Activin A promotes fetal mouse testis development, including driving Sertoli cell proliferation and cord morphogenesis, but its mechanisms of action are undefined. We performed ribonucleic acid sequencing (RNA-seq) on testicular somatic cells from fetal activin A-deficient mice (Inhba KO) and wildtype littermates at embryonic day (E) E13.5 and E15.5. Analysis of whole gonads provided validation, and cultures with a pathway inhibitor discerned acute from chronic effects of altered activin A bioactivity. Activin A deficiency predominantly affects the Sertoli cell transcriptome. New candidate targets include Minar1, Sel1l3, Vnn1, Sfrp4, Masp1, Nell1, Tthy1 and Prss12. Importantly, the testosterone (T) biosynthetic enzymes present in fetal Sertoli cells, Hsd17b1 and Hsd17b3, were identified as activin-responsive. Activin-deficient testes contained elevated androstenedione (A4), displayed an Inhba gene dose-dependent A4/T ratio, and contained 11-keto androgens. The remarkable accumulation of lipid droplets in both Sertoli and germ cells at E15.5 indicated impaired lipid metabolism in the absence of activin A. This demonstrated for the first time that activin A acts on Sertoli cells to determine local steroid production during fetal testis development. These outcomes reveal how compounds that perturb fetal steroidogenesis can function through cell-specific mechanisms and can indicate how altered activin levels in utero may impact testis development.

Background The integration of time with dietary patterns throughout a day, or temporal dietary patterns (TDPs), have been linked with dietary quality but relations to health are unknown. Objective The association between TDPs and selected health status indicators and obesity, type 2 diabetes (T2D), and metabolic syndrome (MetS) was determined. Methods The first-day 24-h dietary recall from 1627 nonpregnant US adult participants aged 20–65 y from the NHANES 2003–2006 was used to determine timing, amount of energy intake, and sequence of eating occasions (EOs). Modified dynamic time warping (MDTW) and kernel k-means algorithm clustered participants into 4 groups representing distinct TDPs. Multivariate regression models determined associations between TDPs and health status, controlling for potential confounders, and adjusting for the survey design and multiple comparisons (P <0.05/6). Results A cluster representing a TDP with evenly spaced, energy balanced EOs reaching ≤1200 kcal between 06:00 to 10:00, 12:00 to 15:00, and 18:00 to 22:00, had statistically significant and clinically meaningful lower mean BMI (P <0.0001), waist circumference (WC) (P <0.0001), and 75% lower odds of obesity compared with 3 other clusters representing patterns with much higher peaks of energy: 1000–2400 kcal between 15:00 and 18:00 (OR: 5.3; 95% CI: 2.8, 10.1), 800–2400 kcal between 11:00 and 15:00 (OR: 4.4; 95% CI: 2.5, 7.9), and 1000–2600 kcal between 18:00 and 23:00 (OR: 6.7; 95% CI: 3.9, 11.6). Conclusions Individuals with a TDP characterized by evenly spaced, energy balanced EOs had significantly lower mean BMI, WC, and odds of obesity compared with the other patterns with higher energy intake peaks at different times throughout the day, providing evidence that incorporating time with other aspects of a dietary pattern may be important to health status.

