Inhibition of Soluble Epoxide Hydrolase Ameliorates Phenotype and Cognitive Abilities in a Murine Model of Niemann Pick Type C Disease

Niemann–Pick type C (NPC) disease is a rare autosomal recessive inherited childhood neurodegenerative disease characterized by the accumulation of cholesterol and glycosphingolipids, involving the autophagy-lysosome system. Inhibition of soluble epoxide hydrolase (sEH), an enzyme that metabolizes epoxy fatty acids (EpFAs) to 12-diols, exerts beneficial effects in modulating inflammation and autophagy, critical features of the NPC disease. This study aims to evaluate the effects of UB-EV-52, an sEH inhibitor (sEHi), in an NPC mouse model (Npc) by administering it for 4 weeks (5 mg/kg/day). Behavioral and cognitive tests (open-field test (OF)), elevated plus maze (EPM), novel object recognition test (NORT) and object location test (OLT) demonstrated that the treatment produced an improvement in short- and long-term memory as well as in spatial memory. Furthermore, UB-EV-52 treatment increased body weight and lifespan by 25% and reduced gene expression of the inflammatory markers (i.e., Il-1β and Mcp1) and enhanced oxidative stress (OS) markers (iNOS and Hmox1) in the treated Npc mice group. As for autophagic markers, surprisingly, we found significantly reduced levels of LC3B-II/LC3B-I ratio and significantly reduced brain protein levels of lysosomal-associated membrane protein-1 (LAMP-1) in treated Npc mice group compared to untreated ones in hippocampal tissue. Lipid profile analysis showed a significant reduction of lipid storage in the liver and some slight changes in homogenated brain tissue in the treated NPC mice compared to the untreated groups. Therefore, our results suggest that pharmacological inhibition of sEH ameliorates most of the characteristic features of NPC mice, demonstrating that sEH can be considered a potential therapeutic target for this disease.     

The Bark Beetle Dendroctonus rhizophagus (Curculionidae: Scolytinae) Has Digestive Capacity to Degrade Complex Substrates: Functional Characterization and Heterologous Expression of an α-Amylase

Dendroctonus-bark beetles are natural agents contributing to vital processes in coniferous forests, such as regeneration, succession, and material recycling, as they colonize and kill damaged, stressed, or old pine trees. These beetles spend most of their life cycle under stem and roots bark where they breed, develop, and feed on phloem. This tissue is rich in essential nutrients and complex molecules such as starch, cellulose, hemicellulose, and lignin, which apparently are not available for these beetles. We evaluated the digestive capacity of Dendroctonus rhizophagus to hydrolyze starch. Our aim was to identify α-amylases and characterize them both molecularly and biochemically. The findings showed that D. rhizophagus has an α-amylase gene (AmyDr) with a single isoform, and ORF of 1452 bp encoding a 483-amino acid protein (53.15 kDa) with a predicted signal peptide of 16 amino acids. AmyDr has a mutation in the chlorine-binding site, present in other phytophagous insects and in a marine bacterium. Docking analysis showed that AmyDr presents a higher binding affinity to amylopectin compared to amylose, and an affinity binding equally stable to calcium, chlorine, and nitrate ions. AmyDr native protein showed amylolytic activity in the head-pronotum and gut, and its recombinant protein, a polypeptide of ~53 kDa, showed conformational stability, and its activity is maintained both in the presence and absence of chlorine and nitrate ions. The AmyDr gene showed a differential expression significantly higher in the gut than the head-pronotum, indicating that starch hydrolysis occurs mainly in the midgut. An overview of the AmyDr gene expression suggests that the amylolytic activity is regulated through the developmental stages of this bark beetle and associated with starch availability in the host tree.     

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.     

基于XGBoost算法的垃圾短信分层分级治理体系

为有效整治垃圾短信,不断提升不良信息治理的精准性,文章基于XGBoost算法构建了一套科学的分层分级垃圾短信治理体系。通过对用户入网、消费、通信行为等特征进行建模与运算,识别出用户发送垃圾短信的风险系数,并定义了六级用户。分级名单生成后,依托于垃圾短信拦截系统的分级策略管理功能,分别设置相匹配的拦截策略。在加大对中高危用户的识别和拦截力度的同时,有效降低了高价值用户因不良信息治理导致被误拦截的风险。该治理体系应用于辽宁移动管理实际以来,垃圾短信平均投诉量降幅34.82%。误关停投诉率稳定在0.1%以内。一至三级高价值客户群关停投诉量降幅27.43%。     

WavNet — Visual saliency detection using Discrete Wavelet Convolutional Neural Network

In the recent advancements in image and video analysis, the detection of salient regions in the image becomes the initial step. This plays a crucial role in deciding the performance of such algorithms. In this work, a Multi-Resolution Feature Extraction (MRFE) technique that makes use of Discrete Wavelet Convolutional Neural Network (DWCNN) for generating features is employed. An Enhanced Feature Extraction (EFE) module extracts additional features from the high level features of the DWCNN, which are used to frame both channel as well as spatial attention models for yielding contextual attention maps. A new hybrid loss function is also proposed, which is a combination of Balanced Cross Entropy (BCE) loss and Edge based Structural Similarity (ESSIM) loss that effectively identifies and segments the salient regions with clear boundaries. The method is tested exhaustively with five different benchmark datasets and is proved superior to the existing state-of-the-art methods with a minimum Mean Absolute error (MAE) of 0.03 and F-measure of 0.956.     

