Sensing and Bio-Sensing Research最新文献

The demand for analysing biological molecules such as dopamine (DA), ascorbic acid (AA), and uric acid (UA) is growing more than ever in applied science for better health and medicine. Over the past two decades, molecular imprinted polmers (MIPs) have been developed as synthetic receptors or substitute materials for antibodies due to their high stability, short time needed for electropolymerization, and high specificity towards the target analyte. However, the sensitivity of electrochemical sensors decreased as a result of MIPs' low conductivity and lack of electrocatalytic activity. To overcome this limitation, nanomaterials such as gold nanoparticles (AuNPs), carbon nanotubes (CNTs), graphene (GR), titanium carbide MXene (Ti₃C₂T_x), carbon dots (CDs), molybdenum diselenide (MoSe₂), and black phosphorus quantum dots (BPQDs) and their nanocomposites have been employed as biosensing transducers to construct MIPs based on electrochemical biosensors for cost-effective detection of biological molecules with high sensitivity and specificity. This is because the high surface area, good electrical conductivity, and ease of functionalization of nanomaterials all increase MIP sensitivity to targeted biological molecules. When these advantages of nanomaterials are combined with those of electrochemical methods, such as rapid response time, ease of use, low cost, and miniature ability, MIPs based on nanomaterial-modified electrodes are widely preferred tools for sensing AA, DA, and UA. Herein, this review provides insight into recent developments in the application of molecularly imprinted polymer (MIP) nanomaterial-based electrochemical biosensors for detecting biological molecules, including AA, DA, and UA. The integration of nanomaterials with MIPs into electrochemical biosensors has led to an unprecedented impact on improving the limit of detection of biomolecules, indicating great potential for use in public health and medical care.

The early-stage diagnosis and monitoring of disease evolution is still one of the most challenging tasks in the field of cancer research. Several research have been driven toward the discovery of new cancer biomarkers as well as to the development of biosensors able to detect these biomarkers with high specificity and sensitivity. Many types of cancer have been detected at an advanced stage and, in particular, epithelial ovarian cancer (EOC) has a high incidence of diagnosis in the metastatic stage. This cancer is considered as the most aggressive type of gynecological cancer with a 5-year survival and until now, no specific biomarkers have been identified. Nevertheless, some studies have indicated that mesothelin, a protein overexpressed by tumour cells in the ovary, interacts with the CA-125 biomarker present in the blood system accelerating the metastatic process. Therefore, the simultaneous presence of CA-125 and mesothelin in the blood during the evolution of EOC could be used to diagnose this disease before the metastasis. Therefore, with this motivation, this work aimed at the development of a biosensor capable of simultaneously detecting mesothelin and CA-125 at low concentrations. A biosensor based on the surface plasmon resonance imaging (SPRi) technique was developed and gold nanoparticles (AuNPs) were used in order to enhance the sensitivity. The study analysed successive injections of the biomarkers CA-125 and mesothelin, both in solution (analytical range of 9–120 nM). The limits of detection were obtained for CA-125 and mesothelin, being of 3.03 nM and 13.62 nM, respectively. The biosensor detected mesothelin at a concentration close to the cutoff point for EOC (3 nM) and was able to detect the biomarker CA-125 at 9 nM. Furthermore, the biosensor interacted preferentially and simultaneously with the biomarkers CA-125 and mesothelin incubated in fetal bovine serum. Finally, the use of AuNPs increased the sensor signal for CA-125 detection compared to its direct detection and showed greater selectivity for both biomarkers. Therefore, the biosensor has important characteristics that allow testing with real samples. In a future project, it could be applied in the research of diagnosis and prognosis of EOC.

Marburg Virus is one of the most neglected diseases that dated back to 1967. Prior to the 21st century, the outbreak of the virus was recorded trice, In 1967, 1998 and 2004. Accurate and early detection of pathogenic viruses such as Marburg, Ebola, Zika, Human Immunodeficiency Virus (HIV), Dengue, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-COV-2) etc. is crucial for treatment and prevention. In the Last 2 decades, scientists relied on molecular diagnostic assays which include antigen-antibody and nucleic acid-based testing approaches for the detection of pathogenic viruses, bacteria, fungi and pathogenic surveillances. Despite the widely used of these assays, they are hindered by several factors which includes high cost, the use of expensive tools, long turnaround time, the use of chemicals and the need for trained personnel. In order to counter some of these challenges, scientists developed Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-based biosensor characterized by high specificity. Integration of CRISPR-based biosensor with nanomaterials have shown to increase the performance of the biosensors. Thus, this review provides extensive knowledge on the pathogenicity of Zika and Marburg viruses, conventional diagnosis and the prospect of CRISPR-Cas toolbox in conducting accurate diagnosis of these viruses. The review cover 6 sections which include introduction as section 1, overview of the pathogenicity of Ebola and Marburg viruses in terms of pathology, transmission, number of cases are discussed in section 2, conventional approaches are covered in section 3, CRISPR/Cas systems in both prokaryotic and eukaryotic are overviewed in section 4, the link between CRISPR/Cas system and detection of Ebola and Marburg viruses are presented in section 5, open research and issues are highlighted in section 6 while section 7 covers the concluding remarks.

