scholarly journals The Advent of Salivary Breast Cancer Biomarker Detection Using Affinity Sensors

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2373 ◽  
Author(s):  
Imad Abrao Nemeir ◽  
Joseph Saab ◽  
Walid Hleihel ◽  
Abdelhamid Errachid ◽  
Nicole Jafferzic-Renault ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Low Cost ◽  
Current Trend ◽  
High Sensitivity ◽  
Breast Cancer Diagnosis ◽  
Current Status ◽  
Attractive Alternative ◽  
Early Screening ◽  
Screening Programs ◽  
Sensitivity And Selectivity

Breast Cancer is one of the world’s most notorious diseases affecting two million women in 2018 worldwide. It is a highly heterogeneous disease, making it difficult to treat. However, its linear progression makes it a candidate for early screening programs, and the earlier its detection the higher the chance of recovery. However, one key hurdle for breast cancer screening is the fact that most screening techniques are expensive, time-consuming, and cumbersome, making them impractical for use in several parts of the world. One current trend in breast cancer detection has pointed to a possible solution, the use of salivary breast cancer biomarkers. Saliva is an attractive medium for diagnosis because it is readily available in large quantities, easy to obtain at low cost, and contains all the biomarkers present in blood, albeit in lower quantities. Affinity sensors are devices that detect molecules through their interactions with biological recognition molecules. Their low cost, high sensitivity, and selectivity, as well as rapid detection time make them an attractive alternative to traditional means of detection. In this review article, we discuss the current status of breast cancer diagnosis, its salivary biomarkers, as well as the current trends in the development of affinity sensors for their detection.

Modern nanobiotechnologies for efficient detection and remediation of mercury

Sensor Review ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mulayam Singh Gaur ◽  
Rajni Yadav ◽  
Mamta Kushwah ◽  
Anna Nikolaevna Berlina
Keyword(s):  
Heavy Metals ◽  
Water Samples ◽  
Low Cost ◽  
High Sensitivity ◽  
Environmental Water ◽  
Mercury Ions ◽  
Content Type ◽  
Efficient Detection ◽  
Sensitivity And Selectivity ◽  
Selection Of

Purpose This information will be useful in the selection of materials and technology for the detection and removal of mercury ions at a low cost and with high sensitivity and selectivity. The purpose of this study is to provide the useful information for selection of materials and technology to detect and remove the mercury ions from water with high sensitivity and selectivity. The purpose of this study is to provide the useful information for selection of materials and technology to detect and remove the mercury ions from water with high sensitivity and selectivity. Design/methodology/approach Different nano- and bio-materials allowed for the development of a variety of biosensors – colorimetric, chemiluminescent, electrochemical, whole-cell and aptasensors – are described. The materials used for their development also make it possible to use them in removing heavy metals, which are toxic contaminants, from environmental water samples. Findings This review focuses on different technologies, tools and materials for mercury (heavy metals) detection and remediation to environmental samples. Originality/value This review gives up-to-date and systemic information on modern nanotechnology methods for heavy metal detection. Different recognition molecules and nanomaterials have been discussed for remediation to water samples. The present review may provide valuable information to researchers regarding novel mercury ions detection sensors and encourage them for further research/development.

scholarly journals Identification of differentially methylated genes as diagnostic and prognostic biomarkers of breast cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Xiao-hong Mao ◽  
Qiang Ye ◽  
Guo-bing Zhang ◽  
Jin-ying Jiang ◽  
Hong-ying Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
High Sensitivity ◽  
Breast Cancer Diagnosis ◽  
Diagnostic Value ◽  
Methylation Pattern ◽  
Clinical Value ◽  
Roc Curve Analysis ◽  
Differentially Methylated Genes ◽  
Sensitivity Specificity

Abstract Background Aberrant DNA methylation is significantly associated with breast cancer. Methods In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis. Results In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994–1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976–1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival. Conclusions Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer.

Development of a high-performance, blood-based screening diagnostic to detect early-stage breast cancer.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e22083-e22083
Author(s):  
Joseph Wagner ◽  
Karen Chapman ◽  
Maria Prendes-Garcia ◽  
Markus Lacher ◽  
Jennifer Kidd ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Performance ◽  
Early Stage ◽  
Low Cost ◽  
High Sensitivity ◽  
Screening Mammography ◽  
Early Stage Breast Cancer ◽  
Breast Cancer Patients ◽  
Elevated Expression ◽  
Sera Samples

