Human Breast Milk Contamination with Phthalates and Alterations of Endogenous Reproductive Hormones in Infants Three Months of Age

Phthalates adversely affect the male reproductive system in animals. We investigated whether phthalate monoester contamination of human breast milk had any influence on the postnatal surge of reproductive hormones in newborn boys as a sign of testicular dysgenesis. DESIGN: We obtained biologic samples from a prospective Danish–Finnish cohort study on cryptorchidism from 1997 to 2001. We analyzed individual breast milk samples collected as additive aliquots 1–3 months postnatally (n = 130; 62 cryptorchid/68 healthy boys) for phthalate monoesters [mono-methyl phthalate (mMP), mono-ethyl phthalate (mEP), mono-n-butyl phthalate (mBP), mono-benzyl phthalate (mBzP), mono-2-ethylhexyl phthalate (mEHP), mono-isononyl phthalate (miNP)]. We analyzed serum samples (obtained in 74% of all boys) for gonadotropins, sex-hormone binding globulin (SHBG), testosterone, and inhibin B. RESULTS: All phthalate monoesters were found in breast milk with large variations [medians (minimum–maximum)]: mMP 0.10 (< 0.01–5.53 μg/L), mEP 0.95 (0.07–41.4 μg/L), mBP 9.6 (0.6–10,900 μg/L), mBzP 1.2 (0.2–26 μg/L), mEHP 11 (1.5–1,410 μg/L), miNP 95 (27–469 μg/L). Finnish breast milk had higher concentrations of mBP, mBzP, mEHP, and Danish breast milk had higher values for miNP (p = 0.0001–0.056). No association was found between phthalate monoester levels and cryptorchidism. However, mEP and mBP showed positive correlations with SHBG (r = 0.323, p = 0.002 and r = 0.272, p = 0.01, respectively); mMP, mEP, and mBP with LH:free testosterone ratio (r = 0.21–0.323, p = 0.002–0.044) and miNP with luteinizing hormone (r = 0.243, p = 0.019). mBP was negatively correlated with free testosterone (r = −0.22, p = 0.033). Other phthalate monoesters showed similar but nonsignificant tendencies. CONCLUSIONS: Our data on reproductive hormone profiles and phthalate exposures in newborn boys are in accordance with rodent data and suggest that human Leydig cell development and function may also be vulnerable to perinatal exposure to some phthalates. Our findings are also in line with other recent human data showing incomplete virilization in infant boys exposed to phthalates prenatally

Nonexistence of marginally trapped surfaces and geons in 2+1 gravity

We use existence results for Jang's equation and marginally outer trapped surfaces (MOTSs) in 2+1 gravity to obtain nonexistence of geons in 2+1 gravity. In particular, our results show that any 2+1 initial data set, which obeys the dominant energy condition with cosmological constant \Lambda \geq 0 and which satisfies a mild asymptotic condition, must have trivial topology. Moreover, any data set obeying these conditions cannot contain a MOTS. The asymptotic condition involves a cutoff at a finite boundary at which a null mean convexity condition is assumed to hold; this null mean convexity condition is satisfied by all the standard asymptotic boundary conditions. The results presented here strengthen various aspects of previous related results in the literature. These results not only have implications for classical 2+1 gravity but also apply to quantum 2+1 gravity when formulated using Witten's solution space quantization.Comment: v3: Elements from the original two proofs of the main result have been combined to give a single proof, thereby circumventing an issue with the second proof associated with potential blow-ups of solutions to Jang's equation. To appear in Commun. Math. Phy

Некоторые аспекты эффективности обучения при переходе от очной формы обучения к дистанционной

ВЫСШЕЕ МЕДИЦИНСКОЕ ОБРАЗОВАНИЕОБРАЗОВАНИЕ МЕДИЦИНСКОЕ /МЕТОДЫОЧНАЯ ФОРМА ОБУЧЕНИЯЗАОЧНАЯ ФОРМА ОБУЧЕНИЯДИСТАНЦИОННОЕ ОБУЧЕНИЕ /МЕТОДЫОБРАЗОВАТЕЛЬНЫЙ ПРОЦЕССХИМИЯ (ДИСЦИПЛИНА

