A convenient sampling and noninvasive dried spot method of uric acid in human saliva: Comparison of serum uric acid value and salivary uric acid in healthy volunteers and hyperuricemia patients

Nanocubic cobalt-containing Prussian blue analogue-derived carbon-coated CoFe alloy nanoparticles for noninvasive uric acid sensing

This work describes an electrochemical sensor for the fast noninvasive detection of uric acid (UA) in saliva. The sensing material was based on a cobalt-containing Prussian blue analogue (Na2-xCo[Fe(CN)6]1-y, PCF). By optimizing the ratio of Co and Fe as 1.5 : 1 in PCF (PCF1.5,0), particles with a regular nanocubic morphology were formed. The calcination of PCF1.5,0 produced a carbon-coated CoFe alloy (CCF1.5), which possessed abundant defects and achieved an excellent electrochemical performance. Subsequently, CCF1.5 was modified on a screen-printed carbon electrode (SPCE) to fabricate the electrochemical sensor, CCF1.5/SPCE, which showed a sensitive and selective response toward salivary UA owing to its good conductivity, sufficient surface active sites and efficient catalytic activity. The determination of UA in artificial saliva achieved the wide linear range of 40 nM-30 μM and the low limit of detection (LOD) of 15.3 nM (3σ/s of 3). The performances of the sensor including its reproducibility, stability and selectivity were estimated to be satisfactory. The content of UA in human saliva was determined and the recovery was in the range of 98-107% and the total RSD was 4.14%. The results confirmed the reliability of CCF1.5/SPCE for application in noninvasive detection.

Disposable solar microcell array-based addressable photoelectrochemical sensor for high-throughput and multiplexed analysis of salivary metabolites

The high-throughput detection of multiple metabolites in saliva by electrochemical sensors is usually a challenge, which however is essential to the comprehensive evaluation of health status or screening of diseases. Here, a light-addressable and paper-based hydrogen peroxide (H₂O₂) photoelectrochemical (PEC) sensor for the high-throughput detection of multiple salivary metabolites is reported. This sensor has a unique solar microcell array structure with a silver nanowires/fullerene-Congo red (AgNWs/C₆₀-CR) disc working electrode (WE) and a single-walled carbon nanotubes/platinum nanowires (SWCNTs/PtNWs) ring reference/counter electrode (RE/CE) in each microcell. Enzymes of different metabolites are immobilized on different separated microcells of a cover slide over the sensor, from which enzymatically produced H₂O₂ can react with p-hydroxyphenyl boric acid (4-HPBA) on the WE of the sensor to generate hydroquinone (HQ) for photocurrent responses. Based on this strategy, a disposable PEC sensor of saliva was developed, which allows the multiplexed detection of uric acid (UA), glucose (GLU) and lactate (LA) in diluted human saliva with high sensitivity and selectivity. Moreover, the detection throughput and application field of the sensor can be easily extended by connecting a series of sensors in parallel or varying the enzymes. The present work thus establishes a cost-effective approach to the scalable construction of versatile biosensing platforms with tunable throughput and varied analytes.

Potential use of a dried saliva spot (DSS) in therapeutic drug monitoring and disease diagnosis

In recent years, scientific researchers have increasingly become interested in noninvasive sampling methods for therapeutic drug monitoring and disease diagnosis. As a result, dried saliva spot (DSS), which is a sampling technique for collecting dried saliva samples, has been widely used as an alternative matrix to serum for the detection of target molecules. Coupling the DSS method with a highly sensitive detection instrument improves the efficiency of the preparation and analysis of biological samples. Furthermore, dried blood spots, dried plasma spots, and dried matrix spots, which are similar to those of the DSS method, are discussed. Compared with alternative biological fluids used in dried spot methods, including serum, tears, urine, and plasma, saliva has the advantage of convenience in terms of sample collection from children or persons with disabilities. This review aims to provide integral strategies and guidelines for dried spot methods to analyze biological samples by illustrating several dried spot methods. Herein, we summarize recent advancements in DSS methods from June 2014 to March 2021 and discuss the advantages and disadvantages of the key aspects of this method, including sample preparation and method validation. Finally, we outline the challenges and prospects of such methods in practical applications.

Non-invasive quantitative analysis of human blood components in renal three items using spectral compensation method based on spectral data and component content correlation

BACKGROUND AND OBJECTIVE

The non-invasive measurement of the blood component contents in humans using spectroscopic methods has important clinical application value. In the absorption spectrum of human blood, for a target component with a small content, the absorption spectrum line is low, the absorption spectrum line of the target component changes weakly at different wavelengths, and the absorption spectrum lines of the target and non-target components overlap. The above reasons cause the spectral line difference between the target and non-target components to be small. However, non-target components also have physical properties such as scattering, which will reduce the contribution of the target component in the absorption spectrum of blood, that is, the spectral line difference between the target and non-target components becomes smaller, thus making the accuracy of the target component model lower.

