3,502 research outputs found

    The Human Phenotype Ontology in 2024: phenotypes around the world.

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    The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

    Protocol of an individual participant data meta-analysis to quantify the impact of high ambient temperatures on maternal and child health in Africa (HE 2 AT IPD)

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    Introduction: Globally, recognition is growing of the harmful impacts of high ambient temperatures (heat) on health in pregnant women and children. There remain, however, major evidence gaps on the extent to which heat increases the risks for adverse health outcomes, and how this varies between settings. Evidence gaps are especially large in Africa. We will conduct an individual participant data (IPD) meta-analysis to quantify the impacts of heat on maternal and child health in sub-Saharan Africa. A detailed understanding and quantification of linkages between heat, and maternal and child health is essential for developing solutions to this critical research and policy area. Methods and analysis: We will use IPD from existing, large, longitudinal trial and cohort studies, on pregnant women and children from sub-Saharan Africa. We will systematically identify eligible studies through a mapping review, searching data repositories, and suggestions from experts. IPD will be acquired from data repositories, or through collaboration with data providers. Existing satellite imagery, climate reanalysis data, and station-based weather observations will be used to quantify weather and environmental exposures. IPD will be recoded and harmonised before being linked with climate, environmental, and socioeconomic data by location and time. Adopting a one-stage and two-stage meta-analysis method, analytical models such as time-to-event analysis, generalised additive models, and machine learning approaches will be employed to quantify associations between exposure to heat and adverse maternal and child health outcomes. Ethics and dissemination: The study has been approved by ethics committees. There is minimal risk to study participants. Participant privacy is protected through the anonymisation of data for analysis, secure data transfer and restricted access. Findings will be disseminated through conferences, journal publications, related policy and research fora, and data may be shared in accordance with data sharing policies of the National Institutes of Health. PROSPERO registration number: CRD42022346068

    The intriguing molecular dynamics of Cer[EOS] in rigid skin barrier lipid layers requires improvement of the model

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    Omega-O-acyl ceramides such as 32-linoleoyloxydotriacontanoyl sphingosine (Cer[EOS]) are essential components of the lipid skin barrier, which protects our body from excessive water loss and the penetration of unwanted substances. These ceramides drive the lipid assembly to epidermal-specific long periodicity phase (LPP), structurally much different than conventional lipid bilayers. Here, we synthesized Cer[EOS] with selectively deuterated segments of the ultralong N-acyl chain or deuterated or 13C-labeled linoleic acid and studied their molecular behavior in a skin lipid model. Solid-state 2H NMR data revealed surprising molecular dynamics for the ultralong N-acyl chain of Cer[EOS] with increased isotropic motion toward the isotropic ester-bound linoleate. The sphingosine moiety of Cer[EOS] is also highly mobile at skin temperature, in stark contrast to the other LPP components, N-lignoceroyl sphingosine acyl, lignoceric acid, and cholesterol, which are predominantly rigid. The dynamics of the linoleic chain is quantitatively described by distributions of correlation times and using dynamic detector analysis. These NMR results along with neutron diffraction data suggest an LPP structure with alternating fluid (sphingosine chain-rich), rigid (acyl chain-rich), isotropic (linoleate-rich), rigid (acyl-chain rich), and fluid layers (sphingosine chain-rich). Such an arrangement of the skin barrier lipids with rigid layers separated with two different dynamic ‚Äúfillings‚ÄĚ i) agrees well with ultrastructural data, ii) satisfies the need for simultaneous rigidity (to ensure low permeability) and fluidity (to ensure elasticity, accommodate enzymes, or antimicrobial peptides), and iii) offers a straightforward way to remodel the lamellar body lipids into the final lipid barrier

    Anticholinergic burden measures, symptoms, and fall-associated risk in older adults with polypharmacy: Development and validation of a prognostic model.

