Sensors International最新文献

The present research article describes a newly designed sensing method for determining folic acid levels. Folic acid is a B vitamin that helps the body makes healthy new cells. It is also known as vitamin B9 or folic acid. A new folic acid biosensor was constructed based on dihydrofolic acid reductase (DHFR) immobilized on c-MWCNT/TiO₂NPs modified gold electrode. Prepared titanium dioxide nanoparticles have been characterized by Transmission electron microscope (TEM), X-Ray Diffractometer (XRD), and Fourier Transform Infrared spectroscopy (FTIR). Fabricated working gold electrode (i.e. DHFR/c-MWCNTs/TiO₂NPs/AuE) was characterized at various stages of its construction by Scanning electron microscope (SEM), electrochemical impedance spectroscopy (EIS), FTIR, and cyclic voltammetry to confirm its fabrication. The biosensor showed an optimum response at pH 7.5 and 35 ​°C temperature. The maximum current of the constructed folic acid biosensor was due to electrons generated at 0.125 ​V against Ag/AgCl electrode. The proposed biosensor showed a low detection limit (11.48 ​nM), a wide linear range (5 ​nM–50 ​nM), a sensitivity of 0.42 ​μA/nM/cm², and good storage stability. Folic acid biosensor was evaluated and utilized for folic acid level quantification in serum samples of pregnant women.

ABA (abscisic acid) is a phytohormone that is important in regulating stress and various pathological conditions in humans. ABA can be ingested exogenously or endogenously, and is naturally produced by stem cells, macrophages, and keratinocytes. ABA mediates immunological reactions such as phagocytosis, chemotaxis, and reactive oxygen species (ROS) production. In humans, LANCL2 serves as an ABA receptor. Depending on the signaling pathway involved, ABA can act as an inflammatory or anti-inflammatory agent. ABA plays a vital role in glucose tolerance, atherosclerosis treatment, prostate cancer dormancy, malaria, type 2 diabetes, and dementia. Various detection methods have been developed to detect ABA, including chromatographic, spectroscopic, and colorimetric assays, as well as high-performance liquid chromatography (HPLC) and mass spectrometry. Biosensors are commonly used to detect analytes in low concentrations. LSPR and FRET sensors are two types of biosensors that have been developed for the detection of ABA. LSPR sensors rely on light interacting with metal nanoparticles to detect analytes, while FRET sensors rely on energy transfer between a donor and acceptor molecule. LSPR sensors offer high sensitivity, label-free detection, and the ability to detect multiple targets simultaneously, while FRET sensors offer high specificity and customizability. Aptamers have recently been used as a substitute for antibodies in biosensors to provide higher sensitivity and lower cost. This review focuses on the role of ABA and the various biosensors used to detect it in the treatment of various diseases in mammals.

The novel coronavirus is the new member of the SARS family, which can cause mild to severe infection in the lungs and other vital organs like the heart, kidney and liver. For detecting COVID-19 from images, traditional ANN can be employed. This method begins by extracting the features and then feeding the features into a suitable classifier. The classification rate is not so high as feature extraction is dependent on the experimenters' expertise. To solve this drawback, a hybrid CNN–KNN-based model with 5-fold cross-validation is proposed to classify covid-19 or non-covid19 from CT scans of patients. At first, some pre-processing steps like contrast enhancement, median filtering, data augmentation, and image resizing are performed. Secondly, the entire dataset is divided into five equal sections or folds for training and testing. By doing 5-fold cross-validation, the generalization of the dataset is ensured and the overfitting of the network is prevented. The proposed CNN model consists of four convolutional layers, four max-pooling layers, and two fully connected layers combined with 23 layers. The CNN architecture is used as a feature extractor in this case. The features are taken from the CNN model's fourth convolutional layer and finally, the features are classified using K Nearest Neighbor rather than softmax for better accuracy. The proposed method is conducted over an augmented dataset of 4085 CT scan images. The average accuracy, precision, recall and F1 score of the proposed method after performing a 5-fold cross-validation is 98.26%, 99.42%,97.2% and 98.19%, respectively. The proposed method's accuracy is comparable with the existing works described further, where the state of the art and the custom CNN models were used. Hence, this proposed method can diagnose the COVID-19 patients with higher efficiency.

