Population Genetics of Franciscana Dolphins (Pontoporia blainvillei): Introducing a New Population from the Southern Edge of Their Distribution

Due to anthropogenic factors, the franciscana dolphin, Pontoporia blainvillei, is the most threatened small cetacean on the Atlantic coast of South America. Four Franciscana Management Areas have been proposed: Espiritu Santo to Rio de Janeiro (FMA I), São Paulo to Santa Catarina (FMA II), Rio Grande do Sul to Uruguay (FMA III), and Argentina (FMA IV). Further genetic studies distinguished additional populations within these FMAs. We analyzed the population structure, phylogeography, and demographic history in the southernmost portion of the species range. From the analysis of mitochondrial DNA control region sequences, 5 novel haplotypes were found, totalizing 60 haplotypes for the entire distribution range. The haplotype network did not show an apparent phylogeographical signal for the southern FMAs. Two populations were identified: Monte Hermoso (MH) and Necochea (NC)+Claromecó (CL)+Río Negro (RN). The low levels of genetic variability, the relative constant size over time, and the low levels of gene flow may indicate that MH has been colonized by a few maternal lineages and became isolated from geographically close populations. The apparent increase in NC+CL+RN size would be consistent with the higher genetic variability found, since genetic diversity is generally higher in older and expanding populations. Additionally, RN may have experienced a recent split from CL and NC; current high levels of gene flow may be occurring between the latter ones. FMA IV would comprise four franciscana dolphin populations: Samborombón West+Samborombón South, Cabo San Antonio+Buenos Aires East, NC+CL+Buenos Aires Southwest+RN and MH. Results achieved in this study need to be taken into account in order to ensure the long-term survival of the species.Fil: Gariboldi, María Constanza. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Maimónides. Área de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; ArgentinaFil: Tunez, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Luján; ArgentinaFil: Dejean, Cristina Beatriz. Universidad Maimónides. Área de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; Argentina. Universidad de Buenos Aires. Facultad de Filosofía y Letras. Instituto de Ciencias Antropológicas. Sección Antropología Biológica; ArgentinaFil: Failla, Mauricio. Fundación Cethus; ArgentinaFil: Vitullo, Alfredo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Maimónides. Área de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; ArgentinaFil: Negri, Maria Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales ; ArgentinaFil: Cappozzo, Humberto Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Maimónides. Área de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales ; Argentin

Infall of gas as the formation mechanism of stars up to 20 times more massive than the Sun

Theory predicts and observations confirm that low-mass stars (like the Sun) in their early life grow by accreting gas from the surrounding material. But for stars ~ 10 times more massive than the Sun (~10 M_sun), the powerful stellar radiation is expected to inhibit accretion and thus limit the growth of their mass. Clearly, stars with masses >10 M_sun exist, so there must be a way for them to form. The problem may be solved by non-spherical accretion, which allows some of the stellar photons to escape along the symmetry axis where the density is lower. The recent detection of rotating disks and toroids around very young massive stars has lent support to the idea that high-mass (> 8 M_sun) stars could form in this way. Here we report observations of an ammonia line towards a high-mass star forming region. We conclude from the data that the gas is falling inwards towards a very young star of ~20 M_sun, in line with theoretical predictions of non-spherical accretion.Comment: 11 pages, 2 figure

Antipsychotics and Torsadogenic Risk: Signals Emerging from the US FDA Adverse Event Reporting System Database

