From immune system to health systems--challenges for health research

There are many similarities between the immune system and health systems. Both are knowledge-based learning systems with an ultimate common objective of maintaining the health of individuals and populations, respectively. The immune system learns from the environment, and knowledge and discovery are key drivers of health systems improvement and improving health status. But discovery goes well beyond immunology, virology and genomics, for example, in the quest to develop new drugs, vaccines and diagnostic tests. New ways must also be discovered to make sure that these products reach the people who need it most. We must discover ways for knowledge to be turned into effective policies, to inform the practice of healthcare and to inform the public and society at large. Only if discovery is seen in its broadest perspective will we be able to reach the goal of health for all.     

Nutritional genomics era: opportunities toward a genome-tailored nutritional regimen

There is increasing evidence indicating that nutritional genomics represents a promise to improve public health. This goal will be reached by highlighting the mechanisms through which diet can reduce the risk of monogenic and common polygenic diseases. Indeed, nutrition is a very relevant environmental factor involved in the development and progression of metabolic disorders, as well as other kind of diseases. The revolutionary changes in the field of genomics have led to the development and implementation of new technologies and molecular tools. These technologies have a useful application in the nutritional sciences, since they allow a more precise and accurate analysis of biochemical alterations, in addition to filling fundamental gaps in the knowledge of nutrient–genome interactions in both health and disease. Overall, these advances will open undiscovered ways in genome-customized diets for disease prevention and therapy. This review summarizes the recent knowledge concerning this novel nutritional approach, paying attention to the human genome variations, such as single-nucleotide polymorphisms and copy number variations, gene expression and innovative molecular tools to reveal them.     

Wild immunology

In wild populations, individuals are regularly exposed to a wide range of pathogens. In this context, organisms must elicit and regulate effective immune responses to protect their health while avoiding immunopathology. However, most of our knowledge about the function and dynamics of immune responses comes from laboratory studies performed on inbred mice in highly controlled environments with limited exposure to infection. Natural populations, on the other hand, exhibit wide genetic and environmental diversity. We argue that now is the time for immunology to be taken into the wild. The goal of 'wild immunology' is to link immune phenotype with host fitness in natural environments. To achieve this requires relevant measures of immune responsiveness that are both applicable to the host-parasite interaction under study and robustly associated with measures of host and parasite fitness. Bringing immunology to nonmodel organisms and linking that knowledge host fitness, and ultimately population dynamics, will face difficult challenges, both technical (lack of reagents and annotated genomes) and statistical (variation among individuals and populations). However, the affordability of new genomic technologies will help immunologists, ecologists and evolutionary biologists work together to translate and test our current knowledge of immune mechanisms in natural systems. From this approach, ecologists will gain new insight into mechanisms relevant to host health and fitness, while immunologists will be given a measure of the real-world health impacts of the immune factors they study. Thus, wild immunology can be the missing link between laboratory-based immunology and human, wildlife and domesticated animal health.     

A Roadmap to an Equitable Digital Diabetes Ecosystem

ObjectivesDiabetes management presents a substantial burden to individuals living with the condition and their families, health care professionals, and health care systems. Although an increasing number of digital tools are available to assist with tasks such as blood glucose monitoring and insulin dose calculation, multiple persistent barriers continue to prevent their optimal use.MethodsAs a guide to creating an equitable connected digital diabetes ecosystem, we propose a roadmap with key milestones that need to be achieved along the way.ResultsDuring the Coronavirus 2019 pandemic, there was an increased use of digital tools to support diabetes care, but at the same time, the pandemic also highlighted problems of inequities in access to and use of these same technologies. Based on these observations, a connected diabetes ecosystem should incorporate and optimize the use of existing treatments and technologies, integrate tasks such as glucose monitoring, data analysis, and insulin dose calculations, and lead to improved and equitable health outcomes.ConclusionsDevelopment of this ecosystem will require overcoming multiple obstacles, including interoperability and data security concerns. However, an integrated system would optimize existing devices, technologies, and treatments to improve outcomes.     

