Search Results (3,340)

Capsaicinoids, mostly from chili peppers, are widely used in daily life. Capsaicinoids are considered to be markers for the identification of illegal cooking oil (ICO), which is a serious threat to public health. The identification of capsaicinoids can help reveal food-related fraud, thereby safeguarding consumers’ health. Here, a novel and ultrasensitive method was established with a signal amplification strategy for the detection of capsaicinoids. AuNPs@Fe₃O₄ nanocomposites were functionalized with 4-aminothiophenol (4-atp). After diazotization, 4-atp on AuNPs@Fe₃O₄ reacted with capsaicinoids and formed capsaicinoids-azo-atp-AuNPs@Fe₃O₄. Ultimately, capsaicinoids-azo-atp-AuNPs@Fe₃O₄ was dropped onto the surface of a screen-printed carbon electrode (SPCE) and detected via the differential pulse voltammetry (DPV) method. AuNPs@Fe₃O₄ nanocomposites increased the specific surface area of the electrode. Moreover, the diazotization–coupling reaction enriched the analytes on the electrode surface. Liquid–liquid extraction was used for sample pretreatment. Under a pH value of 9.0 and concentration of 0.20 mol/L for the supporting electrolyte, the linearity of capsaicinoids in ICO is from 0.10 to 10.00 ng/mL, and the limit of detection (S/N = 3) is 0.05 ng/mL. This method is ultra-sensitive, reliable, and cost-effective for the detection of capsaicinoids. Herein, this method provides a promising tool for the identification of ICO. Full article

Due to the frailty of elderly individuals’ physical condition, falling can lead to severe bodily injuries. Effective fall detection can significantly reduce the occurrence of such incidents. However, current fall detection methods heavily rely on visual and multi-sensor devices, which incur higher costs and complex wearable designs, limiting their wide-ranging applicability. In this paper, we propose a fall detection method based on nursing aids integrated with multi-array flexible tactile sensors. We design a kind of multi-array capacitive tactile sensor and arrange the distribution of tactile sensors on the foot based on plantar force analysis and measure tactile sequences from the sole of the foot to develop a dataset. Then we construct a fall detection model based on a graph convolution neural network and long-short term memory network (GCN-LSTM), where the GCN module and LSTM module separately extract spatial and temporal features from the tactile sequences, achieving detection on tactile data of foot and walking states for specific time series in the future. Experiments are carried out with the fall detection model, the Mean Squared Error (MSE) of the predicted tactile data of the foot at the next time step is 0.0716, with the fall detection accuracy of 96.36%. What is more, the model can achieve fall detection on 5-time steps with 0.2-s intervals in the future with high confidence results. It exhibits outstanding performance, surpassing other baseline algorithms. Besides, we conduct experiments on different ground types and ground morphologies for fall detection, and the model showcases robust generalization capabilities. Full article

The coronavirus disease (COVID-19) pandemic has increased pressure to develop low-cost, compact, user-friendly, and ubiquitous virus sensors for monitoring infection outbreaks in communities and preventing economic damage resulting from city lockdowns. As proof of concept, we developed a wearable paper-based virus sensor based on a molecular imprinting technique, using a conductive polyaniline (PANI) polymer to detect the lentivirus as a test sample. This sensor detected the lentivirus with a 4181 TU/mL detection limit in liquid and 0.33% to 2.90% detection efficiency in aerosols at distances ranging from 30 cm to 60 cm. For fabrication, a mixture of a PANI monomer solution and virus were polymerized together to form a conductive PANI sensing element on a polyethylene terephthalate (PET) paper substrate. The sensing element exhibited formation of virus recognition sites after the removal of the virus via ultrasound sonication. A dry measurement technique was established that showed aerosol virus detection by the molecularly imprinted sensors within 1.5 h of virus spraying. This was based on the mechanism via which dispensing virus droplets on the PANI sensing element induced hybridization of the virus and molecularly imprinted virus recognition templates in PANI, influencing the conductivity of the PANI film upon drying. Interestingly, the paper-based virus sensor was easily integrated with a wearable face mask for the detection of viruses in aerosols. Since the paper sensor with molecular imprinting of virus recognition sites showed excellent stability in dry conditions for long periods of time, unlike biological reagents, this wearable biosensor will offer an alternative approach to monitoring virus infections in communities. Full article

