The antidepressant fluoxetine acts on energy balance and leptin sensitivity via BDNF

Leptin and Brain Derived Neurotrophic Factor (BDNF) pathways are critical players in body weight homeostasis. Noninvasive treatments like environmental stimulation are able to increase response to leptin and induce BDNF expression in the brain. Emerging evidences point to the antidepressant selective serotonin reuptake inhibitor Fluoxetine (FLX) as a drug with effects similar to environmental stimulation. FLX is known to impact on body weight, with mechanisms yet to be elucidated. We herein asked whether FLX affects energy balance, the leptin system and BDNF function. Adult lean male mice chronically treated with FLX showed reduced weight gain, higher energy expenditure, increased sensitivity to acute leptin, increased hypothalamic BDNF expression, associated to changes in white adipose tissue expression typical of "brownization". In the Ntrk2tm1Ddg/J model, carrying a mutation in the BDNF receptor Tyrosine kinase B (TrkB), these effects are partially or totally reversed. Wild type obese mice treated with FLX showed reduced weight gain, increased energy output, and differently from untreated obese mice, a preserved acute response to leptin in terms of activation of the intracellular leptin transducer STAT3. In conclusion, FLX impacts on energy balance and induces leptin sensitivity and an intact TrkB function is required for these effects to take place

Face morphology: Can it tell us something about body weight and fat?

This paper proposes a method for an automatic extraction of geometric features, related to weight parameters, from 3D facial data acquired with low-cost depth scanners. The novelty of the method relies both on the processing of the 3D facial data and on the definition of the geometric features which are conceptually simple, robust against noise and pose estimation errors, computationally efficient, invariant with respect to rotation, translation, and scale changes. Experimental results show that these measurements are highly correlated with weight, BMI, and neck circumference, and well correlated with waist and hip circumference, which are markers of central obesity. Therefore the proposed method strongly supports the development of interactive, non-obtrusive systems able to provide a support for the detection of weight-related problems