Quantifying understorey vegetation in the US Lake States: a proposed framework to inform regional forest carbon stocks

The contribution of understorey vegetation (UVEG) to forest ecosystem biomass and carbon (C) across diverse forest types has, to date, eluded quantification at regional and national scales. Efforts to quantify UVEG C have been limited to field-intensive studies or broad-scale modelling approaches lacking field measurements. Although large-scale inventories of UVEG C are not common, species-and community-level inventories of vegetation structure are available and may prove useful in quantifying UVEG C stocks. This analysis developed a general framework for estimating UVEG C stocks by employing per cent cover estimates of UVEG from a region-wide forest inventory coupled with an estimate of maximum UVEG C across the US Lake States (i.e. Michigan, Minnesota and Wisconsin). Estimates of UVEG C stocks from this approach reasonably align with expected C stocks in the study region, ranging from 0.86+0.06 Mg ha 21 in red pine-dominated to 1.59+0.06 Mg ha 21 for aspen/birch-dominated forest types. Although the data employed here were originally collected to assess broad-scale forest structure and diversity, this study proposes a framework for using UVEG inventories as a foundation for estimating C stocks in an often overlooked, yet important ecosystem C pool

Activity and expression of progesterone metabolizing 5α-reductase, 20α-hydroxysteroid oxidoreductase and 3α(β)-hydroxysteroid oxidoreductases in tumorigenic (MCF-7, MDA-MB-231, T-47D) and nontumorigenic (MCF-10A) human breast cancer cells

BACKGROUND: Recent observations indicate that human tumorous breast tissue metabolizes progesterone differently than nontumorous breast tissue. Specifically, 5α-reduced metabolites (5α-pregnanes, shown to stimulate cell proliferation and detachment) are produced at a significantly higher rate in tumorous tissue, indicating increased 5α-reductase (5αR) activity. Conversely, the activities of 3α-hydroxysteroid oxidoreductase (3α-HSO) and 20α-HSO enzymes appeared to be higher in normal tissues. The elevated conversion to 5α-pregnanes occurred regardless of estrogen (ER) or progesterone (PR) receptor levels. To gain insight into these differences, the activities and expression of these progesterone converting enzymes were investigated in a nontumorigenic cell line, MCF-10A (ER- and PR-negative), and the three tumorigenic cell lines, MDA-MB-231 (ER- and PR-negative), MCF-7 and T-47D (ER- and PR-positive). METHODS: For the enzyme activity studies, either whole cells were incubated with [(14)C]progesterone for 2, 4, 8, and 24 hours, or the microsomal/cytosolic fraction was incubated for 15–60 minutes with [(3)H]progesterone, and the metabolites were identified and quantified. Semi-quantitative RT-PCR was employed to determine the relative levels of expression of 5αR type1 (SRD5A1), 5αR type 2 (SRD5A2), 20α-HSO (AKR1C1), 3α-HSO type 2 (AKR1C3), 3α-HSO type 3 (AKR1C2) and 3β-HSO (HSD3B1/HSD3B2) in the four cell lines using 18S rRNA as an internal control. RESULTS: The relative 5α-reductase activity, when considered as a ratio of 5α-pregnanes/4-pregnenes, was 4.21 (± 0.49) for MCF-7 cells, 6.24 (± 1.14) for MDA-MB-231 cells, 4.62 (± 0.43) for T-47D cells and 0.65 (± 0.07) for MCF-10A cells, constituting approximately 6.5-fold, 9.6-fold and 7.1 fold higher conversion to 5α-pregnanes in the tumorigenic cells, respectively, than in the nontumorigenic MCF-10A cells. Conversely, the 20α-HSO and 3α-HSO activities were significantly higher (p < 0.001) in MCF-10A cells than in the other three cell types. In the MCF-10A cells, 20α-HSO activity was 8-14-fold higher and the 3α-HSO activity was 2.5-5.4-fold higher than in the other three cell types. The values of 5αR:20α-HSO ratios were 16.9 – 32.6-fold greater and the 5αR:3α-HSO ratios were 5.2 – 10.5-fold greater in MCF-7, MDA-MB-231 and T-47D cells than in MCF-10A cells. RT-PCR showed significantly higher expression of 5αR1 (p < 0.001), and lower expression of 20α-HSO (p < 0.001), 3α-HSO2 (p < 0.001), 3α-HSO3 (p < 0.001) in MCF-7, MDA-MB-231 and T-47D cells than in MCF-10A cells. CONCLUSION: The findings provide the first evidence that the 5αR activity (leading to the conversion of progesterone to the cancer promoting 5α-pregnanes) is significantly higher in the tumorigenic MCF-7, MDA-MB-231 and T-47D breast cell lines than in the nontumorigenic MCF-10A cell line. The higher 5αR activity coincides with significantly greater expression of 5αR1. On the other hand, the activities of 20α-HSO and 3α-HSO are higher in the MCF-10A cells than in MCF-7, MDA-MB-231 and T-47D cells; these differences in activity correlate with significantly higher expression of 20α-HSO, 3α-HSO2 and 3α-HSO3 in MCF-10A cells. Changes in progesterone metabolizing enzyme expression (resulting in enzyme activity changes) may be responsible for stimulating breast cancer by increased production of tumor-promoting 5α-pregnanes and decreased production of anti-cancer 20α – and 3α-4-pregnenes

