The prognostic value of positron emission tomography in non-small cell lung cancer: Analysis of 266 cases

Positron emission tomography (PET) is more accurate than computed tomography (CT) in the staging of non-small cell lung cancer (NSCLC). We analyzed the prognostic value of PET for survival in NSCLC patients. Methods: Consecutive patients with proven NSCLC with PET for staging were selected. Staging by laboratory tests, bronchoscopy, chest X-ray, and CT was performed in all patients, leading to a clinical stage (c-TNM) prior to PET. A separate classification (pet-TNM) was obtained from PET images by observers blinded to clinical data. We performed univariate survival analysis with ECOG performance score, sex, weight loss, comorbidity, histology, c-TNM, and pet-TNM as variables. Cox regression analysis was performed with significant variables from the univariate analyses. Results: Two hundred and sixty-six patients were included, 205 men and 61 women. c-TNM and pet-TNM were identical in 150 (56%) patients, 69 were upstaged, and 47 were downstaged by PET. At time of analysis, 198 (74%) patients had died. Univariate analysis showed significant survival differences for ECOG performance score (0 versus 1/2), weight toss (<10% versus :10%), pulmonary comorbidity, c-TNM, and pet-TNM (stage IA versus IB, IIA, IIB, IIIA, IIIB, IV). Cox regression analysis identified pet-TNM as the most significant (p < 0.001) prognostic factor, followed by ECOG performance score (p = 0.018). Conclusion: Tumor stage as determined by PET is the most significant prognostic factor for survival in patients with NSCLC. (C) 2006 Elsevier Ireland Ltd. All rights reserved

Synthesis of a mucous glycoprotein in the human uterus

Scrapings of endometrium and uterine contents of 10 women were analysed. In the uterine lumina of two women that used synthetic progestagens, a considerable amount of mucus was present. We fractionated the mucus by CsCl density equilibrium centrifugation into glycoprotein and protein fractions. With sugar and amino acid analysis the glycoprotein could be classified as a typical epithelial glycoprotein, resembling the cervical glycoprotein. It contains neuraminic acid (6.2%) and sulfate (8.4%). From the uteri of the other 8 women, who did not use hormones, a small amount of a similar glycoprotein could be isolated

Cavitation for improved sludge conversion into biogas

In several studies the beneficial influence of pre-treatment of waste activated sludge with cavitation on the biogas production was demonstrated. It is however, still not fully certain whether this effect should be mainly contributed to an increase in conversion rate of organics into biogas by anaerobic bacteria, and how much cavitation increases the total biogas yield. An increase in yield is only the case if cavitation can further disrupt otherwise inaccessible cell membrane structures and long chain organic molecules. In this study the influence of hydrodynamic cavitation on sludge that was already digested for 30 days was investigated. The total biogas yield could indeed be increased. The effect of the backpressure behind the venturi tube on the yield could not yet be established.Process and EnergyMechanical, Maritime and Materials Engineerin

Novel Design Integrating a Microwave Applicator into a Crystallizer for Rapid Temperature Cycling. A Direct Nucleation Control Study

The control of nucleation in crystallization processes is a challenging task due to the often lacking knowledge on the process kinetics. Inflexible (predetermined) control strategies fail to grow the nucleated crystals to the desired quality because of the variability in the process conditions, disturbances, and the stochastic nature of crystal nucleation. Previously, the concept of microwave assisted direct nucleation control (DNC) was demonstrated in a laboratory setup to control the crystal size distribution in a batch crystallization process by manipulating the number of particles in the system. Rapid temperature cycling was used to manipulate the super(under)saturation and hence the number of crystals. The rapid heating response achieved with the microwave heating improved the DNC control efficiency, resulting in halving of the batch time. As an extension, this work presents a novel design in which the microwave applicator is integrated in the crystallizer, hence avoiding the external loop though the microwaves oven. DNC implemented in the 4 L unseeded crystallizer, at various count set points, resulted in strong efficiency enhancement of DNC, when compared to the performance with a slow responding system. The demonstrated crystallizer design is a basis for extending the enhanced process control opportunity to other applications.Intensified Reaction and Separation System

A comparison of nonlinear observers for output feedback model-based control of seeded batch crystallization processes

This paper presents a comparative analysis of various nonlinear estimation techniques when applied for output feedback model-based control of batch crystallization processes. Several nonlinear observers, namely an extended Luenberger observer, an extended Kalman filter, an unscented Kalman filter, an ensemble Kalman filer and a moving horizon estimator are used for closed-loop control of a semi-industrial fed-batch crystallizer. The performance of the nonlinear observers is evaluated in terms of their closed-loop behavior as well as their ability to cope with model imperfections and process uncertainties such as measurement errors and uncertain initial conditions. The simulation results suggest that the extended Kalman filter and the unscented Kalman filter provide accurate state estimates that ensure adequate fulfillment of the control objective. The results also confirm that adopting a time-varying process noise covariance matrix further enhances the estimation accuracy of the latter observers at the expense of a slight increase in their computational burden. This tuning method is particularly suited for batch processes as the state variables often vary significantly along the batch run. It is observed that model imperfections and process uncertainties are largely detrimental to the accuracy of state estimates. The degradation in the closed-loop control performance arisen from inadequate state estimation is effectively suppressed by the inclusion of a disturbance model into the observers