Influence of plasticizers and cryogenic grinding on the high‐cooling‐rate solidification behavior of PBT/PET blends

Two structurally different plasticizers (cyclic and linear) and the effect of cryogenic grinding on the solidification behavior at high cooling rates by a continuous cooling transformation approach of poly(butylene terephthalate)/poly(ethylene terephthalate), PBT/PET, blends are described. The solidification curve (density versus cooling rate) is confirmed as an effective tool to compare the differences in crystallization behavior under conditions mimicking processing. In comparison to the bulky cyclic plasticizer, the linear oligomeric one was found to have a more pronounced influence on the crystallization behavior. A 60/40 by weight PBT/PET blend shows a drop‐off of density at ～50 K/s. In the plasticized sample, the long‐range crystalline order appears up to a cooling rate of ～250K/s, making the blend comparable to pure PBT. Grinding the components before blending further improves crystallizability and synergy to the addition of the plasticizer. The results suggest the important role of local chain mobility in the solidification behavior at high cooling rates. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43083.     

Colorectal Cancer Apoptosis Induced by Dietary δ-Valerobetaine Involves PINK1/Parkin Dependent-Mitophagy and SIRT3

Understanding the mechanisms of colorectal cancer progression is crucial in the setting of strategies for its prevention. δ-Valerobetaine (δVB) is an emerging dietary metabolite showing cytotoxic activity in colon cancer cells via autophagy and apoptosis. Here, we aimed to deepen current knowledge on the mechanism of δVB-induced colon cancer cell death by investigating the apoptotic cascade in colorectal adenocarcinoma SW480 and SW620 cells and evaluating the molecular players of mitochondrial dysfunction. Results indicated that δVB reduced cell viability in a time-dependent manner, reaching IC50 after 72 h of incubation with δVB 1.5 mM, and caused a G2/M cell cycle arrest with upregulation of cyclin A and cyclin B protein levels. The increased apoptotic cell rate occurred via caspase-3 activation with a concomitant loss in mitochondrial membrane potential and SIRT3 downregulation. Functional studies indicated that δVB activated mitochondrial apoptosis through PINK1/Parkin pathways, as upregulation of PINK1, Parkin, and LC3B protein levels was observed (p < 0.0001). Together, these findings support a critical role of PINK1/Parkin-mediated mitophagy in mitochondrial dysfunction and apoptosis induced by δVB in SW480 and SW620 colon cancer cells.     

The Role of Endothelium in COVID-19

The 2019 novel coronavirus, known as severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) or coronavirus disease 2019 (COVID-19), is causing a global pandemic. The virus primarily affects the upper and lower respiratory tracts and raises the risk of a variety of non-pulmonary consequences, the most severe and possibly fatal of which are cardiovascular problems. Data show that almost one-third of the patients with a moderate or severe form of COVID-19 had preexisting cardiovascular comorbidities such as diabetes mellitus, obesity, hypertension, heart failure, or coronary artery disease. SARS-CoV2 causes hyper inflammation, hypoxia, apoptosis, and a renin–angiotensin system imbalance in a variety of cell types, primarily endothelial cells. Profound endothelial dysfunction associated with COVID-19 can be the cause of impaired organ perfusion that may generate acute myocardial injury, renal failure, and a procoagulant state resulting in thromboembolic events. We discuss the most recent results on the involvement of endothelial dysfunction in the pathogenesis of COVID-19 in patients with cardiometabolic diseases in this review. We also provide insights on treatments that may reduce the severity of this viral infection.     

