Key Conceptual Advances Research Articles

DNA Barcoding in Species Delimitation: From Genetic Distances to Integrative Taxonomy.

Over the past two decades, DNA barcoding has become the most popular exploration approach in molecular taxonomy, whether for identification, discovery, delimitation, or description of species. The present contribution focuses on the utility of DNA barcoding for taxonomic research activities related to species delimitation, emphasizing the following aspects:(1) To what extent DNA barcoding can be a valuable ally for fundamental taxonomic research, (2) its methodological and theoretical limitations, (3) the conceptual background and practical use of pairwise distances between DNA barcode sequences in taxonomy, and (4) the different ways in which DNA barcoding can be combined with complementary means of investigation within a broader integrative framework. In this chapter, we recall and discuss the key conceptual advances that have led to the so-called renaissance of taxonomy, elaboratea detailed glossary for the terms specific to this discipline (see Glossary in Chap. 35 ), and propose a newly designed step-by-step species delimitation protocol starting from DNA barcode data that includes stepsfrom the preliminary elaboration of an optimal sampling strategy to the final decision-making process which potentially leads to nomenclatural changes.

Role of the duodenal microbiota in functional dyspepsia.

Functional dyspepsia (FD) is a common and debilitating gastrointestinal disorder attributed to altered gut-brain interactions. While the etiology of FD remains unknown, emerging research suggests the mechanisms are likely multifactorial and heterogenous among patient subgroups. Small bowel motor disturbances, visceral hypersensitivity, chronic microinflammation, and increased intestinal tract permeability have all been linked to the pathogenesis of FD. Recently, alterations to the gut microbiome have also been implicated to play an important role in the disease. Changes to the duodenal microbiota may either trigger or be a consequence of immune and neuronal disturbances observed in the disease, but the mechanisms of influence of small intestinal flora on gastrointestinal function and symptomatology are unknown. This review summarizes and synthesizes the literature on the link between the microbiota, low-grade inflammatory changes in the duodenum and FD. This review is not intended to provide a complete overview of FD or the small intestinal microbiota, but instead outline some of the key conceptual advances in understanding the interactions between altered gastrointestinal bacterial communities; dietary factors; host immune activation; and stimulation of the gut-brain axes in patients with FD versus controls. Current and emerging treatment approaches such as dietary interventions and antibiotic or probiotic use that have demonstrated symptom benefits for patients are reviewed, and their role in modulating the host-microbiota is discussed. Finally, suggested opportunities for diagnostic and therapeutic improvements for patients with this condition are presented.

Mass movements

AbstractIn this chapter, we consider key advances in the understanding of mass movements betweenc.1965 andc.2000. This period saw a burgeoning need for a greater level of understanding of mass-movement processes in response to a series of high-impact mass-movement events, and because of the need to develop infrastructure safely. A series of step changes were enabled through hillslope geomorphology (broadly defined) being open to overarching and consolidating concepts, methods and models from cognate disciplines, whilst seizing opportunities to gain insight from rapidly advancing methods increasingly focused at a scale of investigation relevant to landsliding. Byc.2000, geomorphologists had made significant contributions to our understanding of mass-movement processes and ultimately led many key conceptual advances, notably relating to: bridging across scales of hillslope investigation; linking and developing understanding of process, form and mechanisms of slope stability; and articulating the temporal characteristics of slope stability and mass movement.

The behavioural ecology of marine cleaning mutualisms.

