Chemical Composition of Cork from Quercus Variablis

Cork is a natural and renewable raw material harvested from the outer bark of oak (Quercus spp.) trees. Unique and valuable properties of cork include low density, low permeability, high elasticity, good heat and acoustic insulation properties, and resistance to chemical and microbial attack. Chemical composition of cork is affected by many factors including the Quercus species and the number of times that cork has been harvested from the tree (ie virgin vs reproduction cork). Differences in chemical composition can significantly influence cork properties. In this study, chemical composition of virgin and reproduction cork from Quercus variablis trees in Shaanxi Province, China, was investigated. Cork samples were sequentially extracted with dichloromethane, ethanol, and water in a Soxhlet extractor. Eluted fractions were analyzed using ion chromatography. Chemical composition of virgin Q. variablis cork was 34.3% suberin, 20.6% lignin, 17.4% extractives, and 15.2% polysaccharides. Composition of reproduction cork was 36.9% suberin, 19.9% lignin, 12.7% extractives, and 12.0% polysaccharides. These results show that composition of virgin and reproduction Q. variablis cork was similar. Virgin Q. variablis cork had greater extractives and polysaccharides content than reproduction cork but a little less suberin. Chemical composition of Q. variablis cork from China is significantly different from that of Quercus suber L. cork from Europe

Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction

Recent advances and achievements of artificial intelligence (AI) as well as deep and graph learning models have established their usefulness in biomedical applications, especially in drug-drug interactions (DDIs). DDIs refer to a change in the effect of one drug to the presence of another drug in the human body, which plays an essential role in drug discovery and clinical research. DDIs prediction through traditional clinical trials and experiments is an expensive and time-consuming process. To correctly apply the advanced AI and deep learning, the developer and user meet various challenges such as the availability and encoding of data resources, and the design of computational methods. This review summarizes chemical structure based, network based, NLP based and hybrid methods, providing an updated and accessible guide to the broad researchers and development community with different domain knowledge. We introduce widely-used molecular representation and describe the theoretical frameworks of graph neural network models for representing molecular structures. We present the advantages and disadvantages of deep and graph learning methods by performing comparative experiments. We discuss the potential technical challenges and highlight future directions of deep and graph learning models for accelerating DDIs prediction.Comment: Accepted by Briefings in Bioinformatic

Dynamic redox and nutrient cycling response to climate forcing in the Mesoproterozoic ocean

Controls on Mesoproterozoic ocean redox heterogeneity, and links to nutrient cycling and oxygenation feedbacks, remain poorly resolved. Here, we report ocean redox and phosphorus cycling across two high-resolution sections from the ~1.4 Ga Xiamaling Formation, North China Craton. In the lower section, fluctuations in trade wind intensity regulated the spatial extent of a ferruginous oxygen minimum zone, promoting phosphorus drawdown and persistent oligotrophic conditions. In the upper section, high but variable continental chemical weathering rates led to periodic fluctuations between highly and weakly euxinic conditions, promoting phosphorus recycling and persistent eutrophication. Biogeochemical modeling demonstrates how changes in geographical location relative to global atmospheric circulation cells could have driven these temporal changes in regional ocean biogeochemistry. Our approach suggests that much of the ocean redox heterogeneity apparent in the Mesoproterozoic record can be explained by climate forcing at individual locations, rather than specific events or step-changes in global oceanic redox conditions

Rare deleterious germline variants and risk of lung cancer

Recent studies suggest that rare variants exhibit stronger effect sizes and might play a crucial role in the etiology of lung cancers (LC). Whole exome plus targeted sequencing of germline DNA was performed on 1045 LC cases and 885 controls in the discovery set. To unveil the inherited causal variants, we focused on rare and predicted deleterious variants and small indels enriched in cases or controls. Promising candidates were further validated in a series of 26,803 LCs and 555,107 controls. During discovery, we identified 25 rare deleterious variants associated with LC susceptibility, including 13 reported in ClinVar. Of the five validated candidates, we discovered two pathogenic variants in known LC susceptibility loci, ATM p.V2716A (Odds Ratio [OR] 19.55, 95%CI 5.04–75.6) and MPZL2 p.I24M frameshift deletion (OR 3.88, 95%CI 1.71–8.8); and three in novel LC susceptibility genes, POMC c.*28delT at 3′ UTR (OR 4.33, 95%CI 2.03–9.24), STAU2 p.N364M frameshift deletion (OR 4.48, 95%CI 1.73–11.55), and MLNR p.Q334V frameshift deletion (OR 2.69, 95%CI 1.33–5.43). The potential cancer-promoting role of selected candidate genes and variants was further supported by endogenous DNA damage assays. Our analyses led to the identification of new rare deleterious variants with LC susceptibility. However, in-depth mechanistic studies are still needed to evaluate the pathogenic effects of these specific alleles

Characterization of an aspartate aminotransferase encoded by YPO0623 with frequent nonsense mutations in Yersinia pestis

