Water is indispensable for life, yet many lack access to clean drinking water, resulting in fatalities from waterborne bacterial infections. Precise assessment of microbial abundance and viability in natural aquatic environments is vital. Adenosine triphosphate (ATP) serves as a parameter for viability assessments due to its presence in viable bacterial cells as an energy carrier. Traditional ATP detection methods involve chemical or enzymatic extraction, followed by measurement of light emission via the Luciferin–Luciferase complex. However, these methods are costly, present a low stability, require specialized equipment, and entail complex sample pretreatment. To overcome these limitations, we developed a biosensor based on aptamers, nucleic acid sequences with specific target-molecule-binding capabilities. Aptamers offer advantages such as an enhanced stability, a lower cost, and ease of design compared to antibodies. Recently, ATP has been used for aptamer selection testing. Our proposed biosensor utilizes a structure-switching ATP-binding DNA nanoswitch with two functional domains: a catalytic DNA-zyme domain and an ATP-binding aptamer domain. In the presence of ATP, its binding to the aptamer domain triggers the activation of the DNA-zyme domain, which is exploited for chemiluminescence (CL) detection. Integrating functional DNA biosensors with microfluidic paper-based analytical devices (µPADs) holds promise for point-of-care (POC) applications. However, achieving proper DNA binding on paper remains challenging, often requiring solution-based assay protocols, leaving µPADs for final signal readout. Here, we introduce an origami µPAD with preloaded dried reagents, allowing for on-paper assay execution upon sample addition and proper folding. Paper functionalization strategies and assay protocols were optimized to ensure simple and straightforward detection of ATP, employing a portable charge-coupled device (CCD) camera for CL detection. Calibration curves plotted against the logarithm of ATP concentration in the range of 1 to 500 µM facilitated determination of the assay's limit of detection (LOD), which was found to be 3 µM.

Seafood is known for its mineral, vitamin, and polyunsaturated fatty acid content, which means that its consumption is related to several health benefits. Moreover, fish products are characterized by their high water activity, pH, and nutrient content, especially non-protein nitrogen (NPN) compounds. Because of their composition, fish products are one of the most perishable foods, so the shelf life maintenance of these products is a challenge for the food industry. Seafood spoilage occurs because of biochemical reactions or/and because of the metabolic activity of naturally present microorganisms, producing alterations in the product that negatively affect its sensory characteristics and make it unsuitable for consumption. Moreover, the spoilage produced in fish products is the leading cause of fish losses globally, creating a sustainability problem. Despite the challenge of investigating the deterioration and degradation process of fish freshness, research related to biosensors as flexible and reliable devices to detect fish quality attributes in different scenarios has exponentially risen in the past few years. Among biosensors, bionanosensors stand out since they provide consumers with information in response to changes in internal or external quality and safety parameters of raw materials and/or their environment, ensuring food quality and safety. This communication is a review of how different nanobiosensors (bioreceptors, transducers, and optical biosensors) may help extend seafood shelf life, guaranteeing its quality and safety during storage, as well as the main challenges associated with these devices (e.g., the limited application in biological systems), together with the future perspectives to overcome these limitations. For this purpose, keywords were used in different databases and the data from the information collected were analysed.

Current food safety techniques and equipment are struggling to meet the evolving demands of the food industry. Traditional practices rely on reactive measures, leading to delays in monitoring, early warnings, and risk assessments, thereby impeding their effectiveness in risk mitigation. The integration of nanotechnology and biosensors into food sensing offers significant advantages, including enhanced speed, cost-effectiveness, and on-site detection, surpassing the capabilities of larger analytical tools. This integration is pivotal for the early detection of pathogens, the effective control of fresh food, and the prevention of food-borne illnesses by identifying spoilage before it reaches consumers. Nevertheless, biosensors based on antibodies or aptamers face limitations in lifetime and stability that impact their commercial viability. To overcome these challenges, researchers are turning to artificial intelligence as a groundbreaking solution. The application of machine learning, also known as deep learning, has the potential to transform conventional biosensors into intelligent systems capable of automated analyte prediction through a decision-making process. This facilitates the control of harmful substances during food traceability processing. However, this innovative convergence has raised ethical and privacy concerns that demand careful consideration [1–5]. This review evaluates the integration of artificial intelligence into biosensors, aiming to create cost-effective, real-time recognition devices for the identification of contaminants in food matrices.

