Investigation of micro-devices for neurobiological applications

The aim of this project is to integrate neuronal cell culture with commercial or in-house built micro-electrode arrays and MEMS devices. The resulting device is intended to support neuronal cell culture on its surface, expose specific portions of a neuronal population to different environments using microfluidic gradients and stimulate/record neuronal electrical activity using micro-electrode arrays. Additionally, through integration of chemical surface patterning, such device can be used to build neuronal cell networks of specific size, conformation and composition. The design of this device takes inspiration from the nervous system because its development and regeneration are heavily influenced by surface chemistry and fluidic gradients. Hence, this device is intended to be a step forward in neuroscience research because it utilizes similar concepts to those found in nature. The large part of this research revolved around solving technical issues associated with integration of biology, surface chemistry, electrophysiology and microfluidics. Commercially available microelectrode arrays (MEAs) are mechanically and chemically brittle making them unsuitable for certain surface modification and micro-fluidic integration techniques described in the literature. In order to successfully integrate all the aspects into one device, some techniques were heavily modified to ensure that their effects on MEA were minimal. In terms of experimental work, this thesis consists of 3 parts. The first part dealt with characterization and optimization of surface patterning and micro-fluidic perfusion. Through extensive image analysis, the optimal conditions required for micro-contact printing and micro-fluidic perfusion were determined. The second part used a number of optimized techniques and successfully applied these to culturing patterned neural cells on a range of substrates including: Pyrex, cyclo-olefin and SiN coated Pyrex. The second part also described culturing neurons on MEAs and recording electrophysiological activity. The third part of the thesis described integration of MEAs with patterned neuronal culture and microfluidic devices. Although integration of all methodologies proved difficult, a large amount of data relating to biocompatibility, neuronal patterning, electrophysiology and integration was collected. Original solutions were successfully applied to solve a number of issues relating to consistency of micro printing and microfluidic integration leading to successful integration of techniques and device components.

Accuracy of shoulder joint and subacromial injections in cadavers.

OBJECTIVE:

"Blind" shoulder injections are often inaccurate and infiltrate untargeted structures. We tested a hypothesis that optimizing certain anatomical and positional factors would improve accuracy and reduce dispersal.

METHODS:

We evaluated one subacromial and one glenohumeral injection technique on cadavers.

RESULTS:

Mean accuracy was 91% for subacromial-targeted and 74 and 91% (worst- and best-case scenarios) for joint-targeted injections. Mean dispersal was 19% for subacromial-targeted and 16% for joint-targeted injections. All results bettered those reported previously.

CONCLUSION:

These "optimized" techniques might improve accuracy and limit dispersal of blind shoulder injections in clinical situations, benefiting efficacy and safety. However, evaluation is required in a clinical setting.

Development of phantom for radiographic image optimization of standard patient in the lateral view of chest and skull examination

We present the construction of a homogeneous phantom to be used in simulating the scattering and absorption of X-rays by a standard patient chest and skull when irradiated laterally. This phantom consisted of Incite and aluminium plates with their thickness determined by a tomographic exploratory method applied to the anthropomorphic phantom. Using this phantom, an optimized radiographic technique was established for chest and skull of standard sized patient in lateral view. Images generated with this optimized technique demonstrated improved image quality and reduced radiation doses. (c) 2006 Elsevier Ltd. All rights reserved.

Construction of pediatric homogeneous phantoms for optimization of chest and skull radiographs

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Combined marrow stromal cell-sheet techniques and high-strength biodegradable composite scaffolds for engineered functional bone grafts

In this study, cell sheets comprising multilayered porcine bone marrow stromal cells (BMSC) were assembled with fully interconnected scaffolds made from medical-grade polycaprolactone–calcium phosphate (mPCL–CaP), for the engineering of structural and functional bone grafts. The BMSC sheets were harvested from culture flasks and wrapped around pre-seeded composite scaffolds. The layered cell sheets integrated well with the scaffold/cell construct and remained viable, with mineralized nodules visible both inside and outside the scaffold for up to 8 weeks culture. Cells within the constructs underwent classical in vitro osteogenic differentiation with the associated elevation of alkaline phosphatase activity and bone-related protein expression. In vivo, two sets of cell-sheet-scaffold/cell constructs were transplanted under the skin of nude rats. The first set of constructs (554mm3) were assembled with BMSC sheets and cultured for 8 weeks before implantation. The second set of constructs (10104mm3) was implanted immediately after assembly with BMSC sheets, with no further in vitro culture. For both groups, neo cortical and well-vascularised cancellous bone were formed within the constructs with up to 40% bone volume. Histological and immunohistochemical examination revealed that neo bone tissue formed from the pool of seeded BMSC and the bone formation followed predominantly an endochondral pathway, with woven bone matrix subsequently maturing into fully mineralized compact bone; exhibiting the histological markers of native bone. These findings demonstrate that large bone tissues similar to native bone can be regenerated utilizing BMSC sheet techniques in conjunction with composite scaffolds whose structures are optimized from a mechanical, nutrient transport and vascularization perspective.

