Oxidative stress is defined by an imbalance between the generation of reactive oxygen species and the biological system's ability to neutralize them. This condition is commonly linked to various pathological conditions [1]. Superoxide dismutase (SOD) is a widely used enzyme to assess oxidative stress, and various techniques have been developed for its detection in biological samples such as blood, urine, and saliva [2]. Surface-enhanced photoluminescence (PL) is a particularly sensitive method, offering minimal interference from the sample matrix [3]. In this work, silver nanostructured surfaces were implemented as substrates for the immunochemical determination of SOD in synthetic saliva through PL. The substrates were prepared using a single-step metal-assisted chemical etching method (MACE), resulting in the formation of silicon nanowires decorated with silver dendrites of approximately 1.5 μm in height [4]. For SOD detection, a three-step competitive immunoassay configuration was followed. Briefly, SOD was immobilized onto the substrates and then the functionalized substrates were incubated with mixtures of SOD with anti-SOD primary antibody, prepared either in assay buffer or synthetic saliva. Then, a solution of biotinylated anti-species specific antibody was added, followed by a reaction with streptavidin labelled with the fluorescent dye Rhodamine Red-X, and the signal was determined through an in-house developed optical set-up. The developed method presents similar or slightly lower sensitivity (detection limit 0.05 μg/mL) compared to the literature; however, it does not require labor-intensive sample pretreatment steps [5,6]. The aforementioned findings demonstrate the capability of the developed method to detect superoxide dismutase in natural saliva, in order to evaluate the oxidative stress status of an organism.

[1] Pizzino G., et al., Oxidat. Med. Cell. Longev. 2017 (2017), 8416763.

[2] L.A. MacMillan-Crow, D.L. Cruthirds, Free Radic. Res. 34 (2001) 325–336.

[3] Y. Jeong, et al., Biosens. Bioelectron. 111 (2018) 102-116.

[4] I. Kochylas, et al., Nanomaterials 11 (2021) 1760.

[5] M. Cottat, et al., J. Phys. Chem. C 119 (2015), 15532-15540.

[6] X. Yang, et al., Analyst 138 (2013), 3246-3252.

Coupling spectroscopic ellipsometry (SE), quartz crystal microbalance with dissipation (QCM-D), X-ray photoemission spectroscopy (XPS), and atomic force microscopy (AFM), we developed a multi-technique approach to characterize the surface immobilization of probe DNA strands, as a tool for the design of a DNA-based biosensor for the detection of disease-related oligonucleotide strands [1-3]. The hybridization of complementary target sequences is monitored through in situ, non-destructive, and real-time analysis.

The multiplexing detection of different oligonucleotide sequences is of great interest for differential diagnosis. To this end, we exploit AFM in a nanolithography mode to obtain micrometric platforms of thiolated DNA. Grafting is performed by removing previously chemisorbed inert alkanethiol SAMs and replacing them with short thiolated DNA molecules. Changing grafting parameters, DNA patches with different molecular densities were obtained. The analysis of images acquired in low-perturbative quantitative imaging (QI) mode highlighted the coexistence of molecular domains of different heights and thus different densities, which were not formerly observed using contact AFM imaging. By exposing the DNA platforms to target DNA (down to the nM level), all patches increased in height, indicating a successful hybridization. Comparing the height of the patches before and after hybridization showed a higher relative height increase in the less dense patches, indicating them as most suitable for targeting oligonucleotide sequences [4]. This method allows the grafting of different thiolated DNA strands onto the same substrate. Different sequences, characterized by 10 mismatches, were employed. Upon exposing the platform to different targets, a selective hybridization of specific probe DNA patches was observed, demonstrating efficient multiplexing targeting.

[1] G. Pinto, et al., 15 (2019) Soft Matter,11, 2463-2468.

[2] G. Pinto, et al., 13 (2020) Materials, 13,2888.

[3] G. Pinto, et al., 9 (2022) Adv. Mater. Interfaces, 9, 19, 2200364.

[4] S.M.C. Rotondi et al., 23 (2023) Biosensors, 9, 4557.

Introduction

In recent years, there has been development in the creation of biomimetic sensors, in which bioselectors are replaced by enzyme analogues that combine high sensitivity and stability. The requirements of a modern analysis are sensitivity, selectivity, low cost, simplicity and expressness. Biomimetic sensors perfectly meet these requirements. This work is devoted to the study of a catalase biomimetic sensor using a smart material, where metals such as Pb, Ag and Al were used as transducers.

