scholarly journals Symposium 2: Modern approaches to nutritional research challenges Targeted and non-targeted approaches for metabolite profiling in nutritional research

2009 ◽  
Vol 69 (1) ◽  
pp. 95-102 ◽  
Author(s):  
John K. Lodge
Keyword(s):  
Data Analysis ◽  
Metabolic Pathways ◽  
Present Report ◽  
New Technology ◽  
Nutrient Status ◽  
Tolerance Test ◽  
Careful Consideration ◽  
Metabolite Profiles ◽  
Health And Disease ◽  
Isoflavone Metabolism

The present report discusses targeted and non-targeted approaches to monitor single nutrients and global metabolite profiles in nutritional research. Non-targeted approaches such as metabolomics allow for the global description of metabolites in a biological sample and combine an analytical platform with multivariate data analysis to visualise patterns between sample groups. In nutritional research metabolomics has generated much interest as it has the potential to identify changes to metabolic pathways induced by diet or single nutrients, to explore relationships between diet and disease and to discover biomarkers of diet and disease. Although still in its infancy, a number of studies applying this technology have been performed; for example, the first study in 2003 investigated isoflavone metabolism in females, while the most recent study has demonstrated changes to various metabolic pathways during a glucose tolerance test. As a relatively new technology metabolomics is faced with a number of limitations and challenges including the standardisation of study design and methodology and the need for careful consideration of data analysis, interpretation and identification. Targeted approaches are used to monitor single or multiple nutrient and/or metabolite status to obtain information on concentration, absorption, distribution, metabolism and elimination. Such applications are currently widespread in nutritional research and one example, using stable isotopes to monitor nutrient status, is discussed in more detail. These applications represent innovative approaches in nutritional research to investigate the role of both single nutrients and diet in health and disease.

Mass spectrometry approaches for vitamin E research

2008 ◽  
Vol 36 (5) ◽  
pp. 1066-1070 ◽  
Author(s):  
John K. Lodge
Keyword(s):  
Vitamin E ◽  
Stable Isotope ◽  
Metabolic Pathways ◽  
Protective Role ◽  
Cigarette Smokers ◽  
Metabolite Profiles ◽  
Health And Disease ◽  
Isotope Studies ◽  
Vitamin E Status

Vitamin E is an important nutrient with antioxidant and non-antioxidant functions, and certain evidence suggests that it has a cardiovascular protective role. It is therefore important to maintain an optimal vitamin E status. In the present paper, a number of MS applications to monitor vitamin E status and its interactions, including the use of stable-isotope-labelled vitamin E and metabonomics, are highlighted. Specifically, stable-isotope studies have been used to monitor vitamin E absorption, hepatic processing and lipoprotein transport. As oxidative stress may influence vitamin E status, a number of studies comparing vitamin E biokinetics and metabolism in cigarette smokers and non-smokers have been able to show differences in vitamin E processing in smokers. Metabonomics represents a method to identify changes to metabolite profiles, offering the potential to investigate interactions between vitamin E and metabolic pathways. These applications represent innovative approaches to investigate the role of vitamin E in health and disease.

scholarly journals The Role of Cell Metabolism in Innate Immune Memory

2020 ◽  
pp. 1-9
Author(s):  
Anaisa Valido Ferreira ◽  
Jorge Domiguéz-Andrés ◽  
Mihai Gheorghe Netea
Keyword(s):  
Metabolic Pathways ◽  
Tricarboxylic Acid Cycle ◽  
Cell Metabolism ◽  
Innate Immune ◽  
Immune Memory ◽  
Functional Changes ◽  
Trained Immunity ◽  
Health And Disease

Immunological memory is classically attributed to adaptive immune responses, but recent studies have shown that challenged innate immune cells can display long-term functional changes that increase nonspecific responsiveness to subsequent infections. This phenomenon, coined <i>trained immunity</i> or <i>innate immune memory</i>, is based on the epigenetic reprogramming and the rewiring of intracellular metabolic pathways. Here, we review the different metabolic pathways that are modulated in trained immunity. Glycolysis, oxidative phosphorylation, the tricarboxylic acid cycle, amino acid, and lipid metabolism are interplaying pathways that are crucial for the establishment of innate immune memory. Unraveling this metabolic wiring allows for a better understanding of innate immune contribution to health and disease. These insights may open avenues for the development of future therapies that aim to harness or dampen the power of the innate immune response.

