Abstract: Quantification and identification of microplastics (MPs) (plastics < 5 mm) remain challenging due to the current laborious, inconsistent, and time-intensive measurement techniques. A promising time- and cost-effective alternative is staining with the fluorescent dye Nile red (NR). This review covers the wide range of NR staining methods, illumination conditions, and instrumentation for fluorescence-based detection and classification that have been developed thus far, highlighting the potential of NR fluorescence imaging to distinguish plastics. Despite notable advancements in NR staining techniques and conditions that have strengthened detection capabilities, there remains a need for further development and standardization of NR staining protocols, fluorescence imaging methods, and illumination instruments. We conduct a thorough assessment of both the advantages and limitations associated with diverse fluorescence imaging instruments, image segmentation, and classification techniques employed for detecting NR fluorescence and identifying polymer species. We also highlight critical considerations that should guide future research efforts to establish NR staining as a comprehensive, standalone method for environmental monitoring. They include investigating fluorescence behavior, especially intensity and Stokes shift, to understand the impact of solvent functional groups, plastic materials, additives and color pigments, weathering and application methods on NR sorption and fluorescence. Consideration of these factors will improve the ability to accurately identify polymer types based on their fluorescent behaviors, promoting widespread adoption of fluorescence imaging as a standalone method and enhancing cross-compatibility between NR studies.

Abstract: A novel electrochemical sensing approach was developed to detect DNA, RNA, and protein targets, utilizing the host–guest interaction between methylene blue (MB)-labeled probe and β-cyclodextrin-based nanocomposite (rGO/β-CDP). During the assay, the MB-labeled probe interacted with the corresponding target to form a probe/target complex. Due to steric hindrance, the formation of this complex reduced the amount of MB-labeled probes that can be captured by the β-cyclodextrin-based nanocomposite on the electrode surface, resulting in a measurable decrease in the electrochemical signal. Upon optimization, the sensing platform exhibited satisfactory analytical performance for three cancer-related model analytes: p53 DNA, microRNA-21 RNA, and thrombin protein, achieving low detection limits of 3.4 nM, 4.4 nM, and 5.7 pM, respectively. In this work, the electrochemical assay separates the detection process into two stages: target recognition in solution and signal transduction on the electrode surface. This fabrication effectively circumvents the issues associated with nonspecific conformational changes and the complicated probe installation procedures on electrode surfaces that are common in traditional sensing platforms. Integrating host–guest recognition with electrochemical assay, the developed approach not only advances the understanding of host–guest chemistry in sensor applications but also establishes a foundation for future innovations in the detection of biomarkers.

Abstract: This work reports the development and application of a new fluorescent nanoprobe sensor depending on using luminescent metal organic framework (LMOF). The developed sensor composed of hybridized Ca 1,3,5-benzenetricarboxylic acid metal organic framework with microcrystalline cellulose (Ca-BTC/MCC MOF) as a fluorescent probe for the determination of the monosodium glutamate (MSG), a non-chromophoric food additive. The developed sensor was characterized using a high-resolution scanning electron microscope (HR-SEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The Ca-BTC/MCC MOF hybrid, examined under the HR-SEM, showed morphological features different from the MCC and the Ca-BTC MOF. The diffraction patterns of Ca-BTC/MCC composites clearly displayed the characteristic Ca-BTC MOF diffraction bands, indicating that MCC was successfully incorporated in the formation of crystalline MOF hybrids. The FTIR spectra show the bands of MCC, as well as the bands of Ca-BTC MOFs. The prepared nanoprobe was successfully applied as a sensitive sensor for the determination of MSG in food sample. The method was validated following the International ICH (Q2)R2 guidelines in terms of precision, trueness and other main analytical figures of merit, comprised the green profile and practicability metrics. A wide linearity range was achieved (5–50 µg/mL) with good correlation coefficient (R2 ≥ 0.9993). The recoveries (%) were found in the range of 100.0 to 101.5 and the RSDs (%) were in the range of 0.1 to 0.9 %. These results show that the developed nanoprobe was selective, and highly accurate to determine this important food additive in the seasonings of instant noodles, also showing a reduced environmental impact based on the metrics currently accepted for the evaluation of the green profile and practicability.

