Correlation of MET-Receptor Overexpression with MET Gene Amplification and Patient Outcome in Malignant Mesothelioma

Thanks to clinically newly introduced inhibitors of the mesenchymal–epithelial transition (MET) receptor tyrosine-kinase, MET-gene copy number gain/amplification (MET-GCNG/GA) and increased expression of the MET protein are considered very promising therapeutic targets in lung cancer and other malignancies. However, to which extent these MET alterations occur in malignant mesothelioma (MM) remains unclear. Thus, we investigated by well-established immunohistochemistry and fluorescence in situ hybridization methods, the frequency of these alterations in specimens from 155 consecutive MMs of different subtypes obtained from pleural or peritoneal biopsies and pleurectomies. Thirty-three benign reactive mesothelial proliferations (RMPs) were used as controls. MET-protein upregulation was observed in 35% of all MM-cases, though restricted to predominantly epithelioid MMs. We detected low-/intermediate-level MET-GCNG/GA in 22.2% of MET-overexpressing MMs (7.8% of whole MM-cohort) and no MET-GCNG/GA in the other 77.8%, suggesting other upregulating mechanisms. In contrast, 100% of RMPs exhibited no MET-upregulation or MET-GCNG/-GA. Neither MET exon 14 skipping mutations nor MET-fusions were detected as mechanisms of MET overexpression in MM using RNA next-generation sequencing. Finally, in two cohorts of 30 MM patients with or without MET overexpression (MET-positive/-negative) that were matched for several variables and received the same standard chemotherapy, the MET-positive cases showed a significantly lower response rate, but no significant difference in progression-free or overall survival. Our results imply that MET overexpression occurs in a substantial fraction of predominantly epithelioid MMs, but correlates poorly with MET-amplification status, and may impact the likelihood of response to mesothelioma standard chemotherapy. The predictive significance of MET-IHC and -FISH for possible MET-targeted therapy of MM remains to be elucidated.     

Dynamic State Estimation for Microgrid Structures

Abstract

In this article, the dynamic state estimation of the islanded microgrids problem is addressed. The electrical network and energy sources are represented as a set of Nonlinear Differential Algebraic Equations, with the aim to capture the nonlinear phenomena and a novel solution, by using a variation of the Kalman Filter ad hoc for differential algebraic systems, is presented. In this representation, the state is given by the voltage phasors at each bus and the variables related to the energy sources. The proposed algorithm permits not only to effectively obtain an estimate of the state variables but also it allows to recover these variables during the microgrid transient behavior. Moreover, the estimation may be carried out using fewer measurements than those needed by conventional static estimators. The performance of the proposed dynamic state estimator is evaluated via numerical experiments using two practical microgrids containing wind power and hydroelectric generators. This novel method has been tested for load variations and wind speed changes demonstrating its capabilities and efficiency.     

On‐line estimation of switched reluctance motor parameters

This paper addresses the problem of on‐line parameter estimation of switched reluctance motors and provides, to the best of the authors' knowledge, the first result that takes into account the dynamics of both electrical and mechanical subsystems. Based on a widely‐used standard model of the motor and establishing a reasonable structure for modeling the unknown load torque, a linear parametric model is derived and a 2‐stage identification scheme is proposed and implemented with the recursive least‐squares algorithm with forgetting factor. It is assumed that stator voltages and currents and rotor position and speed are available through measurements. Numerical simulations and experimental tests are included for a 3‐phase 12/8 switched reluctance motor. The results show a good performance of the proposed methodology, and the estimated parameters are validated through their use in a closed‐loop control scheme. Key features of the proposed solution are that it does not rely on locked‐rotor tests nor does it assume previous knowledge of the magnetization curves of the motor. The estimation scheme is intended to improve the performance and efficiency of currently available control algorithms, and it is potentially useful for the design of selfcommissioning switched reluctance drives, ie, drives that can automatically adjust the controller parameters for a wide range of motors and loads.     

