CHO Model Research Articles

A Novel Method to Predict Carbohydrate and Energy Expenditure During Endurance Exercise Using Measures of Training Load.

Sports nutrition guidelines recommend carbohydrate (CHO) intake be individualized to the athlete and modulated according to changes in training load. However, there are limited methods to assess CHO utilization during training sessions. We aimed to (1) quantify bivariate relationships between both CHO and overall energy expenditure (EE) during exercise and commonly used, non-invasive measures of training load across sessions of varying duration and intensity and (2) build and evaluate prediction models to estimate CHO utilization and EE with the same training load measures and easily quantified individual factors. This study was undertaken in two parts: a primary study, where participants performed four different laboratory-based cycle training sessions, and a validation study where different participants performed a single laboratory-based training session using one of three exercise modalities (cycling, running, or kayaking). The primary study included 15 cyclists (five female; maximal oxygen consumption [ O2max], 51.9 ± 7.2mL/kg/min), the validation study included 21 cyclists (seven female; O2max 53.5 ± 11.0mL/kg/min), 20 runners (six female; O2max 57.5 ± 7.2mL/kg/min), and 18 kayakers (five female; O2max 45.6 ± 4.8mL/kg/min). Training sessions were quantified using six training load metrics: two using heart rate, three using power, and one using perceived exertion. Carbohydrate use and EE were determined separately for aerobic (gas exchange) and anaerobic (net lactate accumulation, body mass, and O2 lactate equivalent method) energy systems and summed. Repeated-measures correlations were used to examine relationships between training load and both CHO utilization and EE. General estimating equations were used to model CHO utilization and EE, using training load alongside measures of fitness and sex. Models were built in the primary study and tested in the validation study. Model performance is reported as the coefficient of determination (R2) and mean absolute error, with measures of calibration used for model evaluation and for sport-specific model re-calibration. Very-large to near-perfect within-subject correlations (r = 0.76-0.96) were evident between all training load metrics and both CHO utilization and EE. In the primary study, all models explained a large amount of variance (R2 = 0.77-0.96) and displayed good accuracy (mean absolute error; CHO = 16-21g [10-14%], EE = 53-82kcal [7-11%]). In the validation study, the mean absolute error ranged from 16-50g [15-45%] for CHO models to 53-182kcal [9-31%] for EE models. The calibrated mean absolute error ranged from 9-20g [8-18%] for CHO models to 36-72kcal [6-12%] for EE models. At the individual level, there are strong linear relationships between all measures of training load and both CHO utilization and EE during cycling. When combined with other measures of fitness, EE and CHO utilization during cycling can be estimated accurately. These models can be applied in running and kayaking when used with a calibration adjustment.

Cholesterol-dependent dynamic changes in the conformation of the type 1 cholecystokinin receptor affect ligand binding and G protein coupling.

Development of optimal therapeutics for disease states that can be associated with increased membrane cholesterol requires better molecular understanding of lipid modulation of the drug target. Type 1 cholecystokinin receptor (CCK1R) agonist actions are affected by increased membrane cholesterol, enhancing ligand binding and reducing calcium signaling, while agonist actions of the closely related CCK2R are not. In this work, we identified a set of chimeric human CCK1R/CCK2R mutations that exchange the cholesterol sensitivity of these 2 receptors, providing powerful tools when expressed in CHO and HEK-293 model cell lines to explore mechanisms. Static, low energy, high-resolution structures of the mutant CCK1R constructs, stabilized in complex with G protein, were not substantially different, suggesting that alterations to receptor dynamics were key to altered function. We reveal that cholesterol-dependent dynamic changes in the conformation of the helical bundle of CCK receptors affects both ligand binding at the extracellular surface and G protein coupling at the cytosolic surface, as well as their interrelationships involved in stimulus-response coupling. This provides an ideal setting for potential allosteric modulators to correct the negative impact of membrane cholesterol on CCK1R.

