Automated extraction of quality indicators for treatment of children with complex developmental disorders: A feasibility study using the example of attention-deficit/hyperactivity disorder.

QUALITY ISSUE: Quality assessment is challenging in children with developmental disorders. Previously, a set of quality indicators (QIs) was developed and analyzed in terms of feasibility of use with patients with attention-deficit/hyperactivity disorder (ADHD). QI assessment turned out to be possible but highly complex. Thus, we compared different technologies for automated extraction of data for assessment of QIs. CHOICE OF SOLUTION: Four automated extraction technologies (regular expressions, Apache Solr, Apache Mahout, Apache OpenNLP) were compared with respect to their properties regarding the complexity of implementing the QI, the complexity of implementing a check module, the reliability and quality of results, the complexity of preparation of interdisciplinary medical reports, and the complexity of deployment and installation. IMPLEMENTATION: Twenty medical reports from different institutions were reviewed for compliance with three QIs by these technologies and compared with expert opinions. EVALUATION: Among the four technologies, Apache Solr had the best overall performance. For manual extraction of the three QIs, at least 77 s were necessary per medical report, whereas the prototype evaluated and extracted the QIs automatically in 8 s on average. Unexpectedly, different assessments of the degree of compliance by the experts turned out to be one of the stumbling blocks. An in-depth evaluation compared results on a semantic level. LESSONS LEARNED: It is possible to extract QIs by post-processing automated technologies. This approach can also be applied to other developmental disorders. However, a more uniform documentation throughout institutions involved will be necessary in order to implement this method in daily practice.

Strategies of anaerobic sludge granulation in an EGSB reactor.

Anaerobic sludge granulation was evaluated in an expanded granular sludge bed (EGSB) reactor based on the increases in the specific organic loading rate (SOLR). The effect of precursor substances (calcium chloride, sodium chloride, and tannin) on the development of granular sludge was also investigated in batch reactors. The reactors were fed with synthetic sewage and operated in mesophilic conditions. The EGSB was operated with a variable hydraulic retention time (HRT) and the batch reactors, with cycles of 8 h and 16 h. The increase of SOLR from 17.4 ±â€¯7.4 to 104.6 ±â€¯66.7 mgCOD gVSS-1 d-1 in the EGSB resulted in an increase on the average granules diameter from 344.3 to 1583.3 µm. These conditions also favored the reduction rates of chemical oxygen demand (COD) and volatile fatty acids (VFAs) concentration in the reactor. When the upflow velocity suffered an abrupt increase (from 0.06 L h-1 to 0.25 L h-1), the granules size began to decrease and lose their settleability characteristics. Considering this, it is proposed to start the biomass granulation process without effluent recirculation, and, after the granules reach the desired size and settleability capacity, the normal operation of EGSB reactor starts. The results showed that calcium chloride was more efficient for granulation. CaCl2 addition can be performed only during the reactor's start-up, improving granulation and reducing start-up time. Thus, these results have practical implications as granules maintenance is the key to the proper EGSB operation.

Receptor for advanced glycation end products polymorphisms in coronary artery ectasia.

BACKGROUND: Although the implication of receptor of advanced glycation endproducts (RAGE) has been reported in coronary artery disease, its roles in coronary artery ectasia (CAE) have remained undetermined. Furthermore, the effect of RAGE polymorfisms were not well-defined in scope of soluble RAGE (sRAGE) levels. Thus, we aimed to investigate the influence of the functional polymorphisms of RAGE -374T > A (rs1800624) and G82S (rs2070600) in CAE development. METHODS: This prospective observational study was conducted in 2 groups selected of 2452 patients who underwent elective coronary angiography (CAG) for evaluation after positive noninvasive heart tests. Group-I included 98 patients with non-obstructive coronary artery disease and CAE, and Group-II (control) included 100 patients with normal coronary arteries. SNPs were genotyped by real-time PCR using Taqman® genotyping assay. Serum sRAGE and soluble lectin-like oxidized receptor-1 (sOLR1) were assayed by ELISA and serum lipids were measured enzymatically. RESULTS: The frequencies of the RAGE -374A allele and -374AA genotype were significantly higher in CAE patients compared to controls (p < 0.001). sRAGE levels were not different between study groups, while sOLR1 levels were elevated in CAE (p = 0.004). In controls without systemic disease, -374A allele was associated with low sRAGE levels (p < 0.05), but this association was not significant in controls with HT. Similarly, sRAGE levels of CAE patients with both HT and T2DM were higher than those no systemic disease (p = 0.02). The -374A allele was also associated with younger patient age and higher platelet count in the CAE group in both total and subgroup analyses. In the correlation analyses, the -374A allele was also negatively correlated with age and positively correlated with Plt in all of these CAE groups. In the total CAE group, sRAGE levels also showed a positive correlation with age and a negative correlation with HDL-cholesterol levels. On the other hand, a negative correlation was observed between sRAGE and Plt in the total, hypertensive and no systemic disease control subgroups. Multivariate logistic regression analysis confirmed that the -374A allele (p < 0.001), hyperlipidemia (p < 0.05), and high sOLR1 level (p < 0.05) are risk factors for CAE. ROC curve analysis shows that RAGE -374A allele has AUC of 0.713 (sensitivity: 83.7 %, specificity: 59.0 %), which is higher than HLD (sensitivity: 59.2 %, specificity: 69.0 %), HT (sensitivity: 62.4 %, specificity: 61.1 %) and high sOLR1 level (≥0.67 ng/ml)) (sensitivity: 59.8 %, specificity: 58.5 %). CONCLUSION: Beside the demonstration of the relationship between -374A allele and increased risk of CAE for the first time, our results indicate that antihypertensive and antidiabetic treatment in CAE patients causes an increase in sRAGE levels. The lack of an association between the expected -374A allele and low sRAGE levels in total CAE group was attributed to the high proportion of hypertensive patients and hence to antihypertensive treatment. Moreover, the RAGE -374A allele is associated with younger age at CAE and higher Plt, suggesting that -374A may also be associated with platelet activation, which plays a role in the pathogenesis of CAE. However, our data need to be confirmed in a large study for definitive conclusions.

