Convective drying of onion: modeling of drying kinetics parameters.

Drying is a simultaneous heat and mass transfer processes. Drying kinetics is determined by both internal properties and external drying conditions. In this study, two important drying kinetics parameters of onions i.e. effective water diffusivity and relative activation energy of reaction engineering approach (REA) are determined. The generated parameters are used to model thin layer drying of onion at different temperatures (40, 50, 60, and 70 °C) and relative humidity of 20%. The effective water diffusivity is in the range of 2.8 × 10-10 m2 s-1 and 8.1 × 10-10 m2 s-1. Unlike the diffusivity, the relative activation energy of the REA is independent on drying conditions and thus the latter approach requires less effort in generating the transport properties. The transport parameters can be applied for assisting in designing dryer units and evaluating the performance of existing dryer units.

An efficient thermostable organophosphate hydrolase and its application in pesticide decontamination.

In vitro evolution of enzymes represents a powerful device to evolve new or to improve weak enzymatic functions. In the present work a semi-rational engineering approach has been used to design an efficient and thermostable organophosphate hydrolase, starting from a lactonase scaffold (SsoPox from Sulfolobus solfataricus). In particular, by in vitro evolution of the SsoPox ancillary promiscuous activity, the triple mutant C258L/I261F/W263A has been obtained which, retaining its inherent stability, showed an enhancement of its hydrolytic activity on paraoxon up to 300-fold, achieving absolute values of catalytic efficiency up to 10(5) M(-1) s(-1). The kinetics and structural determinants of this enhanced activity were thoroughly investigated and, in order to evaluate its potential biotechnological applications, the mutant was tested in formulations of different solvents (methanol or ethanol) or detergents (SDS or a commercial soap) for the cleaning of pesticide-contaminated surfaces.

Intestine-Liver Axis On-Chip Reveals the Intestinal Protective Role on Hepatic Damage by Emulating Ethanol First-Pass Metabolism.

Intestine-Liver-on-chip systems can be useful to predict oral drug administration and first-pass metabolism in vitro in order to partly replace the animal model. While organ-on-chip technology can count on sophisticated micro-physiological devices, the engineered organs still remain artificial surrogates of the native counterparts. Here, we used a bottom-up tissue engineering strategy to build-up physiologically functional 3D Human Intestine Model (3D-HIM) as well as 3D Liver-microtissues (HepG2-µTPs) in vitro and designed a microfluidic Intestine-Liver-On-Chip (InLiver-OC) to emulate first-pass mechanism occurring in vivo. Our results highlight the ethanol-induced 3D-HIM hyper-permeability and stromal injury, the intestinal prevention on the liver injury, as well as the synergic contribution of the two 3D tissue models on the release of metabolic enzymes after high amount of ethanol administration.

Systems Modeling Approach for Reducing the Risk of Healthcare-Associated Infections.

Healthcare-associated infections (HAIs) are a major cause of concern because of the high levels of associated morbidity, mortality, and cost. In addition, children and intensive care unit (ICU) patients are more vulnerable to these infections due to low levels of immunity. Various medical interventions and statistical process control techniques have been suggested to counter the spread of these infections and aid early detection of an infection outbreak. Methods such as hand hygiene help in the prevention of HAIs and are well-documented in the literature. This chapter demonstrates the utilization of a systems methodology to model and validate factors that contribute to the risk of HAIs in a pediatric ICU. It proposes an approach that has three unique aspects: it studies the problem of HAIs as a whole by focusing on several HAIs instead of a single type, it projects the effects of interventions onto the general patient population using the system-level model, and it studies both medical and behavioral interventions and compares their effectiveness. This methodology uses a systems modeling framework that includes simulation, risk analysis, and statistical techniques for studying interventions to reduce the transmission likelihood of HAIs.

The effect of intermittent drying on the cracking ratio of soybeans (Glycine max) at different relative humidity using reaction engineering approach modeling.

