The distribution of HBV, HCV and HGV among livers with fulminant hepatic failure of different aetiology

BACKGROUND/AIMS: The aim of the study was to assess the impact factor of HCV and HGV in fulminant hepatic failure. METHODS: The 5'-untranslated regions of HCV RNA and HGV RNA and a segment of the core antigen sequence of HBV were amplified after extracting the nucleic acids from snap-frozen tissue aliquots from explanted livers of 26 consecutive patients undergoing orthotopic liver transplantation for fulminant hepatic failure preoperatively diagnosed as either autoimmune (n=2), HAV/HBV (n=8), toxic (n=4) or aetiologically unknown (n=12). RESULTS: HCV RNA was detected in five of 26 (19.2%) livers with fulminant hepatic failure. All five HCV RNA-positive livers belonged to the group of non-toxic, non-autoimmune liver failure (n=20), three of them were found in the group of liver failure with unknown aetiology (n=12) and two in the group of HBV-associated liver failure (n=7), making an HCV incidence of 25%, 25% and 28.6%, in the different groups, respectively. HGV RNA was detected in 10 of 17 (58.8%) explants and in all four groups of fulminant hepatic failure as defined preoperatively. HBV DNA was identified in six livers of 26 patients (23.1%) with fulminant hepatic failure. Neither HCV RNA nor HBV DNA was detected in the livers of patients with toxic or autoimmune fulminant hepatic failure. CONCLUSIONS: These results indicate that HBV and HCV, but not HGV, play an aetiologic role in fulminant hepatic failure. HCV-positive cases were concentrated either in the group of otherwise unexplained fulminant hepatic failure or in the group of HBV fulminant hepatic failure. HGV-positive cases, on the other hand, were found within all four preoperatively defined groups, indicating a role as cofactor rather than as single aetiologic agent.     

Using the Percolation Theory to Explain the Release Behavior from Inert Matrix Systems

A novel analysis of drug release process from binary matrix systems has been realized and a study of the initial stage of the process has been carried out. A fast and easy technique has allowed the acquisition of one experimental datum per second. Release data have been analyzed by means of a detailed statistical study. The dissolution profiles were studied applying different kinetic models (zero order, logarithmic, and Higuchi equation). In all the cases studied, a starting process of zero or first order, indicative of a surface-dependent mechanism, has been found. Then, a parameter, named as critical time of kinetic change (t_c), has enabled the authors to establish the instant at which a diffusion release mechanism, according to Higuchi equation, is consolidated. From this time until the end of the process, release mechanism of matrices was shown to be diffusion controlled. The influence of the drug loading and the particle size over the release properties of tablets has also been investigated and it has been evaluated on the basis of percolation theory. The results show a major significance of particle size over the initial drug release and a decrease of its influence along the time. On the other hand, the drug loading variable shows an important influence over the release properties along the whole process.     

Internet in teachers' professional practice outside the classroom: Examining supportive and management uses in primary and secondary schools

In recent years there has been widespread interest in the implementation of information and communication technologies (ICT) in schools. While most studies primarily focus on the use of ICT in teaching and learning, little attention has been given to their incorporation as a professional tool outside the classroom. Using a digital inequality approach, the aim of this paper is to develop and test a model of the factors that affect teachers' professional use of ICT, particularly the Internet, in primary and secondary schools. One thousand four hundred and five (1405) teachers from a representative sample of 536 primary and 273 secondary schools in Spain were surveyed. The dependent variables include attitudes towards the professional use of ICT and the use of the Internet in professional practice. The explanatory variables are the socio-demographics, school-level information, frequency of Internet access within and outside the school, educational ICT training, digital literacy, and organisational development. Controlling for socio-demographics and school-level information, multiple regression analyses are used to make inferential judgements and test the separate effects of the independent variables. Findings suggest that technological factors and organisational practices are important predictors of ICT appropriation for professional purposes.     

