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This is the first investigation to perform an unsupervised cluster analysis of activities performed by individuals with lower limb amputation (ILLAs) and individuals without gait impairment, in free-living conditions. Eight individuals with no gait impairments and four ILLAs wore a thigh-based accelerometer and walked on an improvised route across a variety of terrains in the vicinity of their homes. Their physical activity data were clustered to extract 'unique' groupings in a low-dimension feature space in an unsupervised learning approach, and an algorithm was created to automatically distinguish such activities. After testing three dimensionality reduction methods-namely, principal component analysis (PCA), t-distributed stochastic neighbor embedding (tSNE), and uniform manifold approximation and projection (UMAP)-we selected tSNE due to its performance and stable outputs. Cluster formation of activities via DBSCAN only occurred after the data were reduced to two dimensions via tSNE and contained only samples for a single individual. Additionally, through analysis of the t-SNE plots, appreciable clusters in walking-based activities were only apparent with ground walking and stair ambulation. Through a combination of density-based clustering and analysis of cluster distance and density, a novel algorithm inspired by the t-SNE plots, resulting in three proposed and validated hypotheses, was able to identify cluster formations that arose from ground walking and stair ambulation. Low dimensional clustering of activities has thus been found feasible when analyzing individual sets of data and can currently recognize stair and ground walking ambulation.

The continuous evolution of cancer biology has led to the discovery of mammaglobin, a potential novel biomarker for breast carcinoma. This review aims to unravel the enigmatic aspects of mammaglobin and elucidate its potential role in redefining the paradigm of breast carcinoma biomarkers. We will thoroughly examine its expression in tumoral and peritumoral tissues and its circulating levels in the blood, thereby providing insights into its possible function in cancer progression and metastasis. Furthermore, the potential application of mammaglobin as a non-invasive diagnostic tool and a target for personalized treatment strategies will be discussed. Given the increasing incidence of breast carcinoma worldwide, the exploration of novel biomarkers such as mammaglobin is crucial in advancing our diagnostic capabilities and treatment modalities, ultimately contributing to improved patient outcomes.

With the massive, worldwide, smart metering roll-out, both energy suppliers and users are starting to tap into the potential of higher resolution energy readings for accurate billing, improved demand response, improved tariffs better tuned to users and the grid, and empowering end-users to know how much their individual appliances contribute to their electricity bills via nonintrusive load monitoring (NILM). A number of NILM approaches, based on machine learning (ML), have been proposed over the years, focusing on improving the NILM model performance. However, the trustworthiness of the NILM model itself has hardly been addressed. It is important to explain the underlying model and its reasoning to understand why the model underperforms in order to satisfy user curiosity and to enable model improvement. This can be done by leveraging naturally interpretable or explainable models as well as explainability tools. This paper adopts a naturally interpretable decision tree (DT)-based approach for a NILM multiclass classifier. Furthermore, this paper leverages explainability tools to determine local and global feature importance, and design a methodology that informs feature selection for each appliance class, which can determine how well a trained model will predict an appliance on any unseen test data, minimising testing time on target datasets. We explain how one or more appliances can negatively impact classification of other appliances and predict appliance and model performance of the REFIT-data trained models on unseen data of the same house and on unseen houses on the UK-DALE dataset. Experimental results confirm that models trained with the explainability-informed local feature importance can improve toaster classification performance from 65% to 80%. Additionally, instead of one five-classifier approach incorporating all five appliances, a three-classifier approach comprising a kettle, microwave, and dishwasher and a two-classifier comprising a toaster and washing machine improves classification performance for the dishwasher from 72% to 94% and the washing machine from 56% to 80%.

Robotic manipulation challenges, such as grasping and object manipulation, have been tackled successfully with the help of deep reinforcement learning systems. We give an overview of the recent advances in deep reinforcement learning algorithms for robotic manipulation tasks in this review. We begin by outlining the fundamental ideas of reinforcement learning and the parts of a reinforcement learning system. The many deep reinforcement learning algorithms, such as value-based methods, policy-based methods, and actor-critic approaches, that have been suggested for robotic manipulation tasks are then covered. We also examine the numerous issues that have arisen when applying these algorithms to robotics tasks, as well as the various solutions that have been put forth to deal with these issues. Finally, we highlight several unsolved research issues and talk about possible future directions for the subject.

