages, 13 figure

    Software Design Change Artifacts Generation through Software Architectural Change Detection and Categorisation

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    Software is solely designed, implemented, tested, and inspected by expert people, unlike other engineering projects where they are mostly implemented by workers (non-experts) after designing by engineers. Researchers and practitioners have linked software bugs, security holes, problematic integration of changes, complex-to-understand codebase, unwarranted mental pressure, and so on in software development and maintenance to inconsistent and complex design and a lack of ways to easily understand what is going on and what to plan in a software system. The unavailability of proper information and insights needed by the development teams to make good decisions makes these challenges worse. Therefore, software design documents and other insightful information extraction are essential to reduce the above mentioned anomalies. Moreover, architectural design artifacts extraction is required to create the developer’s profile to be available to the market for many crucial scenarios. To that end, architectural change detection, categorization, and change description generation are crucial because they are the primary artifacts to trace other software artifacts. However, it is not feasible for humans to analyze all the changes for a single release for detecting change and impact because it is time-consuming, laborious, costly, and inconsistent. In this thesis, we conduct six studies considering the mentioned challenges to automate the architectural change information extraction and document generation that could potentially assist the development and maintenance teams. In particular, (1) we detect architectural changes using lightweight techniques leveraging textual and codebase properties, (2) categorize them considering intelligent perspectives, and (3) generate design change documents by exploiting precise contexts of components’ relations and change purposes which were previously unexplored. Our experiment using 4000+ architectural change samples and 200+ design change documents suggests that our proposed approaches are promising in accuracy and scalability to deploy frequently. Our proposed change detection approach can detect up to 100% of the architectural change instances (and is very scalable). On the other hand, our proposed change classifier’s F1 score is 70%, which is promising given the challenges. Finally, our proposed system can produce descriptive design change artifacts with 75% significance. Since most of our studies are foundational, our approaches and prepared datasets can be used as baselines for advancing research in design change information extraction and documentation

    Privacy-preserving artificial intelligence in healthcare: Techniques and applications

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    There has been an increasing interest in translating artificial intelligence (AI) research into clinically-validated applications to improve the performance, capacity, and efficacy of healthcare services. Despite substantial research worldwide, very few AI-based applications have successfully made it to clinics. Key barriers to the widespread adoption of clinically validated AI applications include non-standardized medical records, limited availability of curated datasets, and stringent legal/ethical requirements to preserve patients' privacy. Therefore, there is a pressing need to improvise new data-sharing methods in the age of AI that preserve patient privacy while developing AI-based healthcare applications. In the literature, significant attention has been devoted to developing privacy-preserving techniques and overcoming the issues hampering AI adoption in an actual clinical environment. To this end, this study summarizes the state-of-the-art approaches for preserving privacy in AI-based healthcare applications. Prominent privacy-preserving techniques such as Federated Learning and Hybrid Techniques are elaborated along with potential privacy attacks, security challenges, and future directions. [Abstract copyright: Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.

    Genomic insights for safety assessment of foodborne bacteria.

