60 research outputs found

    Nutrient Composition of Avocados Grown in Hawai‘i and Cameroon.

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    M.S. Thesis. University of Hawaiʻi at Mānoa 2017

    A Qualitative Analysis of a Caregivers’ Experience of Complementary Feeding in a Population of Native Hawaiian, Other Pacific Islander and Filipino Infants: The Timing of the Introduction of Complementary Foods, and the Role of Transgenerational Experience

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    The aim of this study was to investigate caregivers’ experiences of complementary feeding (CF) among the Native Hawaiian and Other Pacific Islander (NHPI), and Filipino populations. Research focused on the timing of CF commencement, and the influence of transgenerational experience on feeding practices. The experiences and practices of those who fed human milk exclusively (HME), were compared to those who included infant formula (F&HM). Caregivers of a subset of 32 infants who were participating in a larger longitudinal study relating to CF and diet diversity, took part in voluntary in-depth interviews relating to CF practices. Interviews were recorded and transcribed. Two researchers analyzed interview transcripts. Interrater reliability and saturation were established. Institutional Review Board exemption was confirmed prior to study commencement. Interviews with 29 caregivers of infants were included in this study. Only infants of the F&HM group had an early introduction to complementary foods (age). Caregivers reported receiving conflicting advice from healthcare professionals (HCPs) in relation to timing of the introduction of complementary foods. Nonetheless, the majority of caregivers reported following the advice of HCPs. Extended family (including grandparents) played less of a role in infant feeding, compared to previous generations. While transgenerational practices were valued and included, ultimately, the perceived health and safety of the practice for infants influenced decisions

    Evaluating the performance of ChatGPT-4 on the United Kingdom Medical Licensing Assessment

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    IntroductionRecent developments in artificial intelligence large language models (LLMs), such as ChatGPT, have allowed for the understanding and generation of human-like text. Studies have found LLMs abilities to perform well in various examinations including law, business and medicine. This study aims to evaluate the performance of ChatGPT in the United Kingdom Medical Licensing Assessment (UKMLA).MethodsTwo publicly available UKMLA papers consisting of 200 single-best-answer (SBA) questions were screened. Nine SBAs were omitted as they contained images that were not suitable for input. Each question was assigned a specialty based on the UKMLA content map published by the General Medical Council. A total of 191 SBAs were inputted in ChatGPT-4 through three attempts over the course of 3 weeks (once per week).ResultsChatGPT scored 74.9% (143/191), 78.0% (149/191) and 75.6% (145/191) on three attempts, respectively. The average of all three attempts was 76.3% (437/573) with a 95% confidence interval of (74.46% and 78.08%). ChatGPT answered 129 SBAs correctly and 32 SBAs incorrectly on all three attempts. On three attempts, ChatGPT performed well in mental health (8/9 SBAs), cancer (11/14 SBAs) and cardiovascular (10/13 SBAs). On three attempts, ChatGPT did not perform well in clinical haematology (3/7 SBAs), endocrine and metabolic (2/5 SBAs) and gastrointestinal including liver (3/10 SBAs). Regarding to response consistency, ChatGPT provided correct answers consistently in 67.5% (129/191) of SBAs but provided incorrect answers consistently in 12.6% (24/191) and inconsistent response in 19.9% (38/191) of SBAs, respectively.Discussion and conclusionThis study suggests ChatGPT performs well in the UKMLA. There may be a potential correlation between specialty performance. LLMs ability to correctly answer SBAs suggests that it could be utilised as a supplementary learning tool in medical education with appropriate medical educator supervision

    Rarefaction and extrapolation with beta diversity under a framework of Hill numbers : the iNEXT.beta3D standardization