This study presents a new two compartmental model with, recently defined General fractional derivative. We review that concept of General fractional derivative and use the kernel function that generalizes the classical Caputo derivative in a mathematically consistent way. Next we use this model to study the release of antibiotic gentamicin in poly (vinyl alcohol)/gentamicin(PVA/Gent) hydrogel aimed for wound dressing in medical treatment of deep chronical wounds. The PVA/Gent hydrogel was prepared by physical cross linking of poly (vinyl alcohol) dispersion using freezing-thawing method, and then was swollen in gentamicin solution at 37 °C during 48 h. The concentration of released gentamicin was determined using a high-performance liquid chromatography coupled with mass spectrometer. The advantage of this model is the existence of new parameters in the definition of fractional derivative, as compared with classical fractional compartmental models. The model proposed here in the special case reduces to the classical (integer order) linear two compartmental model as well as classical fractional order two compartmental model since it has more parameters that are determined from the experimental results., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Slope instabilities caused by heavy rainfall, man-made activity or earthquakes can be characterised by seismic events. To minimise mortality and infrastructure damage, a good understanding of seismic signal properties characterising slope failures is therefore crucial to classify seismic events recorded from continuous recordings effectively. However, there are limited contributions towards understanding the importance of feature selection for the classification of seismic signals from continuous noisy recordings from multiple channels/sensors. This paper first proposes a novel multi-channel event-detection scheme based on Neyman-Pearson lemma and Multi-channel Coherency Migration (MCM) on the stacked signal across multi-channels. Furthermore, this paper adapts graph-based feature weight optimisation as feature selection, exploiting the signal's physical characteristics, to improve signal classification. Specifically, we alternatively optimise the feature weight and classification label with graph smoothness and semidefinite programming (SDP). Experimental results show that with expert interpretation, compared with the conventional short-time average/long-time average (STA/LTA) detection approach, our detection method identified 614 more seismic events in five days. Furthermore, feature selection, especially via graph-based feature weight optimisation, provides more focused feature sets with less than half of the original number of features, at the same time enhancing the classification performance; for example, with feature selection, the Graph Laplacian Regularisation classifier (GLR) raised the rockfall and slide quake sensitivities to 92% and 88% from 89% and 85%, respectively.

This paper proposes energy-efficient solutions for the smart light-emitting diode (LED) lighting system, which provides minimal energy consumption while simultaneously satisfying illuminance requirements of the users in a typical office space. In addition to artificial light from dimmable LED lamps, natural daylight coming from external sources, such as windows, is considered as a source of illumination in an indoor environment. In order to reduce total energy consumption, the smart LED system has the possibility to dim LED lamps, resulting in reduced LED output power. Additionally, various LED lamps' functionality, such as semi-angle of the half illuminance and LED tilting, are introduced as an additional parameter to be optimized to achieve greater energy saving of the designed system. In order to properly exploit external lighting, the idea to reduce overall daylight intensity at a users' location is realized by the option to dim the windows with a shading factor. Based on the users' requirements for a minimal and desired level of illumination, the proposed optimization problems can be solved by implementing different optimization algorithms. The obtained solutions are able to give instructions to a smart LED system to manage and control system parameters (LEDs dimming levels, semi-angles of the half illuminance, orientation of LEDs, the shading factor) in order to design total illumination, which ensures minimal energy consumption and users' satisfaction related to illuminance requirements.

Background and Objectives: Mounting evidence implicates oxidative damage in prostate carcinogenesis, contributing to modifications of macromolecules that drive cellular malignant transformation. Functional single-nucleotide polymorphisms (SNPs) of enzymes involved in redox homeostasis can disrupt pro-oxidant-antioxidant balance, leading to accumulation of reactive oxygen species and oxidative damage. We investigated the potential role of genetic polymorphisms of antioxidant enzymes glutathione peroxidase 1 ( GPX1 rs1050450) and superoxide dismutase 2 ( SOD2 rs4880) and regulatory antioxidant protein nuclear factor erythroid 2-related factor 2 ( Nrf2 rs6721961) in the susceptibility to prostate cancer development (PC) and prognosis. Materials and Methods: We conducted a case-control study consisting of 235 patients with PC and 240 controls. Gene polymorphisms were determined by quantitative polymerase chain reaction (qPCR) and polymerase chain reaction with confronting two-pair primers (PCR-CTTP) methods. Multiple risk models were composed to inspect the separate and mutual effect of multiple genes and in combination with acquired contributory factors on the risk of PC development. Results: Independently, carriers of at least one SOD2*C allele had increased risk of PC development, which was significantly further amplified in advanced statistical models. When tested in combination, individuals with both SOD2*C allele and Nrf2*C/C genotype were also at increased risk of PC development, which was augmented when combined with acquired contributory factors. During the mean 75 ± 25 months of follow-up, investigated gene polymorphisms did not affect overall survival. Conclusion: Our results suggest that these gene polymorphisms could be used as risk biomarkers of PC evolution.

This pilot study aimed to investigate the implementation of supervised classifiers and a neural network for the recognition of activities carried out by Individuals with Lower Limb Amputation (ILLAs), as well as individuals without gait impairment, in free living conditions. Eight individuals with no gait impairments and four ILLAs wore a thigh-based accelerometer and walked on an improvised route in the vicinity of their homes across a variety of terrains. Various machine learning classifiers were trained and tested for recognition of walking activities. Additional investigations were made regarding the detail of the activity label versus classifier accuracy and whether the classifiers were capable of being trained exclusively on non-impaired individuals' data and could recognize physical activities carried out by ILLAs. At a basic level of label detail, Support Vector Machines (SVM) and Long-Short Term Memory (LSTM) networks were able to acquire 77-78% mean classification accuracy, which fell with increased label detail. Classifiers trained on individuals without gait impairment could not recognize activities carried out by ILLAs. This investigation presents the groundwork for a HAR system capable of recognizing a variety of walking activities, both for individuals with no gait impairments and ILLAs.