Introduction: The rate of recruiting a target analyte on a receptor-functionalized electrode is a limiting step in most electrochemical biosensors, and is predominantly diffusion-controlled. Enhancing the interaction dynamics between the target analyte and the electrode-immobilized receptors offer great potential for improving electrochemical assay parameters in terms of assay time and sensitivity. Nanostructured electrodes, such as those modified with nanoparticles, can enhance the functional surface area; however, they have a limited ratio of sample volume to electrode surface area.

Methods: We propose the use of highly conductive mesh electrodes as a solid support for the immobilization of receptors (using antibodies as a model) and apply this in an electrochemical sensor that can be used for the detection of a range of target species. This approach involves coating commercially available mesh supports with low-fouling conductive polymers, which can be further modified with bio-receptors such as antibodies, proteins, or aptamers.

Results and conclusion: These functionalized mesh electrodes are employed for the isolation and detection of target biomarkers. The system is integrated within a 3D-rpinted microfluidic chip to allow real-time isolation and detection of the analytes under continuous flow using impedimetric, voltammetric, or amperometric assays. This integrated system allows for high target recovery within the mesh-like structures, overcoming the mass transport limitations associated with conventional disc or screen-printed electrode-based electrochemical assays. Additionally, this system is applied for dual-mode target isolation, where the mesh electrode enables size-based exclusion of the target analyte, thereby improving assay specificity. This method significantly boosts the ratio of sample volume to surface area (approximately a tenfold increase compared to disc electrodes), facilitating a more effective interaction between target analytes and receptors immobilized on the electrode. This augmentation is bolstered by the flow-through format of the system, as opposed to the traditional sample incubation method used with disc electrodes.

Introduction: Multilayer films incorporating chitosan (CHI) and hyaluronic acid (HA) offer significant potential for diverse biotechnological applications, particularly in early cancer detection, owing to the interaction between HA and the CD44 receptor, commonly overexpressed on circulating tumor cells (CTCs). This study pioneers the utilization of such films to enhance CTC adhesion on TI6Al4V alloy electrodes, manufactured through additive manufacturing for the development of biosensors. Therefore, establishing an effective deposition methodology for these films on electrodes is essential to optimize biosensor performance. The investigation of plasma pretreatment and a polyethyleneimine (PEI) film precursor layer on electrodes aims to improve the adhesion of multilayer coatings and surface properties, and consequently increase the selectivity and sensitivity of the biosensor for the detection of oncological diseases.

Methods: Ti6Al4V samples were mechanically sanded and cleaned, with certain electrodes undergoing additional plasma treatment and deposition of a PEI pre-layer. Multilayer films were deposited using the layer-by-layer technique. Surface characteristics of the Ti6Al4V electrodes before and after coating were evaluated, focusing on water affinity and topography relevant to cellular interaction. PC3 cells were cultured for adhesion studies on the electrodes.

Results: The application of the coating increased hydrophilicity, attributed to the well-known properties of HA. AFM analysis revealed a reduction in surface roughness after coating, possibly due to the filling of grooves by HA and CHI. Electrodes subjected to plasma pretreatment and PEI pre-layer deposition showed an intermediate roughness value, suggesting improved adhesion properties. The coated electrodes exhibited superior adhesion of PC3 prostate cancer cells, particularly those with pretreatments, consistent with the interaction of HA with CD44 receptors.

Conclusions: Plasma pretreatment and PEI pre-layer deposition further enhanced cell adhesion by facilitating effective polyelectrolyte deposition, resulting in increased roughness and potentially benefiting PC3 cell adhesion given their contact cell nature.

