Occurrence of heavy metals (Hg, Cd, and Pb) and polychlorinated biphenyls in salted anchovies.

The most popular brands of salted anchovies (Engraulis encrasicolus) from the Mediterranean Sea and Atlantic Ocean were purchased from several Italian supermarkets and grocery stores. Heavy metal (Hg, Cd, and Pb) and polychlorinated biphenyl (PCB) levels were determined and assessed by comparing the concentrations in these samples with the maximum permissible limits set by the European Union (Reg EC 629/2008 and Reg EC 1881/2006 [Off. J. Eur. Union L 173:3-9 and 364:5-24, respectively]). The Hg and Cd levels were higher than those of Pb in all samples examined. For Hg and Pb, the concentrations recorded in this study were below the authorized limits, while an appreciable percentage of samples from both locations (Mediterranean Sea, 35%, and Atlantic Ocean, 25%) showed Cd levels exceeding the threshold recommended for human consumption. Concerning PCBs, the results of principal component analysis showed that samples from the two different marine areas appeared to be discriminate, with Mediterranean anchovies more contaminated than the others, in spite of their lower lipid content. However, anchovy samples from both locations had dioxinlike-PCB levels (Mediterranean Sea, 0.011 pg World Health Organization toxic equivalency [WHO-TEQ] g(-1), wet weight, and Atlantic Ocean, 0.007 pg WHO-TEQ g(-1), wet weight) that were below the WHO-TEQ maximum concentration set by European regulation. The results of this study will help in generating data needed for the assessment of heavy metal and PCB intake from this food

Geodesic acoustic modes in a fluid model of tokamak plasma : the effects of finite beta and collisionality

Starting from the Braginskii equations, relevant for the tokamak edge region, a complete set of nonlinear equations for the geodesic acoustic modes (GAM) has been derived which includes collisionality, plasma beta and external sources of particle, momentum and heat. Local linear analysis shows that the GAM frequency increases with collisionality at low radial wave number $k_{r}$ and decreases at high $k_{r}$. GAM frequency also decreases with plasma beta. Radial profiles of GAM frequency for two Tore Supra shots, which were part of a collisionality scan, are compared with these calculations. Discrepency between experiment and theory is observed, which seems to be explained by a finite $k_{r}$ for the GAM when flux surface averaged density $\langle n \rangle$ and temperature $\langle T \rangle$ are assumed to vanish. It is shown that this agreement is incidental and self-consistent inclusion of $\langle n \rangle$ and $\langle T \rangle$ responses enhances the disagreement more with $k_r$ at high $k_{r}$ . So the discrepancy between the linear GAM calculation, (which persist also for more "complete" linear models such as gyrokinetics) can probably not be resolved by simply adding a finite $k_{r}$

Evaluation of Feature Selection Techniques for Breast Cancer Risk Prediction

This study evaluates several feature ranking techniques together with some classifiers based on machine learning to identify relevant factors regarding the probability of contracting breast cancer and improve the performance of risk prediction models for breast cancer in a healthy population. The dataset with 919 cases and 946 controls comes from the MCC-Spain study and includes only environmental and genetic features. Breast cancer is a major public health problem. Our aim is to analyze which factors in the cancer risk prediction model are the most important for breast cancer prediction. Likewise, quantifying the stability of feature selection methods becomes essential before trying to gain insight into the data. This paper assesses several feature selection algorithms in terms of performance for a set of predictive models. Furthermore, their robustness is quantified to analyze both the similarity between the feature selection rankings and their own stability. The ranking provided by the SVM-RFE approach leads to the best performance in terms of the area under the ROC curve (AUC) metric. Top-47 ranked features obtained with this approach fed to the Logistic Regression classifier achieve an AUC = 0.616. This means an improvement of 5.8% in comparison with the full feature set. Furthermore, the SVM-RFE ranking technique turned out to be highly stable (as well as Random Forest), whereas relief and the wrapper approaches are quite unstable. This study demonstrates that the stability and performance of the model should be studied together as Random Forest and SVM-RFE turned out to be the most stable algorithms, but in terms of model performance SVM-RFE outperforms Random Forest.The study was partially funded by the “Accion Transversal del Cancer”, approved on the Spanish Ministry Council on the 11th October 2007, by the Instituto de Salud Carlos III-FEDER (PI08/1770, PI08/0533, PI08/1359, PS09/00773, PS09/01286, PS09/01903, PS09/02078, PS09/01662, PI11/01403, PI11/01889, PI11/00226, PI11/01810, PI11/02213, PI12/00488, PI12/00265, PI12/01270, PI12/00715, PI12/00150), by the Fundación Marqués de Valdecilla (API 10/09), by the ICGC International Cancer Genome Consortium CLL, by the Junta de Castilla y León (LE22A10-2), by the Consejería de Salud of the Junta de Andalucía (PI-0571), by the Conselleria de Sanitat of the Generalitat Valenciana (AP 061/10), by the Recercaixa (2010ACUP 00310), by the Regional Government of the Basque Country by European Commission grants FOOD-CT- 2006-036224- HIWATE, by the Spanish Association Against Cancer (AECC) Scientific Foundation, by the The Catalan Government DURSI grant 2009SGR1489. Samples: Biological samples were stored at the Parc de Salut MAR Biobank (MARBiobanc; Barcelona) which is supported by Instituto de Salud Carlos III FEDER (RD09/0076/00036). Furthermore, at the Public Health Laboratory from Gipuzkoa and the Basque Biobank. Furthermore, sample collection was supported by the Xarxa de Bancs de Tumors de Catalunya sponsored by Pla Director d’Oncologia de Catalunya (XBTC). Biological samples were stored at the “Biobanco La Fe” which is supported by Instituto de Salud Carlos III (RD 09 0076/00021) and FISABIO biobanking, which is supported by Instituto de Salud Carlos III (RD09 0076/00058).S

In vitro and in vivo evaluation of a new active heat moisture exchanger.