Introduction: The outbreak of COVID-19 has had an impact on global healthcare as well as on radiotherapy practice in many countries. This study aimed to identify clinical characteristics of Coronavirus Disease 2019 (COVID-19) infected cancer inpatients, as well as what impact this infection had on radiation treatment of the patients., Methodology: In this retrospective study, we included cancer inpatients with laboratory confirmed COVID-19 infection during the radiotherapy or chemoradiation in April 2020 in National Cancer Research Center in Serbia. Data were obtained from the medical records between 1 April and 1 July 2020., Results: A total of 49 COVID-19 infected cancer inpatients were included. The most frequently reported cancers were head and neck cancers, in twenty-three patients (46.8%). Lymphopenia was present in 77.5% of the patients. Red blood cells, haemoglobin and platelets were significantly lower during incubation or diagnosis of COVID-19. Twenty-seven (55.1%) patients did not finish radiotherapy. The age of patients who finished radiotherapy after COVID-19 infection was significantly lower compared to the patients who did not finish radiotherapy (60.5 ± 7.8 vs. 68.6 ± 11.2; p < 0.005)., Conclusions: COVID-19 infected cancer patients in radiotherapy practice show similar symptoms and demographic characteristics as the general population infected with SARS-CoV-2 virus. Patients with head and neck cancers may be susceptible to infection with COVID-19. Old age and male gender may be risk factors for discontinuation of radiotherapy in COVID-19 infected cancer patients., Competing Interests: No Conflict of Interest is declared, (Copyright (c) 2021 Aleksandar Stepanovic, Tatjana Arsenijevic, Vesna Stankovic, Vukac Vujanac, Anja Lazovic, Tanja Raonic-Stevanovic, Marina Nikitovic.)

Considering the pleiotropic roles of glutathione transferase (GST) omega class members in redox homeostasis, we hypothesized that polymorphisms in GSTO1 and GSTO2 might contribute to prostate cancer (PC) development and progression. Therefore, we performed a comprehensive analysis of GSTO1 and GSTO2 SNPs' role in susceptibility to PC, as well as whether they might serve as prognostic biomarkers independently or in conjunction with other common GST polymorphisms ( GSTM1 , GSTT1 , and GSTP1 ). Genotyping was performed in 237 PC cases and 236 age-matched controls by multiplex PCR for deletion of GST polymorphisms and quantitative PCR for SNPs. The results of this study, for the first time, demonstrated that homozygous carriers of both GSTO1 *A/A and GSTO2 *G/G variant genotypes are at increased risk of PC. This was further confirmed by haplotype analysis, which showed that H2 comprising both GSTO1 *A and GSTO2 *G variant alleles represented a high-risk combination. However, the prognostic relevance of polymorphisms in GST omega genes was not found in our cohort of PC patients. Analysis of the role of other investigated GST polymorphisms ( GSTM1 , GSTT1 , and GSTP1 ) in terms of PC prognosis has shown shorter survival in carriers of GSTP1 *T/T ( rs1138272 ) genotype than in those carrying at least one referent allele. In addition, the presence of GSTP1 *T/T genotype independently predicted a four-fold higher risk of overall mortality among PC patients. This study demonstrated a significant prognostic role of GST polymorphism in PC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Santric, Dragicevic, Matic, Djokic, Pljesa-Ercegovac, Radic, Suvakov, Nikitovic, Stankovic, Milojevic, Radovanovic, Dzamic, Simic and Savic-Radojevic.)

Socioeconomic reasons post-COVID-19 demand unsupervised home-based rehabilitation and, specifically, artificial ambient intelligence with individualisation to support engagement and motivation. Artificial intelligence must also comply with accountability, responsibility, and transparency (ART) requirements for wider acceptability. This paper presents such a patient-centric individualised home-based rehabilitation support system. To this end, the Timed Up and Go (TUG) and Five Time Sit To Stand (FTSTS) tests evaluate daily living activity performance in the presence or development of comorbidities. We present a method for generating synthetic datasets complementing experimental observations and mitigating bias. We present an incremental hybrid machine learning algorithm combining ensemble learning and hybrid stacking using extreme gradient boosted decision trees and k -nearest neighbours to meet individualisation, interpretability, and ART design requirements while maintaining low computation footprint. The model reaches up to 100% accuracy for both FTSTS and TUG in predicting associated patient medical condition, and 100% or 83.13%, respectively, in predicting area of difficulty in the segments of the test. Our results show an improvement of 5% and 15% for FTSTS and TUG tests, respectively, over previous approaches that use intrusive means of monitoring such as cameras.

Building on recent unsupervised Non-intrusive load monitoring (NILM) algorithms that use graph Laplacian regularization (GLR) and achieve state-of-the-art performance, in this paper, we propose a novel unsupervised approach to design an underlying graph to model the correlation within time-series smart meter measurements. We propose a variable-length data segmentation approach to extract potential events, assign all measurements associated with an identified event to each graph node, employ dynamic time warping to define the adjacency matrix of the graph, and propose a robust cluster labeling approach. Our simulation results on four different datasets show up to 10% improvement in classification performance over competing approaches.