Adipocytes under assault: Environmental disruption of adipose physiology

The burgeoning obesity epidemic has placed enormous strains on individual and societal health mandating a careful search for pathogenic factors, including the contributions made by endocrine disrupting chemicals (EDCs). In addition to evidence that some exogenous chemicals have the capacity to modulate classical hormonal signaling axes, there is mounting evidence that several EDCs can also disrupt metabolic pathways and alter energy homeostasis. Adipose tissue appears to be a particularly important target of these metabolic disruptions. A diverse array of compounds has been shown to alter adipocyte differentiation, and several EDCs have been shown to modulate adipocyte physiology, including adipocytic insulin action and adipokine secretion. This rapidly emerging evidence demonstrating that environmental contaminants alter adipocyte function emphasizes the potential role that disruption of adipose physiology by EDCs may play in the global epidemic of metabolic disease. Further work is required to better characterize the molecular targets responsible for mediating the effects of EDCs on adipose tissue. Improved understanding of the precise signaling pathways altered by exposure to environmental contaminants will enhance our understanding of which chemicals pose a threat to metabolic health and how those compounds synergize with lifestyle factors to promote obesity and its associated complications. This knowledge may also improve our capacity to predict which synthetic compounds may alter energy homeostasis before they are released into the environment while also providing critical evidentiary support for efforts to restrict the production and use of chemicals that pose the greatest threat to human metabolic health. This article is part of a Special Issue entitled: Modulation of Adipose Tissue in Health and Disease.     

The emerging role for rat models in gene discovery

Rat models have been used for many decades to study physiological and pathophysiological mechanisms. Prior to the release of the rat genome and new technologies for targeting gene manipulation, the rat had been the underdog in the genomics era, despite the abundance of physiological data compared to the mouse. The overarching goal of biomedical research is to improve health and advance medical science. Translating human disease gene discovery and validation in the rat, through the use of emerging technologies and integrated tools and databases, is providing power to understand the genetics, environmental influences, and biology of disease. In this review we briefly outline the rat models, bioinformatics tools, and technologies that are changing the landscape of translational research. The strategies used to translate disease traits to genes to function, and, ultimately, to improve human health is discussed. Finally, our perspective on how rat models will continue to positively impact biomedical research is provided.     

Protein interaction-targeted drug discovery: evaluating critical issues

Employment of the decision strategies outlined in this general discussion should help to pinpoint mode of activity in drug development and validation. Overall, as a paradigm for drug development, a search for small molecules that can interfere with PPIs would seem to have significant long term potential. At present, the level of structural knowledge in databases is not sufficient to predict in toto the protein binding properties of a modeled drug, but as databases improve, this may become generally feasible. A major point that remains to be determined is how much specificity of protein binding can be incorporated into molecules of generally less than 500 Da. Finally, integration of PPI-targeting strategies with other approaches towards drug design will enhance the number of signaling pathways that can effectively be targeted. These points will be particularly pertinent as technologies permit a systematic identification of encoded protein interactions that govern the proteornic complement of cells.     

Metabolic deterioration of the sedentary control group in clinical trials

Randomized clinical trials of exercise training regimens in sedentary individuals have provided a mechanistic understanding of the long-term health benefits and consequences of physical activity and inactivity. The sedentary control periods from these trials have provided evidence of the progressive metabolic deterioration that results from as little as 4-6 mo of continuing a physically inactive lifestyle. These clinical trials have also demonstrated that only a modest amount of physical activity is required to prevent this metabolic deterioration, and this amount of physical activity is consistent with current physical activity recommendations (150 min/wk of moderate intensity physical activity). These recommendations have been issued to the general population for a vast array of health benefits. While greater adherence to these recommendations should result in substantial improvements in the health of the population, these recommendations still remain inadequate for many individuals. An individual's physical activity requirements are influenced by such factors as an individual's diet, nonexercise physical activity patterns, genetic profile, and medications. Improving the understanding of how these factors influence an individual's physical activity requirements will help advance the field and help move the field toward the development of more personalized physical activity recommendations.     

