Understanding the effect of moisture in an adsorbent that is selective to CO2 over N2 is central to the design and development of adsorption technology for CO2 capture and concentration from power ...plant flue gas. Molecular simulations of wet flue gas adsorption on Zeolite 13X were here performed in the grand canonical (μVT) ensemble using the Monte Carlo technique in atomistic detail. The generated multicomponent isotherm data spanned the complete gas mixture composition range for adsorbing species CO2, N2 and H2O from 25 °C to 75 °C at 1atm. The adsorption simulations consisted of faujasite zeolite crystal structures with a fixed Si/Al ratio of 1.31, Na+ cation mobility and beta sodalite cage blocking of CO2 and N2 using 4 Å radius virtual blocking spheres. Simulated equilibrium isotherm data demonstrated that the presence of even small amounts of water vapor in the gas mixture has a significant impact on the adsorbate loadings for the remaining gas components in Zeolite 13X. Structural analysis with radial distribution functions revealed a shift in CO2 adsorption away from the framework structure towards α-cavity pore centres and exclusion from sites adjacent to Na+(II) when H2O is present in the gas mixture. A degree of competitive adsorption of CO2 at Na+(III) sites persists at up to 15% relative humidity (RH) at 298 K (0.5 mol% H2O) with significant lateral adorbate-H2O interactions but exclusion beyond that threshold. Lower CO2 loadings were associated with the growth of hydrogen bonded clusters with major changes complete by RH = 20% at 298 K.
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•Using GCMC, a wide set of CO2/N2/H2O equilibrium data on Z13X was obtained.•CO2 adsorption loadings are strongly influenced by H2O.•Structural characterization of adsorbate layer revealed the dominant role of H2O.•RH dependent access of CO2 to Na+(III) sites and exclusion near Na+(II) for all RH.•Low CO2 loadings were associated with the growth of hydrogen bonded H2O clusters.
A history of periodontal disease and the presence of circulating antibodies to selected oral pathogens have been associated with increased risk of pancreatic cancer; however, direct relationships of ...oral microbes with pancreatic cancer have not been evaluated in prospective studies. We examine the relationship of oral microbiota with subsequent risk of pancreatic cancer in a large nested case-control study.
We selected 361 incident adenocarcinoma of pancreas and 371 matched controls from two prospective cohort studies, the American Cancer Society Cancer Prevention Study II and the National Cancer Institute Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. From pre-diagnostic oral wash samples, we characterised the composition of the oral microbiota using bacterial 16S ribosomal RNA (16S rRNA) gene sequencing. The associations between oral microbiota and risk of pancreatic cancer, controlling for the random effect of cohorts and other covariates, were examined using traditional and L1-penalised least absolute shrinkage and selection operator logistic regression.
Carriage of oral pathogens,
and
, were associated with higher risk of pancreatic cancer (adjusted OR for presence vs absence=1.60 and 95% CI 1.15 to 2.22; OR=2.20 and 95% CI 1.16 to 4.18, respectively). Phylum
and its genus
were associated with decreased pancreatic cancer risk (OR per per cent increase of relative abundance=0.94 and 95% CI 0.89 to 0.99; OR=0.87 and 95% CI 0.79 to 0.95, respectively). Risks related to these phylotypes remained after exclusion of cases that developed within 2 years of sample collection, reducing the likelihood of reverse causation in this prospective study.
This study provides supportive evidence that oral microbiota may play a role in the aetiology of pancreatic cancer.
Bacteria may play a role in esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC), although evidence is limited to cross-sectional studies. In this study, we examined the ...relationship of oral microbiota with EAC and ESCC risk in a prospective study nested in two cohorts. Oral bacteria were assessed using 16S rRNA gene sequencing in prediagnostic mouthwash samples from
= 81/160 EAC and
= 25/50 ESCC cases/matched controls. Findings were largely consistent across both cohorts. Metagenome content was predicted using PiCRUST. We examined associations between centered log-ratio transformed taxon or functional pathway abundances and risk using conditional logistic regression adjusting for BMI, smoking, and alcohol. We found the periodontal pathogen
to be associated with higher risk of EAC. Furthermore, we found that depletion of the commensal genus
and the species
was associated with lower EAC risk. Bacterial biosynthesis of carotenoids was also associated with protection against EAC. Finally, the abundance of the periodontal pathogen
trended with higher risk of ESCC. Overall, our findings have potential implications for the early detection and prevention of EAC and ESCC.
