Detection of a Substantial Molecular Gas Reservoir in a brightest cluster galaxy at z = 1.7

We report the detection of CO(2-1) emission coincident with the brightest cluster galaxy (BCG) of the high-redshift galaxy cluster SpARCS1049+56, with the Redshift Search Receiver (RSR) on the Large Millimetre Telescope (LMT). We confirm a spectroscopic redshift for the gas of z = 1.7091+/-0.0004, which is consistent with the systemic redshift of the cluster galaxies of z = 1.709. The line is well-fit by a single component Gaussian with a RSR resolution-corrected FWHM of 569+/-63 km/s. We see no evidence for multiple velocity components in the gas, as might be expected from the multiple image components seen in near-infrared imaging with the Hubble Space Telescope. We measure the integrated flux of the line to be 3.6+/-0.3 Jy km/s and, using alpha_CO = 0.8 Msun (K km s^-1 pc^2)^-1 we estimate a total molecular gas mass of 1.1+/-0.1x10^11 Msun and a M_H2/M_star ~ 0.4. This is the largest gas reservoir detected in a BCG above z > 1 to date. Given the infrared-estimated star formation rate of 860+/-130 Msun/yr, this corresponds to a gas depletion timescale of ~0.1Gyr. We discuss several possible mechanisms for depositing such a large gas reservoir to the cluster center -- e.g., a cooling flow, a major galaxy-galaxy merger or the stripping of gas from several galaxies -- but conclude that these LMT data are not sufficient to differentiate between them.Comment: accepted for publication in ApJ Letter

The Human–Nature Relationship and Its Impact on Health: A Critical Review

Within the past four decades, research has been increasingly drawn toward understanding whether there is a link between the changing human–nature relationship and its impact on people’s health. However, to examine whether there is a link requires research of its breadth and underlying mechanisms from an interdisciplinary approach. This article begins by reviewing the debates concerning the human–nature relationship, which are then critiqued and redefined from an interdisciplinary perspective. The concept and chronological history of “health” is then explored, based on the World Health Organization’s definition. Combining these concepts, the human–nature relationship and its impact on human’s health are then explored through a developing conceptual model. It is argued that using an interdisciplinary perspective can facilitate a deeper understanding of the complexities involved for attaining optimal health at the human–environmental interface

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

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

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

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

Additive and interaction effects at three amino acid positions in HLA-DQ and HLA-DR molecules drive type 1 diabetes risk.

Variation in the human leukocyte antigen (HLA) genes accounts for one-half of the genetic risk in type 1 diabetes (T1D). Amino acid changes in the HLA-DR and HLA-DQ molecules mediate most of the risk, but extensive linkage disequilibrium complicates the localization of independent effects. Using 18,832 case-control samples, we localized the signal to 3 amino acid positions in HLA-DQ and HLA-DR. HLA-DQβ1 position 57 (previously known; P = 1 × 10(-1,355)) by itself explained 15.2% of the total phenotypic variance. Independent effects at HLA-DRβ1 positions 13 (P = 1 × 10(-721)) and 71 (P = 1 × 10(-95)) increased the proportion of variance explained to 26.9%. The three positions together explained 90% of the phenotypic variance in the HLA-DRB1-HLA-DQA1-HLA-DQB1 locus. Additionally, we observed significant interactions for 11 of 21 pairs of common HLA-DRB1-HLA-DQA1-HLA-DQB1 haplotypes (P = 1.6 × 10(-64)). HLA-DRβ1 positions 13 and 71 implicate the P4 pocket in the antigen-binding groove, thus pointing to another critical protein structure for T1D risk, in addition to the HLA-DQ P9 pocket.This research utilizes resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases (NIAID), National Human Genome Research Institute (NHGRI), National Institute of Child Health and Human Development (NICHD), and Juvenile Diabetes Research Foundation International (JDRF) and supported by U01 DK062418. This work is supported in part by funding from the National Institutes of Health (5R01AR062886-02 (PIdB), 1R01AR063759 (SR), 5U01GM092691-05 (SR), 1UH2AR067677-01 (SR), R01AR065183 (PIWdB)), a Doris Duke Clinical Scientist Development Award (SR), the Wellcome Trust (JAT) and the National Institute for Health Research (JAT and JMMH), and a Vernieuwingsimpuls VIDI Award (016.126.354) from the Netherlands Organization for Scientific Research (PIWdB). TLL was supported by the German Research Foundation (LE 2593/1-1 and LE 2593/2-1).This is the accepted manuscript. The final version is available at http://www.nature.com/ng/journal/v47/n8/full/ng.3353.html

Validity of wearable physical activity monitors during activities of daily living

