Steady pressure measurements in the strap-on booster interference Region of 1/20 scale aslv configuration

Wind tunnel studies were carried out to obtain pressure distribution in the strap-on booster interference region of 1/20th scale Augmented Satellite Launch Vehicle model configuration. Tests were done in the 1 .2m tunnel at NAL in the Mach number range of 0 .5 to 2.5 for the clean configuration as well as with spring housing attachments on the strap-on boosters. Both the model configurations with the boosters strapped on to the core vehicle in the horizontal plane (pitch) and in the vertical plane (yaw) were tested for incidences at 0, 4 and -4 deg. In addition pressure measurements were also done on the core vehicle alone at Mach numbers 2.1, 2.5 and 3.0 for 0, +4 degree incidences. The test Reynolds number was varied from 0.7 to 1.3 millions based on the maximum diameter of the model. The pressure distribution showed significant interference effects of boosters on the core vehicle. It is observed that the positive pressure peak associated with flow compression at the flare junction increases with increase in Mach number. In the pitch plane the normal force distribution remains positive along the core vehicle whereas in the yaw plane it is of less magnitude

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites. google.com/site/gaussianbhc

ExoPranayama: a biofeedback-driven actuated environment for supporting yoga breathing practices

Both breathing and internal self-awareness are an integral part of any yoga practice. We describe and discuss the development of ExoPranayama, an actuated environment that physically manifests users’ breathing in yoga. Through a series of trials with yoga practitioners and expert teachers, we explore its role in the practice of yoga. Our interview results reveal that biofeedback through the environment supported teaching and improved self-awareness, but it impacted group cohesion. Two practical uses of the technology emerged for supporting breath control in yoga: (1) biofeedback can provide new information about users’ current internal states; (2) machine-driven feedback provides users with a future state or goal, and leads to improved cohesiveness

Differential proteomic alterations between localised and metastatic prostate cancer

Molecular alterations in the prostate cancer proteome mediate the functional and phenotypic transformation from clinically localised to metastatic cancer, a transition that drives patient's mortality and challenges therapeutic intervention. A first approximation of differential proteomic alterations stratified by disease stage has yielded repertoires of potential diagnostic and prognostic markers, multiplex signatures of predictive value, and yield fundamental insight into molecular commonalities in cancer progression. Deciphering these causative proteomic alterations from the molecular noise will continue to mature our understanding of tumour biology and drive new computational and integrative approaches to model a system's view that accommodates the heterogeneity of prostate cancer progression

The Marker State Space (MSS) Method for Classifying Clinical Samples

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications. © 2013 Fallon et al

3-Deazaneplanocin A (DZNep), an Inhibitor of the Histone Methyltransferase EZH2, Induces Apoptosis and Reduces Cell Migration in Chondrosarcoma Cells

ObjectiveGrowing evidences indicate that the histone methyltransferase EZH2 (enhancer of zeste homolog 2) may be an appropriate therapeutic target in some tumors. Indeed, a high expression of EZH2 is correlated with poor prognosis and metastasis in many cancers. In addition, 3-Deazaneplanocin A (DZNep), an S-adenosyl-L homocysteine hydrolase inhibitor which induces EZH2 protein depletion, leads to cell death in several cancers and tumors. The aim of this study was to determine whether an epigenetic therapy targeting EZH2 with DZNep may be also efficient to treat chondrosarcomas.MethodsEZH2 expression was determined by immunohistochemistry and western-blot. Chondrosarcoma cell line CH2879 was cultured in the presence of DZNep, and its growth and survival were evaluated by counting adherent cells periodically. Apoptosis was assayed by cell cycle analysis, Apo2.7 expression using flow cytometry, and by PARP cleavage using western-blot. Cell migration was assessed by wound healing assay.ResultsChondrosarcomas (at least with high grade) highly express EZH2, at contrary to enchondromas or chondrocytes. In vitro, DZNep inhibits EZH2 protein expression, and subsequently reduces the trimethylation of lysine 27 on histone H3 (H3K27me3). Interestingly, DZNep induces cell death of chondrosarcoma cell lines by apoptosis, while it slightly reduces growth of normal chondrocytes. In addition, DZNep reduces cell migration.ConclusionThese results indicate that an epigenetic therapy that pharmacologically targets EZH2 via DZNep may constitute a novel approach to treat chondrosarcomas

EZH2 promotes a bi-lineage identity in basal-like breast cancer cells

The mechanisms regulating breast cancer differentiation state are poorly understood. Of particular interest are molecular regulators controlling the highly aggressive and poorly differentiated traits of basal-like breast carcinomas. Here we show that the Polycomb factor EZH2 maintains the differentiation state of basal-like breast cancer cells, and promotes the expression of progenitor-associated and basal-lineage genes. Specifically, EZH2 regulates the composition of basal-like breast cancer cell populations by promoting a ‘bi-lineage’ differentiation state, in which cells co-express basal- and luminal-lineage markers. We show that human basal-like breast cancers contain a subpopulation of bi-lineage cells, and that EZH2-deficient cells give rise to tumors with a decreased proportion of such cells. Bi-lineage cells express genes that are active in normal luminal progenitors, and possess increased colony-formation capacity, consistent with a primitive differentiation state. We found that GATA3, a driver of luminal differentiation, performs a function opposite to EZH2, acting to suppress bi-lineage identity and luminal-progenitor gene expression. GATA3 levels increase upon EZH2 silencing, mediating a decrease in bi-lineage cell numbers. Our findings reveal a novel role for EZH2 in controlling basal-like breast cancer differentiation state and intra-tumoral cell composition