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (??=??0.71 to ?1.37; P?<?0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (??=??0.95, P?=?0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P?=?0.0032, 8.9?×?10?6, 1.7?×?10?9, 3.5?×?10?12 and 1.0?×?10?4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes.1000BRAINS is a populationbased cohort based on the Heinz-Nixdorf Recall Study and is supported in part by the German National Cohort. We thank the Heinz Nixdorf Foundation (Germany) for their generous support in terms of the Heinz Nixdorf Study. The HNR study is also supported by the German Ministry of Education and Science (FKZ 01EG940), and the German Research Council (DFG, ER 155/6-1). The authors are supported by the Initiative and Networking Fund of the Helmholtz Association (Svenja Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 7202070 (Human Brain Project SGA1; Katrin Amunts, Sven Cichon). This work was further supported by the German Federal Ministry of Education and Research (BMBF) through the Integrated Network 592 I. E. Sønderby et al. IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders) under the auspices of the e:Med Program (grant 01ZX1314A to M.M.N. and S.C.), and by the Swiss National Science Foundation (SNSF, grant 156791 to S.C.). 16p.11.2 European Consortium: B.D. is supported by the Swiss National Science Foundation (NCCR Synapsy, project grant Nr 32003B_159780) and Foundation Synapsis. LREN is very grateful to the Roger De Spoelberch and Partridge Foundations for their generous financial support. This work was supported by grants from the Simons Foundation (SFARI274424) and the Swiss National Science Foundation (31003A_160203) to A.R. and S.J. Betula: The relevant Betula data collection and analyses were supported by a grant from the Knut & Alice Wallenberg (KAW) to L. Nyberg. Brainscale: the Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Dorret Boomsma), 51.02.060 (Hilleke Hulshoff Pol), 668.772 (Dorret Boomsma & Hilleke Hulshoff Pol); NWO/SPI 56-464-14192 (Dorret Boomsma), the European Research Council (ERC-230374) (Dorret Boomsma), High Potential Grant Utrecht University (Hilleke Hulshoff Pol), NWO Brain and Cognition 433-09-220 (Hilleke Hulshoff Pol). Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers of the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience departments of the Radboud university medical centre and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative has received supported from the participating departments and centres and from external grants, i.e., the Biobanking and Biomolecular Resources Research Infrastructure (the Netherlands) (BBMRI-NL), the Hersenstichting Nederland, and the Netherlands Organisation for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant ‘Language in Interaction’, the European Community’s Seventh Framework Programme (FP7/2007–2013) under grant agreements n° 602450 (IMAGEMEND), n°278948 (TACTICS), and n°602805 (Aggressotype) as well as from the European Community’s Horizon 2020 programme under grant agreement n° 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. COBRE: This work was supported by a NIH COBRE Phase I grant (1P20RR021938, Lauriello, PI and 2P20GM103472, Calhoun, PI) awarded to the Mind Research Network. We wish to express our gratitude to numerous investigators who were either external consultants to the Cores and projects, mentors on the projects, members of the external advisory committee and members of the internal advisory committee. Decode: The research leading to these results has received financial contribution from the European Union’s Seventh Framework Programme (EU-FP7/2007–2013), EU-FP7 funded grant no. 602450 (IMAGEMEND) as well as support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no.115300 (EUAIMS). DemGene: Norwegian Health Association and Research Council of Norway. Dublin: Work was supported by Science Foundation Ireland (SFI grant 12/IP/1359 to Gary Donohoe and SFI08/IN.1/B1916-Corvin to Aidan C Corvin) and the European Research Council (ERC-StG-2015-677467). EPIGEN-UK (SMS, CL): The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health’s NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner, and the Epilepsy Society for supporting CL. Haavik: The work at the K.G.Jebsen center for neuropsychiatric disorders at the University of Bergen, Norway, was supported by Stiftelsen K.G. Jebsen, European Community’s Seventh Framework Program under grant agreement no 602805 and the H2020 Research and Innovation Program under grant agreement numbers 643051 and 667302. HUNT: The HUNT Study is a collaboration between HUNT Research Centre (Faculty of Medicine, Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. IMAGEN: The work received support from the European Union-funded FP6Integrated Project IMAGEN (Reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), the FP7 projects IMAGEMEND (602450; IMAging GEnetics for MENtal Disorders) and MATRICS (603016), the Innovative Medicine Initiative Project EUAIMS (115300), the Medical Research Council Grant ‘c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the Swedish Research Council FORMAS, the Medical Research Council, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152; 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL), the Deutsche Forschungsgemeinschaft (DFG grants SM 80/7-1, SM 80/7-2, SFB 940/1). Further support was provided by grants from: ANR (project AF12-NEUR0008-01—WM2NA, and ANR-12-SAMA-0004), the Fondation de France, the Fondation pour la Recherche Médicale, the Mission Interministérielle de Lutte-contreles-Drogues-et-les-Conduites-Addictives (MILDECA), the AssistancePublique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1), and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. MCIC: This work was supported primarily by the Department of Energy DE-FG02-99ER62764 through its support of the Mind Research Network and the consortium as well as by the National Association for Research in Schizophrenia and Affective Disorders (NARSAD) Young Investigator Award (to SE) as well as through the Blowitz-Ridgeway and Essel Foundations, and through NWO ZonMw TOP 91211021, the DFG research fellowship (to SE), the Mind Research Network, National Institutes of Health through NCRR 5 month-RR001066 (MGH General Clinical Research Center), NIMH K08 MH068540, the Biomedical Informatics Research Network with NCRR Supplements to P41 RR14075 (MGH), M01 RR 01066 (MGH), NIBIB R01EB006841 (MRN), R01EB005846 (MRN), 2R01 EB000840 (MRN), 1RC1MH089257 (MRN), as well as grant U24 RR021992. NCNG: this sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the K.G. Jebsen Foundation, the Research Council of Norway, to SLH, VMS and TE. The Bergen group was supported by grants from the Western Norway Regional Health Authority (Grant 911593 to AL, Grant 911397 and 911687 to AJL). NESDA: Funding for NESDA was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10-000-1002); the Center for Medical Systems Biology (CSMB, NWO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University’s Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, R01D0042157-01A, MH081802, 16p11.2 distal copy number variant brain structure 593 Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health.Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. NTR: The NTR study was supported by the Netherlands Organization for Scientific Research (NWO), MW904-61-193 (Eco de Geus & Dorret Boomsma), MaGW-nr: 400-07- 080 (Dennis van ‘t Ent), MagW 480-04-004 (Dorret Boomsma), NWO/SPI 56-464-14192 (Dorret Boomsma), the European Research Council, ERC-230374 (Dorret Boomsma), and Amsterdam Neuroscience. OATS: OATS (Older Australian Twins Study) was facilitated by access to Twins Research Australia, which is funded by a National Health and Medical Research Council (NHMRC) Enabling Grant 310667. OATS is also supported via a NHMRC/Australian Research Council Strategic Award (401162) and a NHMRC Project Grant (1045325). DNA extraction was performed by Genetic Repositories Australia, which was funded by a NHMRC Enabling Grant (401184). OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. PAFIP: PAFIP data were collected at the Hospital Universitario Marqués de Valdecilla, University of Cantabria, Santander, Spain, under the following grant support: Carlos III Health Institute PIE14/00031 and SAF2013-46292-R and SAF2015-71526-REDT. We wish to acknowledge IDIVAL Neuroimaging Unit for imaging acquirement and analysis.We want to particularly acknowledge the patients and the BioBankValdecilla (PT13/0010/0024) integrated in the Spanish National Biobanks Network for its collaboration. QTIM: The QTIM study was supported by grants from the US National Institute of Child Health and Human Development (R01 HD050735) and the Australian National Health and Medical Research Council (NHMRC) (486682, 1009064). Genotyping was supported by NHMRC (389875). Lachlan Strike is supported by an Australian Postgraduate Award (APA). AFM is supported by NHMRC CDF 1083656. We thank the twins and siblings for their participation, the many research assistants, as well as the radiographers, for their contribution to data collection and processing of the samples. SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, 01ZZ0403 and 01ZZ0701), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg- West Pomerania. Whole-body MR imaging was supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. StrokeMRI: StrokeMRI has been supported by the Research Council of Norway (249795), the South-Eastern Norway Regional Health Authority (2014097, 2015044, 2015073) and the Norwegian ExtraFoundation for Health and Rehabilitation. TOP: TOP is supported by the Research Council of Norway (223273, 213837, 249711), the South East Norway Health Authority (2017-112), the Kristian Gerhard Jebsen Stiftelsen (SKGJ‐MED‐008) and the European Community’s Seventh Framework Programme (FP7/2007–2013), grant agreement no. 602450 (IMAGEMEND). We acknowledge the technical support and service from the Genomics Core Facility at the Department of Clinical Science, the University of Bergen for the 16p11.2 European Consortium; for the ENIGMA-CNV working group Ida Elken Sønderby (NORMENT, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway), Ómar Gústafsson (deCODE Genetics/Amgen, Reykjavik, Iceland), Nhat Trung Doan (NORMENT, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway), Derrek Paul Hibar (Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, USA), (Janssen Research and Development, La Jolla, CA USA, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, U. S.A), Sandra Martin-Brevet (Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Rue du Bugnon 46, 1011 Lausanne, Switzerland), Abdel