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.     

Scalable phase extraction methods for phase plane motion estimation

To efficiently compute the phase difference (PD) between two complex numbers, two novel approaches are described. The problem of fast PD computation is central in many applications. As a case study, the main focus is on the phase correlation technique that is used for motion estimation. Starting from the problem statement, the system requirements are dealt with showing how PD requires a remarkable amount of computational resources. Reduced complexity techniques are then proposed and specifically tailored to suit the application needs. Each solution is completely implemented both in 0.25 mum as well as 0.13 mum CMOS. The so-called LUT-ROT exhibits noteworthy figures in terms of area occupation, delay and power dissipation, saving nearly 50% in terms of area and power when compared to recent work on this subject     

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.     

Neuramide stimulates adrenocorticotropin but not prolactin release from rat pituitary

Neuramide (NMD), a substance found in crude preparations of porcine stomach extract, is a viral inhibitor that also has putative immunostimulatory effects. The effects of NMD on stress-hormone (ACTH and prolactin-PRL) release were assessed in in vivo and in vitro studies. In the former, blood levels of corticosterone and PRL were measured in NMD-treated male rats. In vitro experiments were performed to evaluate the effects of NMD and three of its fractions (obtained with high performance liquid chromatography) on ACTH and PRL release from perfused rat pituitary slices. NMD increased plasma corticosterone levels in vivo and produced dose-dependent increases in in vitro pituitary release of ACTH. No effects on PRL secretion were observed in vivo or in vitro. The stimulatory effects on ACTH release were caused by the NMD fraction with a molecular weight of > 5000 < 10000 Da.     

Unrelated bone marrow transplantation in a Wiskott-Aldrich syndrome patient sharing two HLA-extended haplotypes with the donor

OBJECTIVE: To determine the distribution and amount of elastic fibers in the dermis of clinically normal dogs and dogs with dermatoses, particularly solar dermatitis. DESIGN: Skin specimens from 7 anatomic sites were obtained from 19 clinically normal dogs after euthanasia to evaluate the normal distribution of elastic fibers. Biopsy specimens also were obtained from 34 dogs with dermatoses, including 16 with solar dermatitis. Tissue sections were stained with H&E, Verhoeff-van Gieson, and periodic acid-Schiff. ANIMALS: 19 clinically normal dogs and 34 dogs with dermatoses. PROCEDURE: Numbers of elastic fibers were graded subjectively. Comparisons between clinically normal dogs and dogs with dermatoses were made. RESULTS: Normal elastic fibers were present in low numbers in the dermis of adult dogs, regardless of anatomic site or presence or severity of dermatitis. Condensed elastotic material was visualized in only 2 dogs with solar dermatitis. In both dogs, the elastotic material was Verhoeff-van Gieson and periodic acid-Schiff stain positive but was not visible with H&E stain. The most frequent histopathologic finding in the dermis of dogs with solar dermatitis was superficial dermal fibrosis. CONCLUSIONS: The dermis of clinically normal dogs does not contain abundant elastic fibers. Alterations of elastic fibers in dogs with solar dermatitis are rare. Superficial dermal fibrosis may be a better indicator of solar damage.     

Switching Device Based on a Thin Film of an Azo-Containing Polymer for Application in Memory Cells

Results obtained on a conductive multilevel device realized with a 100 nm azo-polymer film are reported. The capability to switch between three different conductance states makes the device versatile both for Write Once Read Many and Write Many Read Many memory cell application. The analysis of the - curves indicates that the hysteretic conductance change with the external voltage can be explained in terms of different hopping distances existing between the nearest neighbors intervening in the two conformational states of the molecular structure.     

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.     

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.