scholarly journals A Non-invasive, Low-cost Procedure to Detect Cancer Biomarkers from Biological Fluids

2021 ◽  
Author(s):  
Anton Iliuk
Keyword(s):  
Biological Fluids ◽  
Low Cost ◽  
Cancer Biomarkers ◽  
Non Invasive

scholarly journals Isolation of Extracellular Vesicles from Biological Fluids via the Aggregation–Precipitation Approach for Downstream miRNAs Detection

Diagnostics ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 384
Author(s):  
Maria Y. Konoshenko ◽  
Evgeniy A. Lekchnov ◽  
Olga E. Bryzgunova ◽  
Elena Kiseleva ◽  
Inna A. Pyshnaya ◽  
...  
Keyword(s):  
Extracellular Vesicles ◽  
Biological Fluids ◽  
Low Cost ◽  
Precipitation Method ◽  
Medical Applications ◽  
Non Invasive ◽  
Clinical Laboratories ◽  
Healthy Donors ◽  
Invasive Diagnostics ◽  
Productive Method

Extracellular vesicles (EVs) have high potential as sources of biomarkers for non-invasive diagnostics. Thus, a simple and productive method of EV isolation is demanded for certain scientific and medical applications of EVs. Here we aim to develop a simple and effective method of EV isolation from different biofluids, suitable for both scientific, and clinical analyses of miRNAs transported by EVs. The proposed aggregation–precipitation method is based on the aggregation of EVs using dextran blue and the subsequent precipitation of EVs using 1.5% polyethylene glycol solutions. The developed method allows the effective isolation of EVs from plasma and urine. As shown using TEM, dynamic light scattering, and miRNA analyses, this method is not inferior to ultracentrifugation-based EV isolation in terms of its efficacy, lack of inhibitors for polymerase reactions and applicable for both healthy donors and cancer patients. This method is fast, simple, does not need complicated equipment, can be adapted for different biofluids, and has a low cost. The aggregation–precipitation method of EV isolation accessible and suitable for both research and clinical laboratories. This method has the potential to increase the diagnostic and prognostic utilization of EVs and miRNA-based diagnostics of urogenital pathologies.

Microextraction and Chromatographic Analysis of Budesonide Epimers in Exhaled Breath Condensate

2020 ◽  
Vol 16 (8) ◽  
pp. 1032-1040
Author(s):  
Laleh Samini ◽  
Maryam Khoubnasabjafari ◽  
Mohamad M. Alimorad ◽  
Vahid Jouyban-Gharamaleki ◽  
Hak-Kim Chan ◽  
...  
Keyword(s):  
Biological Fluids ◽  
Exhaled Breath Condensate ◽  
Low Cost ◽  
Exhaled Breath ◽  
Chromatography Method ◽  
Extraction Solvent ◽  
Drug Concentrations ◽  
Dispersive Liquid Liquid Microextraction ◽  
Breath Condensate

Background: Analysis of drug concentrations in biological fluids is required in clinical sciences for various purposes. Among other biological samples, exhaled breath condensate (EBC) is a potential sample for follow up of drug concentrations. Methods: A dispersive liquid-liquid microextraction (DLLME) procedure followed by a validated liquid chromatography method was employed for the determination of budesonide (BDS) in EBC samples collected using a homemade setup. EBC is a non-invasive biological sample with possible applications for monitoring drug concentrations. The proposed analytical method is validated according to the FDA guidelines using EBC-spiked samples. Its applicability is tested on EBC samples collected from healthy volunteers receiving a single puff of BDS. Results: The best DLLME conditions involved the use of methanol (1 mL) as a disperser solvent, chloroform (200 μL) as an extraction solvent, and centrifugation rate of 3500 rpm for 5 minutes. The method was validated over a concentration range of 21-210 μg·L-1 in EBC. Inter- and intra-day precisions were less than 10% where the acceptable levels are less than 20%. The validated method was successfully applied for the determination of BDS in EBC samples. Conclusion: The findings of this study indicate that the developed method can be used for the extraction and quantification of BDS in EBC samples using a low cost method.

scholarly journals The grades and freshness assessment of eggs based on density detection using machine vision and weighing sensor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Supakorn Harnsoongnoen ◽  
Nuananong Jaroensuk
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Measuring System ◽  
Coefficient Of Determination ◽  
Water Displacement ◽  
Non Invasive ◽  
Future Potential ◽  
Non Destructive ◽  
Egg Freshness

AbstractThe water displacement and flotation are two of the most accurate and rapid methods for grading and assessing freshness of agricultural products based on density determination. However, these techniques are still not suitable for use in agricultural inspections of products such as eggs that absorb water which can be considered intrusive or destructive and can affect the result of measurements. Here we present a novel proposal for a method of non-destructive, non-invasive, low cost, simple and real—time monitoring of the grading and freshness assessment of eggs based on density detection using machine vision and a weighing sensor. This is the first proposal that divides egg freshness into intervals through density measurements. The machine vision system was developed for the measurement of external physical characteristics (length and breadth) of eggs for evaluating their volume. The weighing system was developed for the measurement of the weight of the egg. Egg weight and volume were used to calculate density for grading and egg freshness assessment. The proposed system could measure the weight, volume and density with an accuracy of 99.88%, 98.26% and 99.02%, respectively. The results showed that the weight and freshness of eggs stored at room temperature decreased with storage time. The relationship between density and percentage of freshness was linear for the all sizes of eggs, the coefficient of determination (R2) of 0.9982, 0.9999, 0.9996, 0.9996 and 0.9994 for classified egg size classified 0, 1, 2, 3 and 4, respectively. This study shows that egg freshness can be determined through density without using water to test for water displacement or egg flotation which has future potential as a measuring system important for the poultry industry.

