miRConnect 2.0: identification of oncogenic, antagonistic miRNA families in three human cancers

Abstract Background Based on their function in cancer micro(mi)RNAs are often grouped as either tumor suppressors or oncogenes. However, miRNAs regulate multiple tumor relevant signaling pathways raising the question whether two oncogenic miRNAs could be functional antagonists by promoting different steps in tumor progression. We recently developed a method to connect miRNAs to biological function by comparing miRNA and gene array expression data from the NCI60 cell lines without using miRNA target predictions (miRConnect). Results We have now extended this analysis to three primary human cancers (ovarian cancer, glioblastoma multiforme, and kidney renal clear cell carcinoma) available at the Cancer Genome Atlas (TCGA), and have correlated the expression of the clustered miRNAs with 158 oncogenic signatures (miRConnect 2.0). We have identified functionally antagonistic groups of miRNAs. One group (the agonists), which contains many of the members of the miR-17 family, correlated with c-Myc induced genes and E2F gene signatures. A group that was directly antagonistic to the agonists in all three primary cancers contains miR-221 and miR-222. Since both miR-17 ~ 92 and miR-221/222 are considered to be oncogenic this points to a functional antagonism of different oncogenic miRNAs. Analysis of patient data revealed that in certain patients agonistic miRNAs predominated, whereas in other patients antagonists predominated. In glioblastoma a high ratio of miR-17 to miR-221/222 was predictive of better overall survival suggesting that high miR-221/222 expression is more adverse for patients than high miR-17 expression. Conclusion miRConnect 2.0 is useful for identifying activities of miRNAs that are relevant to primary cancers. The new correlation data on miRNAs and mRNAs deregulated in three primary cancers are available at miRConnect.orghttp://deepblue.lib.umich.edu/bitstream/2027.42/112974/1/12864_2013_Article_4929.pd

miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells

micro(mi)RNAs are small non-coding RNAs that negatively regulate expression of most mRNAs. They are powerful regulators of various differentiation stages, and the expression of genes that either negatively or positively correlate with expressed miRNAs is expected to hold information on the biological state of the cell and, hence, of the function of the expressed miRNAs. We have compared the large amount of available gene array data on the steady state system of the NCI60 cell lines to two different data sets containing information on the expression of 583 individual miRNAs. In addition, we have generated custom data sets containing expression information of 54 miRNA families sharing the same seed match. We have developed a novel strategy for correlating miRNAs with individual genes based on a summed Pearson Correlation Coefficient (sPCC) that mimics an in silico titration experiment. By focusing on the genes that correlate with the expression of miRNAs without necessarily being direct targets of miRNAs, we have clustered miRNAs into different functional groups. This has resulted in the identification of three novel miRNAs that are linked to the epithelial-to-mesenchymal transition (EMT) in addition to the known EMT regulators of the miR-200 miRNA family. In addition, an analysis of gene signatures associated with EMT, c-MYC activity, and ribosomal protein gene expression allowed us to assign different activities to each of the functional clusters of miRNAs. All correlation data are available via a web interface that allows investigators to identify genes whose expression correlates with the expression of single miRNAs or entire miRNA families. miRConnect.org will aid in identifying pathways regulated by miRNAs without requiring specific knowledge of miRNA targets

Effectiveness of an Essay Writing Strategy for Post-Secondary Students with Developmental Disabilities

Abstract: This study examined the effectiveness of the ANSWER Strateg

Exergy Loss Assessment Method for CNC Milling System Considering the Energy Consumption of the Operator