We describe a machine learning (ML) approach to processing the signals collected from a COVID-19 optical-based detector. Multilayer perceptron (MLP) and support vector machine (SVM) were used to process both the raw data and the feature engineering data, and high performance for the qualitative detection of the SARS-CoV-2 virus with concentration down to 1 TCID₅₀/mL was achieved. Valid detection experiments contained 486 negative and 108 positive samples, and control experiments, in which biosensors without antibody functionalization were used to detect SARS-CoV-2, contained 36 negative samples and 732 positive samples. The data distribution patterns of the valid and control detection dataset, based on T-distributed stochastic neighbor embedding (t-SNE), were used to study the distinguishability between positive and negative samples and explain the ML prediction performance. This work demonstrates that ML can be a generalized effective approach to process the signals and the datasets of biosensors dependent on resonant modes as biosensing mechanism. Full article

Sesamol (SM) is a potent natural antioxidant that can quench free radicals and modulate the cholinergic system in the brain, thereby ameliorating memory and cognitive impairment in Alzheimer’s disease patients. Moreover, the total antioxidant capacity can be amplified by synergistic interactions between different antioxidants. Here, we constructed a ternary heterojunction graphitic carbon nitride/cupric sulfide/titanium dioxide (g-C₃N₄/CuS/TiO₂) photoelectrochemical (PEC) sensor for the quantification of SM and its synergistic interactions with other antioxidants. Crucially, the Schottky barrier in ternary semiconductors considerably enhances electron transfer. The PEC sensor showed a wide linear range for SM detection, ranging from 2 to 1277 μmol L⁻¹, and had a limit of detection of 1.8 μmol L⁻¹. Remarkably, this sensing platform could evaluate the synergism between SM and five typical lipid-soluble antioxidants: tert-butyl hydroquinone, vitamin E, butyl hydroxyanisole, propyl gallate, and butylated hydroxytoluene. Owing to its low redox potential, SM could reduce antioxidant radicals and promote their regeneration, which increased the overall antioxidant performance. The g-C₃N₄/CuS/TiO₂ PEC sensor exhibited high sensitivity, satisfactory selectivity, and stability, and was successfully applied for SM determination in both soybean and peanut oils. The findings of this study provide guidance for the development of nutritional foods, nutrition analysis, and the treatment of diseases caused by free radicals. Full article

The effective control of infectious diseases, including Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, depends on the availability of rapid and accurate monitoring techniques. However, conventional SARS-CoV-2 detection technologies do not support continuous self-detection and may lead to cross-infection when utilized in medical institutions. In this study, we introduce a prototype of a mask biosensor designed for the long-term collection and self-detection of SARS-CoV-2. The biosensor utilizes the average resonance Rayleigh scattering intensity of Au nanocluster-aptamers. The inter-mask surface serves as a medium for the long-term collection and concentration enhancement of SARS-CoV-2, while the heterogeneous-nucleation nanoclusters (NCs) contribute to the exceptional stability of Au NCs for up to 48 h, facilitated by the adhesion of Ti NCs. Additionally, the biosensors based on Au NC-aptamers exhibited high sensitivity for up to 1 h. Moreover, through the implementation of a support vector machine classifier, a significant number of point signals can be collected and differentiated, leading to improved biosensor accuracy. These biosensors offer a complementary wearable device-based method for diagnosing SARS-CoV-2, with a limit of detection of 10³ copies. Given their flexibility, the proposed biosensors possess tremendous potential for the continuous collection and sensitive self-detection of SARS-CoV-2 variants and other infectious pathogens. Full article

Point-of-care tests play an important role in serological diagnostics of infectious diseases and post-vaccination immunity monitoring, including in COVID-19. Currently, lateral flow tests dominate in this area and show good analytical performance. However, studies to improve the effectiveness of such tests remain important. In comparison with lateral flow tests, vertical flow immunoassays allow for a reduction in assay duration and the influence of the hook effect. Additionally, the use of carbon black nanoparticles (CNPs) as a color label can provide a lower detection limit (LOD) compared to conventional colloidal gold. Therefore, we have developed a vertical flow immunoassay for the detection of IgG against SARS-CoV-2 spike protein in human serum samples by applying a conjugate of CNPs with anti-human IgG mouse monoclonal antibodies (CNP@MAb). The vertical flow assay device consists of a plastic cassette with a hole on its top containing a nitrocellulose membrane coated with spike protein and an absorbent pad. The serum sample, washing buffer, and CNP@MAb flow vertically through the nitrocellulose membrane and absorbent pads, reducing assay time and simplifying the procedure. In positive samples, the interaction of CNP@MAb with anti-spike antibodies leads to the appearance of black spots, which can be visually detected. The developed method allows for rapid visual detection (5–7 min) of IgG vs. spike protein, with a LOD of 7.81 BAU/mL. It has been shown that an untrained operator can perform the assay and visually evaluate its results. Thus, the presented assay can be used in the further development of test systems for the serological diagnostics of COVID-19 or post-vaccination immunity monitoring. Full article

