7,887 research outputs found
Investigating the Innate Immune Systems of Bats and Their Roles as Zoonotic Viral Reservoirs
The zoonotic spillover of viral pathogens from wild animal reservoirs into human populations remains the leading cause of emerging and re-emerging infectious diseases globally. Bats represent important viral reservoirs, notorious for the diversity and richness of the viruses they host, several of which are highly pathogenic when transmitted to humans. Remarkably, bats appear to host an abundance of these viruses without exhibiting any clinical signs of disease. A dominant hypothesis for this ability suggests that bats can control viral replication early in the innate immune response, which acts as the first line of defence against infection. However, bat immunology remains fundamentally understudied, largely due to their high species diversity and the lack of accessible reagents required for bat research. Therefore, in this work we explored and characterised key components of bat innate immunity to gain a better understanding of bats as viral reservoirs and contribute to the currently limited literature. Here, we demonstrated the in vitro transcriptomic response of the bat model species, Pteropus alecto (P.alecto) upon stimulation with the bat henipavirus Cedar virus and also with a type III bat interferon (paIFNĪ»). These investigations highlighted key transcripts, some of which were immune-related, in the response of bats to the separate stimuli and presents a foundation for further research into significant genes concerned in bat viral infection. Building from genome-wide transcriptomics, three distinctive bat innate immune genes representative of different stages of interferon signalling were selected for comparative genomics and functional characterisation. Our work demonstrated the conservation of genes between bats and humans, including IRF7, IFIT5 and IFI35. Specific findings for IRF7 included its successful translocation to the cell nucleus upon stimulation. IFIT5 and IFI35 were specifically selected for exploration due to previous research demonstrating the respective antiviral and conflicting anti- or pro-viral roles of these genes in humans. Significantly, our research demonstrated the direct antiviral action of P.alecto IFIT5 against negative-sense RNA viruses. Collectively, our findings offer valuable contributions to the field of bat antiviral immunity and provide the framework for future investigative studies into the role and function of the bat innate immune system and bat viral tolerance mechanisms
Overcoming drug resistance: targeting the BCL-2 family and the long non-coding RNA HCP5 in medulloblastoma and colorectal cancer
Colorectal cancer (CRC) is one of the most common cancers in the UK and medulloblastoma is a common cancer found in children. While there has been a progressive improvement in treatment outcomes, success has been marred by drug resistance and severe side effects. Therefore, this project focused on two aspects of chemotherapeutic drug resistance, the first using the antimitotic agent vincristine in combination with inhibitors of the anti-apoptotic Bcl-2 family proteins, while the second investigated the role of the long non-coding RNA (lncRNA), HCP5 in the resistance of cells to genotoxic agents. In the first part, three medulloblastoma cell lines (DAOY, MB03, ONS76) were analysed for the expression of Bcl-xL and ONS76 cells found to have the highest level of this anti-apoptotic protein. Subsequent results indicated that Bcl-xL encourages mitotic slippage and stemness and that knockdown of Bcl-xL in the high expressing ONS76 cells, reduces these and sensitizes the cells to the anti-mitotic agent vincristine. Thus, pharmacological inhibition of Bcl-xL should sensitize medulloblastoma cells to low doses of vincristine. Regarding the lncRNA HCP5, results showed that HCP5 was generally more highly expressed in a panel of CRC cell lines than the three medulloblastoma cell lines, corroborating data from an in-silico analysis for the corresponding tumours. One function of HCP5 is to translocate the multifunctional YB-1 protein from the cytoplasm to the nucleus where it carries out many of its functions. Knockdown of HCP5 followed by immunofluorescence indicated a reduction in the amount of YB-1 in the nucleus, confirming this function. Subsequently, HCP5 silencing sensitized all cell lines tested to the DNA damaging agents, cisplatin, oxaliplatin and tert-butyl hydroperoxide and also resulted in an increase in double-strand breaks as determined by H2AX formation. Finally, fluorescence activated cell sorting using Annexin V and propidium iodide confirmed a decrease in cell viability in HCP5 knockdown cells following treatment with genotoxic agents and that this was mirrored by an increased apoptotic fraction. Together, these studies indicate the possibilities of using novel therapeutics to increase the functionality of existing treatments to combat acquired drug resistance in cancer patients
Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse
This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses.
This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups.
