Inferring epidemic contact structure from phylogenetic trees.

Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Innovative method for carbon dioxide determination in human postmortem cardiac gas samples using headspace-gas chromatography-mass spectrometry and stable labeled isotope as internal standard.

A novel approach to measure carbon dioxide (CO2) in gaseous samples, based on a precise and accurate quantification by (13)CO2 internal standard generated in situ is presented. The main goal of this study was to provide an innovative headspace-gas chromatography-mass spectrometry (HS-GC-MS) method applicable in the routine determination of CO2. The main drawback of the GC methods discussed in the literature for CO2 measurement is the lack of a specific internal standard necessary to perform quantification. CO2 measurement is still quantified by external calibration without taking into account analytical problems which can often occur considering gaseous samples. To avoid the manipulation of a stable isotope-labeled gas, we have chosen to generate in situ an internal labeled standard gas ((13)CO2) on the basis of the stoichiometric formation of CO2 by the reaction of hydrochloric acid (HCl) with sodium hydrogen carbonate (NaH(13)CO3). This method allows a precise measurement of CO2 concentration and was validated on various human postmortem gas samples in order to study its efficiency.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Energy expenditure by doubly labeled water: validation in humans and proposed calculation.

To further validate the doubly labeled water method for measurement of CO2 production and energy expenditure in humans, we compared it with near-continuous respiratory gas exchange in nine healthy young adult males. Subjects were housed in a respiratory chamber for 4 days. Each received 2H2(18)O at either a low (n = 6) or a moderate (n = 3) isotope dose. Low and moderate doses produced initial 2H enrichments of 5 and 10 X 10(-3) atom percent excess, respectively, and initial 18O enrichments of 2 and 2.5 X 10(-2) atom percent excess, respectively. Total body water was calculated from isotope dilution in saliva collected at 4 and 5 h after the dose. CO2 production was calculated by the two-point method using the isotopic enrichments of urines collected just before each subject entered and left the chamber. Isotope enrichments relative to predose samples were measured by isotope ratio mass spectrometry. At low isotope dose, doubly labeled water overestimated average daily energy expenditure by 8 +/- 9% (SD) (range -7 to 22%). At moderate dose the difference was reduced to +4 +/- 5% (range 0-9%). The isotope elimination curves for 2H and 18O from serial urines collected from one of the subjects showed expected diurnal variations but were otherwise quite smooth. The overestimate may be due to approximations in the corrections for isotope fractionation and isotope dilution. An alternative approach to the corrections is presented that reduces the overestimate to 1%.

The use of classification and regression trees to predict the likelihood of seasonal influenza.

Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.

Large multi-gene phylogenetic trees of the grasses (Poaceae): progress towards complete tribal and generic level sampling.

In this paper we included a very broad representation of grass family diversity (84% of tribes and 42% of genera). Phylogenetic inference was based on three plastid DNA regions rbcL, matK and trnL-F, using maximum parsimony and Bayesian methods. Our results resolved most of the subfamily relationships within the major clades (BEP and PACCMAD), which had previously been unclear, such as, among others the: (i) BEP and PACCMAD sister relationship, (ii) composition of clades and the sister-relationship of Ehrhartoideae and Bambusoideae + Pooideae, (iii) paraphyly of tribe Bambuseae, (iv) position of Gynerium as sister to Panicoideae, (v) phylogenetic position of Micrairoideae. With the presence of a relatively large amount of missing data, we were able to increase taxon sampling substantially in our analyses from 107 to 295 taxa. However, bootstrap support and to a lesser extent Bayesian inference posterior probabilities were generally lower in analyses involving missing data than those not including them. We produced a fully resolved phylogenetic summary tree for the grass family at subfamily level and indicated the most likely relationships of all included tribes in our analysis.

A protocol for preparing GFP-labeled neurons previously imaged in vivo and in slice preparations for light and electron microscopic analysis.

