Label-free biosensors for the detection and quantification of cardiovascular risk markers

This paper presents a biosensor implementation for the detection of protein molecules using specific antibodies. Affinity sensors allow the detection and quantification of target molecules in complex mixtures by affinity-based interactions. Immobilized antibody molecules are the probes that bind to specific protein molecules (targets) in biological fluids. In this study, inter-digitated electrodes in the form of capacitance on glass slide were designed, fabricated and used to measure the changes in the dielectric properties of the inter-digitated capacitances. Our results in this study present that with a careful design of micro-interdigitated capacitors, a wider dynamic range and higher sensitivity can be achieved for the detection and quantification of C-Reeactive Protein

A new lab-on-chip transmitter for the detection of proteins using RNA aptamers

A new RNA aptamer based affinity biosensor for CReactive Protein (CRP), a risk marker for cardiovascular disease was developed using interdigitated capacitor (IDC), integrated in Voltage Controlled Oscillator (VCO) and output signal is amplified using Single Stage Power Amplifier (PA) for transmitting signal to receiver at Industrial, Scientific and Medical (ISM) band. The Lab-on-Chip transmitter design includes IDC, VCO and PA. The design was implemented in IHP 0.25μm SiGe BiCMOS process; post-CMOS process was utilized to increase the sensitivity of biosensor. The CRP was incubated between or on interdigitated electrodes and the changes in capacitance of IDC occurred. In blank measurements, the oscillation frequency was 2.464GHz whereas after RNA aptamers were immobilized on open aluminum areas of IDC and followed by binding reaction processed with 500pg/ml CRP solution, the capacitance shifted to 2.428GHz. Phase noise is changed from -114.3dBc/Hz to -116.5dBc/Hz

Role of metallurgy in the thermal conductivity of superconducting niobium

Superconducting radio frequency (SRF) cavities for particle accelerators are fabricated using high purity niobium to allow for continuous high power operation. A hot-spot generated at a surface defect during accelerator operation can quench superconductivity and limit its performance. Increased heat conduction to the liquid helium bath dissipates hot spots, maintaining performance. Properly treated niobium may exhibit a local maximum (i.e., phonon peak) in thermal conductivity at T=1.8 K, the accelerator operating temperature. Conductivity with a phonon peak may be more than ten times that without the peak. Fabrication from ingot to cavity involves substantial processing, which in turn defines the metallurgical state of the niobium. Understanding the role of metallurgy and processing on conduction in the phonon regime can lead to improved accelerator performance.This study reveals the role of metallurgy (e.g., grain size and orientation, imperfection density, metal purity) and processing (e.g., deformation, heat treatment) on the magnitude of the phonon peak. This study examines the most comprehensive set of conditions in a group of related uniaxial tensile specimens of mono- and bicrystal niobium with purity of 100 ≤ RRR ≤ 200. Measurements of the thermal conductivity of the niobium were made with a coldest bath temperature of 1.6 K. A novel parameter estimation technique used data from a range of temperatures to determine parameters in a theoretically based model of the thermal conductivity of superconducting metals, without resorting to intermediate approximations.The grain orientations and imperfection densities of the specimens were examined using electron backscatter diffraction and high energy X-ray diffraction, respectively. The role of deformation was examined by uniaxially straining several specimens to 2–38%, typical of SRF cavity manufacturing. The kinetics of recovering the phonon peak post-deformation was revealed by heat treating specimens from 140 °C for 48 h to 1200 °C for 2 h in a high-vacuum furnace. Two specimens were saturated with hydrogen to examine its effect on thermal conductivity.The as-received specimens displayed no phonon peak due to thermal strain-induced dislocations from ingot production. The recovery of a phonon peak depended sigmoidally on the heat treatment temperature, with a plateau after 1000 °C. The dislocation density of the specimens decreased with increasing heat treatment temperature, but the vacancy concentration increased dramatically. Phonon conductivity appears to be dependent on the vacancy concentration. In addition, smaller RRR yielded a smaller phonon peak. Results revealed that the density of dislocations introduced during deformation depends on both grain orientation and strain level. The recovery of the phonon peak by post-deformation heat treatment at 1000 °C for 2 h was complete for specimens with ≤ 74% reduction in the phonon peak due to strain-induced dislocations. Although hydrogen infused during typical cavity processing steps left the phonon peak unchanged, specimens saturated with hydrogen displayed a 25% reduction. The concentration of hydrogen was deduced to be affected by vacancy concentration of the specimens.These results should assist those designing and manufacturing SRF cavities by guiding them to the processes that may provide the greatest possible thermal conductivity for niobium cavities operating at T=1.8 K.Thesis (Ph. D.)--Michigan State University. Mechanical Engineering, 2013Includes bibliographical reference

