Bmi1 Confers Resistance to Oxidative Stress on Hematopoietic Stem Cells

The polycomb-group (PcG) proteins function as general regulators of stem cells. We previously reported that retrovirus-mediated overexpression of Bmi1, a gene encoding a core component of polycomb repressive complex (PRC) 1, maintained self-renewing hematopoietic stem cells (HSCs) during long-term culture. However, the effects of overexpression of Bmi1 on HSCs in vivo remained to be precisely addressed.In this study, we generated a mouse line where Bmi1 can be conditionally overexpressed under the control of the endogenous Rosa26 promoter in a hematopoietic cell-specific fashion (Tie2-Cre;R26Stop(FL)Bmi1). Although overexpression of Bmi1 did not significantly affect steady state hematopoiesis, it promoted expansion of functional HSCs during ex vivo culture and efficiently protected HSCs against loss of self-renewal capacity during serial transplantation. Overexpression of Bmi1 had no effect on DNA damage response triggered by ionizing radiation. In contrast, Tie2-Cre;R26Stop(FL)Bmi1 HSCs under oxidative stress maintained a multipotent state and generally tolerated oxidative stress better than the control. Unexpectedly, overexpression of Bmi1 had no impact on the level of intracellular reactive oxygen species (ROS).Our findings demonstrate that overexpression of Bmi1 confers resistance to stresses, particularly oxidative stress, onto HSCs. This thereby enhances their regenerative capacity and suggests that Bmi1 is located downstream of ROS signaling and negatively regulated by it

Epithelial Tissues Have Varying Degrees of Susceptibility to KrasG12D-Initiated Tumorigenesis in a Mouse Model

Activating mutations in the Kras gene are commonly found in some but not all epithelial cancers. In order to understand the susceptibility of different epithelial tissues to Kras-induced tumorigenesis, we introduced one of the most common Kras mutations, KrasG12D, broadly in epithelial tissues. We used a mouse model in which the G12D mutation is placed in the endogenous Kras locus controlled by inducible, Cre-mediated recombination in tissues expressing cytokeratin 19 including the oral cavity, GI tract, lungs, and ducts of the liver, kidney, and the pancreas. Introduction of the KrasG12D mutation in adult mouse tissues led to neoplastic changes in some but not all of these tissues. Notably, many hyperplasias, metaplasias and adenomas were observed in the oral cavity, stomach, colon and lungs, suggesting that exposure to products of the outside environment promotes KrasG12D-initiated tumorigenesis. However, environmental exposure did not consistently correlate with tumor formation, such as in the small intestine, suggesting that there are also intrinsic differences in susceptibility to Kras activation. The pancreas developed small numbers of mucinous metaplasias with characteristics of early stage pancreatic intraepithelial neoplasms (PanINs), supporting the hypothesis that pancreatic ducts have the potential to give rise pancreatic cancer

Learning, Memory, and the Role of Neural Network Architecture

The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems

Claudin-7 Is Frequently Overexpressed in Ovarian Cancer and Promotes Invasion

Background: Claudins are tight junction proteins that are involved in tight junction formation and function. Previous studies have shown that claudin-7 is frequently upregulated in epithelial ovarian cancer (EOC) along with claudin-3 and claudin-4. Here, we investigate in detail the expression patterns of claudin-7, as well as its possible functions in EOC. Methodology/Principal Findings: A total of 95 ovarian tissue samples (7 normal ovarian tissues, 65 serous carcinomas, 11 clear cell carcinomas, 8 endometrioid carcinomas and 4 mucinous carcinomas) were studied for claudin-7 expression. In real-time RT-PCR analysis, the gene for claudin-7, CLDN7, was found to be upregulated in all the tumor tissue samples studied. Similarly, immunohistochemical analysis and western blotting showed that claudin-7 protein was significantly overexpressed in the vast majority of EOCs. Small interfering RNA-mediated knockdown of claudin-7 in ovarian cancer cells led to significant changes in gene expression as measured by microarrays and validated by RT-PCR and immunoblotting. Analyses of the genes differentially expressed revealed that the genes altered in response to claudin-7 knockdown were associated with pathways implicated in various molecular and cellular functions such as cell cycle, cellular growth and proliferation, cell death, development, and cell movement. Through functional experiments in vitro, we found that both migration and invasion were altered in cells where CLDN7 had been knocked down or overexpressed. Interestingly, claudin-7 expression was associated with a net increase in invasion, but also with a decrease in migration

