Heavy metal ions are potent inhibitors of protein folding.

Environmental and occupational exposure to heavy metals such as cadmium, mercury and lead results in severe health hazards including prenatal and developmental defects. The deleterious effects of heavy metal ions have hitherto been attributed to their interactions with specific, particularly susceptible native proteins. Here, we report an as yet undescribed mode of heavy metal toxicity. Cd2+, Hg2+ and Pb2+ proved to inhibit very efficiently the spontaneous refolding of chemically denatured proteins by forming high-affinity multidentate complexes with thiol and other functional groups (IC(50) in the nanomolar range). With similar efficacy, the heavy metal ions inhibited the chaperone-assisted refolding of chemically denatured and heat-denatured proteins. Thus, the toxic effects of heavy metal ions may result as well from their interaction with the more readily accessible functional groups of proteins in nascent and other non-native form. The toxic scope of heavy metals seems to be substantially larger than assumed so far.

Identifying the unmet health needs of patients with congenital hypogonadotropic hypogonadism using a web-based needs assessment: implications for online interventions and peer-to-peer support.

BACKGROUND: Patients with rare diseases such as congenital hypogonadotropic hypogonadism (CHH) are dispersed, often challenged to find specialized care and face other health disparities. The internet has the potential to reach a wide audience of rare disease patients and can help connect patients and specialists. Therefore, this study aimed to: (i) determine if web-based platforms could be effectively used to conduct an online needs assessment of dispersed CHH patients; (ii) identify the unmet health and informational needs of CHH patients and (iii) assess patient acceptability regarding patient-centered, web-based interventions to bridge shortfalls in care. METHODS: A sequential mixed-methods design was used: first, an online survey was conducted to evaluate health promoting behavior and identify unmet health and informational needs of CHH men. Subsequently, patient focus groups were held to explore specific patient-identified targets for care and to examine the acceptability of possible online interventions. Descriptive statistics and thematic qualitative analyses were used. RESULTS: 105 male participants completed the online survey (mean age 37 ± 11, range 19-66 years) representing a spectrum of patients across a broad socioeconomic range and all but one subject had adequate healthcare literacy. The survey revealed periods of non-adherence to treatment (34/93, 37%) and gaps in healthcare (36/87, 41%) exceeding one year. Patient focus groups identified lasting psychological effects related to feelings of isolation, shame and body-image concerns. Survey respondents were active internet users, nearly all had sought CHH information online (101/105, 96%), and they rated the internet, healthcare providers, and online community as equally important CHH information sources. Focus group participants were overwhelmingly positive regarding online interventions/support with links to reach expert healthcare providers and for peer-to-peer support. CONCLUSION: The web-based needs assessment was an effective way to reach dispersed CHH patients. These individuals often have long gaps in care and struggle with the psychosocial sequelae of CHH. They are highly motivated internet users seeking information and tapping into online communities and are receptive to novel web-based interventions addressing their unmet needs.

Genesis of the Jurassic carbonate-hosted Pb-Zn deposits of Jebel Ressas (North-eastern Tunisia): Evidence from mineralogy, petrography and trace metal contents and isotope (O, C, S, Pb) geochemistry

The Jebel Ressas Pb-Zn deposits in North-Eastern Tunisia occur mainly as open-space fillings (lodes, tectonic breccia cements) in bioclastic limestones of the Upper Jurassic Ressas Formation and along the contact of this formation with Triassic rocks. The galena-sphalerite association and their alteration products (cerussite, hemimorphite, hydrozincite) are set within a calcite gangue. The Triassic rocks exhibit enrichments in trace metals, namely Pb, Co and Cd enrichment in clays and Pb, Zn, Cd, Co and Cr enrichment in carbonates, suggesting that the Triassic rocks have interacted with the ore-bearing fluids associated with the Jebel Ressas Pb-Zn deposits. The delta(18)O content of calcite associated with the Pb-Zn mineralization suggests that it is likely to have precipitated from a fluid that was in equilibrium with the Triassic dolostones. The delta(34)S values in galenas from the Pb-Zn deposits range from -1.5 to +11.4%, with an average of 5.9% and standard deviation of 3.9%. These data imply mixing of thermochemically-reduced heavy sulfur carried in geothermal- and fault-stress-driven deep-seated source fluid with bacterially-reduced light sulfur carried in topography-driven meteoric fluid. Lead isotope ratios in galenas from the Pb-Zn deposits are homogenous and indicate a single upper crustal source of base-metals for these deposits. Synthesis of the geochemical data with geological data suggests that the base-metal mineralization at Jebel Ressas was formed during the Serravallian-Tortonian (or Middle-Late Miocene) Alpine compressional tectonics.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Prospective study of the barriers to nutritional support in a paediatric intensive care unit : P16

Introduction and aim: Children hospitalised in a paediatric intensive care unit (PICU) are mainly fed by nutritional support (NS) which may often be interrupted. The aims of the study were to verify the relationship between prescribed (PEI) and actual energy intake (AEI) and to identify the reasons for NS interruption. Methods: Prospective study in a PICU. PEI and AEI from day 1 to 15, type of NS (enteral, parenteral, mixed), position of the feeding tube, interruptions in NS and reasons for these were noted. Inter - ruptions were classified in categories of barriers and their frequency and duration were analysed. Results: Fifteen children (24 ± 25.2 months) were studied for 84 days. The NS was exclusively enteral (69%) or mixed (31%). PEI were significantly higher than AEI (54.7 ± 32.9 vs 49.2 ± 33.6 kcal/kg, p = 0.0011). AEI represented 93% of the PEI. Ninety-eight interruptions were noted and lasted 189 h, i.e. 9.4% of the evaluated time. The most frequent barriers were nursing procedures, respiratory physiotherapy and unavailability of intravenous access. The longest were caused by the necessity to stop NS for surgery or diagnostic studies, to treat burns or to carry out medical procedures. Conclusion: AEI in PICU were inferior by 7% to PEI, considerably lower than in adult studies. Making these results available to medical staff for greater anticipation and compensation could reduce NS interruptions. Starving protocols should be reconsidered.