Intermittent drying (ID) was applied to reduce soybean cracking because of the low moisture gradient and little thermal stress on soybeans during their tempering period. The drying temperature and relative humidity (RH) for the drying and tempering periods were 35°C and 20% and 25°C and 43%, respectively. The intermittency (α) of the drying was defined as the ratio of the drying period to the duration of the drying and tempering periods, and it varied at α = 1, 0.5, 0.4, and 0.25 to evaluate the drying characteristics and the soybeans' quality. Intermittency processes redistributed the moisture in the soybean so that the low thermal stress was applied to the soybeans. The percentage of cracked grains increased with increasing the duration of drying period and decreasing tempering period. The moisture content and temperature changes during drying of soybeans were well fitted by reaction engineering approach (REA) modeling. Additionally, the physics that describe the soybeans' drying behavior during ID were explained by the model parameters obtained from the REA modeling, such as the surface relative humidity and the surface water vapor concentration. ID showed the highest drying efficiency at α = 0.25 regarding the total drying time (13,800 s, i.e., the shortest drying time) and the lowest cracking ratio (<2.18%).

A new model to predict diffusive self-heating during composting incorporating the reaction engineering approach (REA) framework.

During composting, self-heating may occur due to the exothermicities of the chemical and biological reactions. An accurate model for predicting maximum temperature is useful in predicting whether the phenomena would occur and to what extent it would have undergone. Elevated temperatures would lead to undesirable situations such as the release of large amount of toxic gases or sometimes would even lead to spontaneous combustion. In this paper, we report a new model for predicting the profiles of temperature, concentration of oxygen, moisture content and concentration of water vapor during composting. The model, which consists of a set of equations of conservation of heat and mass transfer as well as biological heating term, employs the reaction engineering approach (REA) framework to describe the local evaporation/condensation rate quantitatively. A good agreement between the predicted and experimental data of temperature during composting of sewage sludge is observed. The modeling indicates that the maximum temperature is achieved after some 46weeks of composting. Following this period, the temperature decreases in line with a significant decrease in moisture content and a tremendous increase in concentration of water vapor, indicating the massive cooling effect due to water evaporation. The spatial profiles indicate that the maximum temperature is approximately located at the middle-bottom of the compost piles. Towards the upper surface of the piles, the moisture content and concentration of water vapor decreases due to the moisture transfer to the surrounding. The newly proposed model can be used as reliable simulation tool to explore several geometry configurations and operating conditions for avoiding elevated temperature build-up and self-heating during industrial composting.

Sustained Local Release of NGF from a Chitosan-Sericin Composite Scaffold for Treating Chronic Nerve Compression.

Chronic nerve compression (CNC), a common form of peripheral nerve injury, always leads to chronic peripheral nerve pain and dysfunction. Current available treatments for CNC are ineffective as they usually aim to alleviate symptoms at the acute phase with limited capability toward restoring injured nerve function. New approaches for effective recovery of CNC injury are highly desired. Here we report for the first time a tissue-engineered approach for the repair of CNC. A genipin cross-linked chitosan-sericin 3D scaffold for delivering nerve growth factor (NGF) was designed and fabricated. This scaffold combines the advantages of both chitosan and sericin, such as high porosity, adjustable mechanical properties and swelling ratios, the ability of supporting Schwann cells growth, and improving nerve regeneration. The degradation products of the composite scaffold upregulate the mRNA levels of the genes important for facilitating nerve function recovery, including glial-derived neurotrophic factor (GDNF), early growth response 2 (EGR2), and neural cell adhesion molecule (NCAM) in Schwann cells, while down-regulating two inflammatory genes' mRNA levels in macrophages, tumor necrosis factor alpha (TNF-α), and interleukin-1 beta (IL-1ß). Importantly, our tissue-engineered strategy achieves significant nerve functional recovery in a preclinical CNC animal model by decreasing neuralgia, improving nerve conduction velocity (NCV), accelerating microstructure restoration, and attenuating gastrocnemius muscles dystrophy. Together, this work suggests a promising clinical alternative for treating chronic peripheral nerve compression injury.

A Tri-Leaflet Nitinol Mesh Scaffold for Engineering Heart Valves.