Ruthenium complexes have attracted considerable interest as potential antitumor agents. Therefore, antitumor activity and systemic toxicity of ruthenium(II) terpyridine complexes were evaluated in heterotopic mouse colon carcinoma. In the present study, cytotoxic effects of recently synthesized ruthenium(II) terpyridine complexes [Ru(Cl-tpy)(en)Cl][Cl] (en = ethylenediamine, tpy = terpyridine, Ru-1 ) and [Ru(Cl-tpy)(dach)Cl][Cl] (dach = 1,2-diaminocyclohexane, Ru-2 ) towards human and murine colon carcinoma cells were tested in vitro and in vivo and compared with oxaliplatin, the most commonly used chemotherapeutic agent against colorectal carcinoma. Ruthenium(II) complexes showed moderate cytotoxicity with IC 50 values ranging between 19.1 to 167.3 μM against two human, HCT116 and SW480, and one mouse colon carcinoma cell line, CT26. Both ruthenium(II) terpyridine complexes exerted a moderate apoptotic effect in colon carcinoma cells, but induced significant necrotic death. Additionally, both complexes induced cell cycle disturbances, but these effects were specific for the cell line. Further, Ru-1 significantly reduced the growth of primary heterotopic tumor in mice, similarly to oxaliplatin. Renal damage in Ru-1 treated mice was lower in comparison with oxaliplatin treated mice, as evaluated by serum levels of urea and creatinine and histological evaluation, but Ru-1 induced higher liver damage than oxaliplatin, evaluated by the serum levels of alanine aminotransferase. Additionally, the interaction of these ruthenium(II) terpyridine complexes with the tripeptide glutathione (GSH) was investigated by proton nuclear magnetic resonance ( 1 H NMR) spectroscopy. All reactions led to the formation of monofunctional thiolate adducts [Ru(Cl-tpy)(en)GS- S ] ( 3 ) and [Ru(Cl-tpy)(dach)GS- S ] ( 4 ). Our data highlight the significant cytotoxic activity of [Ru(Cl-tpy)(en)Cl][Cl] against human and mouse colon carcinoma cells, as well as in vivo antitumor activity in CT26 tumor-bearing mice similar to standard chemotherapeutic oxaliplatin, accompanied with lower nephrotoxicity in comparison with oxaliplatin.

Background and Objectives : One of the most frequent genetic alterations reported to date in prostate cancer (PC) is aberrant methylation of glutathione transferase P1 ( GSTP1 ). Taking into consideration the involvement of oxidative stress in PC pathogenesis and recent advances in scientific understanding of the role of GSTP1* Ala114Val rs1138272 polymorphism in carcinogenesis, we hypothesized that this single-nucleotide polymorphism (SNP) influences the risk of PC independently of, or in combination with, other GST polymorphisms, including GSTP1* IIe105Val rs1695 or GSTM1 and GSTT1 deletion polymorphisms. Materials and Methods : Genotyping was performed in 237 PC cases and in 236 age-matched controls by multiplex polymerase chain reaction (PCR) for deletion of GST polymorphisms and by quantitative PCR for SNPs. Results : We found that carriers of either GSTP1 *Val (rs1138272) or GSTP1 *Val (rs1695) variant alleles had a PC risk compared to individuals with both referent alleles (OR = 4.93, 95%CI: 2.89-8.40, p < 0.001 and OR = 1.8, 95%CI: 1.19-2.73, p = 0.006, respectively). Additionally, in a haplotype analysis we found that individuals with GSTP1*C haplotype, represented by both variant alleles (GSTP1*Val rs1695 + GSTP1*Val rs1138272) , had a 5.46 times higher risk of PC development compared to individuals with the most frequent haplotype (95%CI = 2.56-11.65, p < 0.001), suggesting a potential role of those variants in PC susceptibility. A regression analysis on the number of risk-associated alleles per individual ( GSTM1*active, GSTT1*null, GSTP1*Val rs1695 and GSTP1*Val rs1138272 ) showed a significant increase in the risk of developing PC, from 3.65-fold in carriers of two risk alleles (95%CI = 1.55-8.61, p = 0.003) to an approximately 12-fold increase in carriers of all four risk alleles (95%CI = 3.05-44.93, p < 0.001). Conclusion : Prostate cancer may be influenced by multiple glutathione transferase (GST) polymorphic genes, especially GSTP1 , highlighting the role of gene-gene interactions in human susceptibility to this cancer.

Federated learning is a decentralized topology of deep learning, that trains a shared model through data distributed among each client (like mobile phones, wearable devices), in order to ensure data privacy by avoiding raw data exposed in data center (server). After each client computes a new model parameter by stochastic gradient descent (SGD) based on their own local data, these locally-computed parameters will be aggregated to generate an updated global model. Many current state-of-the-art studies aggregate different client-computed parameters by averaging them, but none theoretically explains why averaging parameters is a good approach. In this paper, we treat each client computed parameter as a random vector because of the stochastic properties of SGD, and estimate mutual information between two client computed parameters at different training phases using two methods in two learning tasks. The results confirm the correlation between different clients and show an increasing trend of mutual information with training iteration. However, when we further compute the distance between client computed parameters, we find that parameters are getting more correlated while not getting closer. This phenomenon suggests that averaging parameters may not be the optimum way of aggregating trained parameters.

With increased demand for tele-rehabilitation, many autonomous home-based rehabilitation systems have appeared recently. Many of these systems, however, suffer from lack of patient acceptance and engagement or fail to provide satisfactory accuracy; both are needed for appropriate diagnostics. This paper first provides a detailed discussion of current sensor-based home-based rehabilitation systems with respect to four recently established criteria for wide acceptance and long engagement. A methodological procedure is then proposed for the evaluation of accuracy of portable sensing home-based rehabilitation systems, in line with medically-approved tests and recommendations. For experiments, we deploy an in-house low-cost sensing system meeting the four criteria of acceptance to demonstrate the effectiveness of the proposed evaluation methodology. We observe that the deployed sensor system has limitations in sensing fast movement. Indicators of enhanced motivation and engagement are recorded through the questionnaire responses with more than 83 % of the respondents supporting the system's motivation and engagement enhancement. The evaluation results demonstrate that the deployed system is fit for purpose with statistically significant ( ϱ c > 0 . 99 , R 2 > 0 . 94 , I C C > 0 . 96 ) and unbiased correlation to the golden standard.

