8,455 research outputs found
Converging organoids and extracellular matrix::New insights into liver cancer biology
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/
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Plasma engineering of advanced functional materials for photocatalytic wastewater treatment
Semiconductor metal oxide photocatalyst with favourable light absorption and charge transport characteristics have been widely used as a photocatalyst in various applications, to name a few, energy harvesting and storage, environmental remediation and air pollution. Energy harvesting which comprises the full utilisation of the wide solar light (wavelength) spectrum has become a central point of research in the field of materials science and engineering. Hence, the development of sustainable materials from environmentally sustainable techniques which can absorb majority of the solar light spectrum has become a huge challenge. For efficient utilisation of solar energy in catalytic applications, it is important to create photocatalyst that can absorb the full solar spectrum involving ultraviolet (UV), visible (VIS) and near infrared (NIR) wavelengths. More than three decades, TiO2 and its composites have been widely researched academically and used industrially as a low-cost material for photocatalytic applications. However, the large bandgap of TiO2 limits its photocatalytic activity to the UV region which is just 3-5% of sunlight on Earth’s atmosphere. TiO2 also suffers from rapid recombination of photogenerated carriers (i.e., holes and electrons) thereby affecting its photocatalytic efficiency. Over the years, there has been active research in altering the chemistries of TiO2 to overcome these aforementioned shortcomings. The most recent advantage is the use of two dimensional (2D) materials because of its layered structure One of the unexplored and interesting layered structure is MXene. The aim of this thesis is to modify the chemical structure of Ti2C MXene to produce TiO2 as an efficient photocatalyst for absorbing solar energy especially in the UV and visible regions. As a compound of titanium and carbon, Ti2C MXene could facilitate the creation of TiO2 and carbonaceous materials hereby improving the photocatalytic performance. The abundance of surface terminal groups on Ti2C MXene allow for ease of surface modification and functionalisation. In this thesis, for the first time, the functionalisation of TiO2 from Ti2C MXene using a dry and low powered system, atmospheric pressure plasma jet (APPJ) is reported. This process involved using Ti2C nano colloidal ink with highly reactive oxygen plasma source which can tune the electronic properties (engineering bandgap) of Ti2C MXene in-situ while simultaneously printing on to a substrate. X-ray/Ultraviolet Photoelectron spectroscopy showed an additional density of states (DOS) close to valence band edge and changes to the Ti, O core level spectra due to the oxygen plasma functionalisation. Density functional Theory calculation suggests that the changes in the electron structure might be due to the influence of oxygen vacancies and hence the increase in efficiency of catalytic process. Also, time dependent oxygen plasma functionalisation studies reveal the morphology and size of the in-situ generated TiO2 nanoparticles varied from 5-8 nm with exceptionally high photocatalytic performance.
The second aim of the thesis is to create a heterostructure of Ti2C MXene with low cost and earth abundant graphitic carbon nitride, g-C3N4 (GCN) with visible light properties. For the first time, a lower power APPJ method was reported to produce a ternary in-situ TiO2/Ti2C/GCN heterostructure. In this thesis, GCN nanosheets were used as a semiconducting photocatalyst that could efficiently harvest the energy from visible light. Ti2C MXene nanosheets acted as an excellent electron sink while providing enhanced surface area which could facilitate the interfacial charge carriers. Structural studies show the formation of heterostructure formation between Ti2C MXene and GCN. Influence of morphology and hence changes to the optical properties were discussed. The synthesized ternary in-situ TiO2/Ti2C/GCN nanosheets showed enhancement in photocatalytic performance.
The third aim of my research was to integrate TiO2 onto earth abundant natural cellulose fibres. Utilising the power of low power atmospheric pressure plasma (APPJ) to in-situ anchor TiO2 onto cellulose fibres to prevent the thermal degradation and chemical instability leading to leaching of the oxides from the cellulose fibres. APPJ in the presence of highly oxidised species caused an increase in COO- bonds which provided a strong linkage between TiO2 and cellulose materials. Also, structural studies revealed polymorphic changes in the structure of cellulose materials that improved its crystallinity and surface area for photocatalytic applications. APPJ is also able to create oxygen vacancies in the TiO2 which further reduced the bandgap of as synthesized TiO2/cellulose nanocomposites that enhanced photocatalytic applications. Toxicity studies showed that TiO2 was not cytotoxic.
