Enzymatic biosensors are a crucial component of modern analytical science, offering exceptional molecular specificity across clinical, environmental, and industrial applications. Despite their widespread use, the development of reliable biosensor platforms continues to face challenges, particularly regarding enzymatic stability, reproducibility, and long-term operational lifespan. This review critically examines the core principles of high-performance enzymatic biosensors, integrating biochemical fundamentals with advances in materials. Our analysis begins with the kinetic and thermodynamic factors that govern sensor sensitivity and dynamic range, focusing on how immobilization alters Michaelis–Menten parameters and how diffusional and mass-transport limitations impact traditional kinetic models. We also examine environmental factors such as pH, temperature, and cofactor regeneration. Special attention is given to interfacial engineering, comparing oriented and random immobilization, considering factors such as fabrication complexity, cost, enzyme-specific applicability, and activity losses due to modifications. The review evaluates various signal transduction mechanisms, including electrochemical, optical, semiconductor-based, wearable, and emerging in-sensor computing architectures. Using gas-phase biosensing of volatile organic compounds as a case study, we highlight how this niche stresses every design parameter, revealing it to be smaller and more chemically constrained than is often implied. Finally, we discuss major unresolved challenges, especially the lack of standardized benchmarking methods that would permit fair comparison between competing strategies.
A one-pot, ultrasound-assisted and environmentally responsible strategy is proposed for the simultaneous partial reduction and biofunctionalization of graphene oxide (GO), using L-tyrosine (L-tyr) and ascorbic acid (AA) as mild and complementary reducing agents. This synergistic approach enables controlled partial restoration of the sp2 carbon framework while preserving oxygen functionalities required for biomolecular anchoring. Avidin is incorporated in situ during the reduction process, eliminating post-synthetic modification steps while enabling its functional role in biotinylated recognition element immobilization. The resulting avidin-functionalized reduced graphene oxide (rGO) provides a functional electrochemical interface for the oriented immobilization of biotinylated recognition elements through the avidin-biotin affinity interaction. This immobilization strategy was conceived to facilitate the assembly of different biosensing interfaces without requiring surface re-engineering. The platform was implemented as a label-free electrochemical interface and characterized by electrochemical impedance spectroscopy to monitor interfacial assembly and biorecognition events. As a proof-of-concept, the proposed immobilization strategy was experimentally validated using the thrombin-binding aptamer as a representative biotinylated recognition element for the detection of human α-thrombin (α-th). The platform exhibited a linear response from 1.34 × 10−9 M to 2.67 × 10−6 M (R2 = 0.987) and a detection limit of 4.4 × 10−10 M, demonstrating selective response in the presence of potentially interfering proteins and enriched human serum samples. These results demonstrate a sustainable one-pot strategy for producing avidin-functionalized rGO and establish a proof-of-concept for an avidin-based electrochemical biointerface. Although the present study experimentally validates the approach using a single aptamer-target pair, the proposed immobilization strategy may enable the future development of adaptable electrochemical biosensing platforms employing different biotinylated recognition elements without modifying the underlying transducer.
Since the trachea has complex anatomical, mechanical, and biological needs, tracheal problems caused by congenital defects, injuries, prolonged intubation, infections, and cancer still pose major clinical problems. The trachea should be able to keep an open airway, possess a functional respiratory epithelium that is able to perform mucociliary clearance, and also be flexible during breathing and neck movements. Nonetheless, limited availability of donors, immune rejection, infections, restenosis, mechanical misfits, and long-term failures are all problems that hinder the current clinical treatments such as autografts, allografts, and synthetic stents. Therefore, tracheal regeneration remains a problem. This review shows how 3D bioprinting with the use of biosensing technologies, which include biosensors to measure oxygen concentration, pH level, mechanical strain, and tissue maturation in real-time, allows creating smart tracheal tissues. Alongside with the methods of extrusion bioprinting, stereolithography, multimaterial bioprinting, and hybrid bioprinting, the mentioned approaches allow recreating the complex structure of the trachea, its biomechanical gradient, and microenvironment of the trachea. This advancement in 3D bioprinting results in designing smart and functional tracheal grafts that can respond to the changing biological environment. Nevertheless, there are many translational obstacles, which include airway patency, mechanical stability, biocompatibility, and biosensor reliability among others. The integration of biosensors ensures the monitoring of cellular activity, scaffold behavior, and tissue development, which helps in designing the printing techniques. This review paper emphasizes the developments in 3D bioprinting, smart biosensing, digital twin, and artificial intelligence used for tracheal regeneration. Such integrated technology helps in the transformation of experimental products to clinical products of higher quality and intelligence.
The rapid miniaturisation of biosensors, be it wearable health monitors, point-of-care diagnostics, and community-scale environmental sensing, has enabled health data collection at a rapidly increasing and more distributed scale across Low- and Middle-Income Countries (LMICs). This rise in the scale of adoption in LMICs is due to these technologies becoming more feasible, portable, and orientated toward low-resource deployment. Yet the Privacy-Enhancing Technologies (PETs) developed to protect these data were designed and validated in high-income, high-compute contexts. This Perspective argues that deploying next-generation miniaturised biosensors for LMICs without rethinking the PET design agenda risks compounding existing health inequities. Current PET implementations face three structural mismatches with LMIC biosensor deployment: the computational overhead of secure multiparty computation and homomorphic encryption exceeds the resource envelope of low-power edge devices; differential privacy can disproportionately degrade model utility for underrepresented populations when datasets are small, imbalanced, or hard to model, conditions that are endemic to LMIC biosensor cohorts; and regulatory-technical translation remains underdeveloped in the jurisdictions where biosensor rollout is accelerating fastest. We propose a reorientation around three design principles: computational proportionality (matching PET selection to hardware constraints), equity-aware privacy budgeting (calibrating differential privacy parameters to population representation), and community data sovereignty (architecting local governance into federated biosensor networks). We identify five priority research questions that reframe the field’s open challenges through an LMIC lens. The goal is not to caution against biosensor deployment, but to ensure that privacy-by-design is embedded in the next-generation of sensing systems, while accounting for adoption challenges and broader digital transformation in resource-constrained health systems.
Thermally induced particulate matter (TIPM) may provide an indicator of abnormal cable-material heating before combustion. This study combines thermogravimetric analysis, a qualitative comparison with a particle counter, and sensor measurements in a 6 m simulated cable trench. The PVC sample lost approximately 1.6% of its mass below 200 °C. This observation is consistent with low-temperature volatile release but does not identify the emitted species or establish a particle-formation pathway. Five laser particle sensors (LPS), spaced 1 m apart, monitored end-source and central-source configurations at 100 °C–110 °C, 150 °C–160 °C, and 200 °C–210 °C. No sensor response was reported at 100 °C–110 °C in the trench tests. At the two higher temperature ranges, response onset depended on source position and distance. In the reported end-source test at 200 °C–210 °C, N1 responded at 18.31 min and the HCl sensor at 27 min, a difference of 8.69 min. This is a single-run comparison, not a validated lead time to ignition. The spatial response patterns support further evaluation of distributed particle sensing, while replication, quantitative detection thresholds, and field-interference testing are needed before deployment rules can be established.
