Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
Add filters








Language
Year range
1.
Journal of Biomedical Research ; : 129-133, 2015.
Article in English | WPRIM | ID: wpr-155583

ABSTRACT

A 5-year-old, 8.95 kg, female Schnauzer presented anorexia with a 3-day history and increased heart sound intensity. Based on the clinical and echocardiographic findings along with the positive blood culture result, the dog was diagnosed with infective endocarditis (IE). Using proper antibiotics treatment, clinical signs were improved within 3 days and resolved within 1 week. For exact identification of the causative agent, multiplex polymerase chain reaction (PCR) and PCR-restriction fragment length polymorphism (RFLP) methods were performed. The etiological agent was confirmed as Staphylococcus pseudintermedius with antibiotics resistance genes such as beta-lactamase (blaZ) and methicilline resistance (mecA). The bacterial virulence factors included pyogenic toxin genes such as staphylococcal enterotoxins A, B, C, D, and E and toxic shock syndrome toxin 1. Diagnosis of IE is challenging due to a variety of non-specific clinical presentations, rapid disease progression, and lack of a confirmative diagnostic technique. This report demonstrated that such molecular diagnostics could be very useful for diagnosing and identifying characteristics of the causative organism for prediction of prognosis and proper treatment. To our knowledge, this is the first report on the isolation of S. pseudintermedius using molecular diagnostics from a clinical case of canine IE.


Subject(s)
Animals , Child, Preschool , Dogs , Female , Humans , Anorexia , Anti-Bacterial Agents , beta-Lactamases , Diagnosis , Disease Progression , Echocardiography , Endocarditis , Enterotoxins , Heart Sounds , Methicillin , Multiplex Polymerase Chain Reaction , Pathology, Molecular , Prognosis , Shock, Septic , Staphylococcus , Virulence Factors
2.
Experimental & Molecular Medicine ; : 824-831, 2009.
Article in English | WPRIM | ID: wpr-174318

ABSTRACT

Hu protein R (HuR) binds to the AU-rich element (ARE) in the 3'UTR to stabilize TNF-alpha mRNA. Here, we identified chemical inhibitors of the interaction between HuR and the ARE of TNF-alpha mRNA using RNA electrophoretic mobility gel shift assay (EMSA) and filter binding assay. Of 179 chemicals screened, we identified three with a half-maximal inhibitory concentration (IC(50)) below 10 micrometer. The IC(50) of quercetin, b-40, and b-41 were 1.4, 0.38, and 6.21 micrometer, respectively, for binding of HuR protein to TNF-alpha mRNA. Quercetin and b-40 did not inhibit binding of tristetraprolin to the ARE of TNF-alpha mRNA. When LPS-treated RAW264.7 cells were treated with quercetin and b-40, we observed decreased stability of TNF-alpha mRNA and decreased levels of secreted TNF-alpha. From these results, we could find inhibitors for the TNF-alpha mRNA stability, which might be used advantageously for both the study for post-transcriptional regulation and the discovery of new anti-inflammation drugs.


Subject(s)
Animals , Mice , 3' Untranslated Regions , Anti-Inflammatory Agents/pharmacology , Antigens, Surface/metabolism , Antioxidants/pharmacology , Cell Line , Dose-Response Relationship, Drug , Drug Evaluation, Preclinical , Protein Binding/drug effects , Quercetin/pharmacology , RNA Stability/drug effects , RNA-Binding Proteins/antagonists & inhibitors , Tumor Necrosis Factor-alpha/biosynthesis
3.
Genomics & Informatics ; : 161-166, 2006.
Article in English | WPRIM | ID: wpr-91153

ABSTRACT

The establishment of DNA microarray technology has enabled high-throughput analysis and molecular profiling of various types of cancers. By using the gene expression data from microarray analysis we are able to investigate diagnostic applications at the molecular level. The most important step in the application of microarray technology to cancer diagnostics is the selection of specific markers from gene expression profiles. In order to select markers of immortalization and transformation we used c-myc and H-ras(V12) oncogene-transfected NIH3T3 cells as our model system. We have identified 8751 differentially expressed genes in the immortalization/transformation model by multivariate permutation F-test (95% confidence, FDR <0.01). Using the support vector machine algorithm, we selected 13 discriminative genes which could be used to predict immortalization and transformation with perfect accuracy. We assayed H-ras(V12)-transfected "transformed" cells to validate our immortalization/transformation classification system. The selected molecular markers generated valuable additional information for tumor diagnosis, prognosis and therapy development.


Subject(s)
Classification , Diagnosis , Gene Expression , Microarray Analysis , Oligonucleotide Array Sequence Analysis , Prognosis , Transcriptome , Support Vector Machine
SELECTION OF CITATIONS
SEARCH DETAIL