| 1. |
- Lee, Bruce Y., et al.
(författare)
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Research gaps and opportunities in precision nutrition : an NIH workshop report
- 2022
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Ingår i: The American journal of clinical nutrition. - : Elsevier BV. - 1938-3207 .- 0002-9165. ; 116:6, s. 1877-1900
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Tidskriftsartikel (refereegranskat)abstract
- Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.
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| 2. |
- Bermon, Stephane, et al.
(författare)
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Consensus Statement Immunonutrition and Exercise.
- 2017
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Ingår i: Exercise immunology review. - 1077-5552. ; 23, s. 8-50
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Forskningsöversikt (refereegranskat)abstract
- In this consensus statement on immunonutrition and exercise, a panel of knowledgeable contributors from across the globe provides a consensus of updated science, including the background, the aspects for which a consensus actually exists, the controversies and, when possible, suggested directions for future research.
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| 3. |
- Fereidunian, A., et al.
(författare)
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AAHES: A hybrid expert system realization of adaptive autonomy for Smart Grid
- 2010
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Ingår i: IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2010; Gothenburg; Sweden; 11 October 2010 through 13 October 2010. - 9781424485109 ; , s. Art. no. 5638929-
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Konferensbidrag (refereegranskat)abstract
- Smart grid expectations objectify the need for optimizing power distribution systems greater than ever. Distribution Automation (DA) is an integral part of the SG solution; however, disregarding human factors in the DA systems can make it more problematic than beneficial. As a consequence, Human-Automation Interaction (HAI) theories can be employed to optimize the DA systems in a human-centered manner. Earlier we introduced a novel framework for the realization of Adaptive Autonomy (AA) concept in the power distribution network using expert systems. This research presents a hybrid expert system for the realization of AA, using both Artificial Neural Networks (ANN) and Logistic Regression (LR) models, referred to as AAHES, respectively. AAHES uses neural networks and logistic regression as an expert system inference engine. This system fuses LR and ANN models' outputs which will results in a progress, comparing to both individual models. The practical list of environmental conditions and superior experts' judgments are used as the expert systems database. Since training samples will affect the expert systems performance, the AAHES is implemented using six different training sets. Finally, the results are interpreted in order to find the best training set. As revealed by the results, the presented AAHES can effectively determine the proper level of automation for changing the performance shaping factors of the HAI systems in the smart grid environment.
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| 4. |
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| 5. |
- Joma, Basma H, et al.
(författare)
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A Murine Model for Enhancement of Streptococcus pneumoniae Pathogenicity Upon Viral Infection and Advanced Age
- 2021
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Ingår i: Infection and Immunity. - 1098-5522. ; 89:8
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Tidskriftsartikel (refereegranskat)abstract
- Streptococcus pneumoniae (pneumococcus) resides asymptomatically in the nasopharynx but can progress from benign colonizer to lethal pulmonary or systemic pathogen. Both viral infection and aging are risk factors for serious pneumococcal infections. Previous work established a murine model that featured the movement of pneumococcus from the nasopharynx to the lung upon nasopharyngeal inoculation with influenza A virus (IAV) but did not fully recapitulate the severe disease associated with human co-infection. We built upon this model by first establishing pneumococcal nasopharyngeal colonization, then inoculating both the nasopharynx and lungs with IAV. In young (2 months) mice, co-infection triggered bacterial dispersal from the nasopharynx into the lungs, pulmonary inflammation, disease and mortality in a fraction of mice. In old mice (20-22 months), co-infection resulted in earlier and more severe disease. Aging was not associated with greater bacterial burdens but rather with more rapid pulmonary inflammation and damage. Both aging and IAV infection led to inefficient bacterial killing by neutrophils ex vivo Conversely, aging and pneumococcal colonization also blunted IFN-α production and increased pulmonary IAV burden. Thus, in this multistep model, IAV promotes pneumococcal pathogenicity by modifying bacterial behavior in the nasopharynx, diminishing neutrophil function, and enhancing bacterial growth in the lung, while pneumococci increase IAV burden likely by compromising a key antiviral response. Thus, this model provides a means to elucidate factors, such as age and co-infection, that promote the evolution of S. pneumoniae from asymptomatic colonizer to invasive pathogen, as well as to investigate consequences of this transition on antiviral defense.
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