This plasma modified surfaces (of all the samples) show exceptional degradation of wastewater with ternary in-situ TiO2/Ti2C/GCN showing two times more improvement in methylene blue degradation (84% degradation) as compared to in-situ TiO2/Ti2C MXene (42% degradation). Also, TiO2/cellulose bionanocomposite showed excellent adsorptive-photocatalytic performance in degrading industrial waste dye providing a clear route as nanocomposites from research into industrialisation
Non-invasive and non-intrusive diagnostic techniques for gas-solid fluidized beds – A review
Gas-solid fluidized-bed systems offer great advantages in terms of chemical reaction efficiency and temperature control where other chemical reactor designs fall short. For this reason, they have been widely employed in a range of industrial application where these properties are essential. Nonetheless, the knowledge of such systems and the corresponding design choices, in most cases, rely on a heuristic expertise gained over the years rather than on a deep physical understanding of the phenomena taking place in fluidized beds. This is a huge limiting factor when it comes to the design, the scale-up and the optimization of such complex units. Fortunately, a wide array of diagnostic techniques has enabled researchers to strive in this direction, and, among these, non-invasive and non-intrusive diagnostic techniques stand out thanks to their innate feature of not affecting the flow field, while also avoiding direct contact with the medium under study. This work offers an overview of the non-invasive and non-intrusive diagnostic techniques most commonly applied to fluidized-bed systems, highlighting their capabilities in terms of the quantities they can measure, as well as advantages and limitations of each of them. The latest developments and the likely future trends are also presented. Neither of these methodologies represents a best option on all fronts. The goal of this work is rather to highlight what each technique has to offer and what application are they better suited for
Effects of municipal smoke-free ordinances on secondhand smoke exposure in the Republic of Korea
ObjectiveTo reduce premature deaths due to secondhand smoke (SHS) exposure among non-smokers, the Republic of Korea (ROK) adopted changes to the National Health Promotion Act, which allowed local governments to enact municipal ordinances to strengthen their authority to designate smoke-free areas and levy penalty fines. In this study, we examined national trends in SHS exposure after the introduction of these municipal ordinances at the city level in 2010.MethodsWe used interrupted time series analysis to assess whether the trends of SHS exposure in the workplace and at home, and the primary cigarette smoking rate changed following the policy adjustment in the national legislation in ROK. Population-standardized data for selected variables were retrieved from a nationally representative survey dataset and used to study the policy action’s effectiveness.ResultsFollowing the change in the legislation, SHS exposure in the workplace reversed course from an increasing (18% per year) trend prior to the introduction of these smoke-free ordinances to a decreasing (−10% per year) trend after adoption and enforcement of these laws (β2 = 0.18, p-value = 0.07; β3 = −0.10, p-value = 0.02). SHS exposure at home (β2 = 0.10, p-value = 0.09; β3 = −0.03, p-value = 0.14) and the primary cigarette smoking rate (β2 = 0.03, p-value = 0.10; β3 = 0.008, p-value = 0.15) showed no significant changes in the sampled period. Although analyses stratified by sex showed that the allowance of municipal ordinances resulted in reduced SHS exposure in the workplace for both males and females, they did not affect the primary cigarette smoking rate as much, especially among females.ConclusionStrengthening the role of local governments by giving them the authority to enact and enforce penalties on SHS exposure violation helped ROK to reduce SHS exposure in the workplace. However, smoking behaviors and related activities seemed to shift to less restrictive areas such as on the streets and in apartment hallways, negating some of the effects due to these ordinances. Future studies should investigate how smoke-free policies beyond public places can further reduce the SHS exposure in ROK
A Map-Free LiDAR-Based System for Autonomous Navigation in Vineyards
Agricultural robots have the potential to increase production yields and
reduce costs by performing repetitive and time-consuming tasks. However, for
robots to be effective, they must be able to navigate autonomously in fields or
orchards without human intervention. In this paper, we introduce a navigation
system that utilizes LiDAR and wheel encoder sensors for in-row, turn, and
end-row navigation in row structured agricultural environments, such as
vineyards. Our approach exploits the simple and precise geometrical structure
of plants organized in parallel rows. We tested our system in both simulated
and real environments, and the results demonstrate the effectiveness of our
approach in achieving accurate and robust navigation. Our navigation system
achieves mean displacement errors from the center line of 0.049 m and 0.372 m
for in-row navigation in the simulated and real environments, respectively. In
addition, we developed an end-row points detection that allows end-row
navigation in vineyards, a task often ignored by most works
IoT-Based Vehicle Monitoring and Driver Assistance System Framework for Safety and Smart Fleet Management
Curbing road accidents has always been one of the utmost priorities in every country. In Malaysia, Traffic Investigation and Enforcement Department reported that Malaysia’s total number of road accidents has increased from 373,071 to 533,875 in the last decade. One of the significant causes of road accidents is driver’s behaviours. However, drivers’ behaviour was challenging to regulate by the enforcement team or fleet operators, especially heavy vehicles. We proposed adopting the Internet of Things (IoT) and its’ emerging technologies to monitor and alert driver’s behavioural and driving patterns in reducing road accidents. In this work, we proposed a lane tracking and iris detection algorithm to monitor and alert the driver’s behaviour when the vehicle sways away from the lane and the driver feeling drowsy, respectively. We implemented electronic devices such as cameras, a global positioning system module, a global system communication module, and a microcontroller as an intelligent transportation system in the vehicle. We implemented face recognition for person identification using the same in-vehicle camera and recorded the working duration for authentication and operation health monitoring, respectively. With the GPS module, we monitored and alerted against permissible vehicle’s speed accordingly. We integrated IoT on the system for the fleet centre to monitor and alert the driver’s behavioural activities in real-time through the user access portal. We validated it successfully on Malaysian roads. The outcome of this pilot project benefits the safety of drivers, public road users, and passengers. The impact of this framework leads to a new regulation by the government agencies towards merit and demerit system, real-time fleet monitoring of intelligent transportation systems, and socio-economy such as cheaper health premiums. The big data can be used to predict the driver’s behavioural in the future
Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment. FMER is a subset of image processing and it
is a multidisciplinary topic to analysis. So, it requires familiarity with
other topics of Artifactual Intelligence (AI) such as machine learning, digital
image processing, psychology and more. So, it is a great opportunity to write a
book which covers all of these topics for beginner to professional readers in
the field of AI and even without having background of AI. Our goal is to
provide a standalone introduction in the field of MFER analysis in the form of
theorical descriptions for readers with no background in image processing with
reproducible Matlab practical examples. Also, we describe any basic definitions
for FMER analysis and MATLAB library which is used in the text, that helps
final reader to apply the experiments in the real-world applications. We
believe that this book is suitable for students, researchers, and professionals
alike, who need to develop practical skills, along with a basic understanding
of the field. We expect that, after reading this book, the reader feels
comfortable with different key stages such as color and depth image processing,
color and depth image representation, classification, machine learning, facial
micro-expressions recognition, feature extraction and dimensionality reduction.
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment.Comment: This is the second edition of the boo
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