Inferring time-derivatives including cell growth rates using Gaussian processes

Often the time derivative of a measured variable is of as much interest as the variable itself. For a growing population of biological cells, for example, the population's growth rate is typically more important than its size. Here we introduce a non-parametric method to infer first and second time derivatives as a function of time from time-series data. Our approach is based on Gaussian processes and applies to a wide range of data. In tests, the method is at least as accurate as others, but has several advantages: it estimates errors both in the inference and in any summary statistics, such as lag times, and allows interpolation with the corresponding error estimation. As illustrations, we infer growth rates of microbial cells, the rate of assembly of an amyloid fibril and both the speed and acceleration of two separating spindle pole bodies. Our algorithm should thus be broadly applicable

Active learning and optimal climate policy

This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education

PHYTOTHERAPY RESEARCH

Two edible wild mushrooms, namely Clitocybe alexandri (Gill.) Konr. (Tricholomataceae) and Rhizopogon roseolus (Cords) T.M. Fries (Rhizopogonaceae), collected from the southwest of Turkey, were tested for their antimicrobial activity by using the disc diffusion method. The ethanol, methanol, diethyl ether, water, ethylacetate and n-hexane extracts from the fruit bodies of mushrooms were assayed against 13 microorganisms. In comparison with the test antibiotics penicillin, novobiocin, nalidixic acid and ampicillin, the methanol extract obtained from the two mushrooms presented significant activity against E. coli, Bacillus subtilis and Enterobacter aerogenes. On the other hand, the ethylacetate extract from C. alexandri was found to be active against Candida albicans and Saccharomyces cerevisiae, whereas the ethanol extract of Rhizopogon roseolus was active against Saccharomyces cerevisiae. This research has shown that various extracts obtained from two macrofungi could be used in vitro to inhibit the growth of some important bacteria and fungi. Copyright (c) 2006 John Wiley & Sons, Ltd

New records of macrofungi from Turkey.

This taxonomic study is based on macrofungi collected Babadağ District (Denizli) in the period 2005-2006. As a result of field and laboratory studies, five new records are presented. These species are Leptopodia elastica, Entoloma incarnatofuscescens, Geastrum minimum, Hygrophorus speciosus and Russula sororia

Predicting streptococcal pharyngitis in adults in primary care: a systematic review of the diagnostic accuracy of symptoms and signs and validation of the Centor score

Background: Stratifying patients with a sore throat into the probability of having an underlying bacterial or viral cause may be helpful in targeting antibiotic treatment. We sought to assess the diagnostic accuracy of signs and symptoms and validate a clinical prediction rule (CPR), the Centor score, for predicting group A ?-haemolytic streptococcal (GABHS) pharyngitis in adults (> 14 years of age) presenting with sore throat symptoms. Methods: A systematic literature search was performed up to July 2010. Studies that assessed the diagnostic accuracy of signs and symptoms and/or validated the Centor score were included. For the analysis of the diagnostic accuracy of signs and symptoms and the Centor score, studies were combined using a bivariate random effects model, while for the calibration analysis of the Centor score, a random effects model was used. Results: A total of 21 studies incorporating 4,839 patients were included in the meta-analysis on diagnostic accuracy of signs and symptoms. The results were heterogeneous and suggest that individual signs and symptoms generate only small shifts in post-test probability (range positive likelihood ratio (+LR) 1.45-2.33, -LR 0.54-0.72). As a decision rule for considering antibiotic prescribing (score ? 3), the Centor score has reasonable specificity (0.82, 95% CI 0.72 to 0.88) and a post-test probability of 12% to 40% based on a prior prevalence of 5% to 20%. Pooled calibration shows no significant difference between the numbers of patients predicted and observed to have GABHS pharyngitis across strata of Centor score (0-1 risk ratio (RR) 0.72, 95% CI 0.49 to 1.06; 2-3 RR 0.93, 95% CI 0.73 to 1.17; 4 RR 1.14, 95% CI 0.95 to 1.37). Conclusions: Individual signs and symptoms are not powerful enough to discriminate GABHS pharyngitis from other types of sore throat. The Centor score is a well calibrated CPR for estimating the probability of GABHS pharyngitis. The Centor score can enhance appropriate prescribing of antibiotics, but should be used with caution in low prevalence settings of GABHS pharyngitis such as primary care