Large Dog Relinquishment to Two Municipal Facilities in New York City and Washington, D.C.: Identifying Targets for Intervention

While the overall trend in euthanasia has been decreasing nationally, large dogs are at a higher risk of euthanasia than other sized dogs in most animal shelters in the United States. We hypothesized one way to increase the lives saved with respect to these large dogs is to keep them home when possible. In order to develop solutions to decrease relinquishment, a survey was developed to learn more about the reasons owners relinquish large dogs. The survey was administered to owners relinquishing their dogs at two large municipal facilities, one in New York City and one in Washington, D.C. There were 157 responses between the two facilities. We found both significant similarities and differences between respondents and their dogs from the two cities. We identified opportunities to potentially support future relinquishers and found that targets for interventions are likely different in each community

Bibliografia historii gospodarczej Polski w latach 1944-1989

S\u142owa kluczowe: historia gospodarcza Polski Ludowej; bibliografia prac z lat 1944-2002; biografie i pami\u119tniki; informatory; prasa gospodarcz

Assessing adaptation of the cancer kinome in response to targeted therapies

Cancer cells are dependent on protein kinase signalling networks to drive proliferation and to promote survival, and, accordingly, kinases continue to represent a major target class for development of anti-cancer therapeutics. Kinase inhibitors nevertheless have yielded only limited success with many different malignancies due to the inability of single agents to sustain a durable clinical response. Cancer cell kinomes are highly resilient and able to bypass targeted kinase inhibition, leading to tumour resistance. A novel platform has been developed to analyse the activity of the expressed kinome using MIBs (multiplexed inhibitor beads), which consist of Sepharose beads with covalently immobilized inhibitors that preferentially bind activated kinases. Coupling MIB capture with MS (MIB-MS) allows simultaneous determination of the activity of over 75% of the expressed kinome, facilitating high-throughput assessment of adaptive kinase responses resulting from deregulated feedback and feedforward regulatory mechanisms. The adaptive response frequently involves transcriptional up-regulation of specific kinases that allow bypass of the targeted kinase. Understanding how the kinome reprogrammes to targeted kinase inhibition will allow novel therapeutic strategies to be developed for durable clinical responses

hTERT mediates gastric cancer metastasis partially through the indirect targeting of ITGB1 by microRNA-29a.

Human telomerase reverse transcriptase (hTERT) plays a key role in tumor invasion and metastasis, but the mechanism of its involvement in these processes is not clear. The purpose of this study is to investigate the possible molecular mechanism of hTERT in the promotion of gastric cancer (GC) metastasis. We found that the up-regulation of hTERT in gastric cancer cells could inhibit the expression of miR-29a and enhance the expression of Integrin β1 (ITGB1). In addition, the invasive capacity of gastric cancer cells was also highly increased after hTERT overexpression. Our study also found that the restoration of miR-29a suppressed the expression of ITGB1 and inhibited GC cell metastasis both in vitro and in vivo. Taken together, our results suggested that hTERT may promote GC metastasis through the hTERT-miR-29a-ITGB1 regulatory pathway

A RhoC Biosensor Reveals Differences in the Activation Kinetics of RhoA and RhoC in Migrating Cells

RhoA and RhoC GTPases share 92% amino acid sequence identity, yet play different roles in regulating cell motility and morphology. To understand these differences, we developed and validated a biosensor of RhoC activation (RhoC FLARE). This was used together with a RhoA biosensor to compare the spatio-temporal dynamics of RhoA and RhoC activity during cell protrusion/retraction and macropinocytosis. Both GTPases were activated similarly at the cell edge, but in regions more distal from the edge RhoC showed higher activation during protrusion. The two isoforms differed markedly in the kinetics of activation. RhoC was activated concomitantly with RhoA at the cell edge, but distally, RhoC activation preceded RhoA activation, occurring before edge protrusion. During macropinocytosis, differences were observed during vesicle closure and in the area surrounding vesicle formation

Evaluating methods for the analysis of rare variants in sequence data

A number of rare variant statistical methods have been proposed for analysis of the impending wave of next-generation sequencing data. To date, there are few direct comparisons of these methods on real sequence data. Furthermore, there is a strong need for practical advice on the proper analytic strategies for rare variant analysis. We compare four recently proposed rare variant methods (combined multivariate and collapsing, weighted sum, proportion regression, and cumulative minor allele test) on simulated phenotype and next-generation sequencing data as part of Genetic Analysis Workshop 17. Overall, we find that all analyzed methods have serious practical limitations on identifying causal genes. Specifically, no method has more than a 5% true discovery rate (percentage of truly causal genes among all those identified as significantly associated with the phenotype). Further exploration shows that all methods suffer from inflated false-positive error rates (chance that a noncausal gene will be identified as associated with the phenotype) because of population stratification and gametic phase disequilibrium between noncausal SNPs and causal SNPs. Furthermore, observed true-positive rates (chance that a truly causal gene will be identified as significantly associated with the phenotype) for each of the four methods was very low (<19%). The combination of larger than anticipated false-positive rates, low true-positive rates, and only about 1% of all genes being causal yields poor discriminatory ability for all four methods. Gametic phase disequilibrium and population stratification are important areas for further research in the analysis of rare variant data