Characterization of the Tetraspan Junctional Complex (4JC) superfamily

Connexins or innexins form gap junctions, while claudins and occludins form tight junctions. In this study, statistical data, derived using novel software, indicate that these four junctional protein families and eleven other families of channel and channel auxiliary proteins are related by common descent and comprise the Tetraspan (4 TMS) Junctional Complex (4JC) Superfamily. These proteins all share similar 4 transmembrane α-helical (TMS) topologies. Evidence is presented that they arose via an intragenic duplication event, whereby a 2 TMS-encoding genetic element duplicated tandemly to give 4 TMS proteins. In cases where high resolution structural data were available, the conclusion of homology was supported by conducting structural comparisons. Phylogenetic trees reveal the probable relationships of these 15 families to each other. Long homologues containing fusions to other recognizable domains as well as internally duplicated or fused domains are reported. Large “fusion” proteins containing 4JC domains proved to fall predominantly into family-specific patterns as follows: (1) the 4JC domain was N-terminal; (2) the 4JC domain was C-terminal; (3) the 4JC domain was duplicated or occasionally triplicated and (4) mixed fusion types were present. Our observations provide insight into the evolutionary origins and subfunctions of these proteins as well as guides concerning their structural and functional relationships

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Identification of Cryptosporidium parvum Oocysts by an Artificial Neural Network Approach

Microscopic detection of Cryptosporidium parvum oocysts is time-consuming, requires trained analysts, and is frequently subject to significant human errors. Artificial neural networks (ANN) were developed to help identify immunofluorescently labeled C. parvum oocysts. A total of 525 digitized images of immunofluorescently labeled oocysts, fluorescent microspheres, and other miscellaneous nonoocyst images were employed in the training of the ANN. The images were cropped to a 36- by 36-pixel image, and the cropped images were placed into two categories, oocyst and nonoocyst images. The images were converted to grayscale and processed into a histogram of gray color pixel intensity. Commercially available software was used to develop and train the ANN. The networks were optimized by varying the number of training images, number of hidden neurons, and a combination of these two parameters. The network performance was then evaluated using a set of 362 unique testing images which the network had never “seen” before. Under optimized conditions, the correct identification of authentic oocyst images ranged from 81 to 97%, and the correct identification of nonoocyst images ranged from 78 to 82%, depending on the type of fluorescent antibody that was employed. The results indicate that the ANN developed were able to generalize the training images and subsequently discern previously unseen oocyst images efficiently and reproducibly. Thus, ANN can be used to reduce human errors associated with the microscopic detection of Cryptosporidium oocysts

Effects of pH and Magnetic Material on Immunomagnetic Separation of Cryptosporidium Oocysts from Concentrated Water Samples

In this study, we examined the effect that magnetic materials and pH have on the recoveries of Cryptosporidium oocysts by immunomagnetic separation (IMS). We determined that particles that were concentrated on a magnet during bead separation have no influence on oocyst recovery; however, removal of these particles did influence pH values. The optimal pH of the IMS was determined to be 7.0. The numbers of oocysts recovered from deionized water at pH 7.0 were 26.3% higher than those recovered from samples that were not at optimal pH. The results indicate that the buffers in the IMS kit did not adequately maintain an optimum pH in some water samples. By adjusting the pH of concentrated environmental water samples to 7.0, recoveries of oocysts increased by 26.4% compared to recoveries from samples where the pH was not adjusted