Gold nanostars-enhanced Raman fingerprint strip for rapid detection of trace tetracycline in water samples

Analytical methods for determining environmental contaminants of concern in water and wastewater

Control and prevention of environmental pollution have emerged as paramount global concerns. Anthropogenic activities, such as industrial discharges, agricultural runoff, and improper waste disposal, introduce a wide range of contaminants into various ecosystems. These pollutants encompass organic and inorganic compounds, particulates, microorganisms, and disinfection by-products, posing severe threats to human health, ecosystems, and the environment. Effective monitoring methods are indispensable for assessing environmental quality, identifying pollution sources, and implementing remedial measures. This paper suggests that the development and utilization of highly advanced analytical tools are both essential for the analysis of contaminants in water samples, presenting a foundational hypothesis for the review. This paper comprehensively reviews the development and utilization of highly advanced analytical tools which is mandatory for the analysis of contaminants in water samples. Depending on the specific pollutants being studied, the choice of analytical methods widely varies. It also reveals insights into the diverse applications and effectiveness of these methods in assessing water quality and contaminant levels. By emphasizing the critical role of the reviewed monitoring methods, this review seeks to deepen the understanding of pollution challenges and inspire innovative monitoring solutions that contribute to a cleaner and more sustainable global environment.•Urgent global concerns: control and prevention of pollution from diverse sources.•Varied contaminants, diverse methods: comprehensive review of analytical tools.•Inspiring a sustainable future: innovative monitoring for a cleaner environment.

Dual-layers Raman reporter-tagged Au@Ag combined with core-satellite assemblies for SERS detection of Zearalenone

Zearalenone (ZEN) is a prevalent mycotoxin identified in corn. A SERS-based immunosensor by constructing core-satellite assemblies was developed for ZEN detection. ZEN monoclonal antibody modified gold nanostars (AuNSs) were fabricated as the capture probe (core). The Raman signal probes (satellites) utilized ZEN antigen linked to the core-shell structures loaded with two layers of Raman reporter molecules (AuMBA@AgMBANPs). The coupling between AuNSs and AuMBA@AgMBANPs can produce a poweful electromagnetic field, thus considerably amplifying the Raman signal. The detection range of ZEN for corn samples under the optimal conditions was 5 ∼ 400 μg/kg with a LOD of 3 μg/kg, which completely satisfying the requirement of maximum residual level (60 μg/kg). Moreover, the proposed SERS method was consistent with the HPLC-FLD method for the detection of ZEN in naturally contaminated corn samples (90.58% ∼ 105.29%). Conclusively, fabricated immunosensor with exceptional sensitivity and specificity broaden the application of SERS in mycotoxin detection.

A multiple lateral flow immunoassay based on AuNP for the detection of 5 chemical contaminants in milk

Melamine (MEL), enrofloxacin (ENR), sulfamethazine (SMZ), tetracycline (TC), and aflatoxin M₁ (AFM₁) are the main chemical contaminants in milk. It is necessary to detect these miscellaneous chemical contaminants in milk synchronously to ensure the safety of the milk. In this study, a multiple lateral flow immunoassay (LFIA) was developed for the detection of MEL, ENR, SMZ, TC, and AFM₁ in milk. Under optimal experimental conditions, the cutoff values were 25 ng/mL for MEL, 1 ng/mL for ENR, 2.5 ng/mL for SMZ, 2.5 ng/mL for TC, and 0.25 ng/mL for AFM₁ in milk samples. The limits of detection of LFIA were 0.173 ng/mL for MEL, 0.078 ng/mL for ENR, 0.059 ng/mL for SMZ, 0.082 ng/mL for TC, and 0.0064 ng/mL for AFM₁. The recovery rates of LFIA in milk were 83.2-104.4% for MEL, 76.5-127.3% for ENR, 96.8-113.5% for SMZ, 107.1-166.6% for TC, and 93.5-130.3% for AFM₁. The coefficients of variation were all less than 15%. As a whole, the developed multiple lateral flow immunoassay showed potential as a highly reliable and excellent tool for the rapid and sensitive screening of MEL, ENR, SMZ, TC, and AFM₁ in milk.

