Quercetin (QU), a hyperthermic sensitizer, when combined with cisplatin (CP) affects tumor growth. To determine the effects of QU and CP and their interactions, multimodal treatment in vitro and in vivo models under physiological and hyperthermic conditions was performed. In vitro, different sensitivity of T24 and UMUC human bladder cancer cells was observed after short-term exposure to QU (2 h) and CP (1 h). Effects of both compounds were investigated at low and high micromolar concentrations (1 and 50 µM, respectively) under both thermal conditions. QU acted in additive or synergistic manner in combination with CP between physiological condition and hyperthermia. As determined by 3-(4,5-dimethylthiazol2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, short-term application of QU and CP reduced cell viability. Clonal assay also indicated that combined treatment with QU and CP is lethal to bladder cancer cells in both conditions. In vivo, CP (5 or 10 mg kg−1) and QU (50 mg kg−1) acted synergistically with hyperthermia (43 °C) and inhibited tumor growth, activated immune effectors and increased mice survival. Our results demonstrate that combined treatment with CP and QU may increase death of tumor cells in physiological and hyperthermic conditions which could be clinically relevant in locoregional chemotherapy.

We propose a framework for designing observers possessing global convergence properties and desired asymptotic behaviors for the state estimation of nonlinear systems. The proposed scheme consists in combining two given continuous-time observers: One, denoted as global, ensures (approximate) convergence of the estimation error for any initial condition ranging in some prescribed set, while the other, denoted as local, guarantees a desired local behavior. We make assumptions on the properties of these two observers, and not on their structures, and then explain how to unite them as a single scheme using hybrid techniques. Two case studies are provided to demonstrate the applicability of the framework. Finally, a numerical example is presented.

We study the design of state observers for nonlinear networked control systems (NCSs) affected by disturbances and measurement noise, via an emulation-like approach. That is, given an observer designed with a specific stability property in the absence of communication constraints, we implement it over a network, and we provide sufficient conditions on the latter to preserve the stability property of the observer. In particular, we provide a bound on the maximum allowable transmission interval (MATI) that guarantees an input-to-state stability (ISS) property for the corresponding estimation error system. The stability analysis is trajectory-based, utilizes small-gain arguments, and exploits a persistently exciting property of the scheduling protocols. This property is key in our analysis and allows us to obtain significantly larger MATI bounds in comparison to the ones found in the literature. Our results hold for a general class of NCSs; however, we show that these results are also applicable to NCSs implemented over a specific physical network called WirelessHART (WH). The latter is mainly characterized by its multihop structure, slotted communication cycles, and the possibility to simultaneously transmit over different frequencies. We show that our results can be further improved by taking into account the intrinsic structure of the WH–NCS model. That is, we explicitly exploit the model structure in our analysis to obtain an even tighter MATI bound that guarantees the same ISS property for the estimation error system. Finally, to illustrate our results, we present analysis and numerical simulations for a class of Lipschitz nonlinear systems and high-gain observers.

Hercegovački pršut as a traditional dry-cured smoked ham (prosciutto) produced by using an open fire that can be potentially contaminated with polycyclic aromatic hydrocarbons (PAHs) and can pose a health risk for consumers. The aim of this research was to identify the types and concentrations of 16 PAHs in 34 samples of traditionally smoked prosciutto. Out of 16 investigated PAHs, identified in the EPA (Environmental Protection Agency) list of priority pollutants, 14 compounds were detected. Average levels of cancerogenic benzo[a]pyrene (BaP) and PAH4 (benzo[a]anthracene (BaA), benzo[b]fluoranthene (BbF), chrysene (Chry), and benzo[a]pyrene (BaP)) ranged from <LOQ (level of quantification) to 5.08 μg/kg and 0.45 μg/kg to 22.67 μg/kg. Two analyzed samples exceeded currently prescribed values according to the Bosnia and Herzegovina legislation for BaP concentrations and one sample for PAH4 content. PAH16 concentrations were on average between 2.92 μg/kg and 87.6 μg/kg. The highest PAH concentrations were found in samples from the Herzegovina-Neretva canton. The results of the research highlight the importance of standardizing smoking procedures and manufacturing practice, in the production of Hercegovački pršut, in order to reduce the PAH content.

