Fabrication and spectroscopic studies of folic acid-conjugated Fe3O4@Au core-shell for targeted drug delivery application.

Gold coated magnetite core shell is a kind of nanoparticle that include magnetic iron oxide core with a thin layer nanogold. Fe3O4-gold core-shell nanostructure can be used in biomedical applications such as magnetic bioseparation, bioimaging, targeting drug delivery and cancer treatment. In this study, the synthesis and characterization of gold coated magnetite nanoparticles were discussed. Magnetite nanoparticles with an average size of 6 nm in diameter were synthesized by the chemical co-precipitation method and gold-coated Fe3O4 core-shell nanostructures were produced with an average size of 11.5 nm in diameter by reduction of Au(3+) with citrate ion in the presence of Fe3O4. Folate-conjugated gold coated magnetite nanoparticles were synthesized to targeting folate receptor that is overexpressed on the surface of cancerous cells. For this purpose, we used l-cysteine, as a bi-functional linker for attachment to gold surface and it was linked to the gold nanoparticles surface through its thiol group. Then, we conjugated amino-terminated nanoparticles to folic acid with an amide-linkage formation. These gold magnetic nanoparticles were characterized by various techniques such as X-ray powder diffraction (XRD) analysis, Fourier transform infrared spectrometer (FT-IR), UV-visible spectroscopy, transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), dispersive analysis of X-ray (EDAX) and vibrating sample magnetometer (VSM) analysis. The magnetic and optical properties of Fe3O4 nanostructure were changed by gold coating and attachment of l-cysteine and folic acid to Fe3O4@Au nanoparticles.

Numerical study on the splitting of a vapor bubble in the ultrasonic assisted EDM process with the curved tool and workpiece.

Electrical discharge machining (EDM) is a powerful and modern method of machining. In the EDM process, a vapor bubble is generated between the tool and the workpiece in the dielectric liquid due to an electrical discharge. In this process dynamic behavior of the vapor bubble affects machining process. Vibration of the tool surface affects bubble behavior and consequently affects material removal rate (MRR). In this paper, dynamic behavior of the vapor bubble in an ultrasonic assisted EDM process after the appearance of the necking phenomenon is investigated. It is noteworthy that necking phenomenon occurs when the bubble takes the shape of an hour-glass. After the appearance of the necking phenomenon, the vapor bubble splits into two parts and two liquid jets are developed on the boundaries of the upper and lower parts of the vapor bubble. The liquid jet developed on the upper part of the bubble impinges to the tool and the liquid jet developed on the lower part of the bubble impinges to the workpiece. These liquid jets cause evacuation of debris from the gap between the tool and the workpiece and also cause erosion of the workpiece and the tool. Curved tool and workpiece affect the shape and the velocity of the liquid jets during splitting of the vapor bubble. In this paper dynamics of the vapor bubble after its splitting near the curved tool and workpiece is investigated in three cases. In the first case surfaces of the tool and the workpiece are flat, in the second case surfaces of the tool and the workpiece are convex and in the third case surfaces of the tool and workpiece are concave. Numerical results show that in the third case, the velocity of liquid jets which are developed on the boundaries of the upper and lower parts of the vapor bubble after its splitting have the highest magnitude and their shape are broader than the other cases.

In situ biomimetic synthesis and characterization of nano hydroxyapatite in gelatin matrix.

In this work, nano hydroxyapatite (nHAp) composites were synthesized via an in situ biomimetic process at room temperature by using gelatin as a template agent. Formation of hydroxyapatite nanoparticles and the effect of biopolymer concentration on the shape and morphology of the nHAp nanoparticles were confirmed and investigated by using X-ray diffraction (XRD), Fourier Transform Infrared spectroscopy (FT-IR), Scanning and Transmission Electron Microscopy (SEM and TEM). The results indicated that, the gelatin biopolymer as a template agent in the preparation batch has influences the size and morphology of the HAp nanocrystals precipitated in an aqueous solution of gelatin.

Biocompatibility evaluation of nano hydroxyapatite-starch biocomposites.

