Impact of SARS-CoV-2 infection during pregnancy on postnatal brain development: The potential role of glial cells

Glial cells are crucial for maintaining central nervous system (CNS) homeostasis. They actively participate in immune responses, as well as form functional barriers, such as blood-brain barrier (BBB), which restrict the entry of pathogens and inflammatory mediators into the CNS. In general, viral infections during the gestational period can alter the embryonic and fetal environment, and the related inflammatory response may affect neurodevelopment and lead to behavioral dysfunction during later stage of life, as highlighted by our group for Zika virus infection. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) induces a cytokine storm and, during pregnancy, may be related to a more severe form of the coronavirus disease-19 (COVID-19) and also to higher preterm birth rates. SARS-CoV-2 can also affect the CNS by inducing neurochemical remodeling in neural cells, which can compromise neuronal plasticity and synaptic function. However, the impact of SARS-CoV-2 infection during pregnancy on postnatal CNS, including brain development during childhood and adulthood, remains undetermined. Our group has recently highlighted the impact of COVID-19 on the expression of molecular markers associated with neuropsychiatric disorders, which are strongly related to the inflammatory response. Thus, based on these relationships, we discussed the impact of SARS-CoV-2 infection either during pregnancy or in critical periods of neurodevelopment as a risk factor for neurological consequences in the offspring later in life, focusing on the potential role of glial cells. Thus, it is important to consider future and long-term public health concerns associated with SARS-CoV-2 infection during pregnancy.     

Implant surface features as key role on cell behavior

It has been recognized that physical and chemical properties of biomaterial surfaces mediate the quality of extracellular matrix (ECM) that may affect cell behaviors. In nature, ECM is a heterogeneous three-dimensional superstructure formed by three major components, glycosaminoglycan, glycoconjugate, and protein, that anchors cellular compartments in tissues and regulates the function and the behavior of cells. Changes in the biointerface alter the quality of ECM and morphology through cell surface receptors, which, in turn, enable it to trigger specific cell signaling and different cellular responses. In fact, a number of strategies have been used to improve the functionality of surfaces and direct cell behavior through precisely designed environments. Herein, we aimed to discuss, through a science-based viewpoint, the biomaterial surface features on cell behavior and analyze the impact of cell physical modification on dental implant development.     

Influence of core stiffness on the behavior of tall timber buildings subjected to wind loads

This study analyzes the feasibility of the use of cross-laminated timber (CLT) as a load-bearing structural element in a 40-story building based on Chinese design requirements. The proposed design of the high-rise concrete–CLT building utilizes the core–outrigger system. Concrete is used for the central core and outriggers, and CLT is used for the rest of the structure of the building. Finite element models with different types of connections were developed using SAP2000 to analyze the lateral behavior of the building under wind action. The finite element models with rigid connections deduce the wind load distributions on individual structural elements, which determine the total number and the stiffness of fasteners of the CLT panels. Accordingly, spring links with equivalent stiffness that simulate the mechanical fasteners were employed in SAP2000. The results indicate that CLT increases the lateral flexibility of the building. A closed concrete core was substituted by two half cores to measure the requirement of the maximum lateral deflection. However, the acceleration at the building top still exceeded the limitation prescribed in Chinese Code JGJ 3–2010 owing to the lightweight of CLT and decreased stiffness of the hybrid building. To restrict this top acceleration within the limit, further approaches to increase the stiffness in the weak direction of the building are required. Methods such as the modification of the floor layout, increase in the thickness of walls, and addition of extra damping capacity should be considered and verified in the future.     

Facile synthesis of asymmetric patchy Janus Ag/Cu particles and study of their antifungal activity

Asymmetric patchy Ag/Cu Janus nanoparticles (NPs) were synthesized via a “seed-mediated” approach. This is the first report of synthesis of nanometer sized metal-based Janus NPs without using complicated methods. Selective adsorption of the surfactant onto the seed NPs leads to the formation of Janus type structure. Subsequently the reduction potential of Ag⁺/Ag⁰ and Cu²⁺/Cu⁰ systems directs the formation of the “patch”. The patchy Janus NPs show significant antifungal activity towards a potent rice pathogen thus offering the prospect of future application in crop protection.     

Extension and partial optimization of a modified Smith predictor and controller for unstable processes with time delay

Extension and partial parameter optimization are applied to a modified Smith predictor and controller, designed by de Paor( 1985) for a class of unstable processes having transfer functions of the form k₁A exp(—sT)/B, where A is a monic, Hurwitz polynomial of degree (n — l) and the nth degree monic polynomial B has a single right half-plane root at s=λ It is found that for l = 1,2,3 asymptotic stability can be achieved for λ T> 1, which more than doubles the best result obtained earlier. For a specific process, responses are compared with those obtained using the optimum stability PI controller of de Paor and O'Malley (1989). The advantages of the optimized, modified predictor in terms of tightness of control and faster settling time are highlighted     

APPLICATION OF A PERTURBATION THEORY FOR EVALUATION ALGORITHMS FOR IDENTIFICATION OF A CONTINUOUS PLANT FROM DISCRETE DATA

Abstract

A perturbation theory for evaluation algorithms of arithmetic expressions is applied to the generalized least-squares identification of the continuous parameters by using nonperiodic discrete data. The sampling instants are distributed in such a way that a sequence of the elemental arithmetic expressions of the identification algorithm are suboptimized according to bang-bang rules on the extrema of appropriate variation intervals. The weighting scalars in the generalized least-squares method are updated with the same purpose.