Metabolic Profiling of Resistant and Susceptible Tobaccos Response Incited by Ralstonia pseudosolanacearum Causing Bacterial Wilt

The causal agent of bacterial wilt, Ralstonia pseudosolanacearum, can cause significant economic losses during tobacco production. Metabolic analyses are a useful tool for the comprehensive identification of plant defense response metabolites. In this study, a gas chromatography-mass spectrometry (GC-MS) approach was used to identify metabolites differences in tobacco xylem sap in response to R. pseudosolanacearum CQPS-1 in two tobacco cultivars: Yunyan87 (susceptible to R. pseudosolanacearum) and K326 (quantitatively resistant). Metabolite profiling 7 days post inoculation with R. pseudosolanacearum identified 88 known compounds, 42 of them enriched and 6 depleted in the susceptible cultivar Yunyan87, while almost no changes occurred in quantitatively resistant cultivar K326. Putrescine was the most enriched compound (12-fold) in infected susceptible tobacco xylem, followed by methyl-alpha-d-glucopyranoside (9-fold) and arabinitol (6-fold). Other sugars, amino acids, and organic acids were also enriched upon infection. Collectively, these metabolites can promote R. pseudosolanacearum growth, as shown by the increased growth of bacterial cultures supplemented with xylem sap from infected tobacco plants. Comparison with previous metabolic data showed that beta-alanine, phenylalanine, and leucine were enriched during bacterial wilt in both tobacco and tomato xylem

Cell-Based Assays in High-Throughput Screening for Drug Discovery

Drug screening is a long and costly process confronted with low productivity and challenges in using animals, which limit the discovery of new drugs.  To improve drug screening efficacy and minimize animal testing, recent efforts have been dedicated to developing cell-based high throughput screening (HTS) platforms that can provide more relevant in vivo biological information than biochemical assays and thus reduce the number of animal tests and accelerate the drug discovery process. Today, cell-based assays are used in more than half of all high-throughput drug screenings for target validation and ADMET (absorption, distribution, metabolism, elimination and toxicity) in the early stage of drug discovery. In this review, we discuss the uses of different types of cells and cell culture systems, including 2D, 3D and perfusion cell cultures, in cell-based HTS for drug discovery. Optical and electrochemical methods for online, non-invasive detection and quantification of cells or cellular activities are discussed. Recent progresses and applications of 3D cultures and microfluidic systems for cell-based HTS are also discussed, followed with several successful examples of using cell-based HTS in commercial development of new drugs. Finally, a brief discussion on potential applications of cell-based HTS for screening phytochemicals and herbal medicines is provided in this review

Soluble oligomerization provides a beneficial fitness effect on destabilizing mutations

Mutations create the genetic diversity on which selective pressures can act, yet also create structural instability in proteins. How, then, is it possible for organisms to ameliorate mutation-induced perturbations of protein stability while maintaining biological fitness and gaining a selective advantage? Here we used a new technique of site-specific chromosomal mutagenesis to introduce a selected set of mostly destabilizing mutations into folA - an essential chromosomal gene of E. coli encoding dihydrofolate reductase (DHFR) - to determine how changes in protein stability, activity and abundance affect fitness. In total, 27 E.coli strains carrying mutant DHFR were created. We found no significant correlation between protein stability and its catalytic activity nor between catalytic activity and fitness in a limited range of variation of catalytic activity observed in mutants. The stability of these mutants is strongly correlated with their intracellular abundance; suggesting that protein homeostatic machinery plays an active role in maintaining intracellular concentrations of proteins. Fitness also shows a significant correlation with intracellular abundance of soluble DHFR in cells growing at 30oC. At 42oC, on the other hand, the picture was mixed, yet remarkable: a few strains carrying mutant DHFR proteins aggregated rendering them nonviable, but, intriguingly, the majority exhibited fitness higher than wild type. We found that mutational destabilization of DHFR proteins in E. coli is counterbalanced at 42oC by their soluble oligomerization, thereby restoring structural stability and protecting against aggregation

Electronic structure and possible pseudogap behavior in iron based superconductors

Starting from the simplified analytic model of electronic spectrum of iron - pnictogen (chalcogen) high - temperature superconductors close to the Fermi level, we discuss the influence of antiferromagneting (AFM)scattering both for stoichiometric case and the region of possible short - range order AFM fluctuations in doped compounds. Qualitative picture of the evolution of electronic spectrum and Fermi surfaces (FS) for different dopings is presented, with the aim of comparison with existing and future ARPES experiments. Both electron and hole dopings are considered and possible pseudogap behavior connected with partial FS "destruction" is demonstrated, explaining some recent experiments.Comment: 5 pages, 4 figures, published versio

Network Pruning Spaces

Network pruning techniques, including weight pruning and filter pruning, reveal that most state-of-the-art neural networks can be accelerated without a significant performance drop. This work focuses on filter pruning which enables accelerated inference with any off-the-shelf deep learning library and hardware. We propose the concept of \emph{network pruning spaces} that parametrize populations of subnetwork architectures. Based on this concept, we explore the structure aspect of subnetworks that result in minimal loss of accuracy in different pruning regimes and arrive at a series of observations by comparing subnetwork distributions. We conjecture through empirical studies that there exists an optimal FLOPs-to-parameter-bucket ratio related to the design of original network in a pruning regime. Statistically, the structure of a winning subnetwork guarantees an approximately optimal ratio in this regime. Upon our conjectures, we further refine the initial pruning space to reduce the cost of searching a good subnetwork architecture. Our experimental results on ImageNet show that the subnetwork we found is superior to those from the state-of-the-art pruning methods under comparable FLOPs