MAP3K4 Controls the Chromatin Modifier HDAC6 during Trophoblast Stem Cell Epithelial-to-Mesenchymal Transition

The first epithelial-to-mesenchymal transition (EMT) occurs in trophoblast stem (TS) cells during implantation. Inactivation of the serine/threonine kinase MAP3K4 in TS cells (TSKI4 cells) induces an intermediate state of EMT, where cells retain stemness, lose epithelial markers, and gain mesenchymal characteristics. Investigation of relationships among MAP3K4 activity, stemness, and EMT in TS cells may reveal key regulators of EMT. Here, we show that MAP3K4 activity controls EMT through the ubiquitination and degradation of HDAC6. Loss of MAP3K4 activity in TSKI4 cells results in elevated HDAC6 expression and the deacetylation of cytoplasmic and nuclear targets. In the nucleus, HDAC6 deacetylates the promoters of tight junction genes, promoting the dissolution of tight junctions. Importantly, HDAC6 knockdown in TSKI4 cells restores epithelial features, including cell-cell adhesion and barrier formation. These data define a role for HDAC6 in regulating gene expression during transitions between epithelial and mesenchymal phenotypes

Molecular Pathways: Adaptive Kinome Reprogramming in Response to Targeted Inhibition of the BRAF-MEK-ERK Pathway in Cancer

The central role of the BRAF-MEK-ERK pathway in controlling cell fate has made this pathway a primary target for deregulated activation in cancer. BRaf is activated by Ras proteins allowing Ras oncogenes to constitutively activate the pathway. Activating BRaf mutations are also frequent in several cancers, being the most common oncogenic mutation in thyroid carcinoma and melanoma. There are currently two inhibitors, vemurafenib and dabrafenib, approved for treatment of malignant melanoma having activating BRaf mutations. Concurrent administration of BRAF inhibitor and MEK inhibitor (trametinib) is significantly more active in patients with BRAF mutant melanoma than either single agent alone, but progression to resistance ultimately occurs by different mechanisms that increase the activation of ERK. Such adaptive changes in tumor cell signaling networks allows bypass of targeted oncoprotein inhibition. This is true with targeted inhibitors for BRaf and MEK as well as specific inhibitors for AKT, mTOR and many receptor tyrosine kinases such as EGFR and HER2. It is this adaptive response to targeted kinase inhibitors that contributes to the failure of single agent kinase inhibitors to have durable responses. This failure is seen in virtually all cancers treated with single agent kinase inhibitors, most of which are not as dependent on a single signaling pathway such as BRaf-MEK-ERK in melanoma. Thus, understanding the breadth of adaptive reprogramming responses to specific targeted kinase inhibition will be critical to develop appropriate combination therapies for durable clinical responses

Evaluating methods for combining rare variant data in pathway-based tests of genetic association

Analyzing sets of genes in genome-wide association studies is a relatively new approach that aims to capitalize on biological knowledge about the interactions of genes in biological pathways. This approach, called pathway analysis or gene set analysis, has not yet been applied to the analysis of rare variants. Applying pathway analysis to rare variants offers two competing approaches. In the first approach rare variant statistics are used to generate p-values for each gene (e.g., combined multivariate collapsing [CMC] or weighted-sum [WS]) and the gene-level p-values are combined using standard pathway analysis methods (e.g., gene set enrichment analysis or Fisher’s combined probability method). In the second approach, rare variant methods (e.g., CMC and WS) are applied directly to sets of single-nucleotide polymorphisms (SNPs) representing all SNPs within genes in a pathway. In this paper we use simulated phenotype and real next-generation sequencing data from Genetic Analysis Workshop 17 to analyze sets of rare variants using these two competing approaches. The initial results suggest substantial differences in the methods, with Fisher’s combined probability method and the direct application of the WS method yielding the best power. Evidence suggests that the WS method works well in most situations, although Fisher’s method was more likely to be optimal when the number of causal SNPs in the set was low but the risk of the causal SNPs was high