科研成果

Current studies indicate that long-term exposure to ambient fine particulate matter (PM2.5) is related with global mortality, yet no studies have explored relationships of PM2.5 and its species with DNAm PhenoAge acceleration (DNAmPhenoAccel), a new epigenetic biomarker of phenotypic age. We identified which PM2.5 species had association with DNAmPhenoAccel in a one-year exposure window in a longitudinal cohort. We collected whole blood samples from 683 elderly men in the Normative Aging Study between 1999 and 2013 (n = 1254 visits). DNAm PhenoAge was calculated using 513 CpGs retrieved from the Illumina Infinium HumanMethylation450 BeadChip. Daily concentrations of PM2.5 species were measured at a fixed air-quality monitoring site and one-year moving averages were computed. Linear mixed-effect (LME) regression and Bayesian kernel machine (BKM) regression were used to estimate the associations. The covariates included chronological age, body mass index (BMI), cigarette pack years, smoking status, estimated cell types, batch effects etc. Benjamini-Hochberg false discovery rate at a 5% false positive threshold was used to adjust for multiple comparison. During the study period, the mean DNAm PhenoAge and chronological age in our subjects were 68 and 73 years old, respectively. Using LME model, only lead and calcium were significantly associated with DNAmPhenoAccel. For example, an interquartile range (IQR, 0.0011 mug/m(3)) increase in lead was associated with a 1.29-year [95% confidence interval (CI): 0.47, 2.11] increase in DNAmPhenoAccel. Using BKM model, we selected PM2.5, lead, and silicon to be predictors for DNAmPhenoAccel. A subsequent LME model showed that only lead had significant effect on DNAmPhenoAccel: 1.45-year (95% CI: 0.46, 2.46) increase in DNAmPhenoAccel following an IQR increase in one-year lead. This is the first study that investigates long-term effects of PM2.5 components on DNAmPhenoAccel. The results demonstrate that lead and calcium contained in PM2.5 was robustly associated with DNAmPhenoAccel.

One-carbon metabolism is an important contributor to aging-related diseases; nevertheless, relationships of one-carbon metabolites with novel DNA methylation-based measures of biological aging remain poorly characterized. We examined relationships of one-carbon metabolites with three DNA methylation-based measures of biological aging: DNAmAge, GrimAge, and PhenoAge. We measured plasma levels of four common one-carbon metabolites (vitamin B6, vitamin B12, folate, and homocysteine) in 715 VA Normative Aging Study participants with at least one visit between 1999 and 2008 (observations = 1153). DNA methylation age metrics were calculated using the HumanMethylation450 BeadChip. We utilized Bayesian Kernel Machine Regression (BKMR) models adjusted for chronological age, lifestyle factors, age-related diseases, and study visits to determine metabolites important to the aging outcomes. BKMR models allowed for the estimation of the relationships of single metabolites and the cumulative metabolite mixture with methylation age. Log vitamin B6 was selected as important to PhenoAge (beta = -1.62-years, 95%CI: -2.28, -0.96). Log folate was selected as important to GrimAge (beta = 0.75-years, 95%CI: 0.41, 1.09) and PhenoAge (beta = 1.62-years, 95%CI: 0.95, 2.29). Compared to a model where each metabolite in the mixture is set to its 50 th percentile, the log cumulative mixture with each metabolite at its 30 th (beta = -0.13-years, 95%CI: -0.26, -0.005) and 40 th percentile (beta = -0.06-years, 95%CI: -0.11, -0.005) was associated with decreased GrimAge. Our results provide novel characterizations of the relationships between one-carbon metabolites and DNA methylation age in a human population study. Further research is required to confirm these findings and establish their generalizability.

We propose an experiment to test the uniform-Berry-curvature picture of composite fermions. We show that the asymmetry of geometrical resonances observed in a periodically modulated composite fermion system can be explained with the uniform-Berry-curvature picture. Moreover, we show that an alternative way of modulating the system, i.e., modulating the external magnetic field, will induce an asymmetry opposite to that of the usual periodic grating modulation which effectively modulates the Chern-Simons field. The experiment can serve as a critical test of the uniform-Berry-curvature picture and probe the dipole structure of composite fermions proposed by Read.

As an important reactive trace gases in the troposphere, nitryl chloride (ClNO2) has significant impacts on atmospheric oxidation capacity , the degradation of primary pollutants and the formation of secondary pollutants, and plays indispensable roles in global cycles of both nitrogen and chlorine. In this paper, we introduce basic properties of ClNO2 as well as its formation and removal mechanisms in the troposphere, and describe in brief techniques currently used in laboratory and field work to measure ClNO2. In addition , we review spatial and temporal distributions of tropospheric ClNO2 over the globe as reported in the last 10 similar to 20 years , discuss in a systematical manner chemical mechanisms and environmental factors which determine its heterogeneous formation in the atmosphere via critical analysis of important results from laboratory studies and field measurements, and summarize impacts of ClNO(2 )on chlorine radicals, atmospheric oxidation capacity as well as the formation of O-3 and nitrate aerosol. We emphasize that ClNO2 couples gas phase chemistry and heterogeneous chemistry , and also couples nocturnal atmospheric chemistry with daytime photochemistry , thus very likely playing an important role in the formation of air pollution complex in China. Important questions which remain to be answered to better understand atmospheric chemistry of ClNO2 are outlined at the end, and we also discuss in brief how these questions can be addressed in future work.