Development of a new biosensor array and lab-on-a-chip for portable applications using a label-free detection method

The detection and quantification of cardiac biomarkers in serum is crucial to diagnose patients in the early stage of a disease. The recent advances in microfluidics technology can improve diagnostics by reducing the application time and integrating several clinical analysis into a single, portable device called lab-on-a-chip (LOC). The development of such immunosensing LOC is a major thrust of the rapidly growing bionanotechnology industry. It involves a multidisciplinary research effort encompassing microfluidics, microelectronics and biochemistry. This thesis work focused on the development of immunoassays on microfabricated gold inter-digitated transducers (IDT) on silica and glass substrates. The concept of label-free, affinity-based biosensing is introduced with a special emphasis to impedance spectroscopy. Different protocols involving the covalent immobilization of cancer risk marker (human epidermal growth factor, hEGFR) and cardiac risk marker proteins C reactive protein (CRP), interleukin (IL6) and nicotinamide phosphoribosyltransferase (Nampt) single stranded deoxyribonucleic acid were investigated. For this, IDTs were fabricated using integrated circuit (IC) fabrication processes providing compatibility for the integration of electronic circuits, for single-chip and lab-on-a-chip biosensing applications. The thesis also involves development of a poly dimethylsiloxane (PDMS)-based fluidic system comprising on-chip actuated mechanism for multi-target immunosensing applications. The fluidic flow is controlled by an applied hydraulic pressure on the micropump. Label-free affinity type sensing was carried out using two different biological recognition elements (a) immunosensing approach using antibodies for hEGFR and IL-6 was employed and the function of the LOC was analyzed for detection of hEGFR and IL-6 as model analytes. A detection limit of 0.1ng/ml of hEGFR and IL-6 in serum was obtained without any signal amplification. (b) label-free affinity-based methodology using ssDNA aptamers specific for Nampt to develop an aptasensor and obtained a detection limit of 1 ng/ml in serum for Nampt, which is the most sensitive detection range with the application of the aptamer for Nampt

Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach

Cloud service owners need to continuously monitor their services to ensure high availability and reliability. Gaps in monitoring can lead to delay in incident detection and significant negative customer impact. Current process of monitor creation is ad-hoc and reactive in nature. Developers create monitors using their tribal knowledge and, primarily, a trial and error based process. As a result, monitors often have incomplete coverage which leads to production issues, or, redundancy which results in noise and wasted effort. In this work, we address this issue by proposing an intelligent monitoring framework that recommends monitors for cloud services based on their service properties. We start by mining the attributes of 30,000+ monitors from 791 production services at Microsoft and derive a structured ontology for monitors. We focus on two crucial dimensions: what to monitor (resources) and which metrics to monitor. We conduct an extensive empirical study and derive key insights on the major classes of monitors employed by cloud services at Microsoft, their associated dimensions, and the interrelationship between service properties and this ontology. Using these insights, we propose a deep learning based framework that recommends monitors based on the service properties. Finally, we conduct a user study with engineers from Microsoft which demonstrates the usefulness of the proposed framework. The proposed framework along with the ontology driven projections, succeeded in creating production quality recommendations for majority of resource classes. This was also validated by the users from the study who rated the framework's usefulness as 4.27 out of 5