Sorafenib delivery nanoplatform based on superparamagnetic iron oxide nanoparticles magnetically targets hepatocellular carcinoma

Currently,sorafenib is the only systemic therapy capable of increasing overall survival of hepatocellular carcinoma patients.Unfortunately,its side effects,particularly its overall toxicity,limit the therapeutic response that can be achieved.Superparamagnetic iron oxide nanoparticles (SPIONs) are very attractive for drug delivery because they can be targeted to specific sites in the body through application of a magnetic field,thus improving intratumoral accumulation and reducing adverse effects.Here,nanoformulations based on polyethylene glycol modified phospholipid micelles,loaded with both SPIONs and sorafenib,were successfully prepared and thoroughly investigated by complementary techniques.This nanovector system provided effective drug delivery,had an average hydrodynamic diameter of about 125 nm,had good stability in aqueous medium,and allowed controlled drug loading.Magnetic analysis allowed accurate determination of the amount of SPIONs embedded in each micelle.An in vitro system was designed to test whether the SPION micelles can be efficiently held using a magnetic field under typical flow conditions found in the human liver.Human hepatocellular carcinoma (HepG2) cells were selected as an in vitro system to evaluate tumor cell targeting efficacy of the superparamagnetic micelles loaded with sorafenib.These experiments demonstrated that this delivery platform is able to enhance sorafenib's antitumor effectiveness by magnetic targeting.The magnetic nanovectors described here represent promising candidates for targeting specific hepatic tumor sites,where selective release of sorafenib can improve its efficacy and safety profile.     

Granular neural networks for numerical-linguistic data fusion andknowledge discovery

We present a neural-networks-based knowledge discovery and data mining (KDDM) methodology based on granular computing, neural computing, fuzzy computing, linguistic computing, and pattern recognition. The major issues include 1) how to make neural networks process both numerical and linguistic data in a database, 2) how to convert fuzzy linguistic data into related numerical features, 3) how to use neural networks to do numerical-linguistic data fusion, 4) how to use neural networks to discover granular knowledge from numerical-linguistic databases, and 5) how to use discovered granular knowledge to predict missing data. In order to answer the above concerns, a granular neural network (GNN) is designed to deal with numerical-linguistic data fusion and granular knowledge discovery in numerical-linguistic databases. From a data granulation point of view the GNN can process granular data in a database. From a data fusion point of view, the GNN makes decisions based on different kinds of granular data. From a KDDM point of view the GNN is able to learn internal granular relations between numerical-linguistic inputs and outputs, and predict new relations in a database. The GNN is also capable of greatly compressing low-level granular data to high-level granular knowledge with some compression error and a data compression rate. To do KDDM in huge databases, parallel GNN and distributed GNN will be investigated in the future.     

Detection of epileptic electroencephalogram based on Permutation Entropy and Support Vector Machines

The electroencephalogram (EEG) has proven a valuable tool in the study and detection of epilepsy. This paper investigates for the first time the use of Permutation Entropy (PE) as a feature for automated epileptic seizure detection. A Support Vector Machine (SVM) is used to classify segments of normal and epileptic EEG based on PE values. The proposed system utilizes the fact that the EEG during epileptic seizures is characterized by lower PE than normal EEG. It is shown that average sensitivity of 94.38% and average specificity of 93.23% is obtained by using PE as a feature to characterize epileptic and seizure-free EEG, while 100% sensitivity and specificity were also obtained in single-trial classifications.     

Applying EuroWordNet to Cross-Language Text Retrieval

We discuss ways in which EuroWordNet (EWN) can be used in multilingual information retrieval activities, focusing on two approaches to Cross-Language Text Retrieval that use the EWN database as a large-scale multilingual semantic resource. The first approach indexes documents and queries in terms of the EuroWordNet Inter-Lingual-Index, thus turning term weighting and query/document matching into language-independent tasks. The second describes how the information in the EWN database could be integrated with a corpus-based technique, thus allowing retrieval of domain-specific terms that may not be present in our multilingual database. Our objective is to show the potential of EuroWordNet as a promising alternative to existing approaches to Cross-Language Text Retrieval.     

