Bernard Marcos

Bone repair: new developments in growth factor delivery systems and their mathematical modeling.

More and more of our aging populations will suffer from large bone defects in the next few years. But the growth factor (GF) delivery systems (DSs) currently under investigation will help overcome the limitations of the bone grafts presently used. Some GFDSs accredited by the Food and Drug Administration (FDA) are commercially available, but they have mechanical, structural and GF retention weaknesses. New studies focus on polymers and the composition of GFs in order to mimic as closely as possible the physiological environment of healing bone. This review first summarizes the process of endochondral bone healing and the major cytokines involved. We then review the latest GFDSs, with their combinations of organic, inorganic, natural and synthetic biomaterials, the kinetics of GF release and their biological effects. We will explore new research avenues such as the use of peptides derived from bone morphogenetic proteins, including our own results, and the sequential release of bone-inducing GFs. We then review the latest mathematical models of drug delivery systems (DDSs) for several transport phenomena that may be encountered when using GFDS. The final section discusses new improvements for GFDS modeling.

Bioexpert—an expert system for wastewater treatment process diagnosis

Abstract This paper presents a prototype of an expert system, named BIOEXPERT, to control a wastewater treatment plant with applications to failure detection and diagnosis. The knowledge to be included in BIOEXPERT and the structure of the expert system are described. The BIOEXPERT knowledge base can be divided into knowledge about plant and knowledge necessary for problem solving related to diagnosis. The plant knowledge encompasses physical components of the plant (pumps, valves, pH electrode, tank, reactor), their functional purpose and the behavior of the plant. To solve problems, the expert system uses two methods for diagnosis reasoning. A shallow approach needs physical knowledge of the plant to establish relationship between symptoms and trouble. A deep knowledge-based approach uses a diagnosis model with functional and behavioral knowledge. For this first application of an expert system to an anaerobic wastewater treatment, special care has been given to the reasoning transparency and graceful degradation. The first on-line experiences have proved the utility of the expert system to explain the behavior of the process and to help operators during diagnosis.

Nanoparticle-mediated growth factor delivery systems: A new way to treat Alzheimer's disease

The number of people diagnosed with Alzheimers disease (AD) is increasing steadily as the world population ages, thus creating a huge socio-economic burden. Current treatments have only transient effects and concentrate on a single aspect of AD. There is much evidence suggesting that growth factors (GFs) have a great therapeutic potential and can play on all AD hallmarks. Because GFs are prone to denaturation and clearance, a delivery system is required to ensure protection and a sustainable delivery. This review provides information about the latest advances in the development of GF delivery systems (GFDS) targeting the brain in terms of in vitro and in vivo effects in the context of AD and discusses new strategies designed to increase the availability and the specificity of GFs to the brain. This paper also discusses, on a mechanistic level, the different delivery hurdles encountered by the carrier or the GF itself from its injection site up to the brain tissue. The major mass transport phenomena influencing the delivery systems targeting the brain are addressed and insights are given about how mechanistic mathematical frameworks can be developed to use and optimize them.

Predicting gaseous emissions from small-scale combustion of agricultural biomass fuels.

A prediction model of gaseous emissions (CO, CO2, NOx, SO2 and HCl) from small-scale combustion of agricultural biomass fuels was developed in order to rapidly assess their potential to be burned in accordance to current environmental threshold values. The model was established based on calculation of thermodynamic equilibrium of reactive multicomponent systems using Gibbs free energy minimization. Since this method has been widely used to estimate the composition of the syngas from wood gasification, the model was first validated by comparing its prediction results with those of similar models from the literature. The model was then used to evaluate the main gas emissions from the combustion of four dedicated energy crops (short-rotation willow, reed canary grass, switchgrass and miscanthus) previously burned in a 29-kW boiler. The prediction values revealed good agreement with the experimental results. The model was particularly effective in estimating the influence of harvest season on SO2 emissions.

Flaxseed‐Enriched Cereal‐Based Products: A Review of the Impact of Processing Conditions

The properties of cereals products, bread, pasta, muffins, cookies, cakes, and bars, enriched with flaxseed, were reviewed to highlight suitable processing conditions for the production of high-quality flaxseed-enriched products with the desired health attributes. The review highlights the contrasting effect of flaxseed enrichment on the mechanical and physical properties of cereal products according to product type, flaxseed enrichment level, and processing history. Flaxseed lipids remain stable for most processing and storage conditions, presumably due to the significant antioxidant properties of lignans, but information is lacking on the impact of home-handling, such as bread toasting, on lipid oxidation. Cereal products enriched with flaxseed generally exhibit similar or improved shelf life compared to equivalent products with no flaxseed enrichment, suggesting that flaxseed may limit starch retrogradation, maintain moisture content, and delay microbial growth. Sensory analysis shows lower organoleptic properties of most cereal products containing flaxseed, but similar consumer acceptance for cereal products without and with flaxseed enrichment up to 15% is reported in the literature. This review indicates the need to better understand the impact of flaxseed enrichment on product microstructure and to conduct an extensive assessment of the health effects of flaxseed-enriched products, since very few studies have focused on the quantification of the bioaccessibility, bioavailability, and activity of flaxseed bioactive compounds for a variety of processing conditions and product formulation.

