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1.
Anal Methods ; 15(3): 322-332, 2023 01 19.
Artigo em Inglês | MEDLINE | ID: mdl-36594673

RESUMO

Kidney disease is highly prevalent and may result in severe clinical outcomes. Serum creatinine (Scr) and blood urea nitrogen (BUN) are the most widely used biomarkers for kidney function assessment, yet when measured alone, the result can be affected by a variety of parameters such as age, gender, protein consumption, etc. Measuring Scr and BUN simultaneously can eliminate most of the external influences and greatly improve the assessment of kidney function. In this study, a real-time kidney function assessment system based on dual biomarker detection was proposed. Scr and BUN were determined using surface-enhanced Raman scattering (SERS) within the concentration range of 10-1 to 10-6 M and 0.28 to 100 mg dl-1, respectively. A one-dimensional convolutional neural network (1D-CNN) model was employed to quantitatively analyze the concentration of biomarkers from the SERS spectral measurements. Moreover, we simulated a variety of kidney health conditions with 16 groups of mixed Scr and BUN in serum. The proposed CNN-assisted SERS method was used to quantify both biomarkers and provide diagnostic results. The Au core-Ag shell nanoprobes provided ultra-sensitive SERS detection and the CNN model achieved excellent regression results with an R2 of 0.9871 in the testing dataset. The system demonstrated a rapid and robust evaluation for the assessment of kidney function, providing a promising idea for medical diagnosis with the help of spectroscopy and deep learning methods.


Assuntos
Rim , Fenômenos Fisiológicos do Sistema Urinário , Nitrogênio da Ureia Sanguínea , Análise Espectral Raman , Biomarcadores
2.
Opt Express ; 30(2): 1452-1465, 2022 Jan 17.
Artigo em Inglês | MEDLINE | ID: mdl-35209305

RESUMO

Due to the global challenge of donor kidney shortage, expanding the pool of deceased donors has been proposed to include expanded criteria donors. However, the lack of methods to precisely measure donor kidney injury and predict the outcome still leads to high discard rates and recipient complications. As such, evaluation of deceased donor kidney quality is critical prior to transplantation. Biomarkers from donor urine or serum provide potential advantages for the precise measure of kidney quality. Herein, simultaneous detection of secretory leukocyte peptidase inhibitor (SLPI) and interleukin 18 (IL-18), two important kidney injury biomarkers, has been achieved, for the first time, with an ultra-high sensitivity using surface enhanced Raman scattering (SERS). Specifically, black phosphorus/gold (BP/Au) nanohybrids synthesized by depositing Au nanoparticles (NPs) onto the BP nanosheets serve as SERS-active substrates, which offer a high-density of inherent and accessible hot-spots. Meanwhile, the nanohybrids possess biocompatible surfaces for the enrichment of target biomarkers through the affinity with BP nanosheets. Quantitative detection of SLPI and IL-18 were then achieved by characterizing SERS signals of these two biomarkers. The results indicate high sensitivity and excellent reproducibility of this method. The limits of detection reach down to 1.53×10-8 mg/mL for SLPI and 0.23×10-8 mg/mL for IL-18. The limits of quantification are 5.10×10-8 mg/mL and 7.67×10-9 mg/mL for SLPI and IL-18. In addition, simultaneous detection of these biomarkers in serum was investigated, which proves the feasibility in biologic environment. More importantly, this method is powerful for detecting multiple analytes inheriting from excellent multiplexing ability of SERS. Giving that the combined assessment of SLPI and IL-18 expression level serves as an indicator of donor kidney quality and can be rapidly and reproducibly conducted, this SERS-based method holds great prospective in clinical practice.


Assuntos
Biomarcadores/metabolismo , Ouro/química , Interleucina-18/metabolismo , Rim/metabolismo , Fósforo/química , Inibidor Secretado de Peptidases Leucocitárias/metabolismo , Análise Espectral Raman/métodos , Humanos , Transplante de Rim , Nanopartículas Metálicas/química , Modelos Teóricos , Doadores de Tecidos
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