In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in usersā speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018ā6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena
Artificial Intelligence, Robots, and Philosophy
This book is a collection of all the papers published in the special issue āArtificial Intelligence, Robots, and Philosophy,ā Journal of Philosophy of Life, Vol.13, No.1, 2023, pp.1-146. The authors discuss a variety of topics such as science fiction and space ethics, the philosophy of artificial intelligence, the ethics of autonomous agents, and virtuous robots. Through their discussions, readers are able to think deeply about the essence of modern technology and the future of humanity. All papers were invited and completed in spring 2020, though because of the Covid-19 pandemic and other problems, the publication was delayed until this year. I apologize to the authors and potential readers for the delay. I hope that readers will enjoy these arguments on digital technology and its relationship with philosophy. ***
Contents***
Introduction
: Descartes and Artificial Intelligence;
Masahiro Morioka***
Isaac Asimov and the Current State of Space Science Fiction
: In the Light of Space Ethics;
Shin-ichiro Inaba***
Artificial Intelligence and Contemporary Philosophy
: Heidegger, Jonas, and Slime Mold;
Masahiro Morioka***
Implications of Automating Science
: The Possibility of Artificial Creativity and the Future of Science;
Makoto Kureha***
Why Autonomous Agents Should Not Be Built for War;
IstvƔn ZoltƔn ZƔrdai***
Wheat and Pepper
: Interactions Between Technology and Humans;
Minao Kukita***
Clockwork Courage
: A Defense of Virtuous Robots;
Shimpei Okamoto***
Reconstructing Agency from Choice;
Yuko Murakami***
Gushing Prose
: Will Machines Ever be Able to Translate as Badly as
Humans?;
Rossa Ć Muireartaigh**
Commercialization of Separated Human Body Parts - Unpacking Instrumentalization Approach
The principle of non-commercialization, which prohibits trade in separated human body parts, has long been firmly embedded in many European legal orders and has become an integral part of them. However, many new uses for human biomaterials have now been discovered, and the need for them has reached a historical climax. This paper aims to explain the main tenets of non-commercialization theory, including such principles as human dignity and need to protect humanās health, and to show that these categories have so far been understood in a very one-sided and visceral way, and largely in contradiction to their true spirit. We will not dwell on a critique of the existing approach, but will propose an instrumental approach to human health based primarily on the will of the individual. At the end of this paper, we will describe possible legal constructs through which the market for separated human body parts can function, and the outcomes of adoption of one or another model
Meta-ontology fault detection
Ontology engineering is the field, within knowledge representation, concerned with using logic-based formalisms to represent knowledge, typically moderately sized knowledge bases called ontologies. How to best develop, use and maintain these ontologies has produced relatively large bodies of both formal, theoretical and methodological research.
One subfield of ontology engineering is ontology debugging, and is concerned with preventing, detecting and repairing errors (or more generally pitfalls, bad practices or faults) in ontologies. Due to the logical nature of ontologies and, in particular, entailment, these faults are often both hard to prevent and detect and have far reaching consequences. This makes ontology debugging one of the principal challenges to more widespread adoption of ontologies in applications.
Moreover, another important subfield in ontology engineering is that of ontology alignment: combining multiple ontologies to produce more powerful results than the simple sum of the parts. Ontology alignment further increases the issues, difficulties and challenges of ontology debugging by introducing, propagating and exacerbating faults in ontologies.
A relevant aspect of the field of ontology debugging is that, due to the challenges and difficulties, research within it is usually notably constrained in its scope, focusing on particular aspects of the problem or on the application to only certain subdomains or under specific methodologies. Similarly, the approaches are often ad hoc and only related to other approaches at a conceptual level. There are no well established and widely used formalisms, definitions or benchmarks that form a foundation of the field of ontology debugging.
In this thesis, I tackle the problem of ontology debugging from a more abstract than usual point of view, looking at existing literature in the field and attempting to extract common ideas and specially focussing on formulating them in a common language and under a common approach. Meta-ontology fault detection is a framework for detecting faults in ontologies that utilizes semantic fault patterns to express schematic entailments that typically indicate faults in a systematic way. The formalism that I developed to represent these patterns is called existential second-order query logic (abbreviated as ESQ logic). I further reformulated a large proportion of the ideas present in some of the existing research pieces into this framework and as patterns in ESQ logic, providing a pattern catalogue.
Most of the work during my PhD has been spent in designing and implementing
an algorithm to effectively automatically detect arbitrary ESQ patterns in arbitrary ontologies. The result is what we call minimal commitment resolution for ESQ logic, an extension of first-order resolution, drawing on important ideas from higher-order unification and implementing a novel approach to unification problems using dependency graphs. I have proven important theoretical properties about this algorithm such as its soundness, its termination (in a certain sense and under certain conditions) and its fairness or completeness in the enumeration of infinite spaces of solutions.