Regulation of proteasome assembly and activity in health and disease

The proteasome degrades most cellular proteins in a controlled and tightly regulated manner and thereby controls many processes, including cell cycle, transcription, signalling, trafficking and protein quality control. Proteasomal degradation is vital in all cells and organisms, and dysfunction or failure of proteasomal degradation is associated with diverse human diseases, including cancer and neurodegeneration. Target selection is an important and well-established way to control protein degradation. In addition, mounting evidence indicates that cells adjust proteasome-mediated degradation to their needs by regulating proteasome abundance through the coordinated expression of proteasome subunits and assembly chaperones. Central to the regulation of proteasome assembly is TOR complex 1 (TORC1), which is the master regulator of cell growth and stress. This Review discusses how proteasome assembly and the regulation of proteasomal degradation are integrated with cellular physiology, including the interplay between the proteasome and autophagy pathways. Understanding these mechanisms has potential implications for disease therapy, as the misregulation of proteasome function contributes to human diseases such as cancer and neurodegeneration.</p

Whole-Exome Sequencing Reveals High Mutational Concordance between Primary and Matched Recurrent Triple-Negative Breast Cancers

PURPOSE Triple-negative breast cancer (TNBC) is a molecularly complex and heterogeneous breast cancer subtype with distinct biological features and clinical behavior. Although TNBC is associated with an increased risk of metastasis and recurrence, the molecular mechanisms underlying TNBC metastasis remain unclear. We performed whole-exome sequencing (WES) analysis of primary TNBC and paired recurrent tumors to investigate the genetic profile of TNBC. METHODS Genomic DNA extracted from 35 formalin-fixed paraffin-embedded tissue samples from 26 TNBC patients was subjected to WES. Of these, 15 were primary tumors that did not have recurrence, and 11 were primary tumors that had recurrence (nine paired primary and recurrent tumors). Tumors were analyzed for single-nucleotide variants and insertions/deletions. RESULTS The tumor mutational burden (TMB) was 7.6 variants/megabase in primary tumors that recurred (n = 9); 8.2 variants/megabase in corresponding recurrent tumors (n = 9); and 7.3 variants/megabase in primary tumors that did not recur (n = 15). MUC3A was the most frequently mutated gene in all groups. Mutations in MAP3K1 and MUC16 were more common in our dataset. No alterations in PI3KCA were detected in our dataset. CONCLUSIONS We found similar mutational profiles between primary and paired recurrent tumors, suggesting that genomic features may be retained during local recurrence

Characterization of glycine-N-acyltransferase like 1 (GLYATL1) in prostate cancer

BackgroundRecent microarray and sequencing studies of prostate cancer showed multiple molecular alterations during cancer progression. It is critical to evaluate these molecular changes to identify new biomarkers and targets. We performed analysis of glycine-N-acyltransferase like 1 (GLYATL1) expression in various stages of prostate cancer in this study and evaluated the regulation of GLYATL1 by androgen.MethodWe performed in silico analysis of cancer gene expression profiling and transcriptome sequencing to evaluate GLYATL1 expression in prostate cancer. Furthermore, we performed immunohistochemistry using specific GLYATL1 antibody using high-density prostate cancer tissue microarray containing primary and metastatic prostate cancer. We also tested the regulation of GLYATL1 expression by androgen and ETS transcription factor ETV1. In addition, we performed RNA-sequencing of GLYATL1 modulated prostate cancer cells to evaluate the gene expression and changes in molecular pathways.ResultsOur in silico analysis of cancer gene expression profiling and transcriptome sequencing we revealed an overexpression of GLYATL1 in primary prostate cancer. Confirming these findings by immunohistochemistry, we show that GLYATL1 is overexpressed in primary prostate cancer compared with metastatic prostate cancer and benign prostatic tissue. Low-grade cancers had higher GLYATL1 expression compared to high-grade prostate tumors. Our studies showed that GLYATL1 is upregulated upon androgen treatment in LNCaP prostate cancer cells which harbors ETV1 gene rearrangement. Furthermore, ETV1 knockdown in LNCaP cells showed downregulation of GLYATL1 suggesting potential regulation of GLYATL1 by ETS transcription factor ETV1. Transcriptome sequencing using the GLYATL1 knockdown prostate cancer cell lines LNCaP showed regulation of multiple metabolic pathways.ConclusionsIn summary, our study characterizes the expression of GLYATL1 in prostate cancer and explores the regulation of its regulation in prostate cancer showing role for androgen and ETS transcription factor ETV1. Future studies are needed to decipher the biological significance of these findings.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151252/1/pros23887.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151252/2/pros23887_am.pd