ENDOCRINE DISTURBANCES IN PATIENTS WITH CONGENITAL AQUEDUCTAL STENOSIS

1975 ◽  
Vol 80 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Robert Fiedler ◽  
Dorothy T. Krieger
Keyword(s):  
Present Report ◽  
Aqueductal Stenosis ◽  
Tolerance Test ◽  
Insulin Tolerance Test ◽  
Endocrine Function ◽  
Insulin Tolerance ◽  
Endocrine Disturbances ◽  
Reversible Lesion ◽  
Hormone Responses

ABSTRACT Congenital stenosis of the aqueduct of Sylvius is reported to be associated with sella turcia enlargement and clinical and laboratory abnormalities of the hypothalamic-pituitary-target-organ axis. It is a surgically reversible lesion. In the present report, 3 female patients with this lesion were studied with tests of basal endocrine function, as well as insulin tolerance tests, response to metyrapone and determination of circadian periodicity of plasma cortisol levels. In one patient all testing was normal and no surgery was performed. In 2 other patients the insulin tolerance test revealed either abnormal cortisol or growth hormone responses and in one patient urinary gonadotrophins were absent. All tests became normal post-operatively although in one instance not completely so until 5 years after surgery.

scholarly journals Consequences of Paternal Nutrition on Offspring Health and Disease

Nutrients ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 2818
Author(s):  
Pauline Dimofski ◽  
David Meyre ◽  
Natacha Dreumont ◽  
Brigitte Leininger-Muller
Keyword(s):  
Metabolic Pathways ◽  
Maternal Diet ◽  
Disease Onset ◽  
Adult Life ◽  
Intermittent Fasting ◽  
Low Protein ◽  
Periconceptional Period ◽  
Health And Disease ◽  
Offspring Health ◽  
The Impact

It is well established that the maternal diet during the periconceptional period affects the progeny’s health. A growing body of evidence suggests that the paternal diet also influences disease onset in offspring. For many years, sperm was considered only to contribute half of the progeny’s genome. It now appears that it also plays a crucial role in health and disease in offspring’s adult life. The nutritional status and environmental exposure of fathers during their childhood and/or the periconceptional period have significant transgenerational consequences. This review aims to describe the effects of various human and rodent paternal feeding patterns on progeny’s metabolism and health, including fasting or intermittent fasting, low-protein and folic acid deficient food, and overnutrition in high-fat and high-sugar diets. The impact on pregnancy outcome, metabolic pathways, and chronic disease onset will be described. The biological and epigenetic mechanisms underlying the transmission from fathers to their progeny will be discussed. All these data provide evidence of the impact of paternal nutrition on progeny health which could lead to preventive diet recommendations for future fathers.

scholarly journals DIGITAL MARKETING 5-GENERATION TECHNOLOGY AND ITS ACCEPTANCE BEHAVIOR

2021 ◽  
pp. 46-59
Keyword(s):  
Data Analysis ◽  
Technology Acceptance ◽  
Digital Media ◽  
New Technology ◽  
Mobile Services ◽  
Perceived Usefulness ◽  
Mobile Technologies ◽  
Digital Marketing ◽  
Cross Sectional ◽  
Factors Affecting

Cumulative usage of digital media by customers, most of the companies are exploitation the digital marketing to get the access towards their target clients and markets. With the development of mobile technologies, mobile services have become an essential part of people's lives. After an ample research a series of advance experimentation and development, the mobile technology emerged and enters into more advance 5-G period. The purpose of this study is to examine various marketing strategies and investigate Pakistani consumers’ approach towards the existing mobile services and classify the factors affecting their preferences towards 5-G acceptance. With a view to accomplish this study. A cross-sectional technique with the help of questionnaire was used to collect data. 15 to 45 years age people male & female were our targeted audience from the different places of Multan city (Punjab province) Pakistan. 500 questionnaires were distributed and received (n) 430 which were completed by all aspects. (F=58%) & (M=42%). SPSS, (22nd) version used for data analysis. After the data analysis and discussion, (r) correlation was retrospection that (DV), (IV) & (MV) have a strong and positive relationship between each other. (r2) regression analysis also showed the confident, positive and durable relation among the all variables. Results show that the convenience, price, service quality, self-efficacy and value are the factors affecting consumers’ acceptance in the presence of a moderator that is perceived usefulness. Suggested an extended TAM (Technology Acceptance Model) for checking consumer’s behavior towards 5-G mobile services. Consumers should adopt the new technology and utilize it for the benefits of him/herself and for the community, nation and state.