This document presents a new complete standalone system for a recognition of sleep apnea using signals from the pressure sensors placed under the mattress. The developed hardware part of the system is tuned to filter and to amplify the signal. Its software part performs more accurate signal filtering and identification of apnea events. The overall achieved accuracy of the recognition of apnea occurrence is 91%, with the average measured recognition delay of about 15 seconds, which confirms the suitability of the proposed method for future employment. The main aim of the presented approach is the support of the healthcare system with the cost-efficient tool for recognition of sleep apnea in the home environment.

The ballistocardiography is a technique that measures the heart rate from the mechanical vibrations of the body due to the heart movement. In this work a novel noninvasive device placed under the mattress of a bed estimates the heart rate using the ballistocardiography. Different algorithms for heart rate estimation have been developed.

Methods based exclusively on heart rate hardly allow to differentiate between physical activity, stress, relaxation, and rest, that is why an additional sensor like activity/movement sensor added for detection and classification. The response of the heart to physical activity, stress, relaxation, and no activity can be very similar. In this study, we can observe the influence of induced stress and analyze which metrics could be considered for its detection. The changes in the Root Mean Square of the Successive Differences provide us with information about physiological changes. A set of measurements collecting the RR intervals was taken. The intervals are used as a parameter to distinguish four different stages. Parameters like skin conductivity or skin temperature were not used because the main aim is to maintain a minimum number of sensors and devices and thereby to increase the wearability in the future.

Abstract In this article, we describe the Cayley graphs of pseudo-unitary homogeneous semigroups with zero 0, which are 0-disjoint unions of their subsets indexed by a groupoid.

Lung sound (LS) signals are often contaminated by impulsive artifacts that complicate the estimation of lung sound intensity (LSI) using conventional amplitude estimators. Fixed sample entropy (fSampEn) has proven to be robust to cardiac artifacts in myographic respiratory signals. Similarly, fSampEn is expected to be robust to artifacts in LS signals, thus providing accurate LSI estimates. However, the choice of fSampEn parameters depends on the application and fSampEn has not previously been applied to LS signals. This study aimed to perform an evaluation of the performance of the most relevant fSampEn parameters on LS signals, and to propose optimal fSampEn parameters for LSI estimation. Different combinations of fSampEn parameters were analyzed in LS signals recorded in a heterogeneous population of healthy subjects and chronic obstructive pulmonary disease patients during loaded breathing. The performance of fSampEn was assessed by means of its cross-covariance with flow signals, and optimal fSampEn parameters for LSI estimation were proposed.

A new method substantially improves the accuracy of mapped brain networks using anatomy and microstructure informed tractography. Diffusion magnetic resonance imaging is a noninvasive imaging modality that has been extensively used in the literature to study the neuronal architecture of the brain in a wide range of neurological conditions using tractography. However, recent studies highlighted that the anatomical accuracy of the reconstructions is inherently limited and challenged its appropriateness. Several solutions have been proposed to tackle this issue, but none of them proved effective to overcome this fundamental limitation. In this work, we present a novel processing framework to inject into the reconstruction problem basic prior knowledge about brain anatomy and its organization and evaluate its effectiveness using both simulated and real human brain data. Our results indicate that our proposed method dramatically increases the accuracy of the estimated brain networks and, thus, represents a major step forward for the study of connectivity.

Diffusion magnetic resonance imaging is a noninvasive imaging modality that has been extensively used in the literature to study the neuronal architecture of the brain in a wide range of neurological conditions using tractography. However, recent studies highlighted that the anatomical accuracy of the reconstructions is inherently limited and challenged its appropriateness. Several solutions have been proposed to tackle this issue, but none of them proved effective to overcome this fundamental limitation. In this work, we present a novel processing framework to inject into the reconstruction problem basic prior knowledge about brain anatomy and its organization and evaluate its effectiveness using both simulated and real human brain data. Our results indicate that our proposed method dramatically increases the accuracy of the estimated brain networks and, thus, represents a major step forward for the study of connectivity.