scholarly journals Printed Electrodes in Microfluidic Arrays for Cancer Biomarker Protein Detection

Biosensors ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 115
Author(s):  
Lasangi Dhanapala ◽  
Colleen E. Krause ◽  
Abby L. Jones ◽  
James F. Rusling
Keyword(s):  
Cancer Progression ◽  
Simultaneous Detection ◽  
Protein Detection ◽  
Medical Diagnostics ◽  
Cancer Diagnostics ◽  
Detection Methods ◽  
Enzyme Linked Immunosorbent Assay ◽  
Grand Challenge ◽  
Patient Records ◽  
Personalized Care

Medical diagnostics is trending towards a more personalized future approach in which multiple tests can be digitized into patient records. In cancer diagnostics, patients can be tested for individual protein and genomic biomarkers that detect cancers at very early stages and also be used to monitor cancer progression or remission during therapy. These data can then be incorporated into patient records that could be easily accessed on a cell phone by a health care professional or the patients themselves on demand. Data on protein biomarkers have a large potential to be measured in point-of-care devices, particularly diagnostic panels that could provide a continually updated, personalized record of a disease like cancer. Electrochemical immunoassays have been popular among protein detection methods due to their inherent high sensitivity and ease of coupling with screen-printed and inkjet-printed electrodes. Integrated chips featuring these kinds of electrodes can be built at low cost and designed for ease of automation. Enzyme-linked immunosorbent assay (ELISA) features are adopted in most of these ultrasensitive detection systems, with microfluidics allowing easy manipulation and good fluid dynamics to deliver reagents and detect the desired proteins. Several of these ultrasensitive systems have detected biomarker panels ranging from four to eight proteins, which in many cases when a specific cancer is suspected may be sufficient. However, a grand challenge lies in engineering microfluidic-printed electrode devices for the simultaneous detection of larger protein panels (e.g., 50–100) that could be used to test for many types of cancers, as well as other diseases for truly personalized care.

scholarly journals A multiepitope fusion protein-based p-ELISA method for diagnosing bovine and goat brucellosis

2021 ◽  
Author(s):  
Dehui Yin ◽  
Qiongqiong Bai ◽  
Xiling Wu ◽  
Han Li ◽  
Jihong Shao ◽  
...  
Keyword(s):  
Fusion Protein ◽  
Negative Predictive Value ◽  
Sensitivity And Specificity ◽  
Predictive Value ◽  
Simultaneous Detection ◽  
Protein Detection ◽  
Economic Losses ◽  
Enzyme Linked Immunosorbent Assay ◽  
Elisa Method ◽  
Roc Curve Analysis

In recent years, the incidence of brucellosis has increased annually, which has caused tremendous economic losses in agriculture and husbandry in various countries. Therefore, developing rapid, sensitive and specific diagnostic techniques for brucellosis has become critical brucellosis research. Bioinformatics technology was used to predict the B cell epitopes of the main antigen proteins of Brucella, and the validity of each epitope was verified by indirect enzyme-linked immunosorbent assay (iELISA). The verified epitopes were connected in series to construct a multiepitope fusion protein, goat, bovine brucellosis sera, and rabbit sera were collected to verify the antigenicity and specificity of this protein. Then, the fusion protein was used as a diagnostic antigen to construct paper-based ELISA (p-ELISA) technology. A total of 22 effective epitopes were predicted, and a fusion protein was successfully constructed, which showed good antigenicity and specificity. The constructed p-ELISA method was used for the simultaneous detection of bovine and goat brucellosis. ROC curve analysis showed that the sensitivity and specificity of protein detection in goat serum were 98.85% and 98.51%, respectively. The positive and the negative predictive value was 99.29% and 98.15%, respectively. When assessing bovine serum, the sensitivity and specificity were 97.85% and 96.61%, respectively. The positive and the negative predictive value was 98.28% and 97.33%, respectively. This study combined bioinformatics, fusion protein development and p-ELISA technologies to establish a sensitive and specific rapid diagnosis technology for brucellosis that can be used to assess the serum of bovine, goats and other livestock.