scholarly journals Implications of a Narrow Automated Vehicle-Exclusive Lane on Interstate 15 Express Lanes

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Sahar Ghanipoor Machiani ◽  
Alidad Ahmadi ◽  
Walter Musial ◽  
Anagha Katthe ◽  
Benjamin Melendez ◽  
...  
Keyword(s):  
Data Analysis ◽  
Simulation Analysis ◽  
Careful Consideration ◽  
Human Capabilities ◽  
Crash Data ◽  
Automated Vehicle ◽  
The Difference ◽  
Differential Increase ◽  
Operational Impacts ◽  
Crash Data Analysis

The main objective of this study is to evaluate the safety and operational impacts of an innovative infrastructure solution for safe and efficient integration of Automated Vehicle (AV) as an emerging technology into an existing transportation system. Filling the gap in the limited research on the effect of AV technology on infrastructure standards, this study investigates implications of adding a narrow reversible AV-exclusive lane to the existing configuration of I-15 expressway in San Diego, resulting in a 9 ft AV reversible lane and, in both directions, two 12-feet lanes for HOV and FasTrak vehicles. Given the difference between the operation of AVs and human-driven vehicles and reliance of AVs on sensors as opposed to human capabilities, the question is should we provide narrower AV-exclusive roadways assuming AVs are more precise in lateral and longitudinal lane keeping behaviour? To accomplish the goal of the project, a historical crash data analysis and a traffic simulation analysis were conducted. Crash data analysis revealed that unsafe speed, improper turning, and unsafe lane change are the most recurring primary collision factors on I-15 ELs. AVs’ automated longitudinal and lateral control systems could potentially reduce these types of collisions on an AV-exclusive lane with proper infrastructure features for AV sensor operation (e.g., distinct lane marking). Microsimulation findings indicated an AV-exclusive lane may increase traffic flow and density by up to 14% and 24%, respectively. It also showed that average speed is reduced. However, this could lead to the speed differential increase between the exclusive lane and adjacent lane requiring careful consideration if additional treatments or barriers are needed. The results of this study contribute to infrastructure adaptation to AV technology and future AV-exclusive lanes implementations.

Wearable Computing

2014 ◽  
pp. 96-120
Author(s):  
John Lindström ◽  
Claas Hanken
Keyword(s):  
New Technology ◽  
Wearable Computing ◽  
Legal Aspects ◽  
Careful Consideration ◽  
Security And Privacy ◽  
Bring Your Own Device ◽  
Work Processes ◽  
Intelligence Gathering ◽  
Recent Developments ◽  
Legal Frameworks

Wearable computing is gaining more and more interest as new “wearables,” intended for both work and leisure, are introduced. This trend brings benefits and challenges; for instance, the potential to improve work processes and issues related to IT management and privacy. The introduction and use of wearable computing provides opportunities to improve and reengineer work processes in organizations but can at the same time introduce alignment problems, as users in organizations may adopt the new technology before organizations are prepared. Further, alignment problems posed by the emerging trend, “Bring Your Own Device” (BYOD), are discussed. In addition, as in the cloud computing area, needed and necessary supportive legal frameworks have not yet fully addressed the new wearable computing technology. In the light of recent developments regarding global intelligence gathering, security and privacy concerns must be given careful consideration. Different alignment concepts for managing security challenges and legal aspects related to wearable computing, such as cultivation, care, hospitality, and care with hospitality, are discussed in the chapter.

Data Mining and Homeland Security

2011 ◽  
pp. 1323-1331
Author(s):  
Jeffrey W. Seifert
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Homeland Security ◽  
Predictive Analytics ◽  
New Technology ◽  
Analytical Techniques ◽  
Data Sources ◽  
High Expectations ◽  
Multiple Data ◽  
Factual Data

