Miniature diagnostic devices combined with powerful smartphone processors have revolutionized healthcare diagnostics by bringing it to our homes, where it was previously confined to laboratories. Smartphone-assisted glucose monitoring systems like iBGStar and iHealth exemplify this by incorporating glucometers in smartphones for data display, analysis and tracking of glucose levels. Inbuilt sensors in smartphones like cameras are being utilized as analytical tools in microfluidic and colourimetric assays for disease diagnosis, where the RGB (red, green blue) intensities can be quantified to determine the severity of the disease. During the COVID-19 pandemic, research in this field rapidly accelerated, as observed by the rapid development and commercial availability of many smartphone-based sensors like the iHealth and Ellume COVID-19 antigen detection kits and application software like the Arogya Setu app for contact tracing using Bluetooth assistance within small distances. AI-assisted Chabot and telehealth platforms further helped patients to remotely access doctors in limited resource settings, while the wearable sensors in smartwatches helped in personalized monitoring of physiological parameters. This promoted isolation of patients, which was a mandate for containment of the disease, indicating their significance in decentralised health management. Wearable sensors offer futuristic development using implantable biosensors, wherein tiny biosensor chips are placed under the skin or in the body to monitor various biological and physicochemical parameters, ranging from diabetes, cardiac movements, and brain activity to cancer biomarkers, in patients for precision and personalized healthcare. The review analyzes the sensing technologies employed in smartphone biosensors, further addressing the strengths and limitations of their integration within point-of-care devices. It concludes by focusing on the future direction of research and development and the potential of smartphone biosensors for personalized and decentralized health management.

Introduction: Even though significant advances have been made, there is still a lack of reliable sensors capable of non-invasively monitoring bilirubin and diagnosing jaundice as the most common neonatal disease, particularly at the point-of-care (POC) where blood sampling from infants is accompanied by serious challenges/concerns. Aiming to address this utmost important necessity, we herein introduce a smart, easy-to-fabricate/use sensing bioplatform that enables the non-invasive optical monitoring of bilirubin in saliva at the POC.

Methods: Herein, the high sensing capability of curcumin as a natural edible pigment is demonstrated in paper-based assays for the optical monitoring of bilirubin in saliva. To measure and quantify the fluorescence signals of the developed sensing bioplatform, we fabricated an Internet of Things (IoT)-enabled hand-held optoelectronic reader, enabling the smart POC diagnosis of jaundice and its therapeutic monitoring by clinicians remotely.

Results: The sensing mechanism behind the selective response of our developed sensor for bilirubin is based on bilirubin photoisomerization under blue light exposure, resulting in the selective recovery of the bilirubin-induced quenched fluorescence of curcumin. The sensor exhibited a linear range (0.5-20.5 μM) with r²=0.984, LOD=0.2 μM, and intra- and inter-day RSDs between 1.8% and 4.9%. The clinical analysis of the saliva of eleven jaundiced infants using our developed sensor strongly proved that it is amenable to be widely exploited in POC applications for bilirubin monitoring as there are excellent correlations (R=0.994, and R=0.99) between its results and those of reference methods for saliva and blood. We also recommended an IoT-based model capable of meeting the Healthcare 4.0 prerequisites.

Conclusions: The developed smart salivary sensor is believed to be highly promising for exploitation in the ultra-low-cost, non-toxic, easy, and non-invasive smart diagnosis and therapeutic monitoring of jaundice, hepatitis, and other bilirubin-induced neurologic diseases at the POC and in patient/home-centric healthcare systems, since it meets all of WHO’s REASSURED criteria for ideal diagnostic devices.

