Harnessing Knowledge for Improving Access to Fruits and Vegetables at Farmers Markets: Interactive Data Visualization to Inform Food Security Programs and Policy.

High consumption of fruits and vegetables leads to decreased risk of various chronic diseases, including obesity and cardiovascular disease. Community-level barriers to access fruits and vegetables include the high cost, limited availability, and transportation. Farmers markets are a priority strategy for improving community access to fresh fruits and vegetables. The U.S. Department of Agriculture (USDA) National Farmers Market Directory is a voluntary self-reported data source on farmers markets. The objective of this investigation of the USDA farmers markets data directory was to determine how farmers markets in the United States are grouped according to (1) availability of fruits and vegetables and (2) the payment accepted. We designed and implemented interactive data visualizations in visual analytics software to understand access to fruits and vegetables at farmers markets from 8,497 entries in the USDA Farmers Market Directory. Among the 665 new or updated entries in year 2018, a subset of 641 (96%) farmers markets with availability of fresh fruits and vegetables had 16 subgroups. Additionally, a subgroup of 102 (16%) farmer markets accepted all four federal nutrition assistance benefits (SFMNP, SNAP, WIC CVVs, and WIC FMNP). The interactive data visualizations including geographic maps connected to social media resources can be useful in advocacy efforts and can inform policy improvements designed to improve physical, social, and economic access to fruits and vegetables at farmers markets.

Bioinformatics Investigations of Universal Stress Proteins from Mercury-Methylating Desulfovibrionaceae.

The presence of methylmercury in aquatic environments and marine food sources is of global concern. The chemical reaction for the addition of a methyl group to inorganic mercury occurs in diverse bacterial taxonomic groups including the Gram-negative, sulfate-reducing Desulfovibrionaceae family that inhabit extreme aquatic environments. The availability of whole-genome sequence datasets for members of the Desulfovibrionaceae presents opportunities to understand the microbial mechanisms that contribute to methylmercury production in extreme aquatic environments. We have applied bioinformatics resources and developed visual analytics resources to categorize a collection of 719 putative universal stress protein (USP) sequences predicted from 93 genomes of Desulfovibrionaceae. We have focused our bioinformatics investigations on protein sequence analytics by developing interactive visualizations to categorize Desulfovibrionaceae universal stress proteins by protein domain composition and functionally important amino acids. We identified 651 Desulfovibrionaceae universal stress protein sequences, of which 488 sequences had only one USP domain and 163 had two USP domains. The 488 single USP domain sequences were further categorized into 340 sequences with ATP-binding motif and 148 sequences without ATP-binding motif. The 163 double USP domain sequences were categorized into (1) both USP domains with ATP-binding motif (3 sequences); (2) both USP domains without ATP-binding motif (138 sequences); and (3) one USP domain with ATP-binding motif (21 sequences). We developed visual analytics resources to facilitate the investigation of these categories of datasets in the presence or absence of the mercury-methylating gene pair (hgcAB). Future research could utilize these functional categories to investigate the participation of universal stress proteins in the bacterial cellular uptake of inorganic mercury and methylmercury production, especially in anaerobic aquatic environments.

Knowledge Visualizations to Inform Decision Making for Improving Food Accessibility and Reducing Obesity Rates in the United States.

The aim of this article is to promote the use of knowledge visualization frameworks in the creation and transfer of complex public health knowledge. The accessibility to healthy food items is an example of complex public health knowledge. The United States Department of Agriculture Food Access Research Atlas (FARA) dataset contains 147 variables for 72,864 census tracts and includes 16 food accessibility variables with binary values (0 or 1). Using four-digit and 16-digit binary patterns, we have developed data analytical procedures to group the 72,684 U.S. census tracts into eight and forty groups respectively. This value-added FARA dataset facilitated the design and production of interactive knowledge visualizations that have a collective purpose of knowledge transfer and specific functions including new insights on food accessibility and obesity rates in the United States. The knowledge visualizations of the binary patterns could serve as an integrated explanation and prediction system to help answer why and what-if questions on food accessibility, nutritional inequality and nutrition therapy for diabetic care at varying geographic units. In conclusion, the approach of knowledge visualizations could inform coordinated multi-level decision making for improving food accessibility and reducing chronic diseases in locations defined by patterns of food access measures.

Integrating Datasets on Public Health and Clinical Aspects of Sickle Cell Disease for Effective Community-Based Research and Practice.

Sickle cell disease (SCD) is a genetic disease that has multiple aspects including public health and clinical aspects. The goals of the research study were to (1) understand the public health aspects of sickle cell disease, and (2) understand the overlap between public health aspects and clinical aspects that can inform research and practice beneficial to stakeholders in sickle cell disease management. The approach involved the construction of datasets from textual data sources produced by experts on sickle cell disease including from landmark publications published in 2020 on sickle cell disease in the United States. The interactive analytics of the integrated datasets that we produced identified that community-based approaches are common to both public health and clinical aspects of sickle cell disease. An interactive visualization that we produced can aid the understanding of the alignment of governmental organizations to recommendations for addressing sickle cell disease in the United States. From a global perspective, the interactive analytics of the integrated datasets can support the knowledge transfer stage of the SICKLE recommendations (Skills transfer, Increasing self-efficacy, Coordination, Knowledge transfer, Linking to adult services, and Evaluating readiness) for effective pediatric to adult transition care for patients with sickle cell disease. Considering the increased digital transformations resulting from the COVID-19 pandemic, the constructed datasets from expert recommendations can be integrated within remote digital platforms that expand access to care for individuals living with sickle cell disease. Finally, the interactive analytics of integrated expert recommendations on sickle cell disease management can support individual and team expertise for effective community-based research and practice.

