Development of a Comprehensive Food Data Citation Standard: A Surprising Gap in the Nutrition Research Literature.

Currently, there is no standard for the citation of food composition data. This leads to the questions: how are food and nutrient data cited in research papers, and are they presented in a way that allows studies to be reproduced? To answer these questions, we performed a review of the literature and quantified the accuracy and completeness of data citations from publications (January to December 2020) in the top 5 nutrition journals as ranked by the Scimago Journal Rankings. We then performed a review of citation guidelines currently in place in other disciplines. Similar to the requirement of completing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist for systematic reviews, we have developed a comprehensive data citation checklist, the Comprehensive Food Data Citation (CFDC) checklist. The CFDC checklist was developed through a benchmarking assessment against established data citation standards. Its purpose is to establish a standardized, best-practice approach for reporting food composition data. The CFDC checklist has been designed to cater to both publishers and authors, ensuring consistency and accuracy in food composition data reporting. The CFDC checklist is also available as an interactive citation generator to facilitate the adoption of consistent and comprehensive citation of food composition data and is available at https://www.nutrientinstitute.org/cfdc. Despite general agreement that accurate data citation is paramount, this is the first citation standard specifically developed to capture food composition data. Because food composition data are the foundation of nutrition research, our proposed guidelines aim to provide the field with a much-needed foundation for acknowledging and sharing data in a way that fosters reproducibility.

Visualizing Data Interoperability for Food Systems Sustainability Research-From Spider Webs to Neural Networks.

Food systems represent all elements and activities needed to feed the growing global population. Research on sustainable food systems is transdisciplinary, relying on the interconnected domains of health, nutrition, economics, society, and environment. The current lack of interoperability across databases poses a challenge to advancing research on food systems transformation. Crosswalks among largely siloed data on climate change, soils, agricultural practices, nutrient composition of foods, food processing, prices, dietary intakes, and population health are not fully developed. Starting with US Department of Agriculture FoodData Central, we assessed the interoperability of databases from multiple disciplines by identifying existing crosswalks and corresponding visualizations. Our visual demonstration serves as proof of concept, identifying databases in need of expansion, integration, and harmonization for use by researchers, policymakers, and the private sector. Interoperability is the key: ontologies and well-defined crosswalks are necessary to connect siloed data, transcend organizational barriers, and draw pathways from agriculture to nutrition and health.

Perspective: Developing a Nutrient-Based Framework for Protein Quality.

The future of precision nutrition requires treating amino acids as essential nutrients. Currently, recognition of essential amino acid requirements is embedded within a generalized measure of protein quality known as the PDCAAS (Protein Digestibility-Corrected Amino Acid Score). Calculating the PDCAAS includes the FAO/WHO/UNU amino acid score, which is based on the limiting amino acid in a food, that is, the single amino acid with the lowest concentration compared to the reference standard. That "limiting" amino acid score is then multiplied by a bioavailability factor to obtain the PDCAAS, which ranks proteins from 0.0 (poor quality) to 1.0 (high quality). However, the PDCAAS has multiple limitations: it only allows for direct protein quality comparison between 2 proteins, and it is not scalable, transparent, or additive. We therefore propose that shifting the protein quality evaluation paradigm from the current generalized perspective to a precision nutrition focus treating amino acids as unique, metabolically active nutrients will be valuable for multiple areas of science and public health. We report the development and validation of the Essential Amino Acid 9 (EAA-9) score, an innovative, nutrient-based protein quality scoring framework. EAA-9 scores can be used to ensure that dietary recommendations for each essential amino acid are met. The EAA-9 scoring framework also offers the advantages of being additive and, perhaps most importantly, allows for personalization of essential amino acid needs based on age or metabolic conditions. Comparisons of the EAA-9 score with PDCAAS demonstrated the validity of the EAA-9 framework, and practical applications demonstrated that the EAA-9 framework is a powerful tool for precision nutrition applications.

Perspective: A Comprehensive Evaluation of Data Quality in Nutrient Databases.

