Beyond The Gap:Placing Biodiversity Finance in the Global Economy

Governments and conservation organisations often point to a large gap between existing financial resources and the resources needed to achieve biodiversity objectives. But the gap is almost always presented without context, as though biodiversity loss will be resolved through increased funding alone. To illuminate crucial pathways for transformative change, this report examines the political and economic dimensions of biodiversity loss. “Beyond the gap: placing biodiversity finance in the global economy” addresses two questions: how does the organization of the global economy drive biodiversity loss, and how has existing biodiversity finance performed? Trade, investment and financial regulation (or lack thereof), global economic pressures that push biodiverse countries into debt, and inequality across racialized, gender, class and colonial lines, all drive biodiversity loss and require urgent attention. Instead of transformation, a series of voluntary measures and market-based mechanisms such as payments for ecosystem services or blended finance schemes have been presented as tools to span the resource gap. This report shows that these efforts are marginal at best, and, at worst, entrench the power of rich world governments and non-state institutions like banks, large international NGOs, and supranationals. It is apparent that we must move “beyond the gap”. Only by placing biodiversity loss in the global economy will it be possible to realize transformative, inclusive and equitable change. The authors offer concrete recommendations for negotiators, civil society organizations, and activist groups to push questions of biodiversity finance beyond the gap

Making Connections: A Handbook for Effective Formal Mentoring Programs in Academia

This book, Making Connections: A Handbook for Effective Formal Mentoring Programs in Academia, makes a unique and needed contribution to the mentoring field as it focuses solely on mentoring in academia. This handbook is a collaborative institutional effort between Utah State University’s (USU) Empowering Teaching Open Access Book Series and the Mentoring Institute at the University of New Mexico (UNM). This book is available through (a) an e-book through Pressbooks, (b) a downloadable PDF version on USU’s Open Access Book Series website), and (c) a print version available for purchase on the USU Empower Teaching Open Access page, and on Amazon

Human and mouse essentiality screens as a resource for disease gene discovery.

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery

Recommendations for enterovirus diagnostics and characterisation within and beyond Europe.

Enteroviruses (EV) can cause severe neurological and respiratory infections, and occasionally lead to devastating outbreaks as previously demonstrated with EV-A71 and EV-D68 in Europe. However, these infections are still often underdiagnosed and EV typing data is not currently collected at European level. In order to improve EV diagnostics, collate data on severe EV infections and monitor the circulation of EV types, we have established European non-polio enterovirus network (ENPEN). First task of this cross-border network has been to ensure prompt and adequate diagnosis of these infections in Europe, and hence we present recommendations for non-polio EV detection and typing based on the consensus view of this multidisciplinary team including experts from over 20 European countries. We recommend that respiratory and stool samples in addition to cerebrospinal fluid (CSF) and blood samples are submitted for EV testing from patients with suspected neurological infections. This is vital since viruses like EV-D68 are rarely detectable in CSF or stool samples. Furthermore, reverse transcriptase PCR (RT-PCR) targeting the 5'noncoding regions (5'NCR) should be used for diagnosis of EVs due to their sensitivity, specificity and short turnaround time. Sequencing of the VP1 capsid protein gene is recommended for EV typing; EV typing cannot be based on the 5'NCR sequences due to frequent recombination events and should not rely on virus isolation. Effective and standardized laboratory diagnostics and characterisation of circulating virus strains are the first step towards effective and continuous surveillance activities, which in turn will be used to provide better estimation on EV disease burden

FTO genetic variants, dietary intake and body mass index: insights from 177 330 individuals

FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177 330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m2, P = 1.9 × 10−105), and all participants (0.30 [0.30, 0.35] kg/m2, P = 3.6 × 10−107). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10−16), and relative weak associations with lower total energy intake (−6.4 [−10.1, −2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (−0.07 [−0.11, −0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10−9) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposit

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.NovartisEli Lilly and CompanyAstraZenecaAbbViePfizer UKCelgeneEisaiGenentechMerck Sharp and DohmeRocheCancer Research UKGovernment of CanadaArray BioPharmaGenome CanadaNational Institutes of HealthEuropean CommissionMinistère de l'Économie, de l’Innovation et des Exportations du QuébecSeventh Framework ProgrammeCanadian Institutes of Health Researc

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.Peer reviewe

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC

Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe