Chemometrics-assisted simultaneous voltammetric determination of multiple neurotransmitters in human serum

Chemometrically assisted differential pulse voltammetry for simultaneous and interference-free quantification of gallic and caffeic acids

This article explores the application of chemometric tools including multivariate curve resolution with alternating least squares for the simultaneous determination of gallic and caffeic acids on the surface of a glassy carbon electrode without additional modification. Gallic and caffeic acids are primary polyphenols, the most abundant in red wines produced in Argentina, and are often used as quality markers for them. These polyphenols significantly contribute to the organoleptic properties of wines from this origin, but their electrochemical signals overlap significantly, making simultaneous quantification challenging without additional experiments such as electrode modification or alternative analytical techniques beyond differential pulse voltammetry. This study successfully quantified these compounds in complex mixtures by generating second-order data from differential pulse voltammetry experiments conducted at various potential steps and subsequently applying multivariate curve resolution with alternating least squares. The use of constraints during optimization prevented rotational ambiguities common in this modeling, leading to unique results in validation samples. The limits of detection (LOD) found for gallic and caffeic acids were 1.6 and 7.6 mg L-1, which are in excellent agreement with the expected concentrations of these compounds in red wines. The concentration ranges analyzed showed a linear dependency (between the LOD and 300 mg L-1) with the signals estimated by the model for both analytes. Advantages such as simplicity, low cost, and high speed, as well as not requiring electrode modification, combined with excellent results obtained for real samples, make it a promising alternative for polyphenol analysis in the wine industry.

Simultaneous detection of norepinephrine and 5-hydroxytryptophan using poly-alizarin/multi-walled carbon nanotubes-graphene modified carbon fiber microelectrode array sensor

Multi-walled carbon nanotubes, graphene and alizarin polymer composites coated carbon fiber microelectrode array sensor (p-AZ/MWCNT-GR/CFMEA) was constructed and used for the simultaneous detection of norepinephrine (NE) and 5-hydroxytryptophan (5-HT). The morphology and structural characteristics of sensor are characterized using scanning electron microscopy, energy dispersive spectroscopy and X-ray diffraction. Its electrochemical behavior has been studied with cyclic voltammetry and electrochemical impedance spectroscopy. The sensor exhibits excellent electrochemical activity for the oxidation of NE and 5-HT, two well separated oxidation peaks with the peak potential difference of 220 mV are observed on the cyclic voltammogram. NE and 5-HT both show two electrons and two protons electrochemical reaction on the p-AZ/MWCNT-GR/CFMEA. Under the optimized experiment conditions, the linear ranges of the sensor for NE and 5-HT are 0. 08- 8 μM and 0. 1-20 μM with detection limits of 4. 22 nM and 14. 2 nM (S/N = 3), respectively. In addition, the microsensor array show good reproducibility, stability and selectivity for the determination of NE and 5-HT. Finally, the p-AZ/MWCNT-GR/CFMEA is applied to the simultaneous detection of NE and 5-HT in human serum samples and macrophages.

Potential of vibrational spectroscopy coupled with machine learning as a non-invasive diagnostic method for COVID-19

BACKGROUND AND OBJECTIVE

Efforts to alleviate the ongoing coronavirus disease 2019 (COVID-19) crisis showed that rapid, sensitive, and large-scale screening is critical for controlling the current infection and that of ongoing pandemics.

METHODS

Here, we explored the potential of vibrational spectroscopy coupled with machine learning to screen COVID-19 patients in its initial stage. Herein presented is a hybrid classification model called grey wolf optimized support vector machine (GWO-SVM). The proposed model was tested and comprehensively compared with other machine learning models via vibrational spectroscopic fingerprinting including saliva FTIR spectra dataset and serum Raman scattering spectra dataset.

RESULTS

For the unknown vibrational spectra, the presented GWO-SVM model provided an accuracy, specificity and F1_score value of 0.9825, 0.9714 and 0.9778 for saliva FTIR spectra dataset, respectively, while an overall accuracy, specificity and F1_score value of 0.9085, 0.9552 and 0.9036 for serum Raman scattering spectra dataset, respectively, which showed superiority than those of state-of-the-art models, thereby suggesting the suitability of the GWO-SVM model to be adopted in a clinical setting for initial screening of COVID-19 patients.