scholarly journals Compact Miniaturized Bioluminescence Sensor Based on Continuous Air-Segmented Flow for Real-Time Monitoring: Application to Bile Salt Hydrolase (BSH) Activity and ATP Detection in Biological Fluids

Chemosensors ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 122
Author(s):  
Aldo Roda ◽  
Pierpaolo Greco ◽  
Patrizia Simoni ◽  
Valentina Marassi ◽  
Giada Moroni ◽  
...  
Keyword(s):  
Bile Salt ◽  
Light Emission ◽  
Ex Vivo ◽  
Biological Fluids ◽  
Low Cost ◽  
Bile Salt Hydrolase ◽  
Segmented Flow ◽  
Active Substrate ◽  
Flat Spiral ◽  
Bsh Activity

A simple and versatile continuous air-segmented flow sensor using immobilized luciferase was designed as a general miniaturized platform based on sensitive biochemiluminescence detection. The device uses miniaturized microperistaltic pumps to deliver flows and compact sensitive light imaging detectors based on BI-CMOS (smartphone camera) or CCD technology. The low-cost components and power supply make it suitable as out-lab device at point of need to monitor kinetic-related processes or ex vivo dynamic events. A nylon6 flat spiral carrying immobilized luciferase was placed in front of the detector in lensless mode using a fiber optic tapered faceplate. ATP was measured in samples collected by microdialysis from rat brain with detecting levels as low as 0.4 fmoles. The same immobilized luciferase was also used for the evaluation of bile salt hydrolase (BSH) activity in intestinal microbiota. An aminoluciferin was conjugatated with chenodeoxycholic acid forming the amide derivative aLuc-CDCA. The hydrolysis of the aLuc-CDCA probe by BSH releases free uncaged aminoluciferin which is the active substrate for luciferase leading to light emission. This method can detect as low as 0.5 mM of aLuc-CDCA, so it can be used on real faecal human samples to study BSH activity and its modulation by diseases and drugs.

scholarly journals Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML)

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 742
Author(s):  
Rima Hajjo ◽  
Dima A. Sabbah ◽  
Sanaa K. Bardaweel ◽  
Alexander Tropsha
Keyword(s):  
Machine Learning ◽  
High Specificity ◽  
Cancer Biomarkers ◽  
Cancer Prognosis ◽  
Current Status ◽  
Imaging Data ◽  
Non Invasive ◽  
Machine Learning Methods ◽  
Cancer Types ◽  
Magnetic Resonance Imaging Mri

The identification of reliable and non-invasive oncology biomarkers remains a main priority in healthcare. There are only a few biomarkers that have been approved as diagnostic for cancer. The most frequently used cancer biomarkers are derived from either biological materials or imaging data. Most cancer biomarkers suffer from a lack of high specificity. However, the latest advancements in machine learning (ML) and artificial intelligence (AI) have enabled the identification of highly predictive, disease-specific biomarkers. Such biomarkers can be used to diagnose cancer patients, to predict cancer prognosis, or even to predict treatment efficacy. Herein, we provide a summary of the current status of developing and applying Magnetic resonance imaging (MRI) biomarkers in cancer care. We focus on all aspects of MRI biomarkers, starting from MRI data collection, preprocessing and machine learning methods, and ending with summarizing the types of existing biomarkers and their clinical applications in different cancer types.

Micromolding Fabrication of Biocompatible Dry Micro-Pyramid Array Electrodes for Wearable Biopotential Monitoring

2021 ◽  
Author(s):  
Marco Vinicio Alban ◽  
Haechang Lee ◽  
Hanul Moon ◽  
Seunghyup Yoo
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Skin Irritation ◽  
Electrode Impedance ◽  
Non Invasive ◽  
Solution Processes ◽  
Dry Electrodes ◽  
Array Electrode ◽  
Low Cost Manufacturing ◽  
Electromyography Signals

Abstract Thin dry electrodes are promising components in wearable healthcare devices. Assessing the condition of the human body by monitoring biopotentials facilitates the early diagnosis of diseases as well as their prevention, treatment, and therapy. Existing clinical-use electrodes have limited wearable-device usage because they use gels, require preparation steps, and are uncomfortable to wear. While dry electrodes can improve these issues and have demonstrated performance on par with gel-based electrodes, providing advantages in mobile and wearable applications; the materials and fabrication methods used are not yet at the level of disposable gel electrodes for low-cost mass manufacturing and wide adoption. Here, a low-cost manufacturing process for thin dry electrodes with a conductive micro-pyramidal array is presented for large-scale on-skin wearable applications. The electrode is fabricated using micromolding techniques in conjunction with solution processes in order to guarantee ease of fabrication, high device yield, and the possibility of mass production compatible with current semiconductor production processes. Fabricated using a conductive paste and an epoxy resin that are both biocompatible, the developed micro-pyramidal array electrode operates in a conformal, non-invasive manner, with low skin irritation, which ensures improved comfort for brief or extended use. The operation of the developed electrode was examined by analyzing electrode-skin-electrode impedance, electroencephalography, electrocardiography, and electromyography signals and comparing them with those measured simultaneously using gel electrodes.

