Detection of the melanoma biomarker TROY using silicon nanowire field-effect transistors

Antibody-functionalized silicon nanowire field-effect transistors have been shown to exhibit excellent analyte detection sensitivity enabling sensing of analyte concentrations at levels not readily accessible by other methods. One example where accurate measurement of small concentrations is necessary is detection of serum biomarkers, such as the recently discovered tumor necrosis factor receptor superfamily member TROY (TNFRSF19), which may serve as a biomarker for melanoma. TROY is normally only present in brain but it is aberrantly expressed in primary and metastatic melanoma cells and shed into the surrounding environment. In this study, we show the detection of different concentrations of TROY in buffer solution using top-down fabricated silicon nanowires. We demonstrate the selectivity of our sensors by comparing the signal with that obtained from bovine serum albumin in buffer solution. Both the signal size and the reaction kinetics serve to distinguish the two signals. Using a fast-mixing two-compartment reaction model, we are able to extract the association and dissociation rate constants for the reaction of TROY with the antibody immobilized on the sensor surface

Sensing of the melanoma biomarker TROY using silicon nanowire field-effect transistors

Antibody-functionalized silicon nanowire field-effect transistors have been shown to exhibit excellent analyte detection sensitivity enabling sensing of analyte concentrations at levels not readily accessible by other methods. One example where accurate measurement of small concentrations is necessary is detection of serum biomarkers, such as the recently discovered tumor necrosis factor receptor superfamily member TROY (TNFRSF19), which may serve as a biomarker for melanoma. TROY is normally only present in brain but it is aberrantly expressed in primary and metastatic melanoma cells and shed into the surrounding environment. In this study, we show the detection of different concentrations of TROY in buffer solution using top-down fabricated silicon nanowires. We demonstrate the selectivity of our sensors by comparing the signal with that obtained from bovine serum albumin in buffer solution. Both the signal size and the reaction kinetics serve to distinguish the two signals. Using a fast-mixing two-compartment reaction model we are able to extract the association and dissociation rate constants for the reaction of TROY with the antibody immobilized on the sensor surface.The authors thank Biosite Diagnostics (San Diego, CA) for providing TROY antibodies. The authors acknowledge NIH, NSF, and Battelle Memorial Institute for support of this work. (NIH; NSF; Battelle Memorial Institute)https://pubs.acs.org/doi/pdf/10.1021/acssensors.6b00017Accepted manuscrip

Field Effect Transistor Nanosensor for Breast Cancer Diagnostics

Silicon nanochannel field effect transistor (FET) biosensors are one of the most promising technologies in the development of highly sensitive and label-free analyte detection for cancer diagnostics. With their exceptional electrical properties and small dimensions, silicon nanochannels are ideally suited for extraordinarily high sensitivity. In fact, the high surface-to-volume ratios of these systems make single molecule detection possible. Further, FET biosensors offer the benefits of high speed, low cost, and high yield manufacturing, without sacrificing the sensitivity typical for traditional optical methods in diagnostics. Top down manufacturing methods leverage advantages in Complementary Metal Oxide Semiconductor (CMOS) technologies, making richly multiplexed sensor arrays a reality. Here, we discuss the fabrication and use of silicon nanochannel FET devices as biosensors for breast cancer diagnosis and monitoring

Non-Invasive Electromagnetic Biological Microwave Testing

Blood glucose monitoring is a primary tool for the care of diabetic patients. At present, there is no noninvasive monitoring technique of blood glucose concentration that is widely accepted in the medical industry. New noninvasive measurement techniques are being investigated. This work focuses on the possibility of a monitor that noninvasively measures blood glucose levels using electromagnetic waves. The technique is based on relating a monitoring antenna’s resonant frequency to the permittivity, and conductivity of skin, which in turn, is related to the glucose levels. This becomes a hot researched field in recent years. Different types of antennas (wideband and narrowband) have been designed, constructed, and tested in free space. An analytical model for the antenna has been developed, which has been validated with simulations. Microstrip antenna is one of the most common planar antenna structures used. Extensive research development aimed at exploiting its advantages such as lightweight, low cost, conformal configurations, and compatibility with integrated circuits have been carried out. Rectangular and circular patches are the basic shapes that are the most commonly used in microstrip antennas. Ideally, the dielectric constant εr, however, and other performance requirements may dictate the use of substrate whose dielectric constant can be greater. As in our prototype blood sensor, the miniaturized size is one of the main challenges

