905 resultados para Remote diagnostics.


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Recent advances in nanotechnology have led to the application of nanoparticles in a wide variety of fields. In the field of nanomedicine, there is great emphasis on combining diagnostic and therapeutic modalities into a single nanoparticle construct (theranostics). In particular, anisotropic nanoparticles have shown great potential for surface-enhanced Raman scattering (SERS) detection due to their unique optical properties. Gold nanostars are a type of anisotropic nanoparticle with one of the highest SERS enhancement factors in a non-aggregated state. By utilizing the distinct characteristics of gold nanostars, new plasmonic materials for diagnostics, therapy, and sensing can be synthesized. The work described herein is divided into two main themes. The first half presents a novel, theranostic nanoplatform that can be used for both SERS detection and photodynamic therapy (PDT). The second half involves the rational design of silver-coated gold nanostars for increasing SERS signal intensity and improving reproducibility and quantification in SERS measurements.

The theranostic nanoplatforms consist of Raman-labeled gold nanostars coated with a silica shell. Photosensitizer molecules for PDT can be loaded into the silica matrix, while retaining the SERS signal of the gold nanostar core. SERS detection and PDT are performed at different wavelengths, so there is no interference between the diagnostic and therapeutic modalities. Singlet oxygen generation (a measure of PDT effectiveness) was demonstrated from the drug-loaded nanocomposites. In vitro testing with breast cancer cells showed that the nanoplatform could be successfully used for PDT. When further conjugating the nanoplatform with a cell-penetrating peptide (CPP), efficacy of both SERS detection and PDT is enhanced.

The rational design of plasmonic nanoparticles for SERS sensing involved the synthesis of silver-coated gold nanostars. Investigation of the silver coating process revealed that preservation of the gold nanostar tips was necessary to achieve the increased SERS intensity. At the optimal amount of silver coating, the SERS intensity is increased by over an order of magnitude. It was determined that a majority of the increased SERS signal can be attributed to reducing the inner filter effect, as the silver coating process moves the extinction of the particles far away from the laser excitation line. To improve reproducibility and quantitative SERS detection, an internal standard was incorporated into the particles. By embedding a small-molecule dye between the gold and silver surfaces, SERS signal was obtained both from the internal dye and external analyte on the particle surface. By normalizing the external analyte signal to the internal reference signal, reproducibility and quantitative analysis are improved in a variety of experimental conditions.

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Many studies have shown the considerable potential for the application of remote-sensing-based methods for deriving estimates of lake water quality. However, the reliable application of these methods across time and space is complicated by the diversity of lake types, sensor configuration, and the multitude of different algorithms proposed. This study tested one operational and 46 empirical algorithms sourced from the peer-reviewed literature that have individually shown potential for estimating lake water quality properties in the form of chlorophyll-a (algal biomass) and Secchi disc depth (SDD) (water transparency) in independent studies. Nearly half (19) of the algorithms were unsuitable for use with the remote-sensing data available for this study. The remaining 28 were assessed using the Terra/Aqua satellite archive to identify the best performing algorithms in terms of accuracy and transferability within the period 2001–2004 in four test lakes, namely Vänern, Vättern, Geneva, and Balaton. These lakes represent the broad continuum of large European lake types, varying in terms of eco-region (latitude/longitude and altitude), morphology, mixing regime, and trophic status. All algorithms were tested for each lake separately and combined to assess the degree of their applicability in ecologically different sites. None of the algorithms assessed in this study exhibited promise when all four lakes were combined into a single data set and most algorithms performed poorly even for specific lake types. A chlorophyll-a retrieval algorithm originally developed for eutrophic lakes showed the most promising results (R2 = 0.59) in oligotrophic lakes. Two SDD retrieval algorithms, one originally developed for turbid lakes and the other for lakes with various characteristics, exhibited promising results in relatively less turbid lakes (R2 = 0.62 and 0.76, respectively). The results presented here highlight the complexity associated with remotely sensed lake water quality estimates and the high degree of uncertainty due to various limitations, including the lake water optical properties and the choice of methods.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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To explore the feasibility of processing Compact Muon Solenoid (CMS) analysis jobs across the wide area network, the FIU CMS Tier-3 center and the Florida CMS Tier-2 center designed a remote data access strategy. A Kerberized Lustre test bed was installed at the Tier-2 with the design to provide storage resources to private-facing worker nodes at the Tier-3. However, the Kerberos security layer is not capable of authenticating resources behind a private network. As a remedy, an xrootd server on a public-facing node at the Tier-3 was installed to export the file system to the private-facing worker nodes. We report the performance of CMS analysis jobs processed by the Tier-3 worker nodes accessing data from a Kerberized Lustre file. The processing performance of this configuration is benchmarked against a direct connection to the Lustre file system, and separately, where the xrootd server is near the Lustre file system.