The field of biosensors has found great use for surface plasmon resonance (SPR), which has attracted attention for its multiple applications. With the goal of early cancer detection at the level of a single living cell, this research numerically investigates a very sensitive D-shaped fiber-optic biosensor based on surface plasmon resonance (SPR). The titanium oxide (TiO2) is coated on gold (Au), which is utilized as a thin-film plasmonic material in the suggested biosensor structure. The guiding of light in the fiber is modeled usingthe finite element technique (FEM) when six different types of healthy human cells and their malignant counterparts are exposed to its sensitive region. Refractive index (RI) differences between cancer cells and healthy cells are found through the analysis of the optical spectra and their amplitudes. This enables us to identify small changes in the optical characteristics of cells that could be a sign of pathogenic alterations. In this work, we concentrated on three forms of cancer: skin cancer (basal cell) and breast cancer (MDA-MB-231 and MCF-7). The results show which parameters are optimal to ensure that the sensor performs well when used to detect the three types of cancer under study. When the suggested sensor's performance is compared to SPR sensors that have previously been published in the literature, it becomes clear that our sensor offers great promise for early cancer detection.

In response to the environmental threat posed by xenobiotic aromatic pollutants in water, we have developed a compact device that integrates biosensor scaffolds with organic electronics. This innovative approach addresses the challenge of detecting these pollutants, which often lack easily detectable functional groups. Our sensor module is specifically designed for the rapid, economical, reliable, and ultra-sensitive detection of phenol, a common water pollutant. The key to our sensor’s functionality is the biosensing protein MopR, which we have coupled with an organic electrochemical transistor (OECT). To ensure the effective integration of the MopR sensing scaffold, we have optimized graphene oxide (GO) nanosheets to serve as a host immobilization matrix. This MopR-GO immobilized sensor module is then used as the gate electrode in the OECT, with PEDOT:PSS serving as the organic semiconductor material. The resulting OECT sensor offers a conducive microenvironment for protein activity, thereby maintaining high specificity in pollutant detection. It has demonstrated the ability to exclusively detect phenol with minimal sensitivity loss (less than 5% error), even in complex pollutant mixtures and real environmental samples. This fabrication strategy, which effectively combines biological biosensors with organic electronics, holds significant potential for the detection of a wide range of emerging pollutants. It represents a promising step towards more effective environmental monitoring and sustainability.

Biosensors employing DNA oligonucleotide probes and electrochemical readout have become valuable tools of growing importance in environmental analysis. DNA-based electrochemical aptasensors owe their broad applicability to the unique sensing properties of single-stranded oligonucleotides. Their appropriate design can result in DNA probes capable of achieving selective interactions with different analytes, such as heavy metal ions. Among these, the determination of Hg²⁺ in drinking water is still a pressing challenge due to the fact that high mercury concentrations are very harmful for human health, often leading to death.

The most common Hg²⁺-sensing mechanism utilizes mercury(II)'s affinity to thymine nucleobases. Various mechanisms of measurable signal generation triggered by ion–aptamer binding are known. The most common ones include the following: (i) Hg²⁺ binding by aptamers composed of thymines, where thymine bridges (T-Hg²⁺-T) are formed between two neighbouring DNA strands, (ii) a cooperative mechanism in which, apart from thymines, other nucleotides also support the adoption of a specific secondary DNA form (usually a 'hairpin’ or 'sandwich’ conformation), (iii) a competitive mechanism in which DNA with an initial 'hairpin' structure undergoes a conformational change under the influence of mercury(II) ion through its dissociation or by Hg²⁺-dependent hampering of DNA–DNA duplex formation. The selection of the signal generation mechanism is crucial for the design of aptasensors and their working parameters.

The research presented here describes comparative studies on different DNA aptamer sequences for Hg²⁺ detection according to different mechanisms. They include the formation of intra- and intermolecular T-Hg²⁺-T bridges. The thermodynamic stability of such probe–analyte complexes is compared to classical dsDNA duplexes. For this purpose, we use label-free methods, i.e. SPR or QCM, to measure the kinetics of ion–aptamer interactions. The final step is the application of the selected DNA-based receptor for the biofunctionalization of magneto-catalytic nanoparticles. Their use should further improve the performance of DNA biosensors.

