A Low Temperature Cofired Ceramic Microfluidic Calorimeter for ELISA Biosensing

2013 ◽  
Vol 2013 (CICMT) ◽  
pp. 000168-000172
Author(s):  
Benjamin Brummel ◽  
Bradley Berron ◽  
Richard E. Eitel
Keyword(s):  
Temperature Sensor ◽  
Protein Detection ◽  
Temperature Sensors ◽  
Cancer Prognosis ◽  
Detection Methods ◽  
Polymerization Reaction ◽  
Biomarker Detection ◽  
Microfluidic Biosensor ◽  
Thermal Detection ◽  
Future Work

The expense and difficulty of current biomarker detection methods is driving the design of microfluidic detection platforms. A ceramic microfluidic biosensor has been developed for conducting enzyme-linked immunosorbent assays (ELISA) using a novel polymerization amplified thermal detection (PATD) scheme. Prototype testing has yielded several results that support the viability of this device. It was seen that LTCC is an effective and durable substrate for the temperature sensor. Noise testing with our prototype revealed that our temperature sensors can detect changes as small as 0.01 K. Additional temperature testing showed that the thermistor behavior matches the expected thermistor beta equation. Finally, it was shown that polymerization reaction induction time is inversely proportional to glucose oxidase (GOx) initiator concentration. These preliminary results provide a foundation for future work developing the sensor into a protein detection device with cancer prognosis applications.

scholarly journals Early Detection Methods for Silicosis in Australia and Internationally: A Review of the Literature

2021 ◽  
Vol 18 (15) ◽  
pp. 8123
Author(s):  
Emma K. Austin ◽  
Carole James ◽  
John Tessier
Keyword(s):  
Early Detection ◽  
Literature Review ◽  
Detection Method ◽  
Detection Methods ◽  
X Rays ◽  
Review Of The Literature ◽  
Occupational Lung Disease ◽  
Work Related ◽  
Growing Body ◽  
Future Work

Pneumoconiosis, or occupational lung disease, is one of the world’s most prevalent work-related diseases. Silicosis, a type of pneumoconiosis, is caused by inhaling respirable crystalline silica (RCS) dust. Although silicosis can be fatal, it is completely preventable. Hundreds of thousands of workers globally are at risk of being exposed to RCS at the workplace from various activities in many industries. Currently, in Australia and internationally, there are a range of methods used for the respiratory surveillance of workers exposed to RCS. These methods include health and exposure questionnaires, spirometry, chest X-rays, and HRCT. However, these methods predominantly do not detect the disease until it has significantly progressed. For this reason, there is a growing body of research investigating early detection methods for silicosis, particularly biomarkers. This literature review summarises the research to date on early detection methods for silicosis and makes recommendations for future work in this area. Findings from this review conclude that there is a critical need for an early detection method for silicosis, however, further laboratory- and field-based research is required.

scholarly journals Electrokinetic Formation of “Microbridges” for Protein Biomarkers as Sensors

2007 ◽  
Vol 12 (5) ◽  
pp. 311-317 ◽  
Author(s):  
Vindhya Kunduru ◽  
Shalini Prasad
Keyword(s):  
Electric Fields ◽  
Microelectrode Array ◽  
Protein Detection ◽  
High Specificity ◽  
Detection Methods ◽  
Label Free ◽  
Protein Biomarkers ◽  
Detection Scheme ◽  
Polystyrene Beads ◽  
Conducting Path