Methods

Experimental studies of the electrode potential of the catalase reaction as a function of time were carried out using the potentiometric method. The experiments were carried out in an electrochemical cell consisting of a reference electrode (Ag/AgCl/AgCl^-) and biomimetic sensors. Double-distilled water served as a background solution.

Results

The experiments were carried out at various concentrations of H₂O₂. The presence of hydrogen peroxide in the system leads to a change in the value of ∆E, and an increase in the H₂O₂ concentration increases the jump in the electrochemical potential. The results showed that biomimetic sensors based on metals (Pb, Ag, Al), using smart material (TPhPFe³⁺/Al₂O₃), exhibit high sensitivity and detect the lowest trace concentrations of hydrogen peroxide in an aqueous solution.

Conclusions

The developed biosensors TPhPFe³⁺/Al₂O₃/Pb, TPhPFe³⁺/Al₂O₃/Al and TPhPFe³⁺/Al₂O₃/Ag of the catalase type are active and make it possible to determine trace concentrations of H₂O₂ in an aqueous solution.

Synthesized catalase biosensors are characterized by long-term stability, high sensitivity and reproducibility. The maximum sensitivity to the concentration of H₂O₂ in an aqueous solution for TPhPFe³⁺/Al₂O₃/Pb was 10^-8 wt.%; for TPhPFe³⁺/Al₂O₃/Al, it was –10^-6 wt.%; and for TPhPFe³⁺/Al₂O₃/Ag, it was –10^-8 wt.%.

Uric acid levels in sweat are indicative of various health conditions, including gout and cardiovascular diseases. A significant challenge in monitoring uric acid in sweat remains due to the low concentration of uric acid, which necessitates a substantial enhancement in the sensitivity of sensors in an economical manner. Thus, we have developed a new and low-cost method to improve the sensitivity of sensors with a non-smooth graphite surface using a scratched electrode.

Utilizing xurography, we constructed a compact, three-layered graphite sensor suitable for wearable applications, featuring a working electrode, counter electrode, and a reference electrode with a silver/silver chloride coating, all 1mm wide.

To integrate this development with smartphone-based biosensors, the enhanced graphite sensor's electrical signals are transmitted to a smartphone application, enabling the real-time monitoring and data analysis of uric acid levels in sweat. This connectivity not only augments the portability and convenience of health monitoring but also leverages the widespread availability of smartphones to facilitate accessible health management.

In testing, we prepared uric acid solutions in phosphate-buffered saline and measured them using Differential Pulse Voltammetry (DPV) with a PalmSens4 device. Sensors with different surface roughness were tested against uric acid solutions to evaluate their effect on sensitivity.

The results demonstrated that sensors with rougher surfaces detected uric acid at lower limits. Specifically, the limit of detection (LOD) with unscratched working electrodes was 100 µM, while with scratched surfaces, the LOD improved to 25 µM. The DPV profiles showed peak currents of 5.954 µA for smooth-surface sensors and 90.478 µA for roughened-surface ones, when detecting the high-concentration (1000µM) uric acid solution.

In conclusion, increasing the surface roughness of graphite electrodes significantly improves the sensitivity of uric acid detection in sweat. This study presents a low-cost yet effective method to increase the surface roughness, providing a reference for the more efficient fabrication of wearable uric acid sensors.

Water quality has a significant impact on public health. Inadequate water conditions are associated with diseases such as cholera, dysentery (shigella), hepatitis, and typhoid fever. Established techniques like Membrane Filtration (MF), Multiple Tube Fermentation (MTF), and enzyme-based defined substrate technology (DST) assays are used tomonitor bacteriological water quality, measuring indicators like Enterococcus faecalis (E. faecalis), Escherichia coli (E. coli), and total coliforms. Despite their high sensitivity and specificity, these methods take 24 to 48 hours to produce results, as well as requiring access to laboratory facilities, specialized equipment, sample preparation steps, and trained personnel. This study presents a portable and low-cost UV-LED/RGB water quality sensor which includes a microfluidic device, a fluorogenic defined substrate assay for the detection of E. faecalis, RGB sensors for fluorescent data acquisition, ultraviolet-light-emitting diode (UV-LED) for sample excitation, a portable incubation system, and embedded systems for data storage and processing. The microfluidic device has a number of independent wells used to carry out Most Probable Number (MPN) analysis for bacteria quantification. The device is pre-loaded with the defined substrate assay and is self-loading when immersed in the target water sample for sample-preparation-free analysis. RGB sensors detect fluorescence from each well to automate the MPN results. Results from fluorescence-versus-time curves are used to generate a comprehensive database. Machine learning (ML) algorithms and real-time RGB data are used to predict whether each individual well will be positive or negative using only the first three hours of fluorescent data. Coupled with MPN, this method significantly reduces the timeframe of bacteria detection and quantification, making it a cost-effective and efficient solution for on-the-go water quality monitoring, addressing critical public health concerns, and underscoring the importance of swift and reliable water quality assessments.

