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Automatic correction of intensity nonuniformity (also termed as the bias correction) is an essential step in brain MR image analysis. Existing methods are typically developed for adult brain MR images based on the assumption that the image intensities within the same brain tissue are relatively uniform. However, this assumption is not valid in infant brain MR images, due to the dynamic and regionally-heterogeneous image contrast and appearance changes, which are caused by the underlying spatiotemporally-nonuniform myelination process. Therefore, it is not appropriate to directly use existing methods to correct the infant brain MR images. In this paper, we propose an end-to-end 3D adversarial bias correction network (ABCnet), tailored for direct prediction of bias fields from the input infant brain MR images for bias correction. The "ground-truth" bias fields for training our network are carefully defined by an improved N4 method, which integrates manually-corrected tissue segmentation maps as anatomical prior knowledge. The whole network is trained alternatively by minimizing generative and adversarial losses. To handle the heterogeneous intensity changes, our generative loss includes a tissue-aware local intensity uniformity term to reduce the local intensity variation in the corrected image. Besides, it also integrates two additional terms to enhance the smoothness of the estimated bias field and to improve the robustness of the proposed method, respectively. Comprehensive experiments with different sizes of training datasets have been carried out on a total of 1492 T1w and T2w MR images from neonates, infants, and adults, respectively. buy Tivantinib Both qualitative and quantitative evaluations on simulated and real datasets consistently demonstrate the superior performance of our ABCnet in both accuracy and efficiency, compared with popularly available methods.Understanding the mechanisms of protein function is indispensable for many biological applications, such as protein engineering and drug design. However, experimental annotations are sparse, and therefore, theoretical strategies are needed to fill the gap. Here, we present the latest developments in building functional subclassifications of protein superfamilies and using evolutionary conservation to detect functional determinants, for example, catalytic-, binding- and specificity-determining residues important for delineating the functional families. We also briefly review other features exploited for functional site detection and new machine learning strategies for combining multiple features.Four dogs were referred to our institution for incessant supraventricular tachycardias causing weakness; congestive heart failure was present in one dog. At admission, all dogs had a surface electrocardiogram showing a narrow QRS complex tachycardia with a ventricular rate ranging from 80 to 300 bpm, variable atrioventricular conduction ratio from 11 to 31, and positive atrial depolarizations in inferior leads (II, II, III, and aVF), with isoelectric lines between them. Three of four dogs had a dilated cardiomyopathy phenotype; one dog had a heart base tumor involving the cranial vena cava wall. According to the electrocardiographic findings, a presumptive diagnosis of reverse typical or atypical atrial flutter was considered, and endocardial mapping was planned for each dog. During the electrophysiologic study, continuous atrial activation compatible with atypical atrial flutter was observed in all dogs, with concealed entrainment obtained at the level of the isthmus located at the distal portion of the cranial vena cava, close to the entrance into the right atrium. A linear radiofrequency catheter ablation was performed from the right atrial wall to the distal part of the cranial vena cava with a permanent interruption of the isthmic conduction in all dogs at a 6-month follow-up.Cellular identity and physiologic function in mammary epithelial cells and in many breast cancers flow from the action of a network of master transcriptional regulators including estrogen receptor alpha, GATA3, and FOXA1. The last decade has seen the completion of multiple large sequencing projects focusing on breast cancer. These massive compendia of sequence data have provided a wealth of new information linking mutation in these transcription factors to alterations in tumor biology and transcriptional program. The emerging details on mutation in cancer, and direct experimental exploration of hypotheses based on it, are now providing a wealth of new information on the roles played by estrogen receptor alpha, GATA3, and FOXA1 in regulating gene transcription and how their combined action contributes to a network shaping cell function in both physiologic and disease states.Silicon (Si), a quasi-essential element for plants, is abundant in the soil typically as insoluble silicate forms. However, plants can uptake Si only in the soluble form of monosilicic acid. Production of monosilicic acid by rock-weathering mostly depends on temperature, pH, redox-potential, water-content, and microbial activities. In the present review, approaches involved in the efficient exploration of silicate solubilizing bacteria (SSB), its potential applications, and available technological advances are discussed. Present understanding of Si uptake, deposition, and subsequent benefits to plants has also been discussed. In agricultural soils, pH is found to be one of the most critical factors deciding silicate solubilization and the formation of different Si compounds. Numerous studies have predicted the role of Indole-3-Acetic Acid (IAA) and organic acids produced by SSB in silicate solubilization. In this regard, approaches for the isolation and characterization of SSB, quantification of IAA, and subsequent Si solubilization mechanisms are addressed. Phylogenetic evaluation of previously reported SSB showed a highly diverse origin which provides an opportunity to study different mechanisms involved in Si solubilization. Soil biochemistry in concern of silicon availability, microbial activity and silicon mediated changes in plant physiology are addressed. In addition, SSB's role in Si-biogeochemical cycling is summarized. The information presented here will be helpful to explore the potential of SSB more efficiently to promote sustainable agriculture.