We present the analysis of the atmospheric budget of nitrophenols and nitrocresols, a class of nitroaromatics that raise great ecosystem and health concerns due to their phytotoxic and genotoxic properties, during the spring wheat harvest season in Eastern China. Significant quantities with maximum concentrations over 100 pptv and distinct diurnal patterns that peak around midnight and maintain low levels throughout the day were observed, in coincidence with the extensive open crop residue burning activities conducted in the vicinity. An observationally constrained zero‐dimension box model was constructed to assess the relative importance of various production and removal pathways at play in determining the measured surface concentrations. The NO3‐initiated dark chemistry, in concert with meteorological variations predominantly dilution and entrainment, exerts major controls over the observed diurnal behaviors of nitrophenols and nitrocresols. Structural isomerism is predicted to have a significant impact on the multiphase partitioning and chemistry of nitrophenol isomers. Furthermore, simulations show that an appreciable amount of nitrophenols is present in the aerosol water, thereby representing an important source of water‐soluble brown carbon in atmospheric aerosols under the humid subtropical weather prevailing during the campaign. Sensitivity analysis performed on the model parameterizations of reaction schemes helps to further understand the chemistry underlying the diurnal cycles. Implementing NO‐dependent yields of cresols from toluene photooxidation improves the model predictions of nitrocresols at low NO ranges (<1 ppb), thereby underscoring the complexity of the peroxy radical reaction pathways from toluene photooxidation under atmospheric relevant conditions.

We derive the definition of the Berry phase for the adiabatic transport of a composite fermion (CF) in a half-filled composite Fermi liquid (CFL). It is found to be different from that adopted in previous investigations by Geraedts et al. For the standard CFL wave function, we analytically show that the Berry curvature is uniformly distributed in the momentum space. For the Jain-Kamilla wave function, we numerically show that its Berry curvature has a continuous distribution inside the Fermi sea and vanishes outside. We conclude that the CF with respect to both the microscopic wave functions is not a massless Dirac particle.

Ambient particulate matter (PM) is often used as a proxy of personal exposure in epidemiological studies of PM-induced health effects, yet whether this proxy biases the estimates of health effects is still unknown. On the basis of a panel study in Beijing, China, we investigated the dependence of 24 h personal exposure concentration to fine particles (PM2.5) and its carbonaceous components on the corresponding 24 h ambient concentration. The associated changes in inflammatory biomarkers with personal and ambient exposure were further examined using linear mixed-effect models. At ambient PM2.5 levels of \textless25 $μ$g m–3, personal exposure to PM2.5 was often several times higher, with a median personal/ambient ratio of ∼3. The ratio declined with an increase in ambient concentration, approaching ∼1 at ambient PM2.5 levels of \textgreater75 $μ$g m–3. Similar trends were also observed for organic carbon and elemental carbon. Personal exposures were significantly associated with both respiratory and systemic inflammatory biomarkers, such as fractional exhaled nitric oxide and white blood cell count. When ambient data were used, the association with systemic inflammation weakened. Our findings imply that the use of the ambient pollutant concentration as a proxy for personal exposure may be inaccurate and could bias the estimates of PM-induced health effects.

This article considers a bilinear model that includes two different latent effects. The first effect has a direct influence on the response variable, whereas the second latent effect is assumed to first influence other latent variables, which in turn affect the response variable. In this article, latent variables are modelled via rank restrictions on unknown mean parameters and the models which are used are often referred to as reduced rank regression models. This article presents a likelihood-based approach that results in explicit estimators. In our model, the latent variables act as covariates that we know exist, but their direct influence is unknown and will therefore not be considered in detail. One example is if we observe hundreds of weather variables, but we cannot say which or how these variables affect plant growth.

Heavy metal contamination poses considerable threats to various ecosystems, yet little is known about the assembly and adaptation of microbial communities at sites with combined heavy metal(loid) pollution. Here, we examined metal(loid) pollutants and bacterial communities in three zones (Zones I, II, and III) of an abandoned sewage reservoir with different usage years. The contamination level of multiple metal(loid)s was higher in Zone I than in the other zones, and arsenic (As), zinc (Zn), selenium (Se), copper (Cu), tin (Sn), molybdenum (Mo), antimony (Sb), cadmium (Cd), lead (Pb), thallium (TI), and nickel (Ni) were the major contaminants (pollution load index > 1). Bioavailable forms of titanium (Ti), chromium (Cr), Sn, and cobalt (Co) played essential roles in shaping the microbial structure, and physicochemical properties, especially organic matter (OM) and pH, also mediated the microbial diversity and composition in the metal(loid) contaminated zones. Metal-microbe interactions and heatmap analysis revealed that the bioavailability of metal(loid)s promoted the niche partitioning of microbial species. Metal-resistant species were abundant in Zone I that had the highest metal-contaminated level, whereas metal-sensitive species prevailed in Zone III that had the lowest pollution level. The bioavailable metal(loid)s rather than physicochemical and spatial variables explained a larger portion of the variance in the microbial community, and the homogeneous selection was the dominant ecological process driving the assembly of the microbial community. Overall, our study highlighted the importance of metal(loid) bioavailability in shaping microbial structure, future bioremediation, and environmental management of metal(loid) contaminated sites. (C) 2020 Elsevier Ltd. All rights reserved.