Cleaning interactions, in which a small 'cleaner' organism removes and often consumes material from a larger 'client', are some of the most enigmatic and intriguing of interspecies interactions. Early research on cleaning interactions canonized the view that they are mutualistic, with clients benefiting from parasite removal and cleaners benefiting from a meal, but subsequent decades of research have revealed that the dynamics of these interactions can be highly complex. Despite decades of research on marine cleaning interactions (the best studied cleaning systems), key questions remain, including how the outcome of an individual cleaning interaction depends on ecological, behavioural, and social context, how such interactions arise, and how they remain stable over time. Recently, studies of marine parasites, long-term data from coral reef communities with and without cleaners, increased behavioural observations recorded using remote video, and a focus on a larger numbers of cleaning species have helped bring about key conceptual advances in our understanding of cleaning interactions. In particular, evidence now suggests that the ecological, behavioural, and social contexts of a given cleaning interaction can result in the outcome ranging from mutualistic to parasitic, and that cleaning interactions are mediated by signals that can also vary with context. Signals are an important means by which animals extract information about one another, and thus represent a mechanism by which interspecific partners can determine when, how, and with whom to interact. Here, I review our understanding of the behavioural ecology of marine cleaning interactions. In particular, I argue that signals provide a useful framework for advancing our understanding of several important outstanding questions. I discuss the costs and benefits of cleaning interactions, review how cleaners and clients recognize and assess one another using signals, and discuss how signal reliability, or 'honesty', may be maintained in cleaning systems. Lastly, I discuss the sensory ecology of both cleaners and clients to highlight what marine cleaning systems can tell us about signalling behaviour, signal form, and signal evolution in a system where signals are aimed at multiple receiver species. Overall, I argue that future research on cleaning interactions has much to gain by continuing to shift the research focus toward examining the variable outcomes of cleaning interactions in relation to the broader behavioural, social, and ecological contexts.

Improving Machine Vision Using Human Perceptual Representations: The Case of Planar Reflection Symmetry for Object Classification.

Achieving human-like visual abilities is a holy grail for machine vision, yet precisely how insights from human vision can improve machines has remained unclear. Here, we demonstrate two key conceptual advances: First, we show that most machine vision models are systematically different from human object perception. To do so, we collected a large dataset of perceptual distances between isolated objects in humans and asked whether these perceptual data can be predicted by many common machine vision algorithms. We found that while the best algorithms explain ∼70% of the variance in the perceptual data, all the algorithms we tested make systematic errors on several types of objects. In particular, machine algorithms underestimated distances between symmetric objects compared to human perception. Second, we show that fixing these systematic biases can lead to substantial gains in classification performance. In particular, augmenting a state-of-the-art convolutional neural network with planar/reflection symmetry scores along multiple axes produced significant improvements in classification accuracy (1-10%) across categories. These results show that machine vision can be improved by discovering and fixing systematic differences from human vision.

Informing disease modelling with brain-relevant functional genomic annotations.

The past decade has seen a surge in the number of disease/trait-associated variants, largely because of the union of studies to share genetic data and the availability of electronic health records from large cohorts for research use. Variant discovery for neurological and neuropsychiatric genome-wide association studies, including schizophrenia, Parkinson's disease and Alzheimer's disease, has greatly benefitted; however, the translation of these genetic association results to interpretable biological mechanisms and models is lagging. Interpreting disease-associated variants requires knowledge of gene regulatory mechanisms and computational tools that permit integration of this knowledge with genome-wide association study results. Here, we summarize key conceptual advances in the generation of brain-relevant functional genomic annotations and amongst tools that allow integration of these annotations with association summary statistics, which together provide a new and exciting opportunity to identify disease-relevant genes, pathways and cell types in silico. We discuss the opportunities and challenges associated with these developments and conclude with our perspective on future advances in annotation generation, tool development and the union of the two.

Setting health research priorities using the CHNRI method: VII. A review of the first 50 applications of the CHNRI method.

