Ruptured Internal Iliac Artery Aneurysm: Staged Emergency Endovascular Treatment in the Interventional Radiology Suite

Ruptured aneurysms of the internal iliac artery (IIA) are rare and challenging to treat surgically. Due to their anatomic location they are difficult to operate on and perioperative morbidity is high. An endovascular approach can be helpful. We recently treated a patient with a ruptured IIA aneurysm in the interventional radiology suite with embolization of the side-branch of the IIA and placement of a covered stent in the ipsilateral common and external iliac arteries. A suitable stent-graft was not available initially and had to be brought in from elsewhere. An angioplasty balloon was temporarily placed across the ostium of the IIA to obtain hemostasis. Two hours later, the procedure was finished by placing the stent-graft

A Genome-Wide Comparative Evolutionary Analysis of Herpes Simplex Virus Type 1 and Varicella Zoster Virus

Herpes simplex virus type 1 (HSV-1) and varicella zoster virus (VZV) are closely related viruses causing lifelong infections. They are typically associated with mucocutaneous or skin lesions, but may also cause severe neurological or ophthalmic diseases, possibly due to viral- and/or host-genetic factors. Although these viruses are well characterized, genome-wide evolutionary studies have hitherto only been presented for VZV. Here, we present a genome-wide study on HSV-1. We also compared the evolutionary characteristics of HSV-1 with those for VZV. We demonstrate that, in contrast to VZV for which only a few ancient recombination events have been suggested, all HSV-1 genomes contain mosaic patterns of segments with different evolutionary origins. Thus, recombination seems to occur extremely frequent for HSV-1. We conclude by proposing a timescale for HSV-1 evolution, and by discussing putative underlying mechanisms for why these otherwise biologically similar viruses have such striking evolutionary differences

The Molecular Chaperone Hsp90α Is Required for Meiotic Progression of Spermatocytes beyond Pachytene in the Mouse

The molecular chaperone Hsp90 has been found to be essential for viability in all tested eukaryotes, from the budding yeast to Drosophila. In mammals, two genes encode the two highly similar and functionally largely redundant isoforms Hsp90α and Hsp90β. Although they are co-expressed in most if not all cells, their relative levels vary between tissues and during development. Since mouse embryos lacking Hsp90β die at implantation, and despite the fact that Hsp90 inhibitors being tested as anti-cancer agents are relatively well tolerated, the organismic functions of Hsp90 in mammals remain largely unknown. We have generated mouse lines carrying gene trap insertions in the Hsp90α gene to investigate the global functions of this isoform. Surprisingly, mice without Hsp90α are apparently normal, with one major exception. Mutant male mice, whose Hsp90β levels are unchanged, are sterile because of a complete failure to produce sperm. While the development of the male reproductive system appears to be normal, spermatogenesis arrests specifically at the pachytene stage of meiosis I. Over time, the number of spermatocytes and the levels of the meiotic regulators and Hsp90 interactors Hsp70-2, NASP and Cdc2 are reduced. We speculate that Hsp90α may be required to maintain and to activate these regulators and/or to disassemble the synaptonemal complex that holds homologous chromosomes together. The link between fertility and Hsp90 is further supported by our finding that an Hsp90 inhibitor that can cross the blood-testis barrier can partially phenocopy the genetic defects

Differential expression of HSPA1 and HSPA2 proteins in human tissues; tissue microarray-based immunohistochemical study

In the present study we determined the expression pattern of HSPA1 and HSPA2 proteins in various normal human tissues by tissue-microarray based immunohistochemical analysis. Both proteins belong to the HSPA (HSP70) family of heat shock proteins. The HSPA2 is encoded by the gene originally defined as testis-specific, while HSPA1 is encoded by the stress-inducible genes (HSPA1A and HSPA1B). Our study revealed that both proteins are expressed only in some tissues from the 24 ones examined. HSPA2 was detected in adrenal gland, bronchus, cerebellum, cerebrum, colon, esophagus, kidney, skin, small intestine, stomach and testis, but not in adipose tissue, bladder, breast, cardiac muscle, diaphragm, liver, lung, lymph node, pancreas, prostate, skeletal muscle, spleen, thyroid. Expression of HSPA1 was detected in adrenal gland, bladder, breast, bronchus, cardiac muscle, esophagus, kidney, prostate, skin, but not in other tissues examined. Moreover, HSPA2 and HSPA1 proteins were found to be expressed in a cell-type-specific manner. The most pronounced cell-type expression pattern was found for HSPA2 protein. In the case of stratified squamous epithelia of the skin and esophagus, as well as in ciliated pseudostratified columnar epithelium lining respiratory tract, the HSPA2 positive cells were located in the basal layer. In the colon, small intestine and bronchus epithelia HSPA2 was detected in goblet cells. In adrenal gland cortex HSPA2 expression was limited to cells of zona reticularis. The presented results clearly show that certain human tissues constitutively express varying levels of HSPA1 and HSPA2 proteins in a highly differentiated way. Thus, our study can help designing experimental models suitable for cell- and tissue-type-specific functional differences between HSPA2 and HSPA1 proteins in human tissues