Abstract: Aflatoxin B1 (AFB1) is the potent carcinogenic toxin secreted by fungi with widespread distribution around the world as the food contaminant. In the present study, a novel strategy has been developed for sensitive detection of AFB1 based on multiplex aptamer mediated probe and ExoIII enzyme activity. Inspired by generated fluorescence signal by DNA templated silver nanocluster (AgNCs), a specific aptasensor was designed to provide efficient interaction with AFB1 and subsequent amplify the released heterostructure included G-quadruplex after Exo-assisted activity for AgNCs fabrication. This strategy triggered repeated recognition-sensing cycle, leading to output colorimetric and fluorometric response signal. The integration of G-quadruplex in released probe, amplified the intrinsic low quantum yield and fluorescence of synthesized AgNCs and also enhanced its nanozyme activity on TMB and H2O2 substrate for colorimetric detection in single tube reaction. The developed AFB1 sensing assay showed LOD of 2.5 pM in colorimetric mode and had more sensitive LOD of 8.5 fM in fluorescence analysis. Smartphone assisted assay was also applied successfully as competitive detection approach. The proposed strategy was applicable in real sample and showed reliable results. Overall, this platform takes advantages of sensitive fluorometric analysis and nanozyme assisted colorimetric method which make it promising in practical application.

Abstract: Addressing sustainability requires developing analytical methods that minimize hazards, waste, and energy utilization per the principles of green and white chemistry. Herein, we present a sustainable spectrophotometric chemometrics technique for quantifying the recently approved Bupivacaine (BUP) and Meloxicam (MEL) combination and the potential BUP carcinogen, 2,6-dimethylaniline (DMA). Our models, including partial least squares (PLS), principal component regression (PCR), genetic algorithm-PLS (GA-PLS), and GA-PCR, were established through a comprehensive experimental design involving 25 mixtures as the calibration set. A key innovation is the utilization of the Latin Hypercube Sampling (LHS) technique, which enables the creation of a robust validation set for evaluating the performance and generalizability of these models. The GA-PLS model demonstrated excellent accuracy, with recovery percentages (R%) from 98 to 102% for all analytes, and root mean square error of calibration (RMSEC) and prediction (RMSEP) of (0.097, 0.050, and 0.112) and (0.119, 0.044 and 0.131) for BUP, DMA, and MEL, respectively. The model also showed a negligible bias-corrected mean square error of prediction (BCMSEP) of (-0.014, −0.003, and 0.018), with relative root mean square error of prediction (RRMSEP) reaching (0.992, 0.752, and 0.659), and limits of detection (LOD) reaching (0.153, 0.081, and 0227) for BUP, DMA, and MEL, respectively. Comprehensive greenness, blueness, and whiteness assessments were performed and compared between the suggested and reported methods. This research pioneers a green–blue-white alternative to conventional approaches, serving as a model for developing sustainable techniques that reduce the usage of resources and chemical waste while meeting the global appeal for environmentally accountable solutions.

Abstract: A fast, practical, and non-hazardous switch-off fluorescent nanosensor for the non-fluorescent antiandrogen drug flutamide (FLU) was developed from nitrogen/sulfur co-doping of carbon quantum dots (N,S-CQDs). For the first time, the highly fluorescent N,S-CQDs were generated via one-pot microwave-assisted synthesis in only 3 min using facilely available precursors (sweet yellow pepper and thiourea). The sensor is characterized by a narrow particle size distribution, high doping efficiency (N, 42.05 % and S, 8.28 %), reproducibility, and high emission at 410 nm after excitation at 330 nm. FLU efficiently and quantitatively turned off the fluorescence of the prepared N,S-CQDs via a synergistic combination of static quenching and inner filter effect. The furnished nanosensor showed good linearity (r = 0.9999) for FLU analysis within concentrations ranged from 1.0 to 30.0 µg mL−1 with a detection limit of 0.293 µg mL−1 and quantitation limit of 0.886µg mL−1. The selectivity of the probe was confirmed in the presence of co-administered drugs, possible co-existing materials, and various metal ions. The N,S-CQDs interestingly showed acceptable cytocompatibility and low toxicity, as revealed by the MTT assay. This feature bestows the N,S-CQDs a practicability as an environmental sensor. Thus, the proposed approach was implemented for FLU analysis in pharmaceutical tablets, tap water, and river water with good percentage recoveries (99.59 ± 1.28, 99.49 ± 1.75 and 101.21 ± 1.67, respectively) and without interferences. Furthermore, the approach was positively assessed with respect to greenness, blueness, and whiteness. The high values of the analytical greenness score AGREE (0.78), the chiefly green ComplexGAPI pictogram, the Blue Applicability Grade Index BAGI (72.5), and the RGB12 (93.6) show the high greenness, blueness, and whiteness features of the method that confirm its minor environmental impact, excellent applicability, and sustainability, respectively.

