Vessel-CAPTCHA: An efficient learning framework for vessel annotation and segmentation

Deep learning techniques for 3D brain vessel image segmentation have not been as successful as in the segmentation of other organs and tissues. This can be explained by two factors. First, deep learning techniques tend to show poor performances at the segmentation of relatively small objects compared to the size of the full image. Second, due to the complexity of vascular trees and the small size of vessels, it is challenging to obtain the amount of annotated training data typically needed by deep learning methods. To address these problems, we propose a novel annotation-efficient deep learning vessel segmentation framework. The framework avoids pixel-wise annotations, only requiring weak patch-level labels to discriminate between vessel and non-vessel 2D patches in the training set, in a setup similar to the CAPTCHAs used to differentiate humans from bots in web applications. The user-provided weak annotations are used for two tasks: (1) to synthesize pixel-wise pseudo-labels for vessels and background in each patch, which are used to train a segmentation network, and (2) to train a classifier network. The classifier network allows to generate additional weak patch labels, further reducing the annotation burden, and it acts as a second opinion for poor quality images. We use this framework for the segmentation of the cerebrovascular tree in Time-of-Flight angiography (TOF) and Susceptibility-Weighted Images (SWI). The results show that the framework achieves state-of-the-art accuracy, while reducing the annotation time by 77% w.r.t. learning-based segmentation methods using pixel-wise labels for training

Identifying Human Kinase-Specific Protein Phosphorylation Sites by Integrating Heterogeneous Information from Various Sources

Phosphorylation is an important type of protein post-translational modification. Identification of possible phosphorylation sites of a protein is important for understanding its functions. Unbiased screening for phosphorylation sites by in vitro or in vivo experiments is time consuming and expensive; in silico prediction can provide functional candidates and help narrow down the experimental efforts. Most of the existing prediction algorithms take only the polypeptide sequence around the phosphorylation sites into consideration. However, protein phosphorylation is a very complex biological process in vivo. The polypeptide sequences around the potential sites are not sufficient to determine the phosphorylation status of those residues. In the current work, we integrated various data sources such as protein functional domains, protein subcellular location and protein-protein interactions, along with the polypeptide sequences to predict protein phosphorylation sites. The heterogeneous information significantly boosted the prediction accuracy for some kinase families. To demonstrate potential application of our method, we scanned a set of human proteins and predicted putative phosphorylation sites for Cyclin-dependent kinases, Casein kinase 2, Glycogen synthase kinase 3, Mitogen-activated protein kinases, protein kinase A, and protein kinase C families (avaiable at http://cmbi.bjmu.edu.cn/huphospho). The predicted phosphorylation sites can serve as candidates for further experimental validation. Our strategy may also be applicable for the in silico identification of other post-translational modification substrates

MicroRNAs Dynamically Remodel Gastrointestinal Smooth Muscle Cells

Smooth muscle cells (SMCs) express a unique set of microRNAs (miRNAs) which regulate and maintain the differentiation state of SMCs. The goal of this study was to investigate the role of miRNAs during the development of gastrointestinal (GI) SMCs in a transgenic animal model. We generated SMC-specific Dicer null animals that express the reporter, green fluorescence protein, in a SMC-specific manner. SMC-specific knockout of Dicer prevented SMC miRNA biogenesis, causing dramatic changes in phenotype, function, and global gene expression in SMCs: the mutant mice developed severe dilation of the intestinal tract associated with the thinning and destruction of the smooth muscle (SM) layers; contractile motility in the mutant intestine was dramatically decreased; and SM contractile genes and transcriptional regulators were extensively down-regulated in the mutant SMCs. Profiling and bioinformatic analyses showed that SMC phenotype is regulated by a complex network of positive and negative feedback by SMC miRNAs, serum response factor (SRF), and other transcriptional factors. Taken together, our data suggest that SMC miRNAs are required for the development and survival of SMCs in the GI tract

Role of monocarboxylate transporters in human cancers : state of the art

Monocarboxylate transporters (MCTs) belong to the SLC16 gene family, presently composed by 14 members. MCT1-MCT4 are proton symporters, which mediate the transmembrane transport of pyruvate, lactate and ketone bodies. The role of MCTs in cell homeostasis has been characterized in detail in normal tissues, however, their role in cancer is still far from understood. Most solid tumors are known to rely on glycolysis for energy production and this activity leads to production of important amounts of lactate, which are exported into the extracellular milieu, contributing to the acidic microenvironment. In this context, MCTs will play a dual role in the maintenance of the hyper-glycolytic acidresistant phenotype of cancer, allowing the maintenance of the high glycolytic rates by performing lactate efflux, and pH regulation by the co-transport of protons. Thus, they constitute attractive targets for cancer therapy, which have been little explored. Here we review the literature on the role of MCTs in solid tumors in different locations, such as colon, central nervous system, breast, lung, gynecologic tract, prostate, stomach, however, there are many conflicting results and in most cases there are no functional studies showing the dependence of the tumors on MCT expression and activity. Additional studies on MCT expression in other tumor types, confirmation of the results already published as well as additional functional studies are needed to deeply understand the role of MCTs in cancer maintenance and aggressiveness

Epithelial cancers in the post-genomic era: should we reconsider our lifestyle?

The age-related epithelial cancers of the breast, colorectum and prostate are the most prevalent and are increasing in our aging populations. Epithelial cells turnover rapidly and mutations naturally accumulate throughout life. Most epithelial cancers arise from this normal mutation rate. All elderly individuals will harbour many cells with the requisite mutations and most will develop occult neoplastic lesions. Although essential for initiation, these mutations are not sufficient for the progression of cancer to a life-threatening disease. This progression appears to be dependent on context: the tissue ecosystem within individuals and lifestyle exposures across populations of individuals. Together, this implies that the seeds may be plentiful but they only germinate in the right soil. The incidence of these cancers is much lower in Eastern countries but is increasing with Westernisation and increases more acutely in migrants to the West. A Western lifestyle is strongly associated with perturbed metabolism, as evidenced by the epidemics of obesity and diabetes: this may also provide the setting enabling the progression of epithelial cancers. Epidemiology has indicated that metabolic biomarkers are prospectively associated with cancer incidence and prognosis. Furthermore, within cancer research, there has been a rediscovery that a switch in cell metabolism is critical for cancer progression but this is set within the metabolic status of the host. The seed may only germinate if the soil is fertile. This perspective brings together the different avenues of investigation implicating the role that metabolism may play within the context of post-genomic concepts of cancer