BackgroundSeveral recent reviews of the methods used to set research priorities have identified the CHNRI method (acronym derived from the “Child Health and Nutrition Research Initiative”) as an approach that clearly became popular and widely used over the past decade. In this paper we review the first 50 examples of application of the CHNRI method, published between 2007 and 2016, and summarize the most important messages that emerged from those experiences.MethodsWe conducted a literature review to identify the first 50 examples of application of the CHNRI method in chronological order. We searched Google Scholar, PubMed and so–called grey literature.ResultsInitially, between 2007 and 2011, the CHNRI method was mainly used for setting research priorities to address global child health issues, although the first cases of application outside this field (eg, mental health, disabilities and zoonoses) were also recorded. Since 2012 the CHNRI method was used more widely, expanding into the topics such as adolescent health, dementia, national health policy and education. The majority of the exercises were focused on issues that were only relevant to low– and middle–income countries, and national–level applications are on the rise. The first CHNRI–based articles adhered to the five recommended priority–setting criteria, but by 2016 more than two–thirds of all conducted exercises departed from recommendations, modifying the CHNRI method to suit each particular exercise. This was done not only by changing the number of criteria used, but also by introducing some entirely new criteria (eg, “low cost”, “sustainability”, “acceptability”, “feasibility”, “relevance” and others).ConclusionsThe popularity of the CHNRI method in setting health research priorities can be attributed to several key conceptual advances that have addressed common concerns. The method is systematic in nature, offering an acceptable framework for handling many research questions. It is also transparent and replicable, because it clearly defines the context and priority–setting criteria. It is democratic, as it relies on “crowd–sourcing”. It is inclusive, fostering “ownership” of the results by ensuring that various groups invest in the process. It is very flexible and adjustable to many different contexts and needs. Finally, it is simple and relatively inexpensive to conduct, which we believe is one of the main reasons for its uptake by many groups globally, particularly those in low– and middle–income countries.

Semi-intact ex vivo approach to investigate spinal somatosensory circuits.

The somatosensory input that gives rise to the perceptions of pain, itch, cold and heat are initially integrated in the superficial dorsal horn of the spinal cord. Here, we describe a new approach to investigate these neural circuits in mouse. This semi-intact somatosensory preparation enables recording from spinal output neurons, while precisely controlling somatosensory input, and simultaneously manipulating specific populations of spinal interneurons. Our findings suggest that spinal interneurons show distinct temporal and spatial tuning properties. We also show that modality selectivity - mechanical, heat and cold - can be assessed in both retrogradely labeled spinoparabrachial projection neurons and genetically labeled spinal interneurons. Finally, we demonstrate that interneuron connectivity can be determined via optogenetic activation of specific interneuron subtypes. This new approach may facilitate key conceptual advances in our understanding of the spinal somatosensory circuits in health and disease.

Setting health research priorities using the CHNRI method: IV. Key conceptual advances

IntroductionChild Health and Nutrition Research Initiative (CHNRI) started as an initiative of the Global Forum for Health Research in Geneva, Switzerland. Its aim was to develop a method that could assist priority setting in health research investments. The first version of the CHNRI method was published in 2007–2008. The aim of this paper was to summarize the history of the development of the CHNRI method and its key conceptual advances.MethodsThe guiding principle of the CHNRI method is to expose the potential of many competing health research ideas to reduce disease burden and inequities that exist in the population in a feasible and cost–effective way.ResultsThe CHNRI method introduced three key conceptual advances that led to its increased popularity in comparison to other priority–setting methods and processes. First, it proposed a systematic approach to listing a large number of possible research ideas, using the “4D” framework (description, delivery, development and discovery research) and a well–defined “depth” of proposed research ideas (research instruments, avenues, options and questions). Second, it proposed a systematic approach for discriminating between many proposed research ideas based on a well–defined context and criteria. The five “standard” components of the context are the population of interest, the disease burden of interest, geographic limits, time scale and the preferred style of investing with respect to risk. The five “standard” criteria proposed for prioritization between research ideas are answerability, effectiveness, deliverability, maximum potential for disease burden reduction and the effect on equity. However, both the context and the criteria can be flexibly changed to meet the specific needs of each priority–setting exercise. Third, it facilitated consensus development through measuring collective optimism on each component of each research idea among a larger group of experts using a simple scoring system. This enabled the use of the knowledge of many experts in the field, “visualising” their collective opinion and presenting the list of many research ideas with their ranks, based on an intuitive score that ranges between 0 and 100.ConclusionsTwo recent reviews showed that the CHNRI method, an approach essentially based on “crowdsourcing”, has become the dominant approach to setting health research priorities in the global biomedical literature over the past decade. With more than 50 published examples of implementation to date, it is now widely used in many international organisations for collective decision–making on health research priorities. The applications have been helpful in promoting better balance between investments in fundamental research, translation research and implementation research.