Background: Few attempts have been made to incorporate multiple aspects of physical activity (PA), including timing and volume, to classify patterns that link to health. Temporal PA patterns integrating time and activity counts were created to determine their association with health. Methods: PA accelerometry data obtained from the cross-sectional National Health and Nutrition Examination Survey 2003-2006 was used to pattern PA counts and time of activity from 1,999 nonpregnant adults with one random valid weekday of activity. Constrained dynamic time warping with Sakoe-Chiba band and kernel k-means clustering grouped participants to 4 clusters representing temporal PA patterns. Multivariate regression models controlling for potential confounders and adjusting for multiple comparisons (p<0.05/6) determined associations between clusters and health status indicators and conditions obesity, type 2 diabetes, and metabolic syndrome.Results: Participants in Cluster 2, represented by a temporal PA pattern with activity counts reaching >1.2e 5 counts/ h (cph) and tapering off through the day, had lower mean body mass index (BMI) (p<0.001), waist circumference (WC) (p<0.01), and 65% lower odds of obesity relative to normal weight status compared with participants in Cluster 1 with the lowest PA counts reaching 4.8e 4 cph from 6:00 to 23:00 (OR: 0.3; 95% CI: 0.2, 0.8). Cluster 3, characterized by a temporal PA pattern with activity counts reaching 9.6e 4 -1.2e 5 cph between 16:00 to 21:00, was associated with lower mean BMI (p<0.001) and WC (p<0.01), and 60% lower odds of obesity relative to normal weight status compared to Cluster 1 (OR: 0.4; 95% CI: 0.2, 0.8). Cluster 4 characterized by activity counts reaching 9.6e 4 cph between 8:00 to 11:00 was associated with lower BMI and WC compared to Cluster 1 (both p<0.05).Conclusions: U.S. adults with temporal PA patterns of higher activity counts ranging between 9.6e 4 ->1.2e 5 cph performed early (8:00 to 11:00), late (16:00 to 21:00), or throughout the day had signi cantly lower mean BMI and WC compared with adults with a temporal PA pattern of the lowest PA counts reaching 4.8e 4 cph from 6:00 to 23:00. Temporal PA patterns created by integrating time with PA counts throughout a day meaningfully link to health status.

Objectives The integration of time with dietary patterns throughout a day, or temporal dietary patterns (TDP), have been linked with dietary quality but links to health outcomes are unknown. TDP were created with the objective to examine their association with health status indicators including body mass index (BMI), waist circumference (WC), fasting plasma glucose, hemoglobin A1c, triglyceride, high-density lipoprotein cholesterol, total cholesterol, blood pressure, and chronic diseases obesity, diabetes, and metabolic syndrome in US adults 20–65 years. Methods The first-day 24-hour dietary recall from 1627 non-pregnant US adult participants of the cross-sectional National Health and Nutrition Examination Survey 2003–2006 was used to determine energy intake (kcal), time of intake (min), and sequence of intake occasions throughout the 24-hour day. Modified dynamic time warping coupled with kernel k-means algorithm, clustered participants into four groups representing distinct TDP. Multivariate regression models determined associations between TDP clusters and all outcomes, controlling for potential confounders, energy misreporting, and adjusting for multiple comparisons and the complex survey design (P &lt; 0.05/6). Results The cluster representing a TDP with proportionally equivalent average energy at three main eating occasions from 8:00 to 23:00 with peaks reaching 175 kcal at 9:00, 13:00, and 19:00, had statistically significant and clinically meaningful lower BMI (P &lt; 0.0001), WC (P &lt; 0.0001) and 75% lower odds of obesity compared to three other clusters representing distinct patterns of much higher average peak energy intake of 500 kcal at 13:00 (odds ratio (OR): 4.4; 95% confidence interval (CI)): 2.5, 7.9), 530 kcal at 18:00 (OR: 5.3; 95% CI: 2.8, 10.1), and 550 kcal at 20:00 (OR: 6.7; 95%CI: 3.9, 11.6). Conclusions A positive association of the TDP of moderate energy intake throughout the day with healthy weight outcomes supports previous findings of higher dietary quality among those with a similar TDP and provides unique evidence that incorporating time with other aspects of a dietary pattern are linked to health. Funding Sources Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health and Purdue University.

The 2020 COVID-19 pandemic brought uncertainty, anxiety, and stress into households; however, it also created an opportunity as many families, sequestered at home, found themselves spending much more time together. To support families and improve their ability to cope, recover, and build resilience amid the pandemic, Purdue University’s College of Health and Human Sciences (HHS) launched Families Tackling Tough Times Together (FT), a strength-based multi-week online program informed by scientific evidence about family resilience. Offered through a Facebook group, FT targeted parents or caregivers, children, youth, young adults, older adults, and helping professionals serving families. FT was designed to appeal to both military and civilian families, in part because both groups were experiencing similar challenges associated with the pandemic. This was not only an opportunity to bring civilian and military families together, but also for civilian families to learn from the experiences of military families in surmounting significant challenges. This article describes the development and implementation of the FT program, as well as lessons learned. Strategies highlighted in this article may be helpful to researchers or practitioners who wish to implement a rapid-response intervention aimed at building family resilience.