Beta-1,3 Oligoglucans Specifically Bind to Immune Receptor CD28 and May Enhance T Cell Activation

Beta glucans are known to have immunomodulatory effects that mediated by a variety of mechanisms. In this article, we describe experiments and simulations suggesting that beta-1,3 glucans may promote activation of T cells by a previously unknown mechanism. First, we find that treatment of a T lymphoblast cell line with beta-1,3 oligoglucan significantly increases mRNA levels of T cell activation-associated cytokines, especially in the presence of the agonistic anti-CD3 antibody. This immunostimulatory activity was observed in the absence of dectin-1, a known receptor for beta-1,3 glucans. To clarify the molecular mechanism underlying this activity, we performed a series of molecular dynamics simulations and free-energy calculations to explore the interaction of beta-1,3 oligoglucans with potential immune receptors. While the simulations reveal little association between beta-1,3 oligoglucan and the immune receptor CD3, we find that beta-1,3 oligoglucans bind to CD28 near the region identified as the binding site for its natural ligands CD80 and CD86. Using a rigorous absolute binding free-energy technique, we calculate a dissociation constant in the low millimolar range for binding of 8-mer beta-1,3 oligoglucan to this site on CD28. The simulations show this binding to be specific, as no such association is computed for alpha-1,4 oligoglucan. This study suggests that beta-1,3 glucans bind to CD28 and may stimulate T cell activation collaboratively with T cell receptor activation, thereby stimulating immune function.     

Constraint hierarchies

Constraints allow programmers and users to state declaratively a relation that should be maintained, rather than requiring them to write procedures to maintain the relation themselves. They are thus useful in such applications as programming languages, user interface toolkits, and simulation packages. In many situations, it is desirable to be able to state bothrequired andpreferential constraints. The required constraints must hold. Since the other constraints are merely preferences, the system should try to satisfy them if possible, but no error condition arises if it cannot. Aconstraint hierarchy consists of a set of constraints, each labeled as either required or preferred at some strength. An arbitrary number of different strengths is allowed. In the discussion of a theory of constraint hierarchies, we present alternate ways of selecting among competing possible solutions, and prove a number of propositions about the relations among these alternatives. We then outline algorithms for satisfying constraint hierarchies, and ways in which we have used constraint hierarchies in a number of programming languages and systems.     

A spectral space partition guided ensemble method for retrieving chlorophyll-a concentration in inland waters from Sentinel-2A satellite imagery

This research proposes an ensemble method for synergistically combining multiple empirical algorithms to better estimate chlorophyll-a (Chl-a) concentration. In previous studies, different empirical algorithms have been employed separately and a single algorithm was often identified as the most suitable predictor for Chl-a retrieval. Our ensemble method combines different individual algorithms to form an ensemble predictor that exploits advantages of each individual algorithm to maximize the overall estimation accuracy. We evaluated two ensemble predictors: the optimally weighted ensemble predictor and the spectral space partition guided ensemble predictor. The ensemble method has been successfully applied to a Sentinel-2A multispectral image acquired over Harsha Lake, Ohio in 2016. Based on in situ water reference data and satellite imagery, we constructed two ensemble predictors that consist of three individual empirical algorithms/estimators, including 2BDA (two-band algorithm), 3BDA (three-band algorithm), and NDCI (Normalized Difference Chlorophyll Index). For the optimally weighted ensemble predictor, the weights for individual algorithms are computed by solving an overdetermined linear system with the pseudoinverse technique. For the spectral space partition guided ensemble predictor, the rules for partitioning spectral space into spectral regions were established as a decision-tree using the CART method. The optimal Chl-a estimate for a pixel is obtained by selectively using the empirical algorithm in the ensemble that has the highest expected accuracy in the spectral region where the pixel is located. Our assessments suggest that the spectral space partition guided ensemble method performs significantly better than three individual empirical algorithms and also better than the optimally weighted ensemble method.     