Ratiometric Sensing for Ultratrace Tetracycline Using Electrochemically Active Metal-Organic Frameworks as Response Signals

A novel ratiometric sensor using an electrochemically active metal-organic framework of Mo@MOF-808 and NH₂-UiO-66 as response signals was developed to detect tetracycline (TET) in ultratrace quantities. To achieve the dual-response strategy, Mo@MOF-808, with a reduction peak at -1.06 V, and NH₂-UiO-66, with an oxidation peak at 0.724 V, were used as signal probes directly. Concretely, Mo@MOF-808, single-stranded DNA (ssDNA), and complex system (Apt@NH₂-UiO-66) of aptamer (Apt) and NH₂-UiO-66 were sequentially immobilized on the electrode. With the addition of TET, Apt was hybridized with TET and Apt@NH₂-UiO-66 was detached from the electrode, resulting in an increase in the current at -1.06 V and a decrease in the current at 0.724 V. Through this strategy, the sensor achieved a wide linear range (0.1-10000 nM) and a low limit of detection (0.009792 nM) for TET. Moreover, the ratiometric sensor exhibited better sensitivity, reproducibility, and stability than a single-signal sensor. Furthermore, the constructed sensor was successfully applied to detect TET in milk samples, suggesting excellent application prospects.

Occurrence, source apportionment and source-specific risk assessment of antibiotics in a typical tributary of the Yellow River basin

The spatial distributions, sources, and source-specific risk apportionments of 26 antibiotics (5 categories) in the Fenhe River basin were determined based on sample data. The results showed that antibiotics were widely distributed in the surface water. There were significant differences between the different types of antibiotics, and the highest mean concentration was that of the sulfonamide category (33.74 ng/L), accounting for 36% of the total antibiotic concentration. Spatially, all antibiotics were mainly detected in the middle and downstream areas. The ecological risk assessment results showed that the significant risk rate of antibiotics accounted for 70% and was mainly distributed in the downstream area; however, the risks differed between the 5 categories. Quinolone antibiotics exhibited the highest significant risk rate, reaching 100%. The ecological risk associated with sulfamethoxazole was the highest among all detected antibiotics. The following five main factors influenced the antibiotic concentrations: aquaculture, pharmaceutical wastewater, livestock discharges, domestic sewage, and sewage treatment plants. Among these, pharmaceutical wastewater sources contributed the most (35%) to the total antibiotic concentration, and were distributed throughout the river. Although livestock discharges were not the main reason for the high level of ecological risk, these discharges were highest at certain sites in the midstream region. Different pollution sources posed different levels of ecological risk to the Fenhe River basin, the highest of which was pharmaceutical wastewater with a significant risk rate of 58%.

Impurities in polyvinylpyrrolidone: the key factor in the synthesis of gold nanostars

Control over the synthesis of anisotropic nanoparticles is crucial as slight differences in their size, shape, sharpness, or the number of tips in the case of gold nanostars, has an inordinate influence on their properties and functionality for future applications. Herein, we show that the supplier and purity of polyvinylpyrrolidone (PVP) can significantly alter the synthesis of gold nanostars, demonstrating that impurities, not PVP itself, are the main factor responsible for star-like shape formation. We demonstrate that in the presence of pure PVP and N,N-dimethylformamide, the use of hydrazine leads to the formation of branched nanoparticles. This synthetic approach opens the door to solving issues associated with the use of commercial PVP during the synthesis of gold nanostars.

A Review of Detection of Antibiotic Residues in Food by Surface-Enhanced Raman Spectroscopy

Antibiotics, as veterinary drugs, have made extremely important contributions to disease prevention and treatment in the animal breeding industry. However, the accumulation of antibiotics in animal food due to their overuse during animal feeding is a frequent occurrence, which in turn would cause serious harm to public health when they are consumed by humans. Antibiotic residues in food have become one of the central issues in global food safety. As a safety measure, rapid and effective analytical approaches for detecting these residues must be implemented to prevent contaminated products from reaching the consumers. Traditional analytical methods, such as liquid chromatography, liquid chromatography mass spectrometry, and capillary electrophoresis, involve time-consuming sample preparation and complicated operation and require expensive instrumentation. By comparison, surface-enhanced Raman spectroscopy (SERS) has excellent sensitivity and remarkably enhanced target recognition. Thus, SERS has become a promising alternative analytical method for detecting antibiotic residues, as it can provide an ultrasensitive fingerprint spectrum for the rapid and noninvasive detection of trace analytes. In this study, we comprehensively review the recent progress and advances that have been achieved in the use of SERS in antibiotic residue detection. We introduce and discuss the basic principles of SERS. We then present the prospects and challenges in the use of SERS in the detection of antibiotics in food. Finally, we summarize and discuss the current problems and future trends in the detection of antibiotics in food.