A View of Tropical Cyclones from Above: The Tropical Cyclone Intensity Experiment

Tropical cyclone (TC) outflow and its relationship to TC intensity change and structure were investigated in the Office of Naval Research Tropical Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from the innovative new High-Definition Sounding System (HDSS) and remotely sensed observations from the Hurricane Imaging Radiometer (HIRAD), both on board the NASA WB-57 that flew in the lower stratosphere. Three noteworthy hurricanes were intensively observed with unprecedented horizontal resolution: Joaquin in the Atlantic and Marty and Patricia in the eastern North Pacific. Nearly 800 dropsondes were deployed from the WB-57 flight level of ∼60,000 ft (∼18 km), recording atmospheric conditions from the lower stratosphere to the surface, while HIRAD measured the surface winds in a 50-km-wide swath with a horizontal resolution of 2 km. Dropsonde transects with 4–10-km spacing through the inner cores of Hurricanes Patricia, Joaquin, and Marty depict the large horizontal and vertical gradients in winds and thermodynamic properties. An innovative technique utilizing GPS positions of the HDSS reveals the vortex tilt in detail not possible before. In four TCI flights over Joaquin, systematic measurements of a major hurricane’s outflow layer were made at high spatial resolution for the first time. Dropsondes deployed at 4-km intervals as the WB-57 flew over the center of Hurricane Patricia reveal in unprecedented detail the inner-core structure and upper-tropospheric outflow associated with this historic hurricane. Analyses and numerical modeling studies are in progress to understand and predict the complex factors that influenced Joaquin’s and Patricia’s unusual intensity changes

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 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

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

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

Genome-wide imputation study identifies novel HLA locus for pulmonary fibrosis and potential role for auto-immunity in fibrotic idiopathic interstitial pneumonia

Fibrotic idiopathic interstitial pneumonias (fIIP) are a group of fatal lung diseases with largely unknown etiology and without definitive treatment other than lung transplant to prolong life. There is strong evidence for the importance of both rare and common genetic risk alleles in familial and sporadic disease. We have previously used genome-wide single nucleotide polymorphism data to identify 10 risk loci for fIIP. Here we extend that work to imputed genome-wide genotypes and conduct new RNA sequencing studies of lung tissue to identify and characterize new fIIP risk loci. Results: We performed genome-wide genotype imputation association analyses in 1616 non-Hispanic white (NHW) cases and 4683 NHW controls followed by validation and replication (878 cases, 2017 controls) genotyping and targeted gene expression in lung tissue. Following meta-analysis of the discovery and replication populations, we identified a novel fIIP locus in the HLA region of chromosome 6 (rs7887 Pmeta = 3.7 × 10-09). Imputation of classic HLA alleles identified two in high linkage disequilibrium that are associated with fIIP (DRB1 15:01 P = 1.3 × 10-7 and DQB1 06:02 P = 6.1 × 10-8). Targeted RNA-sequencing of the HLA locus identified 21 genes differentially expressed between fibrotic and control lung tissue (Q < 0.001), many of which are involved in immune and inflammatory response regulation. In addition, the putative risk alleles, DRB1 15:01 and DQB1 06:02, are associated with expression of the DQB1 gene among fIIP cases (Q < 1 × 10-16)