Unexpected Role of α-Fetoprotein in Spermatogenesis

BACKGROUND: Heat shock severely affects sperm production (spermatogenesis) and results in a rapid loss of haploid germ cells, or in other words, sperm formation (spermiogenesis) is inhibited. However, the mechanisms behind the effects of heat shock on spermatogenesis are obscure. METHODOLOGY/PRINCIPAL FINDINGS: To identify the inhibitory factor of spermiogenesis, experimental cryptorchid (EC) mice were used in this study. Here we show that α-fetoprotein (AFP) is specifically expressed in the testes of EC mice by proteome analysis. AFP was also specifically localized spermatocytes by immunohistochemical analysis and was secreted into the circulation system of EC mice by immunoblot analysis. Since spermatogenesis of an advanced mammal cannot be reproduced with in vitro, we performed the microinjection of AFP into the seminiferous tubules of normal mice to determine whether AFP inhibits spermiogenesis in vivo. AFP was directly responsible for the block in spermiogenesis of normal mice. To investigate whether AFP inhibits cell differentiation in other models, using EC mice we performed a partial hepatectomy (PH) that triggers a rapid regenerative response in the remnant liver tissue. We also found that liver regeneration is inhibited in EC mice with PH. The result suggests that AFP released into the blood of EC mice regulates liver regeneration by inhibiting the cell division of hepatocytes. CONCLUSIONS/SIGNIFICANCE: AFP is a well-known cancer-specific marker, but AFP has no known function in healthy human beings. Our findings indicate that AFP expressed under EC conditions plays a role as a regulatory factor in spermatogenesis and in hepatic generation

Expression of high p53 levels in colorectal cancer: a favourable prognostic factor

The expression of p53 protein was examined in a series of 111 colorectal cancer adenocarcinomas with a long follow-up. A quantitative luminometric immunoassay (LIA) was used for the measurement of wild-type and mutant p53 protein in extracts from colorectal tumour cytosols, p53 being detected in 42% of the samples (range 0.0–52 ng mg−1). Using an arbitrary cut-off value of 2.7 ng mg−1, 25% of the tumours were classified as manifesting high p53 levels. There was no association of p53 expression with patient age, sex, serum preoperative carcinoembryonic antigen (CEA) levels, tumour site and size, nodal status or TNM stage. Significant and independent correlation was found to exist between high p53 levels and prolonged disease-free survival (P = 0.05) at a median follow-up of 60 months. This survival advantage was most apparent among stage III cancer patients. The results from this study would suggest that expression of high p53 levels appear to be useful in selecting a group of colorectal cancer patients with a better prognosis. © 1999 Cancer Research Campaig

Simulating Microdosimetry in a Virtual Hepatic Lobule

The liver plays a key role in removing harmful chemicals from the body and is therefore often the first tissue to suffer potentially adverse consequences. To protect public health it is necessary to quantitatively estimate the risk of long-term low dose exposure to environmental pollutants. Animal testing is the primary tool for extrapolating human risk but it is fraught with uncertainty, necessitating novel alternative approaches. Our goal is to integrate in vitro liver experiments with agent-based cellular models to simulate a spatially extended hepatic lobule. Here we describe a graphical model of the sinusoidal network that efficiently simulates portal to centrilobular mass transfer in the hepatic lobule. We analyzed the effects of vascular topology and metabolism on the cell-level distribution following oral exposure to chemicals. The spatial distribution of metabolically inactive chemicals was similar across different vascular networks and a baseline well-mixed compartment. When chemicals were rapidly metabolized, concentration heterogeneity of the parent compound increased across the vascular network. As a result, our spatially extended lobule generated greater variability in dose-dependent cellular responses, in this case apoptosis, than were observed in the classical well-mixed liver or in a parallel tubes model. The mass-balanced graphical approach to modeling the hepatic lobule is computationally efficient for simulating long-term exposure, modular for incorporating complex cellular interactions, and flexible for dealing with evolving tissues

Application of a Mathematical Model to Describe the Effects of Chlorpyrifos on Caenorhabditis elegans Development

