Classification of the category of diabetes is extremely important for clinicians to diagnose and select the correct treatment plan. Glycosylation, oxidation and other post-translational modifications of membrane and transmembrane proteins, as well as impairment in cholesterol homeostasis, can alter lipid density, packing, and interactions of Red blood cells (RBC) plasma membranes in type 1 and type 2 diabetes, thus varying their membrane micropolarity. This can be estimated, at a submicrometric scale, by determining the membrane relative permittivity, which is the factor by which the electric field between the charges is decreased relative to vacuum. Here, we employed a membrane micropolarity sensitive probe to monitor variations in red blood cells of healthy subjects (n=16) and patients affected by type 1 (T1DM, n=10) and type 2 diabetes mellitus (T2DM, n=24) to provide a cost-effective and supplementary indicator for diabetes classification. We find a less polar membrane microenvironment in T2DM patients, and a more polar membrane microenvironment in T1DM patients compared to control healthy patients. The differences in micropolarity are statistically significant among the three groups (p<0.01). The role of serum cholesterol pool in determining these differences was investigated, and other factors potentially altering the response of the probe were considered in view of developing a clinical assay based on RBC membrane micropolarity. These preliminary data pave the way for the development of an innovative assay which could become a tool for diagnosis and progression monitoring of type 1 and type 2 diabetes.

Background: A high level of glycosylated haemoglobin (HbA1c), which is a nonenzymatic glycosylation product, is correlated with an increased risk of developing microangiopathic complications in Diabetes Mellitus (DM). Erythrocyte membrane fluidity could provide a complementary index to monitor the development of complications since it is influenced by several hyperglycaemia-induced pathways and other independent risk factors. Materials and methods: 15 healthy controls and 33 patients with long-duration (≥20 years) type 1 Diabetes Mellitus (T1DM) were recruited. Diabetic subjects were classified into two groups: T1DM, constituted by 14 nonretinopathic patients, and

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The retinal pigment epithelium (RPE) is a densely pigmented, monostratified epithelium that provides metabolic and functional support to the outer segments of photoreceptors. Endogenous or exogenous oxidative stimuli determine a switch from physiological to pathological conditions, characterized by an increase of intracellular levels of reactive oxygen species (ROS). Accumulating evidence has elucidated that punicalagin (PUN), the major ellagitannin in pomegranate, is a potent antioxidant in several cell types. The present study aimed to investigate the protective effect of PUN on mitochondrial dysfunction associated with hydrogen peroxide (H2O2)–induced oxidative stress. For this purpose, we used a human RPE cell line (ARPE–19) exposed to H2O2 for 24 h. The effects of PUN pre–treatment (24 h) were examined on cell viability, mitochondrial ROS levels, mitochondrial membrane potential, and respiratory chain complexes, then finally on caspase–3 enzymatic activity. The results showed that supplementation with PUN: (a) significantly increased cell viability; (b) kept the mitochondrial membrane potential (ΔΨm) at healthy levels and limited ROS production; (c) preserved the activity of respiratory complexes; (d) reduced caspase–3 activity. In conclusion, due to its activity in helping mitochondrial functions, reducing oxidative stress, and subsequent induction of cellular apoptosis, PUN might be considered a useful nutraceutical agent in the treatment of oxidation–associated disorders of RPE.

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Self-monitoring of weight, diet and physical activity is a valuable component of behavioral weight loss treatment. The validation and user-friendliness of this approach is not optimal since users are selected from homogeneous pools and rely on different applications, increasing the burden and achieving partial, generic and/or unrelated information about their metabolic state. Moreover, studies establishing type, time, duration, and adherence criteria for self-monitoring are lacking. In this study, we developed a digital web-based application (ArmOnIA), which integrates dietary, anthropometric, and physical activity data and provides a personalized estimation of energy balance. Moreover, we determined type, time, duration, and adherence criteria for self-monitoring to achieve significant weight loss in a highly heterogeneous group. A single-arm, uncontrolled prospective study on self-monitored voluntary adults for 7 months was performed. Hierarchical clustering of adherence parameters yielded three behavioral approaches: high (HA), low (LA), and medium (MA) adherence. Average BMI decrease is statistically significant between LA and HA. Moreover, we defined thresholds for the minimum frequencies and duration of dietary and weight self-monitoring. This approach can provide the correct clues to empower citizens with scientific knowledge, augmenting their self-awareness with the aim of achieving long-lasting results when pursuing a healthy lifestyle.

Diabetes-induced oxidative stress leads to the onset of vascular complications, which are major causes of disability and death in diabetic patients. Among these, diabetic retinopathy (DR) often arises from functional alterations of the blood-retinal barrier (BRB) due to damaging oxidative stress reactions in lipids, proteins, and DNA. This study aimed to investigate the impact of the ω3-polyunsaturated docosahexaenoic acid (DHA) on the regulation of redox homeostasis in the human retinal pigment epithelial (RPE) cell line (ARPE-19) under hyperglycemic-like conditions. The present results show that the treatment with DHA under high-glucose conditions activated erythroid 2-related factor Nrf2, which orchestrates the activation of cellular antioxidant pathways and ultimately inhibits apoptosis. This process was accompanied by a marked increase in the expression of NADH (Nicotinamide Adenine Dinucleotide plus Hydrogen) Quinone Oxidoreductase 1 (Nqo1), which is correlated with a contextual modulation and intracellular re-organization of the NAD+/NADH redox balance. This investigation of the mechanisms underlying the impairment induced by high levels of glucose on redox homeostasis of the BRB and the subsequent recovery provided by DHA provides both a powerful indicator for the detection of RPE cell impairment as well as a potential metabolic therapeutic target for the early intervention in its treatment.

Development of predictive computational models of metabolism through mechanistic models is complex and resource demanding, and their personalization remains challenging. Data-driven models of human metabolism would constitute a reliable, fast, and continuously updating model for predictive analytics. Wearable devices, such as smart bands and impedance balances, allow the real time and remote monitoring of physiological parameters, providing for a flux of data carrying information on user metabolism. Here, we developed a data-driven model of end-user metabolism, the Personalized Metabolic Avatar (PMA), to estimate its personalized reactions to diets. PMA consists of a gated recurrent unit (GRU) deep learning model trained to forecast personalized weight variations according to macronutrient composition and daily energy balance. The model can perform simulations and evaluation of diet plans, allowing the definition of tailored goals for achieving ideal weight. This approach can provide the correct clues to empower citizens with scientific knowledge, augmenting their self-awareness with the aim to achieve long-lasting results in pursuing a healthy lifestyle.