Pharmaceutical innovation and parallel trade

This paper was accepted for publication in the journal International Journal of Industrial Organization and the definitive published version is available at https://doi.org/10.1016/j.ijindorg.2014.02.009This paper proposes a North–South model to study the interaction between price regulation policies and parallel trade, with a particular focus on the pharmaceutical sector. We show that, under parallel trade, R&D investment can rise only when the South government takes into full account its impact both on investment and on the firm's decision to supply the regulated country. This arises because of a complete withdrawal from price regulation. When policy choices are endogenized, indeed the South wants to achieve this level of full commitment when it is large in size. When instead it is smaller in size, the South chooses an intermediate form of commitment whereby it anticipates its effect only on local distribution and delivery, but not on global R&D investment. As a response to these credible levels of price control commitments, the North reacts by allowing parallel imports from the South

Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10-8). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10-14), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10-10), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10-8), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10-8). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene

Mitigación con Sistemas Silvopastoriles en Latinoamérica: Aportes para la incorporación en los sistemas de Medición Reporte y Verificación bajo la CMNUCC

En Latinoamérica el 46% de las emisiones de GEI proviene del cambio de usos de la tierra y el 20% de la agricultura, en donde el 58% y el 70% de las emisiones son debidas a la ganadería. El continuo crecimiento de este sector (+32% previsto al 2050) ha impulsado la expansión de la frontera agropecuaria en los bosques, generando múltiples impactos ambientales entre los cuales se encuentra la emisión de Gases Efecto Invernadero (GEI). Sin embargo, el sector tiene un alto potencial de mitigación reconocido por políticas, estrategias y programas de mitigación nacionales como las Contribuciones Nacionalmente Determinadas (NDC) y de desarrollo sectorial como las Acciones de Mitigación nacionalmente Apropiadas (NAMA). Entre estas acciones se incluye la implementación de sistemas silvopastoriles, cuya medición monitoreo y reporte a escala nacional presenta un estado de avance muy limitado, dejando su aporte a la mitigación invisible. A través de un Grupo Técnico de Trabajo ad hoc se han analizado el avance de los países de la región en la incorporación de los sistemas silvopastoriles en los sistemas nacionales de Medición/Monitoreo, Reporte y Verificación (MRV) de los Inventarios Nacionales de Gases Efecto Invernadero, y los requerimientos a cumplir para esto, generando una hoja de ruta a corto-medio plazo así como unas orientaciones técnicas para reducir la brecha existente

Mitigación con Sistemas Silvopastoriles en Latinoamérica: Aportes para la incorporación en los sistemas de Medición Reporte y Verificación bajo la CMNUCC

En Latinoamérica el 46% de las emisiones de GEI proviene del cambio de usos de la tierra y el 20% de la agricultura, en donde el 58% y el 70% de las emisiones son debidas a la ganadería. El continuo crecimiento de este sector (+32% previsto al 2050) ha impulsado la expansión de la frontera agropecuaria en los bosques, generando múltiples impactos ambientales entre los cuales se encuentra la emisión de Gases Efecto Invernadero (GEI). Sin embargo, el sector tiene un alto potencial de mitigación reconocido por políticas, estrategias y programas de mitigación nacionales como las Contribuciones Nacionalmente Determinadas (NDC) y de desarrollo sectorial como las Acciones de Mitigación nacionalmente Apropiadas (NAMA). Entre estas acciones se incluye la implementación de sistemas silvopastoriles, cuya medición monitoreo y reporte a escala nacional presenta un estado de avance muy limitado, dejando su aporte a la mitigación invisible. A través de un Grupo Técnico de Trabajo ad hoc se han analizado el avance de los países de la región en la incorporación de los sistemas silvopastoriles en los sistemas nacionales de Medición/Monitoreo, Reporte y Verificación (MRV) de los Inventarios Nacionales de Gases Efecto Invernadero, y los requerimientos a cumplir para esto, generando una hoja de ruta a corto-medio plazo así como unas orientaciones técnicas para reducir la brecha existente

Language endangerment and language documentation in Africa

Non peer reviewe

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

Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103-14. ©2016 AACR

Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types.

UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis. SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.The Breast Cancer Association Consortium (BCAC), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL), and the Ovarian Cancer Association Consortium (OCAC) that contributed breast, prostate, and ovarian cancer data analyzed in this study were in part funded by Cancer Research UK [C1287/A10118 and C1287/A12014 for BCAC; C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, and C16913/A6135 for PRACTICAL; and C490/A6187, C490/A10119, C490/A10124, C536/A13086, and C536/A6689 for OCAC]. Funding for the Collaborative Oncological Gene-environment Study (COGS) infrastructure came from: the European Community's Seventh Framework Programme under grant agreement number 223175 (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the US National Institutes of Health (CA128978) and the Post-Cancer GWAS Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112), the US Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund [with donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07)]. Additional financial support for contributing studies is documented under Supplementary Financial Support.This is the author accepted manuscript. The final version is available from the American Association for Cancer Research via http://dx.doi.org/10.1158/2159-8290.CD-15-122