Isotopic ratios at z=0.68 from molecular absorption lines toward B 0218+357

Isotopic ratios of heavy elements are a key signature of the nucleosynthesis processes in stellar interiors. The contribution of successive generations of stars to the metal enrichment of the Universe is imprinted on the evolution of isotopic ratios over time. We investigate the isotopic ratios of carbon, nitrogen, oxygen, and sulfur through millimeter molecular absorption lines arising in the z=0.68 absorber toward the blazar B 0218+357. We find that these ratios differ from those observed in the Galactic interstellar medium, but are remarkably close to those in the only other source at intermediate redshift for which isotopic ratios have been measured to date, the z=0.89 absorber in front of PKS1830-211. The isotopic ratios in these two absorbers should reflect enrichment mostly from massive stars, and they are indeed close to the values observed toward local starburst galaxies. Our measurements set constraints on nucleosynthesis and chemical evolution models.Comment: Accepted for publication in Astronomy & Astrophysics; 10 pages, 9 figure

Chlorine-bearing molecules in molecular absorbers at intermediate redshifts

We use observations of chlorine-bearing species in molecular absorbers at intermediate redshifts to investigate chemical properties and Cl-35/Cl-37 isotopic ratios in the absorbing sightlines. Chloronium (H2Cl+) is detected along three independent lines of sight in the z = 0.89 and z = 0.68 molecular absorbers located in front of the lensed quasars PKS 1830-211 and B 0218+357, respectively. Hydrogen chloride (HCl) was observed only toward PKS 1830-211, and is found to behave differently from H2Cl+. It is detected in one line of sight with an abundance ratio [H2Cl+]/[HCl] similar to 1, but remains undetected in the other, more diffuse, line of sight, with a ratio [H2Cl+] / [HCl] > 17. The absorption profiles of these two chlorine-bearing species are compared to other species and discussed in terms of the physical properties of the absorbing gas. Our findings are consistent with the picture emerging from chemical models where different species trace gas with different molecular hydrogen fraction. The Cl-35/Cl-37 isotopic ratios are measured in the different lines of sight and are discussed in terms of stellar nucleosynthesis

Thermodynamic Gravity and the Schrodinger Equation

We adopt a 'thermodynamical' formulation of Mach's principle that the rest mass of a particle in the Universe is a measure of its long-range collective interactions with all other particles inside the horizon. We consider all particles in the Universe as a 'gravitationally entangled' statistical ensemble and apply the approach of classical statistical mechanics to it. It is shown that both the Schrodinger equation and the Planck constant can be derived within this Machian model of the universe. The appearance of probabilities, complex wave functions, and quantization conditions is related to the discreetness and finiteness of the Machian ensemble.Comment: Minor corrections, the version accepted by Int. J. Theor. Phy

Transmission of Single HIV-1 Genomes and Dynamics of Early Immune Escape Revealed by Ultra-Deep Sequencing

We used ultra-deep sequencing to obtain tens of thousands of HIV-1 sequences from regions targeted by CD8+ T lymphocytes from longitudinal samples from three acutely infected subjects, and modeled viral evolution during the critical first weeks of infection. Previous studies suggested that a single virus established productive infection, but these conclusions were tempered because of limited sampling; now, we have greatly increased our confidence in this observation through modeling the observed earliest sample diversity based on vastly more extensive sampling. Conventional sequencing of HIV-1 from acute/early infection has shown different patterns of escape at different epitopes; we investigated the earliest escapes in exquisite detail. Over 3–6 weeks, ultradeep sequencing revealed that the virus explored an extraordinary array of potential escape routes in the process of evading the earliest CD8 T-lymphocyte responses – using 454 sequencing, we identified over 50 variant forms of each targeted epitope during early immune escape, while only 2–7 variants were detected in the same samples via conventional sequencing. In contrast to the diversity seen within epitopes, non-epitope regions, including the Envelope V3 region, which was sequenced as a control in each subject, displayed very low levels of variation. In early infection, in the regions sequenced, the consensus forms did not have a fitness advantage large enough to trigger reversion to consensus amino acids in the absence of immune pressure. In one subject, a genetic bottleneck was observed, with extensive diversity at the second time point narrowing to two dominant escape forms by the third time point, all within two months of infection. Traces of immune escape were observed in the earliest samples, suggesting that immune pressure is present and effective earlier than previously reported; quantifying the loss rate of the founder virus suggests a direct role for CD8 T-lymphocyte responses in viral containment after peak viremia. Dramatic shifts in the frequencies of epitope variants during the first weeks of infection revealed a complex interplay between viral fitness and immune escape

Measured adiposity in relation to head and neck cancer risk in the European Prospective Investigation into Cancer and Nutrition

