Hilal Torul

Herein, a unique electrochemiluminescence (ECL) sensor combined with a paper electrode was proposed for the detection of phenylalanine (L-Phe) in blood samples. The L-Phe detection was performed by converting L-Phe into ammonia using phenylalanine ammonia-lyase (PAL) enzyme and the ECL signal of Ru(bpy)₃ ²⁺ was produced in combination with ammonia as a co-reactant. In this report, we used AuNP decorated paper electrodes to obtain the ECL signal of Ru-(bpy)₃ ²⁺ in the presence of NH₃. The produced ammonia molecules were carried to the working electrode and their contact with the sample was cut off. Since there was no contact between the sample matrix and the electrode, the developed method achieved excellent selectivity. According to experimental data, a linear increase of the ECL signals with the logarithms of varying L-Phe concentrations between 1.5 × 10⁻² and 1.211 mM was observed with a correlation coefficient (R²) of 0.9898 and a limit of detection (LOD) of 8.4 × 10⁻³ mM. The proposed method was efficiently applied for L-Phe detection in reference blood samples and the average recovery was calculated as 96.8%. Furthermore, the HPLC-UV method as a comparison verified that the recovery values provided by the proposed method were acceptable with a similarity of 95.1% for L-Phe detection in a reference blood sample. The results showed that the developed ECL sensor combined with the paper electrode can be considered as a promising unique and powerful technique for a point-of-care diagnosis of PKU.

Paper-based biosensors are considered simple and cost-efficient sensing platforms for analytical tests and diagnostics. Here, a paper-based electrochemical biosensor was developed for the rapid and sensitive detection of microRNAs (miRNA-155 and miRNA-21) related to early diagnosis of lung cancer. Hydrophobic barriers to creating electrode areas were manufactured by wax printing, whereas a three-electrode system was fabricated by a simple stencil approach. A carbon-based working electrode was modified using either reduced graphene oxide or molybdenum disulfide nanosheets modified with gold nanoparticle (AuNPs/RGO, AuNPs/MoS₂) hybrid structures. The resulting paper-based biosensors offered sensitive detection of miRNA-155 and miRNA-21 by differential pulse voltammetry (DPV) in only 5.0 µL sample. The duration in our assay from the point of electrode modification to the final detection of miRNA was completed within only 35 min. The detection limits for miRNA-21 and miRNA-155 were found to be 12.0 and 25.7 nM for AuNPs/RGO and 51.6 and 59.6 nM for AuNPs/MoS₂ sensors in the case of perfectly matched probe-target hybrids. These biosensors were found to be selective enough to distinguish the target miRNA in the presence of single-base mismatch miRNA or noncomplementary miRNA sequences.

Here, we report a rapid method to enumerate Listeria monocytogenes (L. monocytogenes) utilizing magnetic nanoparticle based preconcentration and surface-enhanced Raman spectroscopy measurements. Biological activities of magnetic Au-nanoparticles have been observed to have the high bio-compatibility, and a sample immunosensor model has been designed to use avidin attached Au-nanoparticles for pathogen detection. Antimicrobial activity studies have been done to identify bio-compatibility and bio-characterization of the Au-nanoparticles in our previous study and capturing efficiencies to bacterial surfaces have been also investigated. We constructed the calibration graphs in various population density of L. monocytogenes as 2.2x101 to 2.2x106 cfu/mL and the capture efficiency was found to be 75%. After the optimization procedures, population density of L. monocytogenes and Raman signal intensity showed a good linear correlation (R2 = 0.991) between 102 to 106 cfu/mL L. monocytogenes. The presented sandwich assay provides low detection limits and limit of quantification as 12 cfu/mL and 37 cfu/mL, respectively. We also compared the experimental results with reference plate-counting methods and the practical utility of the proposed assay is demonstrated using milk samples.