Enhancing discovery in spatial data infrastructures using a search engine.

A spatial data infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide an efficient and flexible way to use spatial information. One of the key software components of an SDI is the catalogue service which is needed to discover, query and manage the metadata. Catalogue services in an SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard which defines common interfaces for accessing the metadata information. A search engine is a software system capable of supporting fast and reliable search, which may use 'any means necessary' to get users to the resources they need quickly and efficiently. These techniques may include full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting, recommendations and many others. In this paper we present an example of a search engine being added to an SDI to improve search against large collections of geospatial datasets. The Centre for Geographic Analysis (CGA) at Harvard University re-engineered the search component of its public domain SDI (Harvard WorldMap) which is based on the GeoNode platform. A search engine was added to the SDI stack to enhance the CSW catalogue discovery abilities. It is now possible to discover spatial datasets from metadata by using the standard search operations of the catalogue and to take advantage of the new abilities of the search engine, to return relevant and reliable content to SDI users.

Membrane installation for enhanced up-flow anaerobic sludge blanket (UASB) performance.

It is postulated that up-flow anaerobic sludge blanket (UASB) reactor efficiency can be enhanced by a membrane immersed in the reactor to operate it as an anaerobic membrane bioreactor (AnMBR) for low-strength wastewater treatment. This postulate was tested by comparing the performance with and without a hollow fiber microfiltration membrane module immersed in UASB reactors operated at two specific organic loading rates (SOLR). Results showed that membrane filtration enhanced process performance and stability, with over 90% total organic carbon (TOC) removal consistently achieved. More than 91% of the TOC removal was achieved by suspended biomass, while less than 6% was removed by membrane filtration and digestion in the membrane attached biofilm during stable AnMBRs operation. Although the membrane and its biofilm played an important role in initial stage of the high SOLR test, linear increased TOC removal by bulk sludge mainly accounted for the enhanced process performance, implying that membrane led to enhanced biological activity of the suspended sludge. The high retention of active fine sludge particles in suspension was the main reason for this significant improvement of performance and biological activity, which led to decreased SOLR with time to a theoretical optimal level around 2  g COD/g MLVSS·d and the establishment of a microbial community dominated by Methanothrix-like microbes. It was concluded that UASB process performance can be enhanced by transforming such to AnMBR operation when the loading rate is too high for sufficient sludge retention, and/or when the effluent water quality demands are especially stringent.

Nitrous oxide reduction genetic potential from the microbial community of an intermittently aerated partial nitritation SBR treating mature landfill leachate.

This study investigates the microbial community dynamics in an intermittently aerated partial nitritation (PN) SBR treating landfill leachate, with emphasis to the nosZ encoding gene. PN was successfully achieved and high effluent stability and suitability for a later anammox reactor was ensured. Anoxic feedings allowed denitrifying activity in the reactor. The influent composition influenced the mixed liquor suspended solids concentration leading to variations of specific operational rates. The bacterial community was low diverse due to the stringent conditions in the reactor, and was mostly enriched by members of Betaproteobacteria and Bacteroidetes as determined by 16S rRNA sequencing from excised DGGE melting types. The qPCR analysis for nitrogen cycle-related enzymes (amoA, nirS, nirK and nosZ) demonstrated high amoA enrichment but being nirS the most relatively abundant gene. nosZ was also enriched from the seed sludge. Linear correlation was found mostly between nirS and the organic specific rates. Finally, Bacteroidetes sequenced in this study by 16S rRNA DGGE were not sequenced for nosZ DGGE, indicating that not all denitrifiers deal with complete denitrification. However, nosZ encoding gene bacteria was found during the whole experiment indicating the genetic potential to reduce N2O.