Study of supramolecular structures released from the cell wall of Candida albicans by ethylenediamine treatment

Candida albicans cell wall components were analyzed by ethylenediamine (EDA) treatment. Based on their different solubility properties, the cell wall components produced three fractions (A, B, and C). Fractions B (EDA-soluble, water-insoluble) and C (EDA-insoluble) contained glucan, chitin, and protein in different proportions. After zymolyase (mainly a beta-glucanase complex) or chitinase treatment of fractions B and C, more polysaccharides and proteins were solubilized by a second EDA treatment, suggesting that the solubility of the polymers in EDA depends on the degree of polymer interactions. Western blot analysis using two monoclonal antibodies (1B12 and 4C12) revealed electrophoretic patterns that were similar in mycelial and yeast morphologies, except that in material obtained from mycelial walls, an additional band was detected with MAb 1B12. Fluorescence microscopy of cell wall fractions treated with FITC-labeled Con-A, Calcofluor white, and FITC-labeled agglutinin showed that glucan and mannoproteins are uniformly distributed in fractions B and C, while chitin is restricted to distinct patches. Transmission electron microscopy demonstrated that fraction C maintained the original shape of the cells, with an irregular thickness generally wider than the walls. When fraction C was treated with chitinase, the morphology was still present and was maintained by an external glucan layer, with an internal expanded fibrillar material covering the entire cellular lumen. Degradation of the glucan skeleton of fraction C with zymolyase resulted in the loss of the morphology.     

The effectiveness of bone density measurement and associated treatments for prevention of fractures. An international collaborative review

This review assesses the evidence regarding the effectiveness of bone density measurement (BDM) screening and related interventions--hormone replacement therapy (HRT) and intranasal salmon calcitonin (SCT[N])--in menopausal women to prevent fractures in later life. Data sources included systematic reviews of evidence and relevant primary studies identified through literature searches on MEDLINE and EMBASE. Study selection included trials of BDM screening programs, prospective studies examining the predictive value of BDM, randomized controlled trials, cohort studies, and case-control studies of HRT and SCT (N). The evidence was evaluated using a classification system incorporating study design and quality. Outcomes were measured in terms of relative risk of fracture for a 1 SD decrease in bone mineral density below the age-adjusted mean, relative risks or odds ratios for fractures associated with treatments, and proportion of hip fractures potentially prevented by BDM screening linked to treatments. Fair evidence from prospective cohort studies suggests that BDM can predict the risk of fractures, but not with high accuracy. Fair evidence from low-quality randomized controlled trials and observational studies suggests that HRT and SCT(N) are efficacious in preventing fractures. Good evidence supports the efficacy of these treatments in preserving bone mass, but there is fair evidence that the effect wears off after cessation of therapy. There is little evidence on the impact of screening menopausal women with BDM in association with HRT or SCT(N) treatment. Estimates based on combining existing evidence regarding the predictive value of BDM and efficacy of HRT suggests that 1-7% of hip fractures might be prevented.     

Assessment of clinical assessment reliability among researchers of a multicenter clinical trial

Formal studies examining the antiparkinsonian efficacy of levodopa and pergolide monotherapy in de novo Parkinson's disease (PD) are lacking. The authors conducted a preliminary, 6-month, open-label parallel experimental study with de novo consecutive PD patients who were randomly assigned to three daily doses of pergolide (n = 10; mean age, 63.7 years; mean Hohen & Yahr score, 1.5; mean final dose, 2.8 mg daily) or levodopa (n = 10; mean age, 67.3 years; mean Hohen & Yahr score, 1.8; mean final dose, 435 mg daily). Doses were titrated individually according to patients' evaluation of their own functional ability, known side-effects, and a monthly administration of the Unified Parkinson's Disease Rating Scale (UPDRS) by a clinician blind to the treatment regime. All patients completed the study. There were no significant basal differences between groups and no significant treatment ortreatment-by-time effects in UPDRS scores (according to two-way ANOVA). A clear time effect was observed for most of the functional and motor variables (p < 0.001), with significant improvement during the first month that was maintained for the duration of the study in both groups. Side effects were mild, transient, and comparable. In this preliminary study, pergolide and levodopa exhibited similar symptomatic efficacy and incidence of side effects in the short-term treatment of de novo PD patients at their usual age of clinical manifestation.     

Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application

Many hydrologic phenomena and applications such as drought, flood, irrigation management and scheduling needs high resolution satellite soil moisture data at a local/regional scale. Downscaling is a very important process to convert a coarse domain satellite data to a finer spatial resolution. Three artificial intelligence techniques along with the generalized linear model (GLM) are used to improve the spatial resolution of Soil Moisture and Ocean Salinity (SMOS) derived soil moisture, which is currently available at a very coarse scale of ~40 Km. Artificial neural network (ANN), support vector machine, relevance vector machine and generalized linear models are chosen for this study to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) with the SMOS derived soil moisture. Soil moisture deficit (SMD) derived from a hydrological model called PDM (Probability Distribution Model) is used for the downscaling performance evaluation. The statistical evaluation has also been made with the day-time and night-time MODIS LST differences with the mean day and night-time PDM SMD data for the selection of effective MODIS products. The accuracy and robustness of all the downscaling algorithms are discussed in terms of their assumptions and applicability. The statistical performance indices such as R ² , %Bias and RMSE indicates that the ANN (R ² ? =?0.751, %Bias?=??0.628 and RMSE?=?0.011), RVM (R ² ? =?0.691, %Bias?=?1.009 and RMSE?=?0.013), SVM (R ² ? =?0.698, %Bias?=?2.370 and RMSE?=?0.013) and GLM (R ² ? =?0.698, %Bias?=?1.009 and RMSE?=?0.013) algorithms on the whole are relatively more skillful to downscale the variability of the soil moisture in comparison to the non-downscaled data (R ² ? =?0.418 and RMSE?=?0.017) with the outperformance of ANN algorithm. The other attempts related to growing and non-growing seasons have been used in this study to reveal that season based downscaling is even better than continuous time series with fairly high performance statistics.     

