We combine experiment and computer simulation to show how macromolecular crowding dramatically affects the structure, function, and folding landscape of phosphoglycerate kinase (PGK). Fluorescence labeling shows that compact states of yeast PGK are populated as the amount of crowding agents (Ficoll 70) increases. Coarse-grained molecular simulations reveal three compact ensembles: C (crystal structure), CC (collapsed crystal), and Sph (spherical compact). With an adjustment for viscosity, crowded wild-type PGK and fluorescent PGK are about 15 times or more active in 200 mg/ml Ficoll than in aqueous solution. Our results suggest a previously undescribed solution to the classic problem of how the ADP and diphosphoglycerate binding sites of PGK come together to make ATP: Rather than undergoing a hinge motion, the ADP and substrate sites are already located in proximity under crowded conditions that mimic the in vivo conditions under which the enzyme actually operates. We also examine T-jump unfolding of PGK as a function of crowding experimentally. We uncover a nonmonotonic folding relaxation time vs. Ficoll concentration. Theory and modeling explain why an optimum concentration exists for fastest folding. Below the optimum, folding slows down because the unfolded state is stabilized relative to the transition state. Above the optimum, folding slows down because of increased viscosity.

Memristors are one of the emerging technologies that can potentially replace state-of-the-art integrated electronic devices for advanced computing and digital and analog circuit applications including neuromorphic networks. Over the past few years, research and development mostly focused on revolutionizing the metal oxide materials, which are used as core components of the popular metal-insulator-metal memristors owing to their highly recognized resistive switching behavior. This paper outlines the recent advancements and characteristics of such memristive devices, with a special focus on (i) their established resistive switching mechanisms and (ii) the key challenges associated with their fabrication processes including the impeding criteria of material adaptation for the electrode, capping, and insulator component layers. Potential applications and an outlook into future development of metal oxide memristive devices are also outlined.

The spatial organization of eukaryotic genomes is thought to play an important role in regulating gene expression. The recent advances in experimental methods including chromatin capture techniques, as well as the large amounts of accumulated gene expression data allow studying the relationship between spatial organization of the genome and co-expression of protein-coding genes. To analyse this genome-wide relationship at a single gene resolution, we combined the interchromosomal DNA contacts in the yeast genome measured by Duan et al. with a comprehensive collection of 1,496 gene expression datasets. We find significant enhancement of co-expression among genes with contact links. The co-expression is most prominent when two gene loci fall within 1,000 base pairs from the observed contact. We also demonstrate an enrichment of inter-chromosomal links between functionally related genes, which suggests that the non random nature of the genome organization serves to facilitate coordinated transcription in groups of genes.

In this paper, we explore various aspects of memristor modeling and use them to propose improved access operations and design of a memristor-based memory. We study the current mathematical and SPICE modeling of memristors and compare them with known device specifications. Based on this survey of existing models, we adopt an improved mathematical model of the memristor that captures the well-established features of memristive devices. This modeling is used to analyze the time and voltage characteristics of stable read and write operations. The tradeoffs between the various design parameters such as voltage, frequency, noise margin, and area are also analyzed. Based on the device modeling, we propose a hybrid CMOS-memristor memory cell and architecture that addresses the limitations of memristor such as state drift, cell-cell interference, and refresh requirements. Memristor is used as a state element, and CMOS-based transistors are used to isolate, control, decode, and inter operate the logic. We verify our design using SPICE simulation using a 28-nm model for CMOS and a modified memristor model.

This paper is concerned with fitting the mean-square displacement (MSD) function, and extract reliable and accurate values for the diffusion coefficient $\mathcal{D}$ . In this work, we present a new optimal and robust nonlinear regression model capable of fitting the MSD function with different regimes corresponding to different time scales. The algorithm presented here achieves two major goals; a more accurate estimation of $\mathcal{D}$ as well as extracting information about the short time behavior. The algorithm fits the MSD to a continuous piece-wise function and predicts all the coefficients in the model including the breakpoints. The novelty of this approach lies in its ability to find the breakpoints which separate different modes of motion. We tested our algorithm using numerical experiments, and our fits described the data remarkably well. In addition, we applied our algorithm to extract $\mathcal{D}$ for water based on Molecular Dynamics (MD) simulations. The results of our fits are in good agreement with the experimentally reported values.