A highly reproducible SERS sensor based on an Au nanoparticles/graphene oxide hybrid nanocomposite for label-free quantitative detection of antibiotics

Ampicillin and nitrofurantoin, as broad-spectrum antibiotics, are widely used in the prevention of animal diseases and to ensure livestock growth. Large amounts of antibiotic residues exist in animal-derived foods, affecting food quality and safety, causing adverse side effects, such as allergic and toxic reactions, and increasing bacterial resistance. A sensitive surface enhanced Raman scattering (SERS) sensor is provided to detect low-concentration antibiotics (ampicillin and nitrofurantoin). The sensor is based on an Au nanoparticles/graphene oxide hybrid nanocomposite prepared by an in situ reduction method. The detection limits of ampicillin and nitrofurantoin are as low as 0.01 ng mL^-1 and 5 ng mL^-1, respectively. The relative spectral intensity of the nitrofurantoin characteristic peak has a good linear relationship with the concentration of nitrofurantoin in the range of 500 ng mL^-1 and 5 ng mL^-1 (R² = 0.99235). The structure also allows multi-sample measurement for a variety of antibiotics at the same time. The SERS sensor is easy to prepare, with high uniformity and reproducibility, and the sample does not require complex pretreatment and preparation. Sensitive and quantitative detection of antibiotics by the SERS sensor is of great interest in the fields of health care, food preparation, and environmental sampling.

Recent advances in biosensors for antibiotic detection: Selectivity and signal amplification with nanomaterials

Antibiotics are widely used in the prevention and treatment of infectious diseases in animals due to its bactericidal or bacteriostatic action. Residual antibiotics and their metabolites pose great threats to human and animal health, such as potential carcinogenic and mutagenic effects, and bacterial resistances. Therefore, it is necessary and urgent to accurately monitor trace amounts of antibiotics in food samples. Up to now, many analytical methods have been reported for the determination of antibiotics. Biosensors with the advantages of high sensitivity, rapid response, easy miniaturization, and low price have been widely applied to the detection of antibiotics residues in past decades. This review offered an in-depth evaluation of recognition elements for antibiotic residues in diverse food matrices. In addition, it presented a systematical and critical review on signal amplification via various materials, focusing on recently developed nanomaterials. Finally, the review provided an outlook on the future concepts to help upgrade the sensing techniques for antibiotics in food.

A Comparative Study of Approaches to Improve the Sensitivity of Lateral Flow Immunoassay of the Antibiotic Lincomycin

This study provides a comparative assessment of the various nanodispersed markers and related detection techniques used in the immunochromatographic detection of an antibiotic lincomycin (LIN). Improving the sensitivity of the competitive lateral flow immunoassay is important, given the increasing demands for the monitoring of chemical contaminants in food. Gold nanoparticles (AuNPs) and CdSe/ZnS quantum dots (QDs) were used for the development and comparison of three approaches for the lateral flow immunoassay (LFIA) of LIN, namely, colorimetric, fluorescence, and surface-enhanced Raman spectroscopy (SERS)-based LFIAs. It was demonstrated that, for colorimetric and fluorescence analysis, the detection limits were comparable at 0.4 and 0.2 ng/mL, respectively. A SERS-based method allowed achieving the gain of five orders of magnitude in the assay sensitivity (1.4 fg/mL) compared to conventional LFIAs. Therefore, an integration of a SERS reporter into the LFIA is a promising tool for extremely sensitive quantitative detection of target analytes. However, implementation of this time-consuming technique requires expensive equipment and skilled personnel. In contrast, conventional AuNP- and QD-based LFIAs can provide simple, rapid, and inexpensive point-of-care testing for practical use.

Pinacho D. Personalized Medicine for Antibiotics: The Role of Nanobiosensors in Therapeutic Drug Monitoring

Due to the high bacterial resistance to antibiotics (AB), it has become necessary to adjust the dose aimed at personalized medicine by means of therapeutic drug monitoring (TDM). TDM is a fundamental tool for measuring the concentration of drugs that have a limited or highly toxic dose in different body fluids, such as blood, plasma, serum, and urine, among others. Using different techniques that allow for the pharmacokinetic (PK) and pharmacodynamic (PD) analysis of the drug, TDM can reduce the risks inherent in treatment. Among these techniques, nanotechnology focused on biosensors, which are relevant due to their versatility, sensitivity, specificity, and low cost. They provide results in real time, using an element for biological recognition coupled to a signal transducer. This review describes recent advances in the quantification of AB using biosensors with a focus on TDM as a fundamental aspect of personalized medicine.