Nanotextured Electrical Immunoassays for Ultrasensitive Protein Detection

2011 ◽  
Vol 1346 ◽  
Author(s):  
Timothy O. Mertz ◽  
Krishna Vattipalli ◽  
Tom Barrett ◽  
John Carruthers ◽  
Shalini Prasad
Keyword(s):  
Protein Detection ◽  
Cost Effective ◽  
Disease Diagnosis ◽  
Detection Methods ◽  
Enzyme Linked Immunosorbent Assay ◽  
Detection Accuracy ◽  
Label Free ◽  
Electrode Arrays ◽  
Protein Biomarkers ◽  
Hybrid Sensors

ABSTRACTThis paper describes the development of nanomonitors, which are electrical immunoassays for detection of multiple protein biomarkers. These devices are hybrid sensors with micro-fabricated electrode arrays on a silicon substrate, and integrated nanoporous alumina membranes to provide protein confinement and signal amplification. The disease biomarkers C-reactive protein and Myeloperoxidase have been detected by the nanomonitors in ultra-low concentrations. Proteins were detected in pure samples, human serum, and patient blood samples. The detection accuracy and sensitivity of the nanomonitors in patient samples was comparable to the Enzyme Linked Immunosorbent Assay (ELISA) method of protein detection. Nanomonitors provide the additional benefits of being rapid, label-free, sensitive, and cost effective, providing improvements over traditional protein detection methods, and having potential applications in disease diagnosis.

scholarly journals Enzyme-Antibody-Modified Gold Nanoparticle Probes for the Ultrasensitive Detection of Nucleocapsid Protein in SFTSV

2020 ◽  
Vol 17 (12) ◽  
pp. 4427
Author(s):  
Yuqin Duan ◽  
Wei Wu ◽  
Qiuzi Zhao ◽  
Sihua Liu ◽  
Hongyun Liu ◽  
...  
Keyword(s):  
Rural Areas ◽  
Nucleocapsid Protein ◽  
Disease Risk ◽  
Quantitative Polymerase Chain Reaction ◽  
Protein Detection ◽  
Central China ◽  
Detection Methods ◽  
Enzyme Linked Immunosorbent Assay ◽  
Ultrasensitive Detection ◽  
Optical Sensitivity

As humans and climate change continue to alter the landscape, novel disease risk scenarios have emerged. Sever fever with thrombocytopenia syndrome (SFTS), an emerging tick-borne infectious disease first discovered in rural areas of central China in 2009, is caused by a novel bunyavirus (SFTSV). The potential for SFTS to spread to other countries in combination with its high fatality rate, possible human-to-human transmission, and extensive prevalence among residents and domesticated animals in endemic regions make the disease a severe threat to public health. Because of the lack of preventive vaccines or useful antiviral drugs, diagnosis of SFTS is the key to prevention and control of the SFTSV infection. The development of serological detection methods will greatly improve our understanding of SFTSV ecology and host tropism. We describe a highly sensitive protein detection method based on gold nanoparticles (AuNPs) and enzyme-linked immunosorbent assay (ELISA)—AuNP-based ELISA. The optical sensitivity enhancement of this method is due to the high loading efficiency of AuNPs to McAb. This enhances the concentration of the HRP enzyme in each immune sandwich structure. The detection limit of this method to the nucleocapsid protein (NP) of SFTSV was 0.9 pg mL−1 with good specificity and reproducibility. The sensitivity of AuNP-based ELISA was higher than that of traditional ELISA and was comparable to real-time quantitative polymerase chain reaction (qRT-PCR). The probes are stable for 120 days at 4 °C. This can be applied to diagnosis and hopefully can be developed into a commercial ELISA kit. The ultrasensitive detection of SFTSV will increase our understanding of the distribution and spread of SFTSV, thus helping to monitor the changes in tick-borne pathogen SFTSV risk in the environment.

scholarly journals Circ-ACTR2 aggravates the high glucose-induced cell dysfunction of human renal mesangial cells through mediating the miR-205-5p/HMGA2 axis in diabetic nephropathy

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jie Yun ◽  
Jinyu Ren ◽  
Yufei Liu ◽  
Lijuan Dai ◽  
Liqun Song ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Diabetic Nephropathy ◽  
High Glucose ◽  
Cell Injury ◽  
Mesangial Cells ◽  
Protein Detection ◽  
Cell Counting ◽  
Luciferase Reporter ◽  
Enzyme Linked Immunosorbent Assay ◽  
Cell Dysfunction