Nutrient databases are a critical component of nutrition science and the basis of exciting new research in precision nutrition (PN). To identify the most critical components needed for improvement of nutrient databases, food composition data were analyzed for quality, with completeness being the most important measure, and for FAIRness, how well the data conformed with the data science criteria of findable, accessible, interoperable, and reusable (FAIR). Databases were judged complete if they provided data for all 15 nutrition fact panel (NFP) nutrient measures and all 40 National Academies of Sciences, Engineering, and Medicine (NASEM) essential nutrient measures for each food listed. Using the gold standard the USDA standard reference (SR) Legacy database as surrogate, it was found that SR Legacy data were not complete for either NFP or NASEM nutrient measures. In addition, phytonutrient measures in the 4 USDA Special Interest Databases were incomplete. To evaluate data FAIRness, a set of 175 food and nutrient data sources were collected from worldwide. Many opportunities were identified for improving data FAIRness, including creating persistent URLs, prioritizing usable data storage formats, providing Globally Unique Identifiers for all foods and nutrients, and implementing citation standards. This review demonstrates that despite important contributions from the USDA and others, food and nutrient databases in their current forms do not yet provide truly comprehensive food composition data. We propose that to enhance the quality and usage of food and nutrient composition data for research scientists and those fashioning various PN tools, the field of nutrition science must step out of its historical comfort zone and improve the foundational nutrient databases used in research by incorporating data science principles, the most central being data quality and data FAIRness.

Using participatory research to identify actionable facilitators and barriers to effective inpatient interdisciplinary communication.

BACKGROUND: Communication failures occur often in the inpatient setting. Efforts to understand and improve communication often exclude patients or are siloed by discipline. OBJECTIVE: We aimed to identify barriers and facilitators to effective communication within interdisciplinary inpatient internal medicine (IM) teams using a participatory research approach. DESIGN: We conducted a single-center participatory mixed methods study using group-level assessment (GLA) and concept mapping to iteratively engage stakeholders. Stakeholder groups included patients/families, IM faculty, IM residents, nurses and ancillary staff, and care managers. Stakeholder-specific GLA sessions were conducted. Participants responded to prompts addressing interdisciplinary communication then worked in small groups to synthesize the qualitative data into unique ideas. A subset of each stakeholder group then sorted ideas through a concept mapping exercise. Multidimensional scaling and hierarchical cluster analysis were used to generate a concept map of the data. RESULTS: Participants generated 97 unique ideas that were then sorted. The research team chose an eight-cluster concept map representing patient inclusion and engagement, processes and resources, team morale and inclusive dynamics, attitudes and behaviors, effective communication, barriers to communication, the culture of healthcare, and clear expectations. Three larger domains of patient inclusion and engagement, organizational conditions and role clarity, and team dynamics and behaviors were noted. CONCLUSION: Use of a participatory research approach made it feasible to engage diverse stakeholders including patients. Our results highlight the need to identify context-specific facilitators and barriers of interdisciplinary communication. The importance of clear expectations was identified as a prioritized area to target communication improvement efforts.

Comparing whole-genome shotgun sequencing and DNA metabarcoding approaches for species identification and quantification of pollen species mixtures.

Molecular identification of mixed-species pollen samples has a range of applications in various fields of research. To date, such molecular identification has primarily been carried out via amplicon sequencing, but whole-genome shotgun (WGS) sequencing of pollen DNA has potential advantages, including (1) more genetic information per sample and (2) the potential for better quantitative matching. In this study, we tested the performance of WGS sequencing methodology and publicly available reference sequences in identifying species and quantifying their relative abundance in pollen mock communities. Using mock communities previously analyzed with DNA metabarcoding, we sequenced approximately 200Mbp for each sample using Illumina HiSeq and MiSeq. Taxonomic identifications were based on the Kraken k-mer identification method with reference libraries constructed from full-genome and short read archive data from the NCBI database. We found WGS to be a reliable method for taxonomic identification of pollen with near 100% identification of species in mixtures but generating higher rates of false positives (reads not identified to the correct taxon at the required taxonomic level) relative to rbcL and ITS2 amplicon sequencing. For quantification of relative species abundance, WGS data provided a stronger correlation between pollen grain proportion and sequence read proportion, but diverged more from a 1:1 relationship, likely due to the higher rate of false positives. Currently, a limitation of WGS-based pollen identification is the lack of representation of plant diversity in publicly available genome databases. As databases improve and costs drop, we expect that eventually genomics methods will become the methods of choice for species identification and quantification of mixed-species pollen samples.

