Anomalous Monism in a Digital Universe

Bermúdez (Philosophy of psychology: a contemporary introduction, Routledge, London, 2005) identifies the “Interface Problem” as the central problem in the philosophy of psychology: how commonsensical psychological explanations can be integrated with lower-level (cognitive, biological, etc.) explanations? In particular, since folk psychology is meant to provide causal explanations on a par with, say, neurobiological explanations, the question of how to understand the relation between the two layers arises naturally. Donald Davidson claimed that the interface problem is actually ill-posed and put forward his version of the “Autonomy Picture”, the view known as anomalous monism. This work reviews Davidson’s proposal in the light of digital universes: we model the key claims of the theory using cellular automata and show that Davidson’s original version of the Autonomy Picture (which differs, in some respects, from what is discussed by Bermúdez) is immune to two arguments against autonomy.     

Looking at the viewer: analysing facial activity to detect personal highlights of multimedia contents

This paper presents an approach to detect personal highlights in videos based on the analysis of facial activities of the viewer. Our facial activity analysis was based on the motion vectors tracked on twelve key points in the human face. In our approach, the magnitude of the motion vectors represented a degree of a viewer’s affective reaction to video contents. We examined 80 facial activity videos recorded for ten participants, each watching eight video clips in various genres. The experimental results suggest that useful motion vectors to detect personal highlights varied significantly across viewers. However, it was suggested that the activity in the upper part of face tended to be more indicative of personal highlights than the activity in the lower part.     

Molecular Dynamics Simulations Reveal Structural Interconnections within Sec14-PH Bipartite Domain from Human Neurofibromin

Neurofibromin, the main RasGAP in the nervous system, is a 2818 aa protein with several poorly characterized functional domains. Mutations in the NF1-encoding gene lead to an autosomal dominant syndrome, neurofibromatosis, with an incidence of 1 out of 3000 newborns. Missense mutations spread in the Sec14-PH-encoding sequences as well. Structural data could not highlight the defect in mutant Sec14-PH functionality. By performing molecular dynamics simulations at different temperatures, we found that the lid-lock is fundamental for the structural interdependence of the NF1 bipartite Sec14-PH domain. In fact, increased flexibility in the lid-lock loop, observed for the K1750Δ mutant, leads to disconnection of the two subdomains and can affect the stability of the Sec14 subdomain.     

A Narrative Review: Gingival Stem Cells as a Limitless Reservoir for Regenerative Medicine

The gingival tissue can be collected in an easy way and represent an accessible source to isolate gingival-derived mesenchymal stem cells (GMSCs). GMSCs are a subpopulation of dental-derived mesenchymal stem cells that show the mesenchymal stem cells (MSCs) features, such as differentiation abilities and immunomodulatory properties. Dental-derived stem cells are also expandable in vitro with genomic stability and the possibility to maintain the stemness properties over a prolonged period of passages. Moreover, several preclinical studies have documented that the extracellular vesicles (EVs) released from GMSCs possess similar biological functions and therapeutic effects. The EVs may represent a promising tool in the cell-free regenerative therapy approach. The present review paper summarized the GMSCs, their multi-lineage differentiation capacities, immunomodulatory features, and the potential use in the treatment of several diseases in order to stimulate tissue regeneration. GMSCs should be considered a good stem cell source for potential applications in tissue engineering and regenerative dentistry.     

Self‐Assembled Dual Dye‐Doped Nanosized Micelles for High‐Contrast Up‐Conversion Bioimaging

Sensitized triplet–triplet annihilation based photon up‐conversion (TTA‐UC) greatly improves the scope and applicability of fluorescence bioimaging by enabling anti‐Stokes detection at low powers, thus eliminating the background autofluorescence and limiting the potential damage of the living tissues. Here the authors present a facile, one‐step protocol to prepare dual dye‐doped, TTA‐UC active nanomicelles starting from the commercially available surfactant Kolliphor EL, a component of several FDA approved preparations. These nanosized micelles show an unprecedented up‐conversion yield of 6.5% under 0.1 W cm^?2 excitation intensity in an aqueous, nondeaerated dispersion. The supramolecular architecture obtained preserves the embedded dyes from oxygen quenching, allowing satisfactory anti‐Stokes fluorescence imaging of 3T3 cells. This is the first example of efficient multicomponent up‐converters prepared using highly biocompatible materials approved by the international authority, paving the way for the development of new complex and multifunctional materials for advanced theranostics.     

