The urologic epithelial stem cell database (UESC) – a web tool for cell type-specific gene expression and immunohistochemistry images of the prostate and bladder

Background: Public databases are crucial for analysis of high-dimensional gene and protein expression data. The Urologic Epithelial Stem Cells (UESC) database http://scgap.systemsbiology.net/ is a public database that contains gene and protein information for the major cell types of the prostate, prostate cancer cell lines, and a cancer cell type isolated from a primary tumor. Similarly, such information is available for urinary bladder cell types. Description: Two major data types were archived in the database, protein abundance localization data from immunohistochemistry images, and transcript abundance data principally from DNA microarray analysis. Data results were organized in modules that were made to operate independently but built upon a core functionality. Gene array data and immunostaining images for human and mouse prostate and bladder were made available for interrogation. Data analysis capabilities include: (1) CD (cluster designation) cell surface protein data. For each cluster designation molecule, a data summary allows easy retrieval of images (at multiple magnifications). (2) Microarray data. Single gene or batch search can be initiated with Affymetrix Probeset ID, Gene Name, or Accession Number together with options of coalescing probesets and/or replicates. Conclusion: Databases are invaluable for biomedical research, and their utility depends on data quality and user friendliness. UESC provides for database queries and tools to examine cell typespecific gene expression (normal vs. cancer), whereas most other databases contain only whole tissue expression datasets. The UESC database provides a valuable tool in the analysis of differential gene expression in prostate cancer genes in cancer progression.This work was supported by grant 1U01 DK63630 from NIDDK. Additional funding came from grants CA85859, CA98699 and CA111244 from NCI

A Taxonomy of Explainable Bayesian Networks

Artificial Intelligence (AI), and in particular, the explainability thereof, has gained phenomenal attention over the last few years. Whilst we usually do not question the decision-making process of these systems in situations where only the outcome is of interest, we do however pay close attention when these systems are applied in areas where the decisions directly influence the lives of humans. It is especially noisy and uncertain observations close to the decision boundary which results in predictions which cannot necessarily be explained that may foster mistrust among end-users. This drew attention to AI methods for which the outcomes can be explained. Bayesian networks are probabilistic graphical models that can be used as a tool to manage uncertainty. The probabilistic framework of a Bayesian network allows for explainability in the model, reasoning and evidence. The use of these methods is mostly ad hoc and not as well organised as explainability methods in the wider AI research field. As such, we introduce a taxonomy of explainability in Bayesian networks. We extend the existing categorisation of explainability in the model, reasoning or evidence to include explanation of decisions. The explanations obtained from the explainability methods are illustrated by means of a simple medical diagnostic scenario. The taxonomy introduced in this paper has the potential not only to encourage end-users to efficiently communicate outcomes obtained, but also support their understanding of how and, more importantly, why certain predictions were made

Imaging of hydrothermal altered zones in Wadi Al-Bana, in southern Yemen, using remote sensing techniques and very low frequency–electromagnetic data

© 2019, Saudi Society for Geosciences. Economic mineralization and hydrothermally altered zones are areas of great economic interests. This study focusses on hydrothermal altered zones of high mineralization potentials in Wadi Al-Bana, in southern Yemen. An azimuthal very low frequency–electromagnetic (AVLF-EM) data acquisition was conducted in search for mineralization in the study area. The study integrated observations from geophysical field data with others extracted from object-oriented principal component analysis (PCA) to better map and understand mineralization in the investigated area. This technique was applied to two data sets, ASTER and Landsat 8 Operational Land Imager (OLI) imagery. The results of PCA revealed high accuracy in detecting alteration minerals and for mapping zones of high concentration of these minerals. The PCA-based distribution of selected alteration zones correlated spatially with high conductivity anomalies in the subsurface that were detected by VLF measurements. Finally, a GIS model was built and successfully utilized to categorize the resulted altered zones, into three levels. [Figure not available: see fulltext.]

The complement cascade as a mediator of tissue growth and regeneration

Recent evidence has demonstrated that the complement cascade is involved in a variety of physiologic and pathophysiologic processes in addition to its role as an immune effector. Research in a variety of organ systems has shown that complement proteins are direct participants in maintenance of cellular turnover, healing, proliferation and regeneration. As a physiologic housekeeper, complement proteins maintain tissue integrity in the absence of inflammation by disposing of cellular debris and waste, a process critical to the prevention of autoimmune disease. Developmentally, complement proteins influence pathways including hematopoietic stem cell engraftment, bone growth, and angiogenesis. They also provide a potent stimulus for cellular proliferation including regeneration of the limb and eye in animal models, and liver proliferation following injury. Here, we describe the complement cascade as a mediator of tissue growth and regeneration

Synthesis and propagation of complement C3 by microglia/monocytes in the aging retina