Yersinia pestis, the causative agent of plague, is a genetically monomorphic bacterial pathogen that evolved from Yersinia pseudotuberculosis approximately 7,400 years ago. We observed unusually frequent mutations in Y. pestis YPO0623, mostly resulting in protein translation termination, which implies a strong natural selection. These mutations were found in all phylogenetic lineages of Y. pestis, and there was no apparent pattern in the spatial distribution of the mutant strains. Based on these findings, we aimed to investigate the biological function of YPO0623 and the reasons for its frequent mutation in Y. pestis. Our in vitro and in vivo assays revealed that the deletion of YPO0623 enhanced the growth of Y. pestis in nutrient-rich environments and led to increased tolerance to heat and cold shocks. With RNA-seq analysis, we also discovered that the deletion of YPO0623 resulted in the upregulation of genes associated with the type VI secretion system (T6SS) at 26°C, which probably plays a crucial role in the response of Y. pestis to environment fluctuations. Furthermore, bioinformatic analysis showed that YPO0623 has high homology with a PLP-dependent aspartate aminotransferase in Salmonella enterica, and the enzyme activity assays confirmed its aspartate aminotransferase activity. However, the enzyme activity of YPO0623 was significantly lower than that in other bacteria. These observations provide some insights into the underlying reasons for the high-frequency nonsense mutations in YPO0623, and further investigations are needed to determine the exact mechanism

Cell Membrane Is Impaired, Accompanied by Enhanced Type III Secretion System Expression in Yersinia pestis Deficient in RovA Regulator

BACKGROUND: In the enteropathogenic Yersinia species, RovA regulates the expression of invasin, which is important for enteropathogenic pathogenesis but is inactivated in Yersinia pestis. Investigation of the RovA regulon in Y. pestis at 26 °C has revealed that RovA is a global regulator that contributes to virulence in part by the direct regulation of psaEFABC. However, the regulatory roles of RovA in Y. pestis at 37 °C, which allows most virulence factors in mammalian hosts to be expressed, are still poorly understood. METHODOLOGY/PRINCIPAL FINDINGS: The transcriptional profile of an in-frame rovA mutant of Y. pestis biovar Microtus strain 201 was analyzed under type III secretion system (T3SS) induction conditions using microarray techniques, and it was revealed that many cell-envelope and transport/binding proteins were differentially expressed in the ΔrovA mutant. Most noticeably, many of the T3SS genes, including operons encoding the translocon, needle and Yop (Yersinia outer protein) effectors, were significantly up-regulated. Analysis of Yop proteins confirmed that YopE and YopJ were also expressed in greater amounts in the mutant. However, electrophoresis mobility shift assay results demonstrated that the His-RovA protein could not bind to the promoter sequences of the T3SS genes, suggesting that an indirect regulatory mechanism is involved. Transmission electron microscopy analysis indicated that there are small loose electron dense particle-like structures that surround the outer membrane of the mutant cells. The bacterial membrane permeability to CFSE (carboxyfluorescein diacetate succinimidyl ester) was significantly decreased in the ΔrovA mutant compared to the wild-type strain. Taken together, these results revealed the improper construction and dysfunction of the membrane in the ΔrovA mutant. CONCLUSIONS/SIGNIFICANCE: We demonstrated that the RovA regulator plays critical roles in the construction and functioning of the bacterial membrane, which sheds considerable light on the regulatory functions of RovA in antibiotic resistance and environmental adaptation. The expression of T3SS was upregulated in the ΔrovA mutant through an indirect regulatory mechanism, which is possibly related to the altered membrane construction in the mutant

Molecular Characterization of Transcriptional Regulation of rovA by PhoP and RovA in Yersinia pestis

BACKGROUND: Yersinia pestis is the causative agent of plague. The two transcriptional regulators, PhoP and RovA, are required for the virulence of Y. pestis through the regulation of various virulence-associated loci. They are the global regulators controlling two distinct large complexes of cellular pathways. METHODOLOGY/PRINCIPAL FINDINGS: Based on the LacZ fusion, primer extension, gel mobility shift, and DNase I footprinting assays, RovA is shown to recognize both of the two promoters of its gene in Y. pestis. The autoregulation of RovA appears to be a conserved mechanism shared by Y. pestis and its closely related progenitor, Y. pseudotuberculosis. In Y. pestis, the PhoP regulator responds to low magnesium signals and then negatively controls only one of the two promoters of rovA through PhoP-promoter DNA association. CONCLUSIONS/SIGNIFICANCE: RovA is a direct transcriptional activator for its own gene in Y. pestis, while PhoP recognizes the promoter region of rovA to repress its transcription. The direct regulatory association between PhoP and RovA bridges the PhoP and RovA regulons in Y. pestis

Quality assessment metric of stereo images considering cyclopean integration and visual saliency

This paper was accepted for publication in the journal Information Sciences and the definitive published version is available at http://dx.doi.org/10.1016/j.ins.2016.09.004.In recent years, there has been great progress in the wider use of three-dimensional (3D) technologies. With increasing sources of 3D content, a useful tool is needed to evaluate the perceived quality of the 3D videos/images. This paper puts forward a framework to evaluate the quality of stereoscopic images contaminated by possible symmetric or asymmetric distortions. Human visual system (HVS) studies reveal that binocular combination models and visual saliency are the two key factors for the stereoscopic image quality assessment (SIQA) metric. Therefore inspired by such findings in HVS, this paper proposes a novel saliency map in SIQA metric for the cyclopean image called “cyclopean saliency”, which avoids complex calculations and produces good results in detecting saliency regions. Moreover, experimental results show that our metric significantly outperforms conventional 2D quality metrics and yields higher correlations with human subjective judgment than the state-of-art SIQA metrics. 3D saliency performance is also compared with “cyclopean saliency” in SIQA. It is noticed that the proposed metric is applicable to both symmetric and asymmetric distortions. It can thus be concluded that the proposed SIQA metric can provide an effective evaluation tool to assess stereoscopic image quality

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer