Anti-malarial drug artesunate restores metabolic changes in experimental allergic asthma

The anti-malarial drug artesunate possesses anti-inflammatory and anti-oxidative actions in experimental asthma, comparable to corticosteroid. We hypothesized that artesunate may modulate disease-relevant metabolic alterations in allergic asthma. To explore metabolic profile changes induced by artesunate in allergic airway inflammation, we analysed bronchoalveolar lavage fluid (BALF) and serum from naïve and ovalbumin-induced asthma mice treated with artesunate, using both gas and liquid chromatography-mass spectrometry metabolomics. Pharmacokinetics analyses of serum and lung tissues revealed that artesunate is rapidly converted into the active metabolite dihydroartemisinin. Artesunate effectively suppressed BALF total and differential counts, and repressed BALF Th2 cytokines, IL-17, IL-12(p40), MCP-1 and G-CSF levels. Artesunate had no effects on both BALF and serum metabolome in naïve mice. Artesunate promoted restoration of BALF sterols (cholesterol, cholic acid and cortol), phosphatidylcholines and carbohydrates (arabinose, mannose and galactose) and of serum 18-oxocortisol, galactose, glucose and glucouronic acid in asthma. Artesunate prevented OVA-induced increases in pro-inflammatory metabolites from arginine–proline metabolic pathway, particularly BALF levels of urea and alanine and serum levels of urea, proline, valine and homoserine. Multiple statistical correlation analyses revealed association between altered BALF and serum metabolites and inflammatory cytokines. Dexamethasone failed to reduce urea level and caused widespread changes in metabolites irrelevant to asthma development. Here we report the first metabolome profile of artesunate treatment in experimental asthma. Artesunate restored specific metabolic perturbations in airway inflammation, which correlated well with its anti-inflammatory actions. Our metabolomics findings further strengthen the therapeutic value of using artesunate to treat allergic asthma

Analysis of five deep-sequenced trio-genomes of the Peninsular Malaysia Orang Asli and North Borneo populations

BackgroundRecent advances in genomic technologies have facilitated genome-wide investigation of human genetic variations. However, most efforts have focused on the major populations, yet trio genomes of indigenous populations from Southeast Asia have been under-investigated.ResultsWe analyzed the whole-genome deep sequencing data (30x) of five native trios from Peninsular Malaysia and North Borneo, and characterized the genomic variants, including single nucleotide variants (SNVs), small insertions and deletions (indels) and copy number variants (CNVs). We discovered approximately 6.9 million SNVs, 1.2 million indels, and 9000 CNVs in the 15 samples, of which 2.7% SNVs, 2.3% indels and 22% CNVs were novel, implying the insufficient coverage of population diversity in existing databases. We identified a higher proportion of novel variants in the Orang Asli (OA) samples, i.e., the indigenous people from Peninsular Malaysia, than that of the North Bornean (NB) samples, likely due to more complex demographic history and long-time isolation of the OA groups. We used the pedigree information to identify de novo variants and estimated the autosomal mutation rates to be 0.81x10(-8) - 1.33x10(-8), 1.0x10(-9) - 2.9x10(-9), and 0.001 per site per generation for SNVs, indels, and CNVs, respectively. The trio-genomes also allowed for haplotype phasing with high accuracy, which serves as references to the future genomic studies of OA and NB populations. In addition, high-frequency inherited CNVs specific to OA or NB were identified. One example is a 50-kb duplication in DEFA1B detected only in the Negrito trios, implying plausible effects on host defense against the exposure of diverse microbial in tropical rainforest environment of these hunter-gatherers. The CNVs shared between OA and NB groups were much fewer than those specific to each group. Nevertheless, we identified a 142-kb duplication in AMY1A in all the 15 samples, and this gene is associated with the high-starch diet. Moreover, novel insertions shared with archaic hominids were identified in our samples.ConclusionOur study presents a full catalogue of the genome variants of the native Malaysian populations, which is a complement of the genome diversity in Southeast Asians. It implies specific population history of the native inhabitants, and demonstrated the necessity of more genome sequencing efforts on the multi-ethnic native groups of Malaysia and Southeast Asia

