Radiative Decay Modes of the D0D^{0} Meson

Using data recorded by the CLEO-II detector at CESR we have searched for four radiative decay modes of the $D^0$ meson: $D^0\to\phi\gamma$, $D^0\to\omega\gamma$, $D^0\to\bar{K}^{*}\gamma$, and $D^0\to\rho^0\gamma$. We obtain 90% CL upper limits on the branching ratios of these modes of $1.9\times 10^{-4}$, $2.4\times 10^{-4}$, $7.6\times 10^{-4}$ and $2.4\times 10^{-4}$ respectively.Comment: 15 page postscript file, postscript file also available through http://w4.lns.cornell.edu/public/CLN

Developmental expression of orphan g protein-coupled receptor 50 in the mouse brain

[Image: see text] Mental disorders have a complex etiology resulting from interactions between multiple genetic risk factors and stressful life events. Orphan G protein-coupled receptor 50 (GPR50) has been identified as a genetic risk factor for bipolar disorder and major depression in women, and there is additional genetic and functional evidence linking GPR50 to neurite outgrowth, lipid metabolism, and adaptive thermogenesis and torpor. However, in the absence of a ligand, a specific function has not been identified. Adult GPR50 expression has previously been reported in brain regions controlling the HPA axis, but its developmental expression is unknown. In this study, we performed extensive expression analysis of GPR50 and three protein interactors using rt-PCR and immunohistochemistry in the developing and adult mouse brain. Gpr50 is expressed at embryonic day 13 (E13), peaks at E18, and is predominantly expressed by neurons. Additionally we identified novel regions of Gpr50 expression, including brain stem nuclei involved in neurotransmitter signaling: the locus coeruleus, substantia nigra, and raphe nuclei, as well as nuclei involved in metabolic homeostasis. Gpr50 colocalizes with yeast-two-hybrid interactors Nogo-A, Abca2, and Cdh8 in the hypothalamus, amygdala, cortex, and selected brain stem nuclei at E18 and in the adult. With this study, we identify a link between GPR50 and neurotransmitter signaling and strengthen a likely role in stress response and energy homeostasis

Climate Change, Human Health, and Resilience in the Holocene

Climate change is an indisputable threat to human health, especially for societies already confronted with rising social inequality, political and economic uncertainty, and a cascade of concurrent environmental challenges. Archaeological data about past climate and environment provide an important source of evidence about the potential challenges humans face and the long-term outcomes of alternative short-term adaptive strategies. Evidence from well-dated archaeological human skeletons and mummified remains speaks directly to patterns of human health over time through changing circumstances. Here, we describe variation in human epidemiological patterns in the context of past rapid climate change (RCC) events and other periods of past environmental change. Case studies confirm that human communities responded to environmental changes in diverse ways depending on historical, sociocultural, and biological contingencies. Certain factors, such as social inequality and disproportionate access to resources in large, complex societies may influence the probability of major sociopolitical disruptions and reorganizations—commonly known as “collapse.” This survey of Holocene human–environmental relations demonstrates how flexibility, variation, and maintenance of Indigenous knowledge can be mitigating factors in the face of environmental challenges. Although contemporary climate change is more rapid and of greater magnitude than the RCC events and other environmental changes we discuss here, these lessons from the past provide clarity about potential priorities for equitable, sustainable development and the constraints of modernity we must address

Climate change, human health, and resilience in the Holocene

Climate change is an indisputable threat to human health, especially for societies already confronted with rising social inequality, political and economic uncertainty, and a cascade of concurrent environmental challenges. Archaeological data about past climate and environment provide an important source of evidence about the potential challenges humans face and the long-term outcomes of alternative short-term adaptive strategies. Evidence from well-dated archaeological human skeletons and mummified remains speaks directly to patterns of human health over time through changing circumstances. Here, we describe variation in human epidemiological patterns in the context of past rapid climate change (RCC) events and other periods of past environmental change. Case studies confirm that human communities responded to environmental changes in diverse ways depending on historical, sociocultural, and biological contingencies. Certain factors, such as social inequality and disproportionate access to resources in large, complex societies may influence the probability of major sociopolitical disruptions and reorganizations—commonly known as “collapse.” This survey of Holocene human–environmental relations demonstrates how flexibility, variation, and maintenance of Indigenous knowledge can be mitigating factors in the face of environmental challenges. Although contemporary climate change is more rapid and of greater magnitude than the RCC events and other environmental changes we discuss here, these lessons from the past provide clarity about potential priorities for equitable, sustainable development and the constraints of modernity we must address

Comparative Effectiveness Research: An Empirical Study of Trials Registered in ClinicalTrials.gov

Background The $1.1 billion investment in comparative effectiveness research will reshape the evidence-base supporting decisions about treatment effectiveness, safety, and cost. Defining the current prevalence and characteristics of comparative effectiveness (CE) research will enable future assessments of the impact of this program. Methods We conducted an observational study of clinical trials addressing priority research topics defined by the Institute of Medicine and conducted in the US between 2007 and 2010. Trials were identified in ClinicalTrials.gov. Main outcome measures were the prevalence of comparative effectiveness research, nature of comparators selected, funding sources, and impact of these factors on results. Results 231 (22.3%; 95% CI 19.8%–24.9%) studies were CE studies and 804 (77.7%; 95% CI, 75.1%–80.2%) were non-CE studies, with 379 (36.6%; 95% CI, 33.7%–39.6%) employing a placebo control and 425 (41.1%; 95% CI, 38.1%–44.1%) no control. The most common treatments examined in CE studies were drug interventions (37.2%), behavioral interventions (28.6%), and procedures (15.6%). Study findings were favorable for the experimental treatment in 34.8% of CE studies and greater than twice as many (78.6%) non-CE studies (P<0.001). CE studies were more likely to receive government funding (P = 0.003) and less likely to receive industry funding (P = 0.01), with 71.8% of CE studies primarily funded by a noncommercial source. The types of interventions studied differed based on funding source, with 95.4% of industry trials studying a drug or device. In addition, industry-funded CE studies were associated with the fewest pediatric subjects (P<0.001), the largest anticipated sample size (P<0.001), and the shortest study duration (P<0.001). Conclusions In this sample of studies examining high priority areas for CE research, less than a quarter are CE studies and the majority is supported by government and nonprofits. The low prevalence of CE research exists across CE studies with a broad array of interventions and characteristics.National Library of Medicine (U.S.) (5G08LM009778)National Institutes of Health (U.S.

Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management

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

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