Study on Vehicle Fuel Consumption and Exhaust Emissions Based on a New Viscous Macroscopic Traffic Flow Model

Based on a conserved higher-order traffic flow model (CHO model), we propose a new viscous macroscopic traffic flow model taking into account the diffusion effect in traffic. The model can reasonably smooth the shock wave so that the acceleration is maintained in a reasonable range. To balance the computational efficiency and accuracy, this viscous macroscopic traffic flow model is integrated with the microscopic vehicle fuel consumption and emission models to estimate vehicle fuel consumption and exhaust emissions. The local discontinuous Galerkin (LDG) method is used to solve the viscous model, and the simulation results are inputted into the microscopic models to calculate vehicle fuel consumption and exhaust emissions. Numerical results illustrate that the proposed viscous model is reasonable and that the designed scheme is feasible and effective. Moreover, we provide concrete suggestions for controlling vehicle fuel consumption and exhaust emissions.

CT Image Quality Assessment by a Channelized Hotelling Observer: Optimization of Adaptive Statistical Iterative Reconstruction for Radiation Dose Reduction and Improving Image Quality of Pediatric Abdominal CT Scan

Background: Iterative reconstruction (IR) techniques have tried to reduce the radiation dose of computed tomography (CT) scans while maintaining the image quality. One of the IR techniques is the adaptive statistical iterative reconstruction (ASIR). Increasing the amount of ASIR in image reconstruction can lead to the emergence of artifacts and reduce the ability to detect objects with low contrast. Objective: This study aimed to optimize the ASIR technique to reduce the radiation dose and increase image quality in pediatric abdominal CT. Methods: This is a phantom study performed using variable tube current (40,100,140 and 200mA) and ASIR level (ASIR 10% to ASIR 100%). Various criteria including noise, high-contrast spatial resolution, and Channelized Hotelling observer’s model were used to compare image quality at different captured levels. In this study CHO model was used for low contrast detectability. Results: The result was quit promising in the term of CHO’s used for mentioned purposes. The noise of reconstructed images with 30% ASIR and higher levels had a significant difference compared to the reconstructed images by the Filter Back Projection (FBP) method (P < 0.05). The spatial resolution of the images with tube currents of 140, 100, and 40 mA reconstructed with 30, 50, and 80% levels of ASIR technique was equal to 0.8 ± 0.144 pairs of lines per millimeter. The amount of the spatial resolution of images obtained with standard radiation dose and reconstructed by FBP method was 1 pair of lines per mm (p> 0.05). Conclusion: Based on the results of this study, using 50% ASIR for the pediatric population can reduce the radiation dose on abdominal and pelvic CT scans by 50% while maintaining image quality. Furthermore using ASIR 50% only for the reconstruction of abdominal and pelvic images in children at standard radiation dose leads to optimal image quality.

Biochemical characterization and cytotoxicity of polylactosamine-extended N-glycans binding isolectins from the mushroom Hericium erinaceus

The mushroom Hericium erinaceus expresses isolectins with different glycan binding specificities; of these, the ricin B-like lectin HEL1 and HEL2 (HEL2a and HEL2b) can bind fucosylated N-glycans and core 1 O-glycans, respectively. However, other lectin-like protein-coding transcripts detected in the H. erinaceus transcriptome, named HEL3, remain to be characterized. Therefore, in this study, the expression levels of all these isolectins genes were compared to characterize the molecular and biochemical properties of these carbohydrate-binding proteins. Low expression genes encoding putative cytolysin proteins, HEL3a and HEL3b, were identified. Bioinformatics analyses revealed that these proteins shared highly homologous structures and carbohydrate-binding residues with other mushroom lectins. Further, their recombinant proteins, rHEL3a and rHEL3b showed an octamer composed of identical 17 kDa subunits under non-denaturing conditions and a slightly basic isoelectric point value of approximately 8.3. The hemagglutination activity of these isolectins was strongly inhibited by glycoproteins rather than free glycans. Interestingly, glycan-binding profiles showed that rHEL3 isolectins interacted with most polylactosamine (poly-LacNAc)-extended N-glycans with relatively low binding activity. Isothermal titration calorimetry also revealed that these recombinant lectins have different binding capacities toward N-glycan-containing glycoproteins. Further, treatment with different concentrations of rHEL3 lectins showed cytotoxic effects in K562, UACC62, and CHO model cell lines, which express poly-LacNAc glycans, confirmed by inhibition of proliferation. Overall, these biochemical properties indicate that rHEL3 isolectins may be used as unique lectins for detecting poly-LacNAc-extended glycans, which are known to be over-expressed in leukemia or metastatic melanoma cells, in cancer diagnostic assays and anti-cancer therapies.

