Search Results (1,835)

Alpha-fetoprotein (AFP) is widely utilized for auxiliary diagnosis of primary hepatocellular carcinoma. Therefore, the development of a facile immunosensor is essential for clinical applications. This study aims to develop a simple immunoassay for AFP detection. By incorporating silicon quantum dots (SiQDs) into etching hollow gold nanoshells (EHGNs) via precise nanomanipulation, we designed molecular probes based on SiQDs@EHGNs complex immobilized capture antibodies, which can convert the antigen/antibody binding process into fluorescent divergence signals for AFP measurement. This strategy enabled one-step fluorescence sensing for AFP detection with a linear range of 3.125–200.0 ng/mL and LOD of 0.234 ng/mL. The detection results of 15 clinical serum real samples demonstrated a 93.7% correlation with the market-accepted ECLIA method. The proposed method take advantages of simplicity and rapid response, offering a novel approach for tumor marker analysis with significant potential. Full article

The development of effective fluorescent probes for the detection of acids and bases, both in solution and in the solid state, is of particular interest worldwide, due to the possibility of preventing hazardous consequences for human health and the environment. In the present work, the synthesis of a 1,8-naphthalimide derivative, designed as a “fluorophore-receptor₁-spacer-receptor₂” model, is considered. The compound contains two receptors for analytes in one molecule and can operate as a fluorescent probe via PET and ICT mechanisms. The photophysical behavior of the synthesized derivative in solution, on strip paper, and in thin film was investigated. It was found that the transition from acidic to alkaline medium in solution is associated with a change in color that is visible with the naked eye (yellow–orange-red–blue). The change in fluorescence, both in solution and spread on a supporting surface (strip paper and thin film), can be spectrophotometrically observed. The influence of various volatile acids on the sensing activity of the synthesized compound in solution and deposited on a solid support was investigated. It was found that with increasing acid strength, the fluorescence intensity increases. The strip paper and thin film obtained with the synthesized compound show reversible switching between the “off” and “on” states of fluorescence. The strip paper exhibited good cycling under acid–base vapor stimulation. The results obtained demonstrate the possibility of application of the synthesized compound as a colorimetric and fluorescent probe for determination of pH in solution, and detection of acids, bases, and their vapors in indoor and outdoor residential and industrial premises, as well as in the environment. Full article

Heavy metal mercury is one of the most significant and toxic environmental contaminants. Its inorganic form (Hg²⁺) and organic form (organic mercury, OrHg) can cause irreversible harm to human health and the ecological environment, and the latter is particularly prone to bioaccumulation and bioamplification in the food chain. Therefore, there is an urgent need for a rapid, reliable and specific detection of Hg²⁺ and OrHg to evaluate the potential risk for human health. Here, a novel label-free fluorescent sensing platform based on ssDNA aptamer (A_A-T7)-templated AuNCs was established for sensitive recognition and specific detection of Hg²⁺ and OrHg. In the presence of OrHg, the fluorescence of pure A_A-T7-templated AuNCs was visibly enhanced through forming Ag/AuNCs based on Ag⁰-doped AIEE effect. However, they were obviously quenched because of generating non-fluorescent Au/Ag/Hg ANPs via metallophilic interactions among Au³⁺, Ag⁺, and Hg²⁺ (5d¹⁰-4d¹⁰-5d¹⁰) when only Hg²⁺ existed. This fluorescent sensing platform could detect as low as 20.0 nM (4.0 ng Hg/g) and has a good linear detection range, with target concentrations ranging from 0.25 μM to 2.00 μM, recoveries of 98.0–108.0%, and RSD ≤ 5.0%. Low-toxic A_A-T7-templated AuNCs could be used for cytotoxicity analysis and intracellular fluorescent imaging. The method has been successfully applied to the determination of Hg²⁺ and OrHg in tap water, seawater and dried golden pomfret fish muscle samples, demonstrating promising prospects for the assay of mercury species in environmental samples and aquatic products to ensure human health and food safety. Full article