Abdellaoui (Biological Psychology, Vrije Universiteit Amsterdam, van Boechorststraat 1, 1081 BT Amsterdam, The Netherlands), (Department of Psychiatry, Academic Medical Center, Amsterdam, the Netherlands), David Ames (National Ageing Research Institute, Melbourne, Australia), (Academic Unit for Psychiatry of Old Age, University of Melbourne, Melbourne, Australia), Katrin Amunts (Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Wilhelm-Johnen-Str., 52425 Juelich, Germany), (C. and O. Vogt Institute for Brain Research, Medical Faculty, University of Dusseldorf, Merowingerplatz 1A, 40225 Dusseldorf, Germany), (JARA-BRAIN, Juelich-Aachen Research Alliance, Wilhelm-Johnen-Str., 52425 Juelich, Germany), Michael Andersson (Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187 Umeå, Sweden), Nicola J. Armstrong (Mathematics and Statistics, Murdoch University, Perth, Australia), Manon Bernard (The Hospital for Sick Children, University of Toronto, Toronto, M5G 1X8, Canada), Nicholas Blackburn (South Texas Diabetes and Obesity Institute, Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, One West University Blvd., 78520 Brownsville, TX, USA), John Blangero (South Texas Diabetes and Obesity Institute, Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, One West University Blvd., 78520 Brownsville, TX, USA), Dorret I Boomsma (Netherlands Twin Register, Vrije Universiteit, van der Boechorststraat 1, 1081BT Amsterdam, Netherlands), Janita Bralten (Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands), Hans-Richard Brattbak (Department of Clinical Science, University of Bergen, Bergen, Norway), (Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway), Henry Brodaty (Centre for Healthy Brain Ageing and Dementia Collaborative Research Centre, UNSW, Sydney, Australia), Rachel M. Brouwer (Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands), Robin Bülow (Department of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany), Vince Calhoun (The Mind Research Network, The University of New Mexico, Albuquerque, NM), Svenja Caspers (Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Wilhelm-Johnen-Str., 52425 Juelich, Germany), (C. and O. Vogt Institute for Brain Research, Medical Faculty, University of Dusseldorf, Merowingerplatz 1A, 40225 Dusseldorf, Germany), (JARA-BRAIN, Juelich-Aachen Research Alliance, Wilhelm-Johnen-Str., 52425 Juelich, Germany), Gianpiero Cavalleri (The Royal College of Surgeons in Ireland, 123 St Stephen's Green, Dublin 2, Ireland), Chi-Hua Chen (Department of Radiology, University of California San Diego, La Jolla, USA), (Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, USA), Sven Cichon (Institute of Neuroscience and Medicine (INM-1), Structural and Functional Organisation of the Brain, Genomic Imaging, Research Centre Juelich, Leo-Brandt-Strasse 5, 52425 Jülich, Germany), (Human Genomics Research Group, 594 I. E. Sønderby et al. Department of Biomedicine, University of Basel, Hebelstrasse 20, 4031 Basel, Switzerland), (Institute of Medical Genetics and Pathology, University Hospital Basel, Schönbeinstrasse 40, 4031 Basel, Switzerland), Simone Ciufolini (Psychosis Studies, Insitute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespingy Park, SE5 8AF London, United Kingdom), Aiden Corvin (Neuropsychiatric Genetics Research Group, Discipline of Psychiatry, School of Medicine, Trinity College Dublin, Dublin 2, Ireland.), Benedicto Crespo-Facorro (Department of Medicine and Psychiatry, University Hospital Marque?s de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, 39008 Santander, Spain), (CIBERSAM (Centro Investigación Biomédica en Red Salud Mental), Santander, 39011, Spain), Joanne E. Curran (South Texas Diabetes and Obesity Institute, Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, One West University Blvd., 78520 Brownsville, TX, USA), Anders M Dale (Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, USA), Shareefa Dalvie (Department of Psychiatry and Mental Health, Anzio Road, 7925 Cape Town, South Africa), Paola Dazzan (Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, SE5 8AF London, United Kingdom), (National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, United Kingdom), Eco JC de Geus (Department of Biological Psychology, Behavioral and Movement Sciences, Vrije Universiteit, van der Boechorststraat 1, 1081 BT Amsterdam, Netherlands), (Amsterdam Neuroscience, VU University medical center, van der Boechorststraat 1, 1081 BT Amsterdam, NH, Netherlands), Greig I. de Zubicaray (Faculty of Health and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia), Sonja M.C. de Zwarte (Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands), Norman Delanty (The Royal College of Surgeons in Ireland, 123 St Stephen's Green, Dublin 2, Ireland), (Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology and Center for Neuroscience, University of California at Davis, 4860 Y Street, Suite 3700, Sacramento, California 95817, USA.), Anouk den Braber (Department of Biological Psychology, Behavioral and Movement Sciences, Vrije Universiteit, van der Boechorststraat 1, 1081 BT Amsterdam, Netherlands), (Alzheimer Center and Department of Neurology, VU University Medical Center, De Boelelaan 1105, 1081HV Amsterdam Amsterdam, Amsterdam), Sylvane Desrivières (Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom), Gary Donohoe (Cognitive Genetics