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Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.

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Cigar Lake is a high-grade uranium deposit, located in northern Saskatchewan, Canada. In order to extract the uranium ore remotely, thus ensuring minimal radiation dose to workers and also to access the ore from stable ground, the Jet Boring System (JBS) was developed by Cameco Corporation. This system uses a high-powered water jet to remotely excavate cavities. Survey data is required to determine the final shape, volume, and location of the cavity for mine planning purposes and construction. This paper provides an overview of the challenges involved in remotely surveying a JBS-mined cavity and studies the potential use of a time-of-flight (ToF) camera for remote cavity surveying. It reports on data collected and analyzed from inside an experimental environment as well as on real data acquired on site from the Cigar Lake and Rabbit Lake mines.

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The section of CN railway between Vancouver and Kamloops runs along the base of many hazardous slopes, including the White Canyon, which is located just outside the town of Lytton, BC. The slope has a history of frequent rockfall activity, which presents a hazard to the railway below. Rockfall inventories can be used to understand the frequency-magnitude relationship of events on hazardous slopes, however it can be difficult to consistently and accurately identify rockfall source zones and volumes on large slopes with frequent activity, leaving many inventories incomplete. We have studied this slope as a part of the Canadian Railway Ground Hazard Research Program and have collected remote sensing data, including terrestrial laser scanning (TLS), photographs, and photogrammetry data since 2012, and used change detection to identify rockfalls on the slope. The objective of this thesis is to use a subset of this data to understand how rockfalls identified from TLS data could be used to understand the frequency-magnitude relationship of rockfalls on the slope. This includes incorporating both new and existing methods to develop a semi-automated workflow to extract rockfall events from the TLS data. We show that these methods can be used to identify events as small as 0.01 m3 and that the duration between scans can have an effect on the frequency-magnitude relationship of the rockfalls. We also show that by incorporating photogrammetry data into our analysis, we can create a 3D geological model of the slope and use this to classify rockfalls by lithology, to further understand the rockfall failure patterns. When relating the rockfall activity to triggering factors, we found that the amount of precipitation occurring over the winter has an effect on the overall rockfall frequency for the remainder of the year. These results can provide the railways with a more complete inventory of events compared to records created through track inspection, or rockfall monitoring systems that are installed on the slope. In addition, we can use the database to understand the spatial and temporal distribution of events. The results can also be used as an input to rockfall modelling programs.

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Within Africa, the burden of heart failure is significant. This arises from the increase in cardiovascular disease and associated risk factors such as hypertension and diabetes, as well as causes of heart failure which are particular to sub-Saharan Africa, such as endomyocardial fibrosis. The lack of access to echocardiography and other imaging modalities, from a cost and technical perspective, combined with the predominantly rural nature of many countries with poor transport links, means that the vast majority of people never obtain an appropriate diagnosis. Similarly, research has been limited on the causes and treatment of heart failure in Africa and in particular endemic causes such as EMF and rheumatic heart disease. This review outlines the burden of heart failure in Africa and highlights the opportunity to expand diagnosis through the use of biomarkers, in particular natriuretic peptides. This builds on the success of point-of-care testing in human immunodeficiency virus and tuberculosis which have been extensively deployed in community settings in Africa.