The epidemiology of valvular heart disease has significantly changed in the past few decades with aging as one of the main contributing factors. The available options for replacement of diseased valves are currently limited to mechanical and bioprosthetic valves, while the tissue engineered ones that are under study are currently far from clinical approval. The main problem with the tissue engineered heart valves is their progressive deterioration that leads to regurgitation and/or leaflet thickening a few months after implantation. The use of bioresorbable scaffolds is speculated to be one factor affecting these valves' failure. We have previously developed a non-degradable superelastic nitinol mesh scaffold concept that can be used for heart valve tissue engineering applications. It is hypothesized that the use of a non-degradable superelastic nitinol mesh may increase the durability of tissue engineered heart valves, avoid their shrinkage, and accordingly prevent regurgitation. The current work aims to study the effects of the design features on mechanical characteristics of this valve scaffold to attain proper function prior to in vivo implantation.

Ergonomic Engineering Intervention Of Batik Stamping Work To Reduce Lifting Load

@#One of the common health problems for small and medium enterprise such as batik production is work-related musculoskeletal disorder (WMSD). This health problem may contribute to long-term medical effect on the production workers. For batik stamping workers, the load of the copper block that need to be used repetitively can reach up to 2kg. This study aims to reduce WMSD effect by reducing the lifting load of the cooper block handled by the batik stamping worker. The worker’s working load is observed before the intervention process by using one of the ergonomic risk assessment tools, Rapid Upper Limb Asssessment (RULA). The ergonomic intervention designed in this study is from the engineering approach by modifying tools. It is found out that the intervention done were able to eliminate the lifting load handled by the worker to avoid discomfort or further health complication. This outcome are hoped to be able to improve workers’ health and increase batik stamping work productivity that eventually increased company’s revenue.

Analysis of candidate genes has proposed the role of y chromosome in human prostate cancer.

BACKGROUND: Prostate cancer, a serious genetic disease, has known as the first widespread cancer in men, but the molecular changes required for the cancer progression has not fully understood. Availability of high-throughput gene expression data has led to the development of various computational methods, for identification of the critical genes, have involved in the cancer. METHODS: In this paper, we have shown the construction of co-expression networks, which have been using Y-chromosome genes, provided an alternative strategy for detecting of new candidate, might involve in prostate cancer. In our approach, we have constructed independent co-expression networks from normal and cancerous stages have been using a reverse engineering approach. Then we have highlighted crucial Y chromosome genes involved in the prostate cancer, by analyzing networks, based on party and date hubs. RESULTS: Our results have led to the detection of 19 critical genes, related to prostate cancer, which 12 of them have previously shown to be involved in this cancer. Also, essential Y chromosome genes have searched based on reconstruction of sub-networks which have led to the identification of 4 experimentally established as well as 4 new Y chromosome genes might be linked putatively to prostate cancer. CONCLUSION: Correct inference of master genes, which mediate molecular, has changed during cancer progression would be one of the major challenges in cancer genomics. In this paper, we have shown the role of Y chromosome genes in finding of the prostate cancer susceptibility genes. Application of our approach to the prostate cancer has led to the establishment of the previous knowledge about this cancer as well as prediction of other new genes.

Network-based approach reveals Y chromosome influences prostate cancer susceptibility.

The human Y chromosome contains a small number of genes that play a critical role in the determination of male-specific organs. Today's advances have provided valuable resources for defining the functions of this chromosome in both normal and cancerous prostates. Despite the fact that generation of high-throughput expression data is becoming usual; the systematic methods of data analysis in a biological context are still an impediment. Here we have shown that constructing co-expression networks using Y-chromosome genes provides an alternative strategy for the detection of new candidate genes involved in prostate cancer. In our approach, independent co-expression networks from normal and cancerous stages are reconstructed using a reverse engineering approach. We then highlight crucial pathways, biological processes, and genes involved in the prostate cancer by analyzing each network individually and in concert. Thus, we have identified 18 critical pathways and processes related to prostate cancer, many of which have previously been shown to be involved in cancer. In particular, we identify 22 Y-chromosome genes putatively linked to prostate cancer, 13 of which have been already verified experimentally. Our novel network-based approach is useful for accurate inference of processes and essential regulators that mediate molecular changes during cancer progression.