10,803 research outputs found
Neuroanatomical and gene expression features of the rabbit accessory olfactory system. Implications of pheromone communication in reproductive behaviour and animal physiology
Mainly driven by the vomeronasal system (VNS), pheromone
communication is involved in many species-specific fundamental innate socio-sexual behaviors such as mating and
fighting, which are essential for animal reproduction and survival. Rabbits are a unique model for studying
chemocommunication due to the discovery of the rabbit mammary pheromone, but paradoxically there has been a
lack of knowledge regarding its VNS pathway. In this work, we aim at filling this gap by approaching the system
from an integrative point of view, providing extensive anatomical and genomic data of the rabbit VNS, as well as
pheromone-mediated reproductive and behavioural studies. Our results build strong foundation for further
translational studies which aim at implementing the use of pheromones to improve animal production and welfare
Strategies for Early Learners
Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: • Developing curriculum through the planning cycle • Theories that inform what we know about how children learn and the best ways for teachers to support learning • The three components of developmentally appropriate practice • Importance and value of play and intentional teaching • Different models of curriculum • Process of lesson planning (documenting planned experiences for children) • Physical, temporal, and social environments that set the stage for children’s learning • Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. • Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety • Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp
Targeting Fusion Proteins of HIV-1 and SARS-CoV-2
Viruses are disease-causing pathogenic agents that require host cells to replicate. Fusion of host and viral membranes is critical for the lifecycle of enveloped viruses. Studying viral fusion proteins can allow us to better understand how they shape immune responses and inform the design of therapeutics such as drugs, monoclonal antibodies, and vaccines. This thesis discusses two approaches to targeting two fusion proteins: Env from HIV-1 and S from SARS-CoV-2. The first chapter of this thesis is an introduction to viruses with a specific focus on HIV-1 CD4 mimetic drugs and antibodies against SARS-CoV-2. It discusses the architecture of these viruses and fusion proteins and how small molecules, peptides, and antibodies can target these proteins successfully to treat and prevent disease. In addition, a brief overview is included of the techniques involved in structural biology and how it has informed the study of viruses. For the interested reader, chapter 2 contains a review article that serves as a more in-depth introduction for both viruses as well as how the use of structural biology has informed the study of viral surface proteins and neutralizing antibody responses to them. The subsequent chapters provide a body of work divided into two parts. The first part in chapter 3 involves a study on conformational changes induced in the HIV-1 Env protein by CD4-mimemtic drugs using single particle cryo-EM. The second part encompassing chapters 4 and 5 includes two studies on antibodies isolated from convalescent COVID-19 donors. The former involves classification of antibody responses to the SARS-CoV-2 S receptor-binding domain (RBD). The latter discusses an anti-RBD antibody class that binds to a conserved epitope on the RBD and shows cross-binding and cross-neutralization to other coronaviruses in the sarbecovirus subgenus.</p
Investigation of a Histidine-Based Probe for the Exploration of Proteomes
Leishmaniasis is a neglected tropical disease which affects 0.7-1 million people per year. Current chemotherapies for leishmaniasis are toxic with long treatment times and reports of increasing resistance, which stresses the importance of this research area. Inositol phosphorylceramide synthase is a membrane bound enzyme that has no direct human homologue, which converts ceramide to inositol phosphorylceramide through the action of a highly conserved HHD catalytic triad. An ideal method to study this enzyme further would be through activity-based protein profiling, however, there are currently no activity-based probes reported that reacts with this type of active site. Therefore, an activity-based probe was designed based on the structure of diethyl pyrocarbonate, a compound known to bind covalently to active site histidine residues. The synthesised activity-based probe was shown to inhibit Leishmania major inositol phosphorylceramide synthase in a simple assay. In addition, the probe was shown to selectively bind to the active site histidine residue in two pure enzyme models; one of which has the same catalytic triad as inositol phosphorylceramide synthase, and the other was an acid base active site histidine residue. Further, this activity-based probe was able to isolate an overexpressed enzyme in the lysate of Escherichia coli as well as bind to intrinsic proteins. Following the function validation of the activity-based probe, preliminary work was started in Leishmania to isolate proteins identify expressed enzymes
Statistical Learning for Gene Expression Biomarker Detection in Neurodegenerative Diseases
In this work, statistical learning approaches are used to detect biomarkers for neurodegenerative diseases (NDs). NDs are becoming increasingly prevalent as populations age, making understanding of disease and identification of biomarkers progressively important for facilitating early diagnosis and the screening of individuals for clinical trials. Advancements in gene expression profiling has enabled the exploration of disease biomarkers at an unprecedented scale. The work presented here demonstrates the value of gene expression data in understanding the underlying processes and detection of biomarkers of NDs. The value of novel approaches to previously collected -omics data is shown and it is demonstrated that new therapeutic targets can be identified. Additionally, the importance of meta-analysis to improve power of multiple small studies is demonstrated. The value of blood transcriptomics data is shown in applications to researching NDs to understand underlying processes using network analysis and a novel hub detection method. Finally, after demonstrating the value of blood gene expression data for investigating NDs, a combination of feature selection and classification algorithms were used to identify novel accurate biomarker signatures for the diagnosis and prognosis of Parkinson’s disease (PD) and Alzheimer’s disease (AD). Additionally, the use of feature pools based on previous knowledge of disease and the viability of neural networks in dimensionality reduction and biomarker detection is demonstrated and discussed. In summary, gene expression data is shown to be valuable for the investigation of ND and novel gene biomarker signatures for the diagnosis and prognosis of PD and AD
Antibody Targeting of HIV-1 Env: A Structural Perspective
