Enhancing electrochemical detection through machine learning-driven prediction for canine mammary tumor biomarker with green silver nanoparticles.

This study developed an innovative biosensor strategy for the sensitive and selective detection of canine mammary tumor biomarkers, cancer antigen 15-3 (CA 15-3) and mucin 1 (MUC-1), integrating green silver nanoparticles (GAgNPs) with machine learning (ML) algorithms to achieve high diagnostic accuracy and potential for noninvasive early detection. The GAgNPs-enhanced electrochemical biosensor demonstrated selective detection of CA 15-3 in serum and MUC-1 in tissue homogenates, with limits of detection (LODs) of 0.07 and 0.11 U mL-1, respectively. The nanoscale dimensions of the GAgNPs endowed them with electrochemically active surface areas, facilitating sensitive biomarker detection. Experimental studies targeted CA 15-3 and MUC-1 biomarkers in clinical samples, and the biosensor exhibited ease of use and good selectivity. Furthermore, ML algorithms were employed to analyze the electrochemical data and predict biomarker concentrations, enhancing the diagnostic accuracy. The Random Forest algorithm achieved 98% accuracy in tumor presence prediction, while an Artificial Neural Network attained 76% accuracy in CA 15-3-based tumor grade classification. The integration of ML techniques with the GAgNPs-based biosensor offers a promising approach for noninvasive, accurate, and early detection of canine mammary tumors, potentially revolutionizing veterinary diagnostics. This multilayered strategy, combining eco-friendly nanomaterials, electrochemical sensing, and ML algorithms, holds significant potential for advancing both biomedical research and clinical practice in the field of canine mammary tumor diagnostics.

Cubic-shaped corylus colurna extract coated Cu2O nanoparticles-based smartphone biosensor for the detection of ascorbic acid in real food samples.

Ascorbic acid (AA) is a highly water-soluble organic chemical compound and plays a significant role in human metabolism. For the purpose of food quality monitoring, this study focuses on the development of a smartphone-integrated colorimetric and non-enzymatic electrochemical Corylus Colurna (CC) extract-Cu2O nanoparticles (Cu2O NPs) biosensor to detect AA in real food samples. The characterization of the CC-Cu2O NPs was determined using SEM, SEM/EDX, HRTEM, XRD, FTIR, XPS, TGA, and DSC. The CC-Cu2O NPs are cubic in shape with an approximate size of 10 nm. According to electrochemical results, the oxidation of AA at the modified electrode exhibited a LOD of 27.92 nmolL-1 in a wide concentration range of 0.55-22 mmolL-1. The fabricated digital CC-Cu2O NPs sensor successfully detected AA in food samples. This strategy provides a nanoplatform to determine the detection of AA in food samples.

Highly sensitive and selective rGO based Non-Enzymatic electrochemical sensor for propamocarb fungicide pesticide detection.

In this study, reduced graphene oxide (rGO) was prepared using a green ultrasonic microwave assisted method and investigated rGO based non-enzymatic electrochemical sensor for detecting a synthetic fungicide as a propamocarb (PM) pesticide. The rGO-based sensor exhibited rapid response within 1 min, low detection limit of 0.6 µM and wide linear range of (1-5) µM with a high sensitivity of 101.1 µAµM-1 cm-2 for PM. Besides this, the sensor detected the propamocarb pesticide on the real cucumber sample with high sensitivity in the concentration range of (1-5) µM within a 1-minute cycle. The sensor is highly selective against propamocarb pesticide. The prepared non-enzymatic electrochemical sensor exhibited high sensitivity, high selectivity, reproducibility, and rapid response.

Probing microscopic wetting properties of superhydrophobic surfaces by vibrated micrometer-sized droplets.

We determine contact angles of micrometer-sized NaCl-water droplets on superhydrophobic surfaces by analyzing their lowest-order axisymmetric vibrational resonances driven by vertical oscillations of the surface. Fluorescence spectra of the dye-doped droplets excited by laser light feature whispering-gallery modes (WGMs) whose spectral widths depend on the droplet vibration amplitude, thus enabling precise measurements of the droplet mechanical resonant frequency. Following droplet size determination by WGM mode-matching, we calculate the contact angles from the dependence of the measured mechanical resonant frequency on the droplet size for two surfaces with different superhydrophobicity levels, and find a good correlation with the values measured by direct imaging of millimeter-sized droplets.

Preparation and characterization of superhydrophobic surfaces based on hexamethyldisilazane-modified nanoporous alumina.

Superhydrophobic nanoporous anodic aluminum oxide (alumina) surfaces were prepared using treatment with vapor-phase hexamethyldisilazane (HMDS). Nanoporous alumina substrates were first made using a two-step anodization process. Subsequently, a repeated modification procedure was employed for efficient incorporation of the terminal methyl groups of HMDS to the alumina surface. Morphology of the surfaces was characterized by scanning electron microscopy, showing hexagonally ordered circular nanopores with approximately 250 nm in diameter and 300 nm of interpore distances. Fourier transform infrared spectroscopy-attenuated total reflectance analysis showed the presence of chemically bound methyl groups on the HMDS-modified nanoporous alumina surfaces. Wetting properties of these surfaces were characterized by measurements of the water contact angle which was found to reach 153.2 ± 2°. The contact angle values on HMDS-modified nanoporous alumina surfaces were found to be significantly larger than the average water contact angle of 82.9 ± 3° on smooth thin film alumina surfaces that underwent the same HMDS modification steps. The difference between the two cases was explained by the Cassie-Baxter theory of rough surface wetting.

Fabrication of vertically aligned Pd nanowire array in AAO template by electrodeposition using neutral electrolyte.

A vertically aligned Pd nanowire array was successfully fabricated on an Au/Ti substrate using an anodic aluminum oxide (AAO) template by a direct voltage electrodeposition method at room temperature using diluted neutral electrolyte. The fabrication of Pd nanowires was controlled by analyzing the current-time transient during electrodeposition using potentiostat. The AAO template and the Pd nanowires were characterized by scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) methods and X-Ray diffraction (XRD). It was observed that the Pd nanowire array was standing freely on an Au-coated Ti substrate after removing the AAO template in a relatively large area of about 5 cm2, approximately 50 nm in diameter and 2.5 µm in length with a high aspect ratio. The nucleation rate and the number of atoms in the critical nucleus were determined from the analysis of current transients. Pd nuclei density was calculated as 3.55 × 108 cm-2. Usage of diluted neutral electrolyte enables slower growing of Pd nanowires owing to increase in the electrodeposition potential and thus obtained Pd nanowires have higher crystallinity with lower dislocations. In fact, this high crystallinity of Pd nanowires provides them positive effect for sensor performances especially.