METHODS

To increase the accuracy of modeling analysis, according to the correlation between spectral data and the content of the target component, this paper proposes a spectral compensation method. The method compensates for the influence caused by the non-target components on the target components through the mathematical relations between the data of the spectrum and the contents of the target components. Thus, a high-precision, non-invasive quantitative analysis system of human blood components is obtained. Taking the analysis of the three components of urea nitrogen, creatinine, and uric acid as examples, the experiment used spectral data before and after spectral compensation and partial least squares (PLS) methods to build two models and used them to predict the content of the target component.

RESULTS

When the models of different components established by the spectral compensation method respectively predict the all samples' contents of urea, creatinine, and uric acid, the three correlation coefficients can reach more than 0.9700.

CONCLUSION

It can be obtained from the experimental results that the spectral compensation method can greatly increase the performance of each component model. Spectral compensation is a new and comprehensive method for improving the quality of spectral data. Therefore, this paper obtains a non-invasive quantitative analysis system of human blood components with higher precision, and can quantitatively analyze blood urea nitrogen, creatinine, and uric acid in human blood with high precision, which has great practical application value in clinical practice.

Rapid Detection of Amitriptyline in Dried Blood and Dried Saliva Samples with Surface-Enhanced Raman Spectroscopy

There is growing demand for rapid, nondestructive detection of trace-level bioactive molecules including medicines, toxins, biomolecules, and single cells, in a variety of disciplines. In recent years, surface-enhanced Raman scattering has been increasingly applied for such purposes, and this area of research is rapidly growing. Of particular interest is the detection of such compounds in dried saliva spots (DSS) and dried blood spots (DBS), often in medical scenarios, such as therapeutic drug monitoring (TDM) and disease diagnosis. Such samples are usually analyzed using hyphenated chromatography techniques, which are costly and time consuming. Here we present for the first time a surface-enhanced Raman spectroscopy protocol for the detection of the common antidepressant amitriptyline (AMT) on DBS and DSS using a test substrate modified with silver nanoparticles. The validated protocol is rapid and non-destructive, with a detection limit of 95 ppb, and linear range between 100 ppb and 1.75 ppm on the SERS substrate, which covers the therapeutic window of AMT in biological fluids.

Electrochemical detection of uric acid in undiluted human saliva using uricase paper integrated electrodes

In this study, we introduce a uricase-immobilized paper (UOx­-paper) integrated electrochemical sensor for detection of uric acid (UA) in saliva. The UOx was immobilized on the detection zone in the wax-patterned paper substrate. This UOx-paper was integrated with a Prussian blue­-modified, screen-printed carbon electrode after electropolymerization of o-phenylenediamine to construct an electrochemical cell for small-volume (20 μL) of samples. First, we optimized the fabrication conditions of UOx-paper. Next, the amperometric response of the UOx-paper-based electrochemical UA sensor was analyzed using a known concentration of UA standard solution in artificial saliva at an applied potential of − 0.1 V (versus Ag pseudo-reference electrode). The UOx-­paper based electrochemical UA sensor showed a sensitivity of 4.9 μA·mM⁻¹ in a linear range of 50 to 1000 μM (R² = 0.998), high selectivity and good reproducibility, as well as a limit of detection of 18.7 μM (0.31 mg/dL) UA. Finally, we quantified the UA levels in undiluted saliva samples of healthy controls (n = 20) and gout patients (n = 8). The levels were correlated with those measured with conventional salivary UA enzymatic assays as well as serum UA levels. The UOx-paper-based electrochemical UA sensor is a user-friendly and convenient tool to assess salivary UA levels.

Digital Quantification Method for Sensitive Point-of-Care Detection of Salivary Uric Acid Using Smartphone-Assisted μPADs

Uric acid (UA) is an important biomarker for many diseases. A sensitive point-of-care (POC) testing platform is designed for the digital quantification of salivary UA based on a colorimetric reaction on an easy-to-build smartphone-assisted microfluidic paper-based analytical device (SμPAD). UA levels are quantified according to the color intensity of Prussian blue on the SμPAD with the aid of a MATLAB code or a smartphone APP. A color correction method is specifically applied to exclude the light effect. Together with the engineering design of SμPADs, the background calibration function with the APP increases the UA sensitivity by 100-fold to reach 0.1 ppm with a linear range of 0.1-200 ppm. The assay time is less than 10 min. SμPADs demonstrate a correlation of 0.97 with a commercial UA kit for the detection of salivary UA in clinical samples. SμPADs provide a sensitive, fast, affordable, and reliable tool for the noninvasive POC quantification of salivary UA for early diagnosis of abnormal UA level-associated health conditions.

Recent Advances in Intelligent Wearable Medical Devices Integrating Biosensing and Drug Delivery

The primary roles of precision medicine are to perform real-time examination, administer on-demand medication, and apply instruments continuously. However, most current therapeutic systems implement these processes separately, leading to treatment interruption and limited recovery in patients. Personalized healthcare and smart medical treatment have greatly promoted research on and development of biosensing and drug-delivery integrated systems, with intelligent wearable medical devices (IWMDs) as typical systems, which have received increasing attention because of their non-invasive and customizable nature. Here, the latest progress in research on IWMDs is reviewed, including their mechanisms of integrating biosensing and on-demand drug delivery. The current challenges and future development directions of IWMDs are also discussed.