miRNAs are endogenous small, non-coding RNA molecules that function in post-transcriptional regulation of gene expression. Because miRNA plays a pivotal role in maintaining the intracellular environment, and abnormal expression has been found in many cancer diseases, detection of miRNA as a biomarker is important for early diagnosis of disease and study of miRNA function. However, because miRNA is present in extremely low concentrations in cells and many types of miRNAs with similar sequences are mixed, traditional gene detection methods are not suitable for miRNA detection. Therefore, in order to overcome this limitation, a signal amplification process is essential for high sensitivity. In particular, enzyme-free signal amplification systems such as DNAzyme systems have been developed for miRNA analysis with high specificity. DNAzymes have the advantage of being more stable in the physiological environment than enzymes, easy to chemically synthesize, and biocompatible. In this review, we summarize and introduce the methods using DNAzyme-based biosensors, especially with regard to various signal amplification methods for high sensitivity and strategies for improving detection specificity. We also discuss the current challenges and trends of these DNAzyme-based biosensors. Full article

Electrochemical immunosensors have shown great potential in clinical diagnosis, food safety, environmental protection, and other fields. The feasible and innovative combination of enzyme catalysis and other signal-amplified elements has yielded exciting progress in the development of electrochemical immunosensors. Alkaline phosphatase (ALP) is one of the most popularly used enzyme reporters in bioassays. It has been widely utilized to design electrochemical immunosensors owing to its significant advantages (e.g., high catalytic activity, high turnover number, and excellent substrate specificity). In this work, we summarized the achievements of electrochemical immunosensors with ALP as the signal reporter. We mainly focused on detection principles and signal amplification strategies and briefly discussed the challenges regarding how to further improve the performance of ALP-based immunoassays. Full article

At present, a large number of studies have demonstrated that miRNAs can be used as biological indicators for the diagnosis and treatment of diseases such as tumours and cancer, so it is important to develop a new miRNA detection platform. In this work, miRNA-122 is used as the basis for targeting detection agents. We have designed an unlabelled DNA1 that undergoes partial hybridisation and has a 20 T base long strand. The fluorescent signal in this experiment is derived from copper nanoclusters (CuNCs) generated on the circular T-long strand of DNA1. At the same time, DNA1 is able to react with miRNA-122 and achieve hydrolysis of the part bound to miRNA-122 via the action of nucleic acid exonuclease III (Exo III), leaving a part of the DNA, called DNA3, while releasing miRNA-122 to participate in the next reaction, thus achieving circular amplification. DNA3 is able to react with DNA2, which is bound to streptavidin magnetic beads (SIBs) and separated from the reaction solution via the application of a magnetic field. Overall, this is a fluorescence signal reduction experiment, and the strength of the fluorescence signal from the copper nanoclusters can determine whether the target miRNA-122 is present or not. The degree of fluorescence reduction indicates how much DNA1, and thus the amount of target miRNA-122, has been hydrolysed. By evaluating the variations in the fluorescence signal under optimised conditions, we discovered that this method has good sensitivity, with a detection limit as low as 0.46 nM, better than many other previous works on fluorescence signal-based biosensors for miRNA detection. This technique offers high discrimination and selectivity and can serve as a persuasive reference for early diagnosis. Full article

The development of biosensors for target detection plays a crucial role in advancing various fields of bioscience. This work presents the development of a genosensor that exploits the colorimetric phenol—sulfuric acid sugar reaction for the detection of DNA, and RNA as specific targets, and DNA intercalator molecules. The biosensor combines simplicity and reliability to create a novel bioassay for accurate and rapid analysis. A 96-well microplate based on a polystyrene polymer was used as the platform for an unmodified capture DNA immobilization via a silanization process and with (3-Aminopropyl) triethoxysilane (APTES). After that, a hybridization step was carried out to catch the target molecule, followed by adding phenol and sulfuric acid to quantify the amount of DNA or RNA sugar backbone. This reaction generated a yellow-orange color on the wells measured at 490 nm, which was proportional to the target concentration. Under the optimum conditions, a calibration curve was obtained for each target. The developed biosensor demonstrated high sensitivity, good selectivity, and linear response over a wide concentration range for DNA and RNA targets. Additionally, the biosensor was successfully employed for the detection of DNA intercalator agents that inhibited the hybridization of DNA complementary to the immobilized capture DNA. The developed biosensor offers a potential tool for sensitive and selective detection in various applications, including virus diagnosis, genetic analysis, pathogenic bacteria monitoring, and drug discovery. Full article