Modeling and assessing the sustainability of machining systems has been considered to be a crucial approach to improving the environmental performance of machining processes. As the most common machining system, the computer numerical control (CNC) milling system is a typical man–machine cooperative system where the activities of the machine tool and operator generate material and energy consumption. However, the energy consumption of the operator in the CNC milling system has often been ignored in most existing research. Therefore, existing methods fail to provide a comprehensive understanding of the sustainability of the CNC milling system. To fill this gap, an exergy loss assessment method is proposed to investigate the sustainability of the CNC milling system, where the energy consumption of the operator, the energy consumption of the machine tool, and material consumption are taken into consideration. The key performance indexes of the energy consumption of the operator, the energy consumption of the machine tool, the exergy loss, and the specific exergy loss (SEL) are analyzed and modeled. To demonstrate the feasibility of the proposed method, a case study was carried out on a three-axis machining center (XH714D), in which the energy consumption of the operator, the energy consumption of the machine tool, the exergy loss of energy consumption, the exergy loss of chips, the exergy loss of compressed air, the exergy loss of cutting tool wear, the exergy loss of cooling liquid dissipation, and the SEL were found to be 169,750 J, 758,211 J, 603,131 J, 2,031,404 J, 22,023 J, 301,868 J, 2673 J, and 88.04 J/mm3, respectively. The proposed method is effective to assess the sustainability of the CNC milling system, and the established exergy loss models build a good basis for exergy efficiency optimization

Designed composites for mimicking compressive mechanical properties of articular cartilage matrix

Collagen, chitosan-polycaprolactone (CH-PCL) copolymer with PCL content of around 40wt% and chondroitin sulfate (CS) were mixed together at various ratios to prepare collagen/CH-PCL/CS composites and the resulting composites were used to build stratified porous scaffolds that are potentially applicable for articular cartilage repair. The ternary composites were designed in such a way that collagen content in the scaffolds decreased from the top layer to the bottom layer while the content of CH-PCL and CS altered in a reversed trend in order to reach partial similarity to cartilage matrix in the composition of main components. Porous structures inside collagen/CH-PCL/CS scaffolds were constructed using a low-temperature deposition processing technique and graded average pore-size and porosity for the scaffolds were established. Such produced scaffolds were further crosslinked using 1-ethyl-3-(3-dimethyl aminopropyl) carbodiimide under optimized conditions, and the obtained scaffolds showed well-defined elastic compressive properties. Compressive modulus (E) and stress at 10% strain (σ10) of full scaffolds in wet state reached about 2.8MPa and 0.3MPa, respectively, and meanwhile, E and σ10 of layers inside hydrated scaffolds changed in a gradient-increased manner from the top layer to the bottom layer with significant differences between contiguous layers, which partially mimics compressive mechanical properties of cartilage matrix. In addition, in vitro culture of cell-scaffold constructs exhibited that scaffolds were able to well support the ingrowth and migration of seeded cells, and cells also showed relatively uniform distribution throughout the scaffolds. These results suggest that the presently developed collagen/CH-PCL/CS scaffolds have promising potential for applications in articular cartilage repair. ? 2014 Elsevier Ltd

In Situ Identification of Unknown Crystals in Acute Kidney Injury Using Raman Spectroscopy

Raman spectroscopy is a well-established and powerful tool for in situ biomolecular evaluation. Type 2 crystal nephropathies are characterized by the deposition of crystalline materials in the tubular lumen, resulting in rapid onset of acute kidney injury without specific symptoms. Timely crystal identification is essential for its diagnosis, mechanism exploration and therapy, but remains challenging. This study aims to develop a Raman spectroscopy-based method to assist pathological diagnosis of type 2 crystal nephropathies. Unknown crystals in renal tissue slides from a victim suffered extensive burn injury were detected by Raman spectroscopy, and the inclusion of crystals was determined by comparing Raman data with established database. Multiple crystals were scanned to verify the reproducibility of crystal in situ. Raman data of 20 random crystals were obtained, and the distribution and uniformity of substances in crystals were investigated by Raman imaging. A mouse model was established to mimic the crystal nephropathy to verify the availability of Raman spectroscopy in frozen biopsy. All crystals on the human slides were identified to be calcium oxalate dihydrate, and the distribution and content of calcium oxalate dihydrate on a single crystal were uneven. Raman spectroscopy was further validated to be available in identification of calcium oxalate dihydrate crystals in the biopsy specimens. Here, a Raman spectroscopy-based method for in situ identification of unknown crystals in both paraffin-embedded tissues and biopsy specimens was established, providing an effective and promising method to analyze unknown crystals in tissues and assist the precise pathological diagnosis in both clinical and forensic medicine