17 research outputs found

    Venom Yield, Regeneration, and Composition in the Centipede Scolopendra Polymorpha

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    In this dissertation, I investigated yield, regeneration, and composition of centipede venom. In the first of three empirical studies, I investigated how size influenced venom volume yield and protein concentration in Scolopendra polymorpha and S. subspinipes. I also examined additional potential influences on yield in S. polymorpha, including relative forcipule size, relative mass, geographic origin, sex, time in captivity, and milking history. Volume yield was positively linearly related to body length in both species; however, body length and protein concentration were uncorrelated. In S. polymorpha, yield was most influenced by body length, but was also positively associated with relative forcipule length and relative body mass. In the second study, I investigated venom volume and total protein regeneration during the 14-day period subsequent to venom extraction in S. polymorpha. I further tested the hypothesis that venom protein components, separated by RP-FPLC, undergo asynchronous synthesis. During the first 48 hours, volume and protein mass increased linearly. However, protein regeneration lagged behind volume regeneration, with only 65–86% of venom volume and 29–47% of protein mass regenerated during the first 2 days. No significant additional regeneration occurred over the subsequent 12 days. Analysis of chromatograms of individual venom samples revealed that five of 10 chromatographic regions and 12 of 28 peaks demonstrated changes in percent of total peak area among milking intervals, indicating that venom proteins are regenerated asynchronously. In the third study, I characterized the venom composition of S. polymorpha using proteomic methods. I demonstrated that the venom of S. polymorpha is complex, generating 23 bands by SDS-PAGE and 56 peaks by RP-FPLC. MALDI TOF MS revealed hundreds of components with masses ranging from 1014.5 to 82863.9 Da. The distribution of molecular masses was skewed toward smaller peptides and proteins, with 72% of components found below 12 kDa. BLASTp sequence similarity searching of MS/MSderived amino acid sequences demonstrated 20 different sequences with similarity to known venom components, including serine proteases, ion-channel activators/inhibitors, and neurotoxins. In Appendix A, I reviewed how animals strategically deploy various emissions, including venom, highlighting how the metabolic and ecological value of these emissions leads to their judicious use

    Understanding key parameters affecting needle-free skin penetration by a parenteral drug delivery system

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    This thesis seeks to resolve difficulties in the development of a parenteral needle-free drug delivery system. Analysis of the penetration performance of Glide Pharma’s Solid Dose Injector in two clinical trials on man has shown that skin, and likely its inherent variation, was the cause of incomplete deliveries. As indicated by the literature and issues with previous needle-free technologies, a more complete understanding of skin penetration is required before such systems are capable of ensuring delivery across a patient population. Exploratory skin experiments led to the justification, design and build of a novel skin penetration test rig capable of simulating the delivery of a solid dose implant. This test rig, the Penetrometer, required significant software development to both stabilise and validate its performance before use on the in vivo porcine model, an established non-clinical model for drug delivery through human skin. Two non-clinical studies have been performed using the Penetrometer to capture force displacement profiles, using a metal probe equivalent to an implant, for penetration events on multiple test sites on multiple models. Significant levels of variation in key parameters were shown to be present intra- and inter-test site, as well as intra- and inter-model. It is likely that this variation, as detected in the porcine model, was the cause of problematic system performance during human clinical trials. Penetration experiments have also been performed to establish the validity of using in vitro skin or silicone rubber as an alternative test bed to in vivo models. The key parameters measured are the peak force during penetration, the displacement of the skin at penetration and the work required to penetrate the skin, with variations observed of the order of 30%, 100% and 140%, respectively. The results indicate how challenging it will be to reliably administer drugs using needle-free injection. This information should be used to better specify the device design and implant formulation to ensure delivery success. Prior to this thesis there was no quantitative data available, either published or within the collaborator, describing the magnitude and variation of the key parameters affecting needle-free skin penetration. This thesis has used the porcine model, further work must determine the parameters for the breadth of a human patient population

    Mental Disorders

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    This book brings together an international array of stars of the mental health professions to create a cutting edge volume that sheds light on many important and heretofore poorly understood issues in psychopathology. Mental Disorders-Theoretical and Empirical perspectives will be an important addition to the libraries of scholars and clinicians

    Persuasive by design: a model and toolkit for designing evidence-based interventions

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    Introduction: Ways of Machine Seeing

