Inhibition of the proteasome activity by graphene oxide contributes to its cytotoxicity.

Due to its hydrophobicity and other unique physicochemical properties, graphene oxide (GO) has been extensively utilized in various biological applications. However, introducing nanomaterials into the biological environment may raise serious risk in terms of nanotoxicity, leading to some unintended changes to the structure and the function of other biomolecules. This study investigates the interaction of GO with the ubiquitin-proteasome system, one of the essential machineries in the cellular metabolism, using a combination of experimental and computational approaches.

Multiscale Kinetic Modeling Reveals an Ensemble of Cl/H Exchange Pathways in ClC-ec1 Antiporter.

Despite several years of research, the ion exchange mechanisms in chloride/proton antiporters and many other coupled transporters are not yet understood at the molecular level. Here, we present a novel approach to kinetic modeling and apply it to ion exchange in ClC-ec1. Our multiscale kinetic model is developed by (1) calculating the state-to-state rate coefficients with reactive and polarizable molecular dynamics simulations, (2) optimizing these rates in a global kinetic network, and (3) predicting new electrophysiological results.

An Ultrastable Heterobimetallic Uranium(IV)/Vanadium(III) Solid Compound Protected by a Redox-Active Phosphite Ligand: Crystal Structure, Oxidative Dissolution, and First-Principles Simulation.

The first heterobimetallic uranium(IV)/vanadium(III) phosphite compound, NaUV(HPO) (denoted as UVP), was synthesized via an in situ redox-active hydrothermal reaction. It exhibits superior hydrolytic and antioxidant stability compared to the majority of structures containing low-valent uranium or vanadium, further elucidated by first-principles simulations, and therefore shows potential applications in nuclear waste management.

Differential Pd-nanocrystal facets demonstrate distinct antibacterial activity against Gram-positive and Gram-negative bacteria.

Noble metal-based nanomaterials have shown promise as potential enzyme mimetics, but the facet effect and underlying molecular mechanisms are largely unknown. Herein, with a combined experimental and theoretical approach, we unveil that palladium (Pd) nanocrystals exhibit facet-dependent oxidase and peroxidase-like activities that endow them with excellent antibacterial properties via generation of reactive oxygen species. The antibacterial efficiency of Pd nanocrystals against Gram-positive bacteria is consistent with the extent of their enzyme-like activity, that is {100}-faceted Pd cubes with higher activities kill bacteria more effectively than {111}-faceted Pd octahedrons.

Performance Budget Planning: The Case of a Research University.

We describe a performance budget planning model developed for a research university, comprised of a set of 88 key variables and 38 non-linear structural equations that describe interactions among them. These equations, based on the knowledge of research university's financial working and theoretical considerations, relate expenditures and revenues to teaching and research operations. We demonstrate the value of this model for developing insight into the financial structure of the university.

A flexible ontology for inference of emergent whole cell function from relationships between subcellular processes.

Whole cell responses arise from coordinated interactions between diverse human gene products functioning within various pathways underlying sub-cellular processes (SCP). Lower level SCPs interact to form higher level SCPs, often in a context specific manner to give rise to whole cell function. We sought to determine if capturing such relationships enables us to describe the emergence of whole cell functions from interacting SCPs.

Propensity of a single-walled carbon nanotube-peptide to mimic a KK10 peptide in an HLA-TCR complex.

The application of nanotechnology to improve disease diagnosis, treatment, monitoring, and prevention is the goal of nanomedicine. We report here a theoretical study of a functionalized single-walled carbon nanotube (CNT) mimic binding to a human leukocyte antigen-T cell receptor (HLA-TCR) immune complex as a first attempt of a potential nanomedicine for human immunodeficiency virus (HIV) vaccine development. The carbon nanotube was coated with three arginine residues to imitate the HIV type 1 immunodominant viral peptide KK10 (gag 263-272: KRWIILGLNK), named CNT-peptide hereafter.

Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy.