INTRODUCTION: In order to improve the efficiency of heat moisture exchangers (HMEs), new hybrid humidifiers (active HMEs) that add water and heat to HMEs have been developed. In this study we evaluated the efficiency, both in vitro and in vivo, of a new active HME (the Performer; StarMed, Mirandola, Italy) as compared with that of existing HMEs (Hygroster and Hygrobac; Mallinckrodt, Mirandola, Italy). METHODS: We tested the efficiency by measuring the temperature and absolute humidity (AH) in vitro using a test lung ventilated at three levels of minute ventilation (5, 10 and 15 l/min) and at two tidal volumes (0.5 and 1 l), and in vivo in 42 patients with acute lung injury (arterial oxygen tension/fractional inspired oxygen ratio 283 +/- 72 mmHg). We also evaluated the efficiency in vivo after 12 hours. RESULTS: In vitro, passive Performer and Hygrobac had higher airway temperature and AH (29.2 +/- 0.7 degrees C and 29.2 +/- 0.5 degrees C, [P < 0.05]; AH: 28.9 +/- 1.6 mgH2O/l and 28.1 +/- 0.8 mgH2O/l, [P < 0.05]) than did Hygroster (airway temperature: 28.1 +/- 0.3 degrees C [P < 0.05]; AH: 27 +/- 1.2 mgH2O/l [P < 0.05]). Both devices suffered a loss of efficiency at the highest minute ventilation and tidal volume, and at the lowest minute ventilation. Active Performer had higher airway temperature and AH (31.9 +/- 0.3 degrees C and 34.3 +/- 0.6 mgH2O/l; [P < 0.05]) than did Hygrobac and Hygroster, and was not influenced by minute ventilation or tidal volume. In vivo, the efficiency of passive Performer was similar to that of Hygrobac but better than Hygroster, whereas Active Performer was better than both. The active Performer exhibited good efficiency when used for up to 12 hours in vivo. CONCLUSION: This study showed that active Performer may provide adequate conditioning of inspired gases, both as a passive and as an active device

Purple sulfur bacteria fix N-2 via molybdenum-nitrogenase in a low molybdenum Proterozoic ocean analogue

Biological N-2 fixation was key to the expansion of life on early Earth. The N-2-fixing microorganisms and the nitrogenase type used in the Proterozoic are unknown, although it has been proposed that the canonical molybdenum-nitrogenase was not used due to low molybdenum availability. We investigate N-2 fixation in Lake Cadagno, an analogue system to the sulfidic Proterozoic continental margins, using a combination of biogeochemical, molecular and single cell techniques. In Lake Cadagno, purple sulfur bacteria (PSB) are responsible for high N-2 fixation rates, to our knowledge providing the first direct evidence for PSB in situ N-2 fixation. Surprisingly, no alternative nitrogenases are detectable, and N-2 fixation is exclusively catalyzed by molybdenum-nitrogenase. Our results show that molybdenum-nitrogenase is functional at low molybdenum conditions in situ and that in contrast to previous beliefs, PSB may have driven N-2 fixation in the Proterozoic ocean. N-2 fixation was key to the expansion of life on Earth, but which organisms fixed N-2 and if Mo-nitrogenase was functional in the low Mo early ocean is unknown. Here, the authors show that purple sulfur bacteria fix N-2 using Mo-nitrogenase in a Proterozoic ocean analogue, despite low Mo conditions

A Semiautomatic Method for Multiple Sclerosis Lesion Segmentation on Dual-Echo MR Imaging: Application in a Multicenter Context

BACKGROUND AND PURPOSE: The automatic segmentation of MS lesions could reduce time required for image processing together with inter- and intraoperator variability for research and clinical trials. A multicenter validation of a proposed semiautomatic method for hyperintense MS lesion segmentation on dual-echo MR imaging is presented. MATERIALS AND METHODS: The classification technique used is based on a region-growing approach starting from manual lesion identification by an expert observer with a final segmentation-refinement step. The method was validated in a cohort of 52 patients with relapsing-remitting MS, with dual-echo images acquired in 6 different European centers. RESULTS: We found a mathematic expression that made the optimization of the method independent of the need for a training dataset. The automatic segmentation was in good agreement with the manual segmentation (dice similarity coefficient = 0.62 and root mean square error = 2 mL). Assessment of the segmentation errors showed no significant differences in algorithm performance between the different MR scanner manufacturers (P > .05). CONCLUSIONS: The method proved to be robust, and no center-specific training of the algorithm was required, offering the possibility for application in a clinical setting. Adoption of the method should lead to improved reliability and less operator time required for image analysis in research and clinical trials in MS