CONCLUSIONS

Prospectively, the presented vibrational spectroscopy based GWO-SVM model can facilitate in screening of COVID-19 patients and alleviate the medical service burden. Therefore, herein proof-of-concept results showed the chance of vibrational spectroscopy coupled with GWO-SVM model to help COVID-19 diagnosis and have the potential be further used for early screening of other infectious diseases.

Electrochemical sensor based on Ti3C2 membrane doped with UIO-66-NH2 for dopamine

A Ti₃C₂ membrane was prepared by doping UIO-66-NH₂ with Ti₃C₂ through hydrogen bonds. When the doping mass ratio of Ti₃C₂ and UIO-66-NH₂ was 6:1, the electrochemical performance was optimal. Characterization was done by scanning electron microscopy (SEM), transmission electron microscopy (TEM), and electrochemical impedance spectroscopy (EIS) which exhibited hierarchical cave-like physiognomy, large specific area, outstanding electronic conductive network, and excellent film-forming property. Moreover, the Ti₃C₂ film was analyzed via atomic force microscopy (AFM), which displayed good mechanical properties and rough surface morphology. The fabricated Ti₃C₂ membrane/GCE sensor was applied to the detection of dopamine (working potential of + 0.264 V vs. Ag/AgCl) with LOD of 0.81 fM and a sensitivity of 14.72 µA fM⁻¹ cm⁻². It was demonstrated that the Ti₃C₂ membrane can be used to construct nonenzymatic sensors with excellent performance. The fabricated sensor has high selectivity and stability and has good practicability with recoveries of 101.2–103.5% and a relative standard deviation (RSD) of 1.2–2.4%.

Colorimetry and SERS dual-mode sensing of serotonin based on functionalized gold nanoparticles

In this study, we reported a colorimetry and SERS dual-mode sensing of serotonin (5-HT) based on functionalized gold nanoparticles (AuNPs). Based on the amino and hydroxyl groups in 5-HT can react with dithiobis succinimidyl propionate (DSP) and N-acetyl-L-cysteine (NALC) respectively, we synthesized two kinds of functionalized AuNPs (DSP-AuNPs and NALC-AuNPs). A double interaction between functionalized nanoparticles and the hydroxyl and the amino group of serotonin led to interparticle-crosslinking aggregation. The aggregation of the two functionalized AuNPs can cause the plasmon coupling of AuNPs resulting in a color change visible to the naked eye and the enlargement of SERS "hot spot" area and the enhancement of SERS signal. Furthermore, two kinds of functionalized AuNPs can specifically recognize 5-HT and effectively reduce the interference of biomolecules with similar structure to 5-HT in the experiment. This dual-mode system has the advantages of low detection limit, high sensitivity and good selectivity, and the detection limit is 0.15 nmol L^-1. Besides, the system was applied to the determination of 5-HT content in human serum, and the relative standard deviation (RSD) was lower than 3.75%, which indicated that the system had a good application prospect in the determination of biological samples.

Rationally designed f-MWCNT-coated bismuth molybdate (f-MWCNT@BMO) nanocomposites for the voltammetric detection of biomolecule dopamine in biological samples

Selective and sensitive dopamine (DPA) sensor was developed using hydrothermally prepared functionalized multi-walled carbon nanotube-coated bismuth molybdate (f-MWCNT@BMO). The f-MWCNT@BMO-reinforced electrode exhibited an outstanding electrocatalytic activity towards DPA oxidation. The nanocomposite-reinforced electrode displayed a rapid response towards DPA sensing and possessed the minimized potential of (E_pa + 0.285 V vs Ag/AgCl) in 0.1 M phosphate buffer (PB). The electrochemical results of prepared sensors were analyzed using the differential pulse voltammetry method (DPV). As a result, the f-MWCNT@BMO-reinforced electrode exhibited a widelinear range of 10 nM - 814 μM with a very low detection limit of 3.4 nM towards DPA oxidation. The developed sensor shows excellent selectivity in presence of similar functional group biomolecules. The detection of DPA in real samples was evaluated in human serum, as the results of the proposed sensor possessed good recoveries.