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    How do machines, and, in particular, computational technologies, change the way we see the world? This special issue brings together researchers from a wide range of disciplines to explore the entanglement of machines and their ways of seeing from new critical perspectives. This 'editorial' is for a special issue of AI & Society, which includes contributions from: María Jesús Schultz Abarca, Peter Bell, Tobias Blanke, Benjamin Bratton, Claudio Celis Bueno, Kate Crawford, Iain Emsley, Abelardo Gil-Fournier, Daniel Chávez Heras, Vladan Joler, Nicolas Malevé, Lev Manovich, Nicholas Mirzoeff, Perle Møhl, Bruno Moreschi, Fabian Offert, Trevor Paglan, Jussi Parikka, Luciana Parisi, Matteo Pasquinelli, Gabriel Pereira, Carloalberto Treccani, Rebecca Uliasz, and Manuel van der Veen

    Activation of the pro-resolving receptor Fpr2 attenuates inflammatory microglial activation

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    Poster number: P-T099 Theme: Neurodegenerative disorders & ageing Activation of the pro-resolving receptor Fpr2 reverses inflammatory microglial activation Authors: Edward S Wickstead - Life Science & Technology University of Westminster/Queen Mary University of London Inflammation is a major contributor to many neurodegenerative disease (Heneka et al. 2015). Microglia, as the resident immune cells of the brain and spinal cord, provide the first line of immunological defence, but can become deleterious when chronically activated, triggering extensive neuronal damage (Cunningham, 2013). Dampening or even reversing this activation may provide neuronal protection against chronic inflammatory damage. The aim of this study was to determine whether lipopolysaccharide (LPS)-induced inflammation could be abrogated through activation of the receptor Fpr2, known to play an important role in peripheral inflammatory resolution. Immortalised murine microglia (BV2 cell line) were stimulated with LPS (50ng/ml) for 1 hour prior to the treatment with one of two Fpr2 ligands, either Cpd43 or Quin-C1 (both 100nM), and production of nitric oxide (NO), tumour necrosis factor alpha (TNFα) and interleukin-10 (IL-10) were monitored after 24h and 48h. Treatment with either Fpr2 ligand significantly suppressed LPS-induced production of NO or TNFα after both 24h and 48h exposure, moreover Fpr2 ligand treatment significantly enhanced production of IL-10 48h post-LPS treatment. As we have previously shown Fpr2 to be coupled to a number of intracellular signaling pathways (Cooray et al. 2013), we investigated potential signaling responses. Western blot analysis revealed no activation of ERK1/2, but identified a rapid and potent activation of p38 MAP kinase in BV2 microglia following stimulation with Fpr2 ligands. Together, these data indicate the possibility of exploiting immunomodulatory strategies for the treatment of neurological diseases, and highlight in particular the important potential of resolution mechanisms as novel therapeutic targets in neuroinflammation. References Cooray SN et al. (2013). Proc Natl Acad Sci U S A 110: 18232-7. Cunningham C (2013). Glia 61: 71-90. Heneka MT et al. (2015). Lancet Neurol 14: 388-40

    Blunting Differential Attacks on PIN Processing APIs

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    We propose a countermeasure for a class of known attacks on the PIN processing API used in the ATM (cash machine) network. This API controls access to the tamper-resistant Hardware Security Modules where PIN encryption, decryption and verification takes place. The attacks are differential attacks, whereby an attacker gains information about the plaintext values of encrypted customer PINs by making changes to the non-confidential inputs to a command. Our proposed fix adds an integrity check to the parameters passed to the command. It is novel in that it involves very little change to the existing ATM network infrastructur

    CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

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    The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania

    Prediction of Robot Execution Failures Using Neural Networks

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    In recent years, the industrial robotic systems are designed with abilities to adapt and to learn in a structured or unstructured environment. They are able to predict and to react to the undesirable and uncontrollable disturbances which frequently interfere in mission accomplishment. In order to prevent system failure and/or unwanted robot behaviour, various techniques have been addressed. In this study, a novel approach based on the neural networks (NNs) is employed for prediction of robot execution failures. The training and testing dataset used in the experiment consists of forces and torques memorized immediately after the real robot failed in assignment execution. Two types of networks are utilized in order to find best prediction method - recurrent NNs and feedforward NNs. Moreover, we investigated 24 neural architectures implemented in Matlab software package. The experimental results confirm that this approach can be successfully applied to the failures prediction problem, and that the NNs outperform other artificial intelligence techniques in this domain. To further validate a novel method, real world experiments are conducted on a Khepera II mobile robot in an indoor structured environment. The obtained results for trajectory tracking problem proved usefulness and the applicability of the proposed solution
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