Abstract: Riboflavin was first isolated from milk and widely used in food, biological and pharmaceutical fields. Accurate detection of riboflavin content is of great significance for the treatment of related diseases and the supervision of food/drug quality. In this paper, a 1D chain copper-based coordination polymer with excellent water stability was synthesized by hydrothermal method using rigid ligand 1,10-phenanthroline and flexible ligand 1,4-phenylenedioxydiacetic acid, named Cu-phen-PEDA. Based on the Förster resonance energy transfer (FRET) and dynamic quenching detection mechanism, the emission spectrum of Cu-phen-PEDA overlaps with the absorption spectrum of riboflavin. As an energy donor in this case, Cu-phen-PEDA significantly increases the fluorescence intensity of riboflavin (energy acceptor), while simultaneously decreasing its own fluorescence intensity, which is an effective proportional-building strategy. In the lower concentration range, riboflavin can be specifically recognized by ratiometric fluorescence with a good linear relationship, and the detection limit is as low as 23 nM. The potential aspects of its specificity, stability, reusability and practical application were explored.

Abstract: This study develops a novel fluorometric method for the sensitive and selective determination of urea, based on unique system comprising nitrogen doped red-emissive carbon dots (NRECDs), zinc-dithizone complex, and the urease enzyme. The underlying principle of this method relies on the pH increase resulting from the enzymatic breakdown of urea by urease. Initially, the fluorescence of the NRECDs is quenched by the red-colored zinc-dithizone complex. However, upon the addition of urea, the subsequent release of ammonia and the consequent rise in pH lead to the dissociation of the zinc-dithizone complex, causing a color change from red to yellow. This spectral shift eliminates the quenching effect, resulting in the restoration of the CDs' fluorescence. The prepared NRECDs were comprehensively characterized using various spectroscopic techniques, including fluorometry, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), UV–visible spectroscopy, and transmission electron microscopy (TEM) imaging. The proposed fluorometric method exhibits excellent sensitivity (Limit of detection = 0.0012 mM) and linearity (R2 = 0.9951) in the determination of urea. Notably, this approach addresses the selectivity limitations of previous pH-sensitive CDs-based methods, which relied solely on the intrinsic response of CDs, lacking specificity in either quenching or fluorescence enhancement. Furthermore, the developed method demonstrates remarkable selectivity, as evidenced by negligible interference from various potentially interfering substances, ensuring reliable and accurate urea quantification. When applied to human serum samples, the method showcased excellent recovery with low relative standard deviations, highlighting its practical applicability in biomedical and clinical applications.

Abstract: In this work, a novel Eu-MOF, {[Eu2(L)(phen)2(ox)2(H2O)2]·10H2O·phen}n (H2L = 2,6-bis(4-carboxyphenyl)pyrazine, phen = 1,10-phenanthroline), was assembled under hydrothermal conditions with good water stability and pH stability. The Eu-MOF could be used as a luminescent sensor for detecting gas/liquid benzaldehyde, Hg2+ and Cr2O72-/CrO42- with high sensitivity and selectivity based on luminescence quenching effects. The sensing mechanisms were systematically studied by ICP-AES, PXRD analysis and UV–vis spectroscopy. In addition, the Eu-MOF shows high adsorption of Hg2+ and can be successfully used to quantitatively detect Hg2+ in real samples such as tap water, green tea, and river water. The sensor exhibited a recovery rate in the range of 99.84 %∼102.34 % for detecting Hg2+. The portable fluorescent paper strips based on the Eu-MOF were also successfully fabricated, which can detect benzaldehyde both in gas and liquid phases. The fluorescence sensing system based on Eu-MOF provides a reference for the construction of portable environmental pollutant monitoring sensors.

