Design of an innovative digital application to facilitate access to healthy foods in low-income urban settings.

Background: Under-resourced urban minority communities in the United States are characterized by food environments with low access to healthy foods, high food insecurity, and high rates of diet-related chronic disease. In Baltimore, Maryland, low access to healthy food largely results from a distribution gap between small food sources (retailers) and their suppliers. Digital interventions have the potential to address this gap, while keeping costs low. Methods: In this paper, we describe the technical (I) front-end design and (II) back-end development process of the Baltimore Urban food Distribution (BUD) application (app). We identify and detail four main phases of the process: (I) information architecture; (II) low and high-fidelity wireframes; (III) prototype; and (IV) back-end components, while considering formative research and a pre-pilot test of a preliminary version of the BUD app. Results: Our lessons learned provide valuable insight into developing a stable app with a user-friendly experience and interface, and accessible cloud computing services for advanced technical features. Conclusions: Next steps will involve a pilot trial of the app in Baltimore, and eventually, other urban and rural settings nationwide. Once iterative feedback is incorporated into the app, all code will be made publicly available via an open source repository to encourage adaptation for desired communities. Trial Registration: ClinicalTrials.gov NCT05010018.

Usability and Credibility of a COVID-19 Vaccine Chatbot for Young Adults and Health Workers in the United States: Formative Mixed Methods Study.

BACKGROUND: The COVID-19 pandemic raised novel challenges in communicating reliable, continually changing health information to a broad and sometimes skeptical public, particularly around COVID-19 vaccines, which, despite being comprehensively studied, were the subject of viral misinformation. Chatbots are a promising technology to reach and engage populations during the pandemic. To inform and communicate effectively with users, chatbots must be highly usable and credible. OBJECTIVE: We sought to understand how young adults and health workers in the United States assessed the usability and credibility of a web-based chatbot called Vira, created by the Johns Hopkins Bloomberg School of Public Health and IBM Research using natural language processing technology. Using a mixed method approach, we sought to rapidly improve Vira's user experience to support vaccine decision-making during the peak of the COVID-19 pandemic. METHODS: We recruited racially and ethnically diverse young people and health workers, with both groups from urban areas of the United States. We used the validated Chatbot Usability Questionnaire to understand the tool's navigation, precision, and persona. We also conducted 11 interviews with health workers and young people to understand the user experience, whether they perceived the chatbot as confidential and trustworthy, and how they would use the chatbot. We coded and categorized emerging themes to understand the determining factors for participants' assessment of chatbot usability and credibility. RESULTS: In all, 58 participants completed a web-based usability questionnaire and 11 completed in-depth interviews. Most questionnaire respondents said the chatbot was "easy to navigate" (51/58, 88%) and "very easy to use" (50/58, 86%), and many (45/58, 78%) said its responses were relevant. The mean Chatbot Usability Questionnaire score was 70.2 (SD 12.1) and scores ranged from 40.6 to 95.3. Interview participants felt the chatbot achieved high usability due to its strong functionality, performance, and perceived confidentiality and that the chatbot could attain high credibility with a redesign of its cartoonish visual persona. Young people said they would use the chatbot to discuss vaccination with hesitant friends or family members, whereas health workers used or anticipated using the chatbot to support community outreach, save time, and stay up to date. CONCLUSIONS: This formative study conducted during the pandemic's peak provided user feedback for an iterative redesign of Vira. Using a mixed method approach provided multidimensional feedback, identifying how the chatbot worked well-being easy to use, answering questions appropriately, and using credible branding-while offering tangible steps to improve the product's visual design. Future studies should evaluate how chatbots support personal health decision-making, particularly in the context of a public health emergency, and whether such outreach tools can reduce staff burnout. Randomized studies should also be conducted to measure how chatbots countering health misinformation affect user knowledge, attitudes, and behavior.

Effect of IL-10 Deficiency on TGFß Expression during Fatal Alphavirus Encephalomyelitis in C57Bl/6 Mice.

Sindbis virus (SINV) causes viral encephalitis in mice with strain-dependent virulence. Fatal encephalomyelitis in C57Bl/6 mice infected with a neuroadapted strain of SINV (NSV) is an immunopathogenic process that involves Th17 cells modulated by the regulatory cytokine IL-10. To further characterize the pathogenic immune response to NSV, we analyzed the regulation of transforming growth factor (TGF)-b in both wild-type (WT) and IL-10-deficient mice. NSV infection upregulated the expression of TGFb1 and TGFb3 in the central nervous system (CNS). In the absence of IL-10, levels of brain Tgfb1 mRNA and brain and spinal cord mature active TGFß1 and TGFß3 proteins were higher than in WT mice. Compared to WT mice, IL-10-deficient mice had more TGFß1-expressing type 3 innate lymphoid cells (ILC3s) and CD4+ T cells infiltrating the CNS, but similar numbers in the cervical lymph nodes. Expression of glycoprotein A repetitions predominant protein (GARP) that binds pro-TGFb on the surface of regulatory T cells was decreased on CNS cells from IL-10-deficient mice. Higher CNS TGFb was accompanied by more expression of TGFbRII receptor, activation of SMAD transcription factors, increased PCKα mRNA, and more RORγt-positive and IL-17A-expressing cells. These results suggest a compensatory role for TGFß in the absence of IL-10 that fosters Th17-related immunopathology and more rapid death after NSV infection.

