Toward a better understanding of multifunctional cement-based materials: The impact of graphite nanoplatelets (GNPs)

The impact of graphite nanoplatelets (GNPs) on the physical and mechanical properties of cementitious nanocomposites was investigated. A market-available premixed mortar was modified with 0.01% by weight of cement of commercial GNPs characterized by two distinctively different aspect ratios.The rheological behavior of the GNP-modified fresh admixtures was thoroughly evaluated. Hardened cementitious nanocomposites were investigated in terms of density, microstructure (Scanning Electron Microscopy, SEM and micro–Computed Tomography, μ-CT), mechanical properties (three-point bending and compression tests), and physical properties (electrochemical impedance spectroscopy, EIS and thermal conductivity measurements). At 28 days, all GNP-modified mortars showed about 12% increased density. Mortars reinforced with high aspect ratio GNPs exhibited the highest compressive and flexural strength: about 14% and 4% improvements compared to control sample, respectively. Conversely, low aspect ratio GNPs led to cementitious nanocomposites characterized by 36% decreased electrical resistivity combined with 60% increased thermal conductivity with respect to the control sample.     

Amyloid-Beta Induces Different Expression Pattern of Tissue Transglutaminase and Its Isoforms on Olfactory Ensheathing Cells: Modulatory Effect of Indicaxanthin

Herein, we assessed the effect of full native peptide of amyloid-beta (Aβ) (1-42) and its fragments (25-35 and 35-25) on tissue transglutaminase (TG2) and its isoforms (TG2-Long and TG2-Short) expression levels on olfactory ensheathing cells (OECs). Vimentin and glial fibrillary acid protein (GFAP) were also studied. The effect of the pre-treatment with indicaxanthin from Opuntia ficus-indica fruit on TG2 expression levels and its isoforms, cell viability, total reactive oxygen species (ROS), superoxide anion (O₂⁻), and apoptotic pathway activation was assessed. The levels of Nestin and cyclin D1 were also evaluated. Our findings highlight that OECs exposure to Aβ(1-42) and its fragments induced an increase in TG2 expression levels and a different expression pattern of its isoforms. Indicaxanthin pre-treatment reduced TG2 overexpression, modulating the expression of TG2 isoforms. It reduced total ROS and O₂⁻ production, GFAP and Vimentin levels, inhibiting apoptotic pathway activation. It also induced an increase in the Nestin and cyclin D1 expression levels. Our data demonstrated that indicaxanthin pre-treatment stimulated OECs self-renewal through the reparative activity played by TG2. They also suggest that Aβ might modify TG2 conformation in OECs and that indicaxanthin pre-treatment might modulate TG2 conformation, stimulating neural regeneration in Alzheimer’s disease.     

Exploring Molecular Contacts of MUC1 at CIN85 Binding Interface to Address Future Drug Design Efforts

The modulation of protein-protein interactions (PPIs) by small molecules represents a valuable strategy for pharmacological intervention in several human diseases. In this context, computer-aided drug discovery techniques offer useful resources to predict the network of interactions governing the recognition process between protein partners, thus furnishing relevant information for the design of novel PPI modulators. In this work, we focused our attention on the MUC1-CIN85 complex as a crucial PPI controlling cancer progression and metastasis. MUC1 is a transmembrane glycoprotein whose extracellular domain contains a variable number of tandem repeats (VNTRs) regions that are highly glycosylated in normal cells and under-glycosylated in cancer. The hypo-glycosylation fosters the exposure of the backbone to new interactions with other proteins, such as CIN85, that alter the intracellular signalling in tumour cells. Herein, different computational approaches were combined to investigate the molecular recognition pattern of MUC1-CIN85 PPI thus unveiling new structural information useful for the design of MUC1-CIN85 PPI inhibitors as potential anti-metastatic agents.     