In this work, we report the synthesis and characterization of nano hydroxyapatite (nHAp) in the presence of starch matrix via a biomimetic process for in vitro biocompatibility evaluation. Characterization of the samples was carried out using X-ray diffraction (XRD) and Fourier Transform infrared spectroscopy (FT-IR). The Size and morphology of the nHAp samples were determined using scanning and transmission electron microscopy (SEM and TEM). The results show that, the shape and morphology of nHAp is influenced by the presence of starch as a template agent. It leads to formation of rod-like nHAp. Cell culture and MTT assays were performed for in vitro biocompatibility. They show that n-HAp can affect the proliferation of cells and the n-HAp/starch biocomposites have no negative effect on the cell morphology, viability and proliferation.

Fabrication and characterization of gold-TiO2 core-shell nanowire for immobilization of alkaline protease.

In this work, we report enhancement of the stability and biocatalytic activities of the alkaline protease enzyme immobilized on a gold/TiO2 core-shell nanowires. Gold/TiO2 core-shell nanowires were firstly prepared by the sol-gel method using a mixture of aqueous solution of titanate and chloroauric acid (HAuCI4) under ambient temperature and atmospheric condition and calcined then. As prepared nanowire was found to have a good surface biocompatibility for immobilization of the alkaline protease enzyme. The results obtained in this work showed that alkaline protease immobilized on gold-TiO2 core shell is stable and bioactive at the alkaline pH and ambient temperature. The stability and the biocatalytic activity of the immobilized gold-TiO2 core shell nano composites were monitored by UV-visible spectroscopy. Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM) and dispersive analysis of X-ray (EDAX) were used to characterize the size and morphology of the prepared materials.

Preparation of core-shell ZnO-SiO2 nanowires-nanotubes for immobilization of the alkaline protease enzyme.

The main goal of enzyme immobilization is industrial re-use of enzymes for many reaction cycles. In this purpose, simplicity and improvement of the enzyme properties have to be strongly associated with the design of protocols of enzyme immobilization. In the last decade, nanosized materials have been widely used as a support for enzyme immobilization, for instance, silica nanotubes, phospholipid bilayers, self-assembled monolayers Langmuir_Blodgett films, polymer matrices, galleries of alpha-zirconium, phosphate, mesoporous silicates such as MCM-41, silica nanoparticles. In this work, we report synthesis of core shell ZnO/SiO2 nanowires and used them as a support for immobilization of the alkaline protease. Characterization of this assembled systems was carried out by, Energy-dispersive X-ray spectroscopy (EDAX), Transmission electron microscopy (TEM) and Scanning electron microscopy (SEM). Biocatalytic activity of the alkaline protease in this bioconjugate system was examined and the results showed an increase of biocatalytic activity, in comparison with the free enzyme in solution.

Preparation and characterization of the hydrophilic nanocomposite coating based on epoxy resin and titanate on the glass substrate.

The hydrophilic organic-inorganic nanocomposite hybrid coatings were prepared using Tetrabutyl titanate. A simple sol-gel method has been developed for the preparation of nanocomposite coatings, at a molecular level and providing suitable conditions to obtain a complete conversion. The films were prepared on the glass substrates by dip-coating from a sol containing alcoholic tetrabutyl titanate which after the curing treatment, the gel forms a stable thin homogeneous nanocomposite coating. The obtained films were transparent to visible light and their surface hydrophilicity values were increased by increasing titania content in the water damp permeable self leveling flooring system. Characterization of the nanocomposite coating were performed by Transmission electron microscopy (TEM), Atomic force microscopy (AFM) analysis and contact angle test for water on TiO2 films that gave evidence of a strong interaction between the organic and inorganic phase with the formation of titania domains in the nanoscale range.

Biocatalytic activity of fungal protease on silver nanoparticle-loaded zeolite X microspheres.

Silver nanoparticles are excellent biocompatible surfaces for the immobilization of enzymes. However, separation of the silver nanoparticle-enzyme bioconjugate material from the reaction medium is often difficult. In this study, we investigate the assembly of the silver nanoparticles on the surface of the amine-functionalized zeolite microspheres or formation of zeolite-silver nanoparticle "core-shell" structure and thereafter, using obtained structure in immobilization of fungal protease. The assembly of silver nanoparticles on zeolite surface occurs through the amine groups present in 3-aminopropyltrimethoxysilane (3-APTS). The fungal proteases bound to the massive "core-shell" structures can be easily separated from the reaction medium by mild centrifugation and exhibited excellent reuse characteristics. The biocatalytic activity of fungal protease in the bioconjugate was marginally enhanced relative to the free enzyme in solution.

