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BACKGROUND: Hypertension increases the risk of lymphedema in patients with comorbidities, but whether hypertension directly compromises lymph vessel (LV) function and lymph flow is unclear. We compared the contractions of mesenteric LVs ex vivo and lymph flow in vivo between normotensive and Ang II (angiotensin II)-induced hypertensive rats and explored the ionic basis of contractile patterns. Key studies were recapitulated in spontaneously hypertensive rats and control Wistar-Kyoto rats. METHODS: Video microscopy continuously recorded the diameters of cannulated rat mesenteric LVs, and high-speed optical imaging estimated mesenteric lymph flow in vivo. Jess capillary Western electrophoresis evaluated expression levels of ion channel proteins. RESULTS: Isolated LVs from Ang II-induced hypertensive rats exhibited dysrhythmic contractions, whereas LVs from both Ang II-induced hypertensive rats and spontaneously hypertensive rats exhibited reduced diastolic diameters and cross-sectional flow. Mesenteric lymph flow in vivo was 2.9-fold lower in Ang II-induced hypertensive rats compared with normotensive rats. Surprisingly, the LVs from Ang II-induced hypertensive rats expressed fewer intact L-type Ca2+ channel pore proteins and more modulatory cleaved C-terminal fragments. However, pharmacological block of voltage-gated K+ channels but not other K+ channel types in control LVs established the pattern of contractile dysfunction observed in hypertension. Jess capillary Western electrophoresis analysis confirmed a loss of Shaker-type KV1.2 channels in LVs from hypertensive rats. CONCLUSIONS: We provide initial evidence of lymphatic contractile dysfunction and compromised lymph flow in hypertensive rats, which may be caused by a loss of KV1.2 channels in the lymphatic muscle cells. [ABSTRACT FROM AUTHOR]

Background: Sub-thermoneutral housing increases facultative thermogenesis in mice, which may mask the pre-clinical efficacy of anti-obesity strategies that target energy expenditure (EE). Here, we quantified the impact of protonophore treatment on whole-body energetics in mice housed at 30°C. Methods: C57BL/6J mice (n = 48, 24M/24F) were housed at 24°C for 2 weeks; 32 (16M/16F) were then transitioned to 30°C for a further 4 weeks. Following 2 weeks acclimation at 30°C, mice (n = 16 per group, 8M/8F) received either normal (0 mg/L; Control) or supplemented (400 mg/L; 2,4-Dinitrophenol [DNP]) drinking water. Mice were singly housed in metabolic cages to determine total EE (TEE) and its components via respiratory gas exchange. Mitochondrial respiratory function of permeabilized liver tissue was determined by high-resolution respirometry. Results: Transitioning mice from 24°C to 30°C reduced TEE and basal EE (BEE) by 16% and 41%, respectively (both P < 0.001). Compared to 30°C controls, TEE was 2.6 kcal/day greater in DNP-treated mice (95% CI: 1.6–3.6 kcal/day, P < 0.001), which was partly due to a 1.2 kcal/day higher BEE in DNP-treated mice (95% CI: 0.6–1.7 kcal/day, P < 0.001). The absolute TEE of 30°C DNP-treated mice was lower than that of mice housed at 24°C in the absence of DNP (DNP: 9.4 ± 0.7 kcal/day vs. 24°C control: 10.4 ± 1.5 kcal/day). DNP treatment reduced overall body fat of females by 2.9 percentage points versus sex-matched controls (95% CI: 1.3%–4.5%, P < 0.001), which was at least partly due to a reduction in inguinal white fat mass. Conclusion: Protonophore treatment markedly increases EE in mice housed at 30°C. The magnitude of change in TEE of mice receiving protonophore treatment at 30°C was smaller than that brought about by transitioning mice from 24°C to 30°C, emphasizing that housing temperature must be considered when assessing anti-obesity strategies that target EE in mice. [ABSTRACT FROM AUTHOR]

Background: Scholarly publications are important indicators of research productivity and investigator development in Centers of Biomedical Research Excellence (COBREs). However, no information is available to describe implementation and evaluation of writing development programs within COBREs. Therefore, this paper aimed to evaluate the first year of a campus-wide COBRE-supported writing program. Methods: A convergent parallel mixed-methods design (QUAN + QUAL) was used. All writing program participants were invited to complete post-participation surveys, and a subgroup was selected using purposive sampling to complete individual semi-structured interviews. Descriptive statistics were used to characterize survey data, and qualitative content analysis was employed to analyze interview data. Self-determination theory served as the theoretical framework by which themes were developed and interpreted. Results: Professional staff, post-doctoral fellows, and faculty from all academic ranks (n = 29) participated in the writing program during its first year. Survey respondents (n = 18, response rate 62%) rated social support (89%), group accountability (89%), hearing group members' writing goals (78%), receiving group advice (67%), and setting a weekly writing schedule (56%) as beneficial program components. Participants rated program benefits such as breaking away from other responsibilities, staying on task with writing goals, and receiving social support as most beneficial. During interviews, participants (n = 14) described five major themes related to the benefits received: 1) belonging to a community of writers; 2) managing writing-related emotions; 3) improved productivity; 4) establishing helpful writing habits; and 5) improved motivation for scholarly writing. Conclusions: This first-year programmatic evaluation demonstrates the writing program's effectiveness as a campus-level development resource supported by a research center. Both survey and interview data affirmed that participants perceived autonomy, competence, and relatedness were supported through participation in the writing program. Participants placed particular emphasis on the writing program's successful development of a community of scholarly writers. [ABSTRACT FROM AUTHOR]

