Academic Journal

Smartphone-based colorimetric detection of urease activity in dental plaque for point-of-care screening of Helicobacter pylori infection.

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Τίτλος: Smartphone-based colorimetric detection of urease activity in dental plaque for point-of-care screening of Helicobacter pylori infection.
Συγγραφείς: Wang, Yuhan, Zhang, Ping, Zhou, Chuxian, Zheng, Zicong, Quan, Qiang, He, Guangbo, Zhai, Hening, Song, Qifang, Zhang, Xiaoli, Li, Heng, Peng, Lanhuan, Liao, Yuqin, Fang, Wei, Li, Minmin, Liang, Jiajie, Tang, Yong
Πηγή: Microchimica Acta; Oct2025, Vol. 192 Issue 10, p1-10, 10p
Θεματικοί όροι: Helicobacter pylori, Point-of-care testing, Microsensors, Colorimetric analysis, Enzymology, Dental plaque, Smartphones, Public health
Περίληψη: Helicobacter pylori (H. pylori) is a major pathogen associated with gastric ulcers and gastric cancer, infecting approximately half of the global population. Therefore, developing sensitive, rapid, and cost-effective detection methods for H. pylori is critical for public health. We developed an innovative microscale colorimetric microsensor integrated with smartphone ambient-light sensors for portable, on-site quantification of H. pylori-associated urease activity in dental plaque. This low-cost device (< $ 5 fabrication) employs 3D-printed components and a custom app to measure transmittance changes from urease-catalyzed urea hydrolysis with phenol red, achieving a robust correlation with commercial microplate reader absorbance (R2 = 0.9989). The system demonstrates exceptional Analytical sensitivity, with limits of detection of 9.75 U/L for urease And 1.709 × 103 CFU/mL for H. pylori, alongside high reproducibility (CV < 10%) And stability over 14 days. When applied to the on-site detection of dental plaque among volunteers, the smartphone-based colorimetric microsensor exhibited detection results that were highly aligned with H. pylori infections confirmed by the urea breath test. It outperformed commercial test strips And achieved 100% sensitivity, 95.5% specificity, And 97.1% accuracy. This miniaturized, smartphone-based platform offers a promising solution for home self-testing and demonstrates significant potential for enhancing H. pylori preliminary screening at the community level. [ABSTRACT FROM AUTHOR]
Copyright of Microchimica Acta is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Complementary Index
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  – Url: https://dx.doi.org/doi:10.1007/s00604-025-07496-0
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  Data: Smartphone-based colorimetric detection of urease activity in dental plaque for point-of-care screening of Helicobacter pylori infection.
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  Data: Microchimica Acta; Oct2025, Vol. 192 Issue 10, p1-10, 10p
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  Data: &lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Helicobacter+pylori%22&quot;&gt;Helicobacter pylori&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Point-of-care+testing%22&quot;&gt;Point-of-care testing&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Microsensors%22&quot;&gt;Microsensors&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Colorimetric+analysis%22&quot;&gt;Colorimetric analysis&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Enzymology%22&quot;&gt;Enzymology&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Dental+plaque%22&quot;&gt;Dental plaque&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Smartphones%22&quot;&gt;Smartphones&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Public+health%22&quot;&gt;Public health&lt;/searchLink&gt;
– Name: Abstract
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  Group: Ab
  Data: Helicobacter pylori (H. pylori) is a major pathogen associated with gastric ulcers and gastric cancer, infecting approximately half of the global population. Therefore, developing sensitive, rapid, and cost-effective detection methods for H. pylori is critical for public health. We developed an innovative microscale colorimetric microsensor integrated with smartphone ambient-light sensors for portable, on-site quantification of H. pylori-associated urease activity in dental plaque. This low-cost device (&lt; $ 5 fabrication) employs 3D-printed components and a custom app to measure transmittance changes from urease-catalyzed urea hydrolysis with phenol red, achieving a robust correlation with commercial microplate reader absorbance (R&lt;superscript&gt;2&lt;/superscript&gt; = 0.9989). The system demonstrates exceptional Analytical sensitivity, with limits of detection of 9.75 U/L for urease And 1.709 &#215; 10&lt;superscript&gt;3&lt;/superscript&gt; CFU/mL for H. pylori, alongside high reproducibility (CV &lt; 10%) And stability over 14 days. When applied to the on-site detection of dental plaque among volunteers, the smartphone-based colorimetric microsensor exhibited detection results that were highly aligned with H. pylori infections confirmed by the urea breath test. It outperformed commercial test strips And achieved 100% sensitivity, 95.5% specificity, And 97.1% accuracy. This miniaturized, smartphone-based platform offers a promising solution for home self-testing and demonstrates significant potential for enhancing H. pylori preliminary screening at the community level. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
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  Data: &lt;i&gt;Copyright of Microchimica Acta is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00604-025-07496-0
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        Text: English
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