Point-of-care testing for streptomycin based on aptamer recognizing and digital image colorimetry by smartphone

Lin, Bixia; Yu, Ying; Cao, Ya; Guo, Minzhe; Zhu, Dongmei; Dai, Jiaxing; Zheng, Minshi

doi:10.1016/j.bios.2017.09.028

Cited by 137 publications

(43 citation statements)

References 36 publications

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“…20 O modelo RGB é o modelo mais utilizado em imagens digitais, neste modelo as cores são compostas por combinações lineares das cores primárias, vermelho (Red), verde (Green) e azul (Blue), portanto, neste sistema toda cor pode ser definida como um vetor com três coordenadas (R, G, B) e os valores podem variar de 0 a 255, ou seja, são possíveis mais de 16,77 milhões (255 3 ) de combinações diferentes de cores. 20 Imagens digitais obtidas com scanners e smartphones são utilizadas em substituição a absorbância mensurada com um espectrofotômetro, 19 como, por exemplo, determinar a concentração de vitamina C em suplementos alimentares, 10 determinação da constante de equilíbrio, 13 determinação da concentração de proteínas, 15 atividade da amilase, 16 concentração de cobre na cachaça, 21 diagnostico de dengue, 22 classificação de águas minerais, 23 quantificação de manganês em pilhas, 24 quantificação de fosfato em refrigerante, 25 dureza e alcalinidade da água, 26 acidez de vinho tinto, 27 determinação da concentração de ferro em água e em alimentos, 28,29 quantificação de estreptomicina em medicamentos, 30 determinação da percentagem etanol em bebidas, 31 quantificação do corante (sunset yelloow) em alimentos, 32 quantificação de ácido salicílico 33 e adulteração do álcool combustível. 34…”

Section: Palavras-chaveunclassified

Equilibrium Constant Determination Using Digital Images

Ledesma¹,

Gelinski²,

Borges³

2019

Rev. Virtual Quim

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Herein, analytical chemistry students determine the [Fe(H2O)6] 3+ + CSN- [Fe(H2O)5(SCN)] 2+ + H2O reaction equilibrium constants. [Fe(H2O)6] 3+ has a slight yellow color, CSNis colorless and [Fe(H2O)5(SCN)] 2+ are deep blood-red (λmax = 447 nm). Thus, the reaction is easily observed. Equilibrium constants were calculated using eight [Fe(H2O)6] 3+ (0.002 mol L-1) and SCN-(0.002 mol L-1) mixtures, [Fe(H2O)5(SCN)] 2+ concentrations were determinate using absorbance measured at 447 nm and RGB values extracted from digital images, which were obtained with a flatbed scanner. The paired t test showed that equilibrium constants determine using absorbance and digital images were statistically equivalent, at 95 % confidence interval. Additionally, students evaluated how well a calibration curve follows a straight-line using correlation coefficient, analysis of variance (ANOVA) and residual plots. A Microsoft Excel spreadsheet was provided in Google Drive, this Table organize data, provides calibration plots and determine equilibrium constants in the eight Fe 3+ and SCNmixtures. This laboratory practice was carried out with 14 chemical engineering students working in pairs in Universidade Regional de Blumenau, it takes over 120-150 minutes. Extraction of RGB values from digital images and data analysis was carried out in a separate 50 minutes class.

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Section: Palavras-chaveunclassified

Equilibrium Constant Determination Using Digital Images

Ledesma¹,

Gelinski²,

Borges³

2019

Rev. Virtual Quim

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“…These formal studies created low‐cost on‐site ubiquitous health control methods. However, like other smartphone‐based studies (Li et al, ; Lin et al, ), with the help of external intelligent devices, the proposed barcode smart chip is more sensitive in detection and more intelligent in data‐analysis compared with traditional methods.…”

Section: Resultsmentioning

confidence: 98%

A novel on‐chip solution enabling rapid analysis of melamine and chloramphenicol in milk by smartphones

Yang

Xie

Pan

et al. 2018

J Food Process Engineering

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Ubiquitous food security control is desirable. However, the analysis methods, such as those for milk, are highly based on manual analysis, leading to low efficiency. Thus, we report a multilayer paper-based microfluidic chip transforming chromatic readout to electric signals. First, colloidal gold immunochromatographic assays (GICA) are used to achieve the colorimetric occurrence.Secondly, the test (T) lines and control (C) lines are patterned to encode different EAN-8 barcode. Furthermore, accurate scanning is accomplished by the automatic threshold segmentation.These technologies make the digital determination of melamine (MEL) and chloramphenicol (CAP) by phone readily accessible. Results indicate that the accurate machine-scanning can be assured when MEL and CAP is above 30 ng/mL and 6 ng/mL in milk respectively. The detection time is under 8 min, and the stable storage life is over 90 days. Therefore, this simple chip allows rapid, machine-readable, electric-recordable diagnostic directly from chromatic assays with satisfying stability, specificity and accuracy. Practical applicationsThis article illustrates a method used to determine the concentration of melamine and chloramphenicol in milk. When melamine and chloramphenicol is above 30 and 6 ng/ml in milk, the produced EAN-8 barcode can be recognized with high accurate level, compared with international standards, the results are acceptable and sensitive. This method is highly intellectual and environmentally friendly, with the disposable materials and instant smartphone-readable EAN-8 results patterns. This article demonstrates a multilayer paper chip based on EAN-8 encoding rules, colloidal gold nanoparticles, and immunochromatographic assays. The EAN-8 format assay is achieved by color-development occurrence of colloidal GICA in different encoding areas of EAN-8 code, and the analysis device, namely smartphone, is accessible by almost every individual. Therefore, this chip can pave a potential way for massive health control and digital automated analysis for daily life and industrial manufacture.

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“…Digital image colourimetry (DIC) has attracted much attention as an advanced colourimetric method, including the image acquisition tool to capture the image and the image processing software to analyse the colour of the obtained image. [14] The smartphone has become the most widely used image-acquisition and processing tool with advantages of portability, multiple data transmission function, and storage capacity. [15] Thus, the DIC based on a smartphone reduces the influence of the naked eye and improves the accuracy of the detection results.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Detection of Nitrite in Food Samples Based on Digital Image Colourimetry by Smartphone

Jing

Bai

et al. 2020

ChemistrySelect

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A novel colourimetric method for the detection of nitrite in food samples using digital image colourimetry (DIC) by smartphone is developed. Nitrite directly oxidise 3,3′,5,5′‐tetramethylbenzidine (TMB) to form a yellow TMB diimine (oxTMB). A smartphone was used to capture the image of an inherent colour variation and analyse the image with the RGB (red, green, and blue) model, achieving the quantitative detection of nitrite. Linear response for the detection of nitrite was obtained from 10 μmol L−1 to 440 μmol L−1 and the limit of quantification was 2.34 μmol L−1. The applicability of the method was confirmed by the detection of nitrite in cabbage, pickle, and ham. The recovery was varied in the range from 96.2 % to 108.2 % with a relative standard deviation of less than 5.0 %. The simple, sensitive, and inexpensive method was an alternative for the detection of nitrite in food samples.

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Point-of-care testing for streptomycin based on aptamer recognizing and digital image colorimetry by smartphone

Cited by 137 publications

References 36 publications

Equilibrium Constant Determination Using Digital Images

Equilibrium Constant Determination Using Digital Images

A novel on‐chip solution enabling rapid analysis of melamine and chloramphenicol in milk by smartphones

Quantitative Detection of Nitrite in Food Samples Based on Digital Image Colourimetry by Smartphone

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