Experimental methods in chemical engineering: Artificial neural networks–ANNs

Artificial neural networks (ANNs) are one of the most powerful and versatile tools provided by artificial intelligence and they have now been exploited by chemical engineers for several decades in countless applications. ANNs are computational tools providing a minimalistic mathematical model of neural functions. Coupled with raw data and a learning algorithm, they can be applied to tasks such as modelling, classification, and prediction. Recently, their popularity has grown remarkably and they now constitute one of the most relevant research areas within the fields of artificial intelligence and machine learning. ANNs are large collections of simple classifiers called neurons. Chemical engineers apply them to model complex relationships, predict reactor performance, and to automate process controllers. ANNs can leverage their ability to learn and exploit large data sets, but they can also get stuck in local minima or overfit and are difficult to reverse engineer. In 2016 and 2017, ANNs were cited in 13 245 Web of Science (WoS) articles, 538 of which were in chemical engineering; the top WoS categories were electrical & electronic engineering (1615 occurrences) artificial intelligence (1253), and energy & fuels (980). The top 4 journals mentioning ANNs were Neural Computing & Applications (117), Neurocomputing (84), Energies (76), and Renewable & Sustainable Energy Reviews (76). In the near future, as larger data sets become available (and arduous to analyze), chemical engineers will be able to apply and leverage more sophisticated ANN architectures.     

Resistive random access memory (RRAM) technology: From material,device, selector, 3D integration to bottom-up fabrication

Emerging non-volatile memory technologies are promising due to their anticipated capacity benefits, non-volatility, and zero idle energy. One of the most promising candidates is resistive random access memory (RRAM) based on resistive switching (RS). This paper reviews the development of RS device technology including the fundamental physics, material engineering, three-dimension (3D) integration, and bottom-up fabrication. The device operation, physical mechanisms for resistive switching, reliability metrics, and memory cell selector candidates are summarized from the recent advancement in both industry and academia. Options for 3D memory array architectures are presented for the mass storage application. Finally, the potential application of bottom-up fabrication approaches for effective manufacturing is introduced.     

Inhibition of PKCθ Improves Dystrophic Heart Phenotype and Function in a Novel Model of DMD Cardiomyopathy

Chronic cardiac muscle inflammation and subsequent fibrotic tissue deposition are key features in Duchenne Muscular Dystrophy (DMD). The treatment of choice for delaying DMD progression both in skeletal and cardiac muscle are corticosteroids, supporting the notion that chronic inflammation in the heart plays a pivotal role in fibrosis deposition and subsequent cardiac dysfunction. Nevertheless, considering the adverse effects associated with long-term corticosteroid treatments, there is a need for novel anti-inflammatory therapies. In this study, we used our recently described exercised mdx (ex mdx) mouse model characterised by accelerated heart pathology, and the specific PKCθ inhibitor Compound 20 (C20), to show that inhibition of this kinase leads to a significant reduction in the number of immune cells infiltrating the heart, as well as necrosis and fibrosis. Functionally, C20 treatment also prevented the reduction in left ventricle fractional shortening, which was typically observed in the vehicle-treated ex mdx mice. Based on these findings, we propose that PKCθ pharmacological inhibition could be an attractive therapeutic approach to treating dystrophic cardiomyopathy     

Extracellular Matrix Hydrogels Originated from Different Organs Mediate Tissue-Specific Properties and Function

Porcine extracellular matrix (pECM)-derived hydrogels were introduced, in recent years, aiming to benefit the pECM’s microstructure and bioactivity, while controlling the biomaterial’s physical and mechanical properties. The use of pECM from different tissues, however, offers tissue-specific features that can better serve different applications. In this study, pECM hydrogels derived from cardiac, artery, pancreas, and adipose tissues were compared in terms of composition, structure, and mechanical properties. While major similarities were demonstrated between all the pECM hydrogels, their distinctive attributes were also identified, and their substantial effects on cell-ECM interactions were revealed. Furthermore, through comprehensive protein and gene expression analyses, we show, for the first time, that each pECM hydrogel supports the spontaneous differentiation of induced pluripotent stem cells towards the resident cells of its origin tissue. These findings imply that the origin of ECM should be carefully considered when designing a biomedical platform, to achieve a maximal bioactive impact.