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    La sicurezza alimentare e l'accesso ad essa sono fondamentali per sostenere la vita e promuovere una buona salute. Gli alimenti non sicuri, contenenti microrganismi o sostanze chimiche nocive, sono causa di oltre 200 malattie, dalla diarrea al cancro, che colpiscono in particolare i neonati, i bambini piccoli, gli anziani e gli individui immunocompromessi. L'onere globale delle malattie di origine alimentare si ripercuote sulla salute pubblica, sulla società e sull'economia, pertanto è necessaria una buona collaborazione tra governi, produttori e consumatori per contribuire a garantire la sicurezza alimentare e sistemi alimentari più solidi. L'indagine più recente condotta dall'OMS (2015) ha evidenziato una stima di 600 milioni di individui malati e 420.000 decessi annui associati ad alimenti non sicuri. L'impatto economico è dovuto principalmente alla mancanza di alimenti sicuri nei Paesi a basso e medio reddito, con una perdita di 110 miliardi di dollari l'anno in termini di produttività e spese mediche. Le sfide principali per garantire la sicurezza alimentare rimangono legate alla nostra produzione alimentare e alla catena di approvvigionamento, dove fattori come la contaminazione ambientale, le preferenze dei consumatori, il rilevamento tempestivo e la sorveglianza dei focolai giocano un ruolo cruciale. Recentemente, le metodologie basate sul DNA per il rilevamento e l'indagine microbica hanno suscitato particolare interesse, soprattutto grazie allo sviluppo delle tecnologie di sequenziamento. Contrariamente ai metodi tradizionali dipendenti dalla coltura, le tecniche basate sul DNA, come il sequenziamento dell'intero genoma (WGS), mirano a risultati rapidi e sensibili a un prezzo relativamente basso e a tempi di elaborazione brevi. Inoltre, il WGS conferisce un elevato potere discriminatorio che consente di determinare importanti caratteristiche genomiche legate alla sicurezza alimentare, come la tassonomia, il potenziale patogeno, la virulenza e la resistenza antimicrobica e il relativo trasferimento genetico. La comprensione di queste caratteristiche è fondamentale per progettare strategie di rilevamento e mitigazione da applicare lungo l'intera catena alimentare secondo una prospettiva di "One Health", che porta ad acquisire conoscenze sul microbiota che influenza l'uomo, gli animali e l'ambiente. Lo scopo della tesi è quello di approfondire la genomica dei microbi di origine alimentare per la loro caratterizzazione e per creare o migliorare le strategie per la loro individuazione e i metodi di mitigazione. In particolare, questa tesi si concentra sulla valutazione del potenziale patogeno sulla base di analisi genomiche che includono studi di tassonomia, virulenza, resistenza agli antibiotici e mobiloma. Il secondo obiettivo è quello di trarre vantaggio dalle conoscenze genomiche per progettare dispositivi di rilevamento rapidi ed efficaci e metodi di mitigazione affidabili per affrontare i patogeni di origine alimentare. Più in dettaglio, saranno trattati i seguenti argomenti: La presenza di ceppi multiresistenti negli alimenti fermentati pronti al consumo rappresenta un rischio per la salute pubblica per la diffusione di determinanti AMR nella catena alimentare e nel microbiota intestinale dei consumatori. Le analisi genomiche hanno permesso di valutare accuratamente la sicurezza del ceppo UC7251 di E. faecium, in relazione alla sua virulenza e alla co-localizzazione dei geni di resistenza agli antibiotici e ai metalli pesanti in elementi mobili con capacità di coniugazione in diverse matrici. Questo lavoro sottolinea l'importanza di una sorveglianza della presenza di batteri AMR negli alimenti e di incitare lo sviluppo di strategie innovative per la mitigazione del rischio legato alla diffusione della resistenza antimicrobica negli alimenti. L'accuratezza dell'identificazione tassonomica guida le analisi successive e, per questo motivo, un metodo adeguato per identificare le specie è fondamentale. È stata studiata la riclassificazione delle specie di Enterococcus faecium clade B, utilizzando un approccio combinato di filogenomica, tipizzazione di sequenza multilocus, identità nucleotidica media e ibridazione digitale DNA-DNA. L'obiettivo è dimostrare come l'analisi del genoma sia più efficace e fornisca risultati più dettagliati riguardo alla definizione delle specie, rispetto all'analisi della sequenza del 16S rRNA. Ciò ha portato alla proposta di riclassificare tutto il clade B di E. faecium come E. lactis, riconoscendo che i due gruppi sono filogeneticamente separati, per cui è possibile definire una specifica procedura di valutazione della sicurezza, prima del loro utilizzo negli alimenti o come probiotici, compresa la considerazione per l'inclusione nella lista europea QPS. A partire da questa riclassificazione tassonomica, abbiamo sviluppato un metodo basato sulla PCR per la rapida individuazione e differenziazione di queste due specie e per discutere le principali differenze fenotipiche e genotipiche da una prospettiva clinica. A questo scopo, è stato utilizzato un allineamento del core-genoma basato sull'analisi del pangenoma. La differenza allelica tra alcuni geni del core ha permesso la progettazione di primer e l'identificazione della specie mediante PCR con una specificità del 100% e senza reattività crociata. Inoltre, i genomi clinici di E. lactis sono stati classificati come un rischio potenziale a causa della capacità di aumentare la traslocazione batterica. Gli agenti antimicrobici alternativi agli antibiotici sono una delle principali aree di sviluppo e miglioramento dell'attuale catena alimentare. Le nanoparticelle metalliche, come le nanoparticelle di platino (PtNPs), hanno suscitato interesse per le loro potenti attività catalitiche simili alle ossidasi e alle