We demonstrate a technique to detect protein biomarkers contained in vulnerable coronary plaque using a platform-based microelectrode array (MEA). The detection scheme is based on the property of high specificity binding between antibody and antigen similar to most immunoassay techniques. Rapid clinical diagnosis can be achieved by detecting the amount of protein in blood by analyzing the protein's electrical signature. Polystyrene beads which act as transportation agents for the immobile proteins (antigen) are electrically aligned by application of homogenous electric fields. The principle of electrophoresis is used to produce calculated electrokinetic movement among the anti-C-reactive protein (CRP), or in other words antibody funtionalized polystyrene beads. The electrophoretic movement of antibody-functionalized polystyrene beads results in the formation of “Microbridges” between the two electrodes of interest which aid in the amplification of the antigen—antibody binding event. Sensitive electrical equipment is used for capturing the amplified signal from the “Microbridge” which essentially behaves as a conducting path between the two electrodes. The technique circumvents the disadvantages of conventional protein detection methods by being rapid, noninvasive, label-free, repeatable, and inexpensive. The same principle of detection can be applied for any receptor—ligand-based system because the technique is based only on the volume of the analyte of interest. Detection of the inflammatory coronary disease biomarker CRP is achieved at concentration levels spanning over the lower microgram/milliliter to higher order nanogram/milliliter ranges.

Circadian rhythm changes in core temperature over the menstrual cycle: method for noninvasive monitoring

2000 ◽  
Vol 279 (4) ◽  
pp. R1316-R1320 ◽  
Author(s):  
Mary D. Coyne ◽  
Christina M. Kesick ◽  
Tammy J. Doherty ◽  
Margaret A. Kolka ◽  
Lou A. Stephenson
Keyword(s):  
Circadian Rhythm ◽  
Menstrual Cycle ◽  
Core Temperature ◽  
Temperature Sensor ◽  
Temperature Sensors ◽  
Cycle Phase ◽  
Noninvasive Method ◽  
Menstrual Cycle Phase ◽  
Cosinor Analysis ◽  
Temperature Amplitude

The purpose of this study was to determine whether core temperature (Tc) telemetry could be used in ambulatory women to track changes in the circadian Tc rhythm during different phases of the menstrual cycle and, more specifically, to detect impending ovulation. Tcwas measured in four women who ingested a series of disposable temperature sensors. Data were collected each minute for 2–7 days and analyzed in 36-h segments by automated cosinor analysis to determine the mesor (mean temperature), amplitude, period, acrophase (time of peak temperature), and predicted circadian minimum core temperature (Tc-min) for each cycle. The Tcmesor was higher ( P ≤ 0.001) in the luteal (L) phase (37.39 ±0.13°C) and lower in the preovulatory (P) phase (36.91 ±0.11°C) compared with the follicular (F) phase (37.08 ±0.13°C). The predicted Tc-min was also greater in L (37.06 ± 0.14°C) than in menses (M; 36.69 ± 0.13°C), F (36.6 ± 0.16°C), and P (36.38 ± 0.08°C) ( P ≤ 0.0001). During P, the predicted Tc-min was significantly decreased compared with M and F ( P ≤ 0.0001). The amplitude of the Tc rhythm was significantly reduced in L compared with all other phases ( P ≤ 0.005). Neither the period nor acrophase was affected by menstrual cycle phase in ambulatory subjects. The use of an ingestible temperature sensor in conjunction with fast and accurate cosinor analysis provides a noninvasive method to mark menstrual phases, including the critical preovulatory period.

scholarly journals Application of deep learning to enhance the accuracy of intrusion detection in modern computer networks

2020 ◽  
Vol 9 (3) ◽  
pp. 1137-1148
Author(s):  
Jafar Majidpour ◽  
Hiwa Hasanzadeh
Keyword(s):  
Deep Learning ◽  
Intrusion Detection ◽  
Computer Networks ◽  
Diagnostic Methods ◽  
Detection Methods ◽  
Training Time ◽  
Modern Computer ◽  
Normal Behavior ◽  
Review Protocol ◽  
Future Work