Modified quasi-Newton methods for training neural networks

Abstract The backpropagation algorithm is the most popular procedure to train self-learning feed-forward neural networks. However, the convergence of this algorithm is slow, it being mainly a steepest descent method. Several researchers have proposed other approaches to improve the convergence: conjugate gradient methods, dynamic modification of learning parameters, quasi-Newton or Newton methods, stochastic methods, etc. Quasi-Newton methods were criticized because they require significant computation time and memory space to perform the update of the Hessian matrix limiting their use to middle-sized problems. This paper proposes three variations of the classical approach of the quasi-Newton method that take into account the structure of the network. By neglecting some second-order interactions, the sizes of the resulting approximated Hessian matrices are not proportional to the square of the total number of weights in the network but depend on the number of neurons of each level. The modified quasi-Newton methods are tested on two examples and are compared to classical approaches like regular quasi-Newton methods, backpropagation and conjugate gradient methods. The numerical results show that one of these approaches, named BFGS-N, represents a clear gain in terms of computational time, on large-scale problems, over the traditional methods without the requirement of large memory space.

Effect of initial pBMP-9 loading and collagen concentration on the kinetics of peptide release and a mathematical model of the delivery system.

Type I collagen is one of the most widely used materials for drug delivery in tissue repair. It is the reference carrier for delivering growth factors like bone morphogenetic proteins (BMPs such as BMP-2 and BMP-7) for bone repair. Since BMPs are expensive to produce, we have developed a peptide derived from BMP-9 (pBMP-9) that is 300 times less expensive than the entire protein while still promoting osteogenic differentiation. We have now evaluated the effects of the collagen concentration and the initial pBMP-9 load on peptide release. We then developed a model of pBMP-9 release kinetics by finite differences using a system based on Ficks second law in which the interactions between the peptide and collagen fibers are assumed to follow Langmuir adsorption kinetics. The Langmuir isotherms suggest that the structure of the collagen gel influences the strength of its electrostatic interaction with the peptide, since increasing the collagen concentration decreased the affinity of pBMP-9 for the collagen. The resulting model of the mechanism accurately reflects the experimental data and the parameters estimated indicate that the diffusivities with the different collagen concentrations are similar, whereas the mass transfer coefficient increases with the collagen concentration. The results also indicate that perfect sink conditions cannot be assumed and suggest the presence of an optimal collagen concentration. Finally, we have correlated our conclusions with the differences in collagen fiber organization observed by transmission electron microscopy.

Growth factor treatment to overcome Alzheimer's dysfunctional signaling.

The number of people suffering from Alzheimers disease (AD) will increase as the world population ages, creating a huge socio-economic burden. The three pathophysiological hallmarks of AD are the cholinergic system dysfunction, the β-amyloid peptide deposition and the Tau protein hyperphosphorylation. Current treatments have only transient effects and each tends to concentrate on a single pathophysiological aspect of AD. This review first provides an overall view of AD in terms of its pathophysiological symptoms and signaling dysfunction. We then examine the therapeutic potential of growth factors (GFs) by showing how they can overcome the dysfunctional cell signaling that occurs in AD. Finally, we discuss new alternatives to GFs that help overcome the problem of brain uptake, such as small peptides, with evidence from some of our unpublished data on human neuronal cell line.

Drying of Durum Wheat Pasta and Enriched Pasta: A Review of Modeling Approaches.

Models on drying of durum wheat pasta and enriched pasta were reviewed to identify avenues for improvement according to consumer needs, product formulation and processing conditions. This review first summarized the fundamental phenomena of pasta drying, mass transfer, heat transfer, momentum, chemical changes, shrinkage and crack formation. The basic equations of the current models were then presented, along with methods for the estimation of pasta transport and thermodynamic properties. The experimental validation of these models was also presented and highlighted the need for further model validation for drying at high temperatures (>−100°C) and for more accurate estimation of the pasta diffusion and mass transfer coefficients. This review indicates the need for the development of mechanistic models to improve our understanding of the mass and heat transfer mechanisms involved in pasta drying, and to consider the local changes in pasta transport properties and relaxation time for more accurate description of the moisture transport near glass transition conditions. The ability of current models to describe dried pasta quality according to the consumers expectations or to predict the impact of incorporating ingredients high in nutritional value on the drying of these enriched pasta was also discussed.

Optimal control and CFD modeling for heat flux estimation of a baking process

Abstract An optimal control method was combined with commercial CFD software for the optimization of heat flux during a baking process. The objective function was defined in terms of the transient heat flux, the temperature and the humidity of the baking product. The optimal control was achieved by the conjugate gradient method. The minimum energy consumption for a desired final baking product temperature and humidity was estimated. This study confirmed the relationship between the heat flux and baking product quality attributes and showed that optimal control models represent reliable tools to support decision making for complex processes such as baking. The proposed optimal control approach is general and could be easily extended to other processes.