Testing the accuracy of methods for reconstructing ancestral states of continuous characters.

Many methods are available for estimating ancestral values of continuous characteristics, but little is known about how well these methods perform. Here we compare six methods: linear parsimony, squared-change parsimony, one-parameter maximum likelihood (Brownian motion), two-parameter maximum likelihood (Ornstein-Uhlenbeck process), and independent comparisons with and without branch-length information. We apply these methods to data from 20 morphospecies of Pleistocene planktic Foraminifera in order to estimate ancestral size and shape variables, and compare these estimates with measurements on fossils close to the phylogenetic position of 13 ancestors. No method produced accurate estimates for any variable: estimates were consistently less good as predictors of the observed values than were the averages of the observed values. The two-parameter maximum-likelihood model consistently produces the most accurate size estimates overall. Estimation of ancestral sizes is confounded by an evolutionary trend towards increasing size. Shape showed no trend but was still estimated very poorly: we consider possible reasons. We discuss the implications of our results for the use of estimates of ancestral characteristics.     

Location of the isoleucine arrest point in CHO and 3T3 cells

An isoleucine arrest point in G1 was determined by two methods for CHO and 3T3 cells. In the first method the fraction of cells entering S after isoleucine deprivation was assessed by [³H]thymidine labelling and autoradiography. In the second method cells entering S after isoleucine deprivation were identified by double-label autoradiography using [³H] and [¹⁴C]thymidine. From the fraction of cells entering S, determined by the two methods, the arrest point in G1 (and entry into G0) is located within the last 40 min of G1.     

Reduction in size of prolactin-secreting tumours in men treated with pergolide.

The effect of pergolide mesylate was studied in two previously untreated men with large prolactinomas and exceptionally high prolactin concentrations. The study was designed to determine whether pergolide would be effective in alleviating symptoms, correcting hormonal abnormalities and shrinking the tumour. Starting with 50 micrograms daily the dose of pergolide was slowly increased over 10 weeks to 1 mg once daily, when repeat assessment was performed. Both patients reported complete relief of symptoms, with no side effects. Serum prolactin concentration was suppressed to normal in both subjects, and evidence to suggest tumour shrinkage was observed. Pergolide appears to be effective treatment for men with large prolactinomas.     

A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.