Enhancing Artificial Intelligence for Twitter-based Public Discourse on Food Security During the COVID-19 Pandemic.

OBJECTIVE: Food security during public health emergencies relies on situational awareness of needs and resources. Artificial intelligence (AI) has revolutionized situational awareness during crises, allowing the allocation of resources to needs through machine learning algorithms. Limited research exists monitoring Twitter for changes in the food security-related public discourse during the COVID-19 pandemic. We aim to address that gap with AI by classifying food security topics on Twitter and showing topic frequency per day. METHODS: Tweets were scraped from Twitter from January 2020 through December 2021 using food security keywords. Latent Dirichlet Allocation (LDA) topic modeling was performed, followed by time-series analyses on topic frequency per day. RESULTS: 237,107 tweets were scraped and classified into topics, including food needs and resources, emergency preparedness and response, and mental/physical health. After the WHO's pandemic declaration, there were relative increases in topic density per day regarding food pantries, food banks, economic and food security crises, essential services, and emergency preparedness advice. Threats to food security in Tigray emerged in 2021. CONCLUSIONS: AI is a powerful yet underused tool to monitor food insecurity on social media. Machine learning tools to improve emergency response should be prioritized, along with measurement of impact. Further food insecurity word patterns testing, as generated by this research, with supervised machine learning models can accelerate the uptake of these tools by policymakers and aid organizations.

The Baltimore Urban Food Distribution (BUD) App: Study Protocol to Assess the Feasibility of a Food Systems Intervention.

Low-income urban communities in the United States commonly lack ready access to healthy foods. This is due in part to a food distribution system that favors the provision of high-fat, high-sugar, high-sodium processed foods to small retail food stores, and impedes their healthier alternatives, such as fresh produce. The Baltimore Urban food Distribution (BUD) study is a multilevel, multicomponent systems intervention that aims to improve healthy food access in low-income neighborhoods of Baltimore, Maryland. The primary intervention is the BUD application (app), which uses the power of collective purchasing and delivery to affordably move foods from local producers and wholesalers to the city's many corner stores. We will implement the BUD app in a sample of 38 corner stores, randomized to intervention and comparison. Extensive evaluation will be conducted at each level of the intervention to assess overall feasibility and effectiveness via mixed methods, including app usage data, and process and impact measures on suppliers, corner stores, and consumers. BUD represents one of the first attempts to implement an intervention that engages multiple levels of a local food system. We anticipate that the app will provide a financially viable alternative for Baltimore corner stores to increase their stocking and sales of healthier foods, subsequently increasing healthy food access and improving diet-related health outcomes for under-resourced consumers. The design of the intervention and the evaluation plan of the BUD project are documented here, including future steps for scale-up. Trial registration #: NCT05010018.

Moving Food Assistance into the Digital Age: A Scoping Review.

One of the most basic needs globally, food assistance refers to the multitude of programs, both governmental and non-governmental, to improve food access and consumption by food-insecure individuals and families. Despite the importance of digital and mobile Health (mHealth) strategies in food insecurity contexts, little is known about their specific use in food assistance programs. Therefore, the purpose of this study was to address that gap by conducting a scoping review of the literature. Keywords were defined within the concepts of food assistance and digital technology. The search included relevant peer-reviewed and grey literature from 2011 to 2021. Excluded articles related to agriculture and non-digital strategies. PRISMA guidelines were followed to perform a partnered, two-round scoping literature review. The final synthesis included 39 studies of which most (84.6%) were from the last five years and United States-based (93.2%). The top three types of articles or studies included text and opinion, qualitative research, and website, application, or model development (17.9%). The top three types of digital tools were websites (56.4%), smartphone applications (20.5%), and chatbots (5.1%). Nineteen digital features were identified as desirable. Most tools included just one or two features. The most popular feature to include was online shopping (n = 14), followed by inventory management, and client tracking. Digital tools for individual food assistance represent an opportunity for equitable and stable access to programs that can enhance or replace in-person services. While this review identified 39 tools, all are in early development and/or implementation stages. Review findings highlight an overall lack of these tools, an absence of user-centered design in their development, and a critical need for research on their effectiveness globally. Further analysis and testing of current digital tool usage and interventions examining the health and food security impacts of such tools should be explored in future studies, including in the context of pandemics, where digital tools allow for help from a distance.

Digital Strategies to Improve Food Assistance in Disasters: A Scoping Review.

OBJECTIVE: Modern digital strategies, including Internet of Things, machine learning, and mobile applications, have revolutionized situational awareness during disaster management. Despite their importance, no review of digital strategies to support emergency food security efforts has been conducted. This scoping review fills that gap. METHODS: Keywords were defined within the concepts of food assistance, digital technology, and disasters. After the database searches, PRISMA guidelines were followed to perform a partnered, 2-round scoping literature review. RESULTS: The search identified 3201 articles, and 26 articles met criteria and were included in the analysis. The data types used to describe the tools were text/opinion (42.3%), qualitative (23.1%), system architecture (19.2%), quantitative and qualitative (11.5 %), and quantitative (3.8%). The tools' main functions were Resource Allocation (41.7%), Data Collection and Management (33%), Interagency Communications (15.4 %), Beneficiary Communications (11.5%), and Fundraising (7.7%). The platforms used to achieve these goals were Mobile Application (36%), Internet of Things (20%), Website (20%), and Mobile Survey (8%); 92% covered the disaster response phase. CONCLUSIONS: Digital tools for planning, situational awareness, client choice, and recovery are needed to support emergency food assistance, but there is a lack of these tools and research on their effectiveness across all disaster phases.

Interleukin-10 Modulation of Virus Clearance and Disease in Mice with Alphaviral Encephalomyelitis.

Alphaviruses are an important cause of mosquito-borne outbreaks of arthritis, rash, and encephalomyelitis. Previous studies in mice with a virulent strain (neuroadapted SINV [NSV]) of the alphavirus Sindbis virus (SINV) identified a role for Th17 cells and regulation by interleukin-10 (IL-10) in the pathogenesis of fatal encephalomyelitis (K. A. Kulcsar, V. K. Baxter, I. P. Greene, and D. E. Griffin, Proc Natl Acad Sci U S A 111:16053-16058, 2014, https://doi.org/10.1073/pnas.1418966111). To determine the role of virus virulence in generation of immune responses, we analyzed the modulatory effects of IL-10 on disease severity, virus clearance, and the CD4+ T cell response to infection with a recombinant strain of SINV of intermediate virulence (TE12). The absence of IL-10 during TE12 infection led to longer morbidity, more weight loss, higher mortality, and slower viral clearance than in wild-type mice. More severe disease and impaired virus clearance in IL-10-/- mice were associated with more Th1 cells, fewer Th2 cells, innate lymphoid type 2 cells, regulatory cells, and B cells, and delayed production of antiviral antibody in the central nervous system (CNS) without an effect on Th17 cells. Therefore, IL-10 deficiency led to more severe disease in TE12-infected mice by increasing Th1 cells and by hampering development of the local B cell responses necessary for rapid production of antiviral antibody and virus clearance from the CNS. In addition, the shift from Th17 to Th1 responses with decreased virus virulence indicates that the effects of IL-10 deficiency on immunopathologic responses in the CNS during alphavirus infection are influenced by virus strain.IMPORTANCE Alphaviruses cause mosquito-borne outbreaks of encephalomyelitis, but determinants of outcome are incompletely understood. We analyzed the effects of the anti-inflammatory cytokine IL-10 on disease severity and virus clearance after infection with an alphavirus strain of intermediate virulence. The absence of IL-10 led to longer illness, more weight loss, more death, and slower viral clearance than in mice that produced IL-10. IL-10 influenced development of disease-causing T cells and entry into the brain of B cells producing antiviral antibody. The Th1 pathogenic cell subtype that developed in IL-10-deficient mice infected with a less virulent virus was distinct from the Th17 subtype that developed in response to a more virulent virus, indicating a role for virus strain in determining the immune response. Slow production of antibody in the nervous system led to delayed virus clearance. Therefore, both the virus strain and the host response to infection are important determinants of outcome.

Metabolic stress regulates cytoskeletal dynamics and metastasis of cancer cells.

Metabolic reprogramming is an important driver of tumor progression; however, the metabolic regulators of tumor cell motility and metastasis are not understood. Here, we show that tumors maintain energy production under nutrient deprivation through the function of HSP90 chaperones compartmentalized in mitochondria. Using cancer cell lines, we found that mitochondrial HSP90 proteins, including tumor necrosis factor receptor-associated protein-1 (TRAP-1), dampen the activation of the nutrient-sensing AMPK and its substrate UNC-51-like kinase (ULK1), preserve cytoskeletal dynamics, and release the cell motility effector focal adhesion kinase (FAK) from inhibition by the autophagy initiator FIP200. In turn, this results in enhanced tumor cell invasion in low nutrients and metastatic dissemination to bone or liver in disease models in mice. Moreover, we found that phosphorylated ULK1 levels were correlated with shortened overall survival in patients with non-small cell lung cancer. These results demonstrate that mitochondrial HSP90 chaperones, including TRAP-1, overcome metabolic stress and promote tumor cell metastasis by limiting the activation of the nutrient sensor AMPK and preventing autophagy.

Regulation of lung cancer metastasis by Klf4-Numb-like signaling.

Metastatic traits seem to be acquired by transformed cells with progenitor-like cancer-initiating properties, but there remains little mechanistic insight into this linkage. In this report, we show that the polarity protein Numbl, which is expressed normally in neuronal progenitors, becomes overexpressed and mislocalized in cancer cells from a variety of human tumors. Numbl overexpression relies on loss of the tumor suppressor miRNA-296-5p (miR-296), which actively represses translation of Numbl in normal cells. In turn, deregulated expression of Numbl mediates random tumor cell migration and invasion, blocking anoikis and promoting metastatic dissemination. In clinical specimens of non-small cell lung cancer, we found that Numbl overexpression correlated with a reduction in overall patient survival. Mechanistically, Numbl-mediated tumorigenesis involved suppression of a "stemness" transcriptional program driven by the stem cell programming transcription factor Klf4, thereby preserving a pool of progenitor-like cells in lung cancer. Our results reveal that Numbl-Klf4 signaling is critical to maintain multiple nodes of metastatic progression, including persistence of cancer-initiating cells, rationalizing its therapeutic exploitation to improve the treatment of advanced lung cancer.

Cyclophilin D extramitochondrial signaling controls cell cycle progression and chemokine-directed cell motility.

Mitochondria control bioenergetics and cell fate decisions, but how they influence nuclear gene expression is understood poorly. Here, we show that deletion or reduction in the levels of cyclophilin D (CypD, also called Ppif), a mitochondrial matrix peptidyl prolyl isomerase and apoptosis regulator, results in increased cell proliferation and enhanced cell migration and invasion. These responses are associated with extensive transcriptional changes, modulation of a chemokine/chemokine receptor gene signature, and activation of the pleiotropic inflammatory mediator, STAT3. In the absence of CypD, active STAT3 enhances cell proliferation via accelerated entry into S-phase and stimulates autocrine/paracrine cell motility through Cxcl12-Cxcr4-directed chemotaxis. Therefore, CypD directs mitochondria-to-nuclei inflammatory gene expression in normal and tumor cells. This pathway may contribute to malignant traits under conditions of CypD modulation.

Essential role of the small GTPase Ran in postnatal pancreatic islet development.

The small GTPase Ran orchestrates pleiotropic cellular responses of nucleo-cytoplasmic shuttling, mitosis and subcellular trafficking, but whether deregulation of these pathways contributes to disease pathogenesis has remained elusive. Here, we generated transgenic mice expressing wild type (WT) Ran, loss-of-function Ran T24N mutant or constitutively active Ran G19V mutant in pancreatic islet ß cells under the control of the rat insulin promoter. Embryonic pancreas and islet development, including emergence of insulin(+) ß cells, was indistinguishable in control or transgenic mice. However, by one month after birth, transgenic mice expressing any of the three Ran variants exhibited overt diabetes, with hyperglycemia, reduced insulin production, and nearly complete loss of islet number and islet mass, in vivo. Deregulated Ran signaling in transgenic mice, adenoviral over-expression of WT or mutant Ran in isolated islets, or short hairpin RNA (shRNA) silencing of endogenous Ran in model insulinoma INS-1 cells, all resulted in decreased expression of the pancreatic and duodenal homeobox transcription factor, PDX-1, and reduced ß cell proliferation, in vivo. These data demonstrate that a finely-tuned balance of Ran GTPase signaling is essential for postnatal pancreatic islet development and glucose homeostasis, in vivo.

Evaluation of a domain-specific anger expression assessment strategy.

Previous studies have shown that self-reports of an individual's anger expression vary between the home and the work domain. The aim of this study was to investigate the validity of such self-reports by comparing them with reports of intimate partners and work colleagues in the respective domain. Participants (N= 86) rated their anger expression on the general and on domain-specific versions of the State-Trait-Anger Expression Inventory (Spielberger, 1988). The self-rated anger-out-home scores correlated highly with partner ratings of anger-out-home scores (r = .61) and colleague ratings of anger-out-work scores correlated substantially with self-rated anger-out-work scores (r = .54). A similar but weaker correlation pattern emerged for anger control but not for anger-in. Self-other correspondence was higher for the domain-specific anger expression assessment than for the general anger expression assessment. These results demonstrate that the domain-specific strategy for the assessment of self-reported anger expression can validly measure differences in anger expression in different domains.