Abstract: An efficient electrochemical sensor based on polyaniline-benzothiazole [(3,5-bis (benzo[d]thiazol-2-yl)-[1,1–biphenyl]-4-ol)] (PAni-BEN) composite was designed and synthesized in this study, and it was employed as an electrochemical sensor to detect Hg2+ and Pb2+ ions with good selectivity and sensitivity. Fourier transform-infrared spectroscopy, UV–Vis spectroscopy, scanning electron microscopy, and energy dispersive X-ray analysis spectroscopy were employed to examine the morphology and structure of the produced composite. The electrochemical characteristics of the electrode modifiers were evaluated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Also, they were employed to perform both individual and simultaneous sensing studies of various metal ions using the differential pulse voltammetry technique (DPV) in a different supporting electrolyte (acetate buffer (pH 5), phosphate buffer (pH 7), and 0.1 M HCl) mediums. The PAni-BEN composite modified GCE sensor shows remarkable selectivity and sensitivity towards Hg2+ and Pb2+ ions over the other heavy metal ions in 1 to 24.84 µM, respectively. The limits of detection (S/N = 3) were 1 nM and 4.6 nM for Hg2+ and Pb2+ ions. Density Functional Theory (DFT) was used in the present study to accomplish the adsorption mechanism of the suggested sensors. The DFT calculation demonstrated that the PAni-BEN composite was formed with a lower band gap energy than BEN and DD PAni. These findings showed that the suggested sensor (PAni-BEN), which may used to detect Hg2+ and Pb2+ ions, had the lowest detection limit in the acetate buffer medium compared to the proposed electrolyte medium.

Abstract: In the current study, a fast, ecological, one-pot, and cost-efficient method was developed for the synthesis of nitrogen-doped carbon quantum dots (N-CQDs) using plant wastes. This method includes the treatment of cantaloupe seeds and mush by microwave for four-minutes as a re-cyclable, green, and cheap carbon and nitrogen source. The furnished N-CQDs show a fluorescence quantum yield of 13.15 %, excellent water solubility, and high stability. A full characterization of the plant waste-derived quantum dots revealed the self-doping with nitrogen. The synthesized N-CQDs have been applied as an efficient nanoprobe for fluorometric determination of nizatidine (NZT), a gastroprotective drug, at λex/λem of 325/416 nm within the concentration range of 0.75–100.0 μM and LOD of 0.24 μM. The N-CQDs show excellent selectivity for NZT in the presence of various possibly co-existing substances. Excellent mean % recovery was achieved for the determination of NZT in capsules (101.97 ± 0.91 %). Moreover, the N-CQDs were used for the determination of NZT in human urine within the concentration range of 2.5–100.0 μM with LOD of 0.8 μM, therefore it has been applied for monitoring the excretion profile of NZT in urine. The greenness of the proposed probe has been evaluated using two greenness software and metrics proving excellent greenness feature that is attributed to using a renewable and cheap plant waste product as a feedstock via low-energy/low-cost microwave-assisted synthesis, elimination of organic solvents and hazardous chemicals, and relying on a direct mix-and-read assay.

Abstract: C-reactive protein (CRP) level provides important information about the health status of the individual in predicting many diseases such as cardiovascular, chronic inflammatory, and neurodegenerative diseases. Therefore, determining CRP levels is important for correct health intervention and treatment follow-up. For the selective detection of CRP, we developed a (GO/Au-MIP) SPR sensor containing CRP-imprinted polymer modified with graphene oxide and gold nanoparticles. To prove the enhanced sensitivity of the sensor resulting from the presence of graphene oxide (GO) and gold nanoparticles (AuNPs), a CRP-imprinted (MIP) SPR sensor was prepared using the same method, excluding the incorporation of GO and AuNPs. In addition, a non-imprinted GO/Au-NIP SPR sensor was also prepared to evaluate the imprinting efficiency. In detecting CRP in PBS buffer, the GO/Au-MIP SPR sensor exhibited linearity in the concentration ranges of 0.1–2 ppm (R2 = 0.9721) and 5–100 ppm (R2 = 0.9740). The detection limit of the prepared sensor was calculated as 0.0082 ppm. In the study, the imprinting process efficiency was also evaluated by calculating the imprinting factor value (I.F=13.84). In the selectivity studies, the GO/Au-MIP SPR sensor was determined to be 9.23 times more selective against CRP protein than bovine serum albumin and 29.53 times more selective than hemoglobin. When the repeatability of the GO/Au-MIP SPR sensor was examined, it was determined that the GO/Au-MIP SPR sensor was able to detect CRP without any deterioration in performance in five consecutive reuses (RSD<1.5). Finally, CRP detection studies from the serum and urine solutions, which were selected as real samples, were carried out by the GO/Au-MIP SPR sensor to evaluate the matrix effect. CRP spiked serum sample was analyzed by the other standard method to validate the analytical results using CRP-Analyser.

