Interleukin-1 regulates multiple atherogenic mechanisms in response to fat feeding

Background: Atherosclerosis is an inflammatory process that develops in individuals with known risk factors that include hypertension and hyperlipidaemia, influenced by diet. However, the interplay between diet, inflammatory mechanisms and vascular risk factors requires further research. We hypothesised that interleukin-1 (IL-1) signaling in the vessel wall would raise arterial blood pressure and promote atheroma. Methodology/Principal Findings: Apoe(-/-) and Apoe(-/-)/IL-1R1(-/-) mice were fed high fat diets for 8 weeks, and their blood pressure and atherosclerosis development measured. Apoe(-/-)/IL-R1(-/-) mice had a reduced blood pressure and significantly less atheroma than Apoe(-/-) mice. Selective loss of IL-1 signaling in the vessel wall by bone marrow transplantation also reduced plaque burden (p<0.05). This was associated with an IL-1 mediated loss of endothelium-dependent relaxation and an increase in vessel wall Nox 4. Inhibition of IL-1 restored endothelium-dependent vasodilatation and reduced levels of arterial oxidative stress. Conclusions/Significance: The IL-1 cytokine system links atherogenic environmental stimuli with arterial inflammation, oxidative stress, increased blood pressure and atherosclerosis. This is the first demonstration that inhibition of a single cytokine can block the rise in blood pressure in response to an environmental stimulus. IL-1 inhibition may have profound beneficial effects on atherogenesis in man

Experimental Quantum Hamiltonian Learning

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of foundational physics. Machine-learning enhanced by quantum simulators has been proposed as a route to improve the computational cost of performing these studies. Here we interface two different quantum systems through a classical channel - a silicon-photonics quantum simulator and an electron spin in a diamond nitrogen-vacancy centre - and use the former to learn the latter's Hamiltonian via Bayesian inference. We learn the salient Hamiltonian parameter with an uncertainty of approximately $10^{-5}$. Furthermore, an observed saturation in the learning algorithm suggests deficiencies in the underlying Hamiltonian model, which we exploit to further improve the model itself. We go on to implement an interactive version of the protocol and experimentally show its ability to characterise the operation of the quantum photonic device. This work demonstrates powerful new quantum-enhanced techniques for investigating foundational physical models and characterising quantum technologies

Asteroseismology and Interferometry

Asteroseismology provides us with a unique opportunity to improve our understanding of stellar structure and evolution. Recent developments, including the first systematic studies of solar-like pulsators, have boosted the impact of this field of research within Astrophysics and have led to a significant increase in the size of the research community. In the present paper we start by reviewing the basic observational and theoretical properties of classical and solar-like pulsators and present results from some of the most recent and outstanding studies of these stars. We centre our review on those classes of pulsators for which interferometric studies are expected to provide a significant input. We discuss current limitations to asteroseismic studies, including difficulties in mode identification and in the accurate determination of global parameters of pulsating stars, and, after a brief review of those aspects of interferometry that are most relevant in this context, anticipate how interferometric observations may contribute to overcome these limitations. Moreover, we present results of recent pilot studies of pulsating stars involving both asteroseismic and interferometric constraints and look into the future, summarizing ongoing efforts concerning the development of future instruments and satellite missions which are expected to have an impact in this field of research.Comment: Version as published in The Astronomy and Astrophysics Review, Volume 14, Issue 3-4, pp. 217-36

Smoking Dose Modifies the Association between C242T Polymorphism and Prevalence of Metabolic Syndrome in a Chinese Population

Background: The C242T polymorphism of the CYBA gene that encodes p22phox, a component of NADPH oxidase, has been found to modulate superoxide production. Oxidase is a major source of the superoxide anion that contributes to individual components of metabolic syndrome. We examined the relationship of the C242T polymorphism with the prevalence of metabolic syndrome in a Chinese population, taking account of consumed cigarette amounts. Methodology/Principal Findings: In 870 participants, we collected biomarkers related to metabolic syndrome and detailed history of smoking and genotyped the C242T polymorphisms. After adjustment for covariates, the CT/TT genotypes were associated with a lower risk of metabolic syndrome (P = 0.0008). The odds of having metabolic syndrome in the CT/TT participants were 0.439 (95%CI: 0.265, 0.726), while for CC participants the odds were 1.110 (95%CI: 0.904, 1.362). There was significant (P = 0.014) interaction between the C242T polymorphism and smoking status in relation to the prevalence of metabolic syndrome. For smokers who smoke no less than 25 pack-years, those with CT/TT genotypes had lower risk of metabolic syndrome as compared with CC polymorphism carriers (P = 0.015). In the multiple regression analysis, the CT/TT genotypes were significantly associated with lower serum concentration of triglycerides both in all subjects and smokers; furthermore, the CT/TT genotypes were also related to smaller waist circumference in smokers. Conclusions: Our study suggests that the C242T gene polymorphism is indeed related to the prevalence of metaboli

