12 resultados para Innovative monitoring techniques

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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The history of cerebral aneurysm surgery owes a great tribute to the tenacity of pioneering neurosurgeons who designed and developed the clips used to close the aneurysms neck. However, until the beginning of the past century, surgery of complex and challenging aneurysms was impossible due to the lack of surgical microscope and commercially available sophisticated clips. The modern era of the spring clips began in the second half of last century. Until then, only malleable metal clips and other non-metallic materials were available for intracranial aneurysms. Indeed, the earliest clips were hazardous and difficult to handle. Several neurosurgeons put their effort in developing new clip models, based on their personal experience in the treatment of cerebral aneurysms. Finally, the introduction of the surgical microscope, together with the availability of more sophisticated clips, has allowed the treatment of complex and challenging aneurysms. However, today none of the new instruments or tools for surgical therapy of aneurysms could be used safely and effectively without keeping in mind the lessons on innovative surgical techniques provided by great neurovascular surgeons. Thanks to their legacy, we can now treat many types of aneurysms that had always been considered inoperable. In this article, we review the basic principles of surgical clipping and illustrate some more advanced techniques to be used for complex aneurysms.

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Large numbers and functionally competent T cells are required to protect from diseases for which antibody-based vaccines have consistently failed (1), which is the case for many chronic viral infections and solid tumors. Therefore, therapeutic vaccines aim at the induction of strong antigen-specific T-cell responses. Novel adjuvants have considerably improved the capacity of synthetic vaccines to activate T cells, but more research is necessary to identify optimal compositions of potent vaccine formulations. Consequently, there is a great need to develop accurate methods for the efficient identification of antigen-specific T cells and the assessment of their functional characteristics directly ex vivo. In this regard, hundreds of clinical vaccination trials have been implemented during the last 15 years, and monitoring techniques become more and more standardized.

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In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.

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We propose a novel methodology to generate realistic network flow traces to enable systematic evaluation of network monitoring systems in various traffic conditions. Our technique uses a graph-based approach to model the communication structure observed in real-world traces and to extract traffic templates. By combining extracted and user-defined traffic templates, realistic network flow traces that comprise normal traffic and customized conditions are generated in a scalable manner. A proof-of-concept implementation demonstrates the utility and simplicity of our method to produce a variety of evaluation scenarios. We show that the extraction of templates from real-world traffic leads to a manageable number of templates that still enable accurate re-creation of the original communication properties on the network flow level.

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The design of a high-density neural recording system targeting epilepsy monitoring is presented. Circuit challenges and techniques are discussed to optimize the amplifier topology and the included OTA. A new platform supporting active recording devices targeting wireless and high-resolution focus localization in epilepsy diagnosis is also proposed. The post-layout simulation results of an amplifier dedicated to this application are presented. The amplifier is designed in a UMC 0.18µm CMOS technology, has an NEF of 2.19 and occupies a silicon area of 0.038 mm(2), while consuming 5.8 µW from a 1.8-V supply.

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Various treatment options for deep cartilage defects are presently available. The efficacy of bone marrow stimulation with microfracture, of mosaicplasty and of various autologous chondrocyte implantation (ACI) techniques has been subject to numerous studies recently. Magnetic resonance imaging (MRI) has gained a major role in the assessment of cartilage repair. The introduction of high-field MRI to clinical routine makes high resolution and three-dimensional imaging readily available. New quantitative MRI techniques that directly visualize the molecular structure of cartilage may further advance our understanding of cartilage repair. The clinical evaluation of cartilage repair tissue is a complex issue, and MR imaging will become increasingly important both in research and in clinical routine. This article reviews the clinical aspects of microfracture, mosaicplasty, and ACI and reports the recent technical advances that have improved MRI of cartilage. Morphological evaluation methods are recommended for each of the respective techniques. Finally, an overview of T2 mapping and delayed gadolinium-enhanced MR imaging of cartilage in cartilage repair is provided.

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Cell death is essential for a plethora of physiological processes, and its deregulation characterizes numerous human diseases. Thus, the in-depth investigation of cell death and its mechanisms constitutes a formidable challenge for fundamental and applied biomedical research, and has tremendous implications for the development of novel therapeutic strategies. It is, therefore, of utmost importance to standardize the experimental procedures that identify dying and dead cells in cell cultures and/or in tissues, from model organisms and/or humans, in healthy and/or pathological scenarios. Thus far, dozens of methods have been proposed to quantify cell death-related parameters. However, no guidelines exist regarding their use and interpretation, and nobody has thoroughly annotated the experimental settings for which each of these techniques is most appropriate. Here, we provide a nonexhaustive comparison of methods to detect cell death with apoptotic or nonapoptotic morphologies, their advantages and pitfalls. These guidelines are intended for investigators who study cell death, as well as for reviewers who need to constructively critique scientific reports that deal with cellular demise. Given the difficulties in determining the exact number of cells that have passed the point-of-no-return of the signaling cascades leading to cell death, we emphasize the importance of performing multiple, methodologically unrelated assays to quantify dying and dead cells.