Abstract: In this article, we describe a new platform for probing toxic pollutants, namely Hg2+ and S2-, in aquatic environments by tracing the "on–off-on" fluorescence signals of quantum dots. To achieve this, red lentils and urea, as natural precursors, were utilized as sources of S and N doping, respectively, to fabricate blue fluorescent carbon quantum dots, namely, Lentils/urea quantum dots (LUQDs) with good quantum yield and plentiful S-doping. In the present work, the quality-by-design (QbD) strategy was applied to control and select the optimum conditions for the microwave-aided synthesis of the carbon dots. LUQDs exhibit excitation-dependent emissions, where the maximum fluorescence emission was at 360 nm after excitation at 300 nm. During the detection step, the fluorescence of LUQDs is quenched by the incorporation of Hg2+ over the range of 0.50–70.0 μM. Next, S2- reacts with Hg2+, resulting in turning on the fluorescence emission of LUQDs in the range of 10.0–150.0 µM.The method was applied for the detection of both Hg2+ and S2- in tap, sewage, and river waters samples with a recovery rate ranging between 98.96 % and 101.26 %; in addition, Hg2+ was detected in canned Tuna samples with a recovery of 98.70 %. Furthermore, the greenness of the developed method was confirmed through various greenness metrics.

Abstract: The coloring of foods is one of the main attributes of importance for consumers and it can be decisive for a consumer to accept or reject the product. Models that explore brown sugar coloring are scarce in scientific research. So, a new strategy for brown sugar classification through the combination of digital image processing, machine learning and physicochemical composition data was proposed. RGB channel intensities and color histogram data, obtained from digital image processing, in combination with some physicochemical characteristics (sucrose, Ca, Fe, ICUMSA color and total phenolic compounds (TPC)) were used as training and external validation datasets in the creation of classification models by RF algorithm. Excellent performance of classification models was observed by high overall accuracy rates for ICUMSA color (92.6 %), Ca and sucrose (100 %), Fe (94.9 %), and TPC (97.6 %). Thus, classifying brown sugar based on its color can be a valuable strategy for the beverage and food industries, allowing for greater diversification and meeting consumer needs while enhancing the quality and consistency of products.

Abstract: Poor conductivity and surface passivation pose critical challenges in metal oxide structures during their application for non-enzymatic oxidation. To address this, we systematically employed in-situ deposition of carbon-quantum dots (C-dots) over copper oxide (CuO), enhancing its electrocatalytic properties for direct non-enzymatic glucose oxidation in alkaline media. The process involved the systematic deposition of varying wt.% of C-dots onto the CuO nanostructure. The electrode's sensing capability was assessed through CV, DPV, and amperometric measurements, evaluating its suitability in high (0.1 to 0.85 mM) and low glucose concentration levels (15 to 225 nM) with a representative LOD of 1.4 nM (17142.86 µA mM−1 cm−2). Additionally, the CuO-Cdot-16.6 protective coating allowed for long-term working capability, with chronoamperometric measurement confirming a 99 % current retention ability compared to pristine CuO's 39 % retention during 3500 s of continuous measurement. DFT calculations further confirmed the efficacy of CuO substrate as a scaffold for glucose adsorption. The stable CuO-glucose complex formed due to energetically favorable conditions further strengthens its potential as a sensor. Successful recoveries of spiked glucose serum samples validated the sensor's practical usage in complex matrices. Moreover, Machine learning was also adopted to validate the accuracy of glucose detection, where artificial neural network (ANN) model emerged as a suitable model to interpret the DPV derived data relationships, adding in sensor working capability and promising its future application in precision/intelligent healthcare.

Abstract: A green, facile and selective fluorimetric approach was described for estimating alcaftadine (ALC) in its pure form, eye drop formulation, and artificial aqueous humor for the first time. The developed approach depends on the suppression of the photoinduced electron transfer (PET) impact of the lone pair of the N-atom of the piperidine ring of ALC. PET suppression was attained by using 0.3 M acetic acid as an efficient protonating agent. By virtue of this phenomenon, ALC was quantified from 50 to 400 ng mL−1 with a very low detection and quantitation limit of 2.22 and 6.72 ng mL−1, respectively. Additionally, the presented method was employed for estimating the target drug in artificial aqueous humor and observably there is no significant interference from the aqueous humor matrix.