Integrated Bioassays for Screening Chemical and Biological Species

The idea of having an entire biological assay system on a single silicon wafer is promising with significant advantages in improving experimental throughput and sensitivity. This thesis presents three unique biological assays combining microfluidics and microelectronics technologies for high-throughput screening of biological samples: electronic sensors for detecting biomolecular charges, microchannels to characterize worm locomotion, and modulated trenches for differentiating mutant phenotypes. The first chapter reports a novel floating-gate biosensor to detect and sense nano-scale charged particles such as charged poly amino acids. The device is fully CMOS compatible and has the ease of mass production. The new architecture of the floating gate enables scaling of the device area and incorporation of on-chip readout lines. Testing results show a strong sensitivity to the polarity and concentration of different poly amino acids tested. CMOS compatibility of the device is particularly useful while designing autonomous systems for biochemical sensing which require the on-chip integration of sensors, control circuitry, memory devices, and power lines. The second chapter presents microfluidic bioassays for the phenotypic characterization of a certain class of animal and plant microorganisms called nematodes. Nematodes cause huge economic loss every year to agriculture and farm animals. In humans, exposure to meat or crops infected with nematodes cause long-term depression and reduced work productivity. However, with prolonged exposure to anthelmintic drugs, nematodes have evolved into new strains with varying levels of resistance to known drugs. With a goal to differentiate different isolates, the bioassay measures phenotype using parameters of nematode locomotion. We characterize two different species of nematode and two isolates within one species: a plant parasite Soybean Cyst Nematode (SCN) and two isolates of an animal parasite Oesophagostomum dentatum. Parameters of sinusoidal motion such as propagation velocity, wavelength, wave amplitude, and oscillation frequency depend on the levamisole-sensitivity and strain of parasitic nematode. There are significant differences between the two strains (SENS and LEVR) and the two species (O. dentatum and SCN). This microfluidic technology advances present-day nematode migration assays and provides a better quantification and increased drug sensitivity. It is anticipated that the bioassay will facilitate study of resistance to other anthelmintic drugs that affect locomotion. In the third chapter we report a new scheme to passively screen and sort different isolates of parasitic nematodes that may be visually indistinguishable. Unlike previous devices that immobilize worms or chemically treat them in micro scale chambers, we allow the nematodes to pass through modulated sinusoidal trenches and observe their locomotion at real-time. We then define and characterize locomotion parameters that help us identify and distinguish isolates automatically. We demonstrate this simple scheme of sorting whole animals using two isolates of O. dentatum. In addition, a custom image tracking software is developed to enable automated extraction and analysis of the experiments performed. Such bioassays are critical towards advancing high-throughput screening methods on whole organisms - a field that is relatively new in the scientific community

Detecting and Combating Fraudulent Health Insurance Claims Using ANN

This work was funded by the National Nature Science Foundation of China (71774069), 2014 “Six Talent Peaks” Project of Jiangsu Province (2014- JY-004) Abstract While governments and private sector stakeholders are taking steps to improve the access and quality of health care service to its citizenry, a lot of resources are lost every year due to fraudulent health insurance claims. The aim of this paper is to explore a more robust and accurate ways of predicting fraudulent health insurance claims by the use of artificial neural network (ANN). Using the fraud diamond theory (FDT)’s fraud elements as fraud indicators, a fraud prediction model was created to determine whether a claim presented by a subscriber (individual) is fraudulent or non-fraudulent by varying severally the number of epoch, hidden layer number and threshold of the artificial neural network on a 14 input data to obtain an optimal parameter for the model.The model was able to predict accurately 98.98% with an MSE of 0.0086, which outperformed other artificial neural network (ANN) methods used to predict fraudulent health care claims. The incorporation of the capacity indicator of the fraud diamond theory (FDT) makes this model a tool not only for prediction but also pre-empting the occurrence of fraud. This study is the first to adopt the fraud diamond theory’s fraud elements as fraud indicators together with artificial neural network (ANN) in predicting fraudulent health insurance claims. Keywords: health insurance claim, ANN, fraud prediction model, fraud diamond theor

Bifurcation Analysis of a Chemostat Model of Plasmid-Bearing and Plasmid-Free Competition with Pulsed Input

A chemostat model of plasmid-bearing and plasmid-free competition with pulsed input is proposed. The invasion threshold of the plasmid-bearing and plasmid-free organisms is obtained according to the stability of the boundary periodic solution. By use of standard techniques of bifurcation theory, the periodic oscillations in substrate, plasmid-bearing, and plasmid-free organisms are shown when some conditions are satisfied. Our results can be applied to control bioreactor aimed at producing commercial producers through genetically altered organisms

Effect of combined vitamin D and microwave ablation of parathyroid glands on blood pressure and cardiac function in maintenance-hemodialysis patients with uremic secondary hyperparathyroidism

