SARS-CoV-2 infection: a possible trigger for the recurrence of IgA nephropathy after kidney transplantation?

Immunoglobulin A nephropathy, the most common primary glomerulonephritis worldwide, is a leading cause of chronic kidney disease and end-stage kidney failure. Several cases of immunoglobulin A nephropathy relapse in native kidneys have been described after COVID-19 vaccination or SARS-CoV-2 infection. Here, we report the case of a 52-year-old kidney transplant recipient who had a stable transplant function for more than 14 years, with a glomerular filtration rate above 30 ml/min/1.

MORG1-A Negative Modulator of Renal Lipid Metabolism in Murine Diabetes.

Renal fatty acid (FA) metabolism is severely altered in type 1 and 2 diabetes mellitus (T1DM and T2DM). Increasing evidence suggests that altered lipid metabolism is linked to tubulointerstitial fibrosis (TIF). Our previous work has demonstrated that mice with reduced MORG1 expression, a scaffold protein in HIF and ERK signaling, are protected against TIF in the db/db mouse model.

General-Purpose Coarse-Grained Toughened Thermoset Model for 44DDS/DGEBA/PES.

The objective of this work is to predict the morphology and material properties of crosslinking polymers used in aerospace applications. We extend the open-source dybond plugin for HOOMD-Blue to implement a new coarse-grained model of reacting epoxy thermosets and use the 44DDS/DGEBA/PES system as a case study for calibration and validation. We parameterize the coarse-grained model from atomistic solubility data, calibrate reaction dynamics against experiments, and check for size-dependent artifacts.

Tying Together Multiscale Calculations for Charge Transport in P3HT: Structural Descriptors, Morphology, and Tie-Chains.

Evaluating new, promising organic molecules to make next-generation organic optoelectronic devices necessitates the evaluation of charge carrier transport performance through the semi-conducting medium. In this work, we utilize quantum chemical calculations (QCC) and kinetic Monte Carlo (KMC) simulations to predict the zero-field hole mobilities of ∼100 morphologies of the benchmark polymer poly(3-hexylthiophene), with varying simulation volume, structural order, and chain-length polydispersity. Morphologies with monodisperse chains were generated previously using an optimized molecular dynamics force-field and represent a spectrum of nanostructured order.

Optimization and Validation of Efficient Models for Predicting Polythiophene Self-Assembly.

We develop an optimized force-field for poly(3-hexylthiophene) (P3HT) and demonstrate its utility for predicting thermodynamic self-assembly. In particular, we consider short oligomer chains, model electrostatics and solvent implicitly, and coarsely model solvent evaporation. We quantify the performance of our model to determine what the optimal system sizes are for exploring self-assembly at combinations of state variables.

Enhanced Computational Sampling of Perylene and Perylothiophene Packing with Rigid-Body Models.

Molecular simulations have the potential to advance the understanding of how the structure of organic materials can be engineered through the choice of chemical components but are limited by computational costs. The computational costs can be significantly lowered through the use of modeling approximations that capture the relevant features of a system, while lowering algorithmic complexity or by decreasing the degrees of freedom that must be integrated. Such methods include coarse-graining techniques, approximating long-range electrostatics with short-range potentials, and the use of rigid bodies to replace flexible bonded constraints between atoms.

Digital colloids: reconfigurable clusters as high information density elements.

Through the design and manipulation of discrete, nanoscale systems capable of encoding massive amounts of information, the basic components of computation are open to reinvention. These components will enable tagging, memory storage, and sensing in unusual environments - elementary functions crucial for soft robotics and "wet computing". Here we show how reconfigurable clusters made of N colloidal particles bound flexibly to a central colloidal sphere have the capacity to store an amount of information that increases as O(N ln(N)).

Self-assembled clusters of spheres related to spherical codes.

We consider the thermodynamically driven self-assembly of spheres onto the surface of a central sphere. This assembly process forms self-limiting, or terminal, anisotropic clusters (N-clusters) with well-defined structures. We use Brownian dynamics to model the assembly of N-clusters varying in size from two to twelve outer spheres and free energy calculations to predict the expected cluster sizes and shapes as a function of temperature and inner particle diameter.

Thermal and athermal three-dimensional swarms of self-propelled particles.

Swarms of self-propelled particles exhibit complex behavior that can arise from simple models, with large changes in swarm behavior resulting from small changes in model parameters. We investigate the steady-state swarms formed by self-propelled Morse particles in three dimensions using molecular dynamics simulations optimized for graphics processing units. We find a variety of swarms of different overall shape assemble spontaneously and that for certain Morse potential parameters at most two competing structures are observed.

Calculation of partition functions for the self-assembly of patchy particles.

Partition functions encode all the thermodynamics of a system, but for most systems of practical importance, they cannot be calculated exactly. In this work we present a new hierarchical method for calculating partition functions to arbitrary precision. We discuss the algorithmic details of our implementation, including elements of shape-matching and entropy calculation for on-lattice and off-lattice systems.

Self-assembly and reconfigurability of shape-shifting particles.

Reconfigurability of two-dimensional colloidal crystal structures assembled by anisometric particles capable of changing their shape were studied by molecular dynamics computer simulation. We show that when particles change shape on cue, the assembled structures reconfigure into different ordered structures, structures with improved order, or more densely packed disordered structures, on faster time scales than can be achieved via self-assembly from an initially disordered arrangement. These results suggest that reconfigurable building blocks can be used to assemble reconfigurable materials, as well as to assemble structures not possible otherwise, and that shape shifting could be a promising mechanism to engineer assembly pathways to ordered and disordered structures.