Enhanced Ca2+ Entry Sustains the Activation of Akt in Glucose Deprived SH-SY5Y Cells

The two crucial cellular insults that take place during cerebral ischemia are the loss of oxygen and loss of glucose, which can both activate a cascade of events leading to neuronal death. In addition, the toxic overactivation of neuronal excitatory receptors, leading to Ca²⁺ overload, may contribute to ischemic neuronal injury. Brain ischemia can be simulated in vitro by oxygen/glucose deprivation, which can be reversible by the re-establishment of physiological conditions. Accordingly, we examined the effects of glucose deprivation on the PI3K/Akt survival signaling pathway and its crosstalk with HIF-1α and Ca²⁺ homeostasis in SH-SY5Y human neuroblastoma cells. It was found that glucose withdrawal decreased HIF-1α protein levels even in the presence of the ischemia-mimicking CoCl_2. On the contrary, and despite neuronal death, we identified a strong activation of the master pro-survival kinase Akt, a finding that was also confirmed by the increased phosphorylation of GSK3, a direct target of p-Akt. Remarkably, the elevated Ca²⁺ influx recorded was found to promptly trigger the activation of Akt, while a re-addition of glucose resulted in rapid restoration of both Ca²⁺ entry and p-Akt levels, highlighting the plasticity of neurons to respond to ischemic challenges and the important role of glucose homeostasis for multiple neurological disorders.     

Retention of ethyl butyrate by gellan gels in the presence of potassium ions

The air/biopolymer partition coefficient (K) and percentage of retention (R%) of ethyl butyrate (400 ppm) added to gellan gels were determined, using static headspace gas chromatography. Potassium chloride (40–120 mM) was used to induce gellan gelation. When 5 g of sample were left to equilibrate at 37 °C for 2 and 24 h, the coefficient values initially decreased with salt concentration to a certain value after which they raised again. The lower coefficient values, for the 24 h period, were observed at higher salt concentration than for the 2 h. Moreover, for both time periods, the lower coefficient values were found for the gellan gels with the greater strength and rigidity and were accompanied by positive percentages of retention. When 15 g of sample were used, after equilibration at 37 °C for 24 h, no significant changes in aroma release were observed. Moreover, negative percentages of retention values were calculated for all salt concentrations.     

Migration levels of PVC plasticisers: Effect of ionising radiation treatment

Migration levels of commercial plasticisers [di-(2-ethylhexyl) adipate (DEHA) and acetyl tributyl citrate (ATBC)] from polyvinyl chloride (PVC) film into the EU specified aqueous food simulants (distilled water, 3% w/v acetic acid and 10% v/v ethanol) were monitored as a function of time. Migration testing was carried out at 40 °C for 10 days (EEC, 1993). Determination of the analytes was performed by applying the analytical methodology based on surfactant (Triton X-114) mediated extraction prior to gas chromatographic-flame ionisation detection (GC-FID) recently proposed by our group. The study focuses on the determination of the effect of gamma radiation on plasticiser migration into the selected simulants. PVC cling film used was subjected to ionising treatment with a [⁶⁰Co] source at doses equal to 5, 15 and 25 kGy. DEHA and ATBC migration into the EU aqueous simulating solvents was limited, yielding final concentrations in the respective ranges 10–100 μg/l and 171–422 μg/l; hence, ATBC demonstrated a stronger interaction with all three simulants compared to DEHA. Migration data, with respect to ATBC, showed that the most aggressive simulant seemed to be the 10% ethanol, while in the case of DEHA the 3% aqueous acetic acid exhibited the highest extraction efficiency; distilled water demonstrated the lowest migration in both cases. With regard to PVC treatment with gamma rays, high radiation doses up to 25 kGy produced a statistically significant (p < 0.05) effect on the migration of both plasticisers.     

A Semi-Empirical Model for Predicting the Onset of Drop Formation in Stratified Horizontal Oil-Water Flow

In this study, a semi-empirical modeling approach for predicting the onset of drop formation in stratified horizontal oil-water flow is presented. The model is suggested based on a correlation for the critical wave amplitude for drop detachment proposed by Al-Wahaibi et al. (2007 Al-Wahaibi , T. , and Angeli , P. ( 2007 ). Transition between stratified and non-stratified horizontal oil-water flows. Part I: Stability analysis , Chem. Eng. Sci. , 62 ( 11 ), 2915 – 2928 .[Crossref], [Web of Science ®] , [Google Scholar]) and an experimentally derived formula of the maximum wave amplitude at different phase flow rates in stratified flows that uses previous data with different viscosity oils. The proposed model was found to satisfactorily predict published experimental data when relatively low viscosity oils were used (less than or equal to 12 mPa.s cp) but was found to over-predict the velocities necessary for drop formation for higher viscosity oils (greater than 28 mPa.s).     