Purpose: To investigate the effect of microwave ablation of parathyroid glands in combination with active vitamin D on blood pressure and cardiac function in maintenance-hemodialysis patients with uremic secondary hyperparathyroidism. Methods: One hundred and twenty maintenance-hemodialysis patients with uremic secondary hyperparathyroidism admitted to Meizhou People’s Hospital were assigned to 2 groups (A and B) in the order of their admission. Each group had 60 patients. Both groups were treated with active vitamin D, while patients in group A were, in addition, subjected to microwave ablation of parathyroid glands. Blood pressure, and indices for cardiac function, thyroid function s and anemia were determined. Results: After treatment, the blood pressure of group A was significantly lower than that of group B (p < 0.05). Moreover, after treatment, there were significant improvements in indices of cardiac function, thyroid function and anemia in group A patients, relative to group B patients. Conclusion: Microwave ablation of parathyroid glands, when combined with active vitamin D, improves blood pressure, cardiac function and anemia status. Furthermore, the combined therapy enhances recovery of thyroid function in maintenance-hemodialysis patients with uremic secondary hyperparathyroidism. However, the combined therapy should be subjected to further clinical trials prior to application in clinical practice. Keywords: Microwave ablation; Parathyroid glands; Active vitamin D; Hyperparathyroidis

Optimum Pipeline for Visual Terrain Classification Using Improved Bag of Visual Words and Fusion Methods

We propose an optimum pipeline and develop the hybrid representation to produce an effective and efficient visual terrain classification system. The bag of visual words (BOVW) framework has emerged as a promising approach and effective paradigm for visual terrain classification. The method includes four main steps: (1) feature extraction, (2) codebook generation, (3) feature coding, and (4) pooling and normalization. Recent researches have primarily focused on feature extraction in the development of new handcrafted descriptors that are specific to the visual terrain. However, the effects of other steps on visual terrain classification are still unknown. At the same time, fusion methods are often used to boost classification performance by exploring the complementarity of diverse features. We provide a comprehensive study of all steps in the BOVW framework and different fusion methods for visual terrain classification. Then, multiple approaches in each step and their effects are explored on the visual terrain dataset. Finally, the feature preprocessing technique, improved BOVW framework, and fusion method are used to construct an optimum pipeline for visual terrain classification. The hybrid representation developed by the optimum pipeline performs effectively and rapidly for visual terrain classification in the terrain dataset, outperforming those current methods. Furthermore, it is robust to diverse noises and illumination alterations

Compact source of narrowband and tunable X-rays for radiography

We discuss the development of a compact X-ray source based on inverse-Compton scattering with a laser-driven electron beam. This source produces a beam of high-energy X-rays in a narrow cone angle (5–10 mrad), at a rate of 108 photons-s_1. Tunable operation of the source over a large energy range, with energy spread of ~50%, has also been demonstrated. Photon energies \u3e10 MeV have been obtained. The narrowband nature of the source is advantageous for radiography with low dose, low noise, and minimal shielding

Integrated Bioassays for Screening Chemical and Biological Species

The idea of having an entire biological assay system on a single silicon wafer is promising with significant advantages in improving experimental throughput and sensitivity. This thesis presents three unique biological assays combining microfluidics and microelectronics technologies for high-throughput screening of biological samples: electronic sensors for detecting biomolecular charges, microchannels to characterize worm locomotion, and modulated trenches for differentiating mutant phenotypes. The first chapter reports a novel floating-gate biosensor to detect and sense nano-scale charged particles such as charged poly amino acids. The device is fully CMOS compatible and has the ease of mass production. The new architecture of the floating gate enables scaling of the device area and incorporation of on-chip readout lines. Testing results show a strong sensitivity to the polarity and concentration of different poly amino acids tested. CMOS compatibility of the device is particularly useful while designing autonomous systems for biochemical sensing which require the on-chip integration of sensors, control circuitry, memory devices, and power lines. The second chapter presents microfluidic bioassays for the phenotypic characterization of a certain class of animal and plant microorganisms called nematodes. Nematodes cause huge economic loss every year to agriculture and farm animals. In humans, exposure to meat or crops infected with nematodes cause long-term depression and reduced work productivity. However, with prolonged exposure to anthelmintic drugs, nematodes have evolved into new strains with varying levels of resistance to known drugs. With a goal to differentiate different isolates, the bioassay measures phenotype using parameters of nematode locomotion. We characterize two different species of nematode and two isolates within one species: a plant parasite Soybean Cyst Nematode (SCN) and two isolates of an animal parasite Oesophagostomum dentatum. Parameters of sinusoidal motion such as propagation velocity, wavelength, wave amplitude, and oscillation frequency depend on the levamisole-sensitivity and strain of parasitic nematode. There are significant differences between the two strains (SENS and LEVR) and the two species (O. dentatum and SCN). This microfluidic technology advances present-day nematode migration assays and provides a better quantification and increased drug sensitivity. It is anticipated that the bioassay will facilitate study of resistance to other anthelmintic drugs that affect locomotion. In the third chapter we report a new scheme to passively screen and sort different isolates of parasitic nematodes that may be visually indistinguishable. Unlike previous devices that immobilize worms or chemically treat them in micro scale chambers, we allow the nematodes to pass through modulated sinusoidal trenches and observe their locomotion at real-time. We then define and characterize locomotion parameters that help us identify and distinguish isolates automatically. We demonstrate this simple scheme of sorting whole animals using two isolates of O. dentatum. In addition, a custom image tracking software is developed to enable automated extraction and analysis of the experiments performed. Such bioassays are critical towards advancing high-throughput screening methods on whole organisms - a field that is relatively new in the scientific community.</p