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Type 1 diabetes mellitus is a chronic disease characterized by blood glucose levels out of normal range due to inability of insulin production. This dysfunction leads to many short- and long-term complications. In this paper, a system for tele-monitoring and tele-management of Type 1 diabetes patients is proposed, aiming at reducing the risk of diabetes complications and improving quality of life. The system integrates Wireless Personal Area Networks (WPAN), mobile infrastructure, and Internet technology along with commercially available and novel glucose measurement devices, advanced modeling techniques, and tools for the intelligent processing of the available diabetes patients information. The integration of the above technologies enables intensive monitoring of blood glucose levels, treatment optimisation, continuous medical care, and improvement of quality of life for Type 1 diabetes patients, without restrictions in everyday life activities.

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INTRODUCTION Anatomic imaging alone is often inadequate for tuning systemic treatment for individual tumor response. Optically based techniques could potentially contribute to fast and objective response monitoring in personalized cancer therapy. In the present study, we evaluated the feasibility of dual-modality diffuse reflectance spectroscopy-autofluorescence spectroscopy (DRS-AFS) to monitor the effects of systemic treatment in a mouse model for hereditary breast cancer. METHODS Brca1(-/-); p53(-/-) mammary tumors were grown in 36 mice, half of which were treated with a single dose of cisplatin. Changes in the tumor physiology and morphology were measured for a period of 1 week using dual-modality DRS-AFS. Liver and muscle tissues were also measured to distinguish tumor-specific alterations from systemic changes. Model-based analyses were used to derive different optical parameters like the scattering and absorption coefficients, as well as sources of intrinsic fluorescence. Histopathologic analysis was performed for cross-validation with trends in optically based parameters. RESULTS Treated tumors showed a significant decrease in Mie-scattering slope and Mie-to-total scattering fraction and an increase in both fat volume fraction and tissue oxygenation after 2 days of follow-up. Additionally, significant tumor-specific changes in the fluorescence spectra were seen. These longitudinal trends were consistent with changes observed in the histopathologic analysis, such as vital tumor content and formation of fibrosis. CONCLUSIONS This study demonstrates that dual-modality DRS-AFS provides quantitative functional information that corresponds well with the degree of pathologic response. DRS-AFS, in conjunction with other imaging modalities, could be used to optimize systemic cancer treatment on the basis of early individual tumor response.

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Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects of anthropogenic chemical contamination from diffuse and point sources. While current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals can be detected simultaneously in our aquatic resources. However, exposure to chemical mixtures does not necessarily translate into adverse biological effects nor clearly shows whether mitigation measures are needed. Thus, the question which mixtures are present and which have associated combined effects becomes central for defining adequate monitoring and assessment strategies. Here we describe the vision of the international, EU-funded project SOLUTIONS, where three routes are explored to link the occurrence of chemical mixtures at specific sites to the assessment of adverse biological combination effects. First of all, multi-residue target and non-target screening techniques covering a broader range of anticipated chemicals co-occurring in the environment are being developed. By improving sensitivity and detection limits for known bioactive compounds of concern, new analytical chemistry data for multiple components can be obtained and used to characterise priority mixtures. This information on chemical occurrence will be used to predict mixture toxicity and to derive combined effect estimates suitable for advancing environmental quality standards. Secondly, bioanalytical tools will be explored to provide aggregate bioactivity measures integrating all components that produce common (adverse) outcomes even for mixtures of varying compositions. The ambition is to provide comprehensive arrays of effect-based tools and trait-based field observations that link multiple chemical exposures to various environmental protection goals more directly and to provide improved in situ observations for impact assessment of mixtures. Thirdly, effect-directed analysis (EDA) will be applied to identify major drivers of mixture toxicity. Refinements of EDA include the use of statistical approaches with monitoring information for guidance of experimental EDA studies. These three approaches will be explored using case studies at the Danube and Rhine river basins as well as rivers of the Iberian Peninsula. The synthesis of findings will be organised to provide guidance for future solution-oriented environmental monitoring and explore more systematic ways to assess mixture exposures and combination effects in future water quality monitoring.