Mechanoresponsive stem cells acquire neural crest fate in jaw regeneration.

During both embryonic development and adult tissue regeneration, changes in chromatin structure driven by master transcription factors lead to stimulus-responsive transcriptional programs. A thorough understanding of how stem cells in the skeleton interpret mechanical stimuli and enact regeneration would shed light on how forces are transduced to the nucleus in regenerative processes. Here we develop a genetically dissectible mouse model of mandibular distraction osteogenesis-which is a process that is used in humans to correct an undersized lower jaw that involves surgically separating the jaw bone, which elicits new bone growth in the gap. We use this model to show that regions of newly formed bone are clonally derived from stem cells that reside in the skeleton. Using chromatin and transcriptional profiling, we show that these stem-cell populations gain activity within the focal adhesion kinase (FAK) signalling pathway, and that inhibiting FAK abolishes new bone formation. Mechanotransduction via FAK in skeletal stem cells during distraction activates a gene-regulatory program and retrotransposons that are normally active in primitive neural crest cells, from which skeletal stem cells arise during development. This reversion to a developmental state underlies the robust tissue growth that facilitates stem-cell-based regeneration of adult skeletal tissue.

Evaluation of Walk Across Texas! - a web-based community physical activity program.

BACKGROUND: In response to the chronic disease burden, web- and community-based programs have the potential to address targeted behaviors, such as physical activity (PA), using a novel approach with large audiences. The purpose of this study was to preliminarily evaluate an established team centered, web-based community PA program in Texas. METHODS: Walk Across Texas! (WAT!) is an eight-week community program delivered through a web-based platform to help people of various ages and abilities establish the habit of regular PA. Teams are challenged to walk a minimum of 832 miles. Changes in self-reported PA (miles/week; days/week) and leisure-time sitting (hours/day) were examined from 11,116 adult participants who participated in the program in 2016. Further analysis determined changes in physical activity (miles/week) between groups of pre-program assessment self-reported physical activity levels (0, 1-2, 3-4, or 5-7 days/week). Statistical analysis included paired-sample t-tests, repeated measures ANOVA and participant descriptors for PA change. RESULTS: Overall, mean changes in PA in all variables were statistically significant (p < .001), with the largest, clinically significant changes in submitted miles/week (mean increase of 4.89 ± 20.92). Self-reported PA increased 0.63 ± 2.89 days/week, while leisure-time sitting decreased less than 1 h per day (0.87 ± 1.86 h/day). All sub-groups (inactive, low active, active, high active at pre-program assessment) increased in self-reported miles per week, on average. Both the inactive and low-active groups experienced a statistically significant increase in mileage from week 1 to week 8 (5.48 miles/week or 12,330 steps /week, and 3.91 miles/week or 8797 steps /week, respectively). CONCLUSIONS: The results provide initial support for the effectiveness of WAT! to initially increase and maintain moderate levels of PA of participants over 8-weeks, even in inactive or low-active participants. Descriptor variables were unable to differentiate between those who increased PA and those who did not. However; the results provide a canvas for future research questions regarding PA enhancement within a team-centered, web-based approach.

Physical Activity, Sedentary Behavior, and Diet-Related eHealth and mHealth Research: Bibliometric Analysis.