Abstract Background Circular RNAs (circRNAs) have been considered as pivotal biomarkers in Diabetic nephropathy (DN). CircRNA ARP2 actin-related protein 2 homolog (circ-ACTR2) could promote the HG-induced cell injury in DN. However, how circ-ACTR2 acts in DN is still unclear. This study aimed to explore the molecular mechanism of circ-ACTR2 in DN progression, intending to provide support for the diagnostic and therapeutic potentials of circ-ACTR2 in DN. Methods RNA expression analysis was conducted by the quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Cell growth was measured via Cell Counting Kit-8 and EdU assays. Inflammatory response was assessed by Enzyme-linked immunosorbent assay. The protein detection was performed via western blot. Oxidative stress was evaluated by the commercial kits. The molecular interaction was affirmed through dual-luciferase reporter and RNA immunoprecipitation assays. Results Circ-ACTR2 level was upregulated in DN samples and high glucose (HG)-treated human renal mesangial cells (HRMCs). Silencing the circ-ACTR2 expression partly abolished the HG-induced cell proliferation, inflammation and extracellular matrix accumulation and oxidative stress in HRMCs. Circ-ACTR2 was confirmed as a sponge for miR-205-5p. Circ-ACTR2 regulated the effects of HG on HRMCs by targeting miR-205-5p. MiR-205-5p directly targeted high-mobility group AT-hook 2 (HMGA2), and HMGA2 downregulation also protected against cell injury in HG-treated HRMCs. HG-mediated cell dysfunction was repressed by miR-205-5p/HMGA2 axis. Moreover, circ-ACTR2 increased the expression of HMGA2 through the sponge effect on miR-205-5p in HG-treated HRMCs. Conclusion All data have manifested that circ-ACTR2 contributed to the HG-induced DN progression in HRMCs by the mediation of miR-205-5p/HMGA2 axis.

Research activities for the monitoring of genetically modified organisms in Japan

2010 ◽  
Vol 82 (1) ◽  
pp. 139-147
Author(s):  
Kazumi Kitta
Keyword(s):  
Quality Control ◽  
Genetically Modified Organisms ◽  
Genetically Modified ◽  
Screening Method ◽  
Simultaneous Detection ◽  
Cauliflower Mosaic Virus ◽  
Detection Methods ◽  
Internal Quality ◽  
Research Activities ◽  
Labeling System

The Japanese government introduced a labeling system for genetically modified (GM) foods. To ensure the authenticity of the labeling system, we have developed and validated detection methods for newly approved GM events. One was the development of quantitative analytical methods utilizing plasmid DNAs as calibrators, which enabled us to obtain an unlimited supply of calibrators of consistent quality and also to obtain a stable standard curve to quantify GM organisms (GMOs) in samples. The significance of quality control has been recognized among relevant stakeholders, and in response we launched a project to distribute certified reference materials (CRMs) to the users of our methods for the purpose of internal quality control. In addition to these activities, we have developed time- and cost-effective detection methods, such as a new screening method to simultaneously detect the sequence of Cauliflower mosaic virus 35S promoter (p35S) and the construct-specific sequence of GA21 event utilizing multiplex real-time polymerase chain reaction (PCR). We also developed a qualitative nonaplex PCR detection method, which allows the simultaneous detection of eight events of GM maize lines. Because the influx of any unapproved and unknown GMOs into the Japanese market is not permitted, we continue to explore this issue.

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.

scholarly journals Monoclonal Antibody-Based Antigen Capture Enzyme-Linked Immunosorbent Assay Reveals High Sensitivity of the Nucleocapsid Protein in Acute-Phase Sera of Severe Acute Respiratory Syndrome Patients

2005 ◽  
Vol 12 (1) ◽  
pp. 135-140 ◽  
Author(s):  
Biao Di ◽  
Wei Hao ◽  
Yang Gao ◽  
Ming Wang ◽  
Ya-di Wang ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Acute Phase ◽  
Detection Rate ◽  
Neutralization Test ◽  
Protein Detection ◽  
Enzyme Linked Immunosorbent Assay ◽  
Serum Samples ◽  
N Protein ◽  
Antigen Capture ◽  
Healthy Donors