In this research, the synthesis, fabrication steps and characterization of a new modified glassy carbon electrode (GCE) with CuFe₂O₄ magnetic nanoparticles combined with zeolitic imidazolate framework (ZIF-8) embedded graphene quantum dots (GQDs), (CuFe₂O₄/ZIF-8@GQDs), for electrodetermination of the imatinib (IMB), anti-cancer drug, are reported. The synthesized nanocomposite was characterized using X-ray powder diffraction (XRD), energy dispersive X-ray spectroscopy (EDX) and field emission scanning electron microscopy (FE-SEM). The GCE modified with CuFe₂O₄/ZIF-8@GQDs nanocomposite shows high electrocatalytic activity toward the oxidation of IMB compared with the bare GCE, GQDs/GCE, ZIF-8@GQDs/GCE, CuFe₂O₄/GCE and CuFe₂O₄@GQDs/GCE. The resulted electrocatalytic activity of the CuFe₂O₄/ZIF-8@GQDs/GCE can be attributed to the synergistic effect of the outstanding magnetic, electrical properties of the CuFe₂O₄/ZIF-8@GQDs and high conductivity of GQDs, as well as the high electron transport rate of the nanocomposite. Under optimized conditions, the developed sensor, CuFe₂O₄/ZIF-8@GQDs/GCE, has static properties such as wide linear range responses (0.02–11.85 and 11.85–94.20 μM), low detection limit (1.2 nM), high sensitivity (5.655 μA μM⁻¹), long-term signal stability and reproducibility (RSD = 2.23%). It should be noted that the CuFe₂O₄/ZIF-8@GQDs/GCE sensor could be used for determination of IMB in biological and pharmaceutical samples, indicating its feasibility for real analysis.

This article investigates the design of a surface plasmon resonance (SPR) sensor that utilizes carbon nanotubes (CNT) and graphene to detect formalin concentration in water. The proposed sensor's design optimization and performance evaluation are achieved by implementing Gradient Boosting Regression (GBR), a machine learning (ML) algorithm, and the artificial hummingbird algorithm. An iterative transfer matrix technique is employed to create training and test sets for machine learning analysis, and a dataset of 8505 × 8 is obtained. The optimized thickness of Ag, CNT, and graphene 51.71 nm, 0.489 nm, and 4.32 nm were obtained using the artificial hummingbird algorithm. The results demonstrate that the SPR sensor achieves excellent reflectance curves, leading to a significant increase in detection sensitivity of 340.44 deg./RIU. Other characteristic parameters such as detection accuracy (DA), full width at half maximum (FWHM), and figure of merit (FoM) have also been evaluated.

Nerve agents are highly toxic chemical compounds that pose significant threats to human health and safety. Detecting and identifying these agents quickly is crucial for preventing their exposure and providing timely treatment. This study proposes the use of nanohybrids comprising crystalline octahedral molybdenum iodide cluster material supported on graphene (Mo₆@Graphene) as a novel sensing material for the detection of dimethyl methylphosphonate (DMMP), a simulant of sarin nerve agent. The electrical sensing performance towards different concentrations of DMMP and at room temperature demonstrated fast and sensitive responses to DMMP, with almost full recovery of the sensor baseline in a few minutes. The calibration curve obtained showed a linear relationship between the sensor response and DMMP concentration, enabling the estimation of the limit of detection (LOD) of 270 ppb. The robustness of the Mo₆@Graphene nanomaterial towards DMMP was assessed using various techniques, including Raman spectroscopy, X-ray diffraction and photoelectron spectroscopy. The binding energies (BEs) between DMMP and the supported Mo₆ clusters determined by DFT calculations revealed H-bonding interactions involved in the sensing mechanism. The excellent sensing performance of the Mo₆@Graphene film, combined with its low power consumption and high stability, makes it a promising candidate for the detection of nerve agents and their simulants.

In this study, a selective SBA-15 /Fe₃O₄/Polyaniline /Chitosan nanocomposite was successfully electrodeposited on Screen- Printed Carbon Electrode (SPCE) and used for L-Tyrosine (Tyr) detection.

Biological diagnostic probes such as artificial receptors are one of the important diagnostic layers for the identification of vital biomolecules, including essential amino acids like Tyr. A new electrochemical sensing platform based on differential pulse voltammetry was prepared for selective determination of Tyr in milk samples.

SBA-15 nanoparticles were synthesized from corn leaves as a source of silica. These high-absorbance nanoparticles have been used for surface modification of SPCE. The morphology and electrochemical performance of the modified electrode were characterized by X-ray diffraction, scanning electron microscopy (SEM), transition electron microscopy (TEM), Furrier transform infrared spectroscopy (FTIR), Brunauer-Emmett–Teller techniques, electrochemical impedance spectroscopy (EIS), and cyclic voltammetry(CV).