Seismic Deformation of Bar Mat Mechanically Stabilized Earth Walls. II: A Multiblock Model

A relatively simple rigid plastic multiblock computational model has been developed to predict the permanent seismic displacement of mechanically stabilized earth (MSE) walls. The model formulation was based on many observations made from a series of centrifuge tests carried out on many different configurations of MSE walls. The proposed model is similar to the sliding block method of Newmark. The approach accounted for the variation in acceleration within the backfill and the nonuniform nature of the permanent wall face deformation. The predictive capability of the proposed model has been verified using centrifuge test results obtained for four MSE walls each subjected to three earthquake excitations with strength varying between 0.48 and 0.9g. The analytical model captures many aspects of the characteristic deformation behavior of MSE walls observed in the centrifuge tests. In each of the eleven wall displacement cases studied, the backfill friction angle that yielded a good match between the computed and measured maximum wall displacement was consistent with the corresponding laboratory measured values.     

Establishing In-House Cutoffs of CSF Alzheimer’s Disease Biomarkers for the AT(N) Stratification of the Alzheimer Center Barcelona Cohort

Background: Clinical diagnosis of Alzheimer’s disease (AD) increasingly incorporates CSF biomarkers. However, due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, establishing in-house cutoffs defining the positivity/negativity of CSF biomarkers is recommended. However, the cutoffs currently published are usually reported by using cross-sectional datasets, not providing evidence about its intrinsic prognostic value when applied to real-world memory clinic cases. Methods: We quantified CSF Aβ1-42, Aβ1-40, t-Tau, and p181Tau with standard INNOTEST^® ELISA and Lumipulse G^® chemiluminescence enzyme immunoassay (CLEIA) performed on the automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with probable Alzheimer’s disease (AD, n = 37) and subjective cognitive decline subjects (SCD, n = 45), cognitively stable for 3 years and with no evidence of brain amyloidosis in 18F-Florbetaben-labeled positron emission tomography (FBB-PET). To compare both methods, a subset of samples for Aβ1-42 (n = 519), t-Tau (n = 399), p181Tau (n = 77), and Aβ1-40 (n = 44) was analyzed. Kappa agreement of single biomarkers and Aβ1-42/Aβ1-40 was evaluated in an independent group of mild cognitive impairment (MCI) and dementia patients (n = 68). Next, established cutoffs were applied to a large real-world cohort of MCI subjects with follow-up data available (n = 647). Results: Cutoff values of Aβ1-42 and t-Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for Aβ1-40 and 0.96 for p181TAU. Passing–Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for Aβ1-40. Bland–Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers was good but lower for the Aβ1-42/Aβ1-40 ratio. Using the calculated cutoffs, we were able to stratify MCI subjects into four AT(N) categories. Kaplan–Meier analyses of AT(N) categories demonstrated gradual and differential dementia conversion rates (p = 9.815⁻²⁷). Multivariate Cox proportional hazard models corroborated these findings, demonstrating that the proposed AT(N) classifier has prognostic value. AT(N) categories are only modestly influenced by other known factors associated with disease progression. Conclusions: We established CLEIA and ELISA internal cutoffs to discriminate AD patients from amyloid-negative SCD individuals. The results obtained by both methods are not interchangeable but show good agreement. CLEIA is a good and faster alternative to manual ELISA for providing AT(N) classification of our patients. AT(N) categories have an impact on disease progression. AT(N) classifiers increase the certainty of the MCI prognosis, which can be instrumental in managing real-world MCI subjects.     

Energy-saving scheduling on IaaS HPC cloud environments based on a multi-objective genetic algorithm

The Journal of Supercomputing - Nowadays, cloud computing is a growing scenario applied to many scientific and manufacturing areas due to its flexibility for adapting to highly demanding computing...     

Rubber Particles from Tires Out of Use as Toughness Modifiers of Epoxy-Based Thermosets

Rubber particles from tires out of use (TOU) were used to modify an epoxy-based thermoset. The effect of size and particle content were evaluated. Three bending point and Charpy tests were carried out to study the mechanical behavior of the materials. A steady decrease in the critical stress intensity factor, K_Ic, with the content of TOU was observed, being attributed to the fact that the particles might also act as defects in the polymer matrix. Fractographic analysis confirmed that filled specimens showed localized shear yielding at the end of the particles along the crack propagation direction. No signs of cavitation mechanism were found on the surfaces of fracture, evidencing an extraordinary interfacial adhesion. The total energy absorbed at break increased as the size of TOU particles decreased, pointing out that particle size is crucial for the performance of these materials. Matrix yielding and plastic deformation were considered to be the main toughness mechanisms.