Background: Drug-induced torsades de pointes (TdP) and related clinical entities represent a current regulatory and clinical burden. Objective: As part of the FP7 ARITMO (Arrhythmogenic Potential of Drugs) project, we explored the publicly available US FDA Adverse Event Reporting System (FAERS) database to detect signals of torsadogenicity for antipsychotics (APs). Methods: Four groups of events in decreasing order of drug-attributable risk were identified: (1) TdP, (2) QT-interval abnormalities, (3) ventricular fibrillation/tachycardia, and (4) sudden cardiac death. The reporting odds ratio (ROR) with 95 % confidence interval (CI) was calculated through a cumulative analysis from group 1 to 4. For groups 1+2, ROR was adjusted for age, gender, and concomitant drugs (e.g., antiarrhythmics) and stratified for AZCERT drugs, lists I and II (http://www.azcert.org, as of June 2011). A potential signal of torsadogenicity was defined if a drug met all the following criteria: (a) four or more cases in group 1+2; (b) significant ROR in group 1+2 that persists through the cumulative approach; (c) significant adjusted ROR for group 1+2 in the stratum without AZCERT drugs; (d) not included in AZCERT lists (as of June 2011). Results: Over the 7-year period, 37 APs were reported in 4,794 cases of arrhythmia: 140 (group 1), 883 (group 2), 1,651 (group 3), and 2,120 (group 4). Based on our criteria, the following potential signals of torsadogenicity were found: amisulpride (25 cases; adjusted ROR in the stratum without AZCERT drugs = 43.94, 95 % CI 22.82-84.60), cyamemazine (11; 15.48, 6.87-34.91), and olanzapine (189; 7.74, 6.45-9.30). Conclusions: This pharmacovigilance analysis on the FAERS found 3 potential signals of torsadogenicity for drugs previously unknown for this risk

The tissue micro-array data exchange specification: a web based experience browsing imported data

BACKGROUND: The AIDS and Cancer Specimen Resource (ACSR) is an HIV/AIDS tissue bank consortium sponsored by the National Cancer Institute (NCI) Division of Cancer Treatment and Diagnosis (DCTD). The ACSR offers to approved researchers HIV infected biologic samples and uninfected control tissues including tissue cores in micro-arrays (TMA) accompanied by de-identified clinical data. Researchers interested in the type and quality of TMA tissue cores and the associated clinical data need an efficient method for viewing available TMA materials. Because each of the tissue samples within a TMA has separate data including a core tissue digital image and clinical data, an organized, standard approach to producing, navigating and publishing such data is necessary. The Association for Pathology Informatics (API) extensible mark-up language (XML) TMA data exchange specification (TMA DES) proposed in April 2003 provides a common format for TMA data. Exporting TMA data into the proposed format offers an opportunity to implement the API TMA DES. Using our public BrowseTMA tool, we created a web site that organizes and cross references TMA lists, digital "virtual slide" images, TMA DES export data, linked legends and clinical details for researchers. Microsoft Excel(® )and Microsoft Word(® )are used to convert tabular clinical data and produce an XML file in the TMA DES format. The BrowseTMA tool contains Extensible Stylesheet Language Transformation (XSLT) scripts that convert XML data into Hyper-Text Mark-up Language (HTML) web pages with hyperlinks automatically added to allow rapid navigation. RESULTS: Block lists, virtual slide images, legends, clinical details and exports have been placed on the ACSR web site for 14 blocks with 1623 cores of 2.0, 1.0 and 0.6 mm sizes. Our virtual microscope can be used to view and annotate these TMA images. Researchers can readily navigate from TMA block lists to TMA legends and to clinical details for a selected tissue core. Exports for 11 blocks with 3812 cores from three other institutions were processed with the BrowseTMA tool. Fifty common data elements (CDE) from the TMA DES were used and 42 more created for site-specific data. Researchers can download TMA clinical data in the TMA DES format. CONCLUSION: Virtual TMAs with clinical data can be viewed on the Internet by interested researchers using the BrowseTMA tool. We have organized our approach to producing, sorting, navigating and publishing TMA information to facilitate such review. We have converted Excel TMA data into TMA DES XML, and imported it and TMA DES XML from another institution into BrowseTMA to produce web pages that allow us to browse through the merged data. We proposed enhancements to the TMA DES as a result of this experience. We implemented improvements to the API TMA DES as a result of using exported data from several institutions. A document type definition was written for the API TMA DES (that optionally includes proposed enhancements). Independent validators can be used to check exports against the DTD (with or without the proposed enhancements). Linking tissue core images to readily navigable clinical data greatly improves the value of the TMA

