RESUMEN
This study investigates biomimetic sensors for the detection of methotrexate contaminants in environmental samples. Sensors inspired by biological systems are the focus of this biomimetic strategy. Methotrexate is an antimetabolite that is widely used for the treatment of cancer and autoimmune diseases. Due to the widespread use of methotrexate and its rampant disposal into the environment, the residues of this drug are regarded as an emerging contaminant of huge concern, considering that exposure to the contaminant has been found to lead to the inhibition of some essential metabolic processes, posing serious risks to humans and other living beings. In this context, this work aims to quantify methotrexate through the application of a highly efficient biomimetic electrochemical sensor constructed using polypyrrole-based molecularly imprinted polymer (MIP) electrodeposited by cyclic voltammetry on a glassy carbon electrode (GCE) modified with multi-walled carbon nanotubes (MWCNT). The electrodeposited polymeric films were characterized by infrared spectrometry (FTIR), scanning electron microscopy (SEM), and cyclic voltammetry (CV). The analyses conducted using differential pulse voltammetry (DPV) yielded a detection limit of 2.7 × 10-9 mol L-1 for methotrexate, a linear range of 0.01-125 µmol L-1, and a sensitivity of 0.152 µA L mol-1. The results obtained from the analysis of the selectivity of the proposed sensor through the incorporation of interferents in the standard solution pointed to an electrochemical signal decay of only 15.4%. The findings of this study show that the proposed sensor is highly promising and suitable for use in the quantification of methotrexate in environmental samples.
RESUMEN
Redesigning 3D-printed flow cells is reported used for heat transfer based detection of biomolecules from a flow-through system to an addition-type measurement cell. The aim of this study is to assess the performance of this new measurement design and critically analyse the influence of material properties and 3D printing approach on thermal analysis. Particular attention is paid to reduce the time to stabilisation, the sample volume in order to make the technique suitable for clinical applications, and improving the sensitivity of the platform by decreasing the noise and interference of air bubbles. The three different approaches that were studied included a filament polylactic acid cell using only fused filament fabrication (FFF), a resin cell printed using stereolitography (SLA), and finally a design made of copper, which was manufactured by combining metal injection moulding (MIM) with fused filament fabrication (FFF). Computational fluid dynamic (CFD) modelling was undertaken using ANSYS Fluent V18.1 to provide insight into the flow of heat within the measurement cell, facilitating optimisation of the system and theoretical response speed.It was shown that the measurement cells using SLA had the lowest noise (~ 0.6%) and shortest measurement time (15 min), whereas measurement cells produced using other approaches had lower specificity or suffered from voiding issues. Finally, we assessed the potential of these new designs for detection of biomolecules and amoxicillin, a commonly used beta lactam antibiotic, to demonstrate the proof of concept. It can be concluded that the resin addition-type measurement cells produced with SLA are an interesting affordable alternative, which were able to detect amoxicillin with high sensitivity and have great promise for clinical applications due to the disposable nature of the measurement cells in addition to small sample volumes.