perossidasi che garantiscono forti effetti antimicrobici, e sono state proposte come potenziali candidati per superare gli inconvenienti degli antibiotici come la resistenza ai farmaci. L'obiettivo è studiare la modalità d'azione delle PtNPs in relazione alla capacità di formazione del biofilm, al meccanismo di contrasto delle specie reattive dell'ossigeno (ROS) e al quorum sensing utilizzando batteri di origine alimentare come Enterococcus faecium e Salmonella Typhimurium.Safe food and the access to it is key to sustaining life and promoting good health. Unsafe food containing harmful microorganisms or chemical substances causes more than 200 diseases, ranging from diarrhoea to cancers that particularly affect infants, young children, elderly and immunocompromised individuals. The global burden of foodborne disease affects public health, society, and economy, therefore good collaboration between governments, producers and consumers is needed to help ensure food safety and stronger food systems. The most recent survey conducted by WHO (2015) showed an estimated 600 million ill individuals and 420 000 yearly deaths associated to unsafe food. The economic impact is mainly due to the lack of safe food in low and middle income causing a US$ 110 billion is lost each year in productivity and medical expenses. The main challenges to assure food safety remain tied to our food production and supply chain, where factors like environmental contamination, consumer preferences, timely detection and surveillance of outbreaks play a crucial role. Recently, DNA-based methodologies for microbial detection and investigation have sparked special interest, mainly linked to the development of sequencing technologies. Contrary to the traditional culture-dependent methods, DNA-based techniques such as Whole Genome Sequencing (WGS) that targets fast and sensitive results at a relative low price and short processing time. Moreover, WGS confers high discriminatory power that allows to determine important genomic characteristics linked to food safety like taxonomy, pathogenic potential, virulence and antimicrobial resistance and the genetic transfer thereof. The understanding of these characteristics is fundamental to design detection and mitigation strategies to apply along the entire food-chain following a ‘One Health’ perspective, leading to gain knowledge about the microbiota that affect humans, animals, and environment. The aim of the thesis is to gain insight into the genomics of foodborne microbes for their characterization and to create or improve strategies for their detection and mitigation methods. Particularly, this thesis is focused on the assessment of the pathogenic potential based on genomic analyses including taxonomy, virulence, antibiotic resistance and mobilome studies. The second focus is to profit from the genomic insights to design rapid and time-effective detection devices and reliable mitigation methods to tackle foodborne pathogens. In more detail the following topics will be handled: The presence of multi-drug resistant strains in ready-to-eat fermented food represents a risk of public health for the spread of AMR determinants in the food chain and in the gut microbiota of consumers. Genomic analyses permitted to accurately assess the safety of E. faecium strain UC7251, with respect to its virulence and co-location of antibiotic and heavy metal resistance genes in mobile elements with conjugation capacity in different matrices. This work emphasizes the importance of a surveillance for the presence of AMR bacteria in food and to incite the development of innovative strategies for the mitigation of the risk related to antimicrobial resistance diffusion in food. The accuracy of taxonomic identification drives the subsequent analysis and, for this reason, a suitable method to identify species is crucial. The species re-classification of Enterococcus faecium clade B was investigated, using a combined approach of phylogenomics, multilocus sequence typing, average nucleotide identity and digital DNA–DNA hybridization. The goal is to show how the genome analysis is more effective and give more detailed results concerning the species definition, respect to the analysis of the 16S rRNA sequence. This led to the proposal to reclassify all the E. faecium clade B as E. lactis, recognizing the two groups are phylogenetically separate, where a specific safety assessment procedure can be designed, before their use in food or as probiotics, including the consideration for inclusion in the European QPS list. From this taxonomic re-classification, we developed a PCR-based method for rapid detection and differentiation of these two species and to discuss main phenotypic and genotypic differences from a clinical perspective. To this aim, core-genome alignment base on pangenome analysis was used. Allelic difference between certain core genes allowed primer design and species identification through PCR with 100% specificity and no cross-reactivity. Moreover, clinical E. lactis genomes categorised as a potential risk due to the ability of enhanced bacterial translocation. Antimicrobial agents alternative to antibiotics are one of the main areas of development and improvement in the current food chain. Metallic nanoparticles like Platinum nanoparticles (PtNPs), have awaken interest due to their potent catalytic activities similar to oxidases and peroxidases granting strong antimicrobial effects, have been proposed as potential candidates to overcome the drawbacks of antibiotics like drug resistance. The goal is to study the mode of action of PtNPs related to biofilm formation capacity, reactive oxygen species (ROS) coping mechanism and quorum sensing using foodborne bacteria like Enterococcus faecium and Salmonella Typhimurium
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