Methods for the chemical and sensorial evaluation of olive oil are frequently changed and tuned to oppose the increasingly sophisticated frauds. Although a plethora of promising alternatives has been developed, chromatographic techniques remain the more reliable yet, even at the expense of their related execution time and costs. In perspective of a continuous increment in the number of the analyses as a result of the global market, more rapid and effective methods to guarantee the safety of the olive oil trade are required. In this study, a novel artificial sensorial system, based on gas and liquid analysis, has been employed to deal with olive oil genuineness and authenticity issues. Despite these sensors having been widely used in the field of food science, the innovative electronic interface of the device is able to provide a higher reproducibility and sensitivity of the analysis. The multi-parametric platform demonstrated the capability to evaluate the organoleptic properties of extra-virgin olive oils as well as to highlight the presence of adulterants at blending concentrations usually not detectable through other methods.
The use of wearable sensors for health monitoring is rapidly growing. Over the past decade, wearable technology has gained much attention from the tech industry for commercial reasons and the interest of researchers and clinicians for reasons related to its potential benefit on patients’ health. Wearable devices use advanced and specialized sensors able to monitor not only activity parameters, such as heart rate or step count, but also physiological parameters, such as heart electrical activity or blood pressure. Electrocardiogram (ECG) monitoring is becoming one of the most attractive health-related features of modern smartwatches, and, because cardiovascular disease (CVD) is one of the leading causes of death globally, the use of a smartwatch to monitor patients could greatly impact the disease outcomes on health care systems. Commercial wearable devices are able to record just single-lead ECG using a couple of metallic contact dry electrodes. This kind of measurement can be used only for arrhythmia diagnosis. For the diagnosis of other cardiac disorders, additional ECG leads are required. In this study, we characterized an electronic interface to be used with multiple contactless capacitive electrodes in order to develop a wearable ECG device able to perform several lead measurements. We verified the ability of the electronic interface to amplify differential biopotentials and to reject common-mode signals produced by electromagnetic interference (EMI). We developed a portable device based on the studied electronic interface that represents a prototype system for further developments. We evaluated the performances of the developed device. The signal-to-noise ratio of the output signal is favorable, and all the features needed for a clinical evaluation (P waves, QRS complexes and T waves) are clearly readable.
BackgroundDipstick test is widely used to support the diagnosis of urinary tract infections (UTI). It is effective in ruling out UTI, but urine culture is needed for diagnosis confirmation. In this study we compared the accuracy of voltammetric analysis (VA) with that of DT to detect UTI (diagnosed using urine culture), and its usefulness as a second-stage test in people with positive DT.Methods142 patients were enrolled with no exclusion criteria. VA was performed using the BIONOTE device. Partial Least Square Discrimination Analysis was used to predict UTI based on VA data; diagnostic performance was evaluated using sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), positive and negative likelihood ratios (LR), accuracy, diagnostic odds ratio (DOR).ResultsMean age was 76.6 years (SD 12.6), 57% were male. VA had a better overall performance respect to DT in detecting UTI with accuracy 81.7% vs 75.9%, specificity 90.8% vs 82.5%, PPV 75% vs 61.4%, positive LR 6.68 vs 3.5, DOR 17.7 vs 7.47; sensibility, NPV and negative LR of the two tests were similar. VA had an accuracy of 82.4% in discriminating bacterial from fungal infections. When added as a second-stage test, VA identified 9 of the 17 false positive patients, with a net specificity of 91.7%, sensitivity 54%, PPV 75% and NPV 81%.ConclusionsVA is a quick and easy method that may be used as a second stage after DT to reduce the number of urine culture and of inappropriate antibiotic prescriptions.
E-noses provide potential non-invasive metabolic biomarkers for diagnosing and monitoring pulmonary diseases. The primary aim of the present study was to assess the within-day and between-day repeatability of a modern breath sampling system (Pneumopipe® plus an array of e-nose sensors) in asthmatic and healthy children. The secondary aim was to compare the repeatability of the breath sampling system, spirometry and exhaled nitric oxide (eNO). Fifteen children (age 6–11 years) with asthma and thirty healthy children matched by age and gender (1:2 allocation) were recruited; of them, three healthy children did not complete the study. All measurements were collected twice during the baseline visit, 30 min apart, and once during the final visit, after 7 d. Repeatability was assessed through the intra-cluster correlation coefficient (ICC), and a significance test was performed to detect an at least ‘fair’ repeatability (ICC > 0.2). In asthmatic children, the within-day (0–30 min) ICCs for e-nose sensors (8 sensors × 4 desorption temperatures) ranged from 0.24 to 0.84 (median 0.57, IQR 0.47-0.71), while the between-day (0–7 d) ICCs ranged from 0.25 to 0.83 (median 0.66, IQR 0.55-0.72). In healthy children, the within-day ICCs for e-nose sensors ranged from 0.29 to 0.85 (median 0.58, IQR 0.49-0.63), while the between-day ICCs ranged from 0.33 to 0.82 (median 0.55, IQR 0.49-0.63). In both groups, most of the within-day and between-day ICCs for e-nose sensors were statistically significant. Moreover, the within-day and between-day ICCs for all spirometry parameters and eNO were significant and similar to those of the most reliable sensors. The modern breath sampling system showed more than acceptable within-day and between-day repeatability, in both asthmatic and healthy children. The present study was registered on the central registration system ClinicalTrials.gov (ID: NCT03025061).
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