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Researchers are often interested in understanding the disease subtype heterogeneity by testing whether a risk exposure has the same level of effect on different disease subtypes. The polytomous ...logistic regression (PLR) model provides a flexible tool for such an evaluation. Disease subtype heterogeneity can also be investigated with a case-only study that uses a case-case comparison procedure to directly assess the difference between risk effects on two disease subtypes. Motivated by a large consortium project on the genetic basis of non-Hodgkin lymphoma (NHL) subtypes, we develop PolyGIM, a procedure to fit the PLR model by integrating individual-level data with summary data extracted from multiple studies under different designs. The summary data consist of coefficient estimates from working logistic regression models established by external studies. Examples of the working model include the case-case comparison model and the case-control comparison model, which compares the control group with a subtype group or a broad disease group formed by merging several subtypes. PolyGIM efficiently evaluates risk effects and provides a powerful test for disease subtype heterogeneity in situations when only summary data, instead of individual-level data, is available from external studies due to various informatics and privacy constraints. We investigate the theoretic properties of PolyGIM and use simulation studies to demonstrate its advantages. Using data from eight genome-wide association studies within the NHL consortium, we apply it to study the effect of the polygenic risk score defined by a lymphoid malignancy on the risks of four NHL subtypes. These results show that PolyGIM can be a valuable tool for pooling data from multiple sources for a more coherent evaluation of disease subtype heterogeneity.
Carbon capture from flue gas by adsorption processes requires a suitable isotherm model for use in process simulators. Comparative physical adsorption isotherm models are here tested on an adsorption ...equilibrium loading data set for Zeolite 13X (Z13X) between 298 and 348 K. Dry flue gas mixture adsorption was found to involve enhanced adsorption of N2 by up to 85% relative to levels of N2 mixture adsorption predicted with pure species parameters. This relative N2 deviation was found strongly dependent upon the amount of adsorbed CO2 and suggested to be caused by optimization of molecular quadrupole interactions in the adsorbate layer. A supplemental isotherm expression dependent upon mixture fitting parameters characterized the phenomenon. Prediction of wet flue gas mixture adsorption on Z13X was tested with different numbers of adsorption sites in the α-cavity and logistic formulations to exclude CO2 and N2 from hydrophilic adsorption sites but without success. Shielding the affinity of Z13X toward coadsorbates using the moisture content in the gas mixture improved regression residuals. This method of sticking parameter adjustment described the influence of adsorbed H2O hydrogen-bonded clusters on CO2 and N2 and may provide a path to humid mixture adsorption prediction through studies of pure H2O in porous materials.
Oral microbiome dysbiosis is associated with oral disease and potentially with systemic diseases; however, the determinants of these microbial imbalances are largely unknown. In a study of 1204 US ...adults, we assessed the relationship of cigarette smoking with the oral microbiome. 16S rRNA gene sequencing was performed on DNA from oral wash samples, sequences were clustered into operational taxonomic units (OTUs) using QIIME and metagenomic content was inferred using PICRUSt. Overall oral microbiome composition differed between current and non-current (former and never) smokers (P<0.001). Current smokers had lower relative abundance of the phylum Proteobacteria (4.6%) compared with never smokers (11.7%) (false discovery rate q=5.2 × 10(-7)), with no difference between former and never smokers; the depletion of Proteobacteria in current smokers was also observed at class, genus and OTU levels. Taxa not belonging to Proteobacteria were also associated with smoking: the genera Capnocytophaga, Peptostreptococcus and Leptotrichia were depleted, while Atopobium and Streptococcus were enriched, in current compared with never smokers. Functional analysis from inferred metagenomes showed that bacterial genera depleted by smoking were related to carbohydrate and energy metabolism, and to xenobiotic metabolism. Our findings demonstrate that smoking alters the oral microbiome, potentially leading to shifts in functional pathways with implications for smoking-related diseases.
Abstract
Background
Per- and polyfluoroalkyl substances (PFAS) are highly persistent chemicals that have been detected in the serum of over 98% of the US population. Studies among highly exposed ...individuals suggest an association with perfluorooctanoic acid (PFOA) exposure and kidney cancer. It remains unclear whether PFOA or other PFAS are renal carcinogens or if they influence risk of renal cell carcinoma (RCC) at concentrations observed in the general population.