Nanomaterials based on plasmonic metal nanoparticles have great potential for medicine, pharmaceuticals and sensors. Their unique optical properties are due to the enhancement of local near fields under the influence of external electromagnetic waves upon the excitation of plasmon resonance. The optical properties of such nanomaterials depend on the characteristics of the nanoparticles: shape, size, material. Therefore, the development of methods for the formation of new nanoparticles with a given shape is an urgent task. The plasmon resonance effect can be especially useful for studying the optical properties of chiral molecules, since they give very weak chiroptical signals due to the difference between molecular sizes and the wavelength of incident light. One of the main methods for studying chiral molecules is circular dichroism spectroscopy (CD). It can be expected that in the field of chiral plasmonic nanoparticles, the CD signal of chiral molecules will also be enhanced.

The authors achieved the formation of chiral plasmonic silver nanocrescents using a combination of colloidal lithography and ion-plasma sputtering methods. The new technique makes it possible to obtain chiral nanocrescents of various orientations and widths by controlling the angles of deposition and sputtering. It was shown that the resulting nanoparticles are characterized by enhanced absorption at wavelengths of 470 nm, 655 nm, 1050 nm, and 1400 nm.

To sum up, a new formation method provides a rapid and inexpensive way of forming chiral nanocrescents. Along with the techniques commonly used to measure the optical properties of metal nanoparticles (extinction and fluorescence spectroscopy), we anticipate that CD will play an important role due to the number of effective ways it can be used to detect interactions between biomolecules and chiral plasmonic systems. Broader research is also needed to determine the relationship of crescent asymmetry with the CD signal and how to integrate such surfaces into functional commercial devices.

The increasing demand for high-quality and safe seafood necessitates the development of efficient monitoring systems to ensure the freshness and safety of fish products. In this research, we present an innovative approach utilizing a sensor array consisting of MQ137, MQ135, MQ3, MQ9, TGS 2610, TGS 2620, TGS 2600, and TGS 822 sensors. These sensors, sensitive to various gases associated with fish spoilage, are integrated into a comprehensive system for fish quality monitoring and spoilage detection. The developed system includes an array of chemical gas sensors, a data acquisition system, a processing unit for handling data, and a machine learning model for classification. The chemical gas sensor array enables the real-time detection of the volatile compounds released during the spoilage of fish. The data acquisition system collects and processes information from the sensor array, while the data processing system extracts relevant features for subsequent analysis. A pattern recognition system, employing a robust LDA-XGBoost model, was employed to differentiate between fresh and spoiled fish. The experimental results demonstrate the system's high accuracy in classifying fish quality, achieving an impressive classification accuracy of 96.12%. The integration of various sensors ensures sensitivity to a broad spectrum of chemical compounds associated with fish spoilage, enhancing the system's reliability. The proposed sensor-based approach provides a cost-effective, rapid, and accurate solution for fish quality monitoring, offering potential applications in the seafood industry to ensure the delivery of safe and fresh products to consumers.

In recent days, a digestive abnormality is common due to modern life-style and food habits followed. For every ten adults in the world, four suffer from functional gastrointestinal (GI) disorders of varying severity. Further, this is demonstrated by a study of more than 73,000 people across 33 countries. Also, the subjects who have undergone surgery/medication may feel healthy and they cannot feel or realize the internal health disorders, resulting in severe consequences. In this regard, an electrogastrogram (EGG) has gained more significance since it is non-invasive and involves an easy process for screening digestive abnormalities. EGGs are electrical signals, which have strong association with digestion. Also, the EGG can be recorded using non-invasive/surface electrodes. In this work, two different conductive textile materials, namely stainless steel fibers and Copper–Nickel-plated nylon, are utilised to fabricate non-invasive electrodes. Further, the developed electrodes are placed on the abdomen over the stomach and the EGG signals are acquired from healthy individuals. Also, various time and frequency domain features are extracted from two different EGG signals acquired using developed electrodes with different materials and are analysed. Additionally, the XAI, namely Shapley Additive Explanation (SHAP), technique is utilised to analyse and test the efficacy of the developed textile-based electrodes and to select the best electrode for EGG signal acquisition. This work appears to be highly significant since the developed electrode selected using the XAI tool shall possess a wide scope in wearable applications.

