An evolutionary approach to the delineation of functional areas based on travel-to-work flows

This paper presents a new approach to the delineation of local labor markets based on evolutionary computation. The aim of the exercise is the division of a given territory into functional regions based on travel-to-work flows. Such regions are defined so that a high degree of inter-regional separation and of intra-regional integration in both cases in terms of commuting flows is guaranteed. Additional requirements include the absence of overlap between delineated regions and the exhaustive coverage of the whole territory. The procedure is based on the maximization of a fitness function that measures aggregate intra-region interaction under constraints of inter-region separation and minimum size. In the experimentation stage, two variations of the fitness function are used, and the process is also applied as a final stage for the optimization of the results from one of the most successful existing methods, which are used by the British authorities for the delineation of travel-to-work areas （TTWAs）. The empirical exercise is conducted using real data for a sufficiently large territory that is considered to be representative given the density and variety of travel-to-work patterns that it embraces. The paper includes the quantitative comparison with alternative traditional methods, the assessment of the performance of the set of operators which has been specifically designed to handle the regionalization problem and the evaluation of the convergence process. The robustness of the solutions, something crucial in a research and policy-making context, is also discussed in the paper.     

Improving the performance and functionality of Mondrian open‐source OLAP systems

For a long time, the design of relational databases has focused on the optimization of atomic transactions (insert, select, update or delete). Currently, relational databases store tactical information of data warehouses, mainly for select‐like operations. However, the database paradigm has evolved, and nowadays on‐line analytical processing (OLAP) systems handle strategic information for further analysis. These systems enable fast, interactive and consistent information analysis of data warehouses, including shared calculations and allocations. OLAP and data warehouses jointly allow multidimensional data views, turning raw data into knowledge. OLAP allows ‘slice and dice’ navigation and a top‐down perspective of data hierarchies. In this paper, we describe our experience in the migration from a large relational database management system to an OLAP system on top of a relational layer (the data warehouse), and the resulting contributions in open‐source ROLAP optimization. Existing open‐source ROLAP technologies rely on summarized tables with materialized aggregate views to improve system performance (in terms of response time). The design and maintenance of those tables are cumbersome. Instead, we intensively exploit cache memory, where key data reside, yielding low response times. A cold start process brings summarized data from the relational database to cache memory, subsequently reducing the response time. We ensure concurrent access to the summarized data, as well as consistency when the relational database updates data. We also improve the OLAP functionality, by providing new features for automating the creation of calculated members. This makes it possible to define new measures on the fly using virtual dimensions, without re‐designing the multidimensional cube. We have chosen the XML/A de facto standard for service provision. Copyright © 2008 John Wiley & Sons, Ltd.     

LncRNA H19 Impairs Chemo and Radiotherapy in Tumorigenesis

Various treatments based on drug administration and radiotherapy have been devoted to preventing, palliating, and defeating cancer, showing high efficiency against the progression of this disease. Recently, in this process, malignant cells have been found which are capable of triggering specific molecular mechanisms against current treatments, with negative consequences in the prognosis of the disease. It is therefore fundamental to understand the underlying mechanisms, including the genes—and their signaling pathway regulators—involved in the process, in order to fight tumor cells. Long non-coding RNAs, H19 in particular, have been revealed as powerful protective factors in various types of cancer. However, they have also evidenced their oncogenic role in multiple carcinomas, enhancing tumor cell proliferation, migration, and invasion. In this review, we analyze the role of lncRNA H19 impairing chemo and radiotherapy in tumorigenesis, including breast cancer, lung adenocarcinoma, glioma, and colorectal carcinoma.     

Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG)

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders’ views on AI for therapy discovery in CDG.     

Technical Validation and Clinical Implications of Ultrasensitive PCR Approaches for EGFR-Thr790Met Mutation Detection in Pretreatment FFPE Samples and in Liquid Biopsies from Non-Small Cell Lung Cancer Patients

In pretreatment tumor samples of EGFR-mutated non-small cell lung cancer (NSCLC) patients, EGFR-Thr790Met mutation has been detected in a variable prevalence by different ultrasensitive assays with controversial prognostic value. Furthermore, its detection in liquid biopsy (LB) samples remains challenging, being hampered by the shortage of circulating tumor DNA (ctDNA). Here, we describe the technical validation and clinical implications of a real-time PCR with peptide nucleic acid (PNA-Clamp) and digital droplet PCR (ddPCR) for EGFR-Thr790Met detection in diagnosis FFPE samples and in LB. Limit of blank (LOB) and limit of detection (LOD) were established by analyzing negative and low variant allele frequency (VAF) FFPE and LB specimens. In a cohort of 78 FFPE samples, both techniques showed an overall agreement (OA) of 94.20%. EGFR-Thr790Met was detected in 26.47% of cases and was associated with better progression-free survival (PFS) (16.83 ± 7.76 vs. 11.47 ± 1.83 months; p = 0.047). In LB, ddPCR was implemented in routine diagnostics under UNE-EN ISO 15189:2013 accreditation, increasing the detection rate of 32.43% by conventional methods up to 45.95%. During follow-up, ddPCR detected EGFR-Thr790Met up to 7 months before radiological progression. Extensively validated ultrasensitive assays might decipher the utility of pretreatment EGFR-Thr790Met and improve its detection rate in LB studies, even anticipating radiological progression.     

Academic trajectories of newcomer immigrant youth.