Biocatalysis for pharmaceuticals--status and prospects for a key technology

In reviewing how biocatalysis can be applied to improve chiral synthesis for pharmaceuticals it becomes clear that there will be many opportunities using a simple enzyme system but that many of the more useful applications will require the whole cell because of the requirement for cofactors. An assessment is made of the opportunities to apply metabolic engineering to construct de novo metabolic pathways for the biosynthesis of useful advanced intermediates and a conceptual example is provided for the biosynthesis of cis-aminoindanol. We predict that in the future novel pathways will be assembled for a one-step biosynthesis of many semisynthetic natural products.     

Nutritional status, genetic susceptibility, and insulin resistance--important precedents to atherosclerosis

Atherosclerosis is a progressive disease that starts early in life and is manifested clinically as coronary artery disease (CAD), cerebrovascular disease, or peripheral artery disease. CAD remains the leading cause of morbidity and mortality in Western society despite the great advances made in understanding its underlying pathophysiology. The key risk factors associated with CAD include hypercholesterolemia, hypertension, poor diet, obesity, age, male gender, smoking, and physical inactivity. Genetics also play an important role that may interact with environmental factors, including diet, nutritional status, and physiological parameters. Furthermore, certain chronic inflammatory conditions also predispose to the development of CAD. The spiraling increase in obesity rates worldwide has made it more pertinent than ever before to understand the metabolic perturbations that link over nutrition to enhanced cardiovascular risk. Great breakthroughs have been made at the pharmacological level to manage CAD; statins and aspirin have revolutionized treatment of CAD and prolonged lifespan. Nonetheless, lifestyle intervention prior to clinical presentation of CAD symptoms would negate/delay the need for chronic pharmacotherapy in at-risk individuals which in turn would relieve healthcare systems of a costly burden. Throughout this review, we debate the relative impact of nutrition versus genetics in driving CAD. We will investigate how overnutrition affects adipose tissue biology and drives IR and will discuss the subsequent implications for the cardiovascular system. Furthermore, we will discuss how lifestyle interventions including diet modification and weight loss can improve both IR and metabolic dyslipidemia that is associated with obesity. We will conclude by delving into the concept that nutritional status interacts with genetic susceptibility, such that perhaps a more personalized nutrition approach may be more effective in determining diet-related risk as well as response to nutritional interventions.     

Do we know enough? A scientific and ethical analysis of the basis for genetic-based personalized nutrition

This article discusses the prospects and limitations of the scientific basis for offering personalized nutrition advice based upon individual genetic information. Two divergent scientific positions are presented, with an ethical comment. The crucial question is whether the current knowledge base is sufficiently strong for taking an ethically responsible decision to offer personalized nutrition advice based upon gene–diet–health interaction. According to the first position, the evidence base for translating the outcomes of nutrigenomics research into personalized nutritional advice is as yet immature. There is also limited evidence that genotype-based dietary advice will motivate appropriate behavior changes. Filling the gaps in our knowledge will require larger and better randomized controlled trials. According to the second position, personalized nutrition must be evaluated in relation to generally accepted standard dietary advice—partly derived from epidemiological observations and usually not proven by clinical trials. With personalized nutrition, we cannot demand stronger evidence. In several specific cases of gene–diet interaction, it may be more beneficial for individuals with specific genotypes to follow personalized advice rather than general dietary recommendations. The ethical comment, finally, considers the ethical aspects of deciding how to proceed in the face of such uncertainty. Two approaches for an ethically responsible way forward are proposed. Arguing from a precautionary approach, it is suggested that personalized dietary advice should be offered only when there is strong scientific evidence for health effects, followed by stepwise evaluation of unforeseen behavioral and psychological effects. Arguing from theoretical and applied ethics as well as psychology, it is also suggested that personalized advice should avoid paternalism and instead focus on supporting the autonomous choice of each person.     

