Automated classification of evoked quantal events.

We provide both theoretical and computational improvements to the analysis of synaptic transmission data. Theoretically, we demonstrate the correlation structure of observations within evoked postsynaptic potentials (EPSP) are consistent with multiple random draws from a common autoregressive moving-average (ARMA) process of order (2, 2). We use this observation and standard time series results to construct a statistical hypothesis testing procedure for determining whether a given trace is an EPSP. Computationally, we implement this method in R, a freeware statistical language, which reduces the amount of time required for the investigator to classify traces into EPSPs or non-EPSPs and eliminates investigator subjectivity from this classification. In addition, we provide a computational method for calculating common functionals of EPSPs (peak amplitude, decay rate, etc.). The methodology is freely available over the internet. The automated procedure to index the quantal characteristics greatly facilitates determining if any one or multiple parameters are changing due to experimental conditions. In our experience, the software reduces the time required to perform these analyses from hours to minutes.

Self-modeling structure of evoked postsynaptic potentials.

With the simplicity of the synaptic structure and physiology at neuromuscular junctions (NMJs) of crayfish and the given transmitter being released in quantal packets, a detailed assessment in the fundamental processes of chemical synaptic transmission is possible. Since the quantal event is the basic element of transmission, we consider an approach to further understand the characteristics of quantal responses. In this study, we introduce a method for combining information across excitatory postsynaptic potentials (EPSPs) that are quantal in nature. The method is called self-modeling regression, known in the statistics literature as SEMOR. This method illustrates that the differing timing and heights of EPSPs can be described with four coefficients measuring affine (shift and scale) transformations of the x and y axes. We demonstrate that this relationship allows us to provide a unified schema for the many functionals currently used in the literature, such as peak amplitude, tau, latency, area under the curve, or decay time. Computer code in R is available on the internet to perform the analysis.

Geographic & age variations in invasive cervical cancer in Kentucky, 1995-1999.

The incidence rate of invasive cervical cancer in Kentucky is among the highest in the United States. Data from the Kentucky Cancer Registry and the National Cancer Institute (NCI) show that in 1998, Kentucky's invasive cervical cancer incidence rate was 49% higher than the national rate (11.2 per 100,000 women versus 7.5 per 100,000 women). As with most diseases, the incidence of invasive cervical cancer varies by both time and geographic location. As noted in a previous article by Wyatt et al, this variation is tied to the prevalence of established risk factors for cervical cancer over time and place. To document Kentucky's invasive cervical cancer incidence patterns, incident cases over a five-year period (1995-1999) were analyzed by place (Area Development District, ADD) and age.