e22083 Background: Limitations of current screening mammography, particularly in younger women, demonstrate the need for an alternative breast cancer screening strategy. A non-invasive, easily interpreted and low cost test should address this need. Methods: Gene expression microarray analysis was carried out on 128 individual tumor samples representing over 20 tumor types, 86 samples representing 31 diverse normal tissue types, 68 tumor cell lines and 97 diverse normal primary cell cultures. Genes were ranked for elevated expression in either: i) a large number and variety of tumors relative to normal tissues, or ii) in breast tumors. Elevated expression was verified for a subset of genes using qPCR in a set of independent RNA samples. Proteins coded by genes elevated in breast cancer samples were analyzed in a retrospective training set of breast cancer patient sera samples with cancer-free patient and benign pathology controls using ELISA or bead-based detection assay. Results: Based on availability of suitable reagents, 25 candidate biomarkers were assessed in patient sera samples (31-227 patient samples per biomarker) using ELISA or bead-based assays. Individually, the performance of individual markers varied (ROC AUC, 0.51 - 0.88); however, when expression levels of the best performing markers were combined, the multiplex test demonstrated high-sensitivity (>80%) and specificity (>90%) in identifying early-stage breast cancer patients. Conclusions: A multiplex, proteomic-based approach may provide for a high-performance, blood-based screening diagnostic for breast cancer.

scholarly journals Optical Imaging in Breast Cancer Diagnosis: The Next Evolution

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Michel Herranz ◽  
Alvaro Ruibal
Keyword(s):  
Breast Cancer ◽  
Optical Imaging ◽  
Breast Imaging ◽  
Near Infrared ◽  
High Sensitivity ◽  
Breast Cancer Diagnosis ◽  
Diagnostic Methods ◽  
Infrared Light ◽  
Western World ◽  
Positron Emission

Breast cancer is one of the most common cancers among the population of the Western world. Diagnostic methods include mammography, ultrasound, and magnetic resonance; meanwhile, nuclear medicine techniques have a secondary role, being useful in regional assessment and therapy followup. Optical imaging is a very promising imaging technique that uses near-infrared light to assess optical properties of tissues and is expected to play an important role in breast cancer detection. Optical breast imaging can be performed by intrinsic breast tissue contrast alone (hemoglobin, water, and lipid content) or with the use of exogenous fluorescent probes that target specific molecules for breast cancer. Major advantages of optical imaging are that it does not use any radioactive components, very high sensitivity, relatively inexpensive, easily accessible, and the potential to be combined in a multimodal approach with other technologies such as mammography, ultrasound, MRI, and positron emission tomography. Moreover, optical imaging agents could, potentially, be used as “theranostics,” combining the process of diagnosis and therapy.

Quartz crystal microbalance based biosensors for detecting highly metastatic breast cancer cells via their transferrin receptors

2016 ◽  
Vol 8 (1) ◽  
pp. 153-161 ◽  
Author(s):  
Seda Atay ◽  
Kevser Pişkin ◽  
Fatma Yılmaz ◽  
Canan Çakır ◽  
Handan Yavuz ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Quartz Crystal ◽  
Metastatic Breast ◽  
High Sensitivity ◽  
Breast Cancer Diagnosis ◽  
Metastatic Potential ◽  
Efficient System ◽  
Ligand Interactions

The high sensitivity of the QCM sensor is combined with selectivity of receptor–ligand interactions to construct a biosensor which would discriminate breast cancer cells with high metastatic power from those of low or no metastatic potential to develop a simple, fast and efficient system to be used in breast cancer diagnosis.

scholarly journals An Effective Optical Dual Gas Sensor for Simultaneous Detection of Oxygen and Ammonia

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5124 ◽  
Author(s):  
Sajal Biring ◽  
Annada Sankar Sadhu ◽  
Moumita Deb
Keyword(s):  
Gas Sensor ◽  
Fluorescent Dyes ◽  
Low Cost ◽  
Simultaneous Detection ◽  
High Sensitivity ◽  
Eosin Y ◽  
Practical Applications ◽  
Sensing Material ◽  
Dual Sensor ◽  
Sensitivity And Selectivity

The development of a simple, low-cost sensor for the effective sensing of multiple gases in industrial or residential zones has been in high demand in recent days. In this article, we have proposed an optical sensor for the dual sensing of oxygen (O2) and ammonia (NH3) gases, which consists of oxygen and ammonia-sensitive fluorescent dyes coated individually on both sides of a glass substrate. An ethyl cellulose (EC) matrix doped with platinum (II) meso-tetrakis (pentafluorophenyl) porphyrin (PtTFPP) serves as the oxygen-sensing material, whereas the NH3-sensing material includes an eosin Y fluorescent indicator immobilized within a cellulose acetate (CA) matrix. Both the oxygen and ammonia-sensitive materials were excited by the same LED light source with a 405 nm peak wavelength, while the corresponding emissions were detected separately for the selective sensing of the gases under study. The dual gas sensor exhibits maximum sensitivities of around 60 and 20 for oxygen and ammonia gases, respectively. The high sensitivity and selectivity of the proposed optical dual sensor suggests the feasibility of the simultaneous sensing of oxygen and ammonia for practical applications.