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    BackgroundAnticholinergic burden has been associated with adverse outcomes such as falls. To date, no gold standard measure has been identified to assess anticholinergic burden, and no conclusion has been drawn on which of the different measure algorithms best predicts falls in older patients from general practice. This study compared the ability of five measures of anticholinergic burden to predict falls. To account for patients' individual susceptibility to medications, the added predictive value of typical anticholinergic symptoms was further quantified in this context.Methods and findingsTo predict falls, models were developed and validated based on logistic regression models created using data from two German cluster-randomized controlled trials. The outcome was defined as "‚Č• 1 fall" vs. "no fall" within a 6-month follow-up period. Data from the RIME study (n = 1,197) were used in model development, and from PRIMUM (n = 502) for external validation. The models were developed step-wise in order to quantify the predictive ability of anticholinergic burden measures, and anticholinergic symptoms. In the development set, 1,015 patients had complete data and 188 (18.5%) experienced ‚Č• 1 fall within the 6-month follow-up period. The overall predictive value of the five anticholinergic measures was limited, with neither the employed anticholinergic variable (binary / count / burden), nor dose-dependent or dose-independent measures differing significantly in their ability to predict falls. The highest c-statistic was obtained using the German Anticholinergic Burden Score (0.73), whereby the optimism-corrected c-statistic was 0.71 after interval validation using bootstrapping and 0.63 in the external validation. Previous falls and dizziness / vertigo had the strongest prognostic value in all models.ConclusionsThe ability of anticholinergic burden measures to predict falls does not appear to differ significantly, and the added value they contribute to risk classification in fall-prediction models is limited. Previous falls and dizziness / vertigo contributed most to model performance

    Leveraging Math Cognition to Combat Health Innumeracy

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    Rational numbers (i.e., fractions, percentages, decimals, and whole-number frequencies) are notoriously difficult mathematical constructs. Yet correctly interpreting rational numbers is imperative for understanding health statistics, such as gauging the likelihood of side effects from a medication. Several pernicious biases affect health decision-making involving rational numbers. In our novel developmental framework, the natural-number bias-a tendency to misapply knowledge about natural numbers to all numbers-is the mechanism underlying other biases that shape health decision-making. Natural-number bias occurs when people automatically process natural-number magnitudes and disregard ratio magnitudes. Math-cognition researchers have identified individual differences and environmental factors underlying natural-number bias and devised ways to teach people how to avoid these biases. Although effective interventions from other areas of research can help adults evaluate numerical health information, they circumvent the core issue: people\u27s penchant to automatically process natural-number magnitudes and disregard ratio magnitudes. We describe the origins of natural-number bias and how researchers may harness the bias to improve rational-number understanding and ameliorate innumeracy in real-world contexts, including health. We recommend modifications to formal math education to help children learn the connections among natural and rational numbers. We also call on researchers to consider individual differences people bring to health decision-making contexts and how measures from math cognition might identify those who would benefit most from support when interpreting health statistics. Investigating innumeracy with an interdisciplinary lens could advance understanding of innumeracy in theoretically meaningful and practical ways.</p

    Cancers (Basel)

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    Despite cancer being a leading comorbidity amongst individuals with HIV, there are limited data assessing cancer trends across different antiretroviral therapy (ART)-eras. We calculated age-standardised cancer incidence rates (IRs) from 2006-2021 in two international cohort collaborations (D:A:D and RESPOND). Poisson regression was used to assess temporal trends, adjusted for potential confounders. Amongst 64,937 individuals (31% ART-na√Įve at baseline) and 490,376 total person-years of follow-up (PYFU), there were 3763 incident cancers (IR 7.7/1000 PYFU [95% CI 7.4, 7.9]): 950 AIDS-defining cancers (ADCs), 2813 non-ADCs, 1677 infection-related cancers, 1372 smoking-related cancers, and 719 BMI-related cancers (groups were not mutually exclusive). Age-standardised IRs for overall cancer remained fairly constant over time (8.22/1000 PYFU [7.52, 8.97] in 2006-2007, 7.54 [6.59, 8.59] in 2020-2021). The incidence of ADCs (3.23 [2.79, 3.72], 0.99 [0.67, 1.42]) and infection-related cancers (4.83 [4.2, 5.41], 2.43 [1.90, 3.05]) decreased over time, whilst the incidence of non-ADCs (4.99 [4.44, 5.58], 6.55 [5.67, 7.53]), smoking-related cancers (2.38 [2.01, 2.79], 3.25 [2.63-3.96]), and BMI-related cancers (1.07 [0.83, 1.37], 1.88 [1.42, 2.44]) increased. Trends were similar after adjusting for demographics, comorbidities, HIV-related factors, and ART use. These results highlight the need for better prevention strategies to reduce the incidence of NADCs, smoking-, and BMI-related cancers

