Site-specific dataset of mining and metallurgical residues for resource management.

This geospatial dataset provides a compilation of findings from an evidence-based review of site-specific resource assessments of mining and metallurgical residues. Information pertaining to location, target material, geological knowledge, extractability, resource classification and stakeholder perspectives was collected from publicly available reports, articles, academic theses, and databases. The dataset includes 44 relevant data attributes from 64 mining and metallurgical sites in 27 countries. Resource classification is available for 38 sites. The dataset can be used by evaluators of recovery projects, authorities that provide permits, as well as by decision makers in support of developing regulatory policies. The dataset facilitates future addition of sites by the research community and can be further used as a starting point to bridge the estimates on recoverable quantities to the United Nations Framework Classification (UNFC). The UNFC is a universally applicable scheme for the sustainable management of all energy, primary and secondary mineral resources. Its use is stimulated by the European Commission and is intended to be adopted by geological surveys to harmonize the data on the availability of primary and secondary raw materials in Europe in future.

Autoregulated and Non-Autoregulated Blood Flow Restriction on Acute Arterial Stiffness.

This study aimed to investigate the acute effects of autoregulated and non-autoregulated applied pressures during blood flow restriction resistance exercise to volitional fatigue on indices of arterial stiffness using the Delfi Personalized Tourniquet System. Following a randomized autoregulated or non-autoregulated blood flow restriction familiarization session, 20 physically active adults (23±5 years; 7 females) participated in three randomized treatment-order sessions with autoregulated and non-autoregulated and no blood flow restriction training. Participants performed four sets of dumbbell wall squats to failure using 20% of one repetition maximum. Blood flow restriction was performed with 60% of supine limb occlusion pressure. Testing before and post-session included an ultrasonic scan of the carotid artery, applanation tonometry, and blood pressure acquisition.Carotid-femoral pulse wave velocity increased in the non-autoregulated and no blood flow restriction training groups following exercise while carotid-radial pulse wave velocity increased in the no blood flow restriction training group (all p<0.05). Carotid-femoral pulse wave velocity exhibited an interaction effect between autoregulated and non-autoregulated blood flow restriction in favor of autoregulated blood flow restriction (p<0.05). Autoregulated blood flow restriction training does not influence indices of arterial stiffness while non-autoregulated and no blood flow restriction training increases central stiffness.

Patterns of infringement, risk, and impact driven by coal mining permits in Indonesia.

Coal mining is known for its contributions to climate change, but its impacts on the environment and human lives near mine sites are less widely recognised. This study integrates remote sensing, GIS, stakeholder interviews and extensive review of provincial data and documents to identify patterns of infringement, risk and impact driven by coal mining expansion across East Kalimantan, Indonesia. Specifically, we map and analyse patterns of mining concessions, land clearing, water cover, human settlement, and safety risks, and link them with mining governance and regulatory infractions related to coal mining permits. We show that excessive, improper permit granting and insufficient monitoring and oversight have led to deforestation, widespread overlaps of concessions with settlements, extensive boundary and regulatory violations, lacking reclamation, and numerous deaths. As the world's largest thermal coal exporter, Indonesia's elevated coal infringements, risks, and impacts translate to supply chain, sustainability, and human rights concerns for global coal markets.

Looking Down Under for a Circular Economy of Indium.

Indium is a specialty metal crucial for modern technology, yet it is potentially critical due to its byproduct status in mining. Measures to reduce its criticality typically focus on improving its recycling efficiency at end-of-life. This study quantifies primary and secondary indium resources ("stocks") for Australia through a dynamic material-flow analysis. It is based on detailed assessments of indium mineral resources hosted in lead-zinc and copper deposits, respective mining activities from 1844 to 2013, and the trade of indium-containing products from 1988 to 2015. The results show that Australia's indium stocks are substantial, estimated at 46.2 kt in mineral resources and an additional 14.7 kt in mine wastes. Australian mineral resources alone could meet global demand (∼0.8 kt/year) for more than five decades. Discarded material from post-consumer products, instead, is negligible (43 t). This suggests that the resilience of Australia's indium supply can best be increased through efficiency gains in mining (such as introducing domestic indium refining capacity) rather than at the end of the product life. These findings likely also apply to other specialty metals, such as gallium or germanium, and other resource-dominated countries. Finally, the results illustrate that national circular economy strategies can differ substantially.

