scholarly journals Mapping the Literature on Nutritional Interventions in Cognitive Health: A Data-Driven Approach

Nutrients ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 38
Author(s):  
Erin Walsh ◽  
Nicolas Cherbuin
Keyword(s):  
Citation Network ◽  
Nutritional Intervention ◽  
Data Driven ◽  
Extensive Literature ◽  
Lifestyle Interventions ◽  
Cognitive Ageing ◽  
Cognitive Health ◽  
Nutritional Interventions ◽  
Citation Network Analysis ◽  
Data Driven Approach

Manual review of the extensive literature covering nutrition-based lifestyle interventions to promote healthy cognitive ageing has proved educational, however, data-driven techniques can better account for the large size of the literature (tens of thousands of potentially relevant publications to date) and interdisciplinary nature, where relevant publications may be found. In this study, we present a new way to map the literature landscape, focusing on nutrition-based lifestyle interventions to promote healthy cognitive ageing. We applied a combination of citation network analysis and text mining to map out the existing literature on nutritional interventions and cognitive health. Results indicated five overarching clusters of publications, which could be further deconstructed into a total of 35 clusters. These could be broadly distinguished by the focus on lifespan stages (e.g., infancy versus older age), and specificity regarding nutrition (e.g., a narrow focus on iodine deficiency versus a broad focus on weight gain). Rather than concentrating into a single cluster, interventions were present throughout the majority of the research. We conclude that a data-driven map of the nutritional intervention literature can benefit the design of future interventions, by highlighting topics and themes that could be synthesized across currently disconnected clusters of publications.

scholarly journals Mapping the Literature on Nutritional Interventions in Cognitive Health: A Data-Driven Approach

2018 ◽  
Author(s):  
Erin I. Walsh ◽  
Nicolas Cherbuin
Keyword(s):  
Citation Network ◽  
Nutritional Intervention ◽  
Data Driven ◽  
Extensive Literature ◽  
Lifestyle Interventions ◽  
Cognitive Ageing ◽  
Cognitive Health ◽  
Nutritional Interventions ◽  
Citation Network Analysis ◽  
Data Driven Approach

Manual review of the extensive literature covering nutrition-based lifestyle interventions to promote healthy cognitive ageing has proved educative, however, data-driven techniques can better account for the large size of the literature (tens of thousands of potentially relevant publications to date) and interdisciplinary nature of where relevant publications may be found. In this study we present a new way to map the literature landscape focusing on nutrition-based lifestyle interventions to promote healthy cognitive ageing. We applied a combination of citation network analysis and text mining to map out the existing literature on nutritional interventions and cognitive health. Results indicated five overarching clusters of publications, which could be further deconstructed into a total of 35 clusters. These could be broadly distinguished by focus on lifespan stages (e.g. infancy versus older age), and specificity regarding nutrition (e.g. narrow focus on iodine deficiency versus broad focus on weight gain). Rather than concentrating into a single cluster, interventions were present throughout the majority of the research. We conclude that a data-driven map of the nutritional intervention literature can benefit the design of future interventions, by highlighting topics and themes that could be synthesized across currently disconnected clusters of publications.

scholarly journals Data-driven integration of hippocampal CA1 synapse physiology in silico

2019 ◽  
Author(s):  
András Ecker ◽  
Armando Romani ◽  
Sára Sáray ◽  
Szabolcs Káli ◽  
Michele Migliore ◽  
...  
Keyword(s):  
In Silico ◽  
Hippocampal Neurons ◽  
Data Driven ◽  
Extensive Literature ◽  
Anatomy And Physiology ◽  
Integrative Framework ◽  
Ca1 Region ◽  
Hippocampal Ca1 Region ◽  
Hippocampal Ca1 ◽  
Data Driven Approach

AbstractThe anatomy and physiology of synaptic connections in rodent hippocampal CA1 have been exhaustively characterized in recent decades. Yet, the resulting knowledge remains disparate and difficult to reconcile. Here, we present a data-driven approach to integrate the current state-of-the-art knowledge on the synaptic anatomy and physiology of rodent hippocampal CA1, including axo-dendritic innervation patterns, number of synapses per connection, quantal conductances, neurotransmitter release probability, and short-term plasticity into a single coherent resource. First, we undertook an extensive literature review of paired-recordings of hippocampal neurons and compiled experimental data on their synaptic anatomy and physiology. The data collected in this manner is sparse and inhomogeneous due to the diversity of experimental techniques used by different labs, which necessitates the need for an integrative framework to unify these data. To this end, we extended a previously developed workflow for the neocortex to constrain a unifying in silico reconstruction of the synaptic physiology of CA1 connections. Our work identifies gaps in the existing knowledge and provides a complementary resource towards a more complete quantification of synaptic anatomy and physiology in the rodent hippocampal CA1 region.

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

2012 ◽  
Author(s):  
Michael Ghil ◽  
Mickael D. Chekroun ◽  
Dmitri Kondrashov ◽  
Michael K. Tippett ◽  
Andrew Robertson ◽  
...  
Keyword(s):  
Dynamic Models ◽  
Data Driven ◽  
Stochastic Dynamic ◽  
Extended Range ◽  
Data Driven Approach ◽  
Low Dimensional

A Mostly Data-Driven Approach to Inverse Text Normalization

2017 ◽  
Author(s):  
Ernest Pusateri ◽  
Bharat Ram Ambati ◽  
Elizabeth Brooks ◽  
Ondrej Platek ◽  
Donald McAllaster ◽  
...  
Keyword(s):  
Data Driven ◽  
Data Driven Approach ◽  
Text Normalization

Diet and Nutritional Interventions with the Special Role of Myo-Inositol in Gestational Diabetes Mellitus Management. An Evidence-Based Critical Appraisal

2019 ◽  
Vol 25 (22) ◽  
pp. 2467-2473 ◽  
Author(s):  
Enrique Reyes-Muñoz ◽  
Federica Di Guardo ◽  
Michal Ciebiera ◽  
Ilker Kahramanoglu ◽  
Thozhukat Sathyapalan ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Metabolic Diseases ◽  
Nutritional Intervention ◽  
Attractive Alternative ◽  
Special Role ◽  
Dose Frequency ◽  
Nutritional Interventions

Background: Gestational Diabetes Mellitus (GDM), defined as glucose intolerance with onset or first recognition during pregnancy, represents one of the most common maternal-fetal complications during pregnancy and it is associated with poor perinatal outcomes. To date, GDM is a rising condition over the last decades coinciding with the ongoing epidemic of obesity and Type 2 Diabetes Mellitus (T2DM). Objective: The aim of this review is to discuss the role of diet and nutritional interventions in preventing GDM with the explanation of the special role of myo-inositol (MI) in this matter. Methods: We performed an overview of the most recent literature data on the subject with particular attention to the effectiveness of diet and nutritional interventions in the prevention of GDM with the special role of MI. Results: Nutritional intervention and physical activity before and during pregnancy are mandatory in women affected by GDM. Moreover, the availability of insulin-sensitizers such as different forms of inositol has dramatically changed the scenario, allowing the treatment of several metabolic diseases, such as those related to glucose dysbalance. Although the optimal dose, frequency, and form of MI administration need to be further investigated, diet supplementation with MI appears to be an attractive alternative for the GDM prevention as well as for the reduction of GDM-related complications. Conclusion: More studies should be conducted to prove the most effective nutritional intervention in GDM. Regarding the potential effectiveness of MI, further evidence in multicenter, randomized controlled trials is needed to draw firm conclusions.

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