CD8 T cell-dependent killing of cancer cells requires efficient presentation of tumor antigens by human leukocyte antigen class I (HLA-I) molecules. However, the extent to which patient-specific HLA-I genotype influences response to anti-programmed cell death protein 1 or anti-cytotoxic T lymphocyte-associated protein 4 is currently unknown. We determined the HLA-I genotype of 1535 advanced cancer patients treated with immune checkpoint blockade (ICB).

Concentration-dependent binding of CdSe quantum dots on the SH3 domain.

Quantum dots (QDs) are being used increasingly in applications for solar panels, consumer electronics, and biomedical imaging. For biomedical applications, QDs are typically coated with a biocompatible molecule for the system of interest. Experiments have indicated a QD dose-dependent and surface coating-dependent toxicity, with a portion of the toxicity being ascribed to interference with biomolecules.

Application of Genome Wide Association and Genomic Prediction for Improvement of Cacao Productivity and Resistance to Black and Frosty Pod Diseases.

Chocolate is a highly valued and palatable confectionery product. Chocolate is primarily made from the processed seeds of the tree species . Cacao cultivation is highly relevant for small-holder farmers throughout the tropics, yet its productivity remains limited by low yields and widespread pathogens.

Chemical Welding on Semimetallic TiS Nanosheets for High-Performance Flexible n-Type Thermoelectric Films.

Solution-based processing of two-dimensional (2D) materials provides the possibility of allowing these materials to be incorporated into large-area thin films, which can translate the interesting fundamental properties of 2D materials into available devices. Here, we report for the first time a novel chemical-welding method to achieve high-performance flexible n-type thermoelectric films using 2D semimetallic TiS nanosheets. We employ chemically exfoliated TiS nanosheets bridged with multivalent cationic metal Al to cross-link the nearby sheets during the film deposition process.

A mesoporous cationic thorium-organic framework that rapidly traps anionic persistent organic pollutants.

Many environmental pollutants inherently exist in their anionic forms and are therefore highly mobile in natural water systems. Cationic framework materials that can capture those pollutants are highly desirable but scarcely reported. Here we present a mesoporous cationic thorium-based MOF (SCU-8) containing channels with a large inner diameter of 2.

Nanopatterned Bulk Metallic Glass Biosensors.

Nanopatterning as a surface area enhancement method has the potential to increase signal and sensitivity of biosensors. Platinum-based bulk metallic glass (Pt-BMG) is a biocompatible material with electrical properties conducive for biosensor electrode applications, which can be processed in air at comparably low temperatures to produce nonrandom topography at the nanoscale. Work presented here employs nanopatterned Pt-BMG electrodes functionalized with glucose oxidase enzyme to explore the impact of nonrandom and highly reproducible nanoscale surface area enhancement on glucose biosensor performance.

A new molecular mechanism underlying the EGCG-mediated autophagic modulation of AFP in HepG2 cells.

Epigallocatechingallate (EGCG) is a major bioactive component of green tea and is associated with health benefits against multiple diseases including cancer. As an indicator of hepatocellular carcinoma (HCC), high levels of α-fetal protein (AFP) are related to malignant differentiation and poor prognosis of cancer cells. In this study, EGCG can effectively reduce AFP secretion and simultaneously induce AFP aggregation in human HCC HepG cells.

Does Epileptiform Activity Represent a Failure of Neuromodulation to Control Central Pattern Generator-Like Neocortical Behavior?

Rhythmic motor patterns in invertebrates are often driven by specialized "central pattern generators" (CPGs), containing small numbers of neurons, which are likely to be "identifiable" in one individual compared with another. The dynamics of any particular CPG lies under the control of modulatory substances, amines, or peptides, entering the CPG from outside it, or released by internal constituent neurons; consequently, a particular CPG can generate a given rhythm at different frequencies and amplitudes, and perhaps even generate a repertoire of distinctive patterns. The mechanisms exploited by neuromodulators in this respect are manifold: Intrinsic conductances (e.

Hippocampal morphology mediates biased memories of chronic pain.