Parameters of reflected light, measured in narrow or broad spectral bands, are widely analyzed for remote and proximal sensing of plant responses to stressors. Specifically, parameters of reflectance in red (R), green (G), and blue (B) spectral bands measured using simple color images can be sensitive to characteristics of plants. The conventional view is that RGB reflectance primarily reveals long-term changes in plants (days, weeks, etc.). In this study, we investigated light-induced changes in RGB reflectance in wheat (Triticum aestivum L.) and pea (Pisum sativum L.) leaves. Illumination increased this reflectance for about 10 min in wheat and about 15–20 min in pea; these changes relaxed after light intensity was decreased. The changes in RGB reflectance were strongly related to the effective quantum yield of photosystem II and non-photochemical quenching of chlorophyll fluorescence under high light intensity; these relations were absent under low light intensity. We hypothesized that changes in both RGB reflectance and photosynthetic parameters were related to the light-induced changes in chloroplast localization. A simple mathematical model of optical properties and photosynthesis in leaves was developed; results of the model-based analysis supported the proposed hypothesis. Experimental analysis of the dynamics of light transmittance additionally supported this hypothesis. Our results thus show that RGB imaging can be sensitive to fast changes in plants. Full article

Wastewater-based epidemiology (WBE) has emerged as a powerful approach for population-level monitoring of chemical exposure, health status, and disease transmission by analysing wastewater. Although chromatographic and molecular techniques remain the gold standard in WBE, their high cost, infrastructural demands, and limited suitability for decentralized and real-time monitoring motivate the development of complementary sensing technologies. In this context, optical (bio)sensors, particularly fluorescence-based platforms, have attracted increasing attention due to their high sensitivity, rapid response, and potential for on-site monitoring. This review discusses recent advances in fluorescent optical (bio)sensors for WBE, with a particular focus on carbon dots (CDs), including waste- and biomass-derived CDs produced via green synthesis as well as CDs obtained from commercial chemicals. The applicability of CD-based sensors to wastewater-relevant analytes is evaluated, highlighting current achievements, as well as existing limitations and challenges related to real-sample validation and the translation of these platforms into robust, field-deployable systems for their implementation in sustainable wastewater monitoring and public health surveillance. Full article

The precise determination of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels is critical for understanding the photophysical and photochemical properties of carbon dots (C-dots), which directly govern their performance in optoelectronic, catalytic, and sensing applications. However, the lack of distinct redox peaks in cyclic voltammetry (CV) curves of C-dots poses a major challenge to conventional energy level calculation methods. Herein, we propose a novel strategy to calculate the HOMO–LUMO energy levels of C-dots by combining electron transfer (ET) kinetics with Marcus theory. A series of quinones (electron acceptors, EAs) and ferrocene derivatives (electron donors, EDs) were employed to quench the fluorescence of C-dots, and the ET rate constants (K) were derived from fluorescence lifetime measurements. The CV curves of EAs and EDs provided their respective oxidation and reduction potentials, which were used as reference energy levels. The UV–Vis absorption spectra confirmed that the fluorescence quenching mechanism was dominated by ET rather than energy transfer. Based on Marcus theory, the free energy change (ΔG) of ET reactions was correlated with K, and the HOMO and LUMO energy levels of C-dots were calculated to be −1.84 V (vs. SCE) and +1.60 V (vs. SCE), respectively. This study not only provides a reliable method for determining the energy levels of C-dots without distinct redox peaks but also deepens the understanding of ET mechanisms between C-dots and small molecules. The proposed strategy is expected to be extended to other fluorescent nanomaterials with similar CV limitations. Full article