Cage effects: some researchers worry about them, some don't, and some aren't even aware of them. When statistical analyses do not account for cage effects, there is real reason to worry. Regardless of researchers' worries or lack thereof, all researchers should be aware of how cage effects can affect the results. The "how" depends, in part, on the experimental design. Here, I (a) define cage effects; (b) illustrate a completely randomized design (CRD) often used in animal experiments; (c) explain how statistical significance is artificially inflated when cage effects are ignored and (d) give guidance on proper analyses and on how to increase statistical power in CRDs. [ABSTRACT FROM AUTHOR]

Over the years, animal models of local heart irradiation have provided insight into mechanisms of and treatments for radiation-induced heart disease in human populations. However, it is not completely clear which manifestations of radiation injury are most commonly seen after whole heart irradiation, and whether certain biological factors impact experimental results. Combining 9 homogeneous studies in rat models of whole heart irradiation from one laboratory, we sought to identify experimental and/or biological factors that impact heart outcomes. We evaluated the usefulness of including (1) heart rate and (2) bodyweight as covariates when analyzing biological parameters, and (3) we determined which echocardiography, histological, and immunohistochemistry parameters are most susceptible to radiation effects. Finally, (4) as an educational example, we illustrate a hypothetical sample size calculation for a study design commonly used in evaluating radiation modifiers, using the pooled estimates from the 9 rat studies only for context. The results may assist investigators in the design and analyses of pre-clinical studies of whole heart irradiation. We made use of data from 9 rat studies from our labs, 8 published elsewhere in 2008–2017, and one unpublished study. Echocardiography, histological, and immunohistochemical parameters were collected from these studies. Using mixed effects analysis of covariance models, we estimated slopes for heart rate and bodyweight and estimated the radiation effect on each of the parameters. Bodyweight was related to most echocardiography parameters, and heart rate had an effect on echocardiography parameters related to the diameter of the left ventricle. For some parameters, there was evidence that heart rate and bodyweight relationships with the parameter depended on whether the rats were irradiated. Radiation effects were found in systolic measures of echocardiography parameters related to the diameter of the left ventricle, with ejection fraction and fractional shortening, with atrial wall thickness, and with histological measures of capillary density, collagen deposition, and mast cells infiltration in the heart. Accounting for bodyweight, as well as heart rate, in analyses of echocardiography parameters should reduce variability in estimated radiation effects. Several echocardiography and histological parameters were particularly susceptible to whole heart irradiation, showing robust effects compared to sham-irradiation. Lastly, we provide an example approach for a sample size calculation that will contribute to a rigorous study design and reproducibility in experiments studying radiation modifiers. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to quantify the effects of a 4‐week, supervised, high‐intensity interval training (HIIT) on intrahepatic triglyceride content (IHTG, percentage), cardiorespiratory fitness (CRF), and cardiometabolic markers in adolescents with obesity. Methods: A total of 40 adolescents (age 13–18 y, BMI 36.7 ± 5.8 kg/m2) at risk for metabolic dysfunction‐associated steatotic liver disease (MASLD) based on obesity and elevated Fibroscan measured controlled attenuation parameter (CAP) scores were randomized to HIIT three times a week for 4 weeks (n = 34) or observation (control; n = 6). Liver magnetic resonance imaging proton‐density fat‐fraction (MRI‐PDFF), CAP, oral glucose tolerance test, serum alanine aminotransferase, dual‐energy x‐ray absorptiometry, and CRF tests were performed before and after intervention. Within‐ and between‐group differences were compared. Results: A total of 13 (38%) and 4 (66%) children had MASLD by MRI‐PDFF (IHTG ≥ 5%) in the HIIT and control groups, respectively. The implemented HIIT protocol had no impact on CRF or IHTG (baseline 5.26%, Δ = −0.31 percentage points, 95% CI: −0.77 to 0.15; p = 0.179), but it decreased the 2‐h glucose concentration (baseline 116 mg/dL, Δ = −11 mg/dL; 95% CI: −17.6 to −5.5; p < 0.001). When limiting the analysis to participants with MASLD (n = 17), HIIT decreased IHTG (baseline 8.81%, Δ = −1.05 percentage points, 95% CI: −2.08 to −0.01; p = 0.048). Between‐group comparisons were not different. Conclusions: The implemented exercise protocol did not reduce IHTG, but it led to modest improvement in markers of cardiometabolic health. [ABSTRACT FROM AUTHOR]

Historically, animal numbers have most often been in the hundreds for experiments designed to estimate the dose reduction factor (DRF) of a radiation countermeasure treatment compared to a control treatment. Before 2010, researchers had to rely on previous experience, both from others and their own, to determine the number of animals needed for a DRF experiment. In 2010, a formal sample size formula was developed by Kodell et al. This theoretical work showed that sample sizes for realistic, yet hypothetical, DRF experiments could be less than a hundred animals and still have sufficient power to detect clinically meaningful DRF values. However, researchers have been slow to use the formula for their DRF experiments, whether from ignorance to its existence or hesitancy to depart from "tried and true" sample sizes. Here, we adapt the sample size formula to better fit usual DRF experiments, and, importantly, we provide real experimental evidence from two independent DRF experiments that sample sizes smaller than what have typically been used can still statistically detect clinically meaningful DRF values. In addition, we update a literature review of DRF experiments which can be used to inform future DRF experiments, provide answers to questions that researchers have asked when considering sample size calculations rather than solely relying on previous experience, whether their own or others', and, in the supplementary material, provide R code implementing the formula, along with several exercises to familiarize the user with the adapted formula. [ABSTRACT FROM AUTHOR]