Insulin resistance is associated with mitochondrial dysfunction, but the mechanism by which mitochondria inhibit insulin-stimulated glucose uptake into the cytoplasm is unclear. The mitochondrial permeability transition pore (mPTP) is a protein complex that facilitates the exchange of molecules between the mitochondrial matrix and cytoplasm, and opening of the mPTP occurs in response to physiological stressors that are associated with insulin resistance. In this study, we investigated whether mPTP opening provides a link between mitochondrial dysfunction and insulin resistance by inhibiting the mPTP gatekeeper protein cyclophilin D (CypD) in vivo and in vitro. Mice lacking CypD were protected from high fat diet-induced glucose intolerance due to increased glucose uptake in skeletal muscle. The mitochondria in CypD knockout muscle were resistant to diet-induced swelling and had improved calcium retention capacity compared to controls; however, no changes were observed in muscle oxidative damage, insulin signaling, lipotoxic lipid accumulation or mitochondrial bioenergetics. In vitro, we tested 4 models of insulin resistance that are linked to mitochondrial dysfunction in cultured skeletal muscle cells including antimycin A, C2-ceramide, ferutinin, and palmitate. In all models, we observed that pharmacological inhibition of mPTP opening with the CypD inhibitor cyclosporin A was sufficient to prevent insulin resistance at the level of insulin-stimulated GLUT4 translocation to the plasma membrane. The protective effects of mPTP inhibition on insulin sensitivity were associated with improved mitochondrial calcium retention capacity but did not involve changes in insulin signaling both in vitro and in vivo. In sum, these data place the mPTP at a critical intersection between alterations in mitochondrial function and insulin resistance in skeletal muscle.

3D single-molecule localization microscopy relies on fitting the shape of pointspread-functions (PSFs) recorded on a wide-field detector. However, optical aberrations distort those shapes, which compromise the accuracy and precision of single-molecule localization microscopy. Here we employ a computational phase retrieval based on a vectorial PSF model to quantify the spatially-variance of optical aberrations in a two-channel ultrawide-field singlemolecule localization microscope. The use of a spatially-variant PSF model enables accurate and precise emitter localization in x, y-and z-directions throughout the entire field-of-view.

Bacterial biofilm segmentation poses significant challenges due to lack of apparent structure, poor imaging resolution, limited contrast between conterminous cells and high density of cells that overlap. Although there exist bacterial segmentation algorithms in the existing art, they fail to delineate cells in dense biofilms, especially in 3D imaging scenarios in which the cells are growing and subdividing in a complex manner. A graph-based data clustering method, LCuts, is presented with the application on bacterial cell segmentation. By constructing a weighted graph with node features in locations and principal orientations, the proposed method can automatically classify and detect differently oriented aggregations of linear structures (represent by bacteria in the application). The method assists in the assessment of several facets, such as bacterium tracking, cluster growth, and mapping of migration patterns of bacterial biofilms. Quantitative and qualitative measures for 2D data demonstrate the superiority of proposed method over the state of the art. Preliminary 3D results exhibit reliable classification of the cells with 97% accuracy.