Analysis of free modeling predictions by RBO aleph in CASP11.

The CASP experiment is a biannual benchmark for assessing protein structure prediction methods. In CASP11, RBO Aleph ranked as one of the top-performing automated servers in the free modeling category. This category consists of targets for which structural templates are not easily retrievable. We analyze the performance of RBO Aleph and show that its success in CASP was a result of its ab initio structure prediction protocol. A detailed analysis of this protocol demonstrates that two components unique to our method greatly contributed to prediction quality: residue-residue contact prediction by EPC-map and contact-guided conformational space search by model-based search (MBS). Interestingly, our analysis also points to a possible fundamental problem in evaluating the performance of protein structure prediction methods: Improvements in components of the method do not necessarily lead to improvements of the entire method. This points to the fact that these components interact in ways that are poorly understood. This problem, if indeed true, represents a significant obstacle to community-wide progress. Proteins 2016; 84(Suppl 1):87-104. © 2015 Wiley Periodicals, Inc.

RBO Aleph: leveraging novel information sources for protein structure prediction.

RBO Aleph is a novel protein structure prediction web server for template-based modeling, protein contact prediction and ab initio structure prediction. The server has a strong emphasis on modeling difficult protein targets for which templates cannot be detected. RBO Aleph's unique features are (i) the use of combined evolutionary and physicochemical information to perform residue-residue contact prediction and (ii) leveraging this contact information effectively in conformational space search. RBO Aleph emerged as one of the leading approaches to ab initio protein structure prediction and contact prediction during the most recent Critical Assessment of Protein Structure Prediction experiment (CASP11, 2014). In addition to RBO Aleph's main focus on ab initio modeling, the server also provides state-of-the-art template-based modeling services. Based on template availability, RBO Aleph switches automatically between template-based modeling and ab initio prediction based on the target protein sequence, facilitating use especially for non-expert users. The RBO Aleph web server offers a range of tools for visualization and data analysis, such as the visualization of predicted models, predicted contacts and the estimated prediction error along the model's backbone. The server is accessible at http://compbio.robotics.tu-berlin.de/rbo_aleph/.

Kink characterization and modeling in transmembrane protein structures.

Kinks have been observed to provide important functional and structural features for membrane proteins. Despite their ubiquity in membrane proteins, and their perceived importance, no protein modeling methods explicitly considers kinks. In spite of the limited data for transmembrane proteins, we were able to develop a knowledge-based modeling method for introducing kinks, which we demonstrate can be exploited in modeling approaches to improve the quality of models. The work entailed a thorough analysis of the available high resolution membrane protein structures, concomitantly demonstrating the complexity of the structural considerations for kink prediction. Furthermore, our results indicate that there are systematic and significant differences in the sequence as well as the structural environment between kinked and nonkinked transmembrane helices. To the best of our knowledge, we are reporting a method for modeling kinks for the first time.

A benchmark server using high resolution protein structure data, and benchmark results for membrane helix predictions.

BACKGROUND: Helical membrane proteins are vital for the interaction of cells with their environment. Predicting the location of membrane helices in protein amino acid sequences provides substantial understanding of their structure and function and identifies membrane proteins in sequenced genomes. Currently there is no comprehensive benchmark tool for evaluating prediction methods, and there is no publication comparing all available prediction tools. Current benchmark literature is outdated, as recently determined membrane protein structures are not included. Current literature is also limited to global assessments, as specialised benchmarks for predicting specific classes of membrane proteins were not previously carried out. DESCRIPTION: We present a benchmark server at http://sydney.edu.au/pharmacy/sbio/software/TMH_benchmark.shtml that uses recent high resolution protein structural data to provide a comprehensive assessment of the accuracy of existing membrane helix prediction methods. The server further allows a user to compare uploaded predictions generated by novel methods, permitting the comparison of these novel methods against all existing methods compared by the server. Benchmark metrics include sensitivity and specificity of predictions for membrane helix location and orientation, and many others. The server allows for customised evaluations such as assessing prediction method performances for specific helical membrane protein subtypes.We report results for custom benchmarks which illustrate how the server may be used for specialised benchmarks. Which prediction method is the best performing method depends on which measure is being benchmarked. The OCTOPUS membrane helix prediction method is consistently one of the highest performing methods across all measures in the benchmarks that we performed. CONCLUSIONS: The benchmark server allows general and specialised assessment of existing and novel membrane helix prediction methods. Users can employ this benchmark server to determine the most suitable method for the type of prediction the user needs to perform, be it general whole-genome annotation or the prediction of specific types of helical membrane protein. Creators of novel prediction methods can use this benchmark server to evaluate the performance of their new methods. The benchmark server will be a valuable tool for researchers seeking to extract more sophisticated information from the large and growing protein sequence databases.