Use of non-specific and specific interactions in the analysis of testosterone and related compounds by capillary electromigration techniques

Determination of testosterone and related compounds in body fluids is of utmost importance in doping control and the diagnosis of many diseases. Capillary electromigration techniques are a relatively new approach for steroid research. Owing to their electrical neutrality, however, separation of steroids by capillary electromigration techniques requires the use of charged electrolyte additives that interact with the steroids either specifically or non-specifically. The analysis of testosterone and related steroids by non-specific micellar electrokinetic chromatography (MEKC) was investigated in this study. The partial filling (PF) technique was employed, being suitable for detection by both ultraviolet spectrophotometry (UV) and electrospray ionization mass spectrometry (ESI-MS). Efficient, quantitative PF-MEKC UV methods for steroid standards were developed through the use of optimized pseudostationary phases comprising surfactants and cyclodextrins. PF-MEKC UV proved to be a more sensitive, efficient and repeatable method for the steroids than PF-MEKC ESI-MS. It was discovered that in PF-MEKC analyses of electrically neutral steroids, ESI-MS interfacing sets significant limitations not only on the chemistry affecting the ionization and detection processes, but also on the separation. The new PF-MEKC UV method was successfully employed in the determination of testosterone in male urine samples after microscale immunoaffinity solid-phase extraction (IA-SPE). The IA-SPE method, relying on specific interactions between testosterone and a recombinant anti-testosterone Fab fragment, is the first such method described for testosterone. Finally, new data for interactions between steroids and human and bovine serum albumins were obtained through the use of affinity capillary electrophoresis. A new algorithm for the calculation of association constants between proteins and neutral ligands is introduced.

Protein sequence design on the basis of topology optimization techniques -Using continuous modeling of discrete amino acid types

The notion of optimization is inherent in protein design. A long linear chain of twenty types of amino acid residues are known to fold to a 3-D conformation that minimizes the combined inter-residue energy interactions. There are two distinct protein design problems, viz. predicting the folded structure from a given sequence of amino acid monomers (folding problem) and determining a sequence for a given folded structure (inverse folding problem). These two problems have much similarity to engineering structural analysis and structural optimization problems respectively. In the folding problem, a protein chain with a given sequence folds to a conformation, called a native state, which has a unique global minimum energy value when compared to all other unfolded conformations. This involves a search in the conformation space. This is somewhat akin to the principle of minimum potential energy that determines the deformed static equilibrium configuration of an elastic structure of given topology, shape, and size that is subjected to certain boundary conditions. In the inverse-folding problem, one has to design a sequence with some objectives (having a specific feature of the folded structure, docking with another protein, etc.) and constraints (sequence being fixed in some portion, a particular composition of amino acid types, etc.) while obtaining a sequence that would fold to the desired conformation satisfying the criteria of folding. This requires a search in the sequence space. This is similar to structural optimization in the design-variable space wherein a certain feature of structural response is optimized subject to some constraints while satisfying the governing static or dynamic equilibrium equations. Based on this similarity, in this work we apply the topology optimization methods to protein design, discuss modeling issues and present some initial results.

Area Optimized H.264 Intra Prediction Architecture for 1080p HD Resolution

High performance video standards use prediction techniques to achieve high picture quality at low bit rates. The type of prediction decides the bit rates and the image quality. Intra Prediction achieves high video quality with significant reduction in bit rate. This paper present an area optimized architecture for Intra prediction, for H.264 decoding at HDTV resolution with a target of achieving 60 fps. The architecture was validated on Virtex-5 FPGA based platform. The architecture achieves a frame rate of 64 fps. The architecture is based on multi-level memory hierarchy to reduce latency and ensure optimum resources utilization. It removes redundancy by reusing same functional blocks across different modes. The proposed architecture uses only 13% of the total LUTs available on the Xilinx FPGA XC5VLX50T.