An Integrated and Multivariate Model along with Designing Experiments Approach for Assessment of Micro- and Macro- Ergonomic Factors: The Case of a Gas Refinery.

BACKGROUND: The objectives of this paper are three folds. First, an integrated framework for designing and development of the integrated health, safety and environment (HSE) model is presented. Second, it is implemented and tested for a large gas refinery in Iran. Third, it is shown whether the total ergonomics model is superior to the conventional ergonomics approach. This study is among the first to examine total ergonomics components in a manufacturing system. METHODS: This study was conducted in Sarkhoon & Qeshm Gas refinery- Iran in 2006. To achieve the above objectives, an integrated approach based on total ergonomics factors was developed. Second, it is applied to the refinery and the advantages of total ergonomics approach are discussed. Third, the impacts of total ergonomics factors on local factors are examined through non-parametric statistical analysis. RESULTS: It was shown that total ergonomics model is much more beneficial than conventional approach. It should be noted that the traditional ergonomics methodology is not capable of locating the findings of total ergonomics model. CONCLUSION: The distinguished aspect of this study is the employment of a total system approach based on integration of the conventional ergonomics factors with HSE factors.

An adaptable connectionist text-retrieval system with relevance feedback.

This paper introduces a new connectionist network for certain domain-specific text-retrieval and search applications with expert end users. A new model reference adaptive system is proposed that involves three learning phases. Initial model-reference learning is first performed based upon an ensemble set of input-output of an initial reference model. Model-reference following is needed in dynamic environments where documents are added, deleted, or updated. Relevance feedback learning from multiple expert users then optimally maps the original query using either a score-based or a click-through selection process. The learning can be implemented, in regression or classification modes, using a three-layer network. The first layer is an adaptable layer that performs mapping from query domain to document space. The second and third layers perform document-to-term mapping, search/retrieval, and scoring tasks. The learning algorithms are thoroughly tested on a domain-specific text database that encompasses a wide range of Hewlett Packard (HP) products and for a large number of most commonly used single- and multiterm queries.

Mapping quantitative trait loci associated with resistance to coccidiosis and growth.

To map QTL associated with disease resistance to avian coccidiosis and growth, two commercial broiler lines with different degrees of resistance to the disease were crossed to generate an F1 generation that was intercrossed to produce 314 F2 generation offspring. The F2 offspring were inoculated with sporulated oocysts of Eimeria maxima. Five disease-associated phenotypes were measured after the infection. Intertrait comparisons revealed that oocyst shedding was a good parameter for evaluating disease resistance or susceptibility. One hundred nineteen microsatellite markers, covering 80% of the chicken genome with an average marker interval of 25 cM, were used for genotyping of F1 parents and F2 offspring. Statistical analysis based on the data of four families revealed a locus on chromosome 1 associated with oocyst shedding (logarithm of odds = 3.46). The genetic mechanism of this locus appeared additive. The genomic scan also identified three potential growth QTL on chromosomes 1, 6, and 8. These results provide the foundation for further investigation to validate the QTL.

Phenotypic variation among three broiler pure lines for Marek's disease, coccidiosis, and antibody response to sheep red blood cells.