Experimental study and thermodynamic modeling of the Cu–Sn–Si–O system and sub-systems

Phase equilibria between slag, Cu–Sn alloy and solid oxide phases, SnO₂ (cassiterite) or SiO₂ (tridymite, cristobalite) are important for oxidizing fire refining of black copper produced during the recycling of copper scrap and waste electrical and electronic equipment. Integrated experimental and thermodynamic modeling study is presented for the Cu–Sn–Si–O chemical system and its sub-systems. Experimental technique involved high-temperature equilibration, followed by rapid quenching and direct measurement of Cu, Sn and Si concentrations in the liquid and solid phases using the electron probe X-ray microanalysis. Experimental results and literature data have been used to develop the thermodynamic database for the system. The database works within the environment of FactSage software, as well as ChemApp, ChemSheet and SimuSage. Combined with other assessments, it can be used to optimize and develop recycling processes using the black copper route.     

Ordinary Gasoline Emissions Induce a Toxic Response in Bronchial Cells Grown at Air-Liquid Interface

Gasoline engine emissions have been classified as possibly carcinogenic to humans and represent a significant health risk. In this study, we used MucilAir™, a three-dimensional (3D) model of the human airway, and BEAS-2B, cells originating from the human bronchial epithelium, grown at the air-liquid interface to assess the toxicity of ordinary gasoline exhaust produced by a direct injection spark ignition engine. The transepithelial electrical resistance (TEER), production of mucin, and lactate dehydrogenase (LDH) and adenylate kinase (AK) activities were analyzed after one day and five days of exposure. The induction of double-stranded DNA breaks was measured by the detection of histone H2AX phosphorylation. Next-generation sequencing was used to analyze the modulation of expression of the relevant 370 genes. The exposure to gasoline emissions affected the integrity, as well as LDH and AK leakage in the 3D model, particularly after longer exposure periods. Mucin production was mostly decreased with the exception of longer BEAS-2B treatment, for which a significant increase was detected. DNA damage was detected after five days of exposure in the 3D model, but not in BEAS-2B cells. The expression of CYP1A1 and GSTA3 was modulated in MucilAir™ tissues after 5 days of treatment. In BEAS-2B cells, the expression of 39 mRNAs was affected after short exposure, most of them were upregulated. The five days of exposure modulated the expression of 11 genes in this cell line. In conclusion, the ordinary gasoline emissions induced a toxic response in MucilAir™. In BEAS-2B cells, the biological response was less pronounced, mostly limited to gene expression changes.     

Neuroprotective and Anti-Inflammatory Effects of Evernic Acid in an MPTP-Induced Parkinson’s Disease Model

Oxidative stress, mitochondrial dysfunction, and neuroinflammation are strongly associated with the pathogenesis of Parkinson’s disease (PD), which suggests that anti-oxidative and anti-inflammatory compounds might provide an alternative treatment for PD. Here, we evaluated the neuroprotective effects of evernic aid (EA), which was screened from a lichen library provided by the Korean Lichen Research Institute at Sunchon National University. EA is a secondary metabolite generated by lichens, including Ramalina, Evernia, and Hypogymnia, and several studies have described its anticancer, antifungal, and antimicrobial effects. However, the neuroprotective effects of EA have not been studied. We found that EA protected primary cultured neurons against 1-methyl-4-phenylpyridium (MPP⁺)-induced cell death, mitochondrial dysfunction, and oxidative stress, and effectively reduced MPP⁺-induced astroglial activation by inhibiting the NF-κB pathway. In vivo, EA ameliorated MPTP-induced motor dysfunction, dopaminergic neuronal loss, and neuroinflammation in the nigrostriatal pathway in C57BL/6 mice. Taken together, our findings demonstrate that EA has neuroprotective and anti-inflammatory effects in PD models and suggest that EA is a potential therapeutic candidate for PD.     

纳米药物非临床药代动力学的研究策略及关注要点

随着纳米技术的迅速发展，纳米药物的研发已成为目前药物创新的发展方向之一。纳米药物具有基于纳米结构的尺度效应，其药代动力学特征与普通药物相比存在明显差异，其药代动力学研究与普通药物相比也有其特殊性。本文着重探讨纳米药物的非临床药代动力学的研究策略及关注要点，包括受试物、体内/外试验、生物样本分析、数据评价分析等，期望为研发者提供参考。