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.     

Changes in pain perception and pain-related somatosensory evoked potentials in humans produced by exposure to oscillating magnetic fields

cDNA selection was used to isolate coding sequences from cosmids mapping to the gene-rich telomeric region of human chromosome 21q. A novel cDNA, termed SMT3A, was isolated and mapped between the loci PFKL and D21S171, about 2.2 Mb proximal to the telomere. The predicted protein of 103 amino acids appears to be a homologue of the Saccharomyces cerevisiae SMT3 protein, whose gene was previously isolated as a suppressor of mutations in the MIF2 gene. The yeast MIF2 gene encodes an essential centromeric protein and shows homology to mammalian CENP-C, an integral component of active kinetochores. SMT3A was found to be highly homologous to two other recently isolated human genes, suggesting the presence of a new gene family. Homologous sequences were also found in protozoa, metazoa, and plants. Moreover, all predicted proteins show significant homology to ubiquitin. The proposed role of yeast SMT3 as centromeric protein and the strong evolutionary conservation of the SMT3A gene suggest an involvement of the encoded protein in the function and/or structure of the eukaryotic kinetochore.     

Building kernels from binary strings for image matching.

In the statistical learning framework, the use of appropriate kernels may be the key for substantial improvement in solving a given problem. In essence, a kernel is a similarity measure between input points satisfying some mathematical requirements and possibly capturing the domain knowledge. In this paper, we focus on kernels for images: we represent the image information content with binary strings and discuss various bitwise manipulations obtained using logical operators and convolution with nonbinary stencils. In the theoretical contribution of our work, we show that histogram intersection is a Mercer's kernel and we determine the modifications under which a similarity measure based on the notion of Hausdorff distance is also a Mercer's kernel. In both cases, we determine explicitly the mapping from input to feature space. The presented experimental results support the relevance of our analysis for developing effective trainable systems.     

Promoting the integration of technology in teaching: An analysis of the factors that increase the intention to use technologies among Italian teachers

Background: The rapid spread of COVID-19 forced many countries to adopt severe containment measures, transferring all didactic activities into virtual environments. However, the integration of technology in teaching may present difficulties, especially in some countries, such as Italy. Objectives: The present study analyzed how the two main factors of the Technology Acceptance Model (TAM), namely perceived usefulness and perceived ease of use, combined with online teaching self-efficacy, were associated with the intention to use technology to teach. We posited a moderated moderation model in which perceived usefulness represented the main predictor, with self-efficacy and perceived ease of use as moderators of intention to use technology to teach. Method: The model was tested through multiple regressions, using the PROCESS macro on SPSS 26 with a sample of 178 upper secondary school teachers in Italy. Results and conclusions: Regressions showed that each variable significantly predicted the intention to use technology. In addition, a moderation effect of self-efficacy on the perceived usefulness of using technology was found for medium and high-level of perceived ease of use of technology. Implications: The present study provides targeted implications for distance education policy and practice to promote its adoption (or the blended modality) in Italian upper schools.     

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.     

Molecular Aspects and Prognostic Significance of Microcalcifications in Human Pathology: A Narrative Review

The presence of calcium deposits in human lesions is largely used as imaging biomarkers of human diseases such as breast cancer. Indeed, the presence of micro- or macrocalcifications is frequently associated with the development of both benign and malignant lesions. Nevertheless, the molecular mechanisms involved in the formation of these calcium deposits, as well as the prognostic significance of their presence in human tissues, have not been completely elucidated. Therefore, a better characterization of the biological process related to the formation of calcifications in different tissues and organs, as well as the understanding of the prognostic significance of the presence of these calcium deposits into human tissues could significantly improve the management of patients characterized by microcalcifications associated lesions. Starting from these considerations, this narrative review highlights the most recent histopathological and molecular data concerning the formation of calcifications in breast, thyroid, lung, and ovarian diseases. Evidence reported here could deeply change the current point of view concerning the role of ectopic calcifications in the progression of human diseases and also in the patients’ management. In fact, the presence of calcifications can suggest an unfavorable prognosis due to dysregulation of normal tissues homeostasis.     

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.     

Immersive and desktop virtual reality in virtual fashion stores: a comparison between shopping experiences

Virtual Reality - With the high growth and prosperity of e-commerce, the retail industry needs to explore new technologies that improve digital shopping experiences. In the current technological...