Medical Specialties Commons^™

Clinical And Laboratory Features Distinguishing Juvenile Polymyositis And Muscular Dystrophy, Gulnara Mamyrova, James D. Katz, Robert V. Jones, Ira N. Targoff, Peter A. Lachenbruch, Olcay Y. Jones, Frederick W. Miller, Lisa G. Rider

Pathology Faculty Publications

OBJECTIVE:

To differentiate juvenile polymyositis (PM) and muscular dystrophy, both of which may present with chronic muscle weakness and inflammation.

METHODS:

We studied 39 patients with probable or definite juvenile PM and 9 patients with muscular dystrophies who were initially misdiagnosed as having juvenile PM. Differences in demographic, clinical, and laboratory results; outcomes; and treatment responses were evaluated by Fisher's exact and rank sum tests. Random forests classification analysis and logistic regression were performed to examine significant differences in multivariable models.

RESULTS:

Clinical features and serum muscle enzyme levels were similar between juvenile PM and dystrophy patients, except 89% of …

Role Of Deregulated Micrornas In Breast Cancer Progression Using Ffpe Tissue, Liang Chen, Youhuai Li, Yebo Fu, Jin Peng, Meng-Hsuan Mo, Michael Stamatakos, Christine B. Teal, Rachel F. Brem, Alexander Stojadinovic, Michael Grinkemeyer, Timothy A. Mccaffrey, Yan-Gao Man, Sidney W. Fu

Pathology Faculty Publications

MicroRNAs (miRNAs) contribute to cancer initiation and progression by silencing the expression of their target genes, causing either mRNA molecule degradation or translational inhibition. Intraductal epithelial proliferations of the breast are histologically and clinically classified into normal, atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). To better understand the progression of ductal breast cancer development, we attempt to identify deregulated miRNAs in this process using Formalin-Fixed, Paraffin-Embedded (FFPE) tissues from breast cancer patients. Following tissue microdissection, we obtained 8 normal, 4 ADH, 6 DCIS and 7 IDC samples, which were subject to RNA isolation …

B Cell Acute Lymphoblastic Leukemia Associated With T(8;22)(P11.2q11.2): Role Of Additional Cytogenic Anomalies, Kate M. Serdy, Shireen R. Khoury, Louis Depalma

Pathology Faculty Publications

B lymphoblastic leukemia (B-ALL) may be associated with recurrent cytogenetic and molecular abnormalities. We describe the fourth-known case of B-ALL associated with the t(8;22)(p11.2q11.2) – a translocation seen more frequently in T lymphoblastic leukemia and acute myelogenous leukemia. This patient’s leukemia involves a combination of additional cytogenetic anomalies not yet described in the literature, including del(11)(q13q23), add(9)(p22), and monosomy 7. Given the role in B cell differentiation of genes in the affected regions, including MEN1 (11q13), ATM (11q22), ETS1(11q23), MLL (11q23), AF9 (9p22), and IKZ-F1 (7p12), this case may provide further insight into B cell leukemogenesis associated with the t(8;22). …

Whole Blood Platelet Aggregation And Release Reaction Testing In Uremic Patients, Jay Zeck, Jason Schallheim, Susie Q. Lew, Louis Depalma

Pathology Faculty Publications

Background: Platelet function analysis utilizing platelet-rich plasma and optical density based aggregometry fails to identify patients at risk for uremia associated complications.

Methods: We employed whole blood platelet aggregation analysis based on impedance as well as determination of ATP release from platelet granules detected by a chemiluminescence method. Ten chronic kidney disease (CKD) stage 4 or 5 predialysis patients underwent platelet evaluation. Our study aims to evaluate this platform in this patient population to determine if abnormalities could be detected. Results. Analysis revealed normal aggregation and ATP release to collagen, ADP, and high-dose ristocetin. ATP release had a low response …

On An Ensemble Algorithm For Clustering Cancer Patient Data, Ran Qi, Dengyuan Wu, Li Sheng, Donald E. Henson, Arnold M. Schwartz, Eric Xu, Kai Xing, Dechang Chen

Pathology Faculty Publications

Background

The TNM staging system is based on three anatomic prognostic factors: Tumor, Lymph Node and Metastasis. However, cancer is no longer considered an anatomic disease. Therefore, the TNM should be expanded to accommodate new prognostic factors in order to increase the accuracy of estimating cancer patient outcome. The ensemble algorithm for clustering cancer data (EACCD) by Chen et al. reflects an effort to expand the TNM without changing its basic definitions. Though results on using EACCD have been reported, there has been no study on the analysis of the algorithm. In this report, we examine various aspects of …