770 research outputs found

    Multi-wavelength SPAD photoplethysmography for cardio-respiratory monitoring

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    There is a growing interest in photoplethysmography (PPG) for the continuous monitoring of cardio-respiratory signals by portable instrumentation aimed at the early diagnosis of cardiovascular diseases. In this context, it is conceivable that PPG sensors working at different wavelengths simultaneously can optimize the identification of apneas and the quantification of the associated heart-rate changes or other parameters that depend on the PPG shape (e.g., systematic vascular resistance and pressure), when evaluating the severity of breathing disorders during sleep and in general for health monitoring. Therefore, the objective of this work is to present a novel pulse oximeter that provides synchronous data logging related to three light wavelengths (green, red, and infrared) in transmission mode to optimize both heart rate measurements and a reliable and continuous assessment of oxygen saturation. The transmission mode is considered more robust over motion artifacts than reflection mode, but current pulse oximeters cannot employ green light in transmission mode due to the high absorbance of body tissues at this wavelength. For this reason, our device is based on a Single-Photon Avalanche Diode (SPAD) with very short deadtime (less than 1 ns) to have, at the same time, the single photon sensitivity and high-count rate that allows acquiring all the wavelengths of interest on the same site and in transmission mode. Previous studies have shown that SPAD cameras can be used for measuring the heart rate through remote PPG, but oxygen saturation and heart-rate measures through contact SPAD-based PPG sensors have never been addressed so far. The results of the preliminary validation on six healthy volunteers reflect the expected physiological phenomena, providing rms errors in the Inter Beat Interval estimation smaller than 70 ms (with green light) and a maximum error in the oxygen saturation smaller than 1% during the apneas. Our prototype demonstrates the reliability of SPAD-based devices for continuous long-term monitoring of cardio-respiratory variables as an alternative to photodiodes especially when minimal area and optical power are required

    In silico approach for the definition of radiomirnomic signatures for breast cancer differential diagnosis

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    Personalized medicine relies on the integration and consideration of specific characteristics of the patient, such as tumor phenotypic and genotypic profiling. BACKGROUND: Radiogenomics aim to integrate phenotypes from tumor imaging data with genomic data to discover genetic mechanisms underlying tumor development and phenotype. METHODS: We describe a computational approach that correlates phenotype from magnetic resonance imaging (MRI) of breast cancer (BC) lesions with microRNAs (miRNAs), mRNAs, and regulatory networks, developing a radiomiRNomic map. We validated our approach to the relationships between MRI and miRNA expression data derived from BC patients. We obtained 16 radiomic features quantifying the tumor phenotype. We integrated the features with miRNAs regulating a network of pathways specific for a distinct BC subtype. RESULTS: We found six miRNAs correlated with imaging features in Luminal A (miR-1537, -205, -335, -337, -452, and -99a), seven miRNAs (miR-142, -155, -190, -190b, -1910, -3617, and -429) in HER2+, and two miRNAs (miR-135b and -365-2) in Basal subtype. We demonstrate that the combination of correlated miRNAs and imaging features have better classification power of Luminal A versus the different BC subtypes than using miRNAs or imaging alone. CONCLUSION: Our computational approach could be used to identify new radiomiRNomic profiles of multi-omics biomarkers for BC differential diagnosis and prognosis

    Monitoring a large number of pesticides and transformation products in water samples from Spain and Italy

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    Assessing the presence of pesticides in environmental waters is particularly challenging because of the huge number of substances used which may end up in the environment. Furthermore, the occurrence of pesticide transformation products (TPs) and/or metabolites makes this task even harder. Most studies dealing with the determination of pesticides in water include only a small number of analytes and in many cases no TPs. The present study applied a screening method for the determination of a large number of pesticides and TPs in wastewater (WW) and surface water (SW) from Spain and Italy. Liquid chromatography coupled to high-resolution mass spectrometry (HRMS) was used to screen a database of 450 pesticides and TPs. Detection and identification were based on specific criteria, i.e. mass accuracy, fragmentation, and comparison of retention times when reference standards were available, or a retention time prediction model when standards were not available. Seventeen pesticides and TPs from different classes (fungicides, herbicides and insecticides) were found in WW in Italy and Spain, and twelve in SW. Generally, in both countries more compounds were detected in effluent WW than in influent WW, and in SW than WW. This might be due to the analytical sensitivity in the different matrices, but also to the presence of multiple sources of pollution. HRMS proved a good screening tool to determine a large number of substances in water and identify some priority compounds for further quantitative analysis.N. I. Rousis and R. Bade acknowledge the European Union’s International Training Network SEWPROF (Marie Curie-FP7-PEOPLE Grant no. 317205) for their Early Stage Researcher contracts. The authors of University Jaume I acknowledge the financial support of Generalitat Valenciana (Prometeo II 2014/023) and of the Spanish Ministry of Economy and Competitiveness (Project ref. CTQ2015-65603). The authors are grateful to J. D. Baggott for English editing
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