Transcriptome-Wide Assessment of Human Brain and Lymphocyte Senescence

Identifying biological pathways that vary across the age spectrum can provide insight into fundamental mechanisms that impact disease and frailty in the elderly. Few methodological approaches offer the means to explore this question on as broad a scale as gene expression profiling. Here, we have evaluated mRNA expression profiles as a function of age in two populations; one consisting of 191 individuals with ages-at-death ranging from 65-100 years and with post-mortem brain mRNA measurements of 13,216 genes and a second with 1240 individuals ages 15-94 and lymphocyte mRNA estimates for 18,519 genes.Among negatively correlated transcripts, an enrichment of mitochondrial genes was evident in both populations, providing a replication of previous studies indicating this as a common signature of aging. Sample differences were prominent, the most significant being a decrease in expression of genes involved in translation in lymphocytes and an increase in genes involved in transcription in brain, suggesting that apart from energy metabolism other basic cell processes are affected by age but in a tissue-specific manner. In assessing genomic architecture, intron/exon sequence length ratios were larger among negatively regulated genes in both samples, suggesting that a decrease in the expression of non-compact genes may also be a general effect of aging. Variance in gene expression itself has been theorized to change with age due to accumulation of somatic mutations and/or increasingly heterogeneous environmental exposures, but we found no evidence for such a trend here.Results affirm that deteriorating mitochondrial gene expression is a common theme in senescence, but also highlight novel pathways and features of gene architecture that may be important for understanding the molecular consequences of aging

Biodegradable, flexible silicon nanomembrane-based NO x gas sensor system with record-high performance for transient environmental monitors and medical implants

Abstract: A novel transient electronics technology that is capable of completely dissolving or decomposing in certain conditions after a period of operation offers unprecedented opportunities for medical implants, environmental sensors, and other applications. Here, we describe a biodegradable, flexible silicon-based electronic system that detects NO species with a record-breaking sensitivity of 136 Rs (5 ppm, NO2) and 100-fold selectivity for NO species over other substances with a fast response (~30 s) and recovery (~60 s). The exceptional features primarily depend on not only materials, dimensions, and design layouts but also temperatures and electrical operations. Large-scale sensor arrays in a mechanically pliable configuration exhibit negligible deterioration in performance under various modes of applied loads, consistent with mechanics modeling. In vitro evaluations demonstrate the capability and stability of integrated NOx devices in severe wet environments for biomedical applications

Combined measurement of differential and total cross sections in the H → γγ and the H → ZZ* → 4ℓ decay channels at s=13 TeV with the ATLAS detector

A combined measurement of differential and inclusive total cross sections of Higgs boson production is performed using 36.1 fb−1 of 13 TeV proton–proton collision data produced by the LHC and recorded by the ATLAS detector in 2015 and 2016. Cross sections are obtained from measured H→γγ and H→ZZ*(→4ℓ event yields, which are combined taking into account detector efficiencies, resolution, acceptances and branching fractions. The total Higgs boson production cross section is measured to be 57.0−5.9 +6.0 (stat.) −3.3 +4.0 (syst.) pb, in agreement with the Standard Model prediction. Differential cross-section measurements are presented for the Higgs boson transverse momentum distribution, Higgs boson rapidity, number of jets produced together with the Higgs boson, and the transverse momentum of the leading jet. The results from the two decay channels are found to be compatible, and their combination agrees with the Standard Model predictions

Search for High-Mass Resonances Decaying to τν in pp Collisions at √s=13 TeV with the ATLAS Detector

A search for high-mass resonances decaying to τν using proton-proton collisions at √s=13 TeV produced by the Large Hadron Collider is presented. Only τ-lepton decays with hadrons in the final state are considered. The data were recorded with the ATLAS detector and correspond to an integrated luminosity of 36.1 fb−1. No statistically significant excess above the standard model expectation is observed; model-independent upper limits are set on the visible τν production cross section. Heavy W′ bosons with masses less than 3.7 TeV in the sequential standard model and masses less than 2.2–3.8 TeV depending on the coupling in the nonuniversal G(221) model are excluded at the 95% credibility level