523 research outputs found

    Studies of homologous and heterologous tumor transplantation

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    Targeted Social Distancing Designs for Pandemic Influenza

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    Local community networks can mitigate pandemic influenza in the absence of vaccine and antiviral drugs

    Interferometric Constraints on Quantum Geometrical Shear Noise Correlations

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    Final measurements and analysis are reported from the first-generation Holometer, the first instrument capable of measuring correlated variations in space-time position at strain noise power spectral densities smaller than a Planck time. The apparatus consists of two co-located, but independent and isolated, 40 m power-recycled Michelson interferometers, whose outputs are cross-correlated to 25 MHz. The data are sensitive to correlations of differential position across the apparatus over a broad band of frequencies up to and exceeding the inverse light crossing time, 7.6 MHz. By measuring with Planck precision the correlation of position variations at spacelike separations, the Holometer searches for faint, irreducible correlated position noise backgrounds predicted by some models of quantum space-time geometry. The first-generation optical layout is sensitive to quantum geometrical noise correlations with shear symmetry---those that can be interpreted as a fundamental noncommutativity of space-time position in orthogonal directions. General experimental constraints are placed on parameters of a set of models of spatial shear noise correlations, with a sensitivity that exceeds the Planck-scale holographic information bound on position states by a large factor. This result significantly extends the upper limits placed on models of directional noncommutativity by currently operating gravitational wave observatories.Comment: Matches the journal accepted versio

    Effective, Robust Design of Community Mitigation for Pandemic Influenza: A Systematic Examination of Proposed US Guidance

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    BACKGROUND: The US government proposes pandemic influenza mitigation guidance that includes isolation and antiviral treatment of ill persons, voluntary household member quarantine and antiviral prophylaxis, social distancing of individuals, school closure, reduction of contacts at work, and prioritized vaccination. Is this the best strategy combination? Is choice of this strategy robust to pandemic uncertainties? What are critical enablers of community resilience? METHODS AND FINDINGS: We systematically simulate a broad range of pandemic scenarios and mitigation strategies using a networked, agent-based model of a community of explicit, multiply-overlapping social contact networks. We evaluate illness and societal burden for alterations in social networks, illness parameters, or intervention implementation. For a 1918-like pandemic, the best strategy minimizes illness to <1% of the population and combines network-based (e.g. school closure, social distancing of all with adults' contacts at work reduced), and case-based measures (e.g. antiviral treatment of the ill and prophylaxis of household members). We find choice of this best strategy robust to removal of enhanced transmission by the young, additional complexity in contact networks, and altered influenza natural history including extended viral shedding. Administration of age-group or randomly targeted 50% effective pre-pandemic vaccine with 7% population coverage (current US H5N1 vaccine stockpile) had minimal effect on outcomes. In order, mitigation success depends on rapid strategy implementation, high compliance, regional mitigation, and rigorous rescinding criteria; these are the critical enablers for community resilience. CONCLUSIONS: Systematic evaluation of feasible, recommended pandemic influenza interventions generally confirms the US community mitigation guidance yields best strategy choices for pandemic planning that are robust to a wide range of uncertainty. The best strategy combines network- and case-based interventions; network-based interventions are paramount. Because strategies must be applied rapidly, regionally, and stringently for greatest benefit, preparation and public education is required for long-lasting, high community compliance during a pandemic

    LMSD: LIPID MAPS structure database

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    The LIPID MAPS Structure Database (LMSD) is a relational database encompassing structures and annotations of biologically relevant lipids. Structures of lipids in the database come from four sources: (i) LIPID MAPS Consortium's core laboratories and partners; (ii) lipids identified by LIPID MAPS experiments; (iii) computationally generated structures for appropriate lipid classes; (iv) biologically relevant lipids manually curated from LIPID BANK, LIPIDAT and other public sources. All the lipid structures in LMSD are drawn in a consistent fashion. In addition to a classification-based retrieval of lipids, users can search LMSD using either text-based or structure-based search options. The text-based search implementation supports data retrieval by any combination of these data fields: LIPID MAPS ID, systematic or common name, mass, formula, category, main class, and subclass data fields. The structure-based search, in conjunction with optional data fields, provides the capability to perform a substructure search or exact match for the structure drawn by the user. Search results, in addition to structure and annotations, also include relevant links to external databases. The LMSD is publicly available a

    Measuring Coverage in MNCH:A Validation Study Linking Population Survey Derived Coverage to Maternal, Newborn, and Child Health Care Records in Rural China

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    Accurate data on coverage of key maternal, newborn, and child health (MNCH) interventions are crucial for monitoring progress toward the Millennium Development Goals 4 and 5. Coverage estimates are primarily obtained from routine population surveys through self-reporting, the validity of which is not well understood. We aimed to examine the validity of the coverage of selected MNCH interventions in Gongcheng County, China.We conducted a validation study by comparing women's self-reported coverage of MNCH interventions relating to antenatal and postnatal care, mode of delivery, and child vaccinations in a community survey with their paper- and electronic-based health care records, treating the health care records as the reference standard. Of 936 women recruited, 914 (97.6%) completed the survey. Results show that self-reported coverage of these interventions had moderate to high sensitivity (0.57 [95% confidence interval (CI): 0.50-0.63] to 0.99 [95% CI: 0.98-1.00]) and low to high specificity (0 to 0.83 [95% CI: 0.80-0.86]). Despite varying overall validity, with the area under the receiver operating characteristic curve (AUC) ranging between 0.49 [95% CI: 0.39-0.57] and 0.90 [95% CI: 0.88-0.92], bias in the coverage estimates at the population level was small to moderate, with the test to actual positive (TAP) ratio ranging between 0.8 and 1.5 for 24 of the 28 indicators examined. Our ability to accurately estimate validity was affected by several caveats associated with the reference standard. Caution should be exercised when generalizing the results to other settings.The overall validity of self-reported coverage was moderate across selected MNCH indicators. However, at the population level, self-reported coverage appears to have small to moderate degree of bias. Accuracy of the coverage was particularly high for indicators with high recorded coverage or low recorded coverage but high specificity. The study provides insights into the accuracy of self-reports based on a population survey in low- and middle-income countries. Similar studies applying an improved reference standard are warranted in the future
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