Miniaturized silicon photonics spectrometers capable of detecting specific absorption features have great potential for mass market applications in medicine, environmental monitoring, and hazard detection. However, state-of-the-art silicon spectrometers are limited by fabrication imperfections and environmental conditions, especially temperature variations, since uncontrolled temperature drifts of only 0.1°C distort the retrieved spectrum precluding the detection and classification of the absorption features. Here we present a new strategy that exploits the robustness of machine learning algorithms to signal imperfections, enabling recognition of specific absorption features in a wide range of environmental conditions. We combine on-chip spatial heterodyne Fourier-transform spectrometers and supervised learning to classify different input spectra in the presence of fabrication errors, without temperature stabilization or monitoring. We experimentally show the differentiation of four different input spectra under an uncontrolled 10°C range of temperatures, about $ 100\times $100× increase in operational range, with a success rate up to 82.5% using state-of-the-art support vector machines and artificial neural networks.

Introduction: Nearly sixty percent of patients with prostate cancer (PCa) undergo radiation therapy (RT). During the course of treatment patients may experience normal tissue reactions. It is a well established fact that genetic and epigenetic mechanisms, such as microRNA (miRNA) level changes might be associated with radiotoxicity, as a response to irradiation., Materials and Methods: This is the first study that has investigated levels of radiosensory miRNAs in association with acute genitourinary radiotoxicity extracted from peripheral blood mononuclear cells (PBCs), in three points; before RT (BRT), after RT (ART) and on the first control examination (FCONT). We measured levels of miR-21/146a/155 expression by quantitative real-time PCR (qRT-PCR), comparative ΔΔCt method, in fifteen patients with localized prostate cancer, treated with three-dimensional conformal radiotherapy (3DCRT). Nine subjects have experienced acute genitourinary (GU) radiotoxicity whereas six where without GU radiotoxicity., Results: Firstly, we detected the highest levels of miR-21 in ART group (p = 0.043) in the patients with acute GU radiotoxicity. Secondly, we found trend towards higher miR-21 levels and significantly higher levels of miR-146a/155 within the patients with acute GU toxicity than in patients without (p = 0.068, p = 0.016, and p = 0.010, respectively). Thirdly, we detected significant change in miR-146a/155 levels within the patients without acute GU radiotoxicity during RT p = 0.042, and p = 0.041, respectively)., Conclusion: miR-21/146a/155 might be useful potential factors of radiosensitivity and acute genitourinary radiotoxicity in prostate cancer patients. miRNA might have great potential as predictors of various pathological conditions extracted from PBMCs., (Copyright © 2018 Elsevier GmbH. All rights reserved.)

In this work, functional characterization of biomaterials concerning potential application as articular cartilage implants was performed by using a biomimetic bioreactor with dynamic compression in the physiological regime (10% strain, 0.84 Hz frequency, 1 h on/1 h off). Specifically, two alginate types with low (LG) and high (HG) guluronic/mannuronic residue ratios with electrochemically synthesized silver nanoparticles (AgNPs) were evaluated. HG Ag/alginate hydrogels were clearly indicated as potential candidates due to better initial mechanical properties as compared to LG hydrogels (dynamic compression modulus of ~60 vs. ~40 kPa) as well as the mechanical stability displayed during 7 days of dynamic compression. Cytotoxicity studies in 3D bovine cartilage explant cultures under dynamic compression have shown negligible effects as compared to standard 2D monolayers of bovine chondrocytes where moderate cytotoxicity was observed. Finally, experimental and mathematical modeling studies revealed different mechanisms of AgNP release under physiological-like bioreactor conditions as compared to static conditions. Overall, the results clearly demonstrate bioreactor advantages in characterization and selection of candidate biomaterials as well as potentials to bridge the in vitro-in vivo gap. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 107A: 755-768, 2019., (© 2018 Wiley Periodicals, Inc.)

Aim: Quinine, a frequently used anti-malaria alkaloid isolated from the Cinchona bark, possesses numerous toxic properties, the majority of which arrive from a dysfunction of the gastrointestinal tract. Similarly, cinchonine, another alkaloid from the Cinchona bark, displays a great potential for treating malaria (especially the resistant forms)., Methods: In this work, we aimed to evaluate the effects of cinchonine on spontaneous and induced Wistar rat ileum contractions in order to uncover potential side effects that might arise after its application., Results: Cinchonine produced a concentration-dependent spasmolytic activity, which was found to be reversible (i.e. disappeared after tissue wash-up), with an IC50 value of 273 µM. Furthermore, the mechanism of action of cinchonine at IC50 elucidated through experiments with acetylcholine and Ca2+-induced ileum contractions. The applied IC50 concentration of cinchonine statistically significantly prevented the occurrence of contractions after the application of specific agonist. The obtained results are in a range with the effects seen with standard receptor antagonists, i.e. atropine and verapamil., Conclusions: The obtained results showed that cinchonine inhibited both types of induced contractions, suggesting a Ca2+-channels mediated modus operandi (Fig. 4, Ref. 19).