ABSTRACT Accurate and timely diagnosis of severe acute respiratory syndrome coronavirus (SARS-CoV) infection is a critical step in preventing another global outbreak. In this study, 829 serum specimens were collected from 643 patients initially reported to be infected with SARS-CoV. The sera were tested for the N protein of SARS-CoV by using an antigen capture enzyme-linked immunosorbent assay (ELISA) based on monoclonal antibodies against the N protein of SARS-CoV and compared to 197 control serum samples from healthy donors and non-SARS febrile patients. The results of the N protein detection analysis were directly related to the serological analysis data. From 27 SARS patients who tested positive with the neutralization test, 100% of the 24 sera collected from 1 to 10 days after the onset of symptoms were positive for the N protein. N protein was not detected beyond day 11 in this group. The positive rates of N protein for sera collected at 1 to 5, 6 to 10, 11 to 15, and 16 to 20 days after the onset of symptoms for 414 samples from 298 serologically confirmed patients were 92.9, 69.8, 36.4, and 21.1%, respectively. For 294 sera from 248 serological test-negative patients, the rates were 25.6, 16.7, 9.3, and 0%, respectively. The N protein was not detected in 66 patients with cases of what was initially suspected to be SARS but serologically proven to be negative for SARS and in 197 serum samples from healthy donors and non-SARS febrile patients. The specificity of the assay was 100%. Furthermore, of 16 sera collected from four patients during the SARS recurrence in Guangzhou, 5 sera collected from 7 to 9 days after the onset of symptoms were positive for the N protein. N protein detection exhibited a high positive rate, 96 to 100%, between day 3 and day 5 after the onset of symptoms for 27 neutralization test-positive SARS patients and 298 serologically confirmed patients. The N protein detection rate continually decreased beginning with day 10, and N protein was not detected beyond day 19 after the onset of symptoms. In conclusion, an antigen capture ELISA reveals a high N protein detection rate in acute-phase sera of patients with SARS, which makes it useful for early diagnosis of SARS.

scholarly journals Detection of Breast Cancer using AI Techniques – A Survey

2019 ◽  
Vol 7 (7) ◽  
pp. 08-12
Author(s):  
Riju Bhattacharya ◽  
Diksha Gupta ◽  
Divyatara Rathod
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Diagnostics ◽  
Detection Methods ◽  
Health Issues ◽  
Process Data ◽  
Mortality And Morbidity ◽  
Medical Progress ◽  
Glass Slides ◽  
Abnormal Cells

Cancer refers to any one of a large number of diseases characterized by the development of abnormal cells that divide uncontrollably and have the ability to infiltrate and destroy normal body tissue.Without treatment, it can cause serious health issues andresult in a loss of life. Breast cancer is the most common cancer among women around the world. Despite enormous medical progress, breast cancer has still remained the second leading cause of death worldwide. Early detection of cancer may reduce mortality and morbidity. This paper presents a review of the detection methods for cancer through Artificial Intelligence (AI) in different ways. Previously Microscopic reviews of tissues on glass slides are used for cancer diagnostics to improve diagnostic accuracy. We can use different techniques such as digital imaging and artificial intelligence algorithm. Cancer care is also advancing thanks to AI’s ability to collect and process data. Due to the nature of processing this information, the task is often a time-consuming and tedious job for doctors. This process may be made much easier, quicker and efficient through the advancement as well as by using modified technologies.

scholarly journals Molecular Profiles of Matched Primary and Metastatic Tumor Samples Support a Linear Evolutionary Model of Breast Cancer

2019 ◽  
Author(s):  
Runpu Chen ◽  
Steve Goodison ◽  
Yijun Sun
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Evolutionary Model ◽  
Metastatic Tumor ◽  
Cancer Diagnostics ◽  
Tumor Evolution ◽  
Paired Data ◽  
Cancer Subtypes ◽  
Cancer Data ◽  
Progression Model

AbstractThe interpretation of accumulating genomic data with respect to tumor evolution and cancer progression requires integrated models. We developed a computational approach that enables the construction of disease progression models using static sample data. Application to breast cancer data revealed a linear, branching evolutionary model with two distinct trajectories for malignant progression. Here, we used the progression model as a foundation to investigate the relationships between matched primary and metastasis breast tumor samples. Mapping paired data onto the model confirmed that molecular breast cancer subtypes can shift during progression, and supported directional tumor evolution through luminal subtypes to increasingly malignant states. Cancer progression modeling through the analysis of available static samples represents a promising breakthrough. Further refinement of a roadmap of breast cancer progression will facilitate the development of improved cancer diagnostics, prognostics and targeted therapeutics.

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