BACKGROUND: Emerging evidence from cohort studies indicates that adiposity is associated with greater incidence of head and neck cancer (HNC). However, most studies have used self-reported anthropometry which is prone to error. METHODS: Among 363 094 participants in the European Prospective Investigation into Cancer and Nutrition study (EPIC) with measured anthropometry, there were 837 incident cases of HNC. HNC risk was examined in relation to body mass index (BMI) [lean: 30 kg/m²], waist circumference (WC), hip circumference (HC) and waist to hip ratio (WHR) using Cox proportional hazards models. RESULTS: Among men, a BMI < 22.5 kg/m² was associated with higher HNC risk [hazard ratio (HR) 1.62, 95% confidence interval (CI) 1.23 - 2.12)]; BMI was not associated with HNC among women. WC and WHR were associated with greater risk of HNC among women, (WC per 5 cm: HR 1.08, 95% CI 1.02 - 1.15; WHR per 0.1 unit: HR 1.64, 95% CI 1.38 - 1.93). After stratification by smoking status, the association for WHR was present only among smokers (p interaction 0.004). Among men, WC and WHR were associated with HNC only upon additional adjustment for BMI (WC per 5 cm: HR 1.16, 95% CI 1.07 - 1.26; WHR per 0.1 unit: HR 1.42, 95% CI 1.21 - 1.65). CONCLUSION: Central adiposity, particularly among women, may have a stronger association with HNC risk than previously estimated. IMPACT: Strategies to reduce obesity may beneficially impact HNC incidence.The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF), Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); ERC- 2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), PI13/00061 to Granada; , PI13/01162 to EPIC-Murcia), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to K.T. Khaw, N.J. Wareham; C570/A16491 to R.C. Travis and C8221/A19170 to Tim Key (EPIC-Oxford), Medical Research Council (1000143 to K.T. Khaw, N.J. Wareham, MR/M012190/1 to Tim Key (EPIC-Oxford)) (United Kingdom)

Measured adiposity in relation to head and neck cancer risk in the European Prospective Investigation into Cancer and Nutrition

BACKGROUND: Emerging evidence from cohort studies indicates that adiposity is associated with greater incidence of head and neck cancer (HNC). However, most studies have used self-reported anthropometry which is prone to error. METHODS: Among 363 094 participants in the European Prospective Investigation into Cancer and Nutrition study (EPIC) with measured anthropometry, there were 837 incident cases of HNC. HNC risk was examined in relation to body mass index (BMI) [lean: 30 kg/m²], waist circumference (WC), hip circumference (HC) and waist to hip ratio (WHR) using Cox proportional hazards models. RESULTS: Among men, a BMI < 22.5 kg/m² was associated with higher HNC risk [hazard ratio (HR) 1.62, 95% confidence interval (CI) 1.23 - 2.12)]; BMI was not associated with HNC among women. WC and WHR were associated with greater risk of HNC among women, (WC per 5 cm: HR 1.08, 95% CI 1.02 - 1.15; WHR per 0.1 unit: HR 1.64, 95% CI 1.38 - 1.93). After stratification by smoking status, the association for WHR was present only among smokers (p interaction 0.004). Among men, WC and WHR were associated with HNC only upon additional adjustment for BMI (WC per 5 cm: HR 1.16, 95% CI 1.07 - 1.26; WHR per 0.1 unit: HR 1.42, 95% CI 1.21 - 1.65). CONCLUSION: Central adiposity, particularly among women, may have a stronger association with HNC risk than previously estimated. IMPACT: Strategies to reduce obesity may beneficially impact HNC incidence.The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF), Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); ERC- 2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), PI13/00061 to Granada; , PI13/01162 to EPIC-Murcia), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to K.T. Khaw, N.J. Wareham; C570/A16491 to R.C. Travis and C8221/A19170 to Tim Key (EPIC-Oxford), Medical Research Council (1000143 to K.T. Khaw, N.J. Wareham, MR/M012190/1 to Tim Key (EPIC-Oxford)) (United Kingdom)

Comparison of Statistical Algorithms for the Detection of Infectious Disease Outbreaks in Large Multiple Surveillance Systems

A large-scale multiple surveillance system for infectious disease outbreaks has been in operation in England and Wales since the early 1990s. Changes to the statistical algorithm at the heart of the system were proposed and the purpose of this paper is to compare two new algorithms with the original algorithm. Test data to evaluate performance are created from weekly counts of the number of cases of each of more than 2000 diseases over a twenty-year period. The time series of each disease is separated into one series giving the baseline (background) disease incidence and a second series giving disease outbreaks. One series is shifted forward by twelve months and the two are then recombined, giving a realistic series in which it is known where outbreaks have been added. The metrics used to evaluate performance include a scoring rule that appropriately balances sensitivity against specificity and is sensitive to variation in probabilities near 1. In the context of disease surveillance, a scoring rule can be adapted to reflect the size of outbreaks and this was done. Results indicate that the two new algorithms are comparable to each other and better than the algorithm they were designed to replace

Using GIS to create synthetic disease outbreaks

BACKGROUND: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation. A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment. RESULTS: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment. CONCLUSION: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance