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Background In recent reviews of available measures, no existing measures assessed all four pillars of food security and most only assessed one or two pillars–predominantly the access pillar. The purpose of this study was to preliminarily develop novel measures of availability, utilization, and stability that are complementary to the USDA’s household food security survey measure (HFSSM). Methods A formative phase included an expert advisory group, literature scans, and interviews with individuals experiencing food insecurity. From April-June 2021, the new measures were piloted in five states (California, Florida, Maryland, North Carolina, and Washington). The cross-sectional pilot survey included the new measures (perceived limited availability, utilization barriers, and food insecurity stability), scales and items for validation (e.g., food security, and self-reported dietary and health outcomes), and demographic questions. Exploratory factor analysis was used to assess dimensionality, internal consistency was assessed using Kuder-Richardson formula 21 (KR21), and convergent and discriminant validity were assessed using Spearman’s correlation coefficients. Also, a brief screener version was created for the utilization barriers measure that may be necessary for certain applications (e.g., clinical intake screening to inform referrals to assistance programs). Results The analytic samples (perceived limited availability (n = 334); utilization barriers (n = 428); food insecurity stability (n = 445)) were around 45 years old on average, most households had children, over two-thirds were food insecure, over three-fourths were women, and the samples were racially/ethnically diverse. All items loaded highly and unambiguously to a factor (factor loadings range 0.525–0.903). Food insecurity stability showed a four-factor structure, utilization barriers showed a two-factor structure, and perceived limited availability showed a two-factor structure. KR21 metrics ranged from 0.72 to 0.84. Higher scores for the new measures were generally associated with increased food insecurity (rhos = 0.248–0.497), except for one of the food insecurity stability scores. Also, several of the measures were associated with statistically significantly worse health and dietary outcomes. Conclusions The findings support the reliability and construct validity of these new measures within a largely low-income and food insecure sample of households in the United States. Following further testing, such as Confirmatory Factor Analysis in future samples, these measures may be used in various applications to promote a more comprehensive understanding of the food insecurity experience. Such work can help inform novel intervention approaches to address food insecurity more fully.

Ambient mass spectrometry is an analytical approach that enables ionization of molecules under open-air conditions with no sample preparation and very fast sampling times. Rapid evaporative ionization mass spectrometry (REIMS) is a relatively new type of ambient mass spectrometry that has demonstrated applications in both human health and food science. Here, we present an evaluation of REIMS as a tool to generate molecular scale information as an objective measure for the assessment of beef quality attributes. Eight different machine learning algorithms were compared to generate predictive models using REIMS data to classify beef quality attributes based on the United States Department of Agriculture (USDA) quality grade, production background, breed type and muscle tenderness. The results revealed that the optimal machine learning algorithm, as assessed by predictive accuracy, was different depending on the classification problem, suggesting that a “one size fits all” approach to developing predictive models from REIMS data is not appropriate. The highest performing models for each classification achieved prediction accuracies between 81.5–99%, indicating the potential of the approach to complement current methods for classifying quality attributes in beef.

The growth of the self-concept through increasing perspectives, identities, resources, and efficacy is known as self-expansion and typically involves novelty, challenge, interest, and/or excitement. Self-expansion is positively associated with health factors including self-reported physical activity (PA). This study is the first to investigate self-expansion and daily PA, and with a PA monitor. Fifty community participants completed baseline questionnaires, wore a Fitbit One and completed daily self-report questionnaires for 28 days, and completed follow-up questionnaires. Daily surveys included questions about both general and PA-specific self-expansion. Across the 4 weeks, steps taken was positively correlated with both general (all maximum likelihood r  = 0.17) and PA-specific self-expansion (maximum likelihood rs of 0.15 and 0.16), and PA-specific self-expansion was positively correlated (maximum likelihood rs of 0.38 and 0.50) with aerobic activity. Future research should investigate this relationship in a larger more diverse sample and test whether PA-specific self-expansion can be utilized as an acceptable, feasible, and effective intervention to increase daily steps and other forms of PA.

Advances in neuroimaging technology, like functional near-infrared spectroscopy (fNIRS), support the evaluation of task-dependent brain activity during functional tasks, like balance, in healthy and clinical populations. To date, there have been no studies examining how interventions, like yoga, impact task-dependent brain activity in adults with chronic acquired brain injury (ABI). This pilot study compared eight weeks of group yoga (active) to group exercise (control) on balance and task-dependent neural activity outcomes. Twenty-three participants were randomized to yoga (n = 13) or exercise groups (n = 10). Neuroimaging and balance performance data were collected simultaneously using a force plate and mobile fNIRS device before and after interventions. Linear mixed-effects models were used to evaluate the effect of time, time x group interactions, and simple (i.e., within-group) effects. Regardless of group, all participants had significant balance improvements after the interventions. Additionally, regardless of group, there were significant changes in task-dependent neural activity, as well as distinct changes in neural activity within each group. In summary, using advances in sensor technology, we were able to demonstrate preliminary evidence of intervention-induced changes in balance and neural activity in adults with ABI. These preliminary results may provide an important foundation for future neurorehabilitation studies that leverage neuroimaging methods, like fNIRS.

Each year, millions of Americans sustain acquired brain injuries (ABI) which result in functional impairments, such as poor balance and autonomic nervous system (ANS) dysfunction. Although significant time and energy are dedicated to reducing functional impairment in acute phase of ABI, many individuals with chronic ABI have residual impairments that increase fall risk, decrease quality of life, and increase mortality. In previous work, we have found that yoga can improve balance in adults with chronic (i.e., ≥6 months post-injury) ABI. Moreover, yoga has been shown to improve ANS and brain function in healthy adults. Thus, adults with chronic ABI may show similar outcomes. This protocol details the methods used to examine the effects of a group yoga program, as compared to a group low-impact exercise, on primary and secondary outcomes in adults with chronic ABI. This study is a single-blind randomized controlled trial comparing group yoga to group low-impact exercise. Participants must be ≥18 years old with chronic ABI and moderate balance impairments. Group yoga and group exercise sessions occur twice a week for 1 h for 8 weeks. Sessions are led by trained adaptive exercise specialists. Primary outcomes are balance and ANS function. Secondary outcomes are brain function and structure, cognition, quality of life, and qualitative experiences. Data analysis for primary and most secondary outcomes will be completed with mixed effect statistical methods to evaluate the within-subject factor of time (i.e., pre vs. post intervention), the between-subject factor of group (yoga vs. low-impact exercise), and interaction effects. Deductive and inductive techniques will be used to analyze qualitative data. Due to its accessibility and holistic nature, yoga has significant potential for improving balance and ANS function, along with other capacities, in adults with chronic ABI. Because there are also known benefits of exercise and group interaction, this study compares yoga to a similar, group exercise intervention to explore if yoga has a unique benefit for adults with chronic ABI. ClinicalTrials.gov, NCT05793827. Registered on March 31, 2023.

[This corrects the article DOI: 10.3389/fnhum.2023.1291094.].

Background Placental efficiency (PE) describes the relationship between placental and fetal weights (fetal wt/placental wt). Within litters, PE can vary drastically, resulting in similarly sized pigs associated with differently sized placentas, up to a 25% weight difference. However, the mechanisms enabling the smaller placenta to grow a comparable littermate are unknown. To elucidate potential mechanisms, morphological measurements and gene expression profiles in placental and associated endometrial tissues of high PE and low PE feto-placental units were compared. Tissue samples were obtained from eight maternal line gilts during gestational day 95 ovario-hysterectomies. RNA was extracted from tissues of feto-placental units with the highest and lowest PE in each litter and sequenced. Results Morphological measurements, except placental weight, were not different ( P  > 0.05) between high and low PE. No DEG were identified in the endometrium and 214 DEG were identified in the placenta (FDR < 0.1), of which 48% were upregulated and 52% were downregulated. Gene ontology (GO) analysis revealed that a large percentage of DEG were involved in catalytic activity, binding, transporter activity, metabolism, biological regulation, and localization. Four GO terms were enriched in the upregulated genes and no terms were enriched in the downregulated genes (FDR < 0.05). Eight statistically significant correlations ( P  < 0.05) were identified between the morphological measurements and DEG. Conclusion Morphological measures between high and low PE verified comparisons were of similarly sized pigs grown on different sized placentas, and indicated that any negative effects of a reduced placental size on fetal growth were not evident by day 95. The identification of DEG in the placenta, but absence of DEG in the endometrium confirmed that the placenta responds to the fetus. The GO analyses provided evidence that extremes of PE are differentially regulated, affecting components of placental transport capacity like nutrient transport and blood flow. However, alternative GO terms were identified, indicating the complexity of the relationship between placental and fetal weights. These findings support the use of PE as a marker of placental function and provide novel insight into the genetic control of PE, but further research is required to make PE production applicable.

BACKGROUND: This paper examines the individual factors that influence prevalence rates of canine heartworm in the contiguous United States. A data set provided by the Companion Animal Parasite Council, which contains county-by-county results of over nine million heartworm tests conducted during 2011 and 2012, is analyzed for predictive structure. The goal is to identify the factors that are important in predicting high canine heartworm prevalence rates. METHODS: The factors considered in this study are those envisioned to impact whether a dog is likely to have heartworm. The factors include climate conditions (annual temperature, precipitation, and relative humidity), socio-economic conditions (population density, household income), local topography (surface water and forestation coverage, elevation), and vector presence (several mosquito species). A baseline heartworm prevalence map is constructed using estimated proportions of positive tests in each county of the United States. A smoothing algorithm is employed to remove localized small-scale variation and highlight large-scale structures of the prevalence rates. Logistic regression is used to identify significant factors for predicting heartworm prevalence. RESULTS: All of the examined factors have power in predicting heartworm prevalence, including median household income, annual temperature, county elevation, and presence of the mosquitoes Aedes trivittatus, Aedes sierrensis and Culex quinquefasciatus. Interactions among factors also exist. CONCLUSIONS: The factors identified are significant in predicting heartworm prevalence. The factor list is likely incomplete due to data deficiencies. For example, coyotes and feral dogs are known reservoirs of heartworm infection. Unfortunately, no complete data of their populations were available. The regression model considered is currently being explored to forecast future values of heartworm prevalence.

Collaborative work is inherent to being a statistician or data scientist, yet opportunities for training and exposure to real-world scenarios are often only a small part of a student's academic program. Resources to facilitate effective and meaningful instruction in communication and collaboration are limited, particularly when compared to the abundant resources available to support traditional statistical training in theory and methods. Our work helps fill the need for resources by providing ten modern, freely-available videos of mock collaborative interactions, with supporting discussion questions, scripts, and other resources. Videos are particularly helpful for teaching communication dynamics. These videos are set in the context of academic research discussions, though the scenarios are broad enough to facilitate discussions for other collaborative contexts as well. The videos and associated resources are designed to be incorporated into existing curricula related to collaboration. The materials have been piloted with positive feedback from students and instructors. Supplemental files for this article are available online.

This study considers whether a relationship exists between response to lithium (Li) exposure and select vegetation indices (VI) determined from reflectance spectra in each of four plant species: Arabidopsis thaliana, Helianthus annuus (sunflower), Brassica napus (rape), and Zea mays (corn). Reflectance spectra were collected every week for three weeks using an ASD FieldSpec Pro spectroradiometer with both a contact probe (CP) and a field of view probe (FOV) for plants treated twice weekly in a laboratory setting with 0 mM (control) or 15 mM of lithium chloride (LiCl) solution. Plants were harvested each week after spectra collection for determination of relevant physical endpoints such as relative water content and chlorophyll content. Mixed effects analyses were conducted on selected endpoints and vegetation indices (VI) to determine the significance of the effects of treatment level and length of treatment as well as to determine which VI would be appropriate predictors of treatment-dependent endpoints. Of the species considered, A. thaliana exhibited the most significant effects and corresponding shifts in reflectance spectra. Depending on the species and endpoint, the most relevant VIs in this study were NDVI, PSND, YI, R1676/R1933, R750/R550, and R950/R750.