Astragaloside IV alleviates atherosclerosis through targeting circ_0000231/miR-135a-5p/CLIC4 axis in AS cell model in vitro

Molecular and Cellular Biochemistry - Non-coding RNAs (ncRNAs) have shown to act as crucial mediators in atherosclerosis (AS) development. The purpose of our study was to explore the role of...     

PARP1 rs1136410 C/C genotype associated with an increased risk of esophageal cancer in smokers

Molecular Biology Reports - DNA repair system plays a crucial role in maintaining genomic integrity and stability and in protecting against cancer. Poly(ADP-ribose) polymerase 1 (PARP1) functions...     

Platycodin D Inhibits β-Amyloid-Induced Inflammation and Oxidative Stress in BV-2 Cells Via Suppressing TLR4/NF-κB Signaling Pathway and Activating Nrf2/HO-1 Signaling Pathway

Neurochemical Research - Alzheimer’s disease (AD) is a common neurodegenerative disease associated with deposition of β-amyloid peptide (Aβ). Platycodin D (PLD), a...     

家蚕5龄幼虫精巢和卵巢microRNA芯片及转录组比较分析

【目的】本研究旨在通过对家蚕Bombyx mori 5龄幼虫精巢和卵巢组织微小RNA (microRNA, miRNA)基因芯片及转录组进行分析,找到参与家蚕性腺发育相关的miRNA分子及可能的靶基因。【方法】采用新一代高通量测序平台对家蚕5龄幼虫精巢和卵巢(分别定义为Test和Control)进行miRNA基因芯片检测及转录组测序分析,根据P＜0.05且log₂(fold change, FC)≥2的标准,通过比较筛选出Test vs Control的差异表达miRNA;根据q≤0.05且|log₂(fold change)|≥1的标准,通过比较筛选出Test vs Control的差异表达基因 (differentially expressed genes, DEGs);随机选取8个上调和12个下调差异表达miRNA,对其表达及其预测的5个靶基因进行qRT-PCR验证;对DEGs以及差异表达miRNA的靶基因进行KEGG通路富集分析。【结果】从精巢和卵巢样本中(Test vs Control)分别鉴定出68个差异表达miRNA和3 991个DEGs,其中上调和下调miRNA分别为36和32个,上调和下调DEGs分别为2 033和1 958个。差异表达miRNA的qRT PCR验证结果均与芯片数据一致。KEGG通路富集分析结果显示DEGs在新陈代谢及核糖体的信号通路显著富集。对差异表达miRNA在DEGs中的可能靶基因进行预测,结果找到了4组表达趋势相反的miRNA与靶基因：分别是bmo-miR-2774a与LOC101745556;bmo-miR-92b与LOC101735954以及bmo-miR-3266与LOC733130和LOC778467;1组表达趋势一致的miRNA与靶基因：bmo-miR-3321与LOC101744895。5个靶基因的qRT-PCR验证结果与转录组测序结果一致。【结论】本研究获得了家蚕5龄幼虫精巢和卵巢转录组及miRNA芯片数据,筛选并验证了4组差异表达和1组一致表达miRNA及潜在靶基因,为探究家蚕精巢和卵巢发育差异奠定了基础。     

Ultra‐Conserved Elements and morphology reciprocally illuminate conflicting phylogenetic hypotheses in Chalcididae (Hymenoptera,Chalcidoidea)

Recent technical advances combined with novel computational approaches have promised the acceleration of our understanding of the tree of life. However, when it comes to hyperdiverse and poorly known groups of invertebrates, studies are still scarce. As published phylogenies will be rarely challenged by future taxonomists, careful attention must be paid to potential analytical bias. We present the first molecular phylogenetic hypothesis for the family Chalcididae, a group of parasitoid wasps, with a representative sampling (144 ingroups and seven outgroups) that covers all described subfamilies and tribes, and 82% of the known genera. Analyses of 538 Ultra‐Conserved Elements (UCEs) with supermatrix (RAx ML and IQTREE) and gene tree reconciliation approaches (ASTRAL, ASTRID) resulted in highly supported topologies in overall agreement with morphology but reveal conflicting topologies for some of the deepest nodes. To resolve these conflicts, we explored the phylogenetic tree space with clustering and gene genealogy interrogation methods, analyzed marker and taxon properties that could bias inferences and performed a thorough morphological analysis (130 characters encoded for 40 taxa representative of the diversity). This joint analysis reveals that UCEs enable attainment of resolution between ancestry and convergent/divergent evolution when morphology is not informative enough, but also shows that a systematic exploration of bias with different analytical methods and a careful analysis of morphological features is required to prevent publication of artifactual results. We highlight a GC content bias for maximum‐likelihood approaches, an artifactual mid‐point rooting of the ASTRAL tree and a deleterious effect of high percentage of missing data (>85% missing UCEs) on gene tree reconciliation methods. Based on the results we propose a new classification of the family into eight subfamilies and ten tribes that lay the foundation for future studies on the evolutionary history of Chalcididae.     

Application of plant metabarcoding to identify diverse honeybee pollen forage along an urban–agricultural gradient

Understanding animal foraging ecology requires large sample sizes spanning broad environmental and temporal gradients. For pollinators, this has been hampered by the laborious nature of morphologically identifying pollen. Identifying pollen from urban environments is particularly difficult due to the presence of diverse ornamental species associated with consumer horticulture. Metagenetic pollen analysis represents a potential solution to this issue. Building upon prior laboratory and bioinformatic methods, we applied quantitative multilocus metabarcoding to characterize the foraging ecology of honeybee colonies situated in urban, suburban, mixed suburban–agricultural and rural agricultural sites in central Ohio, USA. In cross‐validating a subset of our metabarcoding results using microscopic palynology, we find strong concordance between the molecular and microscopic methods. Our results suggest that forage from the agricultural site exhibited decreased taxonomic diversity and temporal turnover relative to the urban and suburban sites, though the generalization of this observation will require replication across additional sites and cities. Our work demonstrates the power of honeybees as environmental samplers of floral community composition at large spatial scales, aiding in the distinction of taxa characteristically associated with urban or agricultural land use from those distributed ubiquitously across the sampled landscapes. Observed patterns of high forage diversity and compositional turnover in our more urban sites are likely reflective of the fine‐grain heterogeneity and high beta diversity of urban floral landscapes at the scale of honeybee foraging. This provides guidance for future studies investigating how relationships between urbanization and measures of pollinator health are mediated by variation in floral resource dynamics across landscapes.     

The Bio3D packages for structural bioinformatics

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D‐eddm package supports both experimental and theoretical simulation‐generated structures, is integrated with other methods for dissecting sequence‐structure–function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/ .