Goat anti Human Protein S polyclonal antibody [HRP]

Purpose: The incidence of papillary thyroid carcinomas (PTCs) is rapidly increasing in Korea. Analyzing the gene expression profiling (GEP) of PTCs will facilitate the advent of new methods in diagnosis, prognostication, and treatment. We performed this study to find the GEP of Korean PTCs. Methods: We performed oligonucleotide microarray analysis with 19 PTCs and 7 normal thyroid glands. Differentially expressed genes were selected using a t-test (I fold I >3) and adjusted Benjamini-Hochberg false discovery rate P-value < 0.01. Quantitative reverse transcription-polymerase chain reaction (QRT-PCR) was used to validate microarray data. A classification model was developed by support vector machine (SVM) algorithm to diagnose PTCs based on molecular signatures. Results: We identified 79 differentially expressed genes (70 up-regulated and 9 down-regulated) according to the criteria. QRT-PCR for five genes (CDH3, NGEF, PROS1, TGFA, MET) was confirmatory of the microarray data. Hierarchical cluster analysis and a classification model by the SVM algorithm accurately differentiated PTCs from normal thyroid gland based on GEP. Conclusion: A disease classification model showed excellent accuracy in diagnosing PTCs, thus showing the possibility of molecular diagnosis in the future. This GEP could serve as baseline data for further investigation in the management of PTCs based on molecular signatures.

Introduction: Venous bed specificity could contribute to differential vulnerability to thrombus formation, and is potentially reflected in mRNA profiles. Materials and methods: Microarray-based transcriptome analysis in wall and valve specimens from internal jugular (IJV) and saphenous (SV) veins collected during IJV surgical reconstruction in patients with impaired brain outflow. Multiplex antigenic assay in paired jugular and peripheral plasma samples. Results: Most of the top differentially expressed transcripts have been previously associated with both vascular and neurological disorders. Large expression differences of HOX genes, organ patterning regulators, pinpointed the vein positional identity. The "complement and coagulation cascade" emerged among enriched pathways. In IJV, upregulation of genes for coagulation inhibitors (TFPI, PROS1), activated protein C pathway receptors (THBD, PROCR), fibrinolysis activators (PLAT, PLAUR), and downregulation of the fibrinolysis inhibitor (SERPINE1) and of contact/amplification pathway genes (F11, F12), would be compatible with a thromboprotective profile in respect to SV. Further, in SV valve the prothrombinase complex genes (F5, F2) were up-regulated and the VWF showed the highest expression. Differential expression of several VWF regulators (ABO, ST3GAL4, SCARA5, CLEC4M) was also observed. Among other differentially expressed hemostasis-related genes, heparanase (HPSE)/heparanase inhibitor (HPSE2) were up-/down-regulated in IJV, which might support procoagulant features and disease conditions. The jugular plasma levels of several proteins, encoded by differentially expressed genes, were lower and highly correlated with peripheral levels. Conclusions: The IJV and SV rely on differential expression of many hemostasis and hemostasis-related genes to balance local hemostasis, potentially related to differences in vulnerability to thrombosis.