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P &lt; 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10-6, 1.7 × 10-9, 3.5 × 10-12 and 1.0 × 10-4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes

Stationary Black Holes: Uniqueness and Beyond

The spectrum of known black-hole solutions to the stationary Einstein equations has been steadily increasing, sometimes in unexpected ways. In particular, it has turned out that not all black-hole-equilibrium configurations are characterized by their mass, angular momentum and global charges. Moreover, the high degree of symmetry displayed by vacuum and electro-vacuum black-hole spacetimes ceases to exist in self-gravitating non-linear field theories. This text aims to review some developments in the subject and to discuss them in light of the uniqueness theorem for the Einstein-Maxwell system.Comment: Major update of the original version by Markus Heusler from 1998. Piotr T. Chru\'sciel and Jo\~ao Lopes Costa succeeded to this review's authorship. Significantly restructured and updated all sections; changes are too numerous to be usefully described here. The number of references increased from 186 to 32

Another Avenue for Anatomy of Income Comparisons : Evidence from Hypothetical Choice Experiments

September 2010, Revised December 2010, Secondly Revised November 2011, Thirdly Revised May 2012, Fourthly Revised March 2013

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines

An Active Site Aromatic Triad in Escherichia coli DNA Pol IV Coordinates Cell Survival and Mutagenesis in Different DNA Damaging Agents

DinB (DNA Pol IV) is a translesion (TLS) DNA polymerase, which inserts a nucleotide opposite an otherwise replication-stalling N2-dG lesion in vitro, and confers resistance to nitrofurazone (NFZ), a compound that forms these lesions in vivo. DinB is also known to be part of the cellular response to alkylation DNA damage. Yet it is not known if DinB active site residues, in addition to aminoacids involved in DNA synthesis, are critical in alkylation lesion bypass. It is also unclear which active site aminoacids, if any, might modulate DinB's bypass fidelity of distinct lesions. Here we report that along with the classical catalytic residues, an active site “aromatic triad”, namely residues F12, F13, and Y79, is critical for cell survival in the presence of the alkylating agent methyl methanesulfonate (MMS). Strains expressing dinB alleles with single point mutations in the aromatic triad survive poorly in MMS. Remarkably, these strains show fewer MMS- than NFZ-induced mutants, suggesting that the aromatic triad, in addition to its role in TLS, modulates DinB's accuracy in bypassing distinct lesions. The high bypass fidelity of prevalent alkylation lesions is evident even when the DinB active site performs error-prone NFZ-induced lesion bypass. The analyses carried out with the active site aromatic triad suggest that the DinB active site residues are poised to proficiently bypass distinctive DNA lesions, yet they are also malleable so that the accuracy of the bypass is lesion-dependent

Mapping the Scope of Software Interventions for Moderate Internet Use on Mobile Devices

ICT is expected to form 21% of global electricity demand in 2030, and history has shown that efficiency gains in Internet infrastructure aiming to curtail such impacts are far outstripped by the growth in data traffic. We need to reduce demand for Internet connectivity, yet encouraging moderate interactions with digital devices and online services could potentially benefit users. HCI designs have been suggested for moderate interactions and Internet usage, most commonly on smartphones - but it's currently unclear whether these interventions can actually be implemented and tested to understand the user and environmental impacts. In this paper, we review features for understanding and manipulating data traffic in accordance with the stock Android and iOS development libraries to better scope the potential for implementing moderate and sustainable digital experiences. Specifically, we outline the intervention features plausible for Android implementation, and we provide reasoning for why iOS is currently too restrictive