Sensing and Bio-Sensing Research最新文献

Capecitabine (CAP) is a chemotherapeutic agent used in cancer treatment, necessitating the development of sensitive and selective detection methods for its analysis in clinical samples. The present research utilized a simplified procedure for developing a novel electrochemical sensor based on a carbon paste electrode (CPE) modified with single-stranded DNA (ss-DNA), reduced graphene oxide (RGO), and molybdenum disulfide (MoS2). Unmodified (bare CPE) and modified (ss-DNA/RGO/MoS₂/CPE) electrodes were characterized by scanning electron microscopy (SEM), EDX analysis, and cyclic voltammetry (CV). Characterization data confirm the good conductivity and electrocatalytic nature with more electrochemically active sites in ss-DNA/RGO/MoS₂/CPE compared to bare CPE in the determination of CAP in real samples. Two linear ranges were obtained for CAP concentration within the ranges of 0.01–10.00 μM and 10.00–60.00 μM, with a detection limit of 0.0108 μM and a limit of quantification of 0.036 μM. The lower linear concentration range of 0.01–10.00 μM showed a sensitivity of 276.85 AM⁻¹ cm⁻², while the range of 10–60 μM had a sensitivity of 5.88 AM⁻¹ cm⁻². The performance of the modified electrode was tested in human serum samples, yielding satisfactory recovery results. The selectivity and practical ability of ss-DNA/RGO/MoS₂/CPE to determine CAP in the presence of different interfering species were investigated, demonstrating the sensor's selective, reliable, and accurate response.

In this study, a pioneering electrochemical sensor was developed for simultaneously determining nitrofurantoin (NFT) and furazolidone (FZD) residues in food and municipal wastewater samples. The sensor was prepared by integrating gold‑silver-alloy nanocoral clusters (Au-Ag-ANCCs) with zinc oxide nanoparticles (ZnO-NPs), carbon paste electrode (CPE) and polyethylene oxide (PEO) nanocomposites. The surface morphology and elemental compositions of Au-Ag-ANCCs/ZnO-NPs-CPE/PEO were characterized by FT-IR, XRD, SEM, EDX, EIS, and CV. The sensor showed exceptional performance over a wide linear range, from 1.0 pM to 250 μM for NFT and 0.9 nM to 360 μM for FZD. The detection and quantification limits were found to be 0.26 pM and 0.88 pM for NFT and 0.023 pM and 0.076 pM for FZD, respectively. In addition, the sensor exhibited excellent repeatability, reproducibility, selectivity, and long-lasting stability. When applied to the detection of AZM and ENF residues in poultry, fish, honey, dairy products and municipal wastewater, it exhibited excellent recoveries of 96.3–102.8% and relative standard deviations between 1.87% and 1.53%. In general, the developed sensor represents a significant advance in the fight against antibiotic residue pollution.

As water effluents are often highly contaminated with metals, having a quick and cost-effective method of analysis is crucial. This study used the supernatant derived from the green synthesis of silver nanoparticles (AgNPs) with Solanum mammosum to detect mercury, copper, and iron with a low-cost cellulose paper-based sensor and a rapid colorimetric method applying ultraviolet–visible spectroscopy (UV–Vis). AgNPs in two precursor concentrations using silver nitrate, 1 mM (17.4 ± 9 nm) and 50 mM (and 22 ± 8.1 nm), were utilized to assess the efficacy of the analysis and removal of Hg²⁺, Cu²⁺, and Fe³⁺ from contaminated water. Cellulose paper-based sensor showed limits of detection (LODs) for Hg²⁺ of 2.46 and 123 μM using AgNPs at concentrations of 1 and 50 mM, respectively. For Cu²⁺, the LODs were 55 and 2750 μM, and for Fe³⁺, the LODs were 49  and 2470 μM using the respective concentrations. To differentiate and detect the cations with the naked eye, a potassium iodide and potassium ferrocyanide (1:1) aqueous solution was used, producing a yellow, pink, and blue color for Hg²⁺, Cu²⁺, and Fe³⁺, respectively. Additionally, the titration curves of Hg²⁺, Fe³⁺, and Cu²⁺ were examined by UV–Vis using the supernatant liquid. The LODs for the UV–Vis method using AgNPs at a concentration of 1 mM were 1.50 μM for Hg²⁺, 10.7 μM for Cu²⁺, and 4.33 μM for Fe³⁺, while the LODs for AgNPs at 50 mM were 5.75, 27.6, and 15 μM for Hg²⁺, Cu²⁺, and Fe³⁺, respectively. Furthermore, these nanoparticles were utilized to assess the efficacy of the removal of Hg²⁺, Cu²⁺, and Fe³⁺ from contaminated water. Removal efficiency with the solid 50 mM AgNPs was analyzed via flame absorption spectrophotometry; values over 95% were obtained for the three ions. The results underscore the effectiveness of a green synthesis approach to generating AgNPs, enabling efficient and economical cation analysis and water decontamination.

This work thoroughly reviews nanotechnology's enormous impact on forensic investigations. Various forensic science applications, including explosives detection, chemical warfare agent analysis, latent print visualization, and DNA detection, have been made possible by the unique features of nanotechnology. Rapid and accurate results, simplified analysis processes, and increased sensitivity in evidence identification have all been made possible by its integration. By developing sophisticated nanosensors, nanomanipulators, and nanoimaging instruments, nanotechnology research has also transformed the field of criminal investigation. It has improved forensic methods like document analysis, dating bloodstains, and explosive detection. Nanotechnology holds the potential for more effective investigations and a revolutionary future in forensic science despite difficulties like standardization and expense. To fully realize the potential of nanotechnology for advancing forensic investigations and upholding justice, collaborative efforts and proactive solutions are required. This review provides in-depth knowledge of nanotechnology's function in forensic science and potential future applications.

Uric acid (UA) is a relevant biomarker that at abnormal levels could provide information for the timely diagnosis of chronic-degenerative diseases, such as Diabetes mellitus, cardiovascular deficiencies or gut. This work presents a simple surface functionalization of screen-printed carbon electrodes (SPCE) with cysteamine self-assembled monolayers (SAMs) assembled over electrodeposited gold nanoparticles (AuNPs). The modification allowed the immobilization of uricase enzyme, preserving its biocatalytic activity and resulting in sensitive and selective UA detection. The developed biosensor device exhibited a linear detection range from 100 μM – 1000 μM, a sensitivity of 6.622 nA/μM and a limit of detection (LOD) of 4.6 μM with selectivity to UA molecules over common interfering analytes. When evaluated in urine samples, the analytical capabilities of the PTSPCE/AuNPS/SAMs/Uox biosensor remained, achieving an average recovery rate of 126.91%. The obtained analytical parameters proved to be competitive when utilizing non-invasive fluids, suggesting the possibility of conducting detection assays with potential clinical applications using an implemented electrochemical biosensor through a simple, flexible, and reproducible methodology.

The article introducing an innovative exposed core SPR biosensor employing an asymmetrical elliptic air hole PCF known for remarkable sensitivity. Gold-plated fiber sensor detects changes in refractive index. This sensor effectively covers a RI scale of 1.28 to 1.42 for analytes, showcasing its versatility in simultaneous detection. Taking into account the RI change at the outer surface, attractive sensing implementations such as optimal wavelength sensitivity of 97,000 nm/RIU and optimal amplitude sensitivity of 529.20 RIU⁻¹ are attained. Furthermore, with a resolution of 9.09 × 10⁻⁶ RIU, a figure in merit of 170 RIU⁻¹, an FWHM of 570 nm, and a detection accuracy of 0.0166 nm⁻¹, the suggested sensor is impressive. This suggested sensor finds application in monitoring sucrose solutions across a spectrum ranging from 0% to 45% chemical concentration over time. It has an ideal amplitude sensitivity of 530.95 RIU⁻¹ and an ideal wavelength sensitivity of 10,000 nm/RIU for sucrose solutions at the 40% concentration level. Furthermore, the sensor shows an ideal wavelength sensitivity of 35,000 nm/RIU and an ideal amplitude sensitivity of 793.80 RIU⁻¹ for the detection of 2-propanol. Nevertheless, beyond sucrose noticing auspicious sensing qualities by the suggested sensor its feasibility for impact fully identifying a range of biochemical and organic samples. As a result, the proposed sensor holds promise as an exemplary choice the realms in biomedical sensing, the detection of lower RI analyses as well as chemical analysis. Streamlining practical application, the sensor's structure incorporates eight elliptical air holes, uncomplicated readily manufactural with existing technologies.