The current status of positron emission mammography in breast cancer diagnosis

Breast Cancer ◽  
2012 ◽  
Vol 20 (2) ◽  
pp. 123-130 ◽  
Author(s):  
Vasileios Kalles ◽  
George C. Zografos ◽  
Xeni Provatopoulou ◽  
Dimitra Koulocheri ◽  
Antonia Gounaris
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Current Status ◽  
Positron Emission Mammography ◽  
Positron Emission

scholarly journals DeCompress: tissue compartment deconvolution of targeted mRNA expression panels using compressed sensing

2020 ◽  
Author(s):  
Arjun Bhattacharya ◽  
Alina M. Hamilton ◽  
Melissa A. Troester ◽  
Michael I. Love
Keyword(s):  
Breast Cancer ◽  
Compressed Sensing ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Low Cost ◽  
High Sensitivity ◽  
Microarray Dataset ◽  
Clinical Settings ◽  
Cell Type ◽  
Specific Expression

ABSTRACTTargeted mRNA expression panels, measuring up to 800 genes, are used in academic and clinical settings due to low cost and high sensitivity for archived samples. Most samples assayed on targeted panels originate from bulk tissue comprised of many cell types, and cell-type heterogeneity confounds biological signals. Reference-free methods are used when cell-type-specific expression references are unavailable, but limited feature spaces render implementation challenging in targeted panels. Here, we present DeCompress, a semi-reference-free deconvolution method for targeted panels. DeCompress leverages a reference RNA-seq or microarray dataset from similar tissue to expand the feature space of targeted panels using compressed sensing. Ensemble reference-free deconvolution is performed on this artificially expanded dataset to estimate cell-type proportions and gene signatures. In simulated mixtures, four public cell line mixtures, and a targeted panel (1199 samples; 406 genes) from the Carolina Breast Cancer Study, DeCompress recapitulates cell-type proportions with less error than reference-free methods and finds biologically relevant compartments. We integrate compartment estimates into cis-eQTL mapping in breast cancer, identifying a tumor-specific cis-eQTL for CCR3 (C-C Motif Chemokine Receptor 3) at a risk locus. DeCompress improves upon reference-free methods without requiring expression profiles from pure cell populations, with applications in genomic analyses and clinical settings.

scholarly journals Smartphone-Based Microfluidic Colorimetric Sensor for Gaseous Formaldehyde Determination with High Sensitivity and Selectivity

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3141 ◽  
Author(s):  
Xiao-Liang Guo ◽  
Yan Chen ◽  
Hong-Lan Jiang ◽  
Xian-Bo Qiu ◽  
Du-Li Yu
Keyword(s):  
Microfluidic Chip ◽  
Limit Of Detection ◽  
Low Cost ◽  
Sick Building Syndrome ◽  
High Sensitivity ◽  
Colorimetric Sensor ◽  
World Health ◽  
Formaldehyde Determination ◽  
Sensitivity And Selectivity ◽  
Gaseous Formaldehyde

Formaldehyde is one of the most dangerous air pollutants, which can cause sick building syndrome. Thus, it is very crucial to precisely determine formaldehyde with a low cost and simple operation. In this paper, a smartphone-based microfluidic colorimetric sensor is devised for gaseous formaldehyde determination with high sensitivity and selectivity. Specifically, a novel microfluidic chip is proposed based on the 4-aminohydrazine-5-mercapto-1,2,4-triazole (AHMT) method to determine formaldehyde; the chip consists of two reagent reservoirs, one reaction reservoir and a mixing column. In this design to prevent the fluid from flowing out while letting the gas molecule in, a hydrophobic porous poly tetra fluoroethylene (PTFE) membrane is put on the top of the reaction reservoir. Using the microfluidic chip sensor, a smartphone-based formaldehyde determination system is developed, which makes the measuring process automated and simple. As per the experiment results, the limit-of-detection (LOD) of the system is as low as 0.01 ppm, which is much lower than the maximum exposure concentration (0.08 ppm) recommended by the World Health Organization (WHO). Moreover, the sensor is hardly affected by acetaldehyde, volatile organic compounds (VOCs) or acidic-alkaline, which shows great selectivity. Finally, the performance of the proposed sensor is verified by using it for the determination of formaldehyde in a newly decorated house.

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