A significant amount of attention appears to be focusing on how to better collect, analyze, and disseminate information. In doing so, technology is commonly and increasingly looked upon as both a tool, and, in some cases, a substitute, for human resources. One such technology that is playing a prominent role in homeland security initiatives is data mining. Similar to the concept of homeland security, while data mining is widely mentioned in a growing number of bills, laws, reports, and other policy documents, an agreed upon definition or conceptualization of data mining appears to be generally lacking within the policy community (Relyea, 2002). While data mining initiatives are usually purported to provide insightful, carefully constructed analysis, at various times data mining itself is alternatively described as a technology, a process, and/or a productivity tool. In other words, data mining, or factual data analysis, or predictive analytics, as it also is sometimes referred to, means different things to different people. Regardless of which definition one prefers, a common theme is the ability to collect and combine, virtually if not physically, multiple data sources, for the purposes of analyzing the actions of individuals. In other words, there is an implicit belief in the power of information, suggesting a continuing trend in the growth of “dataveillance,” or the monitoring and collection of the data trails left by a person’s activities (Clarke, 1988). More importantly, it is clear that there are high expectations for data mining, or factual data analysis, being an effective tool. Data mining is not a new technology but its use is growing significantly in both the private and public sectors. Industries such as banking, insurance, medicine, and retailing commonly use data mining to reduce costs, enhance research, and increase sales. In the public sector, data mining applications initially were used as a means to detect fraud and waste, but have grown to also be used for purposes such as measuring and improving program performance. While not completely without controversy, these types of data mining applications have gained greater acceptance. However, some national defense/homeland security data mining applications represent a significant expansion in the quantity and scope of data to be analyzed. Moreover, due to their security-related nature, the details of these initiatives (e.g., data sources, analytical techniques, access and retention practices, etc.) are usually less transparent.

Data Mining and Homeland Security

2011 ◽  
pp. 277-282 ◽  
Author(s):  
J. W. Seifert
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Homeland Security ◽  
Predictive Analytics ◽  
New Technology ◽  
Analytical Techniques ◽  
Data Sources ◽  
High Expectations ◽  
Multiple Data ◽  
Factual Data

A significant amount of attention appears to be focusing on how to better collect, analyze, and disseminate information. In doing so, technology is commonly and increasingly looked upon as both a tool, and, in some cases, a substitute, for human resources. One such technology that is playing a prominent role in homeland security initiatives is data mining. Similar to the concept of homeland security, while data mining is widely mentioned in a growing number of bills, laws, reports, and other policy documents, an agreed upon definition or conceptualization of data mining appears to be generally lacking within the policy community (Relyea, 2002). While data mining initiatives are usually purported to provide insightful, carefully constructed analysis, at various times data mining itself is alternatively described as a technology, a process, and/or a productivity tool. In other words, data mining, or factual data analysis, or predictive analytics, as it also is sometimes referred to, means different things to different people. Regardless of which definition one prefers, a common theme is the ability to collect and combine, virtually if not physically, multiple data sources, for the purposes of analyzing the actions of individuals. In other words, there is an implicit belief in the power of information, suggesting a continuing trend in the growth of “dataveillance,” or the monitoring and collection of the data trails left by a person’s activities (Clarke, 1988). More importantly, it is clear that there are high expectations for data mining, or factual data analysis, being an effective tool. Data mining is not a new technology but its use is growing significantly in both the private and public sectors. Industries such as banking, insurance, medicine, and retailing commonly use data mining to reduce costs, enhance research, and increase sales. In the public sector, data mining applications initially were used as a means to detect fraud and waste, but have grown to also be used for purposes such as measuring and improving program performance. While not completely without controversy, these types of data mining applications have gained greater acceptance. However, some national defense/homeland security data mining applications represent a significant expansion in the quantity and scope of data to be analyzed. Moreover, due to their security-related nature, the details of these initiatives (e.g., data sources, analytical techniques, access and retention practices, etc.) are usually less transparent.

scholarly journals Vertical and horizontal integration of multi-omics data with miodin

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Benjamin Ulfenborg
Keyword(s):  
Data Analysis ◽  
R Package ◽  
Heterogeneous Data ◽  
Omics Data ◽  
Technical Expertise ◽  
Horizontal Integration ◽  
Level Data ◽  
Genomics And Proteomics ◽  
Health And Disease ◽  
Molecular Layers

Abstract Background Studies on multiple modalities of omics data such as transcriptomics, genomics and proteomics are growing in popularity, since they allow us to investigate complex mechanisms across molecular layers. It is widely recognized that integrative omics analysis holds the promise to unlock novel and actionable biological insights into health and disease. Integration of multi-omics data remains challenging, however, and requires combination of several software tools and extensive technical expertise to account for the properties of heterogeneous data. Results This paper presents the miodin R package, which provides a streamlined workflow-based syntax for multi-omics data analysis. The package allows users to perform analysis of omics data either across experiments on the same samples (vertical integration), or across studies on the same variables (horizontal integration). Workflows have been designed to promote transparent data analysis and reduce the technical expertise required to perform low-level data import and processing. Conclusions The miodin package is implemented in R and is freely available for use and extension under the GPL-3 license. Package source, reference documentation and user manual are available at https://gitlab.com/algoromics/miodin.

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