Effects of Buoyancy on Laminar, Transitional, and Turbulent Gas Jet Diffusion Flames

Gas jet diffusion flames have been a subject of research for many years. However, a better understanding of the physical and chemical phenomena occurring in these flames is still needed, and, while the effects of gravity on the burning process have been observed, the basic mechanisms responsible for these changes have yet to be determined. The fundamental mechanisms that control the combustion process are in general coupled and quite complicated. These include mixing, radiation, kinetics, soot formation and disposition, inertia, diffusion, and viscous effects. In order to understand the mechanisms controlling a fire, laboratory-scale laminar and turbulent gas-jet diffusion flames have been extensively studied, which have provided important information in relation to the physico-chemical processes occurring in flames. However, turbulent flames are not fully understood and their understanding requires more fundamental studies of laminar diffusion flames in which the interplay of transport phenomena and chemical kinetics is more tractable. But even this basic, relatively simple flame is not completely characterized in relation to soot formation, radiation, diffusion, and kinetics. Therefore, gaining an understanding of laminar flames is essential to the understanding of turbulent flames, and particularly fires, in which the same basic phenomena occur. In order to improve and verify the theoretical models essential to the interpretation of data, the complexity and degree of coupling of the controlling mechanisms must be reduced. If gravity is isolated, the complication of buoyancy-induced convection would be removed from the problem. In addition, buoyant convection in normal gravity masks the effects of other controlling parameters on the flame. Therefore, the combination of normal-gravity and microgravity data would provide the information, both theoretical and experimental, to improve our understanding of diffusion flames in general, and the effects of gravity on the burning process in particular

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Sunlight mediated seasonality in canopy structure and photosynthetic activity of Amazonian rainforests

Resolving the debate surrounding the nature and controls of seasonal variation in the structure and metabolism of Amazonian rainforests is critical to understanding their response to climate change. In situ studies have observed higher photosynthetic and evapotranspiration rates, increased litterfall and leaf flushing during the Sunlight-rich dry season. Satellite data also indicated higher greenness level, a proven surrogate of photosynthetic carbon fixation, and leaf area during the dry season relative to the wet season. Some recent reports suggest that rainforests display no seasonal variations and the previous results were satellite measurement artefacts. Therefore, here we re-examine several years of data from three sensors on two satellites under a range of sun positions and satellite measurement geometries and document robust evidence for a seasonal cycle in structure and greenness of wet equatorial Amazonian rainforests. This seasonal cycle is concordant with independent observations of solar radiation. Weattribute alternative conclusions to an incomplete study of the seasonal cycle, i. e. the dry season only, and to prognostications based on a biased radiative transfer model. Consequently, evidence of dry season greening in geometry corrected satellite data was ignored and the absence of evidence for seasonal variation in lidar data due to noisy and saturated signals was misinterpreted as evidence of the absence of changes during the dry season. Our results, grounded in the physics of radiative transfer, buttress previous reports of dry season increases in leaf flushing, litterfall, photosynthesis and evapotranspiration in well-hydrated Amazonian rainforests.Peer reviewe

Sunlight mediated seasonality in canopy structure and photosynthetic activity of Amazonian rainforests

Resolving the debate surrounding the nature and controls of seasonal variation in the structure and metabolism of Amazonian rainforests is critical to understanding their response to climate change. In situ studies have observed higher photosynthetic and evapotranspiration rates, increased litterfall and leaf flushing during the Sunlight-rich dry season. Satellite data also indicated higher greenness level, a proven surrogate of photosynthetic carbon fixation, and leaf area during the dry season relative to the wet season. Some recent reports suggest that rainforests display no seasonal variations and the previous results were satellite measurement artefacts. Therefore, here we re-examine several years of data from three sensors on two satellites under a range of sun positions and satellite measurement geometries and document robust evidence for a seasonal cycle in structure and greenness of wet equatorial Amazonian rainforests. This seasonal cycle is concordant with independent observations of solar radiation. Weattribute alternative conclusions to an incomplete study of the seasonal cycle, i. e. the dry season only, and to prognostications based on a biased radiative transfer model. Consequently, evidence of dry season greening in geometry corrected satellite data was ignored and the absence of evidence for seasonal variation in lidar data due to noisy and saturated signals was misinterpreted as evidence of the absence of changes during the dry season. Our results, grounded in the physics of radiative transfer, buttress previous reports of dry season increases in leaf flushing, litterfall, photosynthesis and evapotranspiration in well-hydrated Amazonian rainforests.Keywords: remote sensing, MODIS, seasonality, MISR, Amazonian rainforest

Genome-Wide Analysis of DNA Methylation and Cigarette Smoking in a Chinese Population

Background: Smoking is a risk factor for many human diseases. DNA methylation has been related to smoking, but genome-wide methylation data for smoking in Chinese populations is limited. Objectives: We aimed to investigate epigenome-wide methylation in relation to smoking in a Chinese population. Methods: We measured the methylation levels at > 485,000 CpG sites (CpGs) in DNA from leukocytes using a methylation array and conducted a genome-wide meta-analysis of DNA methylation and smoking in a total of 596 Chinese participants. We further evaluated the associations of smoking-related CpGs with internal polycyclic aromatic hydrocarbon (PAH) biomarkers and their correlations with the expression of corresponding genes. Results: We identified 318 CpGs whose methylation levels were associated with smoking at a genome-wide significance level (false discovery rate < 0.05), among which 161 CpGs annotated to 123 genes were not associated with smoking in recent studies of Europeans and African Americans. Of these smoking-related CpGs, methylation levels at 80 CpGs showed significant correlations with the expression of corresponding genes (including RUNX3, IL6R, PTAFR, ANKRD11, CEP135 and CDH23), and methylation at 15 CpGs was significantly associated with urinary 2-hydroxynaphthalene, the most representative internal monohydroxy-PAH biomarker for smoking. Conclusion: We identified DNA methylation markers associated with smoking in a Chinese population, including some markers that were also correlated with gene expression. Exposure to naphthalene, a byproduct of tobacco smoke, may contribute to smoking-related methylation. Citation: Zhu X, Li J, Deng S, Yu K, Liu X, Deng Q, Sun H, Zhang X, He M, Guo H, Chen W, Yuan J, Zhang B, Kuang D, He X, Bai Y, Han X, Liu B, Li X, Yang L, Jiang H, Zhang Y, Hu J, Cheng L, Luo X, Mei W, Zhou Z, Sun S, Zhang L, Liu C, Guo Y, Zhang Z, Hu FB, Liang L, Wu T. 2016. Genome-wide analysis of DNA methylation and cigarette smoking in Chinese. Environ Health Perspect 124:966–973; http://dx.doi.org/10.1289/ehp.150983