Dean Billheimer

Nonmelanoma skin cancers, including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), are the most common skin cancers, presenting nearly as many cases as all other cancers combined. The current gold-standard for clinical diagnosis of these lesions is histopathologic examination, an invasive, time-consuming procedure. There is thus considerable interest in developing a real-time, automated, noninvasive tool for nonmelanoma skin cancer diagnosis. In this study, we explored the capability of Raman microspectroscopy to provide differential diagnosis of BCC, SCC, inflamed scar tissue, and normal tissue in vivo.

Abstract:

In 1939, an experiment was established on the Jornada Experimental Range to evaluate the effects of shrub removal, rabbit exclusion, furrowing, and seeding in creosotebush [Larrea tridentata (DC.) Cov] vegetation. Sixteen plots (21.3×21.3 m) were laid out in four rows of four plots per row with a buffer zone of 7.6 m between plots and rows. A barbed wire fence excluded cattle and poultry wire fencing excluded lagomorphs. Treatments were factorially applied at two levels. Plant cover in the plots was sampled in 1938 (before treatment), 1947, 1956, 1960, 1967 and 1989 with randomly located, line-intercept transects. Data from all sampling dates were analyzed as a split plot in time and main effects for 1989 tested by analysis of variance for a 2×4 factorial experiment. There were significant (P0.10) year x treatment interactions. Seeding and furrowing treatments were ineffective but lagomorph exclusion and shrub clearing treatments resulted in significant treatment differences for several species. In 1989, basal area of spike dropseed (Sporobolus contractus A.S. Hitchc.) was 30-fold greater on the lagomorph excluded than on the lagomorph unexcluded treatment. Canopy cover of honey mesquite (Prosopis glandulosa Torr. var. glandulosa), tarbush (Flourensia cernua DC.) and mariola (Parthenium incanum H.B.K.) were affected by lagomorph exclusion. None of the responses were viewed as successional in nature. They principally represented individual species sensitivities to either absence of a primary herbivore or removal of aboveground shrub biomass. Though the physical treatments could be regarded as relatively severe disturbances of the system, the impacts on community vegetation dynamics were relatively insignificant. © 1993 Springer-Verlag.

PMID: 19837981;PMCID: PMC2830836;Abstract:

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.

PMID: 11283391;Abstract:

Background and Purpose - We sought to study the range of entry criteria and baseline characteristics in acute stroke trials and to understand their effects on patient outcomes. Methods - Randomized, placebo-controlled therapeutic trials in patients with acute ischemic stroke were identified. Entry criteria, baseline clinical characteristics, and outcome were extracted for the placebo group of each trial. The relationship between key variables was then determined. Results - Across 90 placebo groups identified, there was great variation in entry criteria and outcome measures. This was associated with divergent outcomes; for example, in some studies most placebo group patients died, while in other studies nearly all had no disability. Entry criteria were significantly correlated with outcome; for example, higher age cutoff for study entry correlated with 3-month mortality. Entry criteria also predicted baseline clinical characteristics; for example, wider time window for study entry correlated directly with time to treatment and inversely with stroke severity (initial National Institutes of Health Stroke Scale score). Baseline characteristics predicted outcome. Greater stroke severity predicted higher 3-month mortality rate; despite this, successful thrombolytic trials have enrolled more severe strokes than most trials. The mean age of enrollees also predicted 3-month mortality and was inversely related to percentage of patients with 3-month Barthel Index score ≥95. The strongest predictors of 3-month mortality were obtained with multivariate models. Conclusions - Acute stroke studies vary widely in entry criteria and outcome measures. Across multiple studies, differences in entry criteria, and the baseline clinical characteristics they predict, influence patient outcomes along a continuum. In some studies, enrolling a specific subset of patients may have improved the chances of identifying a treatment-related effect, while in others, such chances may have been reduced. These findings may be useful in the design of future stroke therapeutic trials.

Abstract:

The relative abundance of different species characterizes the structure of a biological community. We analyze an experiment addressing the relationship between omnivorous feeding linkages and community stability. Our goal is to determine whether communities with different predator compositions respond similarly to environmental disturbance. To evaluate these data, we develop a hierarchical statistical model that combines Aitchison's logistic normal distribution with a conditional multinomial observation distribution. In addition, we present an algebra for compositions that includes addition, scalar multiplication, and a metric for differences in compositions. The algebra aids interpretation of treatment effects, treatment interactions, and covariates. Markov chain Monte Carlo (MCMC) is used for inference in a Bayesian framework. Our experimental results indicate that a high degree of omnivory can help to stabilize community dynamics and prevent radical shifts in community composition. This result is at odds with classical food-web predictions, but agrees with recent theoretical formulations.