Translesion Synthesis or Repair by Specialized DNA Polymerases Limits Excessive Genomic Instability upon Replication Stress

DNA can experience “replication stress”, an important source of genome instability, induced by various external or endogenous impediments that slow down or stall DNA synthesis. While genome instability is largely documented to favor both tumor formation and heterogeneity, as well as drug resistance, conversely, excessive instability appears to suppress tumorigenesis and is associated with improved prognosis. These findings support the view that karyotypic diversity, necessary to adapt to selective pressures, may be limited in tumors so as to reduce the risk of excessive instability. This review aims to highlight the contribution of specialized DNA polymerases in limiting extreme genetic instability by allowing DNA replication to occur even in the presence of DNA damage, to either avoid broken forks or favor their repair after collapse. These mechanisms and their key regulators Rad18 and Polθ not only offer diversity and evolutionary advantage by increasing mutagenic events, but also provide cancer cells with a way to escape anti-cancer therapies that target replication forks.     

Adsorption Behavior of Halogenated Anesthetic and Water Vapor on Cr‐Based MOF (MIL‐101) Adsorbent. Part I. Equilibrium and Breakthrough Characterizations

A synthesized chromium‐based metal organic framework (Cr‐MOF) was used for the adsorption of halogenated anesthetics, i.e., sevoflurane (SF). Adsorption isotherm and breakthrough experiments involving SF (reference sorbate) and water vapor were measured at 298 K and atmospheric pressure on both Cr‐MOF and a commercially used reference adsorbent. The Cr‐MOF MIL‐101 showed a significantly higher SF adsorption capacity and much higher selectivity relative to water vapor compared to the reference adsorbent. Binary‐mixture breakthrough tests demonstrated a “roll‐up effect” for SF on the reference adsorbent while no such effect was observed on MIL‐101.     

Coherence of PRNU weighted estimations for improved source camera identification

Multimedia Tools and Applications - This paper presents a method for Photo Response Non Uniformity (PRNU) pattern noise based camera identification. It takes advantage of the coherence between...     

Good teaching inputs do not correspond to desired responses in ecological neural networks

In this paper we analyze how supervised learning occurs in ecological neural networks, i.e. networks that interact with an autonomous external environment and, therefore, at least partially determine with their behavior their own input. Using an evolutionary method for selecting good teaching inputs we surprisingly find that to obtain a desired outputX it is better to use a teaching input different fromX. To explain this fact we claim that teaching inputs in ecological networks have two different effects: (a) to reduce the discrepancy between the actual output of the network and the teaching input, (b) to modify the network's behavior and, as a consequence, the network's learning experiences. Evolved teaching inputs appear to represent a compromise between these two needs. We finally show that evolved teaching inputs that are allowed to change during the learning process function differently at different stages of learning, first giving more weight to (b) and, later on, to (a).     

A graph-based approach for extracting terminological properties from information sources with heterogeneous formats

The problem of handling both the integration and the cooperation of a large number of information sources characterised by heterogeneous representation formats is a challenging issue. In this context, a central role can be played by the knowledge about the semantic relationships holding between concepts belonging to different information sources (intersource properties). In this paper, we propose a semiautomatic approach for extracting two kinds of intersource properties, namely synonymies and homonymies, from heterogeneous information sources. In order to carry out the extraction task, we introduce both a conceptual model, for representing involved sources, and a metrics, for measuring the strength of the semantic relationships holding among concepts represented within the same source.     

A Technique for Extracting Sub-source Similarities from Information Sources Having Different Formats

In this paper we propose a semi-automatic technique for deriving the similarity degree between two portions of heterogeneous information sources (hereafter, sub-sources). The proposed technique consists in two phases: the first one selects the most promising pairs of sub-sources, whereas the second one computes the similarity degree relative to each promising pair. We show that the detection of sub-source similarities is a special case (and a very interesting one, for semi-structured information sources) of the more general problem of Scheme Match. In addition, we present a real example case to clarify the proposed technique, a set of experiments we have conducted to verify the quality of its results, a discussion about its computational complexity and its classification in the context of related literature. Finally, we discuss some possible applications which can benefit by derived similarities.     

Controllability of One Spin and Two Interacting Spins

Mathematics of Control, Signals, and Systems - ?We consider the problem of steering control for the systems of one spin ½ particle and two interacting spin ½ particles in an...