To identify candidate genes, chicken lines with the most divergent phenotypes are usually crossed to generate resource mapping populations, for example, either backcrossed or F2 populations. Linkage between the genetic marker and the phenotypic trait locus is then tested in the mapping population. As an initial step in the development of a mapping population from commercial broilers, the goal of the current research was to evaluate the phenotypic variation among three pure lines for antibody response to SRBC and in resistance to two economically important poultry diseases, Marek's disease (MD) and coccidiosis (Eimeria acervulina). Chicks from each line were received and separated into three experimental studies to evaluate each of their responses. In summary, broiler Line 3 had significantly lower antibody responses to SRBC immunizations compared to the other two lines, and nonvaccinated birds from Line 3 were also more susceptible to MD. With coccidiosis, the response was complex, and ranking of the lines was dependent on the age of infection, and whether it was a first or second challenge. With the first challenge, Line 1 was most susceptible at the younger age (Day 30), whereas Line 3 was susceptible at the older age (Day 58). Upon the second challenge, broiler Line 1 remained susceptible at the younger age, but Line 2 was more susceptible at the older age. Line 3 was completely resistant to the second challenge at the older age. Thus, although the broiler lines have been intensively selected for productivity and general livability, this study also demonstrates that the lines differ for immune response and disease resistance. Based on the phenotypic differences between Lines 1 and 3, they were chosen to establish a mapping population for identifying candidate genes that affect MD and coccidiosis in commercial broiler chickens.

Underwater target classification in changing environments using an adaptive feature mapping.

A new adaptive underwater target classification system to cope with environmental changes in acoustic backscattered data from targets and nontargets is introduced. The core of the system is the adaptive feature mapping that minimizes the classification error rate of the classifier. The goal is to map the feature vector in such a way that the mapped version remains invariant to the environmental changes. A K-nearest neighbor (K-NN) system is used as a memory to provide the closest matches of an unknown pattern in the feature space. The classification decision is done by a backpropagation neural network (BPNN). Two different cost functions for adaptation are defined. These two cost functions are then combined together to improve the classification performance. The test results on a 40-kHz linear FM acoustic backscattered data set collected from six different objects are presented. These results demonstrate the effectiveness of the adaptive system versus nonadaptive system when the signal-to-reverberation ratio (SRR) in the environment is varying.

Genetic variation in susceptibility to Marek's disease in a commercial broiler population.

Two commercial broiler pure lines that were previously identified to differ in their susceptibility to Marek's disease (MD) were line-crossed to generate an F1 population. Eight F1 males were randomly mated to four or five F1 females to produce an F2 test population that would be segregating for genes affecting MD. All F2 progeny (four hatches) were pedigreed at hatch and placed in colony houses as nonvaccinated. At 5 days of age, they were challenged intraabdominally with MD virus RB1B. Clinical signs, mortality, and gross and microscopic lesions were recorded during the MD challenge. At 8 wk postchallenge, all remaining birds were euthanatized and necropsied. During the MD challenge of the first two hatches, we observed that several severely stunted broilers originated from certain families and the differences in body weight among birds appeared as early as 3 wk postchallenge. To confirm this observation, body weight at 6 wk postchallenge was determined for all surviving birds in hatches 3 and 4 (n = 242). Genetic variation in body weight among broiler sire families was apparent; the average body weight for males at this time was 2.07 kg, whereas with females, it was 1.87 kg. At least 12.2% of the broilers, including both sexes, weighed less than 1 kg ("severely stunted") at this time. The incidence of these growth-stunted birds within each broiler sire family ranged from 0 to 26% and for dam families, 0 to 60%. Correlation analyses between stunting and other MD-associated traits revealed that the incidence of stunting had a significant and positive association with paralysis (r = 0.50). Therefore, the data suggest that there may be a genetic component affecting body weight loss during MD infection. The genetic component is speculated to affect susceptibility to MD paralysis with an indirect effect on the body weight of birds. The significance of this finding is best exemplified by the identification of a broiler sire family with over 26% of its progeny affected by this MD-associated trait.

Screening for highly heterozygous chickens in outbred commercial broiler lines to increase detection power for mapping quantitative trait loci.

Two commercial broiler lines were used in an experiment to map quantitative trait loci (QTL) affecting disease resistance. Chickens from these lines were genotyped with 27 microsatellite markers to estimate heterozygosity and polymorphism information content (PIC), the probability that one parent is heterozygous at a marker locus and the other has a different genotype. Heterozygosity estimated from allelic frequencies was 0.52 for the two lines; however, heterozygosity calculated from actual counts of heterozygous loci was much lower (0.36) than the estimated heterozygosity. The PIC was 0.45 in these lines, and average allele number per marker locus was about 3.5. Twenty-five males produced from a cross between these two lines were screened with the DNA markers to select birds with high heterozygosity at marker loci. Mating simulation showed that uninformative matings could be reduced by about 5% if 12 pairs of males and females with the highest heterozygosity at marker loci were selected, which was about a 25% reduction in total uninformative matings. This experiment demonstrated that the heterozygosity and PIC in commercial broiler lines were low and selection for the birds with high heterozygosity at marker loci could increase informative content in chickens used in the experiments of QTL mapping, thus increasing detection power for QTL mapping.