BACKGROUND: Electronic health (eHealth) and mobile health (mHealth) approaches to address low physical activity levels, sedentary behavior, and unhealthy diets have received significant research attention. However, attempts to systematically map the entirety of the research field are lacking. This gap can be filled with a bibliometric study, where publication-specific data such as citations, journals, authors, and keywords are used to provide a systematic overview of a specific field. Such analyses will help researchers better position their work. OBJECTIVE: The objective of this review was to use bibliometric data to provide an overview of the eHealth and mHealth research field related to physical activity, sedentary behavior, and diet. METHODS: The Web of Science (WoS) Core Collection was searched to retrieve all existing and highly cited (as defined by WoS) physical activity, sedentary behavior, and diet related eHealth and mHealth research papers published in English between January 1, 2000 and December 31, 2016. Retrieved titles were screened for eligibility, using the abstract and full-text where needed. We described publication trends over time, which included journals, authors, and countries of eligible papers, as well as their keywords and subject categories. Citations of eligible papers were compared with those expected based on published data. Additionally, we described highly-cited papers of the field (ie, top ranked 1%). RESULTS: The search identified 4805 hits, of which 1712 (including 42 highly-cited papers) were included in the analyses. Publication output increased on an average of 26% per year since 2000, with 49.00% (839/1712) of papers being published between 2014 and 2016. Overall and throughout the years, eHealth and mHealth papers related to physical activity, sedentary behavior, and diet received more citations than expected compared with papers in the same WoS subject categories. The Journal of Medical Internet Research published most papers in the field (9.58%, 164/1712). Most papers originated from high-income countries (96.90%, 1659/1717), in particular the United States (48.83%, 836/1712). Most papers were trials and studied physical activity. Beginning in 2013, research on Generation 2 technologies (eg, smartphones, wearables) sharply increased, while research on Generation 1 (eg, text messages) technologies increased at a reduced pace. Reviews accounted for 20 of the 42 highly-cited papers (n=19 systematic reviews). Social media, smartphone apps, and wearable activity trackers used to encourage physical activity, less sedentary behavior, and/or healthy eating were the focus of 14 highly-cited papers. CONCLUSIONS: This study highlighted the rapid growth of the eHealth and mHealth physical activity, sedentary behavior, and diet research field, emphasized the sizeable contribution of research from high-income countries, and pointed to the increased research interest in Generation 2 technologies. It is expected that the field will grow and diversify further and that reviews and research on most recent technologies will continue to strongly impact the field.

Examining the Role of Income Inequality and Neighborhood Walkability on Obesity and Physical Activity among Low-Income Hispanic Adults.

Obesity is a major public health issue affecting rising medical costs and contributing to morbidity and premature mortality. We aimed to identify factors that may play a role in obesity and physical activity at the individual and environmental/neighborhood levels. We analyzed data from an adult sample who were parents of students enrolled in a school-based health and wellness program. The sample was restricted to those who were Hispanic and whose children were on free/reduced lunch (n = 377). Dependent variables: body mass index (BMI); neighborhood walkability. Walk Score® was used to assess neighborhood walkability. Overall, 46% of participants were obese and 31% were overweight. The median age of respondents was 34 years, and the majority were female (88%) and married (59%). Participants who resided in a census tract with a higher relative income inequality (high, OR 2.54, 90% CI 1.154-5.601; moderate-high OR 2.527, 90% CI 1.324-4.821) and those who were unmarried (OR 1.807, 90% CI 1.119-2.917) were more likely to be obese versus normal weight. Overweight individuals that resided in areas that were walkable versus car-dependent averaged more days engaging in walking for at least 30-min (p <.05). Identifying individual and neighborhood factors associated with obesity can inform more targeted approaches to combat obesity at multiple ecological levels. The importance of understanding how neighborhood characteristics influence health-related and behavioral outcomes is further reinforced with the current findings. Identifying effective strategies to engage communities and organizations in creating, implementing, adopting, evaluating, and sustaining policy and/or environmental interventions will be needed to combat the obesity epidemic.

Past, Present, and Future of eHealth and mHealth Research to Improve Physical Activity and Dietary Behaviors.

Because physical inactivity and unhealthy diets are highly prevalent, there is a need for cost-effective interventions that can reach large populations. Electronic health (eHealth) and mobile health (mHealth) solutions have shown promising outcomes and have expanded rapidly in the past decade. The purpose of this report is to provide an overview of the state of the evidence for the use of eHealth and mHealth in improving physical activity and nutrition behaviors in general and special populations. The role of theory in eHealth and mHealth interventions is addressed, as are methodological issues. Key recommendations for future research in the field of eHealth and mHealth are provided.