The neonatal type of coarctation is characterized by the presence of the ductal sling and coarctational shelf placed proximally in relation to the ductal orifice. Those morphological features are not described in detail yet from immunohistochemical and transmission electron microscopy (TEM) aspects, so the aim of this study was to investigate the smooth muscle cells (SMCs) phenotype in aortic intimal thickening, presence of inflammatory cells and contents of intimal and medial, and adventitial connective tissue. We examined samples of coarctation segments excised at surgery after end-to-end anastomosis from 30 patients, ages from 14 days to three months, histochemicaly, immunocytochemically and by TEM. In all samples, it is noticed focal intimal thickening on the posterior aortic wall, with accumulation of SMCs, which show immunoreactivity on alpha-smooth muscle actin (α-SMA) and vimentin (but not on desmin) and also expressed proliferating cell nuclear antigen (PCNA) and S-100 protein. At TEM analysis, those SMCs show a fibroblast-like morphology, so their functions could be to proliferate and secrete extracellular matrix (ECM) components (a synthetic phenotype). In all studied samples of the coarctation, on the posterior wall, the immunocytochemical and TEM examination revealed the presence of SMCs of the synthetic phenotype. Results also showed an increase of the cell number in intima of this part of aortic wall, followed by proliferated SMCs in inner media and absence of inflammatory cells. This finding suggests that proliferation of the SMCs, their synthetic activity and increase of the cell number could lead to formation of the intimal thickening on the posterior wall.

In the present study, possibilities for using novel nanocomposites based on alginate and silver nanoparticles for wound treatment were investigated in a second-degree thermal burn model in Wistar rats. Silver nanoparticles (AgNPs) were electrochemically synthesized in alginate solutions that were further utilized to obtain the Ag/alginate solution and microfibers for subsequent in vivo studies. Daily applications of the Ag/alginate colloid solution, containing AgNPs, alginate and ascorbic acid (G3), wet Ag/alginate microfibers containing AgNPs (G5) and dry Ag/alginate microfibers containing AgNPs (G6) were compared to treatments with a commercial cream containing silver sulfadiazine (G2) and a commercial Ca-alginate wound dressing containing silver ions (G4), as well as to the untreated controls (G1). Results of the in vivo study have shown faster healing in treated wounds, which completely healed on day 19 (G4, G5 and G6) and 21 (G2 and G3) after the thermal injury, while the period for complete reepitelization of untreated wounds (G1) was 25 days. The macroscopic analysis has shown that scabs fell off between day 10 and 12 after the thermal injury induction in treated groups, whereas between day 15 and 16 in the control group. These macroscopic findings were supported by the results of histopathological analyses, which have shown enhanced granulation and reepithelization, reduced inflammation and improved organization of the extracellular matrix in treated groups without adverse effects. Among the treated groups, dressings based on Ca-alginate (G4-G6) induced enhanced healing as compared to the other two groups (G2, G3), which could be attributed to additional stimuli of released Ca 2+ . The obtained results indicated potentials of novel nanocomposites based on alginate and AgNPs for therapeutic applications in wound treatments.

Smart meter roll-outs provide easy access to granular meter measurements, enabling advanced energy services, ranging from demand response measures, tailored energy feedback and smart home/building automation. To design such services, train and validate models, access to data that resembles what is expected of smart meters, collected in a real-world setting, is necessary. The REFIT electrical load measurements dataset described in this paper includes whole house aggregate loads and nine individual appliance measurements at 8-second intervals per house, collected continuously over a period of two years from 20 houses. During monitoring, the occupants were conducting their usual routines. At the time of publishing, the dataset has the largest number of houses monitored in the United Kingdom at less than 1-minute intervals over a period greater than one year. The dataset comprises 1,194,958,790 readings, that represent over 250,000 monitored appliance uses. The data is accessible in an easy-to-use comma-separated format, is time-stamped and cleaned to remove invalid measurements, correctly label appliance data and fill in small gaps of missing data.

Purpose: To estimate the incidence of acute and late lower gastrointestinal tract toxicity (LGIT) in patients treated with 3D conformal radiotherapy (3DCRT) for localized prostate cancer (PC) and estimate the influence of dosimetric parameters and other possible factors., Methods: Ninety-four patients with localized PC treated with 3DCRT, with an estimated risk of lymph node involvement ?15%, according to the Roach formula, were evaluated in this study. All patients received a total dose of 72Gy in 36 fractions. Acute and late lower gastrointestinal tract (LGIT) toxicity were graded according to the EORTC radiation morbidity scoring scale. Characteristics such as alcohol intake, gastrointestinal (GI) co-morbidities, hemorrhoids, previous abdominal or pelvic surgery (PAPS), diabetes mellitus (DM), the use of antiaggregants, and dosimetric parameters, were analyzed as possible predictive factors of radiation (RT) toxicity., Results: Grade ?1 acute LGIT toxicity during 3DCRT developed in 41 of 94 patients (43.6%). At univariate logistic regression analysis (UVA) using the baseline model, alcohol consumption (p=0.068), hemorrhoids (p=0.004), GI co-morbidities (p=0.018), PAPS (p=0.033), V60 (p=0.070), V65 (p=0.046) and V70 (P=0.056) were significant predictive factors for any grade of acute LGIT toxicity. Predictive factors of grade ?1 acute toxicity in the multivariate logistic regression analysis (MVA) were current hemorrhoids (p=0.007), and the GI co-morbidities (p=0.025). Late grade 1 LGIT toxicity occurred in 17 (18.1%) patients. Late grade ?2 LGIT toxicity as a maximum toxicity score occurred in 9 (9.57%) patients during a median follow-up of 27 months. Following UVA, hemorrhoids (p=0.001) and use of antiaggregants (p=0.034) were significant predictive factors for any grade of late LGIT toxicity. In the MVA, hemorrhoids were significantly associated with late grade ?1 LGIT toxicity (p=0.005)., Conclusion: Hemorrhoids and GI co-morbidities had a significant impact on the occurrence of acute grade ?1 LGIT toxicity. Hemorrhoids had significant influence on the development of any grade of late LGIT toxicity.

