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Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerging as a leading machine learning tool in computer vision and has attracted considerable attention in biomedical image analysis. In this paper, we provide a snapshot of this fast-growing field, specifically for microscopy image analysis. We briefly introduce the popular deep neural networks and summarize current deep learning achievements in various tasks, such as detection, segmentation, and classification in microscopy image analysis. In particular, we explain the architectures and the principles of convolutional neural networks, fully convolutional networks, recurrent neural networks, stacked autoencoders, and deep belief networks, and interpret their formulations or modelings for specific tasks on various microscopy images. In addition, we discuss the open challenges and the potential trends of future research in microscopy image analysis using deep learning.

The hypothalamic hormone gonadotropin-releasing hormone (GnRH) stimulates the synthesis and release of the pituitary gonadotropins. GnRH acts through a plasma membrane receptor that is a member of the G protein-coupled receptor (GPCR) family. These receptors interact with heterotrimeric G proteins to initiate downstream signaling. In this study, we have investigated which G proteins are involved in GnRH receptormediated signaling in L␤T2 pituitary gonadotrope cells. We have shown previously that GnRH activates ERK and induces the c-fos and LH␤ genes in these cells. Signaling via the G i subfamily of G proteins was excluded, as neither ERK activation nor c-Fos and LH␤ induction was impaired by treatment with pertussis toxin or a cell-permeable peptide that sequesters G␤␥-subunits. GnRH signaling was partially mimicked by adenoviral expression of a constitutively active mutant of G␣ q (Q209L) and was blocked by a cell-permeable peptide that uncouples G␣ q from GPCRs. Furthermore, chronic activation of G␣ q signaling induced a state of GnRH resistance. A cell-permeable peptide that uncouples G␣ s from receptors was also able to inhibit ERK, c-Fos, and LH␤, indicating that both G q/11 and G s proteins are involved in signaling. Consistent with this, GnRH caused GTP loading on G s and G q/11 and increased intracellular cAMP. Artificial elevation of cAMP with forskolin activated ERK and caused a partial induction of c-Fos. Finally, treatment of G␣ q (Q209L)-infected cells with forskolin enhanced the induction of c-Fos showing that the two pathways are independent and additive. Taken together, these results indicate that the GnRH receptor activates both G q and G s signaling to regulate gene expression in L␤T2 cells.The family of G protein-coupled receptors is the largest and most complex group of integral membrane proteins involved in signal transduction. These receptors can be activated by a diverse array of external stimuli, including growth factors, neurotransmitters, peptide, and protein hormones, chemokines, and other ligands. Agonist binding to a specific receptor on the cell surface causes a conformational change in the receptor that allows it to interact with its cognate G protein, stimulating guanine nucleotide exchange on the ␣-subunit of the G protein. The release of the GTP-bound ␣-subunit and ␤␥-subunits from the receptor-G protein complex initiates a broad range of intracellular signaling events, including the activation of classical effectors such as phospholipase C, adenylate cyclases, and ion channels, and regulation of the intracellular level of inositol phosphates, calcium, cyclic AMP, and other second messengers (for reviews see Refs. 1-8).Gonadotropin-releasing hormone (GnRH) 1 is a hypothalamic decapeptide, which serves as a key regulator of the reproductive system. In the pituitary, GnRH signals are transmitted via a specific cell surface receptor, which is a member of the G protein-coupled receptor superfamily. When GnRH binds to its receptor, it induces interaction of the receptor with heterot...

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This work was supported by a grant from the National Natural Science Foundation of China (81370013, 81000277 and 81300533) and Shandong Provincial Natural Science Foundation, China (ZR2013HQ002). There were no conflicts of interest.

X-linked myotubular myopathy (XLMTM) results from MTM1 gene mutations and myotubularin deficiency. Most XLMTM patients develop severe muscle weakness leading to respiratory failure and death, typically within 2 years of age. Our objective was to evaluate the efficacy and safety of systemic gene therapy in the p.N155K canine model of XLMTM by performing a dose escalation study. A recombinant adeno-associated virus serotype 8 (rAAV8) vector expressing canine myotubularin (cMTM1) under the muscle-specific desmin promoter (rAAV8-cMTM1) was administered by simple peripheral venous infusion in XLMTM dogs at 10 weeks of age, when signs of the disease are already present. A comprehensive analysis of survival, limb strength, gait, respiratory function, neurological assessment, histology, vector biodistribution, transgene expression, and immune response was performed over a 9-month study period. Results indicate that systemic gene therapy was well tolerated, prolonged lifespan, and corrected the skeletal musculature throughout the body in a dose-dependent manner, defining an efficacious dose in this large-animal model of the disease. These results support the development of gene therapy clinical trials for XLMTM.

A new conceptual method termed as suspension 3D printing is demonstrated using self‐healing hydrogel support to create macroscopic structures of liquid metal that exhibits properties indicative of a nonprintable object. The relationships between the process parameters, supporting gel concentration, and the deposited microdroplet geometry are clarified. The smaller nozzle inner diameter, lower flow rate, and higher printing speed will lead to a smaller droplets size. The gel concentration plays a significant role on patterning the droplets space. The results presented can be applied to design the target feature and further optimize the input parameters. Besides, this paper also illustrates the capability and potential application of the method in constructing 3D macrostructures and stereo electronic systems using these liquid metal droplets. Based on this strategy, it is possible to print liquid metal into sophisticated multidimensional and shape transformable functional structures ignoring the effects of fluid instability, gravity, and surface tension. Furthermore, this work can help remove the limits of materials and technical barriers to enable a wide variety of materials to be printed into arbitrary shapes. It is expected that further practices of the methodology will facilitate the advancements in multiscale droplets generation, flexible electronics, encapsulation technologies, biology and medicine, etc.

In the emerging field of molecular and cellular imaging, flexible strategies to synthesize multimodal contrast agents with targeting ligands are required. Liposomes have the ability to combine with a large variety of nanomaterials, including superparamagnetic iron oxide nanoparticles, to form magnetoliposomes (MLs). MLs can be used as highly efficient MRI contrast agents. Owing to their high flexibility, MLs can be associated with other imaging modality probes to be used as multimodal contrast agents. By using a thermosensitive lipid bilayer in the ML structure, these biocompatible systems offer many possibilities for targeting and delivering therapeutic agents for 'theragnostics', a coincident therapy and diagnosis strategy. This article deals with the fast-growing field of MLs as biomedical diagnostic tools. Different kinds of MLs, their preparation methods, as well as their surface modification with different imaging probes, are discussed. ML applications as multimodal contrast agents and in theragnostics are reviewed. Some important issues for the biomedical uses of magnetic liposomes, such as toxicity, are summarized.