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Aldehyde Dehydrogenases and Prostate Cancer: Shedding Light on Isoform Distribution to Reveal Druggable Target
No full textYesProstate cancer represents the most common malignancy diagnosed in men, and is the second-leading cause of cancer death in this population. In spite of dedicated efforts, the current therapies are rarely curative, requiring the development of novel approaches based on innovative molecular targets. In this work, we validated aldehyde dehydrogenase 1A1 and 1A3 isoform expressions in different prostatic tissue-derived cell lines (normal, benign and malignant) and patient-derived primary prostate tumor epithelial cells, demonstrating their potential for therapeutic intervention using a small library of aldehyde dehydrogenase inhibitors. Compound 3b, 6-(4-fluorophenyl)-2-phenylimidazo [1,2-a]pyridine exhibited not only antiproliferative activity in the nanomolar range against the P4E6 cell line, derived from localized prostate cancer, and PC3 cell lines, derived from prostate cancer bone metastasis, but also inhibitory efficacy against PC3 colony-forming efficiency. Considering its concomitant reduced activity against normal prostate cells, 3b has the potential as a lead compound to treat prostate cancer by means of a still untapped molecular target
Functional linguistic based motivations for a conversational software agent
No full textYesThis chapter discusses a linguistically orientated model of a conversational software agent (CSA) (Panesar 2017) framework sensitive to natural language processing (NLP) concepts and the levels of adequacy of a functional linguistic theory (LT). We discuss the relationship between NLP and knowledge representation (KR), and connect this with the goals of a linguistic theory (Van Valin and LaPolla 1997), in particular Role and Reference Grammar (RRG) (Van Valin Jr 2005). We debate the advantages of RRG and consider its fitness and computational adequacy. We present a design of a computational model of the linking algorithm that utilises a speech act construction as a grammatical object (Nolan 2014a, Nolan 2014b) and the sub-model of belief, desire and intentions (BDI) (Rao and Georgeff 1995). This model has been successfully implemented in software, using the resource description framework (RDF), and we highlight some implementation issues that arose at the interface between language and knowledge representation (Panesar 2017)
A review on hydrodynamics of free surface flows in emergent vegetated channels
No full textYesThis review paper addresses the structure of the mean flow and key turbulence quantities in free-surface flows with emergent vegetation. Emergent vegetation in open channel flow affects turbulence, flow patterns, flow resistance, sediment transport, and morphological changes. The last 15 years have witnessed significant advances in field, laboratory, and numerical investigations of turbulent flows within reaches of different types of emergent vegetation, such as rigid stems, flexible stems, with foliage or without foliage, and combinations of these. The influence of stem diameter, volume fraction, frontal area of stems, staggered and non-staggered arrangements of stems, and arrangement of stems in patches on mean flow and turbulence has been quantified in different research contexts using different instrumentation and numerical strategies. In this paper, a summary of key findings on emergent vegetation flows is offered, with particular emphasis on: (1) vertical structure of flow field, (2) velocity distribution, 2nd order moments, and distribution of turbulent kinetic energy (TKE) in horizontal plane, (3) horizontal structures which includes wake and shear flows and, (4) drag effect of emergent vegetation on the flow. It can be concluded that the drag coefficient of an emergent vegetation patch is proportional to the solid volume fraction and average drag of an individual vegetation stem is a linear function of the stem Reynolds number. The distribution of TKE in a horizontal plane demonstrates that the production of TKE is mostly associated with vortex shedding from individual stems. Production and dissipation of TKE are not in equilibrium, resulting in strong fluxes of TKE directed outward the near wake of each stem. In addition to Kelvin-Helmholtz and von Kármán vortices, the ejections and sweeps have profound influence on sediment dynamics in the emergent vegetated flows
Pentagonal scheme for dynamic XML prefix labelling
Get PDFIn XML databases, the indexing process is based on a labelling or
numbering scheme and generally used to label an XML document to
perform an XML query using the path node information. Moreover, a
labelling scheme helps to capture the structural relationships during the
processing of queries without the need to access the physical document.
Two of the main problems for labelling XML schemes are duplicated
labels and the cost efficiency of labelling time and size. This research
presents a novel dynamic XML labelling scheme, called the Pentagonal
labelling scheme, in which data are represented as ordered XML nodes
with relationships between them. The update of these nodes from large scale XML documents has been widely investigated and represents a
challenging research problem as it means relabelling a whole tree. Our
algorithms provide an efficient dynamic XML labelling scheme that
supports data updates without duplicating labels or relabelling old nodes.
Our work evaluates the labelling process in terms of size and time, and
evaluates the labelling scheme’s ability to handle several insertions in
XML documents. The findings indicate that the Pentagonal scheme
shows a better initial labelling time performance than the compared
schemes, particularly when using large XML datasets. Moreover, it
efficiently supports random skewed updates, has fast calculations and
uncomplicated implementations so efficiently handles updates. Also, it
proved its capability in terms of the query performance and in determining
the relationships.Libyan governmen
Evaluating the use of a theory-based intervention to improve medication-taking behaviours: A Longitudinal mixed-methods study in patients with Pulmonary Arterial Hypertension. Applying Health Belief Model theory to understand patients’ medication and disease beliefs and using this to develop and evaluate targeted interventions delivered by a pharmacist to improve medication adherence
No full textPulmonary Arterial Hypertension (PAH) is a rare incurable condition affecting both the cardiac and respiratory systems. Patients living with PAH face the burden of both intensive medication regimens and debilitating disease symptoms. This study’s primary aim was to identify patients’ medication-taking behaviours and beliefs using a framework derived from the extended health belief model (EHBM), and to use this information to deliver personalised interventions to improve medication-taking behaviours. A
mixed-methodology longitudinal study design recorded patients’ parameters
over a 12-month period. Thirteen participants from Northern Ireland
completed the study. The results showed that the level of high-adherence to
PAH medicines, as assessed using the MARS questionnaire was 80%, but
this value differed when assessed via pill counting and interview data. There was a trend to improvement in observed and predicted medication adherence over the study duration. Participants’ beliefs showed a non-statistical increase in the specific-necessity beliefs and a reduction in
general-overuse belief. This study added to the EHBM new constructs of trust and support in being able to better predict nonadherent behaviours. Key medication-taking themes were self-confidence, perceived ranking of medicines, uncertainty and knowledge. This study developed important
learning that can be applied to future research on behavioural health studies.Heart Trust Fund;
Actelion Pharmaceutical
Investigation of Nigerian Ethno-medicinal Plants as Potential Sources of Cytotoxic and Anti-plasmodial Compounds. Biological activity of Vitellaria paradoxa, Cyperus articulatus, Securidaca longepedunculata and semi-synthetic halogenated analogues of cryptolepine isolated from Cryptolepis sanguinolenta
No full textNatural products are acknowledged sources of novel compounds for use in
the treatment of diseases such as cancer, malaria, and human African
trypanosomiasis. However, health burdens of such diseases still remain high,
with drug resistance leading to failure of current medication. Therefore, there
is a need for new treatments, and this project considers the potential of
Nigerian ethno-medicinal plants and their products. Firstly, the aims were to
isolate cytotoxic compounds through bio-guided evaluation and fractionation
from 3 medicinal plants; Vitellaria paradoxa, Cyperus articulatus and
Securidaca longepedunculata used traditionally in the treatment of cancer in
North-East Nigeria. Extracts from S. longepedunculata were the most active
when assessed in a panel of cancer cell lines, with IC50 values below 10 µg/ml,
whilst fractions isolated from V. paradoxa and C. articulatus were moderately
cytotoxic and able to overcome drug resistance mechanisms in drug resistant cell lines. In the second part of the thesis, novel cryptolepine analogues were
semi-synthesized using environmentally friendly methods and evaluated for
cytotoxic, anti-plasmodial and anti-trypanosomal activity. The compounds
were found to be highly cytotoxic in cancer cell lines with the ability to
overcome drug resistant mechanisms, with sub-µM IC50 values, and were also
active against drug resistant strains of Plasmodium parasites in addition to
Trypanosoma brucei, with IC50 values below 500 nM, and 300 pM respectively.Schlumberger Faculty for the Future Foundatio
Machine Learning for 3D Visualisation Using Generative Models
Get PDFOne of the state-of-the-art highlights of deep learning in the past ten years is the introduction of generative adversarial networks (GANs), which had achieved great success in their ability to generate images comparable to real photos with minimum human intervention. These networks can generalise to a multitude of desired outputs, especially in image-to-image problems and image syntheses. This thesis proposes a computer graphics pipeline for 3D rendering by utilising generative adversarial networks (GANs).
This thesis is motivated by regression models and convolutional neural networks (ConvNets) such as U-Net architectures, which can be directed to generate realistic global illumination effects, by using a semi-supervised GANs model (Pix2pix) that is comprised of PatchGAN and conditional GAN which is then accompanied by a U-Net structure. Pix2pix had been chosen for this thesis for its ability for training as well as the quality of the output images. It is also different from other forms of GANs by utilising colour labels, which enables further control and consistency of the geometries that comprises the output image.
The series of experiments were carried out with laboratory created image sets, to pursue the possibility of which deep learning and generative adversarial networks can lend a hand to enhance the pipeline and speed up the 3D rendering process. First, ConvNet is applied in combination with Support Vector Machine (SVM) in order to pair 3D objects with their corresponding shadows, which can be applied in Augmenter Reality (AR) scenarios. Second, a GANs approach is presented to generate shadows for non-shadowed 3D models, which can also be beneficial in AR scenarios. Third, the possibility of generating high quality renders of image sequences from low polygon density 3D models using GANs. Finally, the possibility to enhance visual coherence of the output image sequences of GAN by utilising multi-colour labels.
The results of the adopted GANs model were able to generate realistic outputs comparable to the lab generated 3D rendered ground-truth and control group output images with plausible scores on PSNR and SSIM similarity index metrices
Understanding the eating and drinking experiences of people living with dementia and dysphagia in care homes: A qualitative study of the multiple perspectives of the person, their family, care home staff and Speech and Language Therapists
Get PDFAims: The aim of this study was to understand the eating and drinking experiences of people living with dementia and dysphagia in care homes from their perspective and those of their family members, formal care staff and Speech and Language Therapists (SLT).
Design and methods: In this multi-method qualitative study, semi-structured interviews were carried out with 14 care home residents, seven family members of people living with dementia and dysphagia, and 13 care home staff with a variety of roles. Structured observations, using Dementia Care Mapping, were carried out with eight people living with dementia and dysphagia. Additionally, focus groups were carried out with a total of 31 SLTs. Data were analysed using thematic analysis.
Findings: The findings of this study highlighted the changes experienced by people living in care homes, and those living with dementia and dysphagia, in relation to eating and drinking. In particular an impact on identity was found. This study highlighted the challenges of multiple people being involved in dysphagia care, with unclear roles and responsibilities and ineffective channels of communication. Despite the challenges identified, there were also examples of positive eating and drinking experiences through connections with others and the celebration of meaningful events.
Conclusion: This was the first study that sought to explore and understand the eating and drinking experiences of people living with dementia and dysphagia from multiple perspectives. The findings highlight the challenges involved and possible solutions to promote a more person-centred approach to eating and drinking for people living with dementia and dysphagia.Alzheimer’s Society;
Compass Grou
Mechanistic understanding of competitive destabilization of carbamazepine cocrystals under solvent free conditions
No full textNoMechanistic understanding of competitive destabilization of carbamazepine:nicotinamide and carbamazepine:saccharin cocrystals under solvent free conditions has been investigated. The crystal phase transformations were monitored using hot stage microscopy, variable-temperature powder X-ray diffraction, and sublimation experiments. The destabilization of the two cocrystals occurs via two distinct mechanisms: vapor and eutectic phase formations. Vapor pressure measurements and thermodynamic calculations using fusion and sublimation enthalpies were in good agreement with experimental findings. The mechanistic understanding is important to maintain the stability of cocrystals during solvent free green manufacturing.EPSRC (EP/J003360/1, EP/ L027011/1). MHD. Bashir would like to thank CARA for providing doctoral degree scholarship
Enhancing poly(lactic acid) microcellular foams by formation of distinctive crystalline structures
No full textYesBy controlling the crystallization behavior of poly(lactic acid) (PLA) in the presence of a hydrazide nucleating agent (HNA), PLA-HNA foams with enhanced microcellular structures were prepared via supercritical CO2 foaming. It was found that HNA can self-assemble into fibrillar networks, inducing the crystallization of PLA on their surface, and "shish-kebab"crystalline structures with high crystallinity formed, which can be maintained during the whole foaming process. Incorporation of HNA promoted the formation of gt conformers, improved the amount of dissolved CO2, hindered the escape of CO2, and increased the viscoelasticity of PLA. Compared with neat PLA foam, for PLA-HNA foam, the average cell diameter decreased obviously, from 64.39 to 6.59 μm, while the cell density increased up to nearly three orders of magnitudes, from 6.82 × 106 to 4.44 × 109 cells/cm3. Moreover, lots of fibrillar structures appeared and entangled with each other on the cell wall of the foam. By forming such dense micropores and enhanced fibrillar structures, PLA foam was highly reinforced with significantly improved compressive strength.This research was financially supported by National Natural Science Foundation of China (grant no. 51773122) and State Key Laboratory of Polymer Materials Engineering (grant no. sklpme2019-2-21)