SiGe/Si resonant-cavity-enhanced photodetectors for 1.3 mu m operation fabricated using wafer bonding techniques

A SiGe/Si multiple-quantum-well resonant-cavity-enhanced (RCE) photodetector for 1.3 mum operation was fabricated using bonding reflector process. A full width at half maximum (FWHM) of 6 nm and a quantum efficiency of 4.2% at 1314 nm were obtained. Compared to our previously reported SiGe RCE photodetectors fabricated on separation-by-implanted-oxygen wafer, the mirrors in the device can be more easily fabricated and the device can be further optimized. The FWHM is expected to be less than 1 nm and the detector is fit for density wavelength division multiplexing applications. (C) 2002 American Institute of Physics.

Au nanorods-semiconductor nanowire hybrid nanostructures : nanofabrication techniques and optoelectronic properties

The objective of this thesis is the exploration and characterization of novel Au nanorod-semiconductor nanowire hybrid nanostructures. I provide a comprehensive bottom-up approach in which, starting from the synthesis and theoretical investigation of the optical properties of Au nanorods, I design, nanofabricate and characterize Au nanorods-semiconductor nanowire hybrid nanodevices with novel optoelectronic capabilities compared to the non-hybrid counterpart. In this regards, I first discuss the seed-mediated protocols to synthesize Au nanorods with different sizes and the influence of nanorod geometries and non-homogeneous surrounding medium on the optical properties investigated by theoretical simulation. Novel methodologies for assembling Au nanorods on (i) a Si/SiO2 substrate with highly-ordered architecture and (ii) on semiconductor nanowires with spatial precision are developed and optimized. By exploiting these approaches, I demonstrate that Raman active modes of an individual ZnO nanowire can be detected in non-resonant conditions by exploring the longitudinal plasmonic resonance mediation of chemical-synthesized Au nanorods deposited on the nanowire surface otherwise not observable on bare ZnO nanowire. Finally, nanofabrication and detailed electrical characterization of ZnO nanowire field-effect transistor (FET) and optoelectronic properties of Au nanorods - ZnO nanowire FET tunable near-infrared photodetector are investigated. In particular we demonstrated orders of magnitude enhancement in the photocurrent intensity in the explored range of wavelengths and 40 times faster time response compared to the bare ZnO FET detector. The improved performance, attributed to the plasmonicmediated hot-electron generation and injection mechanism underlying the photoresponse is investigated both experimentally and theoretically. The miniaturized, tunable and integrated capabilities offered by metal nanorodssemicondictor nanowire device architectures presented in this thesis work could have an important impact in many application fields such as opto-electronic sensors, photodetectors and photovoltaic devices and open new avenues for designing of novel nanoscale optoelectronic devices.

Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis.

As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets.

Comparison of techniques to screen and characterize bacteria-specific hybridomas for high-quality monoclonal antibodies selection

Antibodies are are very important materials for diagnostics. A rapid and simple hybridoma screening method will help in delivering specific monoclonal antibodies. In this study, we systematically developed the first antibody array to screen for bacteria-specific monoclonal antibodies using Listeria monocytogenes as a bacteria model. The antibody array was developed to expedite the hybridoma screening process by printing hybridoma supernatants on a glass slide coated with an antigen of interest. This screening method is based on the binding ability of supernatants to the coated antigen. The bound supernatants were detected by a fluorescently labeled anti-mouse immunoglobulin. Conditions (slide types, coating, spotting, and blocking buffers) for antibody array construction were optimized. To demonstrate its usefulness, antibody array was used to screen a sample set of 96 hybridoma supernatants in comparison to ELISA. Most of the positive results identified by ELISA and antibody array methods were in agreement except for those with low signals that were undetectable by antibody array. Hybridoma supernatants were further characterized with surface plasmon resonance to obtain additional data on the characteristics of each selected clone. While the antibody array was slightly less sensitive than ELISA, a much faster and lower cost procedure to screen clones against multiple antigens has been demonstrated. (C) 2011 Elsevier Inc. All rights reserved.

