Bioinspired synthesis as a potential green method for the preparation of nanomaterials: Opportunities and challenges

Inorganic nanomaterials are widely used in e.g. healthcare, electronics and energy sectors (worth several billion $), but their manufacturing is highly wasteful and hence unsustainable. This review highlights the key reasons that make these manufacturing routes unsustainable. We present alternatives, with special emphasis on bottom-up techniques. Biological and bioinspired routes feature as emerging solutions that can be sustainable yet with the ability to produce high-value nanomaterials. Finally, the review identifies future challenges in developing these routes such that they become commercially attractive manufacturing methods

Designing bioinspired green nanosilicas using statistical and machine learning approaches

The in vitro bioinspired synthesis of silica, inspired from in vivo biosilicification, is a sustainable alternative to the conventional production of high value porous silicas. The short reaction time, mild reaction conditions of room temperature and its use of benign precursors make this an eco-friendly, economical and scalable route with great industrial potential. However, a systematic optimisation of critical process parameters and material attributes of bioinspired silica is lacking. Specifically, statistical approaches such as design of experiments (DoE) and global sensitivity analysis (GSA) using machine learning could be highly effective but have not been applied to this “green” nanomaterial yet. Herein, for the first time, a sequential DoE strategy was developed with pre-screening experiments to outline the feasible design space. A successive screening using 23 full factorial design determined that from the initially investigated three factors (the ratio of the reactant concentrations, pH, and precursor concentration), only the first two were statistically significant for silica yield and surface area. The subsequent concatenated optimisation using central composite design located a maximum yield of 90 mol% and a maximum surface area of 300–400 m2 g−1. Since for successful commercialisation, high yields and large specific surface areas are desirable, their simultaneous optimisation was also achieved with high predictability regression models. For complementation, a variance-based GSA was successfully applied to bioinspired silica for the first time. This method rapidly identified key parameters and interactions that control the physicochemical properties and provided insights in the wide parameter space, which was validated by the extensive DoE campaign. This work is the starting point in holistically modelling the multidimensional factor–response relationship over a large experimental space in order to complement efforts for resource-efficient product and process development and optimisation of bioinspired silica and beyond

Cryo-EM structure of the complete and ligand-saturated insulin receptor ectodomain

Glucose homeostasis and growth essentially depend on the hormone insulin engaging its receptor. Despite biochemical and structural advances, a fundamental contradiction has persisted in the current understanding of insulin ligand-receptor interactions. While biochemistry predicts two distinct insulin binding sites, 1 and 2, recent structural analyses have resolved only site 1. Using a combined approach of cryo-EM and atomistic molecular dynamics simulation, we present the structure of the entire dimeric insulin receptor ectodomain saturated with four insulin molecules. Complementing the previously described insulin-site 1 interaction, we present the first view of insulin bound to the discrete insulin receptor site 2. Insulin binding stabilizes the receptor ectodomain in a T-shaped conformation wherein the membrane-proximal domains converge and contact each other. These findings expand the current models of insulin binding to its receptor and of its regulation. In summary, we provide the structural basis for a comprehensive description of ligand-receptor interactions that ultimately will inform new approaches to structure-based drug design.Peer reviewe

A Pilot Case-Control Study Investigating the Role of Epigenetics in Pediatric Acute Respiratory Distress Syndrome

Acute Respiratory Distress Syndrome (ARDS) is a highly lethal affliction of pulmonary edema and hypoxia commonly associated with trauma, sepsis, and shock. The prevalence and lethality of ARDS in children has motivated continued translational study aimed at further elucidating its pathophysiology. DNA methylation has emerged as a dynamic, epigenetic regulator of gene expression. Previous work has suggested the role of differential DNA methylation as a critical regulator of ARDS pathophysiology in adults; however, this has not yet been investigated in pediatric patients. Here, we report the results of a prospective pilot case-control study investigating potential epigenetic differences underlying pediatric ARDS (PARDS). In addition to investigating disease- and severity-associated differences in DNA methylation in critically ill children, we also assessed epigenetic age acceleration (EAA) and telomere length as biomarkers of cumulative cell stress and proliferative history. Although there were no disease-associated differentially methylated regions (DMRs) observed in whole blood or tracheal aspirate samples, we report six potential DMRs associated with PARDS illness severity. Additionally, we report that samples collected from critically ill children have undergone significant epigenetic age acceleration relative to samples collected from healthy children, and that this difference is not observed when comparing EAA between critically ill and healthy adults. Finally, we report that absolute telomere length (aTL) is significantly shorter in cells found in the tracheal aspirate of children with PARDS—potentially indicative of increased cellular proliferation or exposure to reactive oxygen species

From Catastrophe to Mastery: The Relationship Between Internal Control and Distress During Economic Threat

Every year, many young people navigate through a precarious job market, leading to substantial psychological distress. Across two preregistered experiments, the current program of research examines the curvilinear relationship between perceptions of internal control and distress when people find themselves in an uncertain job market, as well as the psychological mechanism (i.e., self-blame) by which this effect may occur. In Study 1, perceived control over ones life more generally and perceived internal control over ones job prospects did not buffer against lower distress when ones job prospects were threatened, nor were the relationships curvilinear in nature. In Study 2, results indicated that perceived internal control over ones job prospects did not cause distress during economic threat. Furthermore, no evidence was found to suggest that those with high levels of perceived internal control were more likely to engage in self-blame. The theoretical and practical implications of the proposed research are discussed