Comparison of two different PNN training approaches for satellite cloud data classification.

Presents a training algorithm for probabilistic neural networks (PNN) using the minimum classification error (MCE) criterion. A comparison is made between the MCE training scheme and the widely used maximum likelihood (ML) learning on a cloud classification problem using satellite imagery data.

Temporal updating scheme for probabilistic neural network with application to satellite cloud classification--further results.

A novel temporal updating approach for probabilistic neural network classifiers was developed by Tian et al. (2000) to account for temporal changes of spectral and temperature features of clouds in the visible and infrared GOES 8 (Geostationary Operational Environmental Satellite) imagery data. In this paper, a new method referred to as moving singular value decomposition (MSVD) is introduced to improve the classification rate of the boundary blocks or blocks containing cloud types with non-uniform texture. The MSVD method is then incorporated into the temporal updating scheme and its effectiveness is demonstrated on several sequences of GOES 8 cloud imagery data. These results indicate that the incorporation of the new MSVD improves the overall performance of the temporal updating process by almost 10%

Analysis of disease resistance-associated parameters in broiler chickens challenged with Eimeria maxima.

To determine an optimal dose for coccidial inoculation and to evaluate genetic resistance or susceptibility in individual chickens, broilers were inoculated with four different doses of Eimeria maxima oocysts. Body weight gain, fecal oocyst shedding, concentrations of plasma NO2- + NO3-, carotenoid, and interferon-gamma were measured at two different time periods postinfection. The results showed significant dose and sex effects on most parameters and interaction between dose and sex in some parameters. The dose effects were generally linear; however, some significant quadratic effects were also observed. The measurements from chickens inoculated with 10(4) oocysts displayed the highest correlation coefficients among oocyst shedding, body weight gain, and concentrations of carotenoid and NO2- + NO3-. An infection index, calculated from the correlated parameters, displayed high correlation coefficients with the parameters. The infection index may be a better parameter for evaluating individual genetic resistance against coccidial infection.

Underwater target classification using wavelet packets and neural networks.

In this paper, a new subband-based classification scheme is developed for classifying underwater mines and mine-like targets from the acoustic backscattered signals. The system consists of a feature extractor using wavelet packets in conjunction with linear predictive coding (LPC), a feature selection scheme, and a backpropagation neural-network classifier. The data set used for this study consists of the backscattered signals from six different objects: two mine-like targets and four nontargets for several aspect angles. Simulation results on ten different noisy realizations and for signal-to-noise ratio (SNR) of 12 dB are presented. The receiver operating characteristic (ROC) curve of the classifier generated based on these results demonstrated excellent classification performance of the system. The generalization ability of the trained network was demonstrated by computing the error and classification rate statistics on a large data set. A multiaspect fusion scheme was also adopted in order to further improve the classification performance.

Temporal updating scheme for probabilistic neural network with application to satellite cloud classification.

In cloud classification from satellite imagery, temporal change in the images is one of the main factors that causes degradation in the classifier performance. In this paper, a novel temporal updating approach is developed for probabilistic neural network (PNN) classifiers that can be used to track temporal changes in a sequence of images. This is done by utilizing the temporal contextual information and adjusting the PNN to adapt to such changes. Whenever a new set of images arrives, an initial classification is first performed using the PNN updated up to the last frame while at the same time, a prediction using Markov chain models is also made based on the classification results of the previous frame. The results of both the old PNN and the predictor are then compared. Depending on the outcome, either a supervised or an unsupervised updating scheme is used to update the PNN classifier. Maximum likelihood (ML) criterion is adopted in both the training and updating schemes. The proposed scheme is examined on both a simulated data set and the Geostationary Operational Environmental Satellite (GOES) 8 satellite cloud imagery data. These results indicate the improvements in the classification accuracy when the proposed scheme is used.