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1.
Ethical Challenges in COVID-19 Biospecimen Research: Perspectives From Institutional Review Board Members and Bioethicists.
Lapid, MI, Meagher, KM, Giunta, HC, Clarke, BL, Ouellette, Y, Armbrust, TL, Sharp, RR, Wright, RS
Mayo Clinic proceedings. 2021;(1):165-173
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Abstract
Biospecimen research is a prominent investigative strategy that aims to provide novel insights into coronavirus disease 2019 (COVID-19), inform clinical trials, and develop effective, life-saving treatments. However, COVID-19 biospecimen research raises accompanying ethical concerns and practical challenges for investigators and participants. In this special article, we discuss the ethical issues that are associated with autonomy, beneficence, and justice in COVID-19 biospecimen research and describe strategies to manage the practical challenges, with an emphasis on protecting the rights and welfare of human research participants during a pandemic response. Appropriate institutional review board oversight and bioethics guidance for COVID-19 biospecimen research must maintain their focus on protecting the rights and welfare of research participants, despite the urgent need for more knowledge about the virus and the threat it poses to communities and nations.
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Artificial Intelligence in Nutrients Science Research: A Review.
Sak, J, Suchodolska, M
Nutrients. 2021;(2)
Abstract
Artificial intelligence (AI) as a branch of computer science, the purpose of which is to imitate thought processes, learning abilities and knowledge management, finds more and more applications in experimental and clinical medicine. In recent decades, there has been an expansion of AI applications in biomedical sciences. The possibilities of artificial intelligence in the field of medical diagnostics, risk prediction and support of therapeutic techniques are growing rapidly. The aim of the article is to analyze the current use of AI in nutrients science research. The literature review was conducted in PubMed. A total of 399 records published between 1987 and 2020 were obtained, of which, after analyzing the titles and abstracts, 261 were rejected. In the next stages, the remaining records were analyzed using the full-text versions and, finally, 55 papers were selected. These papers were divided into three areas: AI in biomedical nutrients research (20 studies), AI in clinical nutrients research (22 studies) and AI in nutritional epidemiology (13 studies). It was found that the artificial neural network (ANN) methodology was dominant in the group of research on food composition study and production of nutrients. However, machine learning (ML) algorithms were widely used in studies on the influence of nutrients on the functioning of the human body in health and disease and in studies on the gut microbiota. Deep learning (DL) algorithms prevailed in a group of research works on clinical nutrients intake. The development of dietary systems using AI technology may lead to the creation of a global network that will be able to both actively support and monitor the personalized supply of nutrients.
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Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies.
Ho, IS, Azcoaga-Lorenzo, A, Akbari, A, Black, C, Davies, J, Hodgins, P, Khunti, K, Kadam, U, Lyons, RA, McCowan, C, et al
The Lancet. Public health. 2021;(8):e587-e597
Abstract
BACKGROUND A systematic understanding of how multimorbidity has been constructed and measured is unavailable. This review aimed to examine the definition and measurement of multimorbidity in peer-reviewed studies internationally. METHODS We systematically reviewed studies on multimorbidity, via a search of nine bibliographic databases (Ovid [PsycINFO, Embase, Global Health, and MEDLINE], Web of Science, the Cochrane Library, CINAHL Plus, Scopus, and ProQuest Dissertations & Theses Global), from inception to Jan 21, 2020. Reference lists and tracked citations of retrieved articles were hand-searched. Eligible studies were full-text articles measuring multimorbidity for any purpose in community, primary care, care home, or hospital populations receiving a non-specialist service. Abstracts, qualitative research, and case series were excluded. Two reviewers independently reviewed the retrieved studies with conflicts resolved by discussion or a third reviewer, and a single researcher extracted data from published papers. To assess our objectives of how multimorbidity has been measured and examine variation in the chronic conditions included (in terms of number and type), we used descriptive analysis (frequencies, cross-tabulation, and negative binomial regression) to summarise the characteristics of multimorbidity studies and measures (study setting, source of morbidity data, study population, primary study purpose, and multimorbidity measure type). This systematic review is registered with PROSPERO, CRD420201724090. FINDINGS 566 studies were included in our review, of which 206 (36·4%) did not report a reference definition for multimorbidity and 73 (12·9%) did not report the conditions their measure included. The number of conditions included in measures ranged from two to 285 (median 17 [IQR 11-23). 452 (79·9%) studies reported types of condition within a single multimorbidity measure; most included at least one cardiovascular condition (441 [97·6%] of 452 studies), metabolic and endocrine condition (440 [97·3%]), respiratory condition (422 [93·4%]), musculoskeletal condition (396 [87·6%]), or mental health condition (355 [78·5%]) in their measure of multimorbidity. Chronic infections (123 [27·2%]), haematological conditions (110 [24·3%]), ear, nose, and throat conditions (107 [23·7%]), skin conditions (70 [15·5%]), oral conditions (19 [4·2%]), and congenital conditions (14 [3·1%]) were uncommonly included. Only eight individual conditions were included by more than half of studies in the multimorbidity measure used (diabetes, stroke, cancer, chronic obstructive pulmonary disease, hypertension, coronary heart disease, chronic kidney disease, and heart failure), with individual mental health conditions under-represented. Of the 566 studies, 419 were rated to be of moderate risk of bias, 107 of high risk of bias, and 40 of low risk of bias according to the Effective Public Health Practice Project quality assessment tool. INTERPRETATION Measurement of multimorbidity is poorly reported and highly variable. Consistent reporting of measure definitions should be required by journals, and consensus studies are needed to define core and study-dependent conditions to include in measures of multimorbidity. FUNDING Health Data Research UK.
