Do images of a personalised future body shape help with weight loss? A randomised controlled study

Background: This randomised controlled study evaluated a computer-generated future self-image as a personalised, visual motivational tool for weight loss in adults. Methods: One hundred and forty-five people (age 18–79 years) with a Body Mass Index (BMI) of at least 25 kg/m2 were randomised to receive a hard copy future self-image at recruitment (early image) or after 8 weeks (delayed image). Participants received general healthy lifestyle information at recruitment and were weighed at 4-weekly intervals for 24 weeks. The image was created using an iPad app called ‘Future Me’. A second randomisation at 16 weeks allocated either an additional future self-image or no additional image. Results: Seventy-four participants were allocated to receive their image at commencement, and 71 to the delayed-image group. Regarding to weight loss, the delayed-image group did consistently better in all analyses. Twenty-four recruits were deemed non-starters, comprising 15 (21%) in the delayed-image group and 9 (12%) in the early-image group (χ2(1) = 2.1, p = 0.15). At 24 weeks there was a significant change in weight overall (p \u3c 0.0001), and a difference in rate of change between groups (delayed-image group: −0.60 kg, early-image group: −0.42 kg, p = 0.01). Men lost weight faster than women. The group into which participants were allocated at week 16 (second image or not) appeared not to influence the outcome (p = 0.31). Analysis of all completers and withdrawals showed a strong trend over time (p \u3c 0.0001), and a difference in rate of change between groups (delayed-image: −0.50 kg, early-image: −0. 27 kg, p = 0.0008). Conclusion: One in five participants in the delayed-image group completing the 24-week intervention achieved a clinically significant weight loss, having received only future self-images and general lifestyle advice. Timing the provision of future self-images appears to be significant, and promising for future research to clarify their efficacy. Trial Registration: Australian Clinical Trials Registry, identifier: ACTRN12613000883718. Registered on 8 August 2013

Chicken Pleiotrophin: Regulation of Tissue Specific Expression by Estrogen in the Oviduct and Distinct Expression Pattern in the Ovarian Carcinomas

Pleiotrophin (PTN) is a developmentally-regulated growth factor which is widely distributed in various tissues and also detected in many kinds of carcinomas. However, little is known about the PTN gene in chickens. In the present study, we found chicken PTN to be highly conserved with respect to mammalian PTN genes (91–92.6%) and its mRNA was most abundant in brain, heart and oviduct. This study focused on the PTN gene in the oviduct where it was detected in the glandular (GE) and luminal (LE) epithelial cells. Treatment of young chicks with diethylstilbesterol induced PTN mRNA and protein in GE and LE, but not in other cell types of the oviduct. Further, several microRNAs, specifically miR-499 and miR-1709 were discovered to influence PTN expression via its 3′-UTR which suggests that post-transcriptional regulation influences PTN expression in chickens. We also compared expression patterns and CpG methylation status of the PTN gene in normal and cancerous ovaries from chickens. Our results indicated that PTN is most abundant in the GE of adenocarcinoma of cancerous, but not normal ovaries of hens. Bisulfite sequencing revealed that 30- and 40% of −1311 and −1339 CpG sites are demethylated in ovarian cancer cells, respectively. Collectively, these results indicate that chicken PTN is a novel estrogen-induced gene expressed mainly in the oviductal epithelia implicating PTN regulation of oviduct development and egg formation, and also suggest that PTN is a biomarker for epithelial ovarian carcinoma that could be used for diagnosis and monitoring effects of therapies for the disease

Mobile health apps to facilitate self-care: a qualitative study of user experiences

Objective: Consumers are living longer, creating more pressure on the health system and increasing their requirement for self-care of chronic conditions. Despite rapidly-increasing numbers of mobile health applications (‘apps’) for consumers’ self-care, there is a paucity of research into consumer engagement with electronic self-monitoring. This paper presents a qualitative exploration of how health consumers use apps for health monitoring, their perceived benefits from use of health apps, and suggestions for improvement of health apps. Materials and Methods: ‘Health app’ was defined as any commercially-available health or fitness app with capacity for self-monitoring. English-speaking consumers aged 18 years and older using any health app for self-monitoring were recruited for interview from the metropolitan area of Perth, Australia. The semi-structured interview guide comprised questions based on the Technology Acceptance Model, Health Information Technology Acceptance Model, and the Mobile Application Rating Scale, and is the only study to do so. These models also facilitated deductive thematic analysis of interview transcripts. Implicit and explicit responses not aligned to these models were analyzed inductively.Results: Twenty-two consumers (15 female, seven male) participated, 13 of whom were aged 26–35 years. Eighteen participants reported on apps used on iPhones. Apps were used to monitor diabetes, asthma, depression, celiac disease, blood pressure, chronic migraine, pain management, menstrual cycle irregularity, and fitness. Most were used approximately weekly for several minutes per session, and prior to meeting initial milestones, with significantly decreased usage thereafter. Deductive and inductive thematic analysis reduced the data to four dominant themes: engagement in use of the app; technical functionality of the app; ease of use and design features; and management of consumers’ data. Conclusions: The semi-structured interviews provided insight into usage, benefits and challenges of health monitoring using apps. Understanding the range of consumer experiences and expectations can inform design of health apps to encourage persistence in self-monitoring

Deconvolution of complex G protein–coupled receptor signaling in live cells using dynamic mass redistribution measurements

Label-free biosensor technology based on dynamic mass redistribution (DMR) of cellular constituents promises to translate GPCR signaling into complex optical 'fingerprints' in real time in living cells. Here we present a strategy to map cellular mechanisms that define label-free responses, and we compare DMR technology with traditional second-messenger assays that are currently the state of the art in GPCR drug discovery. The holistic nature of DMR measurements enabled us to (i) probe GPCR functionality along all four G-protein signaling pathways, something presently beyond reach of most other assay platforms; (ii) dissect complex GPCR signaling patterns even in primary human cells with unprecedented accuracy; (iii) define heterotrimeric G proteins as triggers for the complex optical fingerprints; and (iv) disclose previously undetected features of GPCR behavior. Our results suggest that DMR technology will have a substantial impact on systems biology and systems pharmacology as well as for the discovery of drugs with novel mechanisms

The specific inherent optical properties of three sub-tropical and tropical water reservoirs in Queensland, Australia

The underwater light climate, which is a major influence on the ecology of aquatic systems, is affected by the absorption and scattering processes that take place within the water column. Knowledge of the Specific Inherent Optical Properties (SIOPs) of water quality parameters and their spatial variation is essential for the modelling of underwater light fields and remote sensing applications. We measured the SIOPs and water quality parameter concentrations of three large inland water impoundments in Queensland, Australia. The measurements ranged from 0.9–42.7 μgl/1 for chlorophyll a concentration, 0.9–170.4 mgl/1 for tripton concentration, 0.36–1.59 m/1 for aCDOM(440) and 0.15–2.5 m for Secchi depth. The SIOP measurements showed that there is sufficient intra-impoundment variation in the specific absorption and specific scattering of phytoplankton and tripton to require a well distributed network of measurement stations to fully characterise the SIOPs of the optical water quality parameters. While significantly different SIOP sets were measured for each of the study sites the measurements were consistent with published values in other inland waters. The multiple measurement stations were allocated into optical domains as a necessary step to parameterise a semi-analytical inversion remote sensing algorithm. This paper also addresses the paucity of published global inland water SIOP sets by contributing Australian SIOP sets to allow international and national comparison