Tin Dioxide (SnO₂), carbazole based hypercrosslinked polymer (C-HCP), and C-HCP/SnO₂ nanocomposites by different C-HCP weight percent concentration (0.05–0.15 %wt.) were synthesized by precipitation method and used as sensing materials for ammonia sensor. These materials were applied for ammonia detection in various temperature (100–350 °C) and ammonia concentration (100, 200, and 300 ppm). The electrical conductivity of materials was measured at different temperature and decreasing of electrical conductivity observed by temperature increasing. The resistance of sensor in air to that in presence of ammonia was considered as sensor response. According to the results, SnO₂ had much greater conductivity than different concentration of C-HCP/SnO₂ composite under same conditions. The results showed that in maximum sensor response with adding the C-HCP in SnO₂, the optimum temperature decrease. The optimum temperature for SnO₂ and 0.05, 0.1, and 0.15 %wt. of C-HCP in SnO₂ composites was obtained 300 °C, 250 °C, 200 °C, and 150 °C, respectively. According to the results, the maximum sensor response observed 0.10 %wt. for ammonia detection at 200 °C. The 0.10 %wt. C-HCP in SnO₂ based sensor showed a response three times higher than that by pure SnO₂ in ammonia detection. Finally, the repeatability of sensors to the ammonia was obtained suitable in 3 continuous cycle and the response and reduction times of sensors was measured.

Coronavirus disease (COVID-19) is a new emerged contagious human-to-human infection that broke out in early December 2019, threatens global public health and causing widespread concern. The high lethality and transmission power of this virus introduce it as a dangerous factor and multiplies the importance of its rapid diagnosis. Tests like computerized tomography (CT) scan, and poly-chain reaction (PCR), were very popular at the beginning of the pandemic, But over time, taking into account the high rate of transmission of the disease, the need for fast and cost-effective diagnostic tests with significant sensitivity and specificity such as clustered regularly interspaced short palindromic repeats (CRISPR), Enzyme-Linked Immunosorbent Assay (ELISA), lateral flow assay (LFA), and biosensor was felt more. In this context, there is a global interest in the feasibility of employing nano-biosensors, especially those using carbon and its derivatives as a key material, for the real-time virus detection. The exceptional properties of carbon and the outstanding performance of nano-biosensors in identifying various viruses prompted a feasibility check on this technology. In this article, we have tried to introduce several carbon-based nano biosensors with various limits of detection (LOD) and different characteristics that have been used in identifying and limiting the spread of Covid-19.

In the current research, we have fabricated an amperometric immunosensor for the detection of breast cancer using HER2 antibody. The sensor was fabricated by immobilization of anti-HER2 antibody on the surface of pencil graphite electrode (PGE). The techniques used for the characterization of the PGE/anti-HER2 were cyclic voltammetry, scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS). The sensor was optimized in terms of pH, temperature, antigen concentration, response time and antibody concentration. A linear range amidst 1 fgml⁻¹ and 20 ngml⁻¹ was observed. The limit of detection was 1 ​fg/ml. HER2 levels were also determined in sera samples of apparently healthy persons and breast cancer patients. The authentication of the fabricated immunosensor was noticeable due to its good regeneration ability and storage stability.

In this paper, we report on the synthesis of strontium oxide nanoparticles (SONPs) using a novel probe sonication method. Powder X-ray diffraction (PXRD) was used to characterize the physicochemical properties of the prepared materials, which confirmed that the average SrO crystallite size was 43 ​nm. The Kubelka-Monk function of diffuse reflectance spectroscopy (DRS) was used to confirm the average energy gap of SONPs (4.06 ​eV). SONPs have been successfully used in conjunction with inventive photocatalysts to remove dyes such as Methylene Blue (MB) and Acid Green (AG). MBand AG dyes were used as standard dyes to investigate the photocatalytic properties of NPs when exposed to UV light and sunlight.These nanometal oxides photodegrade methylene blue (87.70%) and acid green (71.20%) dyes with remarkable efficiency when exposed to UV light. These nanometal oxides demonstrated superior sensitivity when paracetamol was used as an analyte in cyclic voltammetry tests at various scan speeds (10 ​mV/s to 50 ​mV/s). As a result, SONPs may be useful in photocatalytic activity and electrochemical sensor applications.