Investigation on the density of Al2O3/R1234yf, TiO2/R1234yf and CuO/R1234yf nano-refrigerants

Nano-enhanced refrigerant is one of the promising heat transfer fluids in refrigeration systems. It has the capability to boost the efficiency of vapour compression refrigeration and air conditioning systems. In heat transfer application, the density of the fluid plays a crucial role in identifying various heat transfer characteristics such as the Reynolds number, Nusselt number, the friction factor and the pressure loss. Compared to thermal conductivity and viscosity, determining the density of nanofluids has received very less attention in research. The liquid and vapour densities of alumina (Al2O3), titanium dioxide (TiO2) and cupric oxide (CuO) nanoparticles suspended in 2,3,3,3-tetrafluoropropene (R1234yf) are investigated in this study. The Pak and Cho model was adopted to examine the densities of nano-refrigerants as the volume concentration of particles in the base refrigerant and temperature varies from 1% to 5% and 273 to 323 K respectively. The models are validated using the experimental studies conducted by various researchers on different nano-refrigerants. The analysis results indicated that the liquid and vapour densities of CuO/R1234yf nano-refrigerant are 10.3% and 62.93% greater than that of Al2O3/R1234yf at 5% particle concentration. From the liquid and vapour density point of view, the CuO/R1234yf nano-refrigerant is superior over Al2O3/R1234yf and TiO2/R1234yf. Results also indicated that at 308 K the liquid phase density of CuO added with R1234yf nano-refrigerant is higher by 12.99% and 8.65% than R134a and R141b respectively. Hence CuO/R1234yf significantly enhances the performance of refrigeration systems.

Riemann solvers of a conserved high-order traffic flow model with discontinuous fluxes

A conserved high-order traffic flow model (CHO model) is extended to the case with discontinuous fluxes which is called the CHO model with discontinuous fluxes. Based on the independence of its homogeneous subsystem and the property of Riemann invariants, Riemann solvers to the homogeneous CHO model with discontinuous fluxes are discussed. Moreover, we design the first-order Godunov scheme based on the Riemann solvers to solve the extended model, and prove the invariant region principle of numerical solutions. Two numerical examples are given to illustrate the effectiveness of the extended model and the designed scheme.

Determining the Optimum Process Mean for the Larger-The-Better Weibull Quality Characteristic

In Cho and Leonard's piecewise linear loss function for the larger-the-better quality characteristic, the quality loss is positively and linearly proportional to the deviation from the lower specification limit (LSL) when the quality characteristic is less than the LSL. The quality loss is equal to zero when the quality characteristic is greater than or equal to the LSL. However, the quality loss should be equal to zero when the value of quality characteristic approaches infin- ity for the larger-the-better characteristic. In this paper, we modify Cho and Leonard's piecewise linear loss function for measuring the product quality and determine the optimum process mean. Assuming that the quality characteristic follows a Weibull distribution and is larger-the-better, the application of determining the optimum process mean for the modified Cho and Leonard's model with piecewise linear loss function is discussed.

