Time Course Of Disease Progression Research Articles

A simple, reproducible technique for establishing leptomeningeal tumors in nude rats

The incidence of leptomeningeal carcinomatosis is on the rise and current treatment modalities have limited efficacy. The development of new treatment strategies has been hampered by the lack of an appropriate animal model that accurately parallels the clinical condition. We have developed a new surgical technique for the establishment of leptomeningeal tumors in rats. Our technique is simple, reproducible and associated with low morbidity and mortality. Tumor implantation resulted in a defined neurological endpoint and a reproducible time course of disease progression using both human medulloblastoma and breast carcinoma cell lines. This animal model provides an appropriate system for testing conventional and new biologic therapies in both early and late stages of leptomeningeal disease.

Longitudinal analysis of behavioral, neurophysiological, viral and immunological effects of SIV infection in rhesus monkeys.

A model is proposed in which a neurovirulent, microglial-passaged, simian immunodeficiency virus (SIV) is used to produce central nervous system (CNS) pathology and behavioral deficits in rhesus monkeys reminiscent of those seen in humans infected with human immunodeficiency virus (HIV). The time course of disease progression was characterized by using functional measures of cognition and motor skill, as well as neurophysiologic monitoring. Concomitant assessment of immunological and virological parameters illustrated correspondence between impaired behavioral performance and viral pathogenesis. Convergent results were obtained from neuropathological findings indicative of significant CNS disease. In ongoing studies, this SIV model is being used to explore the behavioral sequelae of immunodeficiency virus infection, the viral and host factors leading to neurologic dysfunction, and to begin testing potential therapeutic agents.

Mathematical Model of Progressive Renal Disease

A simple mathematical model is proposed that predicts the dynamics of chronic progressive renal disease. The model consists of coupled linear differential equations formed from three state variables, four control parameters, and three parameters related to initial conditions. All have straightforward physical interpretations. Applied to a population of nephrons, the model predicted the hypertrophic and sclerotic features of parenchyma progressing towards end-stage renal disease. Simulation results compared favorably with measurements obtained from the literature involving the subtotal nephrectomy rat model for renal disease. The time course of disease progression and treatment were considered. Also, the implications of the model for designing new diagnostic techniques using ultrasonic analysis are discussed.