Aptamer-Based Electrochemical Biosensors for the Detection of Salmonella: A Scoping Review

Dose Individualisation of Antimicrobials from a Pharmacometric Standpoint: The Current Landscape

Successful antimicrobial therapy depends on achieving optimal drug concentrations within individual patients. Inter-patient variability in pharmacokinetics (PK) and differences in pathogen susceptibility (reflected in the minimum inhibitory concentration, [MIC]) necessitate personalised approaches. Dose individualisation strategies aim to address this challenge, improving treatment outcomes and minimising the risk of toxicity and antimicrobial resistance. Therapeutic drug monitoring (TDM), with the application of population pharmacokinetic (popPK) models, enables model-informed precision dosing (MIPD). PopPK models mathematically describe drug behaviour across populations and can be combined with patient-specific TDM data to optimise dosing regimens. The integration of machine learning (ML) techniques promises to further enhance dose individualisation by identifying complex patterns within extensive datasets. Implementing these approaches involves challenges, including rigorous model selection and validation to ensure suitability for target populations. Understanding the relationship between drug exposure and clinical outcomes is crucial, as is striking a balance between model complexity and clinical usability. Additionally, regulatory compliance, outcome measurement, and practical considerations for software implementation will be addressed. Emerging technologies, such as real-time biosensors, hold the potential for revolutionising TDM by enabling continuous monitoring, immediate and frequent dose adjustments, and near patient testing. The ongoing integration of TDM, advanced modelling techniques, and ML within the evolving digital health care landscape offers a potential for enhancing antimicrobial therapy. Careful attention to model development, validation, and ethical considerations of the applied techniques is paramount for successfully optimising antimicrobial treatment for the individual patient.

Bismuthene - Tetrahedral DNA nanobioconjugate for virus detection

In this work, we present an electrochemical sensor for fast, low-cost, and easy detection of the SARS-CoV-2 spike protein in infected patients. The sensor is based on a selected combination of nanomaterials with a specific purpose. A bioconjugate formed by Few-layer bismuthene nanosheets (FLB) and tetrahedral DNA nanostructures (TDNs) is immobilized on Carbon Screen-Printed Electrodes (CSPE). The TDNs contain on the top vertex an aptamer that specifically binds to the SARS-CoV-2 spike protein, and a thiol group at the three basal vertices to anchor to the FLB. The TDNs are also marked with a redox indicator, Azure A (AA), which allows the direct detection of SARS-CoV-2 spike protein through changes in the current intensity of its electrolysis before and after the biorecognition reaction. The developed sensor can detect SARS-CoV-2 spike protein with a detection limit of 1.74 fg mL-1 directly in nasopharyngeal swab human samples. Therefore, this study offers a new strategy for rapid virus detection since it is versatile enough for different viruses and pathogens.

Rapid detection of Salmonella in milk by labeling-free electrochemical immunosensor based on an Fe3O4-ionic liquid-modified electrode

Electrochemical sensors show distinct advantages over other types of sensors in the rapid detection of microorganisms. Here, we attempted to construct a label-free electrochemical immunosensor based on an Fe3O4-ionic liquid (IL)-modified electrode to rapidly detect Salmonella in milk. The excellent ionic conductivity of the IL facilitated sensor construction, and the large surface area of nano-Fe3O4 provided numerous sites for subsequent experiments. An antibody was fixed on the Fe3O4-IL complex with polyglutamic acid modification by a simple infusion method. The microstructure of the Fe3O4-IL composites was investigated by scanning electron microscopy, and the elements and structures of the composites were analyzed by energy dispersive X-ray and Fourier transform infrared spectroscopy. Under optimized experimental conditions, the detection range of the constructed sensor was 3.65 × 102-3.65 × 108 CFU mL-1, and the LOD was 1.12 × 102 CFU mL-1 (S/N = 3). In addition, the prepared electrochemical immunosensor is convenient for detecting foodborne pathogens because of its outstanding stability, good selectivity, and repeatability.