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A Scoping Review of the Application of Metabolomics in Nutrition Research: The Literature Survey 2000-2019.
Shibutami, E, Takebayashi, T
Nutrients. 2021;(11)
Abstract
Nutrimetabolomics is an emerging field in nutrition research, and it is expected to play a significant role in deciphering the interaction between diet and health. Through the development of omics technology over the last two decades, the definition of food and nutrition has changed from sources of energy and major/micro-nutrients to an essential exposure factor that determines health risks. Furthermore, this new approach has enabled nutrition research to identify dietary biomarkers and to deepen the understanding of metabolic dynamics and the impacts on health risks. However, so far, candidate markers identified by metabolomics have not been clinically applied and more efforts should be made to validate those. To help nutrition researchers better understand the potential of its application, this scoping review outlined the historical transition, recent focuses, and future prospects of the new realm, based on trends in the number of human research articles from the early stage of 2000 to the present of 2019 by searching the Medical Literature Analysis and Retrieval System Online (MEDLINE). Among them, objective dietary assessment, metabolic profiling, and health risk prediction were positioned as three of the principal applications. The continued growth will enable nutrimetabolomics research to contribute to personalized nutrition in the future.
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Four decades of the Bart's Oxford study: Improved tests to predict type 1 diabetes.
Gillespie, KM, Fareed, R, Mortimer, GL
Diabetic medicine : a journal of the British Diabetic Association. 2021;(12):e14717
Abstract
Recent success in clinical trials to delay the onset of type 1 diabetes has heralded a new era of type 1 diabetes research focused on the most accurate methods to predict risk and progression rate in the general population. Risk prediction for type 1 diabetes has been ongoing since the 1970s and 1980s when human leucocyte antigen (HLA) variants and islet autoantibodies associated with type 1 diabetes were first described. Development of prediction methodologies has relied on well-characterised cohorts and samples. The Bart's Oxford (BOX) study of type 1 diabetes has been recruiting children with type 1 diabetes and their first (and second)-degree relatives since 1985. In this review, we use the timeline of the study to review the accompanying basic science developments which have facilitated improved prediction by genetic (HLA analysis through to genetic risk scores) and biochemical strategies (islet cell autoantibodies through to improved individual tests for antibodies to insulin, glutamate decarboxylase, the tyrosine phosphatase IA-2, zinc transporter 8 and tetraspanin 7). The type 1 diabetes community are poised to move forward using the best predictive markers to predict and delay the onset of type 1 diabetes.
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Global mapping of overviews of systematic reviews in healthcare published between 2000 and 2020: a bibliometric analysis.
Bougioukas, KI, Vounzoulaki, E, Mantsiou, CD, Papanastasiou, GD, Savvides, ED, Ntzani, EE, Haidich, AB
Journal of clinical epidemiology. 2021;:58-72
Abstract
OBJECTIVE To conduct a bibliometric analysis using a large sample of overviews of systematic reviews (OoSRs) and reveal research trends and areas of interest about these studies. STUDY DESIGN AND SETTING We searched MEDLINE, Scopus and Cochrane Database of Systematic Reviews from 1/1/2000 to 15/10/2020. We used Scopus meta-data and two authors recorded supplementary information independently. We summarized the data using frequencies with percentages. RESULTS A total of 1558 studies were considered eligible for analysis. We found that the publications have been increasing yearly and their nomenclature was not uniform (the most frequent label in the title was "overview of systematic reviews"). The largest number of papers and the most cited ones were published by corresponding authors from the UK. The publications were distributed across 737 scholarly journals and many of them were published in the field of complementary/alternative medicine, psychiatry/psychology, nutrition/dietetics, and pediatrics. The co-authorship analysis revealed collaborations among countries. The most common clinical conditions were depression, diabetes, cancer, dementia, pain, cardiovascular disease, stroke, obesity, and schizophrenia. CONCLUSION OoSRs have recently become a popular approach of evidence synthesis. International collaborations between overview authors from countries with increased research productivity and countries with less research activity should be encouraged.
