Thousands of research publications describe the effects of natural product (NP) foods and dietary supplements as well as their potential for drug development. Randomized, controlled clinical trials of such products often produce heterogenous outcomes. These costly trials too rarely have significant impacts on health practices. Reasons for this include; (a) chemical complexity and inherent variability of NP and their human consumers, (b) replicability of research, (c) insufficient focus on the clinical predictive validity of research models, (d) the poorly understood role of the gut microbiota, and (e) the breadth of methodological expertise required to navigate with requisite rigor across disciplines ranging from ethnobotany and epidemiology to nutritional clinical trials. We therefore propose a collection of new research on and good research practices for rigor in the application of 21st century chemical, biological and computational methods for studying the health effects of NP foods and dietary supplements.
Increased rigor and transparency, as well as increased attention to the clinical predictive validity or relevance of models should improve the replicability and impact of research on NP, including foods and dietary supplements. Increased focus on the need for more thorough description of experimental interventions and models, and for models that more consistently predict clinical observations, is leading to advances in areas ranging from comprehensive and quantitative analysis of NP, through computational methods for associating groups of foods or phytochemicals with specific cellular or health effects through development of more powerful models for systems ranging from in vitro cultures through preclinical models of the role of the human gut microbiome in mediating health effects of nutrition. As more sophisticated methods are developed, the impact of the research depends on the extent to which researchers assess and describe the research variables that most strongly affect replicable outcomes and clinical relevance of these methods.
This Research Topic will bring together papers describing research on, and good practices for optimally controlling, standardizing, applying, and describing critical variables of methods important for increasing the understanding of the health effects of chemically complex, inherently variable NP.
Scope includes newer methods that inform the design of clinical trials of safety and health effects of chemically complex, inherently variable NP, including:
· Aspects of these methods affecting their replicability (including variables such as ambient temperature, circadian time of data collection, background diet and prior exposure history of test subjects).
· Good practices in comprehensive and transparent reporting of these variables and of data and analytic procedures, and/or aspects that affect clinical predictive validity across human diversity.
· Methods (or aspects thereof) particularly challenging for chemically complex, inherently variable NP and diverse dietary contexts.
May include experimental analyses of impact of relevant variables on outcomes or outcome replicability, assessment of replicability and comparisons of context-related strengths/weaknesses of model systems, and good practices, including for the assessment of bias in prior reports, and may include Methods, Mini Review, Original Research, Perspective, Review, and Technology and Code submissions.
Thousands of research publications describe the effects of natural product (NP) foods and dietary supplements as well as their potential for drug development. Randomized, controlled clinical trials of such products often produce heterogenous outcomes. These costly trials too rarely have significant impacts on health practices. Reasons for this include; (a) chemical complexity and inherent variability of NP and their human consumers, (b) replicability of research, (c) insufficient focus on the clinical predictive validity of research models, (d) the poorly understood role of the gut microbiota, and (e) the breadth of methodological expertise required to navigate with requisite rigor across disciplines ranging from ethnobotany and epidemiology to nutritional clinical trials. We therefore propose a collection of new research on and good research practices for rigor in the application of 21st century chemical, biological and computational methods for studying the health effects of NP foods and dietary supplements.
Increased rigor and transparency, as well as increased attention to the clinical predictive validity or relevance of models should improve the replicability and impact of research on NP, including foods and dietary supplements. Increased focus on the need for more thorough description of experimental interventions and models, and for models that more consistently predict clinical observations, is leading to advances in areas ranging from comprehensive and quantitative analysis of NP, through computational methods for associating groups of foods or phytochemicals with specific cellular or health effects through development of more powerful models for systems ranging from in vitro cultures through preclinical models of the role of the human gut microbiome in mediating health effects of nutrition. As more sophisticated methods are developed, the impact of the research depends on the extent to which researchers assess and describe the research variables that most strongly affect replicable outcomes and clinical relevance of these methods.
This Research Topic will bring together papers describing research on, and good practices for optimally controlling, standardizing, applying, and describing critical variables of methods important for increasing the understanding of the health effects of chemically complex, inherently variable NP.
Scope includes newer methods that inform the design of clinical trials of safety and health effects of chemically complex, inherently variable NP, including:
· Aspects of these methods affecting their replicability (including variables such as ambient temperature, circadian time of data collection, background diet and prior exposure history of test subjects).
· Good practices in comprehensive and transparent reporting of these variables and of data and analytic procedures, and/or aspects that affect clinical predictive validity across human diversity.
· Methods (or aspects thereof) particularly challenging for chemically complex, inherently variable NP and diverse dietary contexts.
May include experimental analyses of impact of relevant variables on outcomes or outcome replicability, assessment of replicability and comparisons of context-related strengths/weaknesses of model systems, and good practices, including for the assessment of bias in prior reports, and may include Methods, Mini Review, Original Research, Perspective, Review, and Technology and Code submissions.