Serum contains diverse proteins whose concentrations vary with pathological conditions such as cancer, liver disease, neurological disorder, and infections. Conventional methods like serum protein electrophoresis (SPEP) and enzyme-linked immunosorbent assay (ELISA) are gold standards for protein identification; however, they are time-consuming and can miss abnormal serum protein levels. Inspired by chemical nose sensing based on selective sensor–analyte interactions, we synthesized five pyrene-conjugated fluorescent polymers (PFPs) with distinct side-chain head groups to construct a multichannel fluorescence sensor array. These polymers were screened for sensitivity to changes in serum protein levels using linear discriminant analysis (LDA), a machine learning method. This process led to the successful discovery of two PFPs that effectively detect protein level fluctuations. These PFPs provided a sensitive sensor array capable of generating a high-content response pattern (fingerprint) with six fluorescence channels. This sensor array successfully discriminated protein level fluctuations in serum with 98% jackknife classification accuracy and 95% unknown identification accuracy. This polymer sensor array holds strong potential as a diagnostic tool for serum-based samples and can be extended to other applications related to protein identification. Full article

This study evaluated the effects of seven light-emitting diode (LED) spectra on the morphophysiological and plant-quality responses of Korean white dandelion (Taraxacum coreanum Nakai) grown for 30 days under controlled environmental conditions. The treatments included monochromatic red, green, and blue LEDs; a purple-phyto LED containing red, blue, and far-red wavelengths; and three white LEDs (warm white, natural white, and cool white). Morphophysiological responses were assessed together with principal component analysis, correlation analysis, and hierarchical clustering. Green light promoted elongation, increasing shoot height and leaf length, but reduced stem diameter, root length, leaf thickness, biomass accumulation, photochemical performance, and plant quality indices. Red light also resulted in relatively low biomass, SPAD units, F_v/F_m, PI_ABS, normalized difference vegetation index (NDVI), Dickson quality index (DQI), and integrated morphophysiological index (IMI), indicating an imbalanced growth response. In contrast, natural white and cool white LEDs were generally associated with greater stem thickening, root development, leaf thickening, shoot and root dry weight accumulation, and higher F_v/F_m, PI_ABS, NDVI, DQI, and IMI. Warm white showed favorable trends in shoot and root fresh weights and relative moisture content. Multivariate analyses separated the red and green treatments from the white-light treatments. Overall, white LEDs, especially natural and cool white, appeared more effective than monochromatic LEDs in supporting balanced early growth and plant quality in T. coreanum. Full article

The objective of this study was to design and evaluate π-extended 1,8-naphthalimide derivatives as photoinduced electron transfer (PET) optical sensors for protons and metal cations, with emphasis on the role of heterocyclic annulation and receptor–chromophore electronic matching. Benzofuran- and benzodioxin-annulated naphthalimides bearing either a dimethylaminoethyl receptor or a non-donating alkyl substituent at the imide nitrogen were synthesized using tailored synthetic strategies. Their photophysical properties were investigated by absorption and fluorescence spectroscopy, while sensing performance was evaluated by fluorescence titrations. Quantum chemistry calculations were employed to rationalize experimental observations. Benzofuran-annulated derivatives exhibit structured π–π* absorption bands and strong fluorescence, whereas introduction of the receptor induces efficient fluorescence quenching via reductive PET. Protonation or metal ion coordination suppresses PET and leads to pronounced fluorescence enhancement, particularly in the presence of Cu(II) and Sn(II). In contrast, benzodioxin-annulated derivatives display intramolecular charge-transfer absorption bands, large Stokes shifts, and low fluorescence quantum yields in polar media, resulting in a negligible sensing response. Computational results attribute this behavior to an unfavorable energy arrangement of the donor–acceptor orbitals. Overall, the study demonstrates that heterocyclic annulation critically governs the electronic structure and sensing performance of naphthalimide fluorophores, providing guidelines for the rational design of PET-based optical sensors. Full article

