Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0220723 (PCA)
 4,687 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Malignant astrocytoma includes anaplastic astrocytoma (grade III) and glioblastoma (grade IV). Among them, glioblastoma is the most common primary brain tumor with dismal responses to all therapeutic modalities. We performed a large-scale, genome-wide microRNA (miRNA) (n=756) expression profiling of 26 glioblastoma, 13 anaplastic astrocytoma and 7 normal brain samples with an aim to find deregulated miRNA in malignant astrocytoma. We identified several differentially regulated miRNAs between these groups, which could differentiate glioma grades and normal brain as recognized by PCA. More importantly, we identified a most discriminatory 23-miRNA expression signature, by using PAM, which precisely distinguished glioblastoma from anaplastic astrocytoma with an accuracy of 95%. The differential expression pattern of nine miRNAs was further validated by real-time RT-PCR on an independent set of malignant astrocytomas (n=72) and normal samples (n=7). Inhibition of two glioblastoma-upregulated miRNAs (miR-21 and miR-23a) and exogenous overexpression of two glioblastoma-downregulated miRNAs (miR-218 and miR-219-5p) resulted in reduced soft agar colony formation but showed varying effects on cell proliferation and chemosensitivity. Thus we have identified the miRNA expression signature for malignant astrocytoma, in particular glioblastoma, and showed the miRNA involvement and their importance in astrocytoma development.
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PMID:Genome-wide expression profiling identifies deregulated miRNAs in malignant astrocytoma. 2071 Nov 71

The objective of this work was to measure infrared spectra of high explosive materials (HE) in wide spectral range in order to acquire information for their complete characterization and find out the regions that are the most discriminatory for each material. Four HEs were measured by means of Fourier Transform Infrared (FTIR) spectroscopy in a very broad range (from near- via mid- to far-IR). Obtained spectra were subsequently evaluated using multivariate statistical methods for dimension reduction and results grouping. Clustering was assessed in terms of compactness and stability in order to distinguish which region or regions are most suitable for the identification based on spectral signature. Based on outcomes of visualization method (silhouette plot) used to compare results of implemented chemometric methods (HCA, PAM, and PCA) done on FTIR spectra collected for four high explosive materials (PETN, C-4, RDX, and TNT) within all regions, it seems that the mid-IR region is the most informative for the distinction among analyzed HE materials based on substance spectral signatures. However, it is worth noticing that also the near-IR region can be used for good differentiation.
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PMID:Broad Range FTIR Spectroscopy and Multivariate Statistics for High Energetic Materials Discrimination. 3212 27