3D Simulations of Intracerebral Hemorrhage Detection Using Broadband Microwave Technology

Early, preferably prehospital, detection of intracranial bleeding after trauma or stroke would dramatically improve the acute care of these large patient groups. In this paper, we use simulated microwave transmission data to investigate the performance of a machine learning classification algorithm based on subspace distances for the detection of intracranial bleeding. A computational model, consisting of realistic human head models of patients with bleeding, as well as healthy subjects, was inserted in an antenna array model. The Finite-Difference Time-Domain (FDTD) method was then used to generate simulated transmission coefficients between all possible combinations of antenna pairs. These transmission data were used both to train and evaluate the performance of the classification algorithm and to investigate its ability to distinguish patients with versus without intracranial bleeding. We studied how classification results were affected by the number of healthy subjects and patients used to train the algorithm, and in particular, we were interested in investigating how many samples were needed in the training dataset to obtain classification results better than chance. Our results indicated that at least 200 subjects, i.e., 100 each of the healthy subjects and bleeding patients, were needed to obtain classification results consistently better than chance (p < 0.05 using Student\u27s t-test). The results also showed that classification results improved with the number of subjects in the training data. With a sample size that approached 1000 subjects, classifications results characterized as area under the receiver operating curve (AUC) approached 1.0, indicating very high sensitivity and specificity

Measurements and analysis of the microwave dielectric properties of tissues

Knowledge of the microwave dielectric properties of human tissues is essential for the understanding and development of medical microwave techniques. In particular, microwave thermography relies on processes fundamentally determined by the high frequency electromagnetic properties of human tissues. The specific aim of this work was to provide detailed information on the dielectric properties of female human breast tissue at 3-3.5GHz, the frequency of operation of the Glasgow microwave thermography equipment. At microwave frequences the frequency variation of the dielectric properties of biological tissues is thought to be determined mainly by the dipolar relaxation of tissue water. Water exists in different states of binding within the tissue; the relaxation of each component of this water may be parameterised by the Debye or Cole-Cole equations. At a single frequency an average relaxation frequency may be calculated for a given tissue type. Mixture equations may be used to describe the dielectric properties of two-phase mixtures in terms of the dielectric properties and volume fractions of the component phases. Biological tissues are very much more complex than these two phase models. However, comparisons of the observed dielectric properties as a function of water content, with models calculated from mixture theory allow some qualitative conclusions to be drawn regarding tissue structure. Human and animal dielectric data at frequencies between 0.1 and 10GHz have been collected from the literature and are displayed in tabular form. These comprehensive tables were used to examine the widely-held assumption an animal tissue is representative of the corresponding human tissue. This assumption was concluded to be uncertain in most cases because of lack of available data, and perhaps wrong for certain tissue types. The tables were also used to compare in vivo and in vitro dielectric data. These may be expected to be different because the tissue is in a physiologically abnormal state in vitro. However at microwave frequencies in vitro data was found to be representative of the tissue in vivo provided gross deterioration of the tissue is avoided. A new resonant cavity perturbation technique was designed for dielectric measurements of small volumes of lossy materials at a fixed frequency of 3.2GHz. This technique may be used to measure materials of a wide range of permittivities and conductivities with accuracies of 3-4%. The major sources of error were found to be tissue heterogeneity and sample preparation procedures. Using this technique in vitro dielectric measurements were made on human female breast tissues. A large number of data were gathered on fat and normal breast tissues, and on benign and malignant breast tumours. Each data set was parameterised using the Debye equation. Results from this suggest that all breast tissues measured in this work contain a component of bound water. A smaller proportion of water is bound in fat than is bound in other tissues. Comparisons were made of the dielectric properties of breast tissues with values calculated from mixture theories. Permittivity data largely fall within bounds set by mixture theory: conductivity data often fall outside these limits. This may imply that physiological saline is not a good approximation to tissue waters; or it may imply that another relaxation process is occurring in addition to the dipolar relaxation of saline. Comparisons of tissue type indicate that a dielectric imaging system could be designed which would detect breast diseases, but that severe problems could arise in distinguishing disease types from dielectric imaging alone