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The Immune System in Human Milk: A Historic Perspective.
Goldman, AS, Chheda, S
Annals of nutrition & metabolism. 2021;(4):189-196
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Abstract
BACKGROUND Human milk contains a remarkable array of immunological agents that evolved over millions of years to protect the recipient human infant. Furthermore, much of the protection persists long after weaning. However, the scientists who first discovered some components of this immune system have rarely been acknowledged. SUMMARY The scientists who made many fundamental immunological discoveries concerning the immune system in human milk include Alfred François Donné, Paul Ehrlich, Lars Å. Hanson, and Jules Bordet. Based upon their discoveries, a wealth of antimicrobial, anti-inflammatory, and immunomodulating agents, and living, activated leukocytes in human milk were later revealed during the last half of the 20th and the first part of the 21st century. Moreover, it was found that human milk enhances the colonization of commensal bacteria that aid to protect the human infant. Key Message: Their discoveries helped to revitalize breastfeeding in industrialized countries during the past several decades.
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A framework for microbiome science in public health.
Wilkinson, JE, Franzosa, EA, Everett, C, Li, C, , , , , Hu, FB, Wirth, DF, Song, M, Chan, AT, et al
Nature medicine. 2021;(5):766-774
Abstract
Human microbiome science has advanced rapidly and reached a scale at which basic biology, clinical translation and population health are increasingly integrated. It is thus now possible for public health researchers, practitioners and policymakers to take specific action leveraging current and future microbiome-based opportunities and best practices. Here we provide an outline of considerations for research, education, interpretation and scientific communication concerning the human microbiome and public health. This includes guidelines for population-scale microbiome study design; necessary physical platforms and analysis methods; integration into public health areas such as epidemiology, nutrition, chronic disease, and global and environmental health; entrepreneurship and technology transfer; and educational curricula. Particularly in the near future, there are both opportunities for the incorporation of microbiome-based technologies into public health practice, and a growing need for policymaking and regulation around related areas such as prebiotic and probiotic supplements, novel live-cell therapies and fecal microbiota transplants.
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Leveraging the urban-rural divide for epigenetic research.
Cronjé, HT, Elliott, HR, Nienaber-Rousseau, C, Pieters, M
Epigenomics. 2020;(12):1071-1081
Abstract
Urbanization coincides with a complex change in environmental exposure and a rapid increase in noncommunicable diseases (NCDs). Epigenetics, including DNA methylation (DNAm), is thought to mediate part of the association between genetic/environmental exposure and NCDs. The urban-rural divide provides a unique opportunity to investigate the effect of the combined presence of multiple forms of environmental exposure on DNAm and the related increase in disease risk. This review evaluates the ability of three epidemiological study designs (migration, income-comparative and urban-rural designs) to investigate the role of DNAm in the association between urbanization and the rise in NCD prevalence. We also discuss the ability of each study design to address the gaps in the current literature, including the complex methylation-mediated risk attributable to the cluster of forms of exposure characterizing urban and rural living, while providing a platform for developing countries to leverage their demographic discrepancies in future research ventures.
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Naive extrapolations, overhyped claims and empty promises in ageing research and interventions need avoidance.
Rattan, SIS
Biogerontology. 2020;(4):415-421
Abstract
Most proclamations about another wonder breakthrough and another imminent miracle treatment of ageing are usually overhyped claims and empty promises. It is not that the experimental science behind those claims is totally wrong or fake. But it is often a case of being ahistorical and ignoring the cumulated knowledge and understanding of the evolutionary and biological principles of ageing and longevity. Furthermore, remaining stuck to the body-as-a-machine viewpoint reduces ageing and its associated health challenges to a mere problem of engineering and design. However, highly dynamic nature of the living systems with properties of interaction, interdependence, tolerance, adaptation and constant remodelling requires wholistic and interactive modes of understanding and maintaining health. The physiological relevance and significance of progressively accumulating molecular damage remains to be fully understood. As for ageing interventions, the three pillars of health-food, physical activity, and social and mental engagement-which actually show health-promoting effect, cannot simply be reduced to a single or a limited number of molecular targets with hopes of creating an exercise pill, a fasting pill, a happiness pill and so on. If we want to increase the credibility and socio-political-economic support of ageing research and interventions, we need to resist the temptation to overhype the claims or to make far-fetched promises, which undermine the theoretical and practical significance of new discoveries in biogerontology.