The COVID-19 pandemic has motivated scientists to delve deeper into this area and create cutting-edge biosensors that have the potential to enhance sensing beyond the current state of the art in terms of cost and accuracy. Several sensors for virus detection have been developed using chemical and electrochemical approaches as their foundations. Nevertheless, achieving high performance and accurate identification is not trivial. Surface plasmon resonance (SPR)-based optical biosensors are one method to capture very minute changes accurately via label-free sensing. This work offers a numerical approach for an ultra-sensitive multilayered SPR-based biosensor that uses angular interrogation in the near-infrared (NIR) region to detect the novel coronavirus (SARS-CoV-2). The multi-layered biosensor consists of a plasmonic metal, a dielectric layer (MgF₂), and optimized 2D nanomaterial (MoS₂) layers. In order to achieve high sensitivity, the figure of merit (FoM), and detection accuracy, the proposed plasmonic sensor was engineered using the transfer matrix method and finite element method after a thorough investigation. This includes the selection of plasmonic metal and optimization for the different layers. Using the strong binding efficiency of the MoS₂ layer and the high dielectric constant of the MgF₂ layer, the biosensor configuration comprising a glass prism/Al/Au/MgF₂/MoS₂/sensing sample is observed to exhibit the highest sensitivity of 372°/RIU, FoM of 1690 RIU^-1, and detection accuracy of 4.54 degree^-1. According to the investigation's findings, the proposed biosensor numerically exhibits excellent performance in the NIR region, making it easier to employ in the field of biomedical sensing applications.

Introduction. Nearly 50% of the adult population has been exposed to parvovirus B19 (B19V). B19V has an elevated risk of transmission through blood and blood products as it is resistant to common inactivation procedures. Multiple studies have documented high IgM seroprevalence among blood donors that were recently exposed to B19V, which could pose a risk to blood safety programs. This study aimed to develop a lateral surface plasmon resonance (LSPR) U-Bent fiber optic biosensor (fob) that could screen B19V IgM.

Methods. A linear epitope against B19V was identified using Bepipred2.0 and commercially synthesized. The epitope was validated using ELISA against synthetic IgM control and then was tested against clinical B19V IgM samples. A label-free method was employed to mount the biotinylated epitope on the LSPR fob and then test the absorbance against B19V IgM. A bump in the spectral absorbance curve indicated that the sample was positive for B19V IgM. The fob was calibrated at each step, measuring the pre- and post-wash absorbance reading to accommodate the different buffers.

Results. The epitope demonstrated suitable reactivity against B19V IgM as demonstrated by ELISA. The label-free method was suitable in the identification of low levels of a synthetic B19V antibody with similar detection indices to B19V ELISA.

Discussion. Individuals who screen as B19V IgM-positive (that indicates recent infection) can then be screened for B19V DNA. The transfusion of B19V DNA-positive blood and blood products can lead to severe consequences for individuals who are hematologically stressed or immunocompromised. Multiple studies have documented the importance of screening for B19V especially among blood donors by the introduction of routine screening into their national blood safety programs. A sensitive and specific rapid test such as this LSPR fob would be very beneficial in the B19V screening.

This study investigated carbon-based electrode materials for the application of wearable biosensors measuring uric acid concentration. This investigation focused on assessing various combinations of carbon-based electrodes, such as CVD-graphite, graphene ink, and carbon nanotubes, aiming to enhance sensor performance. These carbon materials were deposited on stainless steel (SUS304 SS) plates (2 mm x 10 mm), and their sensitivity for detecting uric acid was evaluated by utilizing cyclic voltammetry (CV) and employing differential pulse voltammetry (DPV). Among the nine electrode combinations tested with potassium ferricyanide, two were identified that generated reversible CV waveforms, indicating their potential for uric acid detection. The effective combinations consisted of one set with CVD graphite for both the working and counter electrodes (WE and CE) and another set combining CVD graphite for the WE with carbon nanotube ink for the CE. The assessments demonstrated that these electrodes could efficiently detect the electron current from the redox reaction of ferricyanide, indicating their potential capability to measure uric acid concentrations effectively. Subsequent analysis using uric acid concentrations ranging from 100 µM to 400 µM showed that CVD-graphite electrodes provided distinct, quantifiable responses in both CV and DPV tests. Notably, the DPV profile for CVD-graphite displayed a significantly high peak current, facilitating the creation of a reliable calibration curve for uric acid concentration detection. The findings concluded that CVD-graphite stands out as the optimal material for both the WE and the CE in uric acid detection within sweat, with a practical detection limit (LOD) of 5.25 µM. This LOD is notably significant, aligning well with the average uric acid concentration in normal sweat, approximately 60 µM, thereby affirming the viability of these carbon-based electrodes for effective disease diagnosis and monitoring through wearable biosensors.