Setting health research priorities using the CHNRI method: IV. Key conceptual advances.

Child Health and Nutrition Research Initiative (CHNRI) started as an initiative of the Global Forum for Health Research in Geneva, Switzerland. Its aim was to develop a method that could assist priority setting in health research investments. The first version of the CHNRI method was published in 2007-2008. The aim of this paper was to summarize the history of the development of the CHNRI method and its key conceptual advances. The guiding principle of the CHNRI method is to expose the potential of many competing health research ideas to reduce disease burden and inequities that exist in the population in a feasible and cost-effective way. The CHNRI method introduced three key conceptual advances that led to its increased popularity in comparison to other priority-setting methods and processes. First, it proposed a systematic approach to listing a large number of possible research ideas, using the "4D" framework (description, delivery, development and discovery research) and a well-defined "depth" of proposed research ideas (research instruments, avenues, options and questions). Second, it proposed a systematic approach for discriminating between many proposed research ideas based on a well-defined context and criteria. The five "standard" components of the context are the population of interest, the disease burden of interest, geographic limits, time scale and the preferred style of investing with respect to risk. The five "standard" criteria proposed for prioritization between research ideas are answerability, effectiveness, deliverability, maximum potential for disease burden reduction and the effect on equity. However, both the context and the criteria can be flexibly changed to meet the specific needs of each priority-setting exercise. Third, it facilitated consensus development through measuring collective optimism on each component of each research idea among a larger group of experts using a simple scoring system. This enabled the use of the knowledge of many experts in the field, "visualising" their collective opinion and presenting the list of many research ideas with their ranks, based on an intuitive score that ranges between 0 and 100. Two recent reviews showed that the CHNRI method, an approach essentially based on "crowdsourcing", has become the dominant approach to setting health research priorities in the global biomedical literature over the past decade. With more than 50 published examples of implementation to date, it is now widely used in many international organisations for collective decision-making on health research priorities. The applications have been helpful in promoting better balance between investments in fundamental research, translation research and implementation research.

Meta-analysis and research on host–parasite interactions: past and future

Host–parasite interactions are characterised by a lack of stable species-specific traits that limits generalisations one can make even about particular host or parasite species. For instance, the virulence, life history traits or transmission mode of a given parasite species can depend on which of its suitable hosts it infects. In the search for general rules or patterns, meta-analysis provides a possible solution to the challenges posed by the highly variable outcomes of host–parasite interactions. It allows an estimate of the overall association between any factor and its biological response that transcends the particulars of given host and parasite taxonomic combinations. In this review, we begin with a historical overview of the use of meta-analysis in research on the ecology and evolution of host–parasite interactions. We then identify several key conceptual advances that were made possible only through meta-analytical synthesis. For example, meta-analysis revealed the predominant association between rates of host and parasite gene flow and local adaptation, as well as an unexpected latitudinal gradient in parasite virulence, or parasite-induced host mortality. Finally, we propose some areas of research on host–parasite interactions that are based on a mature theoretical foundation and for which there now exist sufficient primary results to make them ripe for meta-analysis. The search for the processes causing variability in parasite species richness among host species, and the link between the expression of host resistance and the specificity of parasites, are two such research areas. The main objective of this review is to promote meta-analysis as a synthetic tool overriding the idiosyncrasies of specific host–parasite combinations and capable of uncovering the universal trends, if any, in the evolutionary ecology of parasitism.