PURPOSE: To evaluate the validity of wearable activity monitors in SPT and EE under free-living environment. PURPOSE: To evaluate the validity of wearable activity monitors in SPT and EEunder free-living environment. METHODS: Thirty-nine (24.9+5.4 years) healthymales (n=26) and females (n=11) participated in this study. Total SPT and EE weremeasured by eight monitors; Nike+Fuel Band SE (NFB), Garmin VivoFit (VF), MisfitShine (MF), Fitbit Flex (FF), Jawbone UP (JU), Basis B1 (BB1), Polar Loop (PL), andSense Wear Armband Mini (SWA). The monitors were worn for at least 23 hours to beincluded in final data analysis and no PA restriction was applied. The SWA and a sleeplog were used as a criterion measure for SPT and EE, respectively. RESULTS: Total 24hours of EE (Kcal) (means±SD) were 3234.51+977, 2352.2 ±423, 2291.4±567,2679.8±752, 1955.4±251, 2950.9±864, 2724.9 ±627, 2822.1±525 for SWA, VF, JU,PL, BB1, FB, NFB, and MF, respectively. Mean absolute percent errors (MAPE) werecalculated (means±SD) 23.4%±8.0, 24.2%±8.8, 14.0% ±9.7, 28.9% ±22.0,17.5%±12.1, 16.9%±12.8, and 17.7%±15.0 for the VF, JU, PL, BB1, FB, NFB, andMF, respectively. SPT in minutes (mean±SD) were 481±83.32, 370.1+86.9,432.9±93.2, 467.7 ±51.2, 440.6±85.7, 424.6±103.3, 480.3±128.6, 436.6±35.3, and436.2±78.2 for the log, SWA, SWA laying down, VF, JU, PL, BB1, FB, and NFB,respectively. MAPE were calculated for SPT (mean±SD) 22.77% ±13.6,12.96±11.510.58% ±25.1, 11.6%±9.3, 18.2%±16.4, 14.6%±7.7, 8.7%±9.3, and13.5%±9.9 for the SWA, SWA laying down, VF, JU, PL, BB1, FB, and MF,respectively. ANOVA and post-hoc analyses with LSD indicated no significantdifferences were found with the FB, NFB, and MF in EE estimates. Additional post-hocanalyses with LSD for SPT revealed no significant difference (P\u3e.05) in all monitorsexcept SWA. CONCLUSION: The present study indicates that the FF, MS, and NFBare the most accurate wearable activity monitors when estimating EE and all monitorsprovide reasonable estimates of sleep period time, except SWA

On the track for an efficient detection of Escherichia coli in water : A review on PCR-based methods

Ensuring water safety is an ongoing challenge to public health providers. Assessing the presence of fecal contamination indicators in water is essential to protect public health from diseases caused by waterborne pathogens. For this purpose, the bacteria Escherichia coli has been used as the most reliable indicator of fecal contamination in water. The methods currently in use for monitoring the microbiological safety of water are based on culturing the microorganisms. However, these methods are not the desirable solution to prevent outbreaks as they provide the results with a considerable delay, lacking on specificity and sensitivity. Moreover, viable but non-culturable microorganisms, which may be present as a result of environmental stress or water treatment processes, are not detected by culture-based methods and, thus, may result in false-negative assessments of E. coli in water samples. These limitations may place public health at significant risk, leading to substantial monetary losses in health care and, additionally, in costs related with a reduced productivity in the area affected by the outbreak, and in costs supported by the water quality control departments involved. Molecular methods, particularly polymerase chain reaction-based methods, have been studied as an alternative technology to overcome the current limitations, as they offer the possibility to reduce the assay time, to improve the detection sensitivity and specificity, and to identify multiple targets and pathogens, including new or emerging strains. The variety of techniques and applications available for PCR-based methods has increased considerably and the costs involved have been substantially reduced, which together have contributed to the potential standardization of these techniques. However, they still require further refinement in order to be standardized and applied to the variety of environmental waters and their specific characteristics. The PCR-based methods under development for monitoring the presence of E. coli in water are here discussed. Special emphasis is given to methodologies that avoid pre-enrichment during the water sample preparation process so that the assay time is reduced and the required legislated sensitivity is achieved. The advantages and limitations of these methods are also reviewed, contributing to a more comprehensive overview toward a more conscious research in identifying E. coli in water.Diana Mendes (SFRH/BDE/33752/2009) was recipient of a fellowship from the Fundacao para a Ciencia e a Tecnologia (FCT, Portugal) and Frilabo, Lda. The authors thank Tatiana Aguiar (Centre of Biological Engineering) for English proofreading, the financial support from the Project "Desenvolvimento de um kit de detecao e quantificacao de E. coli e bacterias coliformes em aguas", Ref. 2009/5787, Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER, the FCT Strategic Project PEst-OE/EQB/LA0023/2013 and the Project "Biolnd-Biotechnology and Bioengineering for improved Industrial and processes", REF. NORTE-07-0124-FEDER-000028 Co-funded by the Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER

How accurate are the wrist-based heart rate monitors during walking and running activities? Are they accurate enough?

Background Heart rate (HR) monitors are valuable devices for fitness-orientated individuals. There has been a vast influx of optical sensing blood flow monitors claiming to provide accurate HR during physical activities. These monitors are worn on the arm and wrist to detect HR with photoplethysmography (PPG) techniques. Little is known about the validity of these wearable activity trackers. Aim Validate the Scosche Rhythm (SR), Mio Alpha (MA), Fitbit Charge HR (FH), Basis Peak (BP), Microsoft Band (MB), and TomTom Runner Cardio (TT) wireless HR monitors. Methods 50 volunteers (males: n=32, age 19–43 years; females: n=18, age 19–38 years) participated. All monitors were worn simultaneously in a randomised configuration. The Polar RS400 HR chest strap was the criterion measure. A treadmill protocol of one 30 min bout of continuous walking and running at 3.2, 4.8, 6.4, 8.0, and 9.6 km/h (5 min at each protocol speed) with HR manually recorded every minute was completed. Results For group comparisons, the mean absolute percentage error values were: 3.3%, 3.6%, 4.0%, 4.6%, 4.8% and 6.2% for TT, BP, RH, MA, MB and FH, respectively. Pearson product-moment correlation coefficient (r) was observed: r=0.959 (TT), r=0.956 (MB), r=0.954 (BP), r=0.933 (FH), r=0.930 (RH) and r=0.929 (MA). Results from 95% equivalency testing showed monitors were found to be equivalent to those of the criterion HR (±10% equivalence zone: 98.15–119.96). Conclusions The results demonstrate that the wearable activity trackers provide an accurate measurement of HR during walking and running activities