The CuFe₂O₄ nanoparticle has been successfully synthesized from bio-mediated (Aloe-Vera) combustion process. The structural characterization of synthesized nanoparticle was achieved by spectral-characterizations viz; XRD, SEM, FT-IR and optical examinations. The XRD studies displays a spinel cubic phase development of nanoparticle and its average-particle size (19.3 ​nm). Low band gap energy of synthesized nanoparticle has been recorded to be 2.84 ​eV using UV–Visible absorption spectroscopy, which impacts to higher photodegradation efficiency. The potential photocatalytic activity of synthesized nanoparticle was examined using Malachite Green (MG) organic dye as a model, which is performed under specific quantities of stock solution (60 ​ppm) and obtained nanoparticle (50 ​mg). The photodegradation efficiency of synthesized material was evaluated for MG dye degradation achieved with 87.5% at 140 ​min under Sun-light. The excellent oxidation-reduction peak potentials were observed for synthesized spinel ferrite nanoparticle modified with carbon paste investigated by electrochemical analysis using 0.1 ​M KCl in the different scan rates 0.01–0.05 ​V/s. The charge-discharge studies of CuFe₂O₄-graphite electrode at current density (0.4 A/g) was discussed which is well correspondence to pseudo-capacitive behaviour. The synthesized NPs through bio-resources extract has become a potential new insight into multiple practical applications.

Zinc oxide (ZnO) possesses unique nanostructures. Most ZnO nanostructures have yet seen its use as coating for fiber Bragg grating (FBG) sensors. The properties of zinc oxide nanostructure can be greatly influenced by different additives added with the precursor. This study reports on the influence of different concentration of hexamethylenetetramine (HMT) additive towards the humidity sensing capability of zinc oxide coated on FBG sensors. The synthesis of zinc oxide nanostructure was through a modified hydrothermal method. Morphology observation has confirmed a unique hybrid of nanoflake, and porous hemispherical growth of zinc oxide accompanied with elemental analysis for validation. Sensor response towards change in relative humidity is improved by 400% with functional range between 40 and 80 RH%. The concentration of HMT to achieve such performance is 0.05 ​M with a zinc acetate precursor. The device shows potency with its hybrid nanostructure when integrated with FBG based humidity sensor. Due to its functional range, it can detect relative humidity contents in the air for various industries. The fabricated sensing device is suited for use in industries with several magnetic equipment and requiring many sensor nodes for mapping of data.

Hybrid nanostructured materials currently offer a potential approach for a variety of applications due to improvements in their physio-chemical characteristics. Techniques for XRD, TEM-HRTEM, SAED, and UV-DRS were used to characterize the Cu₂ZnAl₂O₄ (CZA) material. Without any secondary phases and with an average crystallite size of 40 ​nm, X-ray diffraction pattern examination demonstrates the increased crystalline structure. A highly crystalline, polydisperse CZA nanostructure was visible using TEM-HRTEM and SAED. The CZA nanostructure's light-absorbing behavior is presented by UV-DRS analysis, which found that the predicted bandgap energy was 5.0 ​eV. In this article, we describe an easy chemical synthesis of a hybrid CZA nanostructure that works well as a catalyst to break down the acid red 88 (AR-88) dye under UV, sunlight, and low light conditions. Additionally, it was studied to determine how to modify the working electrode's surface to enable the detection of lead and tin metal ions. With 93.1% of degradation and comparison work on decolorizing AR-88 dye in the presence of both sunlight and darkness, CZA nanostructure was looked at as a potential catalyst for the decolorization of AR-88 dye. By using graphite electrode paste and cyclic voltammetry to analyze the synthesized sample in 1 ​N KCl, it was discovered that it had outstanding redox reaction and lead and tin detection capabilities.