Involvement of doublecortin-expressing cells in the arcuate nucleus in body weight regulation.

Hypothalamic functions, including feeding behavior, show a high degree of plasticity throughout life. Doublecortin (DCX) is a marker of plasticity and neuronal migration expressed in the hypothalamus. Therefore, we wanted to map the fate of DCX(+) cells in the arcuate nucleus (ARC) of the hypothalamus. For this purpose, we generated a BAC transgenic mouse line that expresses the inducible recombinase CreER(T2) under control of the DCX locus. Crossing this line with the Rosa26 or Ai14 reporter mouse lines, we found reporter(+) cells in the ARC upon tamoxifen treatment. They were born prenatally and expressed both DCX and the plasticity marker TUC-4. Immediately after labeling, reporter(+) cells had an enlarged soma that normalized over time, suggesting morphological remodeling. Reporter(+) cells expressed ß-endorphin and BSX, neuronal markers of the feeding circuit. Furthermore, leptin treatment led to phosphorylation of STAT3 in reporter(+) cells in accordance with the concept that they are part of the feeding circuits. Indeed, we found a negative correlation between the number of reporter(+) cells and body weight and epididymal fat pads. Our data suggest that DCX(+) cells in the ARC represent a cellular correlate of plasticity that is involved in controlling energy balance in adult mice.

Structural modelling and dynamics of proteins for insights into drug interactions.

Proteins are the workhorses of biomolecules and their function is affected by their structure and their structural rearrangements during ligand entry, ligand binding and protein-protein interactions. Hence, the knowledge of protein structure and, importantly, the dynamic behaviour of the structure are critical for understanding how the protein performs its function. The predictions of the structure and the dynamic behaviour can be performed by combinations of structure modelling and molecular dynamics simulations. The simulations also need to be sensitive to the constraints of the environment in which the protein resides. Standard computational methods now exist in this field to support the experimental effort of solving protein structures. This review presents a comprehensive overview of the basis of the calculations and the well-established computational methods used to generate and understand protein structure and function and the study of their dynamic behaviour with the reference to lung-related targets.

[Funding of obesity surgery: application, appeal and lawsuit]. / Finanzierung der adipositaschirurgie: antrag, widerspruch und klage.

Due to the fact that the statutory health insurance (GKV) follows a restrictive authorisation practice the German population is undersupplied with bariatric operations. The number of patients who refuse to accept this practice increases considerably. Negative decisions can be contested by appeal and lawsuit. The legal situation is yet unclear, those applying the law, such as lawyers, judges and the health insurance authorities, are confused and disorientated. In absolutely comparable cases different courts come to different decisions. Nevertheless the topic is worth the fight: The German social courts are passing more and more patient-friendly judgements. Cases are easily won by plaintiffs if the body mass index (BMI) is higher than 60 kg/m(2). .

Homology model adjustment and ligand screening with a pseudoreceptor of the human histamine H4 receptor.

A computer-assisted method for the generation of pseudoreceptor models is presented together with two practical applications. From a three-dimensional alignment of known histamine H(4) receptor ligands, a pseudoreceptor model of the putative ligand binding site was constructed and used for virtual screening of a large collection of commercially available compounds. Two bioactive chemotypes were retrieved, demonstrating the general applicability of the approach. The pseudoreceptor model was also used to find the putative ligand binding pocket within the transmembrane receptor domain. For each frame of a molecular dynamics simulation of a homology-based H(4) receptor model, we automatically extracted potential ligand binding pockets and used their compatibility with the pseudoreceptor as a selection criterion. The best-matching pocket fits perfectly with existing mutation data and previously published hypotheses suggesting Glu182(5.46) as the preferred binding partner of a positively charged moiety of H(4) receptor ligands. This new pseudoreceptor approach has demonstrated its suitability for both structure-based prioritization of protein receptor models, and ligand-based virtual screening with the aim to perform scaffold hopping.