Immigration to the United States presents both challenges and opportunities that affect students' academic achievement. Using a 5-year longitudinal, mixed-methods approach, we identified varying academic trajectories of newcomer immigrant students from Central America, China, the Dominican Republic, Haiti, and Mexico. Latent class growth curve analysis revealed that although some newcomer students performed at high or improving levels over time, others showed diminishing performance. Multinomial logistic regressions identified significant group differences in academic trajectories, particularly between the high-achieving youth and the other groups. In keeping with ecological–developmental and stage–environment fit theories, School Characteristics (school segregation rate, school poverty rate, and student perceptions of school violence), Family Characteristics (maternal education, parental employment, and household structure), and Individual Characteristics (academic English proficiency, academic engagement, psychological symptoms, gender, and 2 age-related risk factors, number of school transitions and being overaged for grade placement) were associated with different trajectories of academic performance. A series of case studies triangulate many of the quantitative findings as well as illuminate patterns that were not detected in the quantitative data. Thus, the mixed-methods approach sheds light on the cumulative developmental challenges that immigrant students face as they adjust to their new educational settings. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Effects of the Alkaloid Tambjamine J on Mice Implanted with Sarcoma 180 Tumor Cells

The tambjamines are a small group of bipyrrolic alkaloids that, collectively, display a significant range of biological activities including antitumor, antimicrobial and immunosuppressive properties. The key objective of the present study was to undertake preclinical assessments of tambjamine J (T-J) so as to determine its in vivo antitumor effects. To that end, sarcoma 180 cells were transplanted in mice and the impacts of the title compound then evaluated using a range of protocols including hematological, biochemical, histopathological, genotoxic and clastogenic assays. As a result it was established that this alkaloid has a significant therapeutic window and effectively reduces tumor growth (by 40 % and 79 % at doses of 10 and 20 mg/kg/day, respectively). In this regard it displays similar antitumor activity to the anticancer agent cyclophosphamide and alters animal weight in an analogous manner.     

La4Ni3O10±δ – BaCe0.9Y0.1O3-δ cathodes for proton ceramic fuel cells; short-circuiting analysis using BaCe0.9Y0.1O3-δ symmetric cells

Protonic ceramic fuel cells are a promising technology for energy conversion and chemical synthesis in the intermediate temperature range (400–600 °C). Nevertheless, a major restriction to their wider implementation concerns their relatively high cathode polarisation resistance that can become performance limiting as working temperatures decrease. As potential new cathode materials, high order nickelates can be attractive candidates as they exhibit high electrical conductivities at lower temperatures due to their metallic behaviour. In the current work, we investigate the performance of La₄Ni₃O_10±δ and La₄Ni₃O_10±δ–BaCe_0.9Y_0.1O_3-δ composite cathodes, deposited on a BaCe_0.9Y_0.1O_3-δ (BCY10), proton-conducting electrolyte in the temperature range 350–550 °C. The study is performed in symmetrical cell configuration to permit separation of the electrode performance from the overall cell behaviour. For such experiments, possible internal short-circuiting of the electrolyte in oxidising conditions can arise from the presence of p-type electronic conductivity in the BCY10 electrolyte, causing underestimation of measured polarisation resistances. The current work corrects for such factors by knowledge of the transference numbers of the BCY10 electrolyte and the use of a parallel short-circuiting resistor in the equivalent circuit model. The results underscore that the cathode characteristics are highly dependent on the electronic leakage, especially at higher temperatures, and that suitable correction of data is imperative before discussion. Corrected values for polarisation resistance in wet O₂ reveal the composite cathode shows an improvement of total polarisation resistance by a factor of 1.5. The analysis on the oxygen reduction reaction mechanism allows the rate-limiting processes between the electrodes to be differentiated, with the low-frequency term, corresponding to surface processes, being the dominant polarisation resistance and the most improved on formation of the composite. Overall performance analysis indicates that the results from this work are in line with some of the best cathodes currently reported.     

Effects of Y-TZP blank manufacturing control and addition of TiO2 nanotubes on structural reliability of dental materials

Titanium dioxide (TiO₂) nanotubes have been applied to enhance the mechanical and biological properties of dental materials. Yttria-stabilized tetragonal zirconia polycrystals (Y-TZP) have been increasingly used in dentistry as a substructure for crowns and fixed partial prostheses. Aside from its optimal clinical results, Y-TZP is prone to failures due to microstructure-related defects introduced in the manufacturing process that may lower its structural and clinical reliability. The purpose of this study was to evaluate the role of the manufacturing process of blanks as well as their original composition modification by addition of TiO₂ nanotubes (0%, 1%, 2% and 5% in volume) while controlling all manufacturing steps. Materials were subjected to a biaxial flexural strength test, a fractographic qualitative analysis by scanning electron microscopy (SEM), a microstructure evaluation in field emission-SEM and X-ray diffraction. Values of flexural strength were subjected to ANOVA, Tukey (α = 0.05) and Weibull statistics. Grain size values were subjected to Kruskal-Wallis and Dunn tests (α = 0.05). Highlights of the results include that for experimental Y-TZP added 2% vol TiO₂ nanotube ceramics presented flexural strength values at 577 MPa and Weibull modulus (m) at 8.1. The addition of TiO₂ nanotubes in different blends influenced experimental Y-TZP properties, leading to lower flexural strength, although they presented higher m than the commercial Y-TZP. Nanotubes also led to bigger grain sizes, more pores and a slight increase in the monoclinic phase, influencing the microstructure of Y-TZP. Y-TZP blank manufacturing control as well as addition of TiO₂ nanotubes led to higher m values and, hence, greater structural reliability.