Emotional Labor and Other Antecedence of Turnover Intentions, Motivation and Organisational Trust among Employees in Non-Profit Organization of Pakistan

Although the retention of competent workers is critical in all organizations, retaining social workers in nonprofit organizations is especially important because they mainly determine the quality of social services. This paper explores the factors which have an impact on turnover intentions, motivation, and organizational trust in Non-Profit Organizations. For this, we propose a theoretical framework thereby modifying Cho & Song (2017) model, along with adding intrinsic factors like organizational culture, leadership, and rewards. We hypothesize that factors like 1. Supervisory Support, 2. Autonomy, 3. Diverse and inclusive Organizational Culture, 4. Trust in Leadership, 5. Monetary Incentives/ Rewards, and emotional labor (6. Frequency, 7. Variety, 8. Duration, and 9. Intensity level), all produce a positive effect on the motivation of employees, increased Organisational Trust, and decreased Turnover intention among employees of NPO and social workers. This paper particularly focused on emotional labor dimensions such as frequency of emotional display, the intensity of emotional display, and duration of emotional display. Empirical validity was established by conducting a survey using a close-ended questionnaire. Data were collected from 220 social workers and analyzed using confirmatory factor analysis and structured equation modeling. The results indicate that supervisory support, autonomy, leadership organizational culture, and trust have a significant effect on the motivation, retention, and Organizational trust of employees. However, organizational culture have a negative effect on motivation. Moreover, Apart from leadership, all other factors seem to increase the turnover intentions. With regards to emotional labor dimensions, all factors expect duration did not produce any significant effect on all three dependent variables. This research is useful for NPO’s management as well as future scholars for studying the same domain.

A machine learning-based model to estimate the density of nanofluids of nitrides in ethylene glycol

The density of nanofluids is an important thermophysical property whose value is required to evaluate various heat-transfer parameters such as the Reynolds number, the Nusselt number, pressure loss, and the Darcy friction factor. The determination of these parameters is central to the design of many heat-transfer applications. Notably, the density of nanofluids has received relatively little research attention compared with other thermophysical properties. The present study thus focuses on the development of a support vector regression model to estimate the densities of aluminum nitride, titanium nitride, and silicon nitride nanoparticles dispersed in ethylene glycol solution. As inputs, the proposed model uses the mass fraction, temperature, nanoparticle size, and the molecular weight of the nanoparticles. The proposed model predicts the nanofluid densities with high accuracy, as determined by a correlation coefficient of 99.87% and an absolute average relative deviation of 0.0701. To further highlight the accuracy of the proposed model, we compare its results with those of the model of Pak and Cho. The Pak and Cho results deviate considerably from the experimental data except at 298 K. Overall, the proposed support vector regression model is much more accurate than the Pak and Cho model. We thus conclude that the machine learning approach is more reliable for obtaining rapid estimates of the density of nanofluids.

205 - The role of Sdc-4 proteoglycan in the production of NO in endothelial cells

Proteoglycans are transmembrane proteins that act as a signal transducer in communication between cells and with the extracellular matrix. In a recently published article (Lucena et al., 2018) we have shown that there is an increase in the production of reactive oxygen species and nitric oxide (NO) in mutant CHO cells for the expression of Xylosyl transferase, the enzyme responsible for the addition of glycosaminoglycans (GAGs) to the core protein. This production is associated with an increase in endothelial Nitric Oxide Synthase (NOS3) activity. In another recent publication (Cavalheiro et al., 2017), syndecan-4 (Sdc-4), a heparan sulfate proteoglycan (HSPG), was silenced in a rabbit aortic endothelial cell (RAEC). It was observed that Sdc-4 is a central mediator in focal adhesion complex and, when absent, it led to a disruption of the cytoskeleton. This feature was further explored in this present work because we were unable to cultivate the cells in shear stress conditions, most of them would always detach from the surfaces. The wild-type endothelial cells presented an activation of focal adhesion complex. We also measured an increased level of intracellular oxidation (GSSG :GSH ratio) in this present work, as it was observed in the CHO model. Another resemblance was the higher production NO in comparison to the wild-type cells, in this case, the production is maintained by the inducible NOS (NOS2). In conclusion, we account an important role for HSPG on REDOX status alterations within cells, but Sdc-4 has been shown to regulate this by specifically altering iNOS expression. (Financing agencies: FAPESP, CAPES and CNPq).

Effects of phosphorylation state on perilipin 5 localization and trafficking.