Application of deep learning to enhance the accuracy of intrusion detection in modern computer networks were studied in this paper. The identification of attacks in computer networks is divided in to two categories of intrusion detection and anomaly detection in terms of the information used in the learning phase. Intrusion detection uses both routine traffic and attack traffic. Abnormal detection methods attempt to model the normal behavior of the system, and any incident that violates this model is considered to be a suspicious behavior. For example, if the web server, which is usually passive, tries to There are many addresses that are likely to be infected with the worm. The abnormal diagnostic methods are Statistical models, Secure system approach, Review protocol, Check files, Create White list, Neural Networks, Genetic Algorithm, Vector Machines, decision tree. Our results have demonstrated that our approach offers high levels of accuracy, precision and recall together with reduced training time. In our future work, the first avenue of exploration for improvement will be to assess and extend the capability of our model to handle zero-day attacks.

scholarly journals Adherence Over Time: The Course of Adherence to Customized Diabetic Insoles as Objectively Assessed by a Temperature Sensor

2017 ◽  
Vol 12 (3) ◽  
pp. 695-700 ◽  
Author(s):  
Dominic Ehrmann ◽  
Monika Spengler ◽  
Michael Jahn ◽  
Dea Niebuhr ◽  
Thomas Haak ◽  
...  
Keyword(s):  
Diabetic Foot ◽  
Temperature Sensor ◽  
Small Sample Size ◽  
Temperature Sensors ◽  
Small Sample ◽  
Gender Effects ◽  
Kaplan Meier ◽  
Foot Problems ◽  
Mean Time

Background: Temperature sensors are an objective way to assess adherence to diabetic footwear. Good adherence is essential for the prevention of diabetic foot problems. Little is known about the long-term course of adherence in patients at risk for diabetic foot problems. Method: A temperature sensor was incorporated into the specialized footwear of patients with type 2 diabetes after their first plantar ulceration. Kaplan-Meier curve was used to analyze when patients started to become nonadherent (not wearing the footwear for two straight weeks). Gender effects on adherence were also analyzed. Results: 26 patients with a mean observation time of 133.5 days could be analyzed. Mean wearing time of diabetic footwear was 4.2 ± 3.6 h/day (Mdn = 3.4 h/day; interquartile range = 0.5-7.0 h/day) and on 51% of the days patients did not wear their footwear at all. Kaplan-Meier curve revealed that the mean time of adherence was 27.5 weeks. Men achieved a mean time of adherence of 30.5 weeks, while women only achieved 14 weeks. However, due to the small sample size, this difference was not statistically significant. Conclusions: Temperature sensors revealed a low long-term adherence to diabetic footwear. Women seemed to be at a higher risk for earlier nonadherent behavior. Adherence to diabetic footwear should be closely monitored and tailored intervention strategies should be developed.

PLA conductive filament for 3D printed smart sensing applications

2018 ◽  
Vol 24 (4) ◽  
pp. 739-743 ◽  
Author(s):  
Simone Luigi Marasso ◽  
Matteo Cocuzza ◽  
Valentina Bertana ◽  
Francesco Perrucci ◽  
Alessio Tommasi ◽  
...  
Keyword(s):  
Temperature Sensor ◽  
Low Cost ◽  
Conductive Polymer ◽  
Temperature Characteristic ◽  
Temperature Sensors ◽  
Electrical Performance ◽  
Content Type ◽  
Sensing Applications ◽  
3D Printed

Purpose This paper aims to present a study on a commercial conductive polylactic acid (PLA) filament and its potential application in a three-dimensional (3D) printed smart cap embedding a resistive temperature sensor made of this material. The final aim of this study is to add a fundamental block to the electrical characterization of printed conductive polymers, which are promising to mimic the electrical performance of metals and semiconductors. The studied PLA filament demonstrates not only to be suitable for a simple 3D printed concept but also to show peculiar characteristics that can be exploited to fabricate freeform low-cost temperature sensors. Design/methodology/approach The first part is focused on the conductive properties of the PLA filament and its temperature dependency. After obtaining a resistance temperature characteristic of this material, the same was used to fabricate a part of a 3D printed smart cap. Findings An approach to the characterization of the 3D printed conductive polymer has been presented. The major results are related to the definition of resistance vs temperature characteristic of the material. This model was then exploited to design a temperature sensor embedded in a 3D printed smart cap. Practical implications This study demonstrates that commercial conductive PLA filaments can be suitable materials for 3D printed low-cost temperature sensors or constitutive parts of a 3D printed smart object. Originality/value The paper clearly demonstrates that a new generation of 3D printed smart objects can already be obtained using low-cost commercial materials.

