Di-2-ethylhexyl phthalate (DEHP) exposure induces sperm quality and functional defects in mice.

Di-2-ethylhexyl phthalate (DEHP) harms mammalian testis development, yet the specific mechanism of its effect on sperm quality and function is unclear. In this study, male mice were administrated DEHP (200 mg/kg/day) via intragastric (i.g.) injection for 35 days. The sperm quality and function of DEHP-exposed mice were evaluated. DEHP exposure reduced the relative testis weight and serum testosterone levels. In addition, sperm count and motility parameters decreased significantly, which led to reduced sperm fertility characterized by reduced acrosome reaction rate, sperm-egg binding capacity and blastocyte formation. DEHP exposure decreased anti-oxidant indicators and the expressions of Cat, Sod1, Prdx6 and Sirt1 in the testis. DEHP-exposure also resulted in decreased proliferating cell nuclear antigen (PCNA) expression in mice testis, as well as the dose-dependent inhibition of the proliferation of GC-1 and GC-2 cells. These phenotypes may be related to increased cell apoptosis characterized by BAX/BCL2 and P53 up-regulation. DEHP exposure resulted in the down-regulation of SIRT1 and p-AKT in mice testis and decreased levels of GC-1and GC-2 cells. DEHP co-incubation with sperm in vitro resulted in decreased tyrosine phosphorylation and progressive motility, as well as p-AKT expression in capacitated sperm. Differential sperm proteomics identified 495 differentially expressed proteins, including 257 proteins down-regulated in the DEHP-exposure group. Bioinformatics analysis showed that proteins involved in sperm-egg interaction and fertilization processes were significantly down-regulated. Pathway analysis demonstrated that the adhesion pathway was enriched in down-regulated proteins, while the pathway associated with ribosomes was enriched in up-regulated proteins. Conclusively, DEHP exposure impaired male fertility by affecting sperm quality and function, and a pathway mediating the DEHP-induced decline in sperm quality and function was identified. The study provides additional information for understanding the molecular mechanisms of DEHP exposure and its effects on male reproduction.

Deep Learning in Microscopy Image Analysis: A Survey.

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.