As a consequence of the COVID-19 pandemic, the early diagnosis and constant monitoring of respiratory issues have emerged as crucial public health goals. Although the respiratory system is the primary target of the disease's acute phase, subsequent complications of SARS-CoV-2 infection might trigger enduring respiratory problems and symptoms, according to new research. These signs and symptoms, which collectively inflict considerable strain on healthcare systems and people's quality of life, include but are not limited to congestion, shortness of breath, tightness in the chest, and a decrease in lung function. Wearable technology offers a promising remedy to this persistent issue by offering continuous respiratory parameter monitoring, facilitating early control of and intervention in post-COVID-19 respiratory issues. In an effort to enhance patient outcomes and reduce expenses related to healthcare, this paper examines the possibility of using wearable technology to provide remote surveillance and early diagnosis of respiratory problems in individuals suffering from COVID-19. In this work, a fog computing-based and cost-effective smart health monitoring device for infectious disease applications is proposed. The proposed device consists of three different biosensor modules, namely a MAX90614 infrared temperature sensor, a MAX30100 pulse oximeter, and a microphone sensor. All these sensor modules are connected to a fog computing device, i.e., a Raspberry PI microcontroller. Also, the three different sensor modules are integrated with the Raspberry PI microcontroller. The wearer's physiological parameters, such as oxygen saturation (SPO2), heart rate, and cough sounds, are recorded by the computing device. Additionally, a Convolutional Neural Network (CNN)-based deep learning algorithm, trained with normal and COVID-19 cough sounds from the KAGGLE database, is coded inside the Raspberry PI microcontroller. This work appears to be of high clinical significance since the fog computing-based smart heath monitoring device developed herein is capable of identifying the presence of infectious disease with individual physiological parameters.

Introduction: Multilayered films comprising chitosan (CHI) and hyaluronic acid (HA) have prominence in biotechnological applications due to their biocompatibility and capacity to enhance cell adhesion, particularly relevant in cancer research where the interaction between HA and CD44 aids in capturing circulating tumor cells (CTCs). The utilization of these films in biosensing platforms shows significant potential for early detection and monitoring of cancer. This study focuses on the functionalization of titanium electrodes with gold nanoparticles and nanostructured film (CHI-HA) to explore their potential in CTC detection.

Methodology: Ti6Al4V electrodes, were fuctionalized with gold nanoparticles through cyclic voltammetry, and depositing CHI/HA films using Layer-by-Layer technique. Surface morphology was analyzed with atomic force microscopy. PC3 cell adhesion studies were conducted to evaluate the effectiveness of the modified electrodes in promoting tumor cell attachment.

Results: Electrochemical characterization supported the efficacy of cyclic voltammetry-deposited gold nanoparticles, confirming enhanced conductivity of the electrodes, crucial for biosensing applications. Roughness analysis indicated the gold coating's contribution to surface leveling, potentially optimizing interaction with biological molecules. CHI/HA film deposition introduced polymer islands, enhancing surface roughness and promoting cell adhesion. Adhesion studies showed a significant increase in tumor cell attachment on multilayer film-coated electrodes compared to uncoated ones, suggesting their potential for tumor cell detection and CTC capture. Overall, the combination of gold nanoparticle functionalization and CHI/HA film deposition improved conductivity, surface roughness, and tumor cell adhesion properties, promising for cancer diagnostics. Further optimization and validation studies are necessary to fully exploit these electrodes' capabilities in clinical settings

Conclusion: The study presents the effectiveness of gold nanoparticle functionalization and CHI/HA film deposition in enhancing tumor cell adhesion on electrode surfaces. Provinding solid basis for further research in refining fabrication processes and exploring additional functionalities to augment their performance in clinical cancer detection applications.