Genomic Evidence for Bacterial Determinants Influencing Obesity Development.

Obesity is a major global public health problem requiring multifaceted interventional approaches including dietary interventions with probiotic bacteria. High-throughput genome sequencing of microbial communities in the mammalian gastrointestinal system continues to present diverse protein function information to understand the bacterial determinants that influence obesity development. The goal of the research reported in this article was to identify biological processes in probiotic bacteria that could influence the mechanisms for the extraction of energy from diet in the human gastrointestinal system. Our research strategy of combining bioinformatics and visual analytics methods was based on the identification of operon gene arrangements in genomes of Lactobacillus species and Akkermansiamuciniphila that include at least a gene for a universal stress protein. The two major findings from this research study are related to Lactobacillus plantarum and Akkermansia muciniphila bacteria species which are associated with weight-loss. The first finding is that Lactobacillus plantarum strains have a two-gene operon that encodes a universal stress protein for stress response and the membrane translocator protein (TSPO), known to function in mitochondrial fatty acid oxidation in humans. The second finding is the presence of a three-gene operon in Akkermansia muciniphila that includes a gene whose human mitochondrial homolog is associated with waist-hip ratio and fat distribution. From a public health perspective, elucidation of the bacterial determinants influencing obesity will help in educating the public on optimal probiotic use for anti-obesity effects.

Knowledge building insights on biomarkers of arsenic toxicity to keratinocytes and melanocytes.

Exposure to inorganic arsenic induces skin cancer and abnormal pigmentation in susceptible humans. High-throughput gene transcription assays such as DNA microarrays allow for the identification of biological pathways affected by arsenic that lead to initiation and progression of skin cancer and abnormal pigmentation. The overall purpose of the reported research was to determine knowledge building insights on biomarker genes for arsenic toxicity to human epidermal cells by integrating a collection of gene lists annotated with biological information. The information sets included toxicogenomics gene-chemical interaction; enzymes encoded in the human genome; enriched biological information associated with genes; environmentally relevant gene sequence variation; and effects of non-synonymous single nucleotide polymorphisms (SNPs) on protein function. Molecular network construction for arsenic upregulated genes TNFSF18 (tumor necrosis factor [ligand] superfamily member 18) and IL1R2 (interleukin 1 Receptor, type 2) revealed subnetwork interconnections to E2F4, an oncogenic transcription factor, predominantly expressed at the onset of keratinocyte differentiation. Visual analytics integration of gene information sources helped identify RAC1, a GTP binding protein, and TFRC, an iron uptake protein as prioritized arsenic-perturbed protein targets for biological processes leading to skin hyperpigmentation. RAC1 regulates the formation of dendrites that transfer melanin from melanocytes to neighboring keratinocytes. Increased melanocyte dendricity is correlated with hyperpigmentation. TFRC is a key determinant of the amount and location of iron in the epidermis. Aberrant TFRC expression could impair cutaneous iron metabolism leading to abnormal pigmentation seen in some humans exposed to arsenicals. The reported findings contribute to insights on how arsenic could impair the function of genes and biological pathways in epidermal cells. Finally, we developed visual analytics resources to facilitate further exploration of the information and knowledge building insights on arsenic toxicity to human epidermal keratinocytes and melanocytes.

Developmental Regulation of Genes Encoding Universal Stress Proteins in Schistosoma mansoni.

The draft nuclear genome sequence of the snail-transmitted, dimorphic, parasitic, platyhelminth Schistosoma mansoni revealed eight genes encoding proteins that contain the Universal Stress Protein (USP) domain. Schistosoma mansoni is a causative agent of human schistosomiasis, a severe and debilitating Neglected Tropical Disease (NTD) of poverty, which is endemic in at least 76 countries. The availability of the genome sequences of Schistosoma species presents opportunities for bioinformatics and genomics analyses of associated gene families that could be targets for understanding schistosomiasis ecology, intervention, prevention and control. Proteins with the USP domain are known to provide bacteria, archaea, fungi, protists and plants with the ability to respond to diverse environmental stresses. In this research investigation, the functional annotations of the USP genes and predicted nucleotide and protein sequences were initially verified. Subsequently, sequence clusters and distinctive features of the sequences were determined. A total of twelve ligand binding sites were predicted based on alignment to the ATP-binding universal stress protein from Methanocaldococcus jannaschii. In addition, six USP sequences showed the presence of ATP-binding motif residues indicating that they may be regulated by ATP. Public domain gene expression data and RT-PCR assays confirmed that all the S. mansoni USP genes were transcribed in at least one of the developmental life cycle stages of the helminth. Six of these genes were up-regulated in the miracidium, a free-swimming stage that is critical for transmission to the snail intermediate host. It is possible that during the intra-snail stages, S. mansoni gene transcripts for universal stress proteins are low abundant and are induced to perform specialized functions triggered by environmental stressors such as oxidative stress due to hydrogen peroxide that is present in the snail hemocytes. This report serves to catalyze the formation of a network of researchers to understand the function and regulation of the universal stress proteins encoded in genomes of schistosomes and their snail intermediate hosts.

The case for visual analytics of arsenic concentrations in foods.

Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i) metabolism of arsenic in the human body; (ii) arsenic concentrations in various foods; (ii) factors affecting arsenic uptake in plants; (ii) introduction to visual analytics; and (iv) benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species.