High-multiplex detection of protein biomarkers across tissue regions has been an attractive spatial biology approach due to significant advantages over traditional immunohistochemistry (IHC) methods. Different from most methods, spatial multiplex in situ tagging (MIST) transfers the spatial protein expression information to an ultrahigh-density, large-scale MIST array. This technique has been optimized to reach single-cell resolution by adoption of smaller array units and 30% 8-arm PEG polymer as transfer medium. Tissue cell nuclei stained with lamin B have been clearly visualized on the MIST arrays and are colocalized with detection of nine mouse brain markers. Pseudocells defined at 10 μm in size have been used to fully profile tissue regions including cells and the intercellular space. We showcased the versatility of our technology by successfully detecting 20 marker proteins in kidney samples with the addition of five minutes atop the duration of standard immunohistochemistry protocols. Spatial MIST is amenable to iterative staining and detection on the same tissue samples. When 25 proteins were co-detected on 1 mouse brain section for each round and 5 rounds were executed, an ultrahigh multiplexity of 125 proteins was obtained for each pseudocell. With its unique abilities, this single-cell spatial MIST technology has the potential to become an important method in advanced diagnosis of complex diseases. Full article

Here, we report magnetic nanoparticle-based biosensor platforms for the rapid detection of SARS-CoV-2 antibody responses in human serum. The use of the proposed system enabled the detection of anti-SARS-CoV-2 spike (S) and nucleocapsid (N) proteins at a concentration of ng/mL in both buffer and real serum samples. In particular, the protocol, which is considered an indicator of innate immunity after vaccination or post-infection, could be useful for the evaluation of antibody response. We included a total of 48 volunteers who either had COVID-19 but were not vaccinated or who had COVID-19 and were vaccinated with CoronoVac or Biontech. Briefly, in this study, which was planned as a cohort, serum samples were examined 3, 6, and 12 months from the time the volunteers’ showed symptoms of COVID-19 with respect to antibody response in the proposed system. Anti-S Ab and anti-N Ab were detected with a limit of detection of 0.98 and 0.89 ng/mL, respectively. These data were confirmed with the corresponding commercial an electrochemiluminescence immunoassay (ECLIA) assays. Compared with ECLIA, more stable data were obtained, especially for samples collected over 6 months. After this period, a drop in the antibody responses was observed. Our findings showed that it could be a useful platform for exploring the dynamics of the immune response, and the proposed system has translational use potential for the clinic. In conclusion, the MNP-based biosensor platform proposed in this study, together with its counterparts in previous studies, is a candidate for determining natural immunity and post-vaccination antibody response, as well as reducing the workload of medical personnel and paving the way for screening studies on vaccine efficacy. Full article

The abuse of antibiotics has caused a serious threat to human life and health. It is urgent to develop sensors that can detect multiple antibiotics quickly and efficiently. Biosensors are widely used in the field of antibiotic detection because of their high specificity. Advanced artificial intelligence/machine learning algorithms have allowed for remarkable achievements in image analysis and face recognition, but have not yet been widely used in the field of biosensors. Herein, this paper reviews the biosensors that have been widely used in the simultaneous detection of multiple antibiotics based on different detection mechanisms and biorecognition elements in recent years, and compares and analyzes their characteristics and specific applications. In particular, this review summarizes some AI/ML algorithms with excellent performance in the field of antibiotic detection, and which provide a platform for the intelligence of sensors and terminal apps portability. Furthermore, this review gives a short review of biosensors for the detection of multiple antibiotics. Full article

A new method to transfer the standard addition procedure for concentration determination to immunoassays with non-linear calibration curves was developed. The new method was successfully applied to simulated data and benchmarked against a state-of-the-art algorithm, showing a significantly improved performance with improvement factors between 2 and 192. The logit function was used to transform the immunoassay signal response of test samples spiked with known analyte concentrations. The relationship between logit(signal) and log-transformed estimated total analyte concentration is linear if the estimated total analyte concentration is correct. Finally, the new method was validated experimentally using different assays in varying, relevant complex matrices, such as serum, saliva, and milk. Different concentrations of testosterone and amitriptyline between 0.05 and 3.0 µg L⁻¹ were quantified using a binding inhibition assay in combination with reflectometric interference spectroscopy (RIfS) as the transduction principle. The sample concentration was calculated using a numerical method. Samples could be quantified with recoveries between 70 and 118%. The standard addition method accounts for individual matrix interference on the immunoassay by spiking the test sample itself. Although the experiments were carried out using RIfS, the method can be applied to any immunoassay that meets the analytical requirements. Full article