The context dependency of pollinator interference: How environmental conditions and co-foraging species impact floral visitation.

Animals often change their behaviour in the presence of other species and the environmental context they experience, and these changes can substantially modify the course their populations follow. In the case of animals involved in mutualistic interactions, it is still unclear how to incorporate the effects of these behavioural changes into population dynamics. We propose a framework for using pollinator functional responses to examine the roles of pollinator-pollinator interactions and abiotic conditions in altering the times between floral visits of a focal pollinator. We then apply this framework to a unique foraging experiment with different models that allow resource availability and sublethal exposure to a neonicotinoid pesticide to modify how pollinators forage alone and with co-foragers. We found that all co-foragers interfere with the focal pollinator under at least one set of abiotic conditions; for most species, interference was strongest at higher levels of resource availability and with pesticide exposure. Overall our results highlight that density-dependent responses are often context-dependent themselves.

Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures.

Pollen DNA metabarcoding-marker-based genetic identification of potentially mixed-species pollen samples-has applications across a variety of fields. While basic species-level pollen identification using standard DNA barcode markers is established, the extent to which metabarcoding (a) correctly assigns species identities to mixes (qualitative matching) and (b) generates sequence reads proportionally to their relative abundance in a sample (quantitative matching) is unclear, as these have not been assessed relative to known standards. We tested the quantitative and qualitative robustness of metabarcoding in constructed pollen mixtures varying in species richness (1-9 species), taxonomic relatedness (within genera to across class) and rarity (5%-100% of grains), using Illumina MiSeq with the markers rbcL and ITS2. Qualitatively, species composition determinations were largely correct, but false positives and negatives occurred. False negatives were typically driven by lack of a barcode gap or rarity in a sample. Species richness and taxonomic relatedness, however, did not strongly impact correct determinations. False positives were likely driven by contamination, chimeric sequences and/or misidentification by the bioinformatics pipeline. Quantitatively, the proportion of reads for each species was only weakly correlated with its relative abundance, in contrast to suggestions from some other studies. Quantitative mismatches are not correctable by consistent scaling factors, but instead are context-dependent on the other species present in a sample. Together, our results show that metabarcoding is largely robust for determining pollen presence/absence but that sequence reads should not be used to infer relative abundance of pollen grains.

Applying pollen DNA metabarcoding to the study of plant-pollinator interactions.

PREMISE OF THE STUDY: To study pollination networks in a changing environment, we need accurate, high-throughput methods. Previous studies have shown that more highly resolved networks can be constructed by studying pollen loads taken from bees, relative to field observations. DNA metabarcoding potentially allows for faster and finer-scale taxonomic resolution of pollen compared to traditional approaches (e.g., light microscopy), but has not been applied to pollination networks. METHODS: We sampled pollen from 38 bee species collected in Florida from sites differing in forest management. We isolated DNA from pollen mixtures and sequenced rbcL and ITS2 gene regions from all mixtures in a single run on the Illumina MiSeq platform. We identified species from sequence data using comprehensive rbcL and ITS2 databases. RESULTS: We successfully built a proof-of-concept quantitative pollination network using pollen metabarcoding. DISCUSSION: Our work underscores that pollen metabarcoding is not quantitative but that quantitative networks can be constructed based on the number of interacting individuals. Due to the frequency of contamination and false positive reads, isolation and PCR negative controls should be used in every reaction. DNA metabarcoding has advantages in efficiency and resolution over microscopic identification of pollen, and we expect that it will have broad utility for future studies of plant-pollinator interactions.

Heterospecific pollen deposition in Delphinium barbeyi: linking stigmatic pollen loads to reproductive output in the field.

