DNA Methylation Signatures of Bone Metabolism in Osteoporosis and Osteoarthritis Aging-Related Diseases: An Updated Review

DNA methylation is one of the most studied epigenetic mechanisms that play a pivotal role in regulating gene expression. The epigenetic component is strongly involved in aging-bone diseases, such as osteoporosis and osteoarthritis. Both are complex multi-factorial late-onset disorders that represent a globally widespread health problem, highlighting a crucial point of investigations in many scientific studies. In recent years, new findings on the role of DNA methylation in the pathogenesis of aging-bone diseases have emerged. The aim of this systematic review is to update knowledge in the field of DNA methylation associated with osteoporosis and osteoarthritis, focusing on the specific tissues involved in both pathological conditions.     

Network regression with predictive clustering trees

Network data describe entities represented by nodes, which may be connected with (related to) each other by edges. Many network datasets are characterized by a form of autocorrelation, where the value of a variable at a given node depends on the values of variables at the nodes it is connected with. This phenomenon is a direct violation of the assumption that data are independently and identically distributed. At the same time, it offers an unique opportunity to improve the performance of predictive models on network data, as inferences about one entity can be used to improve inferences about related entities. Regression inference in network data is a challenging task. While many approaches for network classification exist, there are very few approaches for network regression. In this paper, we propose a data mining algorithm, called NCLUS, that explicitly considers autocorrelation when building regression models from network data. The algorithm is based on the concept of predictive clustering trees (PCTs) that can be used for clustering, prediction and multi-target prediction, including multi-target regression and multi-target classification. We evaluate our approach on several real world problems of network regression, coming from the areas of social and spatial networks. Empirical results show that our algorithm performs better than PCTs learned by completely disregarding network information, as well as PCTs that are tailored for spatial data, but do not take autocorrelation into account, and a variety of other existing approaches.     

Synthesis and Evaluation of Voltage-Gated Sodium Channel Blocking Pyrroline Derivatives Endowed with Both Antiarrhythmic and Antioxidant Activities

Under the hypothesis that cardioprotective agents might benefit from synergism between antiarrhythmic activity and antioxidant properties, a small series of mexiletine analogues were coupled with the 2,2,5,5-tetramethylpyrroline moiety, known for its antioxidant effect, in order to obtain dual-acting drugs potentially useful in the protection of the heart against post-ischemic reperfusion injury. The pyrroline derivatives reported herein were found to be more potent as antiarrhythmic agents than mexiletine and displayed antioxidant activity. The most interesting tetramethylpyrroline congener, a tert-butyl-substituted analogue, was at least 100 times more active as an antiarrhythmic than mexiletine.     

Electrochemical characterization of 8-hydroxyquinoline-5-sulphonate/aluminium(III) aqueous solutions

8-Hydroxyquinoline-5-sulphonate/Al(III) aqueous solutions were studied both by potentiometric titrations and voltammetric measurements, in order to obtain the number, the stoichiometry and the stability constants of the complexes formed at equilibrium, and to evaluate the redox and (electro)kinetic properties of the free ligand and of the metal/ligand complexes. The complexes formed in 0.2 m (Na)Cl aqueous solution (stability log beta values ± standard deviation) are AlL⁺ (8.95 ± 0.05), AlL₂⁻ (17.43 ± 0.03) and AlL₃³⁻ (24.58 ± 0.05), where “L” denotes the free ligand in the completely deprotonated form (L²⁻, pK_a1 = 3.910 ± 0.008, pK_a2 = 8.319 ± 0.004). AlL₃³⁻ is the predominant Al(III) species in a very wide range of pH, metal and ligand concentrations and metal-to-ligand ratios. The free ligand shows an oxidation wave at 0.62 V versus SCE. The proposed oxidation mechanism includes a first reversible one-electron oxidation of the ligand, followed by a coupling reaction and by a second reversible one-electron oxidation, and finally by a decomposition reaction. The addition of Al(III) lowers the intensity of the oxidation wave due to the formation of the redox-inactive complex AlL₃³⁻. A residual low signal was attributed to the free ligand produced by the complex dissociation, AlL₃³⁻ = AlL₂⁻ + L²⁻. All the kinetic parameters involved in the ligand oxidation and in the complex disruption were calculated on the basis of the agreement between experimental and simulated linear sweep and cyclic voltammetries. Correctness of the mechanisms proposed was further confirmed “a posteriori” by the agreement between potentiometric and linear sweep voltammetric results. The low residual signal observed in the presence of fully formed complex was attributed to the free ligand produced by the complex dissociation, having a kinetic constant estimated 0.2 s⁻¹.     