Meat and fish are the most resource-demanding food products with a high carbon footprint. However, worldwide, tons of meat and fish products that are still safe to consume are discarded as waste due to uncertainty about their freshness. This study evaluates the application of a newly developed electronic nose (e-nose) to assess the freshness level of chicken and turkey under regular processing conditions. The device, comprising a micro-cantilever sensor functionalized with a binder selective to the freshness biomarker cadaverine, is crucial in reducing this waste. Upon exposure to cadaverine, the sensor resonance frequency changes as a function of analyte concentration. Standard cadaverine concentrations are measured by High-Performance Liquid Chromatography (HPLC) and associated with the shelf-life estimation determined by sensory and microbial evaluations during an 18-day storage period (5 °C). The findings show that the sensory panel evaluates the meat as unsuitable between days 7 and 9, while bacterial data shows high bacterial levels after day 4. HPLC and e-nose data show increasing cadaverine levels after day 4, correlating well with the bacterial count. The data calibrates the electronic nose, demonstrating its potential as a shelf-life prediction tool, which can assist human sensorial evaluation and significantly reduce food waste.

The maintenance of good milk quality standards is still a challenge for dairy farmers that requires a rapid control system that is compatible with both the environment and production cost. A patented Hazard Analysis and Critical Control Points-like remote diagnostic (sensor driven) system named BEST was implemented to enable both quality monitoring and traceability in the dairy chain. BEST was daily tested in a dairy farm to identify new reliable indicators of anomalies (safety and quality) in milk production based on a Machine-Learning approach. The database obtained in four months of sensoristic analysis was subjected to a statistical study with AI algorithm to identify outliers. BEST proved ability to spot cows with specific characteristics in the whole herd's database. In particular, AI highlighted the sole cow from a different breed, the only cow that recently gave birth and the only cow in the herd that received treatment with the drug Micospectone® (Lincomycin + Spectinomycin).

The current study outlines four extremely sensitive SPR-based cancer sensors that have the highest sensitivity to date for the quick and accurate diagnosis of six major cancer cells, including adrenal gland, breast (t1/t2), cervical, blood, and skin cancer, where the first two are blamed as the most fatal and infected ones, respectively. Four nitrides—AlN, GaN, InN and Si₃N₄—are employed in four distinct sensor configurations to identify the aforementioned six cancer cell types. The sensor with AlN is found the most suitable for skin/breast (type-1) cancer detection with sensitivity (S) and quality factor (QF) of 370/385 Deg/RIU and 92/113 RIU⁻¹, the GaN based structure for adrenal gland/blood cancer detection with S and QF of 400/400 Deg/RIU and 108/102 RIU⁻¹, the InN-based structure for breast cancer (type-2) detection with S and QF of 414 Deg/RIU and 108 RIU⁻¹, and finally the Si₃N₄-based structure for cervical cancer detection with S and QF of 341 Deg/RIU and 92 RIU⁻¹, respectively. Furthermore, AlN and GaN based sensors can sense all the six types of cancer cells with a minimum sensitivity of around 230 Deg/RIU, an accepted number as per some recently reported results. Finite element method-based simulator COMSOL is used to study and optimize the structures considering an operating wavelength of 633 nm, anticipating for a low-cost sensor prototype. The highest reported sensitivity in this study is 414 Deg/RIU with QF of 108 RIU⁻¹ for the Au-Ag-InN configuration for the breast cancer (type-2) detection.

An infrared (IR) tunable perfect meta-absorber (TPM) is presented, which is configured of metal-insulator-metal (MIM) structure. The unit cell of the TPM device is composed of two opposite T-shaped and two rod-shaped Au resonators on the reflective mirror layer. The optimized feature size of TPM can achieve perfect absorption and the resonant wavelength can be tuned from blue-shift first and then red-shift by increasing the gap size between two T-shaped resonators continuously. The tuning process of red shift is linear. By changing the distance between two rod-shaped resonators, the TPM device exhibits red shift linearly. Moreover, TPM device shows polarization-dependent characteristic that the main absorption resonance can be attenuated from 100% to 0% by changing polarization angle from 0° to 90° of incident IR light. The resonance of TPM device has an excellent linear relationship with the ambient refractive index, and the sensitivity and maximum figure of merit (FOM) are calculated as 1249 nm/RIU and 21 RIU⁻¹, respectively. These results prove that the design of the proposed TPM device is very suitable for the use of IR sensing, polarization switching, and refractive index sensing applications.