As a novel modified electrode, the catalytic activity of the modified SPCE towards electro-oxidation of Tyr was measured by differential pulse voltammetry (DPV). The experimental conditions, including the adsorption time, scan rates, the ratio of SBA-15, pH value, and applied potential, are investigated in detail.

Electrochemical sensor based on SBA-15 (SPCE/SBA-15/Fe₃O₄/Polyaniline /Chitosan) Compared with SPCE/Fe₃O₄/Polyaniline/Chitosan shows good sensitivity, repeatability, reproducibility, low detection limit and high selectivity.

In addition, a linear correlation between oxidation peak current and concentration of Tyr in the ranges 0.1–250 μM with a detection limit of 0.05 μM (S/N = 3) was obtained. Eventually, the suggested sensor was used for quantification of Tyr in real samples, by adding standard solutions to the milk samples.

This study presents a quasi-online method for monitoring of dissolved volatile fatty acids (VFAs) in biogas fermentation processes with a carrier gas probe by use of thermo-cyclically operated metal oxide gas sensor arrays. Each of the two sensor arrays comprises a pure SnO₂ and three different SnO₂/additive-composites (additives: alumina, YSZ, NASICON) but differ by SnO₂ synthesis routes, namely Flame Spray Pyrolysis (FSP) and Sol-Gel (SG) technique, respectively. This allowed comparative studies of the influence of layer morphology on VFA sensing characteristics. For sensitive determination of the dissolved VFAs besides high concentrations of biogas components like CO or CH₄, first a pre-treatment routine of the fermentation sample was introduced to remove those physically dissolved gases without losing VFAs. The Conductance-over-Time-Profiles (CTPs) of eight different sensing layers were measured simultaneously at exposure to the gases extracted from the fermentation sample at different pH conditions. Almost all the investigated SnO₂/additive-composites show CTP-features clearly correlating with the undissociated VFA even at concentrations below 120 ppm as referenced by GC-analysis. The lower detection limit is well below inhibitory concentration for fermentation processes. As expected, most pronounced CTPs representing actual VFAs situation were measured at pH 3, well below the pKa of the VFAs. The FSP-layers highlighted clearly better sensitivity and CTP specificity of higher quality compared to SG-layers. Among the SnO₂/additives, the CTP-features of the SnO₂(FSP)/NASICON and SnO₂(SG)/NASICON layers showed the best specificity to acetic and propionic acid. For the first time, quasi-online analysis of VFAs using metal oxide gas sensors for early warning of VFA-development in biogas fermentation processes was demonstrated.

This work aims to design two-dimensional (2D) catalysts based ZnO and ZnS for CO₂ reduction reaction (CRR), nitrogen reduction reaction (NRR), CO₂ and N₂ captures and sensors. Cheap and abundant elements which are Mg, Cl, and N are doped into Zn, S, and O sites to tune the electronic properties of the ZnO and ZnS monolayers. Also, influences of O, S and Zn vacancies on the electronic properties and gas adsorption are examined as well. Adsorption energy, interaction energy, distortion energy, density of states, Bader charge, shift of Fermi level, and work function of the modified surfaces are studied via density functional theory (DFT) performed on VASP. From the results, Mg, Cl, and N doping as well as vacant sites can extremely change electronic properties, i.e., semiconductive to metallic behavior, the shift of Fermi level and the variation of work function. Some modified ZnS and ZnO monolayers can be good candidates CRR and NRR catalysts since neither too strong nor too light binding of CO₂, CO and N₂. The best catalysts for this study is (Mg, V_Zn)-ZnO and Cl-ZnS because both can be sensors and electrochemical catalysts due to the proper binding strength for CO₂, CO and N₂ adsorption. The change in the electronic properties leading to the change in gas adsorption shows that the ZnO and ZnS modification by cheap-element doping and vacancy-site creation are potential ways to improve their properties, extend their applications and lead to the invention promising catalysts for electrochemical reactions, gas sensors and gas storages.

A new label-free immunosensor containing cetyltrimethylammonium bromide (CTAB) intercalated-graphene oxide (GO) on a polythiophene (PTh) film one-step electrosynthetized is described for detection of hepatitis C antibodies (Anti-HCV). This electroactive film also acted as a substrate for immobilizing the biorecognition element. The ability of the biosensor to bind Anti-HCV was monitored by the square wave voltammetry (SWV) technique through the decrease in anodic peaks. The intercalation of GO nanosheets between CTAB and PTh was very stable, achieving a variation coefficient of approximately 0.65% for redox peaks after 30 cycles, and was also demonstrated as a diffusion-controlled process with excellent electrochemical reversibility. The immunosensor exhibited a linear response range from 0.2 to 8 ng∙mL⁻¹, good reproducibility (square R equal to 0.993, low relative error < 1%), and a limit of detection at 0.07 ng∙mL⁻¹ of Anti-HCV, achieving the clinical range for HCV diagnostic. Furthermore, this approach shows promise for constructing a practical and accurate immunosensor for HCV diagnostic and screening in chronic phases and monitoring other HCV biomarkers utilizing this technology.