Relative protein quantification by isobaric SILAC with immonium ion splitting (ISIS)

Metabolic labeling techniques have recently become popular tools for the quantitative profiling of proteomes. Classical stable isotope labeling with amino acids in cell cultures (SILAC) uses pairs of heavy/light isotopic forms of amino acids to introduce predictable mass differences in protein samples to be compared. After proteolysis, pairs of cognate precursor peptides can be correlated, and their intensities can be used for mass spectrometry-based relative protein quantification. We present an alternative SILAC approach by which two cell cultures are grown in media containing isobaric forms of amino acids, labeled either with 13C on the carbonyl (C-1) carbon or 15N on backbone nitrogen. Labeled peptides from both samples have the same nominal mass and nearly identical MS/MS spectra but generate upon fragmentation distinct immonium ions separated by 1 amu. When labeled protein samples are mixed, the intensities of these immonium ions can be used for the relative quantification of the parent proteins. We validated the labeling of cellular proteins with valine, isoleucine, and leucine with coverage of 97% of all tryptic peptides. We improved the sensitivity for the detection of the quantification ions on a pulsing instrument by using a specific fast scan event. The analysis of a protein mixture with a known heavy/light ratio showed reliable quantification. Finally the application of the technique to the analysis of two melanoma cell lines yielded quantitative data consistent with those obtained by a classical two-dimensional DIGE analysis of the same samples. Our method combines the features of the SILAC technique with the advantages of isobaric labeling schemes like iTRAQ. We discuss advantages and disadvantages of isobaric SILAC with immonium ion splitting as well as possible ways to improve it

Advanced mapping of environmental data: Geostatistics, Machine Learning and Bayesian Maximum Entropy

This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.

Indirect likelihood inference

Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Zn. We call this the maximum indirect likelihood (MIL) estimator. We also propose a computationally tractable Bayesian version of the estimator which we refer to as a Bayesian Indirect Likelihood (BIL) estimator. In most cases, the density of the statistic will be of unknown form, and we develop simulated versions of the MIL and BIL estimators. We show that the indirect likelihood estimators are consistent and asymptotically normally distributed, with the same asymptotic variance as that of the corresponding efficient two-step GMM estimator based on the same statistic. However, our likelihood-based estimators, by taking into account the full finite-sample distribution of the statistic, are higher order efficient relative to GMM-type estimators. Furthermore, in many cases they enjoy a bias reduction property similar to that of the indirect inference estimator. Monte Carlo results for a number of applications including dynamic and nonlinear panel data models, a structural auction model and two DSGE models show that the proposed estimators indeed have attractive finite sample properties.

Prognostic ability of practitioners of traditional arabic medicine: comparison with Western methods through a relative patient progress scale.

The ancient Greek medical theory based on balance or imbalance of humors disappeared in the western world, but does survive elsewhere. Is this survival related to a certain degree of health care efficiency? We explored this hypothesis through a study of classical Greco-Arab medicine in Mauritania. Modern general practitioners evaluated the safety and effectiveness of classical Arabic medicine in a Mauritanian traditional clinic, with a prognosis/follow-up method allowing the following comparisons: (i) actual patient progress (clinical outcome) compared with what the traditional 'tabib' had anticipated (= prognostic ability) and (ii) patient progress compared with what could be hoped for if the patient were treated by a modern physician in the same neighborhood. The practice appeared fairly safe and, on average, clinical outcome was similar to what could be expected with modern medicine. In some cases, patient progress was better than expected. The ability to correctly predict an individual's clinical outcome did not seem to be better along modern or Greco-Arab theories. Weekly joint meetings (modern and traditional practitioners) were spontaneously organized with a modern health centre in the neighborhood. Practitioners of a different medical system can predict patient progress. For the patient, avoiding false expectations with health care and ensuring appropriate referral may be the most important. Prognosis and outcome studies such as the one presented here may help to develop institutions where patients find support in making their choices, not only among several treatment options, but also among several medical systems.

Life Cycle and Fecundity Analysis of Lutzomyia shannoni (Dyar) (Diptera: Psychodidae)

The life cycle of Lutzomyia shannoni (Dyar), was described for laboratory conditions with maximum daily temperatures of 27-30°C, minimum daily temperatures of 22-27°C and relative humidity between 87-99 %. Life cycle in each stage was as follows: egg 6-12 days (ave. 8.5 days); first stage larva 5-13 days (ave. 9.6 days); second stage larva 4-13 days (ave. 9.2 days ); third stage larva 5-19 days (ave. 11.8 days); fourth stage larva 7-37 days (ave. 19.9 days); pupa 7-32 days (ave. 15.2 days). The life expectancy of adults ranged from 4 to 15 days (ave. 8.6 days). The entire egg to adult period ranged from 36 to 74 days (ave. 54.6 days). On average, each female oviposited 22.7 eggs; the average egg retention per female was 24.3 eggs.

Alveolar echinococcosis: from a deadly disease to a well-controlled infection. Relative survival and economic analysis in Switzerland over the last 35 years.

BACKGROUND/AIMS: Alveolar echinococcosis (AE) is a serious liver disease. The aim of this study was to explore the long-term prognosis of AE patients, the burden of this disease in Switzerland and the cost-effectiveness of treatment. METHODS: Relative survival analysis was undertaken using a national database with 329 patient records. 155 representative cases had sufficient details regarding treatment costs and patient outcome to estimate the financial implications and treatment costs of AE. RESULTS: For an average 54-year-old patient diagnosed with AE in 1970 the life expectancy was estimated to be reduced by 18.2 and 21.3 years for men and women, respectively. By 2005 this was reduced to approximately 3.5 and 2.6 years, respectively. Patients undergoing radical surgery had a better outcome, whereas the older patients had a poorer prognosis than the younger patients. Costs amount to approximately Euro108,762 per patient. Assuming the improved life expectancy of AE patients is due to modern treatment the cost per disability-adjusted life years (DALY) saved is approximately Euro6,032. CONCLUSIONS: Current treatments have substantially improved the prognosis of AE patients compared to the 1970s. The cost per DALY saved is low compared to the average national annual income. Hence, AE treatment is highly cost-effective in Switzerland.