Methods
We measured prediagnostic serum concentrations of PFOA and 7 additional PFAS in 324 RCC cases and 324 individually matched controls within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Multivariable conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs) relating serum PFAS concentrations and RCC risk. Individual PFAS were modeled continuously (log2-transformed) and categorically, with adjustment for kidney function and additional potential confounders. All statistical tests were 2-sided.
Results
We observed a positive association with RCC risk for PFOA (doubling in serum concentration, ORcontinuous = 1.71, 95% CI = 1.23 to 2.37, P = .002) and a greater than twofold increased risk among those in the highest quartile vs the lowest (OR = 2.63, 95% CI = 1.33 to 5.20, Ptrend = .007). The association with PFOA was similar after adjustment for other PFAS (ORcontinuous = 1.68, 95% CI = 1.07 to 2.63, P = .02) and remained apparent in analyses restricted to individuals without evidence of diminished kidney function and in cases diagnosed 8 or more years after phlebotomy.
Conclusions
Our findings add substantially to the weight of evidence that PFOA is a renal carcinogen and may have important public health implications for the many individuals exposed to this ubiquitous and highly persistent chemical.
The rising concentration of CO2, emitted into the atmosphere from power plant flue gas, is a major contributor to global warming. Silica gel is an important adsorbent to dry wet flue gas prior to ...sending the dried gas (CO2/N2 mixture) for carbon capture. In the present work, a comprehensive experimental and simulation study is undertaken to establish the adsorption and diffusion of N2 and CO2 and their mixture on silica gel at pressures and temperatures relevant to vacuum swing adsorption (VSA) processes. The adsorption equilibrium of pure N2 and CO2 is captured well by the single component Langmuir isotherm model. Carefully designed controlled experiments are conducted to show that the transport mechanism for the adsorption of pure N2 in silica gel pores is governed by Knudsen flow, while for CO2, it is a combination of Knudsen and surface flow. Binary mixture experiments are performed to confirm the mixture equilibrium and kinetic models necessary to simulate the dry product end of a column in a VSA process for drying wet flue gas. For binary mixture equilibrium of these gases, there is no effect of competition from the other gas present in the mixture, implying that they exhibit noncompetitive adsorption on silica gel. Transport of CO2/N2 mixture in silica gel pores is well captured by the mechanism established from the single component study.
A comprehensive characterization of the effects of cigarette smoke on systemic soluble immune/inflammatory markers may provide insight into the mechanisms through which smoking causes disease.
Levels ...of 78 inflammation, immune, and metabolic markers were measured using multiplex immune assays in 1819 Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) participants aged 55 to 74 years from three existing nested case-control studies. These data were made representative of the entire PLCO screening arm through reweighting with weights estimated in logistic regression models. We assessed associations between smoking status, cigarettes smoked per day, and time since quitting with dichotomized marker levels using adjusted weighted logistic regression models.
Current smoking was associated with 10 inflammation markers after correcting for multiple testing, encompassing several components of the immune/inflammation response. Levels of seven of these markers (interleukin IL-15, IL-1RA, IL-1β, IL-16, stem cell factor, soluble interleukin 6 receptor, and soluble vascular endothelial growth factor receptor 3) were lower among current smokers (n = 414) when compared with never smokers (n = 548), with odds ratios (ORs) ranging from 0.44 to 0.27, while levels of CC motif ligand (CCL)/thymus and activation regulated chemokine (CCL17/TARC) (OR = 4.08, 95% confidence interval CI = 2.01 to 8.25), CCL11/EOTAXIN (OR = 2.57, 95% CI = 1.45 to 4.55), and C-reactive protein (CRP) (OR = 2.54, 95% CI = 1.29 to 4.98) were elevated. These markers were not associated with cigarettes per day among current smokers, but there were trends in IL-15, IL-1RA, IL-1β, CCL17/TARC, CCL11/EOTAXIN, and CRP levels across categories of years since quitting smoking.
Smoking is associated with a broad range of alterations in systemic immune and inflammation marker levels among older, long-term smokers. Smoking cessation may result in marker levels reverting back to those of never smokers over time.
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