Stringency of regulation and innovation in waste management: an empirical analysis on EU countries

The transformation of waste into a valuable resource is a key process towards sustainable development and green growth and therefore represents a major concern for policy-makers. Technological innovation plays a crucial role in waste management and therefore understanding the way in which regulation may spur innovation in this domain constitute is crucial. This article aims at testing the weak version of the Porter hypothesis in waste management, by analysing the dynamic relationship between the stringency of environmental regulation and innovation in a European cross-country setting. Results confirm that the stringency of regulation positively affects innovation, but the effect is non-linear, suggesting the existence of an optimal cap to the stringency of regulation. Furthermore, the overall environmental conditions of the country, as well as the presence of highly polluting sectors hinder the development of environmental innovations.     

The L467F-F508del Complex Allele Hampers Pharmacological Rescue of Mutant CFTR by Elexacaftor/Tezacaftor/Ivacaftor in Cystic Fibrosis Patients: The Value of the Ex Vivo Nasal Epithelial Model to Address Non-Responders to CFTR-Modulating Drugs

Loss-of-function mutations of the CFTR gene cause cystic fibrosis (CF) through a variety of molecular mechanisms involving altered expression, trafficking, and/or activity of the CFTR chloride channel. The most frequent mutation among CF patients, F508del, causes multiple defects that can be, however, overcome by a combination of three pharmacological agents that improve CFTR channel trafficking and gating, namely, elexacaftor, tezacaftor, and ivacaftor. This study was prompted by the evidence of two CF patients, compound heterozygous for F508del and a minimal function variant, who failed to obtain any beneficial effects following treatment with the triple drug combination. Functional studies on nasal epithelia generated in vitro from these patients confirmed the lack of response to pharmacological treatment. Molecular characterization highlighted the presence of an additional amino acid substitution, L467F, in cis with the F508del variant, demonstrating that both patients were carriers of a complex allele. Functional and biochemical assays in heterologous expression systems demonstrated that the double mutant L467F-F508del has a severely reduced activity, with negligible rescue by CFTR modulators. While further studies are needed to investigate the actual prevalence of the L467F-F508del allele, our results suggest that this complex allele should be taken into consideration as plausible cause in CF patients not responding to CFTR modulators.     

Validation of a Cleanroom Compliant Sonication-Based Decellularization Technique: A New Concept in Nerve Allograft Production

Defects of the peripheral nervous system are extremely frequent in trauma and surgeries and have high socioeconomic costs. If the direct suture of a lesion is not possible, i.e., nerve gap > 2 cm, it is necessary to use grafts. While the gold standard is the autograft, it has disadvantages related to its harvesting, with an inevitable functional deficit and further morbidity. An alternative to autografting is represented by the acellular nerve allograft (ANA), which avoids disadvantages of autograft harvesting and fresh allograft rejection. In this research, the authors intend to transfer to human nerves a novel technique, previously implemented in animal models, to decellularize nerves. The new method is based on soaking the nerve tissues in decellularizing solutions while associating ultrasounds and freeze–thaw cycles. It is performed without interrupting the sterility chain, so that the new graft may not require post-production γ-ray irradiation, which is suspected to affect the structural and functional quality of tissues. The new method is rapid, safe, and inexpensive if compared with available commercial ANAs. Histology and immunohistochemistry have been adopted to evaluate the new decellularized nerves. The study shows that the new method can be applied to human nerve samples, obtaining similar, and, sometimes better, results compared with the chosen control method, the Hudson technique.     

The Role of Cytoskeleton Revealed by Quartz Crystal Microbalance and Digital Holographic Microscopy

The connection between cytoskeleton alterations and diseases is well known and has stimulated research on cell mechanics, aiming to develop reliable biomarkers. In this study, we present results on rheological, adhesion, and morphological properties of primary rat cardiac fibroblasts, the cytoskeleton of which was altered by treatment with cytochalasin D (Cyt-D) and nocodazole (Noc), respectively. We used two complementary techniques: quartz crystal microbalance (QCM) and digital holographic microscopy (DHM). Qualitative data on cell viscoelasticity and adhesion changes at the cell–substrate near-interface layer were obtained with QCM, while DHM allowed the measurement of morphological changes due to the cytoskeletal alterations. A rapid effect of Cyt-D was observed, leading to a reduction in cell viscosity, loss of adhesion, and cell rounding, often followed by detachment from the surface. Noc treatment, instead, induced slower but continuous variations in the rheological behavior for four hours of treatment. The higher vibrational energy dissipation reflected the cell’s ability to maintain a stable attachment to the substrate, while a cytoskeletal rearrangement occurs. In fact, along with the complete disaggregation of microtubules at prolonged drug exposure, a compensatory effect of actin polymerization emerged, with increased stress fiber formation.