INTRODUCTION Complement activation is thought to contribute to the pathogenesis of age-related macular degeneration (AMD), which may be mediated in part by para-inflammatory processes. We aimed to investigate the expression and localization of C3, a crucial component of the complement system, in the retina during the course of aging. METHODS SD rats were born and reared in low-light conditions, and euthanized at post-natal (P) days 100, 450, or 750. Expression of C3, IBA1, and Ccl- and Cxcl- chemokines was assessed by qPCR, and in situ hybridization. Thickness of the ONL was assessed in retinal sections as a measure of photoreceptor loss, and counts were made of C3-expressing monocytes. RESULTS C3 expression increased significantly at P750, and correlated with thinning of the ONL, at P750, and up-regulation of GFAP. In situ hybridization showed that C3 was expressed by microglia/monocytes, mainly from within the retinal vasculature, and occasionally the ONL. The number of C3-expressing microglia increased significantly by P750, and coincided spatiotemporally with thinning of the ONL, and up-regulation of Ccl- and Cxcl- chemokines. CONCLUSIONS Our data suggest that recruited microglia/monocytes contribute to activation of complement in the aging retina, through local expression of C3 mRNA. C3 expression coincides with age-related thinning of the ONL at P750, although it is unclear whether the C3-expressing monocytes are a cause or consequence. These findings provide evidence of activation of complement during natural aging, and may have relevance to cellular events underling the pathogenesis of age-related retinal diseases.Funding provided by Australian Research Council Centres of Excellence Program Grant (CE0561903)

670-nm light treatment reduces complement propagation following retinal degeneration

AIM: Complement activation is associated with the pathogenesis of age-related macular degeneration (AMD). We aimed to investigate whether 670-nm light treatment reduces the propagation of complement in a light-induced model of atrophic AMD. METHODS: Sprague–Dawley (SD) rats were pretreated with 9 J/cm(2) 670-nm light for 3 minutes daily over 5 days; other animals were sham treated. Animals were exposed to white light (1,000 lux) for 24 h, after which animals were kept in dim light (5 lux) for 7 days. Expression of complement genes was assessed by quantitative polymerase chain reaction (qPCR), and immunohistochemistry. Counts were made of C3-expressing monocytes/microglia using in situ hybridization. Photoreceptor death was also assessed using outer nuclear layer (ONL) thickness measurements, and oxidative stress using immunohistochemistry for 4-hydroxynonenal (4-HNE). RESULTS: Following light damage, retinas pretreated with 670-nm light had reduced immunoreactivity for the oxidative damage maker 4-HNE in the ONL and outer segments, compared to controls. In conjunction, there was significant reduction in retinal expression of complement genes C1s, C2, C3, C4b, C3aR1, and C5r1 following 670 nm treatment. In situ hybridization, coupled with immunoreactivity for the marker ionized calcium binding adaptor molecule 1 (IBA1), revealed that C3 is expressed by infiltrating microglia/monocytes in subretinal space following light damage, which were significantly reduced in number after 670 nm treatment. Additionally, immunohistochemistry for C3 revealed a decrease in C3 deposition in the ONL following 670 nm treatment. CONCLUSIONS: Our data indicate that 670-nm light pretreatment reduces lipid peroxidation and complement propagation in the degenerating retina. These findings have relevance to the cellular events of complement activation underling the pathogenesis of AMD, and highlight the potential of 670-nm light as a non-invasive anti-inflammatory therapy

Fundamental role of C1q in autoimmunity and inflammation

C1q, historically viewed as the initiating component of the classical complement pathway, also exhibits a variety of complement-independent activities in both innate and acquired immunity. Recent studies focusing on C1q\u27s suppressive role in the immune system have provided new insight into how abnormal C1q expression and bioactivity may contribute to autoimmunity. In particular, molecular networks involving C1q interactions with cell surface receptors and other ligands are emerging as mechanisms involved in C1q\u27s modulation of immunity. Here, we discuss the role of C1q in controlling immune cell function, including recently elucidated mechanisms of action, and suggest how these processes are critical for maintaining tissue homeostasis under steady-state conditions and in preventing autoimmunity

GWAS and drug targets

Genome wide association studies (GWAS) have revealed a large number of links between genome variation and complex disease. Among other benefits, it is expected that these insights will lead to new therapeutic strategies, particularly the identification of new drug targets. In this paper, we evaluate the power of GWAS studies to find drug targets by examining how many existing drug targets have been directly 'rediscovered' by this technique, and the extent to which GWAS results may be leveraged by network information to discover known and new drug targets. We find that only a very small fraction of drug targets are directly detected in the relevant GWAS studies. We investigate two possible explanations for this observation. First, we find evidence of negative selection acting on drug target genes as a consequence of strong coupling with the disease phenotype, so reducing the incidence of SNPs linked to the disease. Second, we find that GWAS genes are substantially longer on average than drug targets and than all genes, suggesting there is a length related bias in GWAS results. In spite of the low direct relationship between drug targets and GWAS reported genes, we found these two sets of genes are closely coupled in the human protein network. As a consequence, machine-learning methods are able to recover known drug targets based on network context and the set of GWAS reported genes for the same disease. We show the approach is potentially useful for identifying drug repurposing opportunities. Although GWA studies do not directly identify most existing drug targets, there are several reasons to expect that new targets will nevertheless be discovered using these data. Initial results on drug repurposing studies using network analysis are encouraging and suggest directions for future development.https://doi.org/10.1186/1471-2164-15-S4-S