Hydroxyapatite (HAP) is the most suitable biocompatible material for bone implant coatings; its brittleness, however, is a major obstacle, and the reason why research focuses on creating composites with biopolymers. Organosolv lignin (Lig) is used for the production of composite coatings, and these composites were examined in this study. Titanium substrate is a key biomedical material due to its well-known properties, but infections of the implantation site still impose a serious threat. One approach to prevent infection is to improve antimicrobial properties of the coating material. Silver doped hydroxyapatite (Ag/HAP) and HAP coatings on titanium were obtained by an electrophoretic deposition method in order to control deposited coating mass and morphology by varying applied voltage and deposition time. The effect of lignin on microstructure, morphology and thermal behavior of biocomposite coatings was investigated. The results showed that higher lignin concentrations protect the HAP lattice during sintering, improving coating stability. The corrosion stability was evaluated in simulated body fluid (SBF) at 37 °C. Newly formed plate-shaped carbonate-HAP was detected, indicating enhanced bioactive performance. The antimicrobial efficiency of Ag/HAP/Lig was confirmed by its higher reduction of bacteria Staphylococcus aureus TL (S. aureus TL) than of HAP/Lig coating. Cytotoxicity assay revealed that both coatings can be classified as non-toxic against healthy immunocompetent peripheral blood mononuclear cells (PBMC).

Purpose: To estimate whether the computed tomography (CT) perfusion imaging could be useful to predict the pathological complete response (pCR) of esophageal cancer to the neoadjuvant chemoradiotherapy (NACRT)., Methods: Twenty-seven patients with the advanced squamous cell esophageal carcinoma, who were treated with concomitant CRT (CIS/5-FU/LV and 45-50 Gy total radiation dose), were re-evaluated using CT examination, which included the low-dose CT perfusion study. CT perfusion series were analysed using the deconvolution-based CT perfusion software (Perfusion 3.0, GE), and color parametric maps of the blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability surface area product (PS) were displayed. All patients were operated and histopathological analysis of the resected esophagus considered the gold standard for pathologic complete response (pCR)., Results: BFpost-NACRT, BVpost-NACRT, and PSpost-NACRT were significantly lower, and MTTpost-NACRT significantly higher in the pCR group. Mean (±SD), or median perfusion parameter values in the pCRs (11 patients) vs non-pCRs (16 patients) were: BFpost-NACRT- 21.4±5.0 vs 86.0±29 ml/min/100 g (p<0.001), BVpost-NACRT- 1.3 vs 3.9 ml/100 g (p<0.001), MTTpost-NACRT- 5.5 vs 3.7 s (p=0.018), and PSpost-NACRT- 5.9 vs 9.8 ml/min/100 g (p=0.006). ROC analysis revealed that BFpost- NACRT (AUC=1.000), BVpost-NACRT (AUC=0.932), MTTpost-NACRT (AUC=0.801), and PSpost-NACRT (AUC=0.844) could predict the pCR (p<0.01), while maximal esophageal wall thickness could not (AUC=0.676, p=0.126). If we set a cut-off value of BFpost-NACRT<30.0 ml/min/100 g, pCR was predicted with sensitivity and specificity of 100%., Conclusion: CT perfusion imaging enables accurate prediction of pCR of esophageal carcinoma to neoadjuvant chemoradiotherapy.

We derive an optimization framework for joint view and rate scalable coding of multi-view video content represented in the texture plus depth format. The optimization enables the sender to select the subset of coded views and their encoding rates such that the aggregate distortion over a continuum of synthesized views is minimized. We construct the view and rate embedded bitstream such that it delivers optimal performance simultaneously over a discrete set of transmission rates. In conjunction, we develop a user interaction model that characterizes the view selection actions of the client as a Markov chain over a discrete state-space. We exploit the model within the context of our optimization to compute user-action-driven coding strategies that aim at enhancing the client's performance in terms of latency and video quality. Our optimization outperforms the state-of-the-art H.264 SVC codec as well as a multi-view wavelet-based coder equipped with a uniform rate allocation strategy, across all scenarios studied in our experiments. Equally important, we can achieve an arbitrarily fine granularity of encoding bit rates, while providing a novel functionality of view embedded encoding, unlike the other encoding methods that we examined. Finally, we observe that the interactivity-aware coding delivers superior performance over conventional allocation techniques that do not anticipate the client's view selection actions in their operation.