Drought is one of the major disasters constraining crop production. The accurate identification of the dominant environmental factors that drive drought stress at different growth stages of maize is essential for developing stage-specific and precise water management strategies, enhancing drought resistance, and ensuring food security. However, a key challenge is quantifying the nonlinear interactions among multiple environmental factors. This study focuses on the rain-fed agricultural region of Northwest China. To address the limited availability of drought event samples in this region and the inadequacy of traditional statistical methods in capturing complex inter-factor relationships, we integrate a small-sample modeling framework based on an improved Conditional Generative Adversarial Network (CGAN) with an attribution framework that employs SHapley Additive exPlanations (SHAP) for interpretability analysis. We incorporate ten environmental factors derived from multi-source remote sensing: temperature (T_max, T_min, T_mean), precipitation (P), evapotranspiration (ET), soil moisture at 0–10 cm (SM_0–10) and at 10–40 cm (SM_10–40), and solar-induced chlorophyll fluorescence (SIF_max, SIF_min, SIF_mean). Sample sets were established for different maize phenological stages. The CGAN model was employed to achieve high-precision estimation of maize drought severity levels, while the SHAP method was used to quantitatively analyze the dominant factors and their contributions at each phenological stage. The results show that the CGAN model achieved coefficients of determination (R²) of 0.963, 0.972, and 0.979 for the seedling, jointing–tasseling, and maturity stages, respectively, demonstrating excellent nonlinear modeling capability under small samples. SHAP analysis reveals a clear dynamic evolution of dominant factors across phenological stages. Evapotranspiration (ET) dominated in the seedling stage, reflecting the primary role of surface water–heat balance, while the jointing–tasseling stage transitioned to a co-dominance of ET, topsoil moisture (SM_0–10), and minimum SIF, indicating intensified crop transpiration and physiological stress under the meteorological drought framework, and the maturity stage shifted to an absolute dominance centered on mean temperature (T_mean), highlighting the critical impact of heat stress. This study provides a data-driven quantitative perspective for understanding maize drought mechanisms and offers a scientific basis for formulating differentiated drought management strategies for different growth stages. Furthermore, it demonstrates the potential of integrating CGAN with SHAP for agricultural remote sensing and drought attribution research in data-scarce regions. Full article

Hydrogen peroxide (H₂O₂) plays a very vital role in industrial and biological processes, but its high concentration may cause health hazards. Therefore, accurate detection of H₂O₂ is crucial for chemical and biological sensing applications. In this work, a ratiometric fluorescent probe was developed using a core–shell structural silica nanoparticle for the detection of H₂O₂. Firstly, a silica core structure with red fluorescence emission was constructed by encapsulating a Schiff base compound (SD). Afterwards, a mesoporous silica shell was fabricated, and the AIE featured fluorophore with a H₂O₂ response character was covalently linked on the surface of the mesoporous shell layer. As recognition sites on the shell, blue-emitting TB molecules specifically identified H₂O₂ through their phenylboronic acid ester group. The blue fluorescence of core–shell structural nanoprobes would be quenched in the presence of H₂O₂, while red fluorescence remained unchanged, ensuring the high sensitivity and specificity of the ratio sensing. This design has demonstrated significant potential for the reliable monitoring of hydrogen peroxide in biological and environmental applications. Full article

A library of twelve heteroditopic bis-urea and bis-thiourea receptors supported on Merrifield and Wang resins was prepared by solid-phase synthesis. The receptors incorporate dual hydrogen-bond-donor units for anion binding and a polyether spacer that simultaneously functions as a cation-binding site, enabling ion-pair recognition at the solid–liquid interface. Molecular recognition studies were performed using several inorganic and tetraalkylammonium salts, and fluorescence changes were monitored by microplate measurements in DMSO and DMSO/H₂O (95:5, v/v). Univariate and factorial statistical analyses revealed statistically significant fluorescence changes and identified the structural variables governing guest recognition in each medium. Under the conditions examined, several systems exhibited reproducible ion-pair-induced fluorescence responses, highlighting the influence of receptor type and spacer architecture. These findings provide a basis for the rational optimization of supported receptors for sensing and extraction applications. Full article