Towards a taxonomy of Bacteria and Archaea based on interactive and cumulative data repositories

Taxonomy in the second decade of the 21st century is benefiting from technological advances in molecular microbiology, especially those related to genomics. Gene and genome databases are significantly increasing due to intense research activities in the field of molecular ecology and genomics. Taxa, and especially species, are tailored by means of the recognition of a phylogenetic, genomic and phenotypic coherence that reveal their uniqueness in the classification schema. Phylogenetic coherence is mainly revealed by means of 16S rRNA gene analyses for which curated databases such as EzTaxon and LTP provide a valuable tool for tree reconstruction to taxonomy users. On the other hand, in silico full or partial genomic sequence comparisons are called on to substitute cumbersome techniques such as DNA-DNA hybridization (DDH) to genomically circumscribe species. DDH similarity values around 70% would be equivalent to ANI values of 96%. Finally, finding an exclusive phenotypic property for the taxa to be classified is of paramount relevance to producing an operative and predictive classification system. The current methods used for taxonomic classification require significant laboratory experimentation, and generally will not produce interactive databases. The new high-throughput metabolomic technologies, such as ICR-FT and MALDI-TOF mass spectrometry methods, open the door to the construction of metabolic databases for taxonomic purposes. It is to be foreseen that, in the future, taxonomists will benefit significantly from public databases speeding up the classification process. However, serious effort will be needed to harmonize them and to prevent inaccurate material.     

Embryology and disorders of sexual development

Recent consensus is that individuals with atypical male or female phenotype are to be considered to have a "disorder of sexual development." The goal is to eliminate previous terminology that included the terms intersex, hermaphrodite, or pseudohermaphrodite. However, the teaching of embryology, and particularly teaching about the development of the reproductive system, still has not made the change to the new terminology. If those who teach embryology to health-care professionals remain unaware of the controversies associated with the old terminology and continue to use it, they will perpetuate a nomenclature that can be destructive. Any terminology must be used carefully to avoid dehumanizing the individual to a disease or a medical state. We should be able to state clearly the variations in morphology that exist, attend to the immediate health of the individual, and avoid any attempt to stigmatize gender-atypical individuals.     

Systems metabolic engineering: Genome-scale models and beyond

The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches – based on the data collected with high throughput technologies – to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems.     

Application of plant tissue cultures in phytoremediation research: Incentives and limitations

The aim of this review is to critically assess the benefits and limitations associated with the use of in vitro plant cell and organ cultures as research tools in phytoremediation studies. Plant tissue cultures such as callus, cell suspensions, and hairy roots are applied frequently in phytoremediation research as model plant systems. In vitro cultures offer a range of experimental advantages in studies aimed at examining the intrinsic metabolic capabilities of plant cells and their capacity for toxicity tolerance. The ability to identify the contributions of plant cells to pollutant uptake and detoxification without interference from microorganisms is of particular significance in the search for fundamental knowledge about plants. However, if the ultimate goal of plant tissue culture experiments is the development of practical phytoremediation technology, the limitations inherent in the use of in vitro cultures as a representative of whole plants in the field must be recognized. The bioavailability of contaminants and the processes of pollutant uptake and metabolite distribution are likely to be substantially different in the two systems; this can lead to qualitative as well as quantitative differences in metabolic profiles and tolerance characteristics. Yet, many studies have demonstrated that plant tissue cultures are an extremely valuable tool in phytoremediation research. The results derived from tissue cultures can be used to predict the responses of plants to environmental contaminants, and to improve the design and thus reduce the cost of subsequent conventional whole plant experiments. Biotechnol. Bioeng. 2009;103: 60–76.     