High-Aspect-Ratio Nanostructured Surfaces as Biological Metamaterials

Materials patterned with high-aspect-ratio nanostructures have features on similar length scales to cellular components. These surfaces are an extreme topography on the cellular level and have become useful tools for perturbing and sensing the cellular environment. Motivation comes from the ability of high-aspect-ratio nanostructures to deliver cargoes into cells and tissues, access the intracellular environment, and control cell behavior. These structures directly perturb cells' ability to sense and respond to external forces, influencing cell fate, and enabling new mechanistic studies. Through careful design of their nanoscale structure, these systems act as biological metamaterials, eliciting unusual biological responses. While predominantly used to interface eukaryotic cells, there is growing interest in nonanimal and prokaryotic cell interfacing. Both experimental and theoretical studies have attempted to develop a mechanistic understanding for the observed behaviors, predominantly focusing on the cell–nanostructure interface. This review considers how high-aspect-ratio nanostructured surfaces are used to both stimulate and sense biological systems.     

Unfolding the Unfolded Protein Response: Unique Insights into Brain Ischemia

The endoplasmic reticulum (ER) is responsible for processing of proteins that are destined to be secreted, enclosed in a vesicle, or incorporated in the plasma membrane. Nascent peptides that enter the ER undergo a series of highly regulated processing steps to reach maturation as they transit the ER. Alterations in the intracellular environment that induce ER stress are thought to interrupt these processing steps, and result in unfolding of proteins in the ER. Accumulation of unfolded proteins concurrently activates three transmembrane stress sensors, IRE1, ATF6 and PERK, and is referred to as the Unfolded Protein Response (UPR). Our understanding of the mechanisms of UPR induction has been assembled primarily from experiments inducing ER stress with chemical and genetic manipulations. However, physiological stress often induces activation of ER stress sensors in a distinct manner from the canonical UPR. The unique activation profiles in vivo have prompted us to examine the mechanism of UPR activation in neurons following cerebral ischemia.     

Multifunctional temperature-responsive polymers as advanced biomaterials and beyond

The versatility and applicability of thermoresponsive polymeric systems have led to great interest and a multitude of publications. Of particular significance, multifunctional poly(N-isopropylacrylamide) (PNIPAAm) systems based on PNIPAAm copolymerized with various functional comonomers or based on PNIPAAm combined with nanomaterials exhibiting unique properties. These multifunctional PNIPAAm systems have revolutionized several biomedical fields such as controlled drug delivery, tissue engineering, self-healing materials, and beyond (e.g., environmental treatment applications). Here, we review these multifunctional PNIPAAm-based systems with various cofunctionalities, as well as highlight their unique applications. For instance, addition of hydrophilic or hydrophobic comonomers can allow for polymer lower critical solution temperature modification, which is especially helpful for physiological applications. Natural comonomers with desirable functionalities have also drawn significant attention as pressure surmounts to develop greener, more sustainable materials. Typically, these systems also tend to be more biocompatible and biodegradable and can be advantageous for use in biopharmaceutical and environmental applications. PNIPAAm-based polymeric nanocomposites are reviewed as well, where incorporation of inorganic or carbon nanomaterials creates synergistic systems that tend to be more robust and widely applicable than the individual components. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48770.     

Core and Corona Modifications for the Design of Polymeric Micelle Drug-Delivery Systems

Polymeric nanoparticle micelles are formed from amphiphilic polymers with a hydrophobic core and a hydrophilic corona. Often comprised of a biodegradable, biocompatible polymer core and a poly(ethylene glycol) corona, these nanoparticle micelles encapsulate a hydrophobic drug and enable surface modification with targeting ligands. Strategies to enhance hydrophobic drug encapsulation are described as chemistries that facilitate covalent modification with antibodies using water-based click chemistry.     

Recent Progress in Photocatalysis Mediated by Colloidal II-VI Nanocrystals

The use of photoexcited electrons and holes in semiconductor nanocrystals as reduction and oxidation reagents is an intriguing way of harvesting photon energy to drive chemical reactions. This review focuses on recent research efforts to understand and control the photocatalytic processes mediated by colloidal II-VI nanocrystalline materials, such as cadmium and zinc chalcogenides. First, we highlight how nanocrystal properties govern the rates and efficiencies of charge-transfer processes relevant to photocatalysis. We then describe the use of nanocrystal catalyst heterostructures for fuel-forming reactions, most commonly H₂ generation. Finally, we review the use of nanocrystal photocatalysis as a synthetic tool for metal–semiconductor nano-heterostructures.