Novel mucoadhesive system based on sulfhydryl-acrylate interactions

We propose a novel cross-linked mucoadhesive system that can interact covalently with mucin type glycoprotein, thus providing both strong bonding to mucosa as well as ability to function as a sustained release matrix. The strong bonding results from Michael type addition reaction between an acrylate end group on a polymer and the sulfide end group of the mucin type glycoprotein. A proof of concept is provided using a polyehtylene glycol hydrogel formed in situ from polyehtylene glycol di-acrylate (PEG-DA) macromers. The ability of PEG-DA to create interactions with mucin type glycoproteins was verified using nuclear magnetic resonance (NMR) and rheology experiments. NMR studies have detected disappearance of the PEG-DA’s vinyl protons upon mucin addition, whereas rheology measurements have shown a viscosity increase. These results provide an evidence for the formation of mucin-polymer covalent bond. The ability PEG-DA to attach to mucus and promote mucoadhesion was evaluated by tensile measurements. PEG-DA adhered at strength comparable to other covalently interacting mucoadhesive polymers. Furthermore, PEG-DA was found to be a suitable candidate for sustained release of the hydrophilic drug Ibuprofen.     

Influence of Time Discretization and Input Parameter on the ANN Based Synthetic Streamflow Generation

The capability of ANN to generate synthetic series of river discharge averaged over different time steps with limited data has been investigated in the present study. While an ANN model with certain input parameters can generate a monthly averaged streamflow series efficiently; it fails to generate a series of smaller time steps with the same accuracy. The scope of improving efficiency of ANN in generating synthetic streamflow by using different combinations of input data has been analyzed. The developed models have been assessed through their application in the river Subansiri in India. Efficiency of the ANN models has been evaluated by comparing ANN generated series with the historical series and the series generated by Thomas-Fiering model on the basis of three statistical parameters-periodical mean, periodical standard deviation and skewness of the series. The results reveal that the periodical mean of the series generated by both Thomas–Fiering and ANN models are in good agreement with that of the historical series. However, periodical standard deviation and skewness coefficient of the series generated by Thomas–Fiering model is inferior to that of the series generated by ANN.     

Determinants of antimicrobial treatment for udder health in Danish dairy cattle herds

Societal pressure to limit the use of antibiotics in livestock production systems, including dairy cattle systems, is consistently increasing. To motivate farmers to reduce antibiotic usage, it is important to understand the factors that determine whether a cow will be treated with antibiotics or not. If farmers' usual practices regarding antibiotic treatments are taken into account, they may be motivated to adopt control measures that can facilitate prudent use of antibiotics and are at the same time cost-effective. In this study, we analyzed database recordings of milk yield and somatic cell count from the routine milk recording scheme, clinical registrations of mastitis and PCR results, and cow factors such as days in milk and parity in relation to antibiotic treatments for 518 dairy herds in Denmark. Farm-wise logistic regressions were used to predict antimicrobial treatment based on these factors. The resulting regression coefficients of 422 herds were further analyzed by principal component analysis and clustering to determine the driving predictors for treatment in different groups of farms. The results showed that determinants that were most important for predicting antibiotic treatments vary from one farm to another. Health indicators such as PCR or somatic cell count were most indicative for treatment on some farms, whereas other groups seemed to depend more on production factors (milk yield) or later culling of the cows. This shows that farmers behave differently and differences can be identified in register data. This information can be considered when developing cost-effective herd-specific control measures of mastitis to promote prudent use of antibiotics in Danish dairy cattle farms.     

An economic perspective on experience curves and dynamic economies in renewable energy technologies

This paper analyzes dynamic economies in renewable energy technologies. The paper has two contributions. The first is to test the robustness of experience in solar photovoltaic, solar thermal and wind energy to the addition of an explicit time trend, which has been done in experience studies for other industries, but not for renewable energy technologies. Estimation is carried out on the assumption that cumulative capacity, industry production, average firm production, and electricity generation affect experience and thus the fall in price. The second contribution is to test the impact of R&D on price reduction. In general cumulative experience is found to be highly statistically significant when estimated alone, and highly statistically insignificant when time is added to the model. The effect of R&D is small and statistically significant in solar photovoltaic technology and statistically insignificant in solar thermal and wind technologies.     

