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Details

Autor(en) / Beteiligte
Titel
Deeply-dyed nanobead system for rapid lateral flow assay testing of drugs at point-of-care
Ist Teil von
  • Sensors and actuators. B, Chemical, 2022-07, Vol.362, p.131829, Article 131829
Ort / Verlag
Lausanne: Elsevier B.V
Erscheinungsjahr
2022
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • Point-of-care test (POCT) allows for rapid and sensitive screening of drugs of abuse. However, traditional gold nanoparticle-based lateral flow immunoassay strip is not sensitive enough for detection of trace drugs in hair samples. Herein, we aimed to develop a more specific system using a composite polymer nanobead that is deeply dyed with oil soluble dyes, and termed as deeply dyed nanobead (DDNB). The prepared composite nanobeads displayed a clear core-shell structure and the core/shell ratios were readily controlled by polymer/dye feeding ratios. The absorbance stable nanobeads capped with carboxyl groups were covalently conjugated with antibodies, and were employed for preparation of lateral flow immunoassay strips for sensitive detection of drugs in hair with naked eye. The developed drug strips allow the detection of drugs such as morphine and methamphetamine in hair samples within 13 min (including hair sample processing ~5 min). The cut-off value of DDNB strip for methamphetamine detection with naked eye is down to concentration of 8.0 ng/mL, which is about 3.1 times more sensitive than the traditional gold nanoparticles based lateral flow immunoassay. Moreover, the colorful DDNB system has the potential for multiplexing detection of analytes at point-of-care settings and low cost. [Display omitted] •Deeply dyed nanobeads (DDNB) were prepared with controlled core-shell structure.•The prepared DDNBs are colorful, brilliant bright, and stable in a wide range of pH buffer and at high temperature.•The DDNB based lateral flow immunoassay strips are 3.1 times more sensitive than gold nanoparticles based strips.•The colorful DDNBs are potential for multiplexing detection.
Sprache
Englisch
Identifikatoren
ISSN: 0925-4005
eISSN: 1873-3077
DOI: 10.1016/j.snb.2022.131829
Titel-ID: cdi_proquest_journals_2697158257

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