Analysis of Fluorescent-Stained Lipid Droplets with 3D Reconstruction for Hepatic Steatosis Assessment.

Lipid droplets (LDs) are specialized organelles that mediate lipid storage and play a very important role in suppressing lipotoxicity and preventing dysfunction caused by free fatty acids (FAs). The liver, given its critical role in the body's fat metabolism, is persistently threatened by the intracellular accumulation of LDs in the form of both microvesicular and macrovesicular hepatic steatosis. The histologic characterization of LDs is typically based on lipid-soluble diazo dyes, such as Oil Red O (ORO) staining, but a number of disadvantages consistently hamper the use of this analysis with liver specimens. More recently, lipophilic fluorophores 493/503 have become popular for visualizing and locating LDs due to their rapid uptake and accumulation into the neutral lipid droplet core. Even though most applications are well-described in cell cultures, there is less evidence demonstrating the reliable use of lipophilic fluorophore probes as an LD imaging tool in tissue samples. Herein, we propose an optimized boron dipyrromethene (BODIPY) 493/503-based protocol for the evaluation of LDs in liver specimens from an animal model of high-fat diet (HFD)-induced hepatic steatosis. This protocol covers liver sample preparation, tissue sectioning, BODIPY 493/503 staining, image acquisition, and data analysis. We demonstrate an increased number, intensity, area ratio, and diameter of hepatic LDs upon HFD feeding. Using orthogonal projections and 3D reconstructions, it was possible to observe the full content of neutral lipids in the LD core, which appeared as nearly spherical droplets. Moreover, with the fluorophore BODIPY 493/503, we were able to distinguish microvesicles (1 µm < d ≤ 3 µm), intermediate vesicles (3 µm < d ≤ 9 µm), and macrovesicles (d > 9 µm), allowing the successful discrimination of microvesicular and macrovesicular steatosis. Overall, this BODIPY 493/503 fluorescence-based protocol is a reliable and simple tool for hepatic LD characterization and may represent a complementary approach to the classical histological protocols.

Unhealthy lifestyles, environment, well-being and health capability in rural neighbourhoods: a community-based cross-sectional study.

BACKGROUND: Non-communicable diseases are a leading cause of health loss worldwide, in part due to unhealthy lifestyles. Metabolic-based diseases are rising with an unhealthy body-mass index (BMI) in rural areas as the main risk factor in adults, which may be amplified by wider determinants of health. Changes in rural environments reflect the need of better understanding the factors affecting the self-ability for making balanced decisions. We assessed whether unhealthy lifestyles and environment in rural neighbourhoods are reflected into metabolic risks and health capability. METHODS: We conducted a community-based cross-sectional study in 15 Portuguese rural neighbourhoods to describe individuals' health functioning condition and to characterize the community environment. We followed a qualitatively driven mixed-method design to gather information about evidence-based data, lifestyles and neighbourhood satisfaction (incorporated in eVida technology), within a random sample of 270 individuals, and in-depth interviews to 107 individuals, to uncover whether environment influence the ability for improving or pursuing heath and well-being. RESULTS: Men showed to have a 75% higher probability of being overweight than women (p-value = 0.0954); and the reporting of health loss risks was higher in women (RR: 1.48; p-value = 0.122), individuals with larger waist circumference (RR: 2.21; IC: 1.19; 4.27), overweight and obesity (RR: 1.38; p-value = 0.293) and aged over 75 years (RR: 1.78; p-value = 0.235; when compared with participants under 40 years old). Metabolic risks were more associated to BMI and physical activity than diet (or sleeping habits). Overall, metabolic risk linked to BMI was higher in small villages than in municipalities. Seven dimensions, economic development, built (and natural) environment, social network, health care, demography, active lifestyles, and mobility, reflected the self-perceptions in place affecting the individual ability to make healthy choices. Qualitative data exposed asymmetries in surrounding environments among neighbourhoods and uncovered the natural environment and natural resources specifies as the main value of rural well-being. CONCLUSIONS: Metabolic risk factors reflect unhealthy lifestyles and can be associated with environment contextual-dependent circumstances. People-centred approaches highlight wider socioeconomic and (natural) environmental determinants reflecting health needs, health expectations and health capability. Our community-based program and cross-disciplinary research provides insights that may improve health-promoting changes in rural neighbourhoods.

Development of a Healthy Lifestyle Assessment Toolkit for the General Public.

The prevalence of age-related non-communicable chronic diseases has increased worldwide, being the leading causes of morbidity and death in many world regions, including in Europe. Innovative models and strategies focused on preventive care, including early identification of risk factors underlying disease onset and progression, and proper modification of lifestyle habits and behaviors, might contribute to promote quality of life, healthy living and active aging. Healthy Lifestyle Innovative Quarters for Cities and Citizens (HeaLIQs4cities) is an EIT Health-funded project aiming to engage, empower and educate citizens toward healthy lifestyles. One of the major objectives of this project was to develop a toolkit for a rapid and informal assessment of healthy lifestyles, to be used at different levels of care pathways, including in informal public environments. In this paper, we describe the methodology underlying the development of the toolkit, which resulted from the collaboration of an interdisciplinary focus group of academic experts, from medicine, sport sciences, psychology, health economics, and innovative technologies applied to health. The following eight components were included in the toolkit: (1) anthropometric assessment and cardiometabolic parameters; (2) physical activity and exercise; (3) well-being, social cohesion, and functional independence; (4) nutrition; (5) mental health; (6) smoking, drinking, and use of illicit substances; (7) sleep habits and quality; and (8) health and disease. A traffic light rating system indicating the risk score was used (low: green; moderate: yellow; and relevant: orange) for each of the 8 components, together with recommendations for the toolkit users. After completing the reduced version of the toolkit, individuals showing moderate or relevant risk in one or more of the 8 dimensions, were invited to participate in a more detailed assessment (toolkit long version), based on deeper and scientifically validated tools. The toolkit was incorporated in eVida, a web-based platform that focuses on delivering services to personalized health and well-being. The validation of the current toolkit has been applied in wide-ranging public events in three different European Regions. Large scale deployment of the toolkit is expected to profit from the Reference Site Collaborative Network of the European Innovation Partnership on Active and Healthy Aging (EIP on AHA).