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The role of the autonomic nervous system in obesity and insulin-resistant conditions has been largely explored. However, the exact mechanisms involved in this relation have not been completely elucidated yet, since most of these mechanisms display a bi-directional effect. Insulin-resistance, for instance, can be caused by sympathetic activation, but, in turn, the associated hyperinsulinemia can activate the sympathetic branch of the autonomic nervous system. The picture is made even more complex by the implicated neural, hormonal and nutritional mechanisms. Among them, leptin plays a pivotal role, being involved not only in appetite regulation and glucose homeostasis but also in energy expenditure. The purpose of this review is to offer a comprehensive view of the complex interplay between leptin and the central nervous system, providing further insights on the impact of autonomic nervous system balance on adipose tissue and insulin-resistance. Furthermore, the link between the circadian clock and leptin and its effect on metabolism and energy balance will be evaluated.

The advanced and performing technologies of glucose monitoring systems provide a large amount of glucose data that needs to be properly read and interpreted by the diabetology team in order to make therapeutic decisions as close as possible to the patient’s metabolic needs. For this purpose, new parameters have been developed, to allow a more integrated reading and interpretation of data by clinical professionals. The new challenge for the diabetes community consists of promoting an integrated and homogeneous reading, as well as interpretation of glucose monitoring data also by the patient himself. The purpose of this review is to offer an overview of the glycemic status assessment, opened by the current data management provided by latest glucose monitoring technologies. Furthermore, the applicability and personalization of the different glycemic monitoring devices used in specific insulin-treated diabetes mellitus patient populations will be evaluated.

Insulin-resistance is one of the main factors responsible for the onset and progression of Metabolic Syndrome (MetS). Among all polyphenols, the effects of flavonoids and their main food sources on insulin sensitivity have been widely evaluated in molecular and clinical studies. The aim of this review is to analyse the data observed in vitro, in vivo and in clinical trials concerning the effects of flavonoids on insulin resistance and to determine the molecular mechanisms with which flavonoids interact with insulin signaling.

Purpose. The purpose of our study is to describe the in vivo corneal confocal microscopy characteristics of subbasal nerve plexus in a highly selected population of patients affected by type 1 diabetes mellitus (T1DM) without any microvascular diabetes complications.Methods. We included 19 T1DM patients without diabetic peripheral neuropathy, diabetic autonomic neuropathy, diabetic retinopathy, and microalbuminuria. All patients underwent in vivo corneal confocal microscopy and blood analysis to determine subbasal nerve plexus parameters and their correlation with clinical data. We compared the results with 19 healthy controls.Results. The T1DM group showed a significant decrease of the nerve fiber length (P=0.032), the nerve fiber length density (P=0.034), the number of fibers (P=0.005), and the number of branchings (P=0.028), compared to healthy subjects. The nerve fiber length, nerve fiber length density, and number of fibers were directly related to the age at onset of diabetes and inversely to the duration of DM. BMI (body mass index) was highly related to the nerve fiber length (r = −0.6,P=0.007), to the nerve fiber length density (r = −0.6,P=0.007), and to the number of fibers (r = −0.587,P=0.008). No significant correlations were found between the corneal parameters and HbA1c.Conclusions. Early subclinical fiber corneal variation could be easily detected using in vivo corneal confocal microscopy, even in type 1 diabetes without any microvascular diabetes complications, including diabetic peripheral neuropathy, diabetic autonomic neuropathy, diabetic retinopathy, and microalbuminuria.