Moreover, I have produced an implementation of minimal commitment resolution for ESQ logic in Haskell that has passed all unit tests and produces non-trivial results on small examples. However, attempts to apply this algorithm to examples of a more realistic size have proven unsuccessful, with computation times that exceed our tolerance levels.
In this thesis, I have provided both details of the challenges faced in this regard,
as well as other successful forms of qualitative evaluation of the meta-ontology fault detection approach, and discussions about both what I believe are the main causes of the computational feasibility problems, ideas on how to overcome them, and also ideas on other directions of future work that could use the results in the thesis to contribute to the production of foundational formalisms, ideas and approaches to ontology debugging that can properly combine existing constrained research. It is unclear to me whether minimal commitment resolution for ESQ logic can, in its current shape, be implemented efficiently or not, but I believe that, at the very least, the theoretical and conceptual underpinnings that I have presented in this thesis will be useful to produce more
foundational results in the field
DeepHTLV: a Deep Learning Framework for Detecting Human T-Lymphotrophic Virus 1 Integration Sites
In the 1980s, researchers found the first human oncogenic retrovirus called human T-lymphotrophic virus type 1 (HTLV-1). Since then, HTLV-1 has been identified as the causative agent behind several diseases such as adult T-cell leukemia/lymphoma (ATL) and a HTLV-1 associated myelopathy or tropical spastic paraparesis (HAM/TSP). As part of its normal replication cycle, the genome is converted into DNA and integrated into the genome. With several hundreds to thousands of unique viral integration sites (VISs) distributed with indeterminate preference throughout the genome, detection of HTLV-1 VISs is a challenging task. Experimental studies typically use molecular biology techniques such as fluorescent in-situ hybridization (FISH) or using rt-qPCR (reverse transcriptase quantitative PCR) to detect VISs. While these methods are accurate, they cannot be applied in a high throughput manner. Next generation sequencing (NGS) has generated vast amounts of data, resulting in the development of several computational methods for VIS detection such as VERSE, VirusFinder, or DeepVISP for the task of rapid detection VIS across an entire genome. However, no such model exists for predicting HTLV-1 VISs. In this study, we have developed DeepHTLV: the first deep neural network for accurate detection of HTLV-1 insertion sites. We focused on 1) accurately predicting HTLV-1 VISs by extracting and generating superior feature representations and 2) uncovering the cis-regulatory features surrounding the insertion sites. DeepHTLV was implemented as a deep convolutional neural network (CNN) with self-attention architecture after comparing with several other deep neural network structures. To improve model accuracy, we trained the model using a bootstrap balanced sampling method with 10-fold CV. Furthermore, we demonstrated that this model has higher accuracy than several traditional machine learning models, with a modest improvement in area under the curve (AUC) values by 3-10%. To study the cis-regulatory features around HTLV-1 insertion sites, we extracted informative motifs from convolutional layer. Clustering of these motifs yielded eight unique consensus sequence motifs that represented potential integration sites in humans. The informative motif sequences were matched with a known transcription factor (TF) binding profile database, JASPAR2020, with the sequence matching tool TOMTOM. 79 TFs associations were enriched in regions surrounding HTLV-1 VISs. Furthermore, literature screening of HTLV-1, ATL, and HAM/TSP validated nearly half (34) of the predicted TFs interactions. This work demonstrates that DeepHTLV can accurately identify HTLV-1 VISs, elucidate surrounding features regulating these insertion sites, and make biologically meaningful predictions about cis-regulatory elements surrounding the insertion sites
Temporary career transition: a case study of the loan transfer process and experience in the English professional football environment
The current PhD explores loan transfers in English professional football as a
temporary transition. In sport, career termination has initially been prioritised, with
wider transitions gaining greater attention over time (see: Ivarsson et al., 2018; Taylor
and Ogilvie, 1994). However, little attention has been given to supporting and
preparing individuals for permanent and temporary transfers in football. This is
particularly important to explore given the introduction, yet lack of evaluation, of the
Elite Player Performance Plan (EPPP) in 2012, which intended to increase holistic
development and home grown talent development in England (Horrocks et al., 2016).
