Root cause analysis during process development using Joint-Y PLS

The original purpose of the JYPLS model was to aid product transfer and scale-up. This work demonstrates that the JYPLS model is also well suited to analyze data from a process in development where the number and type of sensors and sensor locations are also being decided. The specific application in this case was to determine the root cause for a bias found during the development of a multivariate calibration model for a Near Infrared (NIR) instrument. The calibration model was built in parallel with the development of the manufacturing process itself. Each time the calibration model was tested with data from a new batch run, a non-explained bias was observed. Laboratory results on samples gathered from the process show that the NIR signal itself was biased and not the actual concentration of the constituent. Data on the processing conditions were collected for all the batches and included in the JYPLS model along with NIR and lab results. The loadings and scores from the JYPLS model were interpreted to isolate the root cause of the observed drift in the calibration model. This work discusses the general approach and presents the sequence of diagnostics used to analyze the different campaigns during process development. This should be applicable to other scenarios in process development where the data has the same architecture.     

Comparison of electromyographic pattern of sensory experts and untrained subjects during chewing of Mahon cheese

Use of electromyography (EMG) to monitor mastication is a relatively new concept in assessing food physical and sensory properties. Although expert assessment of cheese characteristics is widely used, the effect of training in sensory analysis on mastication patterns, as assessed using EMG is not well known. Nine samples of the same Mahon cheese (60 days ripening) were given to 24 subjects (8 experts, 16 untrained) and EMG recorded for each chewing sequence. Three samples were tested in a single session by each subject, and three sessions carried out on different days. EMG was recorded from four masticatory muscles for each subject. From EMG records the following was extracted: number of chews, chewing time, mean and maximum voltage of EMG bursts (i.e. chews) across chewing sequence, chewing work and chewing rate. No gender bias was found for the EMG parameters considered, therefore, as regards gender, each group was considered to be homogeneous. Variability within-subjects across samples was greater for experts than untrained subjects. Significant differences in chewing time, chewing work and chewing rate were found between the expert and untrained groups. Data analysis of the three sessions showed an influence of cognitive constructs, mediating states, on the chewing process. The experts were found to be goal driven as to their mastication process. Experts showed no significant differences between sessions, untrained subjects were found to vary their EMG output in successive sessions for number of chews, chewing time, mean voltage, and chewing work.     

The total quasi-steady-state approximation for complex enzyme reactions

Biochemistry in general and enzyme kinetics in particular have been heavily influenced by the model of biochemical reactions known as Michaelis–Menten kinetics. Assuming that the complex concentration is approximately constant after a short transient phase leads to the usual Michaelis–Menten (MM) approximation (or standard quasi-steady-state approximation (sQSSA)), which is valid when the enzyme concentration is sufficiently small. This condition is usually fulfilled for in vitro experiments, but often breaks down in vivo. The total QSSA (tQSSA), which is valid for a broader range of parameters covering both high and low enzyme concentrations, has been introduced in the last two decades. We extend the tQSSA to more complex reaction schemes, like fully competitive reactions, double phosphorylation, Goldbeter–Koshland switch and we show that for a very large range of parameters our tQSSA provides excellent fitting to the solutions of the full system, better than the sQSSA and the single reaction tQSSA. Finally, we discuss the need for a correct model formulation when doing “reverse engineering”, which aims at finding unknown parameters by fitting the model to experimentally obtained data. We show that the estimated parameters are much closer to the real values when using the tQSSA rather than the sQSSA, which overestimates the parameter values greatly.     

Molecular-Level Characterization of Heterogeneous Catalytic Systems by Algorithmic Time Dependent Monte Carlo

Monte Carlo algorithms and codes, used to study heterogeneous catalytic systems in the frame of the computational section of the NANOCAT project, are presented along with some exemplifying applications and results. In particular, time dependent Monte Carlo methods supported by high level quantum chemical information employed in the field of heterogeneous catalysis are focused. Technical details of the present algorithmic Monte Carlo development as well as possible evolution aimed at a deeper interrelationship of quantum and stochastic methods are discussed, pointing to two different aspects: the thermal-effect involvement and the three-dimensional catalytic matrix simulation. As topical applications, (i) the isothermal and isobaric adsorption of CO on Group 10 metal surfaces, (ii) the hydrogenation on metal supported catalysts of organic substrates in two-phase and three-phase reactors, and (iii) the isomerization of but-2-ene species in three-dimensional supported and unsupported zeolite models are presented.     