Particle Measurement Programme (PMP) Light-Duty Inter-Laboratory Exercise: Repeatability and Reproducibility of the Particle Number Method

A Euro 4 Light-Duty Diesel vehicle equipped with a diesel particulate filter (DPF) was circulated to 9 labs where repetitions of the current regulatory New European Drive Cycle (NEDC) were conducted. Regulated gaseous and improved (with cyclone, filter temperature 47 ± 5°C, constant filter face velocity, high precision balance at all labs) particulate mass (PM) measurements were also conducted. A reference particle number (PN) measurement system measuring non-volatile particles was circulated along with the test vehicle. Labs also tested their own PN systems built to comply with the reference system's performance specifications. The mean PN emissions level of the vehicle was below 1 × 10¹¹ particles/km. The intra-lab variability (repeatability) was ～ 40% and the inter-lab variation was ～ 25%. The study showed that the new PN method had similar variability to other gaseous pollutants such as carbon monoxide and hydrocarbons and better than the PM (intra-lab variability ～ 55% and inter-lab ～ 35%). Even with the improved PM method the emissions of the vehicle were similar to the background level (～ 0.4 mg/km) and the method was subject to volatile artifact. The PN method showed greater sensitivity than the PM method as it could distinguish the DPF fill state or different preconditioning states of the vehicle. However, the PN emission level of the vehicle estimated by the reference system were on average 15% higher than any given lab's own system, indicating that the procedures and calibration designed for the standardization of performance should be precisely defined and followed.     

Measurement of Automotive Nonvolatile Particle Number Emissions within the European Legislative Framework: A Review

In 2011, the European Commission introduced a limit for nonvolatile particle number (PN) emissions >23 nm from light-duty (LD) vehicles and the stated intent is to implement similar legislation for on-road heavy-duty (HD) engines at the next legislative stage. This paper reviews the recent literature regarding the operation-dependent emission of PN from LD vehicles and HD engines, and the measurement procedure used for regulatory purposes. The repeatability of the PN method is of the order of 5% and higher scatter of the results can easily be explained by the effect of the vehicles or the aftertreatment devices on the PN emissions (e.g., the fill state of the diesel particulate filters). Reproducibility remains an issue since it may exceed 30%. These high-variability levels are mainly associated with calibration uncertainties of the PN instruments. Correlation measurements between the full-flow dilution tunnels (constant-volume samplers, CVS) and the proportional partial-flow dilution systems (PFDS) showed agreement within 15% for the PN method down to 1 × 10¹¹ p/kWh. At lower concentrations, the PN background of the CVS and/or the PFDS can result in larger inconsistencies. The filter-based particulate matter (PM) mass and the PN emissions correlate well down to 1–2 mg/km for LD vehicles and to 2–3 mg/kWh for HD applications. The correlation improves when only elemental carbon mass is considered: it is relatively good down to 0.1–0.3 mg/km or mg/kWh.

Copyright 2012 American Association for Aerosol Research     

An integrative model for the filtration efficiencies in realistic tests with consideration of the filtration velocity profile and challenging particle size distribution

Many well-established models can be applied to calculate the filtration efficiencies. In these models the filtration velocity and challenging particle size are assumed to be known accurately. However, in realistic filtration tests, the filtration velocity has profiles dependent on the filter holder geometry and experimental conditions; the challenging particles have size distributions dependent on the instruments and operation conditions. These factors can potentially affect the measured filtration efficiency and lead to discrepancies with the models.

This study aims to develop an integrative model to predict the filtration efficiencies in realistic tests by incorporating the effects of the filtration velocity profile and challenging particle size distribution classified by a differential mobility analyzer (DMA) into the existing filtration models. Face velocity profile is modeled with fluid mechanics simulations; the initial generated particle size distribution, the particle charging status and the DMA transfer function are modeled to obtain the challenging particle size distribution. These results are then fed into the filtration models. Simulated results are compared with experimental ones to verify the model accuracy. This model can be used to reduce filtration test artifacts and to improve the experimental procedure.

The results reveal that the face velocity upstream the filter exhibits high degree of homogeneity not affecting the filtration efficiency if the filter pressure drop is not very low. The generated particle size distribution and the DMA selection size window could influence the challenging particle size distribution and therefore the measured filtration efficiency.

Copyright © 2017 American Association for Aerosol Research     

The state-of-practice in requirements elicitation: an extended interview study at 12 companies

Requirements Engineering - Requirements engineering remains a discipline that is faced with a large number of challenges, including the implementation of a requirements elicitation process in...     

Improving accuracy in astrocytomas grading by integrating a robust least squares mapping driven support vector machine classifier into a two level grade classification scheme

Grading of astrocytomas is an important task for treatment planning; however, it suffers from significantly great inter-observer variability. Computer-assisted diagnosis systems have been propose to assist towards minimizing subjectivity, however, these systems present either moderate accuracy or utilize specialized staining protocols and grading systems that are difficult to apply in daily clinical practice. The present study proposes a robust mathematical formulation by integrating state-of-art technologies (support vector machines and least squares mapping) in a cascade classification scheme for separating low from high and grade III from grade IV astrocytic tumours. Results have indicated that low from high-grade tumours can be correctly separated with a certainty as high as 97.3%, whereas grade III from grade IV tumours with 97.8%. The overall performance was 95.2%. These high rates have been a result of applying the least squares mapping technique to features prior to classification. A significant byproduct of least squares mapping is that the number of support vectors of the SVM classifiers dropped dramatically from about 80% when no mapping was used to less than 5% when mapping was used. The latter is a clear indication that the SVM classifier has a greater potential to generalize well to new data. In this way, digital image analysis systems for automated grading of astrocytomas are brought closer to clinical practice.