BACKGROUND AND AIMS: Most pollinators are generalists and therefore are likely to transfer heterospecific pollen among co-flowering plants. Most work on the impacts of heterospecific pollen deposition on plant fecundity has utilized hand-pollination experiments in greenhouse settings, and we continue to know very little about the reproductive effects of heterospecific pollen in field settings. METHODS: We explored how patterns of naturally deposited heterospecific pollen relate to the reproductive output of Delphinium barbeyi, a common subalpine perennial herb in the Rocky Mountains (USA). We assessed a wide range of naturally occurring heterospecific pollen proportions and pollen load sizes, and linked stigmatic pollen deposition directly to seed set in individual carpels in the field. KEY RESULTS: We found that heterospecific pollen deposition in D. barbeyi is common, but typically found at low levels across stigmas collected in our sites. Neither conspecific nor heterospecific pollen deposition was related to carpel abortion. By contrast, we saw a significant positive relationship between conspecific pollen amount and viable seed production, as well as a significant negative interaction between the effects of conspecific pollen and heterospecific pollen amount, whereby the effect of conspecific pollen on viable seed production became weaker with greater heterospecific deposition on stigmas. CONCLUSIONS: To our knowledge, this is the first demonstration of a relationship between heterospecific pollen and seed production in a field setting. In addition, it is the first report of an interaction between conspecific and heterospecific pollen quantities on seed production. These findings, taken with the results from other studies, suggest that greenhouse hand-pollination studies and field studies should be more tightly integrated in future work to better understand how heterospecific pollen transfer can be detrimental for plant reproduction.

Conservation biological control and pest performance in lawn turf: does mowing height matter?

With >80 million United States households engaged in lawn and gardening activities, increasing sustainability of lawn care is important. Mowing height is an easily manipulated aspect of lawn management. We tested the hypothesis that elevated mowing of tall fescue lawn grass promotes a larger, more diverse community of arthropod natural enemies which in turn provides stronger biological control services, and the corollary hypothesis that doing so also renders the turf itself less suitable for growth of insect pests. Turf-type tall fescue was mowed low (6.4 cm) or high (10.2 cm) for two growing seasons, natural enemy populations were assessed by vacuum sampling, pitfall traps, and ant baits, and predation and parasitism were evaluated with sentinel prey caterpillars, grubs, and eggs. In addition, foliage-feeding caterpillars and root-feeding scarab grubs were confined in the turf to evaluate their performance. Although some predatory groups (e.g., rove beetles and spiders) were more abundant in high-mowed grass, predation rates were uniformly high because ants, the dominant predators, were similarly abundant regardless of mowing height. Lower canopy temperatures in high-mowed grass were associated with slower growth of grass-feeding caterpillars. Higher lawn mowing reduces fuel consumption and yard waste, and promotes a deep, robust root system that reduces need for water and chemical inputs. Although in this study elevated mowing height did not measurably increase the already-high levels of predation, it did suggest additional ways through which bottom-up effects on insect pest growth might interact with natural enemies to facilitate conservation biological control.

Ameliorative effects of sodium chloride on acute copper toxicity among Cope's gray tree frog (Hyla chrysoscelis) and green frog (Rana clamitans) embryos.

Urban stormwater runoff is composed of a mixture of components, including polycyclic aromatic hydrocarbons, metals, deicing agents, and many others. The fate of these chemicals is often in stormwater detention ponds that are used by amphibians for breeding. Among aquatic organisms, the toxic mechanism for many metals involves interference with active Na(+) and Cl(-) uptake. Addition of cations has been shown to reduce the toxicity of metals among some aquatic organisms through competitive inhibition, but no studies have investigated the interaction between NaCl and Cu among amphibian embryos and larvae. To determine the degree to which NaCl may ameliorate the toxicity of Cu to amphibian embryos and larvae, the authors exposed Hyla chrysoscelis (Cope's gray treefrogs) and Rana (Lithobates) clamitans (green frogs) to seven levels of Cu and NaCl in fully factorial experiments. When exposure was in artificial hard water, Cu was highly toxic to both species (96-h median lethal concentration [LC50] of 44.7 µg/L and 162.6 µg/L for H. chrysoscelis and R. clamitans, respectively). However, approximately 500 mg/L of NaCl eliminated Cu toxicity over the range of Cu concentrations used in the experiments (maximum 150 µg Cu/L for H. chrysoscelis and 325 µg Cu/L for R. clamitans). The current results suggest that NaCl is likely responsible for the toxic effects of NaCl and metal mixtures that might be typical of runoff from road surfaces in northern latitudes.