The nematode Caenorhabditis elegans is being assessed as an alternative model organism as part of an interagency effort to develop better means to test potentially toxic substances. As part of this effort, assays that use the COPAS Biosort flow sorting technology to record optical measurements (time of flight (TOF) and extinction (EXT)) of individual nematodes under various chemical exposure conditions are being developed. A mathematical model has been created that uses Biosort data to quantitatively and qualitatively describe C. elegans growth, and link changes in growth rates to biological events. Chlorpyrifos, an organophosphate pesticide known to cause developmental delays and malformations in mammals, was used as a model toxicant to test the applicability of the growth model for in vivo toxicological testing.L1 larval nematodes were exposed to a range of sub-lethal chlorpyrifos concentrations (0-75 microM) and measured every 12 h. In the absence of toxicant, C. elegans matured from L1s to gravid adults by 60 h. A mathematical model was used to estimate nematode size distributions at various times. Mathematical modeling of the distributions allowed the number of measured nematodes and log(EXT) and log(TOF) growth rates to be estimated. The model revealed three distinct growth phases. The points at which estimated growth rates changed (change points) were constant across the ten chlorpyrifos concentrations. Concentration response curves with respect to several model-estimated quantities (numbers of measured nematodes, mean log(TOF) and log(EXT), growth rates, and time to reach change points) showed a significant decrease in C. elegans growth with increasing chlorpyrifos concentration.Effects of chlorpyrifos on C. elegans growth and development were mathematically modeled. Statistical tests confirmed a significant concentration effect on several model endpoints. This confirmed that chlorpyrifos affects C. elegans development in a concentration dependent manner. The most noticeable effect on growth occurred during early larval stages: L2 and L3. This study supports the utility of the C. elegans growth assay and mathematical modeling in determining the effects of potentially toxic substances in an alternative model organism using high-throughput technologies

Transcriptome Profiling of Testis during Sexual Maturation Stages in Eriocheir sinensis Using Illumina Sequencing

The testis is a highly specialized tissue that plays dual roles in ensuring fertility by producing spermatozoa and hormones. Spermatogenesis is a complex process, resulting in the production of mature sperm from primordial germ cells. Significant structural and biochemical changes take place in the seminiferous epithelium of the adult testis during spermatogenesis. The gene expression pattern of testis in Chinese mitten crab (Eriocheir sinensis) has not been extensively studied, and limited genetic research has been performed on this species. The advent of high-throughput sequencing technologies enables the generation of genomic resources within a short period of time and at minimal cost. In the present study, we performed de novo transcriptome sequencing to produce a comprehensive transcript dataset for testis of E. sinensis. In two runs, we produced 25,698,778 sequencing reads corresponding with 2.31 Gb total nucleotides. These reads were assembled into 342,753 contigs or 141,861 scaffold sequences, which identified 96,311 unigenes. Based on similarity searches with known proteins, 39,995 unigenes were annotated based on having a Blast hit in the non-redundant database or ESTscan results with a cut-off E-value above 10−5. This is the first report of a mitten crab transcriptome using high-throughput sequencing technology, and all these testes transcripts can help us understand the molecular mechanisms involved in spermatogenesis and testis maturation

A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

<p>Abstract</p> <p>Background</p> <p>Bioactivity profiling using high-throughput <it>in vitro </it>assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. Supervised machine learning is a powerful approach to discover combinatorial relationships in complex <it>in vitro/in vivo </it>datasets. We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML) methods.</p> <p>Results</p> <p>The classification performance of Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), Recursive Partitioning and Regression Trees (RPART), and Support Vector Machines (SVM) in the presence and absence of filter-based feature selection was analyzed using K-way cross-validation testing and independent validation on simulated <it>in vitro </it>assay data sets with varying levels of model complexity, number of irrelevant features and measurement noise. While the prediction accuracy of all ML methods decreased as non-causal (irrelevant) features were added, some ML methods performed better than others. In the limit of using a large number of features, ANN and SVM were always in the top performing set of methods while RPART and KNN (k = 5) were always in the poorest performing set. The addition of measurement noise and irrelevant features decreased the classification accuracy of all ML methods, with LDA suffering the greatest performance degradation. LDA performance is especially sensitive to the use of feature selection. Filter-based feature selection generally improved performance, most strikingly for LDA.</p> <p>Conclusion</p> <p>We have developed a novel simulation model to evaluate machine learning methods for the analysis of data sets in which in vitro bioassay data is being used to predict in vivo chemical toxicology. From our analysis, we can recommend that several ML methods, most notably SVM and ANN, are good candidates for use in real world applications in this area.</p