Connecting synthetic chemistry decisions to cell and genome biology using small-molecule phenotypic profiling

Discovering small-molecule modulators for thousands of gene products requires multiple stages of biological testing, specificity evaluation, and chemical optimization. Many cellular profiling methods, including cellular sensitivity, gene expression, and cellular imaging, have emerged as methods to assess the functional consequences of biological perturbations. Cellular profiling methods applied to small-molecule science provide opportunities to use complex phenotypic information to prioritize and optimize small-molecule structures simultaneously against multiple biological endpoints. As throughput increases and cost decreases for such technologies, we see an emerging paradigm of using more information earlier in probe-discovery and drug-discovery efforts. Moreover, increasing access to public datasets makes possible the construction of 'virtual' profiles of small-molecule performance, even when multiplexed measurements were not performed or when multidimensional profiling was not the original intent. We review some key conceptual advances in small-molecule phenotypic profiling, emphasizing connections to other information, such as protein-binding measurements, genetic perturbations, and cell states. We argue that to maximally leverage these measurements in probe-discovery and drug-discovery requires a fundamental connection to synthetic chemistry, allowing the consequences of synthetic decisions to be described in terms of changes in small-molecule profiles. Mining such data in the context of chemical structure and synthesis strategies can inform decisions about chemistry procurement and library development, leading to optimal small-molecule screening collections.

Treatment of chemotherapy-induced emesis in the 1990s: impact of the 5-HT3 receptor antagonists

Considerable progress has been made in the development of means to limit nausea and vomiting arising from cancer chemotherapy. A number of key conceptual advances in the last decade have been critically important. these include recognition of the value of combination antiemetic therapy, identification of important patient- and treatment-related factors predictive of emesis, and appreciation of the importance of serotonin (5-HT) in the pathophysiology of emesis and the value of selective antagonists of the type-3 serotonin receptor. Comparative trials of the 5-HT3 receptor antagonists and classic antiemetic agents have helped define optimal antiemetic approaches in a number of settings. A combination of a 5-HT3 antagonist and dexamethasone is the treatment of choice for patients receiving single- and multiple-day cisplatin. The 5-HT3 antagonists are also effective agents with noncisplatin chemotherapy. Clear-cut superiority to classic antiemetics such as dexamethasone has not been consistently demonstrated, however. Results with the 5-HT3 antagonists in cisplatin-induced delayed emesis have been disappointing to date. The results of ongoing prospective trials should define their role more clearly. At present a combination of metoclopramide and dexamethasone is the treatment of choice in this setting. Results of trials comparing 5-HT3 antagonists are beginning to emerge. Available information suggests no clinically relevant differences in antiemetic efficacy between these agents. Many questions regarding the optimal use of the 5-HT3 antagonists and their integration into clinical practice remain unanswered and are the appropriate focus for additional study.

Young Children's Understanding of Other People's Feelings and Beliefs: Individual Differences and Their Antecedents

Individual differences in young children's understanding of others' feelings and in their ability to explain human action in terms of beliefs, and the earlier correlates of these differences, were studied with 50 children observed at home with mother and sibling at 33 months, then tested at 40 months on affective-labeling, perspective-taking, and false-belief tasks. Individual differences in social understanding were marked; a third of the children offered explanations of actions in terms of false belief, though few predicted actions on the basis of beliefs. These differences were associated with participation in family discourse about feelings and causality 7 months earlier, verbal fluency of mother and child, and cooperative interaction with the sibling. Differences in understanding feelings were also associated with the discourse measures, the quality of mother-sibling interaction, SES, and gender, with girls more successful than boys. The results support the view that discourse about the social world may in part mediate the key conceptual advances reflected in the social cognition tasks; interaction between child and sibling and the relationships between other family members are also implicated in the growth of social understanding.