Perilipins are a family of five proteins found on the surface of lipid storage droplets in nearly all tissues. These proteins act as cofactors for lipases and scaffolding for other proteins involved in lipid metabolism. In addition to the lipid droplet surface, members of the perilipin family have been found in the cytosol, endoplasmic reticulum, plasma membrane and mitochondria. The localization of these proteins is in part determined by their phosphorylation state. Recently perilipin 5 has been shown to localize to the nucleus when phosphorylated by PKA on serine 155 and interact with the peroxisome proliferator‐activated receptor gamma coactivator alpha (PGC‐1a). In silico analysis of a phosphomimetic mutant (Ser155Asp) indicate that this site may contain a nuclear localization sequence. Using a CHO model cell line we observed that translocation to the nucleus could be stimulated by treatment with forskolin and isobutylmethylxanthine (IBMX) and occurred independent of treating cells with oleic acid to promote triacylglycerol deposition. We are currently investigating the affects of stimulating other phosphorylation pathways to determine if they also phosphorylate perilipin 5 and affect subcellular localization. These data have the potential to gain insights to the regulation of perilipin 5 trafficking into the nucleus and therefore interacting with PGC‐1a regulating mitochondrial biogenesis.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Workflow for Target-Oriented Parametrization of an Enhanced Mechanistic Cell Culture Model.

The goal of this study is to develop a macroscopic mechanistic model describing growth and production within fed-batch cultivations of CHO cells. The model should be used for process characterization as well as for process monitoring including real-time parameter adaptations. The model proved to be able to describe a data-set of 40 processes differing in clones, scales, and process conditions with a normalized root mean square error of approximately 10%. However, due to limited parameter identifiability and limited knowledge about physiologically meaningful parameter values, a broad range of parameters could describe the data with similar quality. This hampered comparison of the model parameters as well as their real-time estimation. Therefore an iterative workflow combining techniques like sensitivity and identifiability analysis, analysis of the specific rates as well as structural adaptations of the parameter space is developed. By applying it the parameter variability could be reduced by 80% with similar predictive power as the original parameters. Summing up, based on a mechanistic CHO model, a generic and transferrable workflow is created for target-oriented parameter estimation in case of limited parameter identifiability. Finally, we suggest a methodology, which fits ideally into the frame of Process Analytical Technology aiming to increase process understanding.

Calcium channels are involved in EphB/ephrinB reverse signaling‑induced apoptosis in a rat chronic ocular hypertension model.

Erythropoietin-producing hepatocyte receptor B (EphB)/ephrinB reverse signaling has been revealed to be activated in chronic ocular hypertension (COH) by increasing the apoptosis of retinal ganglion cells (RGCs). However, the exact mechanism is not well understood. The present study investigated the involvement of Ca2+ channels in the apoptosis of RGCs induced by EphB/ephrinB reverse signaling in a rat CHO model, which was established by cauterizing 3 out of the 4 episcleral veins. The expression levels of four voltage-gated Ca2+ channel subunits (Cav3.1–3.3 and Cav1.2) were detected using immunofluorescence and western blot analysis. TUNEL staining was performed to assess RGC apoptosis following an injection with the T type Ca2+ channel blocker. Ca2+ channels, mainly the T type, were upregulated in COH rat retinas when compared with the sham group (P<0.01). Additionally, the Cav3.2 subunit of T type calcium channels was predominantly expressed in Müller cells and RGCs, such as ephrinB2. Furthermore, an intravitreal injection of the Ca2+ channel blocker Mibefradil (3 µM) reduced EphB2-fragment crystallizable region-induced RGC apoptosis in normal rats. Thus, the results suggest that Ca2+ channels in a COH model may be a pathway involved in ephrinB/EphB signaling-induced RGC apoptosis.

Online Advertising

This study expands previous models of avoidance on online advertising, in particular, Cho and Cheon (2004)'s model, and examines two new dimensions on why people avoid advertising on the Internet. The study presents a comprehensive theoretical model and examines seven exogenous latent variables based on structural equation modeling, SEM. By using SEM the authors found that seven latent variables including user-perceived ad quality, internet life style, primary motives, gender differences (initial ad avoidance), perceived ad clutter, prior negative experience, and perceived goal impediment (further ad avoidance) collectively explain why people avoid advertising on the Internet. The authors found that avoidance has two key dimensions «initial ad avoidance» and «further ad avoidance.”