Leaf diseases pose a substantial threat to global agriculture, impacting crop yields and food security. Traditional methods of disease detection often prove time-consuming and labor-intensive, leading to delayed responses and increased losses. In response to this challenge, our research introduces an innovative solution that combines the power of deep learning techniques with targeted treatment recommendations.

Our methodology involves the development of a sophisticated deep learning model trained on a diverse dataset comprising images of leaves affected by various diseases. This model excels in accurate disease classification, enabling it to provide specific and nuanced treatment recommendations based on the identified pathogens. The integration of a user-friendly interface ensures accessibility for farmers with varying technological expertise, fostering seamless interaction with the system.

Extensive field trials conducted across diverse geographical regions and crop varieties validate the adaptability and reliability of our approach. The results affirm the potential of our system as a practical and scalable solution for real-world implementation in various agricultural settings.

Beyond accurate disease identification, our system contributes to sustainable farming practices by offering precision treatment strategies. By understanding the specific pathogens causing the disease, farmers can implement targeted interventions, reducing the reliance on broad-spectrum treatments and minimizing environmental impact.

In conclusion, our research presents a transformative paradigm for leaf disease management, combining the strengths of advanced deep learning technology, realtime processing, and user-friendly interfaces. This holistic approach positions our model as a valuable tool for farmers, empowering them with actionable information for informed decision-making, ultimately contributing to increased agricultural sustainability and food security.

Introduction. It was shown earlier that the use of Fast Protein Liquid Chromatography (FPLC) and low-cost deep-UV-LED-based optical chromatographic sensors with PD-10 desalting columns can facilitate monitoring of patients on peritoneal dialysis (PD). Previously, we established that the first peak in FPLC chromatograms is responsible for proteins and could be used for the assessment of peritoneal protein loss in patients with PD, while the origin and clinical significance of the other two peaks still remain unclear.

Methods. Optical absorption and fluorescence spectroscopy in the UV and visible regions 240…720 nm was used for the analysis of PD effluent fractions obtained with a chromatographic sensor with photometric detection at 280 nm; chromatograms of five samples were processed.

Results. The absorption and fluorescence spectra of the first fraction demonstrated peaks at 280 nm and 330 nm, respectively, which are characteristic of proteins. The absorption spectrum of the third fraction has maxima characteristics of creatinine and uric acid, while the second fraction surprisingly revealed no distinctive absorption bands. When it exited at 280 nm, the second fraction showed a single fluorescence maximum at 300 nm, while for the third fraction, there are maxima at 300, 300, 375 nm—the latter is characteristic of indoxyl sulfate.

For all three fractions, two fluorescence emission peaks are observed at longer excitation wavelengths, 300–320 nm, with the Stokes shifts of about 50 and 150 nm. The ratios of their amplitudes depend on the fraction. These peaks could probably be responsible for ascorbic acid, uridine, 3-indole acetic acid, and other metabolites.

Conclusions. It was demonstrated that deep-UV-LED-based affordable chromatographic sensors could provide sufficiently more information about PD effluents than just protein concentration, including the content of clinically significant metabolites, e.g., indoxyl sulfate. Moreover, the introduction of fluorescence detection could significantly improve the capabilities of such devices.