Alginate colloid solution containing electrochemically synthesized silver nanoparticles (AgNPs) was investigated regarding the nanoparticle stabilization and possibilities for production of alginate based nanocomposite hydrogels in different forms. AgNPs were shown to continue to grow in alginate solutions for additional 3 days after the synthesis by aggregative mechanism and Ostwald ripening. Thereafter, the colloid solution remains stable for 30 days and could be used alone or in mixtures with aqueous solutions of poly(vinyl alcohol) (PVA) and poly(N-vinyl-2-pyrrolidone) (PVP) while preserving AgNPs as verified by UV-Vis spectroscopy studies. We have optimized techniques for production of Ag/alginate microbeads and Ag/alginate/PVA beads, which were shown to efficiently release AgNPs decreasing the Escherichia coli concentration in suspensions for 99.9% over 24 h. Furthermore, Ag/hydrogel discs based on alginate, PVA and PVP were produced by freezing-thawing technique allowing adjustments of hydrogel composition and mechanical properties as demonstrated in compression studies performed in a biomimetic bioreactor.

Purpose: The objective of our study was to make morphological and functional analysis of thyroid C cells in rats chronically exposed to cadmium (Cd)., Methods: The study was carried out on female albino Wistar rats (n=22, age=35-37 days, body mass 120-140 g), divided in control (n=11) and experimental group (n=11). The rats of the experimental group were treated with 15 mg/kg Cd dissolved (as CdCl(2)) in drinking water. The animals were sacrificed 3 months later. The thyroid glands were removed and macroscopic, histological and immunocytochemical examinations were done. Monoclonal antibodies for chromogranin A (Chr A), neuron specific enolase (NSE), calcitonin (CT), somatostatin (SST) and calcitonin gene related peptide (CGRP) were used for immunocytochemical examinations., Results: No pathological changes were found in parafollicular cells of the animals of the control group. All the animals of the experimental group showed bilateral diffuse C cell hyperplasia, mostly in the middle and upper thirds of the lobes. Strong immunoreactivity was present to all tested polypeptides (Chr A, CT, NSE, CGRP and SST). In 5 (45%) of the animals of the experimental group, C cell microadenomas were exclusively made of CGRP-secreting cells., Conclusion: Chronic Cd exposure causes preneoplastic changes and functional differentiation of parafollicular cells of the thyroid gland, the first cell type being present in the area of diffuse hyperplasia, and the other C cell type being the constituent of microadenomas secreting CGRP exclusively. The results of this study indicate that chronic Cd exposure disturbs the structure and function of C cells of the thyroid gland.

Purpose: To investigate the possible existence of increased nephrotoxicity caused by once-daily aminoglycosides in febrile neutropenic patients who were previously treated with cisplatin-based nephrotoxic chemotherapy., Methods: Thirty-one patients with metastatic tumors received chemotherapy and, as a result, developed febrile neutropenia. Patients were stratified with regard to chemotherapy with cisplatin (n=15) or without cisplatin (n=16). Both groups received i.v. empiric antibiotic treatment which included combinations of once-daily aminoglycosides (amikacin vs. gentamicin) with beta-lactams., Results: Increased nephrotoxicity due to administered aminoglycosides appeared significantly more frequently (p<0.05) in patients who received cisplatin-based chemotherapy. Increased nephrotoxicity differed significantly between various aminoglycosides regimens (p<0.05), being greater in the gentamicin group., Conclusion: These results showed that cisplatin-based chemotherapy followed by a once-daily aminoglycosides regimen caused increased renal toxicity, which was more pronounced in patients treated with gentamicin vs. those treated with amikacin.

Purpose: To compare a bi-weekly infusion of leucovorin (LV) 5-fluorouracil (5-FU) for 2 days, plus oxaliplatin (LV5- FU2-oxaliplatin) and LV5-FU2-cisplatin (CDDP) regimens with respect to toxicity, objective response rates, time to progression (TTP) and overall survival (OS) in patients with advanced gastric cancer., Patients and Methods: Patients received LV5-FU2- oxaliplatin (oxaliplatin 85 mg/m(2), day 1; folinic acid 200 mg/m(2), days 1-2; 5-FU 400 mg/m(2), i.v. bolus, days 1-2; 5-FU 600 mg/m(2), 22-hour continuous infusion, days 1-2) or LV5- FU2-CDDP (CDDP 50 mg/m(2), day 1; plus LV5-FU2). A total of 72 patients were enrolled into this study (36 vs. 36)., Results: A total of 305 cycles were administered in the LV5-FU2-oxaliplatin arm (median 8) and 272 cycles in the LV5-FU2-CDDP arm (median 8). Grades 3-4 toxicity were as follows (LV5-FU2-oxaliplatin %/LV5-FU2-CDDP %; p<0.05): neutropenia 5/49, thrombocytopenia 2/6, anemia 6/16 nausea/vomiting 2/15, and mucositis 0/3. Response rate of LV5-FU2-oxaliplatin was 41% (partial response/PR 41%, stable disease/SD 31%, progressive disease/PD 28%; 95% confidence internal/95% CI 27-58) and of LV5-FU2-CDDP was 25% (PR 25%, SD 36%, PD 39%; 95% CI 14-41; p =0.013). The median TTP of the patients in the LV5-FU2-oxaliplatin arm was 8 months and 6 months for those in the LV5- FU2-CDDP arm (p=0.073). The median survival time of the patients in the LV5-FU2-oxaliplatin arm was 10 months and 7 months for those in the LV5-FU2-CDDP arm (p=0.003)., Conclusion: Our study showed that oxaliplatin may be substituted for cisplatin with LV5-FU2 with favorable safety and efficacy profile. The encouraging results from our study support the effectiveness of oxaliplatin-fluoropyrimidine- containing chemotherapy in gastric cancer and could provide a new core on which to add other agents in future investigations.