Correlation between a 2D channelized Hotelling observer and human observers in a low-contrast detection task with multislice reading in CT.

Model observers have been successfully developed and used to assess the quality of static 2D CT images. However, radiologists typically read images by paging through multiple 2D slices (i.e., multislice reading). The purpose of this study was to correlate human and model observer performance in a low-contrast detection task performed using both 2D and multislice reading, and to determine if the 2D model observer still correlate well with human observer performance in multislice reading. A phantom containing 18 low-contrast spheres (6 sizes × 3 contrast levels) was scanned on a 192-slice CT scanner at five dose levels (CTDIvol = 27, 13.5, 6.8, 3.4, and 1.7 mGy), each repeated 100 times. Images were reconstructed using both filtered-backprojection (FBP) and an iterative reconstruction (IR) method (ADMIRE, Siemens). A 3D volume of interest (VOI) around each sphere was extracted and placed side-by-side with a signal-absent VOI to create a 2-alternative forced choice (2AFC) trial. Sixteen 2AFC studies were generated, each with 100 trials, to evaluate the impact of radiation dose, lesion size and contrast, and reconstruction methods on object detection. In total, 1600 trials were presented to both model and human observers. Three medical physicists acted as human observers and were allowed to page through the 3D volumes to make a decision for each 2AFC trial. The human observer performance was compared with the performance of a multislice channelized Hotelling observer (CHO_MS), which integrates multislice image data, and with the performance of previously validated CHO, which operates on static 2D images (CHO_2D). For comparison, the same 16 2AFC studies were also performed in a 2D viewing mode by the human observers and compared with the multislice viewing performance and the two CHO models. Human observer performance was well correlated with the CHO_2D performance in the 2D viewing mode [Pearson product-moment correlation coefficient R = 0.972, 95% confidence interval (CI): 0.919 to 0.990] and with the CHO_MS performance in the multislice viewing mode (R = 0.952, 95% CI: 0.865 to 0.984). The CHO_2D performance, calculated from the 2D viewing mode, also had a strong correlation with human observer performance in the multislice viewing mode (R = 0.957, 95% CI: 879 to 0.985). Human observer performance varied between the multislice and 2D modes. One reader performed better in the multislice mode (P = 0.013); whereas the other two readers showed no significant difference between the two viewing modes (P = 0.057 and P = 0.38). A 2D CHO model is highly correlated with human observer performance in detecting spherical low contrast objects in multislice viewing of CT images. This finding provides some evidence for the use of a simpler, 2D CHO to assess image quality in clinically relevant CT tasks where multislice viewing is used.

Statistical Mechanics of Node-perturbation Learning with Noisy Baseline

Node-perturbation learning is a type of statistical gradient descent algorithm that can be applied to problems where the objective function is not explicitly formulated, including reinforcement learning. It estimates the gradient of an objective function by using the change in the object function in response to the perturbation. The value of the objective function for an unperturbed output is called a baseline. Cho et al. proposed node-perturbation learning with a noisy baseline. In this paper, we report on building the statistical mechanics of Cho's model and on deriving coupled differential equations of order parameters that depict learning dynamics. We also show how to derive the generalization error by solving the differential equations of order parameters. On the basis of the results, we show that Cho's results are also apply in general cases and show some general performances of Cho's model.

