Sterol regulatory element binding protein-1c (SREBP1c) is a transcription factor that mediates insulin effects on hepatic gene expression. It is itself transcriptionally stimulated by insulin in hepatocytes. Here we show that SREBP-1c mRNA is expressed in adult rat skeletal muscles and that this expression is decreased by diabetes. The regulation of SREBP-1c expression was then assessed in cultures of adult muscle satellite cells. These cells form spontaneously contracting multinucleated myotubes within 7 days of culture. SREBP-1c mRNA is expressed in contracting myotubes. A 4-h treatment with 100 nmol/l insulin increases SREBP-1c expression and nuclear abundance by two-to threefold in myotubes. In cultured myotubes, insulin increases the expression of glycolytic and lipogenic enzyme genes and inhibits the 9-cis retinoic acid-induced UCP3 expression. These effects of insulin are mimicked by adenovirus-mediated expression of a transcriptionally active form of SREBP-1c. We conclude that in skeletal muscles, SREBP-1c expression is sensitive to insulin and can transduce the positive and negative actions of the hormone on specific genes and thus has a pivotal role in long-term muscle insulin sensitivity. Diabetes

Histology is the gold standard to unveil microscopic brain structures and pathological alterations in humans and animal models of disease. However, due to tedious manual interventions, quantification of histopathological markers is classically performed on a few tissue sections, thus restricting measurements to limited portions of the brain. Recently developed 3D microscopic imaging techniques have allowed in-depth study of neuroanatomy. However, quantitative methods are still lacking for whole-brain analysis of cellular and pathological markers. Here, we propose a ready-to-use, automated, and scalable method to thoroughly quantify histopathological markers in 3D in rodent whole brains. It relies on block-face photography, serial histology and 3D-HAPi (Three Dimensional Histology Analysis Pipeline), an open source image analysis software. We illustrate our method in studies involving mouse models of Alzheimer’s disease and show that it can be broadly applied to characterize animal models of brain diseases, to evaluate therapeutic interventions, to anatomically correlate cellular and pathological markers throughout the entire brain and to validate in vivo imaging techniques.

We report the preclinical characterization of two engineered botulinum neurotoxin serotype B proteins with significant therapeutic potential.

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