Point-of-care (POC) analysis has become a crucial method for delivering fast and convenient medical diagnostics. The use of smartphone-based solutions further enhances the accessibility and convenience of POC, facilitating efficient analysis on the go. Integrating smartphone technology with POC has led to innovative applications like the Vivoo app, which enables users to conveniently monitor various health parameters. TheVivoo app can detect bilirubin, ketone, leukocyte, pH, specific gravity, protein, magnesium, sodium, calcium, creatinine, vitamin C, and MDA parameters in the same way as existing biosensors. In our test, we performed the detections with the Smartphone-Based Point-of-Care Urinalysis Vivoo app and compared the results to existing biosensors. Our research aimed to confirm the accuracy and dependability of the Vivoo mobile application for urinalysis, using a comparative approach. We compared artificial urine samples analyzed through both the Vivoo app and traditional laboratory methods, assessing a wide range of health parameters. Throughout the study, we evaluated a total of 2618 strips using Vivoo. The results showed that these strips consistently matched the expected measurement results. Moreover, when we applied a ±1 color block acceptance criterion, 2608 out of 2618 measurements from the tested strips aligned perfectly with the expected results. Based on these findings, the 95% confidence interval for the exact match agreement proportion of Vivoo falls within 87.55% ± 1.27% and 99.62% ± 0.24%. Consequently, our study concludes that Vivoo is a reliable and high-performing device for wellness purposes. Its ability to provide precise and timely health insights holds great promise for improving individual health management, particularly in the context of smartphones' growing role in modern healthcare.

Nutrient quantification is crucial for hydroponic systems. However, reagent-less spectral quantification of nitrogen (N), phosphate (P), and potassium (K) encounters challenges in identifying information-rich spectral signals and separating interference from each component. We introduce the concept of 'information specificity, ’ as opposed to 'chemical specificity, ’ which requires physical or chemical reactions to isolate information from a specific nutrient in a complex hydroponic mixture. , the optical configuration used transmittance fiber optics with six illumination fibers and a center collection fiber. To study spectral interference and specificity of information of NPK in Hoagland nutrient solutions, a UV–Vis Deuterium/Halogen light source was used, emitting in the 200–550 nm range. 'Information Specificity' in spectral quantification is paramount to understand if the constituent is being quantified by its unique information and not by a spurious relationship present in the knowledgebase. This is especially relevant when resilient systems are necessary for application in harsh hydroponic conditions, where contamination that leads to spectral interference occurs. Herein, we show that nutrient Hoagland solutions exhibit spectral information specificity for N, P, and K, and this information is preserved in more complex samples obtained from uncontrolled fertirrigation production sites, allowing maximization of information about NPK, minimizing information about interferents, and allowing better predictions under extrapolation. We also present a method for overcoming extrapolation difficulties by data augmentation of the knowledge base by combining the spectral features of a small group of outlier samples and Hoagland nutrient solutions, greatly increasing the prediction accuracy of unknown samples under blind testing.

Enhancing the analytical performance of biosensors is a key factor in fabricating well-organized sensing platforms with high sensitivity. The main challenge in developing selective and sensitive biosensors is the lack of a sensing architecture that allows the detection of small biomolecules at low concentrations in crowded biological media. The functionality and stability of biosensors improve when the surface patterns are in a well-organized arrangement, and when biomaterials are present at a good density. It is common to use antibodies or aptamers as capture molecules for the target analyte, but they have limitations in terms of density and orientation when immobilized on sensor surfaces. Alternatively, simple non-toxic molecules such as folic acid (FA) can be used as recognition elements. They have the ability to construct nanostructures and produce sensing devices with good selectivity and sensitivity. In this study, the conjugation of FA to reduced graphene oxide (rGO) was prepared and then used to functionalize a glassy carbon electrochemical (GCE) electrode for the detection of breast cancer cells (MCF-7). The cyclic voltammetry (CV) technique was employed to characterize the electrochemical proficiency of the developed electrode for detecting MCF-7 cells. The rGO-FA nanobiocomposite demonstrated itself as a promising substrate, offering good electrochemical signals after capturing cancer cells in the range between 1 × 10³ and 1 × 10⁵ cells/mL. The CV results indicated the successful binding of the folate receptor overexpressed on the surface of the cell membrane in the MCF-7 cells to the rGO-FA-modified sensor. The simple design of rGO-FA/GCE showed good, reliable, and satisfactory performance, which may significantly contribute to the development of low-cost biosensors for future cancer diagnosis.