Mixed convection heat transfer of ethylene glycol and water mixture based Al2O3 nanofluids: Effect of thermal conductivity models

The effect of different nanofluid thermal conductivity models on the mixed convection flow and heat transfer in a lid-driven square enclosure heated from the left vertical wall and cooled from the top wall was investigated numerically in this study for various values of the governing parameters. The Al2O3 was assumed as nanoparticle and ethylene glycol-water mixture as the base fluid. Three different nanoparticle volume fractions were taken into consideration: 0%, 4% and 8%. Four different volume ratios of EG to water were considered: 0:100%, 40:60%, 60:40% and 100:0%. The Grashof number was assumed constant at a value of 104 and the Reynolds number was varied in a range so that the Richardson number takes values in the range of 0.1 to 10. The results show that the average Nusselt number has a linear dependency on the nanoparticle volume fraction for all the thermal conductivity models considered in this study. The results also show that the thermal conductivity models produce considerably different average Nusselt numbers. The results also indicate that the average Nusselt number from the highest to the lowest is for: Pak and Cho model, Yu and Choi model, Ghanbarpour et al. model, Maxwell model, and Timofeeave et al. model. The results finally show that Pak and Cho model yields considerably higher average Nusselt numbers than the other models.

Assessment of low contrast detection in CT using model observers: Developing a clinically-relevant tool for characterising adaptive statistical and model-based iterative reconstruction

PurposeThis study aims to assess CT image quality in a way that would meet specific requirements of clinical practice. Physics metrics like Fourier transform derived metrics were traditionally employed for that. However, assessment methods through a detection task have also developed quite extensively lately, and we chose here to rely on this modality for image quality assessment. Our goal was to develop a tool adapted for a fast and reliable CT image quality assessment in order to pave the way for new CT benchmarking techniques in a clinical context. Additionally, we also used this method to estimate the benefits brought by some IR algorithms. Materials and methodsA modified QRM chest phantom containing spheres of 5 and 8mm at contrast levels of 10 and 20HU at 120kVp was used. Images of the phantom were acquired at CTDIvol of 0.8, 3.6, 8.2 and 14.5mGy, before being reconstructed using FBP, ASIR 40 and MBIR on a GE HD 750 CT scanner. They were then assessed by eight human observers undergoing a 4-AFC test. After that, these data were compared with the results obtained from two different model observers (NPWE and CHO with DDoG channels). The study investigated the effects of the acquisition conditions as well as reconstruction methods. ResultsNPWE and CHO models both gave coherent results and approximated human observer results well. Moreover, the reconstruction technique used to retrieve the images had a clear impact on the PC values. Both models suggest that switching from FBP to ASIR 40 and particularly to MBIR produces an increase of the low contrast detection, provided a minimum level of exposure is reached. ConclusionOur work shows that both CHO with DDoG channels and NPWE models both approximate the trend of humans performing a detection task. Both models also suggest that the use of MBIR goes along with an increase of the PCs, indicating that further dose reduction is still possible when using those techniques. Eventually, the CHO model associated to the protocol we described in this study happened to be an efficient way to assess CT images in a clinical environment. In the future, this simple method could represent a sound basis to benchmark clinical practice and CT devices.

Subcellular Localization of Matrin 3 Containing Mutations Associated with ALS and Distal Myopathy.

BackgroundMutations in Matrin 3 [MATR3], an RNA- and DNA-binding protein normally localized to the nucleus, have been linked to amyotrophic lateral sclerosis (ALS) and distal myopathies. In the present study, we have used transient transfection of cultured cell lines to examine the impact of different disease-causing mutations on the localization of Matrin 3 within cells.ResultsUsing CHO and human H4 neuroglioma cell models, we find that ALS/myopathy mutations do not produce profound changes in the localization of the protein. Although we did observe variable levels of Matrin 3 in the cytoplasm either by immunostaining or visualization of fluorescently-tagged protein, the majority of cells expressing either wild-type (WT) or mutant Matrin 3 showed nuclear localization of the protein. When cytoplasmic immunostaining, or fusion protein fluorescence, was seen in the cytoplasm, the stronger intensity of staining or fluorescence was usually evident in the nucleus. In ~80% of cells treated with sodium arsenite (Ars) to induce cytoplasmic stress granules, the nuclear localization of WT and F115C mutant Matrin 3 was not disturbed. Notably, over-expression of mutant Matrin 3 did not induce the formation of obvious large inclusion-like structures in either the cytoplasm or nucleus.ConclusionsOur findings indicate that mutations in Matrin 3 that are associated with ALS and myopathy do not dramatically alter the normal localization of the protein or readily induce inclusion formation.