Defining the role of IL-15 trans-presentation by distinct cell-types during the development and homeostasis of Natural Killer and invariant Natural Killer T cells

The immuno-regulatory functions displayed by NK and iNKT cells have highlighted their importance as key lymphocytes involved in innate and adaptive immunity. Therefore, understanding the dynamics influencing the generation of NK and iNKT cells is extremely important. IL-15 has been shown to provide a critical signal throughout the development and homeostasis of NK and iNKT cells; however, the cellular source of IL-15 has remained unclear. In this investigation, I provide evidence that the cell-type providing IL-15 to NK and iNKT cells via trans-presentation is determined by the tissue site and the maturation status of NK and iNKT cells. For NK cells, I revealed the non-hematopoietic compartment provides IL-15 to NK cells in the early stages of development while hematopoietic cells were crucial for the generation and maintenance of mature NK cells. Regarding iNKT cells in the thymus, IL-15 trans-presentation by non-hematopoietic cells was crucial for the survival of mature iNKT cells. In the liver, both hematopoietic and non-hematopoietic compartments provided IL-15 to both immature and mature iNKT cells. This IL-15 signal helped mediate the survival and proliferation of both NK and iNKT cells as well as induce the functional maturation of mature iNKT cells via enhanced T-bet expression. In conclusion, my work illustrates an important notion that the immunological niche of NK and iNKT cells is tightly regulated and that this regulation is meticulously influenced by the tissue microenvironment.

NONLINEAR TIME SERIES/SYSTEM ANALYSIS (STATE-SPACE, DYNAMICS, INTERVENTION, RESILIENCE, KALMAN)

A discussion of nonlinear dynamics, demonstrated by the familiar automobile, is followed by the development of a systematic method of analysis of a possibly nonlinear time series using difference equations in the general state-space format. This format allows recursive state-dependent parameter estimation after each observation thereby revealing the dynamics inherent in the system in combination with random external perturbations.^ The one-step ahead prediction errors at each time period, transformed to have constant variance, and the estimated parametric sequences provide the information to (1) formally test whether time series observations y(,t) are some linear function of random errors (ELEM)(,s), for some t and s, or whether the series would more appropriately be described by a nonlinear model such as bilinear, exponential, threshold, etc., (2) formally test whether a statistically significant change has occurred in structure/level either historically or as it occurs, (3) forecast nonlinear system with a new and innovative (but very old numerical) technique utilizing rational functions to extrapolate individual parameters as smooth functions of time which are then combined to obtain the forecast of y and (4) suggest a measure of resilience, i.e. how much perturbation a structure/level can tolerate, whether internal or external to the system, and remain statistically unchanged. Although similar to one-step control, this provides a less rigid way to think about changes affecting social systems.^ Applications consisting of the analysis of some familiar and some simulated series demonstrate the procedure. Empirical results suggest that this state-space or modified augmented Kalman filter may provide interesting ways to identify particular kinds of nonlinearities as they occur in structural change via the state trajectory.^ A computational flow-chart detailing computations and software input and output is provided in the body of the text. IBM Advanced BASIC program listings to accomplish most of the analysis are provided in the appendix. ^