Parameters influencing the size of chitosan-TPP nano- and microparticles

Chitosan nanoparticles, produced by ionic gelation, are among the most intensely studied nanosystems for drug delivery. However, a lack of inter-laboratory reproducibility and a poor physicochemical understanding of the process of particle formation have been slowing their potential market applications. To address these shortcomings, the current study presents a systematic analysis of the main polymer factors affecting the nanoparticle formation driven by an initial screening using systematic statistical Design of Experiments (DoE). In summary, we found that for a given chitosan to TPP molar ratio, the average hydrodynamic diameter of the particles formed is strongly dependent on the initial chitosan concentration. The degree of acetylation of the chitosan was found to be the second most important factor involved in the system's ability to form particles. Interestingly, viscosimetry studies indicated that the particle formation and the average hydrodynamic diameter of the particles formed were highly dependent on the presence or absence of salts in the medium. In conclusion, we found that by controlling two simple factors of the polymer solution, namely its initial concentration and its solvent environment, it is feasible to control in a reproducible manner the production and characteristics of chitosan particles ranging in size from nano- to micrometres

Financing of U.S. Biomedical Research and New Drug Approvals across Therapeutic Areas

We estimated U.S. biomedical research funding across therapeutic areas, determined the association with disease burden, and evaluated new drug approvals that resulted from this investment.We calculated funding from 1995 to 2005 and totaled Food and Drug Administration approvals in eight therapeutic areas (cardiovascular, endocrine, gastrointestinal, genitourinary, HIV/AIDS, infectious disease excluding HIV, oncology, and respiratory) primarily using public data. We then calculated correlations between funding, published estimates of disease burden, and drug approvals. Financial support for biomedical research from 1995 to 2005 increased across all therapeutic areas between 43% and 369%. Industry was the principal funder of all areas except HIV/AIDS, infectious disease, and oncology, which were chiefly sponsored by the National Institutes of Health (NIH). Total (rho = 0.70; P = .03) and industry funding (rho = 0.69; P = .04) were correlated with projected disease burden in high income countries while NIH support (rho = 0.80; P = .01) was correlated with projected disease burden globally. From 1995 to 2005 the number of new approvals was flat or declined across therapeutic areas, and over an 8-year lag period, neither total nor industry funding was correlated with future approvals.Across therapeutic areas, biomedical research funding increased substantially, appears aligned with disease burden in high income countries, but is not linked to new drug approvals. The translational gap between funding and new therapies is affecting all of medicine, and remedies must include changes beyond additional financial investment

NIH Disease Funding Levels and Burden of Disease

BACKGROUND: An analysis of NIH funding in 1996 found that the strongest predictor of funding, disability-adjusted life-years (DALYs), explained only 39% of the variance in funding. In 1998, Congress requested that the Institute of Medicine (IOM) evaluate priority-setting criteria for NIH funding; the IOM recommended greater consideration of disease burden. We examined whether the association between current burden and funding has changed since that time. METHODS: We analyzed public data on 2006 NIH funding for 29 common conditions. Measures of US disease burden in 2004 were obtained from the World Health Organization's Global Burden of Disease study and national databases. We assessed the relationship between disease burden and NIH funding dollars in univariate and multivariable log-linear models that evaluated all measures of disease burden. Sensitivity analyses examined associations with future US burden, current and future measures of world disease burden, and a newly standardized NIH accounting method. RESULTS: In univariate and multivariable analyses, disease-specific NIH funding levels increased with burden of disease measured in DALYs (p = 0.001), which accounted for 33% of funding level variation. No other factor predicted funding in multivariable models. Conditions receiving the most funding greater than expected based on disease burden were AIDS ($2474 M), diabetes mellitus ($390 M), and perinatal conditions ($297 M). Depression ($719 M), injuries ($691 M), and chronic obstructive pulmonary disease ($613 M) were the most underfunded. Results were similar using estimates of future US burden, current and future world disease burden, and alternate NIH accounting methods. CONCLUSIONS: Current levels of NIH disease-specific research funding correlate modestly with US disease burden, and correlation has not improved in the last decade