To address this research gap, this thesis adopts a qualitative case study, drawing on
interviews and document analysis, to gain in-depth insight to the experiences of an
elite, high quality sample of players and staff across a range of Premier League and
Championship clubs with regards to the loan process. The objectives of the research
were to: a) explore the role of the Loan Managers (LMs) and their responsibilities in
supporting loan players and processes; b) understand the perspectives of wider club
staff, LMs and players to explore the loan process as a novel temporary transition; and
c) develop recommendations regarding the LM role and broader loans process for
individuals, clubs and policy-makers. There were a range of significant insights and
novel contributions when addressing the objectives, including the lack of clarity for
LMs and their day to day responsibilities. Similarly, consideration of wider perspectives
allowed understanding of multi-disciplinary team (MDT) involvement as well as wider
support and decision-making processes surrounding loan processes. Additionally, the
current research recommends that professional football clubs ensure that a support
structure is provided for LMs, whereby National Governing Bodies (NGBs) and
organisations (e.g. Football Association; FA, English Premier League; EPL) could
provide more formal support networks across clubs and leagues to ensure that sharing
of best practice is in place. This may also help clubs and wider organisations place
greater value on the loan transfer process, especially in line with the EPPPās
prioritisation of holistic development of homegrown talent, along with continued
developments implemented by FeĢdeĢration Internationale de Football Association
(FIFA, 2022) regarding loan regulations
The deubiquitinating enzyme MINDY2 promotes pancreatic cancer proliferation and metastasis by stabilizing ACTN4 expression and activating the PI3K/AKT/mTOR signaling pathway
The pathogenic mechanisms of pancreatic cancer (PC) are still not fully understood. Ubiquitination modifications have a crucial role in tumorigenesis and progression. Yet, the role of MINDY2, a member of the motif interacting with Ub-containing novel DUB family (MINDY), as a newly identified deubiquitinating enzyme, in PC is still unclear. In this study, we found that MINDY2 expression is elevated in PC tissue (clinical samples) and was associated with poor prognosis. We also found that MINDY2 is associated with pro-carcinogenic factors such as epithelial-mesenchymal transition (EMT), inflammatory response, and angiogenesis; the ROC curve suggested that MINDY2 has a high diagnostic value in PC. Immunological correlation analysis suggested that MINDY2 is deeply involved in immune cell infiltration in PC and is associated with immune checkpoint-related genes. In vivo and in vitro experiments further suggested that elevated MINDY2 promotes PC proliferation, invasive metastasis, and EMT. Meanwhile, actinin alpha 4 (ACTN4) was identified as a MINDY2-interacting protein by mass spectrometry and other experiments, and ACTN4 protein levels were significantly correlated with MINDY2 expression. The ubiquitination assay confirmed that MINDY2 stabilizes the ACTN4 protein level by deubiquitination. The pro-oncogenic effect of MINDY2 was significantly inhibited by silencing ACTN4. Bioinformatics Analysis and Western blot experiments further confirmed that MINDY2 stabilizes ACTN4 through deubiquitination and thus activates the PI3K/AKT/mTOR signaling pathway. In conclusion, we identified the oncogenic role and mechanism of MINDY2 in PC, suggesting that MINDY2 is a viable candidate gene for PC and may be a therapeutic target and critical prognostic indicator
Using collections to explore the evolution of plant associated lifestyles in the Ascomycota
The Ascomycota form the largest phylum in the fungal kingdom and show a wide diversity of lifestyles, some involving beneficial or harmful associations with plants. Distinguishing between fungal endophytes ā species which live asymptomatically in plant tissues ā and plant pathogens is of major significance to economic and ecological issues relating to plant health. Evolutionary genomics methods can provide insight into the genetic determinants of these lifestyles, and collections can act as an invaluable source of material to enable such analyses. As endophytes are comparatively poorly studied, comparing plant associated lifestyles in the Ascomycota first requires novel endophyte discovery. In this thesis, I have demonstrated the unexplored promise of Kewās Millennium Seed Bank for isolating viable fungal endophytes and, in the process, highlighted the potential issues of overlooking the seed microbiome in the seed banking practice. I then performed whole genome sequencing, assembly and annotation of novel endophytic Fusarium strains for a case-study exploring lifestyle evolution in the genus. The distribution of lifestyles across the phylogeny; similarity of gene repertoires; and patterns of codon optimisation suggested that Fusarium taxa have a shared capacity for pathogenicity/endophytism. Exploring to what extent these results are common to different lineages of the Ascomycota requires the generation of new genomic resources for endophytes at large. Consequently, I sequenced, assembled and annotated genomes for a further 15 endophyte strains from CABIās collections, which spanned 8 families and 5 orders and additionally represent the first assembly for the genus and/or species for 7 of the strains. Together, this thesis demonstrates the value of existing plant and fungal collections for producing material and data to explore the pathogenic-mutualistic spectrum in plant associated ascomycetes
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