Non-invasive intelligent monitoring system for fault detection in induction motor based on bio piezoelectric sensor using ANN

2022 ◽  
Author(s):  
Massine GANA ◽  
Hakim ACHOUR ◽  
Kamel BELAID ◽  
Zakia CHELLI ◽  
Mourad LAGHROUCHE ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Induction Motor ◽  
Vibration Analysis ◽  
Low Cost ◽  
Piezoelectric Sensor ◽  
Integrated System ◽  
Easy Access ◽  
Non Invasive ◽  
Artificial Neural

Abstract This paper presents a design of a low-cost integrated system for the preventive detection of unbalance faults in an induction motor. In this regard, two non-invasive measurements have been collected then monitored in real time and transmitted via an ESP32 board. A new bio-flexible piezoelectric sensor developed previously in our laboratory, was used for vibration analysis. Moreover an infrared thermopile was used for non-contact temperature measurement. The data is transmitted via Wi-Fi to a monitoring station that intervenes to detect an anomaly. The diagnosis of the motor condition is realized using an artificial neural network algorithm implemented on the microcontroller. Besides, a Kalman filter is employed to predict the vibrations while eliminating the noise. The combination of vibration analysis, thermal signature analysis and artificial neural network provides a better diagnosis. It ensures efficiency, accuracy, easy access to data and remote control, which significantly reduces human intervention.

scholarly journals Method for auxiliary use of thermography in diagnosing inflammation in the coxofemoral joint in dogs

2018 ◽  
Vol 39 (4) ◽  
pp. 1565
Author(s):  
Fernanda Lúcia Passos Fukahori ◽  
Daniela Maria Bastos de Souza ◽  
Eduardo Alberto Tudury ◽  
George Chaves Jimenez ◽  
José Ferreira da Silva Neto ◽  
...  
Keyword(s):  
Thermal Emission ◽  
Low Cost ◽  
Joint Inflammation ◽  
Domestic Animals ◽  
The Body ◽  
Joint Diseases ◽  
Infrared Images ◽  
Infrared Thermometry ◽  
Non Invasive ◽  
Sensitivity Specificity

Joint diseases are relatively common in domestic animals, such as dogs. The involved inflammation produces thermal emission, which can be imaged using specific sensors that allow capturing of infrared images. Given that there have been few reports on the use of thermography in the diagnosis of inflammation associated with diseases of the hip joint in dogs, we here propose a method for identification of inflammatory foci in dogs by using infrared thermometry. The present study aimed to find non-invasive and low-cost resources that couldfacilitate a clinical diagnosis in cases withinflammation in the coxofemoral joint of dogs.To this end, we developed a system in whichthe Flir Systems TG165 thermograph is coupled to a black PVC cannula with a 30-cm focus-to-animal distance.External effects of the environment on the temperature of the animalswere compared with the body temperature as measured by a conventional thermometer.Thirty-one dogs with and without inflammation in the coxofemoral joint underwent clinical evaluation.We verified that the temperature registered by the thermograph inthe animals with joint inflammation was significantlydifferentfrom that incontrol animals without inflammation, in the lateral projection.The method showed a sensitivity of 80%, specificity of 87.5%, and accuracy of 83.87%. This standardized method of diagnosis of inflammatory foci in the coxofemoral articulation of dogs by way of thermography showed sensitivity, specificity, and satisfactory accuracy.

scholarly journals Aptamers for Detection and Diagnostics (ADD): Can mobile systems linked to biosensors support molecular diagnostics of SARS-CoV-2? Should molecular medicine explore multiple alternatives as adjuvants to or replacement for traditional and non-traditional vaccines?

2021 ◽  
Author(s):  
Shoumen Datta
Keyword(s):  
Data Sharing ◽  
Molecular Diagnostics ◽  
Low Cost ◽  
Mobile App ◽  
Mobile Systems ◽  
Molecular Medicine ◽  
Invasive Monitoring ◽  
Non Invasive ◽  
Secure Information ◽  
Biomedical Device

Proposed SARS-CoV-2 surveillance tool using a mobile app for non-invasive monitoring of humans and animals. <p>Engineering a biomedical device as a low-cost, non-invasive, detection, and diagnostic platform for surveillance of infections in humans, and animals. The system embraces the IoT <i>“digital by design”</i> metaphor by incorporating elements of connectivity, data sharing and (secure) information arbitrage. Using an array of aptamers to bind viral targets may help in detection, diagnostics, and potentially prevention in case of SARS-CoV-2. The ADD tool may become part of a broader platform approach.</p>

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