    Identification Of Marine Debris By Focusing The Study Of Clean Coast Index On Karang Ria Tuminting Beach

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    Marine debris is rapidly gaining worldwide recognition as a major anthropogenic threat to global ocean ecosystems and produces a wide range of negative environmental, economic, safety, health and cultural impacts (UNEP, 2009). East Asia is the region with the fastest growing waste production in the world. Indonesia is in second position after China which produces the most waste in the world (Jambeck et al, 2015). The Beach Hygiene Index is a scaled index in a ‚ÄúClean Coast‚ÄĚ program launched by the Israeli ministry in an effort to solve the problem of littering on Israel's beaches. This index can be used as an indicator of pollution in a marine tourism area. The purpose of this study was to identify types of marine debris in the coastal waters of Karang Ria Tuminting and determine the value of the Clean Coast Index as an indicator of pollution. The collected data was then processed and statistically analyzed using Excel, Orange and SPSS software. Sampling was done by adapting the Shoreline Survey Methodology. approximately 1 month and made 2 direct observations, the plastic and rubber waste categories were found as the most common categories with the first observation being 73.4% and the second observation being 10.1%. The activities of the surrounding community are the main factors causing the abundance of marine debris around the coastal areas. The index value obtained is 39.5 with a total of 395 waste in various categories as stated by NOAA (2016). Keywords: Marine debris, Index, Identification, Category ABSTRAK Sampah laut dengan cepat mendapatkan pengakuan dunia sebagai ancaman antropogenik utama bagi ekosistem lautan global dan menghasilkan berbagai macam dampak negatif lingkungan, ekonomi, keselamatan, kesehatan, dan budaya (UNEP, 2009). Asia Timur adalah wilayah dengan pertumbuhan produksi sampah tercepat di dunia. Indonesia berada pada posisi kedua setelah China yang memproduksi sampah terbanyak di dunia (Jambeck et al, 2015). Indeks Kebersihan Pantai adalah skala indeks dalam suatu program ‚ÄúClean Coast‚ÄĚ yang diluncurkan kementerian Israel dalam upaya untuk memecahkan permasalahan sampah di pantai-pantai Israel. Indeks ini dapat digunakan sebagai indikator polusi pada suatu kawasan wisata bahari. Tujuan penelitian ini untuk mengidentifikasi jenis sampah laut di perairan pantai Karang Ria Tuminting dan menentukan nilai Indeks Kebersihan Pantai (Clean Coast Index) sebagai indikator polusi. Data yang dikumpulkan kemudian diolah dan dianalisis secara statistik dengan menggunakan perangkat lunak Excel, Orange dan SPSS. Pengambilan sampel dilakukan dengan mengadaptasi metode Shoreline Survey Methodology. Pengamatan dilaksanakan kurang lebih 1 bulan dan dilakukan 2 kali pengamatan langsung, diperoleh kategori sampah plastik dan karet sebagai kategori yang paling banyak ditemukan dengan komposisi jumlah pada pengamatan pertama sebesar 73.4% dan pengamatan kedua sebanyak 10.1%. aktivitas masyarakat sekitar menjadi faktor utama penyebab berlimpahnya sampah laut di sekitar wilayah pesisir. Nilai indeks yang diperoleh yaitu sebanyak 39,5 dengan jumlah total 395 sampah dengan berbagai kategori sesuai dengan yang dikemukakan oleh NOAA (2016). Kata kunci : Sampah laut, Indeks, Identifikasi, Kategor
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