Label-free colorimetric aptasensor for highly sensitive and selective detection of proteins by using PNA/DNA hybrids and a cyanine dye

Economical, fast and sensitive detection of proteins is essential to biomedical research as well as clinical diagnosis. Here, we demonstrated a label-free colorimetric aptasensor that uses PNA/DNA hybrids and a cyanine dye (DiSC(2)(5)) for highly sensitive and selective detection of proteins in aqueous solution. This protocol, based on the difference in the binding interactions of DiSC(2)(5) with PNA and the PNA/DNA hybrid causing different colors, can be applied for the detection of proteins. This sensing platform can specifically detect thrombin, our example analyte, with a detection limit of 0.4 nM. Moreover, the assay does not involve any chemical modification and enzyme amplification, and hence it is convenient, fast and low-cost. In principle, this approach can be used to detect proteins with specific aptamers by simply changing the sequences of the probe DNA for specific targets. Furthermore, this sensing platform provides a promising approach for the analysis of target proteins at point-of-care in resource-limited settings

Peptide Nucleic Acid-Assisted Label-free Detection of Single-Nucleotide Polymorphisms Based on Light Scattering of Carbon Nanotubes

Peptide Nucleic Acid-Assisted Label-free Detection of Single-Nucleotide Polymorphisms Based on Light Scattering of Carbon Nanotube

Dynamic SFC placement scheme with parallelized SFCs and reuse of initialized VNFs: An A3C-based DRL approach

Mobile Edge Computing (MEC) is a well-known network architecture that extends cloud computing to the network edge. Compared with cloud computing, Network Function Virtualization (NFV) can provide flexible services in MEC for mobile users. Virtual Network Functions (VNFs) have emerged as software-based hardware middleboxes by NFV technology to host real-time applications. Basically, the combination of multiple VNF instances is defined as a Service Function Chain (SFC), which can provide dynamic service requirements in the MEC. Despite the rapid growth of MEC and the widespread support of service providers for SFC, many issues are still challenging and need to be addressed. In MEC scenarios with limited resources, the effective placement of SFCs with the aim of resource efficiency remains a challenging problem. Motivated by the scalability shortcomings of existing schemes to solve dynamic placement of SFCs, we propose Deep Reinforcement Learning (DRL)-based approaches to solve this problem, i.e., Asynchronous Advantage Actor-Critic (A3C). The proposed scheme is based on the reuse of initialized VNFs to improve the Quality of Service (QoS), which is developed with the aim of maximizing the long-term cumulative reward. In addition, a parallel processing approach of SFCs is included in the proposed scheme, which can split the traffic in each flow into sub-flows. This shares the processing load by instantiating duplicate instances of each VNF type in the SFC. The simulation results guarantee the efficiency of the proposed scheme and improves the average performance between 6% and 24% compared to the state-of-the-art clustering methods

Morphology and performance of poly(ether sulfone)/sulfonated poly(ether ether ketone) blend porous membranes for vanadium flow battery application

Poly(ether sulfone) (PES) porous membranes with tunable morphology were fabricated via a phase inversion method and applied in vanadium flow batteries (VFBs). The morphology of the PES membrane was adjusted by changing the polymer concentration and blending with hydrophilic sulfonated poly(ether ether ketone) (SPEEK) in the cast solution. The relationship between the membrane morphology and the performance in VFBs was investigated in detail. The results indicated that with increasing polymer concentration of the cast solution, the number of macrovoids gradually decreased and the finger-like pores became larger. A higher coulombic efficiency (CE) can be obtained due to the lower vanadium permeability, while the voltage efficiency (VE) decreased. In addition, the introduction of SPEEK in cast solution will induce the transformation of membrane structures from finger-like to spongy-like pores. The CE decreased with the higher vanadium permeability, while the VE increased due to the increased proton conductivity. As a result, optimized VFB performance of the PES membranes was obtained, showing a CE of 92.8% and an energy efficiency (EE) of 78.4%. The battery assembled with the prepared membranes showed a stable battery performance after running for more than 200 cycles, showing good oxidation stability. This work presents an effective and facile method to fabricate PES membranes with tunable battery performance