The aim of this work is the realization of a nanostructured platform for the rapid and selective determination of the FKBP12 protein in biological fluids, i.e., CSF and blood. FKBP12 is a peptidyl-prolyl cis-trans isomerase with a clear role both in neurodegenerative processes and in the anti-rejection response after surgical transplantation. The sensor platform is built on a QCM support on which plasmonic silver nanoparticles (AgNPs) are assembled. Self-assembled monolayers (SAMs) containing the GPS-SH1 receptor, specifically designed and synthesized to bind FKBP12, were prepared on the nanostructures using different anti-fouling molecular spacers.

The plasmonic nanostructures were obtained by electrodeposition and have manifold functions: increasing the sensitivity of QCM measurements as well as of creating a plasmonic coating for SERS and SPR applications. Exploring different experimental conditions for the electrodeposition, we prepared two different types of AgNPs: flower-like nanostructures and dendritic nanostructures. The AgNPs were characterized by means of UV-Vis and reflection spectroscopy, SEM, QCM, and contact angle. The body of the results showed that the preparation of the nanostructures was reproducible and provided homogeneous coating of the surface with the AgNP.

The SERS performance of the plasmonic nanoarchitectures was studied using Rhodamine 6G as the analyte, and the measurements revealed low detection limits for both nanostructures, indicating that the Ag dendrites are the most promising platform for the SERS-based nanosensor. QCM measurements have shown that the dendritic nanostructures functionalized with SAM containing GPS-SH1 allowed the detection of the FKPB12 protein at picomolar concentrations. Furthermore, it has been demonstrated that two proteins, i.e., BSA and IgG, present in the biological fluids of interest, do not interfere with the determination of FKBP12 when used at their physiological concentrations. Finally, it was found that the addition of ethanol, following the absorption of FKBP12 and/or interferents, allows the sensor to be fully regenerated.

Uric acid (UA) optical biosensor was developed in this study. Nanocomposites were synthesized using NaYF₄: Er³⁺/Yb³⁺ as the matrix and iron, cobalt, and copper (as dopants) at different rations, in a one-pot hydrothermal treatment. Nanocomposites were prepared with different ratios of Co and Cu while concentration of Fe was constant for all the variants. The detection of UA is based on measuring change in fluorescence signals of the nanocomposites in presence and absence of UA. Fe, Co, and Cu shows peroxidase-like activity which was used for oxidation of o-phenylenediamine (OPD) to 2,3-Diaminophenazine (DAP) in presence of uricase (UAO) to catalyze UA. The co-doped NaYF₄: Er³⁺/Yb³⁺ nanoparticles emit upconversion fluorescence with four typical emission peaks centered at 490 nm, 540 nm, 660 nm, and 800 nm under 980 nm near-infrared (NIR) irradiation which are attributed to transition from ²H_9/2, ⁴H_11/2, ⁴F_9/2 and ⁴I_9/2 to ground state ⁴I_15/2. DAP shows absorbance near 450 nm, the emitted fluorescence at 490nm gets quenched due to the inner filter effect. All the variants show quenching of fluorescence signal at 490 nm with different intensities. Intensity of blank signal with respect to (I_490(o)/I₄₉₀) were measured and are in proportion to UA concentration. Under optimized conditions, colorimetric and ratiometric linear range sensing for UA was 0.1-1 mM. Ratiometric fluorescence detection limit (S/N=3) was 0.66 µM. These results shows that the synthesized nanocomposites have great capability for the detection of UA using colorimetric and ratiometric dual-readout assay methods.