The use of activated charcoal in combination with other fining agents and its influence on the organoleptic properties of sherry wine

Fining experiments have been conducted on fino sherry wine from the Jerez-Xérès-Sherry region (southern Spain), in which the combined use of activated charcoal with proteinaceous fining agents (casein, potassium caseinate, albumin, and gelatin) has been studied. The effect of these fining agents on the polyphenolic content, the aromatic profile, and the resistance to browning of the treated wine has been determined. The polyphenolic content suffers significant decreases following the use of activated charcoal; these decreases are only increased slightly by the subsequent use of the other fining agents. The aromatic profile was not found to be altered by the clarification agents used. Despite the reduction in the polyphenolic content, the treated wines show a tendency to suffer browning similar to that observed in non-clarified wine.     

Experimental evaluation of alkaline treatment as a method for enhancing the enzymatic digestibility of autohydrolysed Acacia dealbata

BACKGROUND: Acacia dealbata wood samples were subjected to hydrothermal processing in aqueous media, yielding a liquid phase (containing xylooligosaccharides) and a solid phase, enriched in cellulose, which was treated with alkaline solutions to obtain solids with improved susceptibility towards enzymatic hydrolysis. The effects of the most influential variables involved in the alkaline processing (sodium hydroxide concentration, temperature and reaction time) on solid yield, solid composition and kinetic parameters involved in the modelling of the enzymatic hydrolysis were assessed using the response surface methodology (RSM). RESULTS: Analysis of the RSM equations allowed selection of operational conditions (temperature = 130 °C, sodium hydroxide concentration = 4.5%, time of alkaline processing = 3 h), leading to selective removal of non‐cellulosic components and to a solid substrate highly susceptible to enzymatic hydrolysis. Operating at an enzyme loading of 20 FPU (filter paper units) g^?1 autohydrolysed, extracted solids (denoted AES) with a liquor to solid ratio of 30 g liquor g^?1 AES, solutions containing 29.7 g glucose L^?1 (corresponding to a yield of 47.3 g glucose per 100 g solids from autohydrolysis) were obtained after 48 h. CONCLUSION: Samples of Acacia dealbata wood were processed by autohydrolysis, sodium hydroxide treatment and enzymatic hydrolysis, yielding xylooligomers and processed solids highly susceptible to the enzymatic hydrolysis. Copyright © 2009 Society of Chemical Industry     

Mechanical Gradient Cues for Guided Cell Motility and Control of Cell Behavior on Uniform Substrates

A novel method for the fabrication and the use of simple uniform poly(dimethylsiloxane) PDMS substrates for controlling cell motility by a mechanical gradient is reported. The substrate is fabricated in PDMS using soft lithography and consists of a soft membrane suspended on top of a patterned PDMS substrate. The difference in the gradient stiffness is related to the underlying pattern. It is shown experimentally that these uniform substrates can modulate the response of cell motility, thus enabling patterning on the surfaces with precise cell motility. Because of the uniformity of the substrate, cells can spread equally and a directional movement to stiffer regions is clearly observed. Varying the geometry underlying the membrane, cell patterning and movement can be quantitatively characterized. This procedure is capable of controlling cell motility with high fidelity over large substrate areas. The most significant advance embodied in this method is that it offers the use of mechanical features to control cell adhesion and not topographical or chemical variations, which has not been reported so far. This modulation of the response of cell motility will be useful for the design and fabrication of advanced planar and 3D biological assemblies suitable for applications in the field of biotechnology and for tissue‐engineering purposes.