Evolution of Local Structural Ordering and Chemical Distribution upon Delithiation of a Rock Salt–Structured Li1.3Ta0.3Mn0.4O2 Cathode

Lithium‐rich disordered rock‐salt oxides have attracted great interest owing to their promising performance as Li‐ion battery cathodes. While experimental and theoretical efforts are critical in advancing this class of materials, a fundamental understanding of key property changes upon Li extraction is largely missing. In the present study, single‐crystal synthesis of a new disordered rock‐salt cathode material, Li_1.3Ta_0.3Mn_0.4O₂ (LTMO), and its use as a model compound to investigate Li concentration–driven evolution of local cationic ordering, charge compensation, and chemical distribution are reported. Through the combined use of 2D and 3D X‐ray nanotomography, it is shown that Li removal accompanied by oxygen oxidation is correlated with the development of morphological defects such as particle cracking. Chemical heterogeneity, quantified by subparticle level distribution of Mn valence state, is minimal during Mn redox, which drastically increases upon the formation of cracks during oxygen redox. Density functional theory and bond valence sum mismatch calculations reveal the presence of local short‐range ordering in the pristine oxide, which gradually disappears along with the extraction of Li. The study suggests that with cycling the transformation into true cation–disordered state can be expected, which likely impacts the voltage profile and obtainable energy density of the oxide cathodes.     

Static fatigue of Hi-Nicalon™-S fiber at elevated temperature in air,steam, and silicic acid-saturated steam

A facility for testing SiC fiber tows in static fatigue and creep at elevated temperatures in air and steam was developed. Static fatigue of Hi-Nicalon™-S fibers was investigated at 800°C-1100°C at applied stresses between 115 and 1250 MPa in air, in Si(OH)₄(g)-saturated steam, and in unsaturated steam. Fibers tested in Si(OH)₄(g)-saturated steam and in air had silica scales throughout the test sections, but those tested in unsaturated steam did not develop scales near the steam injection point. Fiber lifetimes in static fatigue were shortest in unsaturated steam, intermediate in Si(OH)₄(g)-saturated steam, and longest in air. Failure strains did not exceed 0.3%. Steady-state strain rates and static fatigue lifetimes are modelled empirically by the Monkman-Grant relationship. Failure mechanisms are discussed.     

Determination of 3‐D Alumina Grain Orientation,Size, Shape,and Growth Kinetics from 2‐D Data in Nextel™ 610 Fibers

Nextel^? 610 alumina fibers were heat‐treated at 1100°C–1500°C for 1–100 h in air. Grain size distributions (GSDs) and grain orientation distributions (ODs) with respect to the fiber axis were characterized by analysis of TEM images from longitudinal fiber sections. The 2‐D GSDs and ODs were characterized as ellipses. 3‐D GSDs and ODs were calculated by fitting distributions of oriented oblate ellipsoids to 2‐D GSDs and ODs formed by ellipsoid–section‐plane intersections. The standard deviations (SDs) of log‐normal GSDs consistently increased with grain size, which is not diagnostic of normal grain growth. The grain aspect ratio (α) and the tendency of the short grain axis to orient perpendicular to the fiber axis also increased with grain size, resulting in more textured fibers at larger grain sizes. Average 3‐D grain sizes were larger than 2‐D sizes for GSDs with small SDs, but smaller for GSDs with large SDs because of under sampling of small grains. 3‐D grain growth kinetics had the same 815 kJ/mol activation energy as that found by 2‐D analysis, but the grain growth exponent m of 6.0 was larger and the pre‐exponential factor much smaller. Expressions for 3‐D log‐normal GSDs as a function of heat treatment temperature and time were determined. α‐distributions and ODs were determined as a function of grain size. Methods for determining 3‐D GSDs are discussed.     

Targeting SARS-CoV-2 RBD Interface: a Supervised Computational Data-Driven Approach to Identify Potential Modulators

Coronavirus disease 2019 (COVID-19) has spread out as a pandemic threat affecting over 2 million people. The infectious process initiates via binding of SARS-CoV-2 Spike (S) glycoprotein to host angiotensin-converting enzyme 2 (ACE2). The interaction is mediated by the receptor-binding domain (RBD) of S glycoprotein, promoting host receptor recognition and binding to ACE2 peptidase domain (PD), thus representing a promising target for therapeutic intervention. Herein, we present a computational study aimed at identifying small molecules potentially able to target RBD. Although targeting PPI remains a challenge in drug discovery, our investigation highlights that interaction between SARS-CoV-2 RBD and ACE2 PD might be prone to small molecule modulation, due to the hydrophilic nature of the bi-molecular recognition process and the presence of druggable hot spots. The fundamental objective is to identify, and provide to the international scientific community, hit molecules potentially suitable to enter the drug discovery process, preclinical validation and development.