In vivo imaging of green fluorescent protein (GFP)-labeled neurons in the intact brain is being used increasingly to study neuronal plasticity. However, interpreting the observed changes as modifications in neuronal connectivity needs information about synapses. We show here that axons and dendrites of GFP-labeled neurons imaged previously in the live mouse or in slice preparations using 2-photon laser microscopy can be analyzed using light and electron microscopy, allowing morphological reconstruction of the synapses both on the imaged neurons, as well as those in the surrounding neuropil. We describe how, over a 2-day period, the imaged tissue is fixed, sliced and immuno-labeled to localize the neurons of interest. Once embedded in epoxy resin, the entire neuron can then be drawn in three dimensions (3D) for detailed morphological analysis using light microscopy. Specific dendrites and axons can be further serially thin sectioned, imaged in the electron microscope (EM) and then the ultrastructure analyzed on the serial images.

Random mating with a finite number of matings.

Random mating is the null model central to population genetics. One assumption behind random mating is that individuals mate an infinite number of times. This is obviously unrealistic. Here we show that when each female mates a finite number of times, the effective size of the population is substantially decreased.

Phase-I/II radio-immunotherapy study with Iodine-131-labeled anti-CEA monoclonal antibody F6 F(ab')2 in patients with non-resectable liver metastases from colorectal cancer.

Experimental studies in nude mice with human colon-carcinoma grafts demonstrated the therapeutic efficiency of F(ab')2 fragments to carcinoembryonic antigen (CEA) labeled with a high dose of 131Iodine. A phase I/II study was designed to determine the maximum tolerated dose of 131I-labeled F(ab')2 fragments (131I-F(ab')2) from anti-CEA monoclonal antibody F6, its limiting organ toxicity and tumor uptake. Ten patients with non-resectable liver metastases from colorectal cancer (9 detected by CT scan and 1 by laparotomy) were treated with 131I-F(ab')2, doses ranging from 87 mCi to 300 mCi for the first 5 patients, with a constant 300-mCi dose for the last 5 patients. For all the patients, autologous bone marrow was harvested and stored before treatment. Circulating CEA ranged from 2 to 126 ng/ml. No severe adverse events were observed during or immediately following infusion of therapeutic doses. The 9 patients with radiologic evidence of liver metastases showed uptake of 131I-F(ab')2 in the metastases, as observed by single-photon-emission tomography. The only toxicity was hematologic, and no severe aplasia was observed when up to 250 mCi was infused. At the 300-mCi dose, 5 out of 6 patients presented grade-3 or -4 hematologic toxicity, with a nadir for neutrophils and thrombocytes ranging from 25 to 35 days after infusion. In these 5 cases, bone marrow was re-infused. No clinical complications were observed during aplasia. The tumor response could be evaluated in 9 out of 10 patients. One patient showed a partial response of one small liver metastasis (2 cm in diameter) and a stable evolution of the other metastases, 2 patients had stable disease, and 6 showed tumor progression at the time of evaluation (2 or 3 months after injection) by CT scan. This phase-I/II study demonstrated that a dose of 300 mCi of 131I-F(ab')2 from the anti-CEA Mab F6 is well tolerated with bone-marrow rescue, whereas a dose of 200 mCi can be infused without severe bone-marrow toxicity.

The average crossing number of equilateral random polygons.

In this paper, we study the average crossing number of equilateral random walks and polygons. We show that the mean average crossing number ACN of all equilateral random walks of length n is of the form . A similar result holds for equilateral random polygons. These results are confirmed by our numerical studies. Furthermore, our numerical studies indicate that when random polygons of length n are divided into individual knot types, the for each knot type can be described by a function of the form where a, b and c are constants depending on and n0 is the minimal number of segments required to form . The profiles diverge from each other, with more complex knots showing higher than less complex knots. Moreover, the profiles intersect with the ACN profile of all closed walks. These points of intersection define the equilibrium length of , i.e., the chain length at which a statistical ensemble of configurations with given knot type -upon cutting, equilibration and reclosure to a new knot type -does not show a tendency to increase or decrease . This concept of equilibrium length seems to be universal, and applies also to other length-dependent observables for random knots, such as the mean radius of gyration Rg.