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.     

Analysis and verification of SMIL documents

In this paper, we consider the problem of automatic verification of SMIL documents and present a tool which can assist the user in the complex task of authoring a multimedia presentation. The tool is based on a formal semantics defining the temporal aspects of SMIL elements by means of a set of inference rules. The rules, in the spirit of Hoare’s semantics, describe how the execution of a piece of code changes the state of the computation of a player. If any temporal conflict is found, the system returns a message to the user pointing out the element which contains the conflict and its motivation. This helps the user to develop robust and clear code.     

Mixture of KL subspaces for relevance feedback

Relevance feedback has recently emerged as a solution to the problem of improving the retrieval performance of an image retrieval system based on low-level information such as color, texture and shape features. Most of the relevance feedback approaches limit the utilization of the user’s feedback to a single search session, performing a short-term learning. In this paper we present a novel approach for short and long term learning, based on the definition of an adaptive similarity metric and of a high level representation of the images. For short-term learning, the relevant and non-relevant information given by the user during the feedback process is employed to create a positive and a negative subspace of the feature space. For long-term learning, the feedback history of all the users is exploited to create and update a representation of the images which is adopted for improving retrieval performance and progressively reducing the semantic gap between low-level features and high-level semantic concepts. The experimental results prove that the proposed method outperforms many other state of art methods in the short-term learning, and demonstrate the efficacy of the representation adopted for the long-term learning.

The State of the Art of Piezo1 Channels in Skeletal Muscle Regeneration

Piezo1 channels are highly mechanically-activated cation channels that can sense and transduce the mechanical stimuli into physiological signals in different tissues including skeletal muscle. In this focused review, we summarize the emerging evidence of Piezo1 channel-mediated effects in the physiology of skeletal muscle, with a particular focus on the role of Piezo1 in controlling myogenic precursor activity and skeletal muscle regeneration and vascularization. The disclosed effects reported by pharmacological activation of Piezo1 channels with the selective agonist Yoda1 indicate a potential impact of Piezo1 channel activity in skeletal muscle regeneration, which is disrupted in various muscular pathological states. All findings reported so far agree with the idea that Piezo1 channels represent a novel, powerful molecular target to develop new therapeutic strategies for preventing or ameliorating skeletal muscle disorders characterized by an impairment of tissue regenerative potential.     

Eco-Sustainable Silk Fibroin/Pomegranate Peel Extract Film as an Innovative Green Material for Skin Repair

Skin disorders are widespread around the world, affecting people of all ages, and oxidative stress represents one of the main causes of alteration in the normal physiological parameters of skin cells. In this work, we combined a natural protein, fibroin, with antioxidant compounds extracted in water from pomegranate waste. We demonstrate the effective and facile fabrication of bioactive and eco-sustainable films of potential interest for skin repair. The blended films are visually transparent (around 90%); flexible; stable in physiological conditions and in the presence of trypsin for 12 days; able to release the bioactive compounds in a controlled manner; based on Fickian diffusion; and biocompatible towards the main skin cells, keratinocytes and fibroblasts. Furthermore, reactive oxygen species (ROS) production tests demonstrated the high capacity of our films to reduce the oxidative stress induced in cells, which is responsible for various skin diseases.