Experiences and memories are often mismatched. While multiple studies have investigated psychological underpinnings of recall error with respect to emotional events, the neurobiological mechanisms underlying the divergence between experiences and memories remain relatively unexplored in the domain of chronic pain. Here we examined the discrepancy between experienced chronic low back pain (CBP) intensity (twice daily ratings) and remembered pain intensity (n = 48 subjects) relative to psychometric properties, hippocampus morphology, memory capabilities, and personality traits related to reward.

Molecular mechanism of Gd@C(OH) increasing collagen expression: Implication for encaging tumor.

Gadolinium-containing fullerenol Gd@C(OH) has demonstrated low-toxicity and highly therapeutic efficacy in inhibiting tumor growth and metastasis through new strategy of encaging cancer, however, little is known about the mechanisms how this nanoparticle regulates fibroblast cells to prison (instead of poison) cancer cells. Here, we report that Gd@C(OH) promote the binding activity of tumor necrosis factor (TNFα) to tumor necrosis factor receptors 2 (TNFR2), activate TNFR2/p38 MAPK signaling pathway to increase cellular collagen expression in fibrosarcoma cells and human primary lung cancer associated fibroblasts isolated from patients. We also employ molecular dynamics simulations to study the atomic-scale mechanisms that dictate how Gd@C(OH) mediates interactions between TNFα and TNFRs.

Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices.

In a previous work we have detailed the requirements for obtaining maximal deep learning performance benefit by implementing fully connected deep neural networks (DNN) in the form of arrays of resistive devices. Here we extend the concept of Resistive Processing Unit (RPU) devices to convolutional neural networks (CNNs). We show how to map the convolutional layers to fully connected RPU arrays such that the parallelism of the hardware can be fully utilized in all three cycles of the backpropagation algorithm.

Rock climbing: A local-global algorithm to compute minimum energy and minimum free energy pathways.

The calculation of minimum energy or minimum free energy paths is an important step in the quantitative and qualitative studies of chemical and physical processes. The computations of these coordinates present a significant challenge and have attracted considerable theoretical and computational interest. Here we present a new local-global approach to study reaction coordinates, based on a gradual optimization of an action.

Phosphatidylserine-Induced Conformational Modulation of Immune Cell Exhaustion-Associated Receptor TIM3.

In the face of chronic cancers and protracted viral infections, human immune cells are known to adopt an exhausted state in which their effector functions are lost. In recent years, a number of inhibitory receptors have been connected to the immune cell exhaustion phenotype; furthermore, ligands capable of activating these receptors have been discovered. The molecular mechanisms by which these ligands affect the exhausted states of immune cells, however, are largely unknown.

Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.

We propose Segment Convolutional Neural Networks (Seg-CNNs) for classifying relations from clinical notes. Seg-CNNs use only word-embedding features without manual feature engineering. Unlike typical CNN models, relations between 2 concepts are identified by simultaneously learning separate representations for text segments in a sentence: preceding, concept1, middle, concept2, and succeeding.

A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.

We report the results of a DREAM challenge designed to predict relative genetic essentialities based on a novel dataset testing 98,000 shRNAs against 149 molecularly characterized cancer cell lines. We analyzed the results of over 3,000 submissions over a period of 4 months. We found that algorithms combining essentiality data across multiple genes demonstrated increased accuracy; gene expression was the most informative molecular data type; the identity of the gene being predicted was far more important than the modeling strategy; well-predicted genes and selected molecular features showed enrichment in functional categories; and frequently selected expression features correlated with survival in primary tumors.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear "mixed" selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors.

Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images.

Background: Computer vision may aid in melanoma detection.

Objective: We sought to compare melanoma diagnostic accuracy of computer algorithms to dermatologists using dermoscopic images.

Methods: We conducted a cross-sectional study using 100 randomly selected dermoscopic images (50 melanomas, 44 nevi, and 6 lentigines) from an international computer vision melanoma challenge dataset (n = 379), along with individual algorithm results from 25 teams.