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    This work isjointly supported by the Natural Environment Research Council, UK and the Taiwan Ministry of Science and Technology under Contracts NERC-MOST 108-2923-M-007-003 and NE/T004487/1. AEM also acknowledges the Leverhulme Trust (RPG-2019-402). Support for the establishment and monitoring of permanent plots in Costa Rican forests was provided by grants from the Andrew W. Mellon Foundation, the US National Science Foundation (NSF DEB-0424767, NSF DEB-0639393 and NSF DEB-1147429), US NASA Terrestrial Ecology Program, and the University of Connecticut Research Foundation. MD is supported by a Leverhulme Trust Research Centre - the Leverhulme Centre for Anthropocene Biodiversity (RC-2018-021). L.F.S.M. was supported by the Conselho Nacional de Desenvolvimento CientĂ­fico e TecnolĂłgico (CNPq) grant 307984/2022-2.Based on sampling data, we propose a rigorous standardization method to measure and compare beta diversity across datasets. Here beta diversity, which quantifies the extent of among-assemblage differentiation, relies on Whittaker's original multiplicative decomposition scheme, but we use Hill numbers for any diversity order q ≄ 0. Richness-based beta diversity (q = 0) quantifies the extent of species identity shift, whereas abundance-based (q > 0) beta diversity also quantifies the extent of difference among assemblages in species abundance. We adopt and define the assumptions of a statistical sampling model as the foundation for our approach, treating sampling data as a representative sample taken from an assemblage. The approach makes a clear distinction between the theoretical assemblage level (unknown properties/parameters of the assemblage) and the sampling data level (empirical/observed statistics computed from data). At the assemblage level, beta diversity for N assemblages reflects the interacting effect of the species abundance distribution and spatial/temporal aggregation of individuals in the assemblage. Under independent sampling, observed beta (= gamma/alpha) diversity depends not only on among-assemblage differentiation but also on sampling effort/completeness, which in turn induces dependence of beta on alpha and gamma diversity. How to remove the dependence of richness-based beta diversity on its gamma component (species pool) has been intensely debated. Our approach is to standardize gamma and alpha based on sample coverage (an objective measure of sample completeness). For a single assemblage, the iNEXT method was developed, through interpolation (rarefaction) and extrapolation with Hill numbers, to standardize samples by sampling effort/completeness. Here we adapt the iNEXT standardization to alpha and gamma diversity, that is, alpha and gamma diversity are both assessed at the same level of sample coverage, to formulate standardized, coverage-based beta diversity. This extension of iNEXT to beta diversity required the development of novel concepts and theories, including a formal proof and simulation-based demonstration that the resulting standardized beta diversity removes the dependence of beta diversity on both gamma and alpha values, and thus reflects the pure among-assemblage differentiation. The proposed standardization is illustrated with spatial, temporal, and spatiotemporal datasets, while the freeware iNEXT.beta3D facilitates all computations and graphics.Publisher PDFPeer reviewe

    IFITM Proteins Restrict Antibody-Dependent Enhancement of Dengue Virus Infection

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    Interferon-inducible transmembrane (IFITM) proteins restrict the entry processes of several pathogenic viruses, including the flaviviruses West Nile virus and dengue virus (DENV). DENV infects cells directly or via antibody-dependent enhancement (ADE) in Fc-receptor-bearing cells, a process thought to contribute to severe disease in a secondary infection. Here we investigated whether ADE-mediated DENV infection bypasses IFITM-mediated restriction or whether IFITM proteins can be protective in a secondary infection. We observed that IFITM proteins restricted ADE-mediated and direct infection with comparable efficiencies in a myelogenous leukemia cell line. Our data suggest that IFITM proteins can contribute to control of secondary DENV infections

    Precision gestational diabetes treatment: a systematic review and meta-analyses

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    The 13th Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-IV Survey Mapping Nearby Galaxies at Apache Point Observatory

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    The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) began observations in July 2014. It pursues three core programs: APOGEE-2,MaNGA, and eBOSS. In addition, eBOSS contains two major subprograms: TDSS and SPIDERS. This paper describes the first data release from SDSS-IV, Data Release 13 (DR13), which contains new data, reanalysis of existing data sets and, like all SDSS data releases, is inclusive of previously released data. DR13 makes publicly available 1390 spatially resolved integral field unit observations of nearby galaxies from MaNGA,the first data released from this survey. It includes new observations from eBOSS, completing SEQUELS. In addition to targeting galaxies and quasars, SEQUELS also targeted variability-selected objects from TDSS and X-ray selected objects from SPIDERS. DR13 includes new reductions ofthe SDSS-III BOSS data, improving the spectrophotometric calibration and redshift classification. DR13 releases new reductions of the APOGEE-1data from SDSS-III, with abundances of elements not previously included and improved stellar parameters for dwarf stars and cooler stars. For the SDSS imaging data, DR13 provides new, more robust and precise photometric calibrations. Several value-added catalogs are being released in tandem with DR13, in particular target catalogs relevant for eBOSS, TDSS, and SPIDERS, and an updated red-clump catalog for APOGEE.This paper describes the location and format of the data now publicly available, as well as providing references to the important technical papers that describe the targeting, observing, and data reduction. The SDSS website, http://www.sdss.org, provides links to the data, tutorials and examples of data access, and extensive documentation of the reduction and analysis procedures. DR13 is the first of a scheduled set that will contain new data and analyses from the planned ~6-year operations of SDSS-IV.PostprintPeer reviewe

    Genotype-stratified treatment for monogenic insulin resistance: a systematic review

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