A Facile Strategy for In Situ Core-Template-Functionalizing Siliceous Hollow Nanospheres for Guest Species Entrapment

The shell wall-functionalized siliceous hollow nanospheres (SHNs) with functional molecules represent an important class of nanocarriers for a rich range of potential applications. Herein, a self-templated approach has been developed for the synthesis of in situ functionalized SHNs, in which the biocompatible long-chain polycarboxylates (i.e., polyacrylate, polyaspartate, gelatin) provide the framework for silica precursor deposition by simply controlling chain conformation with divalent metal ions (i.e., Ca2+, Sr2+), without the intervention of any external templates. Metal ions play crucial roles in the formation of organic vesicle templates by modulating the long chains of polymers and preventing them from separation by washing process. We also show that, by in situ functionalizing the shell wall of SHNs, it is capable of entrapping nearly an eightfold quantity of vitamin Bc in comparison to the bare bulk silica nanospheres. These results confirm the feasibility of guest species entrapment in the functionalized shell wall, and SHNs are effective carriers of guest (bio-)molecules potentially for a variety of biomedical applications. By rationally choosing the functional (self-templating) molecules, this concept may represent a general strategy for the production of functionalized silica hollow structures

Integrating Phosphorylation Network with Transcriptional Network Reveals Novel Functional Relationships

Phosphorylation and transcriptional regulation events are critical for cells to transmit and respond to signals. In spite of its importance, systems-level strategies that couple these two networks have yet to be presented. Here we introduce a novel approach that integrates the physical and functional aspects of phosphorylation network together with the transcription network in S.cerevisiae, and demonstrate that different network motifs are involved in these networks, which should be considered in interpreting and integrating large scale datasets. Based on this understanding, we introduce a HeRS score (hetero-regulatory similarity score) to systematically characterize the functional relevance of kinase/phosphatase involvement with transcription factor, and present an algorithm that predicts hetero-regulatory modules. When extended to signaling network, this approach confirmed the structure and cross talk of MAPK pathways, inferred a novel functional transcription factor Sok2 in high osmolarity glycerol pathway, and explained the mechanism of reduced mating efficiency upon Fus3 deletion. This strategy is applicable to other organisms as large-scale datasets become available, providing a means to identify the functional relationships between kinases/phosphatases and transcription factors

Mapping Protein Interactions between Dengue Virus and Its Human and Insect Hosts

Dengue virus (DENV) represents a major disease burden in tropical and subtropical regions of the world, and has shown an increase in the number of cases in recent years. DENV is transmitted to humans through the bite of an infected mosquito, typically Aedes aegypti, after which it begins the infection and replication lifecycle within human cells. To perform the molecular functions required for invasion, replication, and spread of the virus, proteins encoded by DENV must interact with and alter the behavior of protein networks in both of these hosts. In this work, we used a computational method based on protein structures to predict interactions between DENV and its human and insect hosts. We predict numerous interactions, with many involved in known cell death, stress, and immune system pathways. Further investigation of these predicted protein-protein interactions should provide targets to combat the clinical manifestations of this disease in humans as well as points of intervention focused within the mosquito vector

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Incremental Motion Reshaping of Autonomous Dynamical Systems

This paper presents an approach to incrementally learn a reshaping term that modifies the trajectories of an autonomous dynamical system without affecting its stability properties. The reshaping term is considered as an additive control input and it is incrementally learned from human demonstrations using Gaussian process regression. We propose a novel parametrization of this control input that preserves the time-independence and the stability of the reshaped system, as analytically proved in the performed Lyapunov stability analysis. The effectiveness of the proposed approach is demonstrated with simulations and experiments on a real robot