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Research in biosensing approaches as alternative techniques for food diagnostics for the detection of chemical contaminants and foodborne pathogens has increased over the last twenty years. The key component of such tests is the biorecognition element whereby polyclonal or monoclonal antibodies still dominate the market. Traditionally the screening of sera or cell culture media for the selection of polyclonal or monoclonal candidate antibodies respectively has been performed by enzyme immunoassays. For niche toxin compounds, enzyme immunoassays can be expensive and/or prohibitive methodologies for antibody production due to limitations in toxin supply for conjugate production. Automated, self-regenerating, chip-based biosensors proven in food diagnostics may be utilised as rapid screening tools for antibody candidate selection. This work describes the use of both single channel and multi-channel surface plasmon resonance (SPR) biosensors for the selection and characterisation of antibodies, and their evaluation in shellfish tissue as standard techniques for the detection of domoic acid, as a model toxin compound. The key advantages in the use of these biosensor techniques for screening hybridomas in monoclonal antibody production were the real time observation of molecular interaction and rapid turnaround time in analysis compared to enzyme immunoassays. The multichannel prototype instrument was superior with 96 analyses completed in 2h compared to 12h for the single channel and over 24h for the ELISA immunoassay. Antibodies of high sensitivity, IC50's ranging from 4.8 to 6.9ng/mL for monoclonal and 2.3-6.0ng/mL for polyclonal, for the detection of domoic acid in a 1min analysis time were selected. Although there is a progression for biosensor technology towards low cost, multiplexed portable diagnostics for the food industry, there remains a place for laboratory-based SPR instrumentation for antibody development for food diagnostics as shown herein.

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The cobas® (Roche) portfolio of companion diagnostics in oncology currently has three assays CE-marked for in vitro diagnostics. Two of these (EGFR and BRAF) are also US FDA-approved. These assays detect clinically relevant mutations that are correlated with response (BRAF, EGFR) or lack of response (KRAS) to targeted therapies such as selective mutant BRAF inhibitors in malignant melanoma, tyrosine kinases inhibitor in non-small cell lung cancer and anti-EGFR monoclonal antibodies in colorectal cancer, respectively. All these assays are run on a single platform using DNA extracted from a single 5 µm section of a formalin-fixed paraffin-embedded tissue block. The assays provide an ‘end-to-end’ solution from extraction of DNA to automated analysis and report on the cobas z 480. The cobas tests have shown robust and reproducible performance, with high sensitivity and specificity and low limit of detection, making them suitable as companion diagnostics for clinical use.

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The progressive elucidation of the molecular pathogenesis of cancer has fueled the rational development of targeted drugs for patient populations stratified by genetic characteristics. Here we discuss general challenges relating to molecular diagnostics and describe predictive biomarkers for personalized cancer medicine. We also highlight resistance mechanisms for epidermal growth factor receptor (EGFR) kinase inhibitors in lung cancer. We envisage a future requiring the use of longitudinal genome sequencing and other omics technologies alongside combinatorial treatment to overcome cellular and molecular heterogeneity and prevent resistance caused by clonal evolution.

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AIMS: Device-based remote monitoring (RM) has been linked to improved clinical outcomes at short to medium-term follow-up. Whether this benefit extends to long-term follow-up is unknown. We sought to assess the effect of device-based RM on long-term clinical outcomes in recipients of implantable cardioverter-defibrillators (ICD). METHODS: We performed a retrospective cohort study of consecutive patients who underwent ICD implantation for primary prevention. RM was initiated with patient consent according to availability of RM hardware at implantation. Patients with concomitant cardiac resynchronization therapy were excluded. Data on hospitalizations, mortality and cause of death were systematically assessed using a nationwide healthcare platform. A Cox proportional hazards model was employed to estimate the effect of RM on mortality and a composite endpoint of cardiovascular mortality and hospital admission due to heart failure (HF). RESULTS: 312 patients were included with a median follow-up of 37.7months (range 1 to 146). 121 patients (38.2%) were under RM since the first outpatient visit post-ICD and 191 were in conventional follow-up. No differences were found regarding age, left ventricular ejection fraction, heart failure etiology or NYHA class at implantation. Patients under RM had higher long-term survival (hazard ratio [HR] 0.50, CI 0.27-0.93, p=0.029) and lower incidence of the composite outcome (HR 0.47, CI 0.27-0.82, p=0.008). After multivariate survival analysis, overall survival was independently associated with younger age, higher LVEF, NYHA class lower than 3 and RM. CONCLUSION: RM was independently associated with increased long-term survival and a lower incidence of a composite endpoint of hospitalization for HF or cardiovascular mortality.