Permittivity Extraction of Glucose Solutions Through Artificial Neural Networks and Non-invasive Microwave Glucose Sensing

An accurate low-cost method is presented for measuring the complex permittivity of glucose/water solutions. Moreover, a compact non-invasive RF/microwave sensor is presented for glucose sensing with the reasoning behind design parameters as well as simulation and measurement results. The complex permittivity values of aqueous solutions of glucose were measured with an in-house manufactured open-ended coaxial probe and the values were extracted from the measured complex reflection coefficients (S11) utilizing artificial neural networks. The obtained results were validated against a commercial probe. The values were fitted to the Debye relaxation model for ease of evaluation for a desired glucose concentration at a desired frequency. The proposed permittivity model in this paper is valid for glucose concentrations of up to 16 g/dl in the 0.3–15 GHz range. The model is useful for simulating and validating non-invasive RF glucose sensors

A Glucose Sensing System Based on Transmission Measurements at Millimetre Waves using Micro strip Patch Antennas

AbstractWe present a sensing system operating at millimetre (mm) waves in transmission mode that can measure glucose level changes based on the complex permittivity changes across the signal path. The permittivity of a sample can change significantly as the concentration of one of its substances varies: for example, blood permittivity depends on the blood glucose levels. The proposed sensing system uses two facing microstrip patch antennas operating at 60 GHz, which are placed across interrogated samples. The measured transmission coefficient depends on the permittivity change along the signal path, which can be correlated to the change in concentration of a substance. Along with theoretical estimations, we experimentally demonstrate the sensing performance of the system using controlled laboratory samples, such as water-based glucose-loaded liquid samples. We also present results of successful glucose spike detection in humans during an in-vivo Intravenous Glucose Tolerance Test (IVGTT). The system could eventually be developed into a non-invasive glucose monitor for continuous monitoring of glucose levels for people living with diabetes, as it can detect as small as 1.33 mmol/l (0.025 wt%) glucose concentrations in the controlled water-based samples satisfactorily, which is well below the typical human glucose levels of 4 mmol/l.</jats:p

Detection and Modeling of Radiation Induced Effects in Tissues by Dielectric Spectroscopy

The work presented here is applied physics research in the field of radiation treatment. We address the development of a new and innovative method, in vivo and possibly non-invasive, for tumor and healthy tissues control during and after the radiation treatment. The radiation treatment is delivered in an almost standardized manner for particular classes of tumors. The large variance in the individual radio sensitivity of healthy tissues and tumors often leads to local recurrence of neoplastic growth and/or distant metastatic disease which often remains untreated. The method is based on the measurement and analysis of electrical impedance data in the frequency domain from 50 mHz to 1MHz. The dielectric signature of the tissue carries information about the integrity of the plasma membrane, as well as about the tissue micro-architecture. We present dielectric models for biological materials and correlate their parameters with the subtle changes characterizing oncosis or apoptosis occurring as result of radiation or excision. Five tissue types (blood, kidney, liver, lung and heart) were studied and specific impedance models were created for each of them. Based on these models, analysis of freshly excised tissue and radiation-induced effects in excised tissue was carried out and model parameters extracted. The data we present shows correlation between known mechanisms of cellular death and the delivery of radiation, thus making possible a quantification of the individual response. Further work will be needed in order to correlate early impedance changes with late tissue changes characterizing the side effects of the radiotherapy