TL;DR: A novel and unique aircraft noise stress model with increased blood pressure and vascular dysfunction associated with oxidative stress is established, enabling future studies of molecular mechanisms, mitigation strategies, and pharmacological interventions to protect from noise-induced vascular damage.
Abstract: Aims Epidemiological studies indicate that traffic noise increases the incidence of coronary artery disease, hypertension and stroke. The underlying mechanisms remain largely unknown. Field studies with nighttime noise exposure demonstrate that aircraft noise leads to vascular dysfunction, which is markedly improved by vitamin C, suggesting a key role of oxidative stress in causing this phenomenon. Methods and results We developed a novel animal model to study the vascular consequences of aircraft noise exposure. Peak sound levels of 85 and mean sound level of 72 dBA applied by loudspeakers for 4 days caused an increase in systolic blood pressure, plasma noradrenaline and angiotensin II levels and induced endothelial dysfunction. Noise increased eNOS expression but reduced vascular NO levels because of eNOS uncoupling. Noise increased circulating levels of nitrotyrosine, interleukine-6 and vascular expression of the NADPH oxidase subunit Nox2, nitrotyrosine-positive proteins and of endothelin-1. FACS analysis demonstrated an increase in infiltrated natural killer-cells and neutrophils into the vasculature. Equal mean sound pressure levels of white noise for 4 days did not induce these changes. Comparative Illumina sequencing of transcriptomes of aortic tissues from aircraft noise-treated animals displayed significant changes of genes in part responsible for the regulation of vascular function, vascular remodelling, and cell death. Conclusion We established a novel and unique aircraft noise stress model with increased blood pressure and vascular dysfunction associated with oxidative stress. This animal model enables future studies of molecular mechanisms, mitigation strategies, and pharmacological interventions to protect from noise-induced vascular damage.
TL;DR: This work focuses on ROS at physiological levels and their central role in redox signalling via different post-translational modifications, denoted as ‘oxidative eustress’.
Abstract: 'Reactive oxygen species' (ROS) is an umbrella term for an array of derivatives of molecular oxygen that occur as a normal attribute of aerobic life. Elevated formation of the different ROS leads to molecular damage, denoted as 'oxidative distress'. Here we focus on ROS at physiological levels and their central role in redox signalling via different post-translational modifications, denoted as 'oxidative eustress'. Two species, hydrogen peroxide (H2O2) and the superoxide anion radical (O2·-), are key redox signalling agents generated under the control of growth factors and cytokines by more than 40 enzymes, prominently including NADPH oxidases and the mitochondrial electron transport chain. At the low physiological levels in the nanomolar range, H2O2 is the major agent signalling through specific protein targets, which engage in metabolic regulation and stress responses to support cellular adaptation to a changing environment and stress. In addition, several other reactive species are involved in redox signalling, for instance nitric oxide, hydrogen sulfide and oxidized lipids. Recent methodological advances permit the assessment of molecular interactions of specific ROS molecules with specific targets in redox signalling pathways. Accordingly, major advances have occurred in understanding the role of these oxidants in physiology and disease, including the nervous, cardiovascular and immune systems, skeletal muscle and metabolic regulation as well as ageing and cancer. In the past, unspecific elimination of ROS by use of low molecular mass antioxidant compounds was not successful in counteracting disease initiation and progression in clinical trials. However, controlling specific ROS-mediated signalling pathways by selective targeting offers a perspective for a future of more refined redox medicine. This includes enzymatic defence systems such as those controlled by the stress-response transcription factors NRF2 and nuclear factor-κB, the role of trace elements such as selenium, the use of redox drugs and the modulation of environmental factors collectively known as the exposome (for example, nutrition, lifestyle and irradiation).
TL;DR: The global concept of oxidative stress is defined as an imbalance between oxidants and antioxidants in favor of the oxidants, leading to a disruption of redox signaling and control and/or molecular damage as discussed by the authors.
Abstract: The global concept of oxidative stress is defined as “an imbalance between oxidants and antioxidants in favor of the oxidants, leading to a disruption of redox signaling and control and/or molecular damage” (see Sies and Jones11). In accordance with H. Selye's initial concept of stress, the term oxidative stress implies an adaptive oxidative stress response. Physiological (low-level) oxidative stress is used in redox signaling and redox regulation, termed oxidative eustress, whereas supraphysiological oxidative challenge leads to disrupted redox signaling and/or oxidative damage to biomolecules, oxidative distress. Much current research effort addresses the consequences in biology and medicine. Using newly developed methods, detailed information on spatiotemporal redox patterns and their regulation in specific settings is becoming accessible.
TL;DR: Noise has been found associated with annoyance, stress, sleep disturbance, and impaired cognitive performance, and epidemiological studies have found that environmental noise is associated with an increased incidence of arterial hypertension, myocardial infarction, heart failure, and stroke.
252 citations
Cites background from "Effects of noise on vascular functi..."
...Importantly, these changes were unique for aircraft noise and not observed in response to white noise exposure (applied in the form of a continuous swoosh) (24), suggesting that the characteristics of the noise stimulus (pattern, frequency, exposure time, and intensity) are important....
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...Nextgeneration sequencing analysis showed that aortic tissues from aircraft noise–treated animals displayed significant changes of genes partly responsible for the regulation of vascular function, vascular remodeling, and cell death (24)....
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...Thus, noise-induced endothelial dysfunction may partly explain the association between transportation noise and CVD found in various epidemiological studies (24,25)....
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...Our aim was to study the nonauditory effects of noise on the cardiovascular system, inflammation, and oxidative stress (24)....
TL;DR: Repeated and chronic social stress leads to glucocorticoid resistance, enhanced myelopoiesis, upregulated proinflammatory gene expression, and oxidative stress, but the causal role of these mechanisms in the development of loneliness-associated CVD remains unclear.
Abstract: Significance: Social and demographic changes have led to an increased prevalence of loneliness and social isolation in modern society. Recent Advances: Population-based studies have demonstrated that both objective social isolation and the perception of social isolation (loneliness) are correlated with a higher risk of mortality and that both are clearly risk factors for cardiovascular disease (CVD). Lonely individuals have increased peripheral vascular resistance and elevated blood pressure. Socially isolated animals develop more atherosclerosis than those housed in groups. Critical Issues: Molecular mechanisms responsible for the increased cardiovascular risk are poorly understood. In recent reports, loneliness and social stress were associated with activation of the hypothalamic–pituitary–adrenocortical axis and the sympathetic nervous system. Repeated and chronic social stress leads to glucocorticoid resistance, enhanced myelopoiesis, upregulated proinflammatory gene expression, and oxidative...
TL;DR: Sies et al. as discussed by the authors defined a global concept of Oxidative Stress as an imbalance between oxidants and antioxidants in favor of the oxidants, leading to a disruption of redox signaling and control and/or molecular damage.
TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Abstract: In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html
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TL;DR: G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested.
Abstract: G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of thet, F, and χ2 test families. In addition, it includes power analyses forz tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.
TL;DR: The Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure outperforms other aligners by a factor of >50 in mapping speed.
Abstract: Motivation Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
TL;DR: It is shown that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads, and estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired- end reads, depending on the number of possible splice forms for each gene.
Abstract: RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.