Aberrant Expression Profiles of lncRNAs and Their Associated Nearby Coding Genes in the Hippocampus of the SAMP8 Mouse Model with AD

The senescence-accelerated mouse prone 8 (SAMP8) mouse model is a useful model for investigating the fundamental mechanisms involved in the age-related learning and memory deficits of Alzheimer's disease (AD), while the SAM/resistant 1 (SAMR1) mouse model shows normal features. Recent evidence has shown that long non-coding RNAs (lncRNAs) may play an important role in AD pathogenesis. However, a comprehensive and systematic understanding of the function of AD-related lncRNAs and their associated nearby coding genes in AD is still lacking. In this study, we collected the hippocampus, the main area of AD pathological processes, of SAMP8 and SAMR1 animals and performed microarray analysis to identify aberrantly expressed lncRNAs and their associated nearby coding genes, which may contribute to AD pathogenesis. We identified 3,112 differentially expressed lncRNAs and 3,191 differentially expressed mRNAs in SAMP8 mice compared to SAMR1 mice. More than 70% of the deregulated lncRNAs were intergenic and exon sense-overlapping lncRNAs. Gene Ontology (GO) and pathway analyses of the AD-related transcripts were also performed and are described in detail, which imply that metabolic process reprograming was likely related to AD. Furthermore, six lncRNAs and six mRNAs were selected for further validation of the microarray results using quantitative PCR, and the results were consistent with the findings from the microarray. Moreover, we analyzed 780 lincRNAs (also called long "intergenic" non-coding RNAs) and their associated nearby coding genes. Among these lincRNAs, AK158400 had the most genes nearby (n = 13), all of which belonged to the histone cluster 1 family, suggesting regulation of the nucleosome structure of the chromosomal fiber by affecting nearby genes during AD progression. In addition, we also identified 97 aberrant antisense lncRNAs and their associated coding genes. It is likely that these dysregulated lncRNAs and their associated nearby coding genes play a role in the development and/or progression of AD

Thermal alteration of biomarkers in the presence of elemental sulfur and sulfur-bearing minerals during hydrous and anhydrous pyrolysis

Although elemental sulfur and sulfur-bearing minerals are not the main constituents of sedimentary rock, they are still important for the formation and destruction of biomarkers. In this study, a bitumen of Sichuan Basin mudstone with abundant biomarkers was separately pyrolyzed (under both hydrous and anhydrous conditions) with elemental sulfur (S degrees) and sulfur-bearing minerals (including pyrite, ferrous sulfate, and ferric sulfate) at various temperatures (300, 330 and 350 degrees C). The results show that the effects of different forms of sulfur on the evolution of biomarkers vary. Pyrite (FeS2) had only a slight influence on the characteristics of the biomarkers during anhydrous and hydrous pyrolysis. On the other hand, the presence of S, ferrous sulfate (FeSO4) and ferric sulfate (Fe-2(SO4)(3)) promoted the thermal cracking of the biomarkers and changed the biomarker distributions under anhydrous conditions. The extent of biomarker thermal alterations decreased in the following order: S degrees > Fe-2(SO4)(3) > FeSO4 > FeS2. Additionally, the presence of water seemed to promote the effects of the sulfur additive on the changes in biomarker compositions, but this did not change their raking in terms of influence. The elemental sulfur alteration of the biomarkers increased with pyrolysis temperature (simulated maturity) and the abundance of elemental sulfur in the sample. The results obtained offer new insights into how biomarkers evolve when elemental sulfur and sulfur-bearing minerals are present. (C) 2018 Elsevier Ltd. All rights reserved

A Novel Angular-Guided Particle Swarm Optimizer for Many-Objective Optimization Problems

Most multiobjective particle swarm optimizers (MOPSOs) often face the challenges of keeping diversity and achieving convergence on tackling many-objective optimization problems (MaOPs), as they usually use the nondominated sorting method or decomposition-based method to select the local or best particles, which is not so effective in high-dimensional objective space. To better solve MaOPs, this paper presents a novel angular-guided particle swarm optimizer (called AGPSO). A novel velocity update strategy is designed in AGPSO, which aims to enhance the search intensity around the particles selected based on their angular distances. Using an external archive, the local best particles are selected from the surrounding particles with the best convergence, while the global best particles are chosen from the top 20% particles with the better convergence among the entire particle swarm. Moreover, an angular-guided archive update strategy is proposed in AGPSO, which maintains a consistent population with balanceable convergence and diversity. To evaluate the performance of AGPSO, the WFG and MaF test suites with 5 to 10 objectives are adopted. The experimental results indicate that AGPSO shows the superior performance over four current MOPSOs (SMPSO, dMOPSO, NMPSO, and MaPSO) and four competitive evolutionary algorithms (VaEA, θ-DEA, MOEA\D-DD, and SPEA2-SDE), when solving most of the test problems used

Aberrant Expression Profiles of lncRNAs and Their Associated Nearby Coding Genes in the Hippocampus of the SAMP8 Mouse Model with AD

The senescence-accelerated mouse prone 8 (SAMP8) mouse model is a useful model for investigating the fundamental mechanisms involved in the age-related learning and memory deficits of Alzheimer's disease (AD), while the SAM/resistant 1 (SAMR1) mouse model shows normal features. Recent evidence has shown that long non-coding RNAs (lncRNAs) may play an important role in AD pathogenesis. However, a comprehensive and systematic understanding of the function of AD-related lncRNAs and their associated nearby coding genes in AD is still lacking. In this study, we collected the hippocampus, the main area of AD pathological processes, of SAMP8 and SAMR1 animals and performed microarray analysis to identify aberrantly expressed lncRNAs and their associated nearby coding genes, which may contribute to AD pathogenesis. We identified 3,112 differentially expressed lncRNAs and 3,191 differentially expressed mRNAs in SAMP8 mice compared to SAMR1 mice. More than 70% of the deregulated lncRNAs were intergenic and exon sense-overlapping lncRNAs. Gene Ontology (GO) and pathway analyses of the AD-related transcripts were also performed and are described in detail, which imply that metabolic process reprograming was likely related to AD. Furthermore, six lncRNAs and six mRNAs were selected for further validation of the microarray results using quantitative PCR, and the results were consistent with the findings from the microarray. Moreover, we analyzed 780 lincRNAs (also called long "intergenic" non-coding RNAs) and their associated nearby coding genes. Among these lincRNAs, AK158400 had the most genes nearby (n = 13), all of which belonged to the histone cluster 1 family, suggesting regulation of the nucleosome structure of the chromosomal fiber by affecting nearby genes during AD progression. In addition, we also identified 97 aberrant antisense lncRNAs and their associated coding genes. It is likely that these dysregulated lncRNAs and their associated nearby coding genes play a role in the development and/or progression of AD

Effects of Pleistocene sea-level fluctuations on mangrove population dynamics: a lesson from Sonneratia alba

Abstract Background A large-scale systematical investigation of the influence of Pleistocene climate oscillation on mangrove population dynamics could enrich our knowledge about the evolutionary history during times of historical climate change, which in turn may provide important information for their conservation. Results In this study, phylogeography of a mangrove tree Sonneratia alba was studied by sequencing three chloroplast fragments and seven nuclear genes. A low level of genetic diversity at the population level was detected across its range, especially at the range margins, which was mainly attributed to the steep sea-level drop and associated climate fluctuations during the Pleistocene glacial periods. Extremely small effective population size (Ne) was inferred in populations from both eastern and western Malay Peninsula (44 and 396, respectively), mirroring the fragility of mangrove plants and their paucity of robustness against future climate perturbations and human activity. Two major genetic lineages of high divergence were identified in the two mangrove biodiversity centres: the Indo-Malesia and Australasia regions. The estimated splitting time between these two lineages was 3.153 million year ago (MYA), suggesting a role for pre-Pleistocene events in shaping the major diversity patterns of mangrove species. Within the Indo-Malesia region, a subdivision was implicated between the South China Sea (SCS) and the remaining area with a divergence time of 1.874 MYA, corresponding to glacial vicariance when the emerged Sunda Shelf halted genetic exchange between the western and eastern coasts of the Malay Peninsula during Pleistocene sea-level drops. Notably, genetic admixture was observed in populations at the boundary regions, especially in the two populations near the Malacca Strait, indicating secondary contact between divergent lineages during interglacial periods. These interregional genetic exchanges provided ample opportunity for the re-use of standing genetic variation, which could facilitate mangrove establishment and adaptation in new habitats, especially in the context of global climate changes. Conclusion Phylogeogrpahic analysis in this study reveal that Pleistocene sea-level fluctuations had profound influence on population differentiation of the mangrove tree S. alba . Our study highlights the fragility of mangrove plants and offers a guide for the conservation of coastal mangrove communities experiencing ongoing changes in sea-level

Network Proximity-based computational pipeline identifies drug candidates for different pathological stages of Alzheimer's disease

Despite the massive investment in Alzheimer’s disease (AD), there are still no disease-modifying treatments (DMTs) for AD. One major reason is attributed to the limitation of clinical ''one‐size‐fits‐all” approach, since the same AD treatment solely based on clinical diagnosis was unlikely to achieve good clinical efficacy. In recent years, computational approaches based on multiomics data have provided an unprecedented opportunity for drug discovery since they can substantially lower the costs and boost the efficiency. In this study, we intended to identify potential drug candidates for different pathological stages of AD by computationally repurposing Food and Drug Administration (FDA) approved drugs. First, we assembled gene expression data from three different AD pathological stages, which include mild cognitive impairment (MCI) and early and late stages of AD (EAD, LAD). We next quantified the network distances between drug target networks and AD modules by utilizing a network proximity approach, and identified 193 candidates that possessed significant associations with AD. After searching for previous literature evidence, 63 out of 193 (32.6%) predicted drugs were demonstrated to exert therapeutic effects on AD. We further explored the novel mechanism of action (MOA) for these drug candidates by determining the specific brain cells they might function on based on AD patient single cell transcriptomic data. Additionally, we selected several promising candidates that could cross the blood brain barrier together with confirmed neuroprotective effects, and subsequently determined the antioxidative activity of these compounds. Experimental results showed that azathioprine decreased the reactive oxygen species (ROS) and malondialdehyde (MDA) levels and improved the superoxide dismutase (SOD) activity in APP-SH-SY5Y cells. Finally, we deciphered the potential MOA of azathioprine against AD via network analysis and validated several apoptosis-related proteins (Caspase 3, Cleaved Caspase 3, Bax, Bcl2) through western blotting. In summary, this study presented an effective computational strategy utilizing omics data for AD drug repurposing, which provides a new perspective for drug discovery and development