A context-awareness model for activity recognition in robot-assisted scenarios

Context awareness in ambient assisted living programmes for the elderly is a cornerstone in the current scenario of noncustomized service robots distributed around the world. This research proposes a context-awareness system for a human–robot scene interpretation based on seven primary contexts and the American Occupational Therapy Association. The context-awareness system defined here proposes an inference mechanism for the activity recognition supported on hierarchical Bayesian networks. However, when the information from sensors increases, the computational cost associated also increases. Thus, an evaluation of different Bayesian network models is necessary for decreasing its impact over the robot performance. Two topological models have been modelled and tested using OpenMarkov application: a two-level approach of an input–observations layer and the activity recognition layer, and a three-layer model setting apart a primary contexts layer, the input–observations layer, and the activity recognition layer. The qualitative and quantitative results presented here show better performance in terms of memory and memory in a three-layer model. Besides, its effect on a hybrid architecture of a robotic platform is presented.     

Evaluating MT for massive open online courses

This article reports a multifaceted comparison between statistical and neural machine translation (MT) systems that were developed for translation of data from massive open online courses (MOOCs). The study uses four language pairs: English to German, Greek, Portuguese, and Russian. Translation quality is evaluated using automatic metrics and human evaluation, carried out by professional translators. Results show that neural MT is preferred in side-by-side ranking, and is found to contain fewer overall errors. Results are less clear-cut for some error categories, and for temporal and technical post-editing effort. In addition, results are reported based on sentence length, showing advantages and disadvantages depending on the particular language pair and MT paradigm.     

Design and development of a digital farmer field school. Experiences with a digital learning environment for cocoa production and certification in Sierra Leone

This article reports on the design and development of the Digital Farmer Field School (DFFS). The DFFS offers a tablet-based digital learning environment for farmers and extension agents for knowledge sharing and knowledge co-creation. It provides an alternative to conventional agricultural extension training and monitoring. The prototype DFFS applies Farmer Field School (FFS) learning principles and is designed and developed following user experience (UX) design principles and user interface (UI) design principles from a responsible innovation perspective, using existing FFS material and tailored films which support and enrich the content. The prototype DFFS has been tested in Sierra Leone to assess its success in providing a substitute for face-to-face voluntary sustainability standard certification training for cocoa farmers. Results show that the DFFS as an off-line, telephonically connected and regular on-line updated learning platform offers an appropriate environment in which collective and individual learning is stimulated and facilitated. The DFFS prototype was socio-culturally and technologically appropriate and fitted the operational and strategic communication skills of cocoa farmers and other value chain stakeholders. Films capturing the testing are available as additional learning media.     

Cross-strand side-chain interactions versus turn conformation in beta-hairpins

A series of designed peptides has been analyzed by 1H-NMR spectroscopy in order to investigate the influence of cross-strand side-chain interactions in beta-hairpin formation. The peptides differ in the N-terminal residues of a previously designed linear decapeptide that folds in aqueous solution into two interconverting beta-hairpin conformations, one with a type I turn (beta-hairpin 4:4) and the other with a type I + G1 beta-bulge turn (beta-hairpin 3:5). Analysis of the conformational behavior of the peptides studied here demonstrates three favorable and two unfavorable cross-strand side-chain interactions for beta-hairpin formation. These results are in agreement with statistical data on side-chain interactions in protein beta-sheets. All the peptides in this study form significant populations of the beta-hairpin 3:5, but only some of them also adopt the beta-hairpin 4:4. The formation of beta-hairpin 4:4 requires the presence of at least two favorable cross-strand interactions, whereas beta-hairpin 3:5 seems to be less susceptible to side-chain interactions. A protein database analysis of beta-hairpins 3:5 and beta-hairpins 4:4 indicates that the former occur more frequently than the latter. In both peptides and proteins, beta-hairpins 3:5 have a larger right-handed twist than beta-hairpins 4:4, so that a factor contributing to the higher stability of beta-hairpin 3:5 relative to beta-hairpin 4:4 is due to an appropriate backbone conformation of the type I + G1 beta-bulge turn toward the right-handed twist usually observed in protein beta-sheets. In contrast, as suggested previously, backbone geometry of the type I turn is not adequate for the right-handed twist. Because analysis of buried hydrophobic surface areas on protein beta-hairpins reveals that beta-hairpins 3:5 bury more hydrophobic surface area than beta-hairpins 4:4, we suggest that the right-handed twist observed in beta-hairpin 3:5 allows a better packing of side chains and that this may also contribute to its higher intrinsic stability.     

Erosion wear and mechanical properties of plasma-sprayed nickel- and iron-based coatings subjected to service conditions in boilers

The erosion wear and mechanical properties after exposure to simulated industrial service conditions in boilers of nickel-based, iron-based and chromium–nickel plasma-sprayed coatings on carbon steel and stainless steel have been obtained. These types of coatings are used as heat transfer and structural elements in boilers. Different tests simulating boiler service conditions under standard and extreme situations were carried out at 400, 600 and 800°C in a laboratory combustion unit. The influence of high temperature oxidation processes on the adherence, microhardness, microstructure, and wear erosion behaviour of both base materials and coatings have been evaluated.