The use of information technology in improving medical performance. Part I. Information systems for medical transactions

Investment in medical information technologies reached $15 billion in 1996. However, these technologies have not had the wide impact predicted in streamlining bureaucracy, improving communications, and raising the effectiveness of care. In this series, we identify how such technologies are being used to improve quality and performance, the future directions for advancement, and the policy and research developments required to maximize public benefit from these technologies. Each of these articles focuses on a different type of information technology: (1) information systems to manage medical transactions; (2) physician-support technologies to improve medical practice; and (3) patient-focused technologies designed to change how people manage their own care. This first article of a 3-part series examines the successes of and opportunities for using advanced information systems that track and manage medical transactions for large populations to improve performance. Examples of such systems include: HEDIS, which gathers standardized data from health plans on quality of care; the USQA Health Services Research Program, which tracks treatment patterns and outcomes for 14 million insurance members; Ford's program to collect medical data for over 600,000 employees; and Harvard Pilgrim Health Care's system of computerized laboratory, pharmacy, ambulatory, and hospital admission records for its 1.5 million members. Data from these systems have led to modest improvements in knowledge and practice patterns for some diseases. Significant barriers are slowing efforts to add outcomes data to these databases and broaden the databases to cover larger populations. Nonetheless, existing data in currently evolving systems could be used to greater benefit in tracking public health and in identifying more effective treatments and causes of diseases.     

The metabolic syndrome - background and treatment

The metabolic syndrome (MBS) is characterised by a clustering of cardiovascular and metabolic risk factors. This syndrome is now widely recognised as a distinct pathological entity, and it is receiving a great deal of attention in the medical literature but also in the lay press.Globally speaking, persons with MBS have a clustering of the following risk factors:[List: see text]MBS is associated with important cardio/cerebrovascular and metabolic risks. Prevention and treatment are therefore of great importance. Preventive measures involving lifestyle are mandatory. In addition, MBS patients require pharmacological treatment, usually for the rest of their lives. Complex patterns of drug treatment will be required, since all the different, heterogenous pathophysiological problems will require appropriate treatment. After an introduction to MBS, this article provides an extensive and critical review of the drug treatment of this complex pathological entity.     

Effects of directional environmental change on extinction dynamics in experimental microbial communities are predicted by a simple model

Global temperatures are expected to rise between 1.1 and 6.4°C over the next 100 years, although the exact rate will depend on future greenhouse emissions, and will vary spatially. Temperature can alter an individual's metabolic rate, and consequently birth and death rates. In declining populations, these alterations may manifest as changes in the rate of that population's decline, and subsequently the timing of extinction events. Predicting such events could therefore be of considerable use. We use a small‐scale experimental system to investigate how the rate of temperature change can alter a population's time to extinction, and whether it is possible to predict this event using a simple phenomenological model that incorporates information about population dynamics at a constant temperature, published scaling of metabolic rates, and temperature. In addition, we examine 1) the relative importance of the direct effects of temperature on metabolic rate, and the indirect effects (via temperature driven changes in body size), on predictive accuracy (defined as the proximity of the predicted date of extinction to the mean observed date of extinction), 2) the combinations of model parameters that maximise accuracy of predictions, and 3) whether substituting temperature change through time with mean temperature produces accurate predictions. We find that extinction occurs earlier in environments that warm faster, and this can be accurately predicted (R² > 0.84). Increasing the number of parameters that were temperature‐dependent increased the model's accuracy, as did scaling these temperature‐dependent parameters with either the direct effects of temperature alone, or with the direct and indirect effects. Using mean temperature through time instead of actual temperature produces less accurate predictions of extinction. These results suggest that simple phenomenological models, incorporating metabolic theory, may be useful in understanding how environmental change can alter a population's rate of extinction. Synthesis Understanding how populations will respond to future climatic change is a key goal in ecology, however the exact rate of future warming will vary both spatially and temporally. Consequently, mathematical models must be used to understand the potential range of future population dynamics under various warming scenarios. We use a combination of experimentation and modelling to show that the effects of varying rates of environmental change on population dynamics can be predicted by a simple model. However, the accuracy of these predictions depends upon, amongst other things, a detailed knowledge of how temperature will change over time, rather than approximating this change to mean temperature.