scholarly journals Differential Temperature Sensors: Review of Applications in the Test and Characterization of Circuits, Usage and Design Methodology

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4815 ◽  
Author(s):  
Enrique Barajas ◽  
Xavier Aragones ◽  
Diego Mateo ◽  
Josep Altet
Keyword(s):  
Integrated Circuits ◽  
Analog Circuits ◽  
Temperature Sensor ◽  
Design Methodology ◽  
Dynamic Range ◽  
Simple Procedure ◽  
High Dynamic Range ◽  
Temperature Sensors ◽  
Time Variability ◽  
Linear Power Amplifier

Differential temperature sensors can be placed in integrated circuits to extract a signature of the power dissipated by the adjacent circuit blocks built in the same silicon die. This review paper first discusses the singularity that differential temperature sensors provide with respect to other sensor topologies, with circuit monitoring being their main application. The paper focuses on the monitoring of radio-frequency analog circuits. The strategies to extract the power signature of the monitored circuit are reviewed, and a list of application examples in the domain of test and characterization is provided. As a practical example, we elaborate the design methodology to conceive, step by step, a differential temperature sensor to monitor the aging degradation in a class-A linear power amplifier working in the 2.4 GHz Industrial Scientific Medical—ISM—band. It is discussed how, for this particular application, a sensor with a temperature resolution of 0.02 K and a high dynamic range is required. A circuit solution for this objective is proposed, as well as recommendations for the dimensions and location of the devices that form the temperature sensor. The paper concludes with a description of a simple procedure to monitor time variability.

scholarly journals Circulating Tumor Cells in Pancreatic Cancer: Current Perspectives

Cancers ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1659 ◽  
Author(s):  
Verena Martini ◽  
Sylvia Timme-Bronsert ◽  
Stefan Fichtner-Feigl ◽  
Jens Hoeppner ◽  
Birte Kulemann
Keyword(s):  
Pancreatic Cancer ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Prognostic Markers ◽  
Cancer Prognosis ◽  
Detection Methods ◽  
Ductal Adenocarcinoma ◽  
Detection Tool ◽  
The Usa ◽  
New Biomarkers

Pancreatic cancer is the fourth leading cause of cancer-related death in the USA and Europe; early symptoms and screenings are lacking, and it is usually diagnosed late with a poor prognosis. Circulating tumor cells (CTCs) have been promising new biomarkers in solid tumors. In the last twenty years (1999–2019), 140 articles have contained the key words “Circulating tumor cells, pancreatic cancer, prognosis and diagnosis.” Articles were evaluated for the use of CTCs as prognostic markers and their correlation to survival in pancreatic ductal adenocarcinoma (PDAC). In the final selected 17 articles, the CTC detection rate varied greatly between different enrichment methodologies and ranged from 11% to 92%; the majority of studies used the antigen-dependent CellSearch© system for CTC detection. Fifteen of the reviewed studies showed a correlation between CTC presence and a worse overall survival. The heterogeneity of CTC-detection methods and the lack of uniform results hinder a comparison of the evaluated studies. However, CTCs can be detected in pancreatic cancer and harbor a hope to serve as an early detection tool. Larger studies are needed to corroborate CTCs as valid biomarkers in pancreatic cancer.

Smart temperature sensors and temperature sensor systems

2018 ◽  
pp. 57-85 ◽  
Author(s):  
Gerard C.M. Meijer ◽  
Guijie Wang ◽  
Ali Heidary
Keyword(s):  
Temperature Sensor ◽  
Temperature Sensors ◽  
Sensor Systems
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