Optimized process for the inclusion of carbon nanotubes in elastomers with improved thermal and mechanical properties

The effects of addition of reinforcing carbon nanotubes (CNTs) into hydrogenated nitrile-butadiene rubber (HNBR) matrix on the mechanical, dynamic viscoelastic, and permeability properties were studied in this investigation. Different techniques of incorporating nanotubes in HNBR were investigated in this research. The techniques considered were more suitable for industrial preparation of rubber composites. The nanotubes were modified with different surfactants and dispersion agents to improve the compatibility and adhesion of nanotubes on the HNBR matrix. The effects of the surface modification of the nanotubes on various properties were examined in detail. The amount of CNTs was varied from 2.5 to 10 phr in different formulations prepared to identify the optimum CNT levels. A detailed analysis was made to investigate the morphological structure and mechanical behavior at room temperature. The viscoelastic behavior of the nanotube filler elastomer was studied by dynamic mechanical thermal analysis (DMTA). Morphological analysis indicated a very good dispersion of the CNTs for a low nanotube loading of 3.5 phr. A significant improvement in the mechanical properties was observed with the addition of nanotubes. DMTA studies revealed an increase in the storage modulus and a reduction in the glass-transition temperature after the incorporation of the nanotubes. Further, the HNBR/CNT nanocomposites were subjected to permeability studies. The studies showed a significant reduction in the permeability of nitrogen gas. Copyright © 2011 Wiley Periodicals, Inc.

COD and NH4-N Estimation in the Inflow of Wastewater Treatment Plants using Machine Learning Techniques

The in-line measurement of COD and NH4-N in the WWTP inflow is crucial for the timely monitoring of biological wastewater treatment processes and for the development of advanced control strategies for optimized WWTP operation. As a direct measurement of COD and NH4-N requires expensive and high maintenance in-line probes or analyzers, an approach estimating COD and NH4-N based on standard and spectroscopic in-line inflow measurement systems using Machine Learning Techniques is presented in this paper. The results show that COD estimation using Radom Forest Regression with a normalized MSE of 0.3, which is sufficiently accurate for practical applications, can be achieved using only standard in-line measurements. In the case of NH4-N, a good estimation using Partial Least Squares Regression with a normalized MSE of 0.16 is only possible based on a combination of standard and spectroscopic in-line measurements. Furthermore, the comparison of regression and classification methods shows that both methods perform equally well in most cases.

An optimized reverse-phase high performance liquid chromatographic method for evaluating percutaneous absorption of glucosamine hydrochloride

A relatively simple, selective, precise and accurate high performance liquid chromatography (HPLC) method based on a reaction of phenylisothiocyanate (PITC) with glucosamine (GL) in alkaline media was developed and validated to determine glucosamine hydrochloride permeating through human skin in vitro. It is usually problematic to develop an accurate assay for chemicals traversing skin because the excellent barrier properties of the tissue ensure that only low amounts of the material pass through the membrane and skin components may leach out of the tissue to interfere with the analysis. In addition, in the case of glucosamine hydrochloride, chemical instability adds further complexity to assay development. The assay, utilising the PITC-GL reaction was refined by optimizing the reaction temperature, reaction time and PITC concentration. The reaction produces a phenylthiocarbamyl-glucosamine (PTC-GL) adduct which was separated on a reverse-phase (RP) column packed with 5 microm ODS (C18) Hypersil particles using a diode array detector (DAD) at 245 nm. The mobile phase was methanol-water-glacial acetic acid (10:89.96:0.04 v/v/v, pH 3.5) delivered to the column at 1 ml min-1 and the column temperature was maintained at 30 degrees C. Galactosamine hydrochloride (Gal-HCl) was used as an internal standard. Using a saturated aqueous solution of glucosamine hydrochloride, in vitro permeation studies were performed at 32+/-1 degrees C over 48 h using human epidermal membranes prepared by a heat separation method and mounted in Franz-type diffusion cells with a diffusional area 2.15+/-0.1 cm2. The optimum derivatisation reaction conditions for reaction temperature, reaction time and PITC concentration were found to be 80 degrees C, 30 min and 1% v/v, respectively. PTC-Gal and GL adducts eluted at 8.9 and 9.7 min, respectively. The detector response was found to be linear in the concentration range 0-1000 microg ml-1. The assay was robust with intra- and inter-day precisions (described as a percentage of relative standard deviation, %R.S.D.) <12. Intra- and inter-day accuracy (as a percentage of the relative error, %RE) was <or=-5.60 and <or=-8.00, respectively. Using this assay, it was found that GL-HCl permeates through human skin with a flux 1.497+/-0.42 microg cm-2 h-1, a permeability coefficient of 5.66+/-1.6x10(-6) cm h-1 and with a lag time of 10.9+/-4.6 h.