A key component of contemporary efforts toward a human immunodeficiency virus 1 (HIV-1) vaccine is the use of structural biology to understand the structural characteristics of antibodies elicited both from human patients and animals immunized with engineered 'immunogens,' or early vaccine candidates. This thesis will report on projects characterizing both types of antibodies against HIV-1. Chapter 1 will introduce relevant topics, including the reasons HIV-1 is particularly capable of evading the immune system in natural infection and after vaccination, the 20+ year history of unsuccessful HIV-1 vaccine large-scale efficacy trials, an introduction to broadly neutralizing antibodies (bNAbs), and a review of common strategies utilized in HIV-1 immunogen design today. Chapter 2 describes the isolation, high-resolution structural characterization, and in vitro resistance profile of a new bNAb, 1-18, that is both very broad and potent, as well as able to restrict HIV-1 escape in vivo. Chapter 3 reports the results of an epitope-focusing immunogen design and immunization experiment carried out in wild type mice, rabbits, and non-human primates where it was shown that B cells targeting the desired epitope were expanded after a single prime immunization with immunogen RC1 or a variant, RC1-4fill. Chapter 4 describes Ab1245, an off-target non-neutralizing monoclonal antibody isolated in a macaque that had been immunized with a series of sequential immunogens after the prime immunization reported in Chapter 3. The antibody structure describes a specific type of distracting response as it binds in a way that causes a large structural change in Env, resulting in the destruction of the neutralizing fusion peptide epitope. Chapter 5 is adapted from a review about how antibodies differentially recognize the viruses HIV-1, SARS-CoV-2, and Zika virus. This review serves as an introduction to the virus SARS-CoV-2, which is the topic of the final chapter, Chapter 6. In this chapter, structures of many neutralizing antibodies isolated from SARS-CoV-2 patients were used to define potentially therapeutic classes of neutralizing receptor-binding domain (RBD) antibodies based on their epitopes and binding profiles
The mechanisms of antibody generation in the llama
The llama is able to generate a unique class of antibody. The heavy chain immunoglobulins consist only of two heavy chain polypeptides and bind antigen specifically through single protein domains. Although the mechanisms by which such an antibody interacts with antigen has been studied at some length the manner in which the heavy chain antibody is generated within the llama is unknown. In this study a number of components of the llama immune system have been characterised. The isolation of genes encoding the variable domain of the heavy chain antibody indicates that specific genetic elements within the llama genome are responsible for the generation of the heavy chain antibody. The discovery of constant region genes that encode the heavy chain antibody provides an explanation for the absence of a major immunoglobulin domain from the final, secreted gene product. The lack of this domain within the expressed antibody is believed to be the result of a single nucleotide splice site mutation. In order to investigate the process of llama antibody generation further additional components of the llama immune system, the recombination activating genes (rag) were isolated. One such llama rag gene (rag-i) was cloned, expressed and utilised in an in vitro assay system to investigate recombination events taking place during antibody generation. This assay involved the use of specific signal sequences derived from variable domain gene sequence data and represents, to our knowledge, the first examination of non-murine RAG activity. Through the use of this system distinct differences between llama and mouse recombination signal sequences (RSSs) were uncovered. These differences, located within a specific region of the RSS known as the coding flank, may play an important role in llama antibody generation. These results have led to the proposal of a number of models for the mechanisms involved in llama antibody generation
SYSTEMS METHODS FOR ANALYSIS OF HETEROGENEOUS GLIOBLASTOMA DATASETS TOWARDS ELUCIDATION OF INTER-TUMOURAL RESISTANCE PATHWAYS AND NEW THERAPEUTIC TARGETS
In this PhD thesis is described an endeavour to compile litterature about Glioblastoma key molecular mechanisms into a directed network followin Disease Maps standards, analyse its topology and compare results with quantitative analysis of multi-omics datasets in order to investigate Glioblastoma resistance mechanisms. The work also integrated implementation of Data Management good practices and procedures
Industry 4.0: product digital twins for remanufacturing decision-making
Currently there is a desire to reduce natural resource consumption and expand circular business principles whilst Industry 4.0 (I4.0) is regarded as the evolutionary and potentially disruptive movement of technology, automation, digitalisation, and data manipulation into the industrial sector. The remanufacturing industry is recognised as being vital to the circular economy (CE) as it extends the in-use life of products, but its synergy with I4.0 has had little attention thus far. This thesis documents the first investigating into I4.0 in remanufacturing for a CE contributing a design and demonstration of a model that optimises remanufacturing planning using data from different instances in a product’s life cycle.
The initial aim of this work was to identify the I4.0 technology that would enhance the stability in remanufacturing with a view to reducing resource consumption. As the project progressed it narrowed to focus on the development of a product digital twin (DT) model to support data-driven decision making for operations planning. The model’s architecture was derived using a bottom-up approach where requirements were extracted from the identified complications in production planning and control that differentiate remanufacturing from manufacturing. Simultaneously, the benefits of enabling visibility of an asset’s through-life health were obtained using a DT as the modus operandi. A product simulator and DT prototype was designed to use Internet of Things (IoT) components, a neural network for remaining life estimations and a search algorithm for operational planning optimisation. The DT was iteratively developed using case studies to validate and examine the real opportunities that exist in deploying a business model that harnesses, and commodifies, early life product data for end-of-life processing optimisation. Findings suggest that using intelligent programming networks and algorithms, a DT can enhance decision-making if it has visibility of the product and access to reliable remanufacturing process information, whilst existing IoT components provide rudimentary “smart” capabilities, but their integration is complex, and the durability of the systems over extended product life cycles needs to be further explored
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