Bioorthogonal chemistry capable of operating in live animals is needed to investigate biological processes such as cell death and immunity. Recent studies have identified a gasdermin family of pore-forming proteins that executes inflammasome-dependent and -independent pyroptosis1,2,3,4,5. Pyroptosis is proinflammatory, but its effect on antitumour immunity is unknown. Here we establish a bioorthogonal chemical system, in which a cancer-imaging probe phenylalanine trifluoroborate (Phe-BF3) that can enter cells desilylates and ‘cleaves’ a designed linker that contains a silyl ether. This system enabled the controlled release of a drug from an antibody–drug conjugate in mice. When combined with nanoparticle-mediated delivery, desilylation catalysed by Phe-BF3 could release a client protein—including an active gasdermin—from a nanoparticle conjugate, selectively into tumour cells in mice. We applied this bioorthogonal system to gasdermin, which revealed that pyroptosis of less than 15% of tumour cells was sufficient to clear the entire 4T1 mammary tumour graft. The tumour regression was absent in immune-deficient mice or upon T cell depletion, and was correlated with augmented antitumour immune responses. The injection of a reduced, ineffective dose of nanoparticle-conjugated gasdermin along with Phe-BF3 sensitized 4T1 tumours to anti-PD1 therapy. Our bioorthogonal system based on Phe-BF3 desilylation is therefore a powerful tool for chemical biology; our application of this system suggests that pyroptosis-induced inflammation triggers robust antitumour immunity and can synergize with checkpoint blockade.

DNA methylation has fundamental roles in gene programming and aging that may help predict mortality. However, no large-scale study has investigated whether site-specific DNA methylation predicts all-cause mortality. We used the Illumina-HumanMethylation450-BeadChip to identify blood DNA methylation sites associated with all-cause mortality for 12, 300 participants in 12 Cohorts of the Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium. Over an average 10-year follow-up, there were 2,561 deaths across the cohorts. Nine sites mapping to three intergenic and six gene-specific regions were associated with mortality (P < 9.3x10(-7)) independently of age and other mortality predictors. Six sites (cg14866069, cg23666362, cg20045320, cg07839457, cg07677157, cg09615688)-mapping respectively to BMPR1B, MIR1973, IFITM3, NLRC5, and two intergenic regions-were associated with reduced mortality risk. The remaining three sites (cg17086398, cg12619262, cg18424841)-mapping respectively to SERINC2, CHST12, and an intergenic region-were associated with increased mortality risk. DNA methylation at each site predicted 5%-15% of all deaths. We also assessed the causal association of those sites to age-related chronic diseases by using Mendelian randomization, identifying weak causal relationship between cg18424841 and cg09615688 with coronary heart disease. Of the nine sites, three (cg20045320, cg07839457, cg07677157) were associated with lower incidence of heart disease risk and two (cg20045320, cg07839457) with smoking and inflammation in prior CHARGE analyses. Methylation of cg20045320, cg07839457, and cg17086398 was associated with decreased expression of nearby genes (IFITM3, IRF, NLRC5, MT1, MT2, MARCKSL1) linked to immune responses and cardiometabolic diseases. These sites may serve as useful clinical tools for mortality risk assessment and preventative care.

The stochastic solutions to the Wigner equation, which explain the nonlocal oscillatory integral operator $\Theta_V$ with an anti-symmetric kernel as the generator of two branches of jump processes,  are analyzed. All existing branching random walk solutions are formulated based on the Hahn-Jordan decomposition $\Theta_V=\Theta^+_V-\Theta^-_V$, i.e., treating $\Theta_V$ as the difference of two positive operators $\Theta^\pm_V$, each of which characterizes the transition of states for one branch of particles. Despite the fact that the first moments of such models solve the Wigner equation, we prove that the bounds of corresponding variances grow exponentially in time with the rate depending on the upper bound of $\Theta^\pm_V$, instead of $\Theta_V$. In other words, the decay of high-frequency components is totally ignored, resulting in a severe numerical sign problem. To fully utilize such decay property, we have recourse to the stationary phase approximation for $\Theta_V$, which captures essential contributions from the stationary phase points as well as the near-cancelation of positive and negative weights. The resulting branching random walk solutions are then proved to asymptotically solve the Wigner equation, but gain a substantial reduction in variances, thereby ameliorating the sign problem. Numerical experiments in 4-D phase space validate our theoretical findings.