Shear-wave splitting as a tool for the characterization of geothermal fractured reservoirs: lessons learned

We review our experience with the construction of models of subsurface fracturing in geothermal fields by the inversion of shear-wave splitting (SWS) observations from natural and induced seismic events recorded by local arrays of three-component digital seismometers. SWS is a phenomenon whereby shear seismic waves split into two as a result of the mechanical anisotropy created in an otherwise isotropic rock by aligned micro-fractures. The two split waves travel at different speeds, and the polarization of the faster wave is usually parallel to crack orientation. The time delay between the two split S-waves is proportional to the number of cracks per unit volume.Success in the inversion of SWS data hinges on the assumption that the observed SWS is due solely to the mechanical anisotropy induced by aligned cracks and micro-cracks in an otherwise isotropic matrix. The presence of lithologic anisotropy and/or strong heterogeneity in the reservoir rock limits the resolvability of the method. However, despite the large amount of data and diversity of geologic settings we have studied so far, the above assumption has been found to be reliable. In practice, stability and resolution in the inversion of SWS data are the issues of utmost importance since both are critically dependent on the distribution of the two SWS measured parameters (polarization and time delay) around each seismic sensor.In this paper we discuss a few lessons we have learned as to the value of SWS for geothermal exploration, its limitations and potential extensions, from nearly a decade of practice.     

Particle size distribution as a useful tool for microbial detection.

Worldwide, raw or treated wastewater is used for irrigation. However, this practice implies that the microbial content must be controlled. Unfortunately, detection techniques for microorganisms are costly, time consuming, and require highly trained personnel. For these reasons, this study used particle size distribution to measure the microbial quality of wastewater through correlations between the number or volume of particles and the concentration of fecal coliforms, Salmonella spp. and helminth ova. Such correlations were obtained for both raw and chemically treated wastewater. The best fit was the one for helminth ova, which applies for both the influent and effluent and also for all the coagulants involved. This technique allows the on-line quantification of helminth ova at a cost of US$3 and it takes only 5 minutes, instead of the US$70 and 5 days for the standard technique. With respect to the coagulants applied, their behavior is different only for particles smaller than 8 microm, and thus this value is considered as the critical size for this particular treatment. The best coagulant was the aluminium polychloride. In addition, this work establishes the distribution of COD, TSS, nitrogen, and phosphorous for particles smaller and larger than 20 microm.     

Effects of retort conditions on ATP-related compounds in pouched fish muscle

To examine the usefulness of high-temperature short time (HTST) process on quality of retorted fish products, adenosine triphosphate (ATP)-related compounds in raw fishes and retorted fish models (10 g/pouch) heated at 115 °C for 90 min (common retort (CR) process) or 125 °C for 9 min (HTST process) were analyzed by HPLC method. The raw materials used in this study were fresh chub mackerel Scomber japonicus for sashimi (raw eating), frozen-thawed yellowfin tuna Thunnus albacares for sashimi, frozen-thawed pink salmon Oncorhynchus gorbuscha for cooking and frozen-thawed pink shrimp Pandalus borealis for sashimi. In all the fish samples, the level of inosine monophosphate (IMP), an umami-taste compound, was higher in HTST fishes than in CR fishes. On the other hand, inosine (HxR) and hypoxanthine (Hx), no-taste and bitter taste compounds, was high in CR fishes. K-value, an index of fish freshness defined as the ratio of the sum of HxR and Hx to the sum of ATP-related compounds, was high in CR fishes. In sensory test of pink salmon by the paired difference test, umami and sweetness in the HTST fish were stronger than the ones of the CR fish. The bitterness was stronger in the CR fish rather than in the HTST fish. These results indicated that HTST is a favorable process for retorted fish product and measurement of ATP-related compounds is useful for the quality check of retorted fishes.