A dual-mode electrical–optical nanocomposite hydrogel is developed by integrating carboxyl-modified upconversion nanoparticles (UCNPs-COOH) and quaternized chitosan (CQAS) into a polyacrylamide (PAAm) covalent network. The hydrogel exhibits high optical transparency (>90% in the visible region), excellent mechanical properties (fracture strain of 1742%, tensile strength of 0.85 MPa, toughness of 6.57 MJ/m³), and robust adhesion to various substrates. The synergistic covalent–noncovalent hybrid network enables efficient energy dissipation, while CQAS-enhanced dispersion of UCNPs significantly improves upconversion luminescence intensity and stability, as evidenced by prolonged fluorescence lifetime from 0.564 ms to 0.691 ms at 539 nm. Leveraging distinct electrical and optical signal transduction pathways, the hydrogel functions as a highly sensitive resistive strain sensor with multistage gauge factors up to 13.85 and excellent cyclic stability over 1200 loading–unloading cycles at 100% strain for human motion monitoring. It also serves as a ratiometric optical pH sensor over a broad range (pH 1–13) based on phenolphthalein-sensitized upconversion luminescence, with excellent repeatability. By integrating real-time resistance responses with optical readouts within a single soft material, this work demonstrates a reliable dual-mode sensing strategy for simultaneous mechanical and chemical monitoring, holding promise for wearable electronics, smart healthcare, and environment-responsive sensing systems. Full article

Abandoned mining areas provide valuable opportunities to investigate ore-forming processes, supergene mineral transformations, and the geochemical behaviour of metals. In this sense, the old Preguiça mine (Beja, Portugal), exploited for Fe–Zn–Pb, was studied providing new mineralogical and geochemical data aimed at improving the understanding of the secondary mineral assemblages of this deposit. A total of 70 samples collected from three accessible underground levels (first, second and third) and mine waste, complemented by 16 samples from a deeper level (fourth) previously collected, were analysed using X-ray diffraction (XRD), scanning electron microscopy (SEM), and a portable X-ray fluorescence (pXRF) equipment. Mineralogical phases are dominated by a wide range of secondary oxides, carbonates, arsenates, vanadates, silicates, phosphates and sulphates, but remnants of primary sulphides were also found. The following minerals can be emphasised: goethite, hematite, calcite, dolomite, descloizite, willemite, mimetite, cerussite, smithsonite and fraipontite. The presence of massicot in the Preguiça mine, is described for the first time. Bulk geochemical analyses show high concentrations of Fe, Ca, Zn and Pb, consistent with the observed mineralogy. The presence of vanadium- and arsenic-bearing minerals highlights the occurrence of critical raw materials, supporting the importance of reassessing other abandoned mining areas in the context of sustainable resource management and strategic raw-material planning. Full article

All forms of neural communications, from cognition to emotion, are regulated by neurotransmitters, which are otherwise the chemical language of the brain. Precise detection of these neurotransmitters is essential for the perception of neurophysiology and diagnosis of neurodegenerative diseases as well. Among the existing techniques for the detection of these molecules, fluorescence sensing is evolving as a powerful approach in terms of high sensitivity, rapid response, and real-time visualization of the chemical events occurring in the neural system. In recent years, nanomaterials have transformed this field by integrating tunable optical properties, excellent photostability, and modifiable surface chemistry into biocompatible nanostructures. We summarize the recent advances of these architectures to show how the material type and dimensionality, as well as the surface functionality, play roles in sensing through the mechanisms of Förster resonance energy transfer (FRET), photoinduced electron transfer (PET), inner filter effect (IFE), and aggregation-induced emission (AIE). The discussion has also been extended to the correlation of fluorescence modulation with the selectivity and sensitivity in the mechanism-to-function relationship. The potential utility of such innovative technologies, including artificial intelligence, spectral deconvolution analysis via big data algorithms, and chip-integrated sensing, was explored as a means to enable real-time neurochemical detection. This converging area of nanotechnology and neuroscience leaves a mark not just in analytical accuracy, but also parallels human brain rhythms. Full article