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Glutathione (GSH) and Hg²⁺ both possess skin-lightening effects, but GSH is a beneficial component while Hg²⁺ poses significant health risks to humans. Accurate quantification of both GSH and Hg²⁺ is crucial for distinguishing the quality of commercial skin lightening cosmetics. In this study, the In₂S₃-Ti₃C₂ photoelectric material was synthesized and modified onto the surface of FTO. By incorporating T-rich Hg²⁺ aptamer DNA with ferrocene-modified termini (Apt-Fc) onto the material surface, a photoelectrochemical (PEC) aptamer sensor was developed for the sequential detection of Hg²⁺ and glutathione (GSH) using the same sensing platform. In the absence of Hg²⁺, Fc acts as an electron acceptor to competitively capture photogenerated electrons from In₂S₃-Ti₃C₂, reducing the number of electrons transferred to the electrode and resulting in a decreased photocurrent. Upon Hg²⁺ addition, the formed T-Hg²⁺-T structure brings Fc into closer proximity to the photoelectrode surface, where the steric hindrance effect of the T-Hg²⁺-T duplex and the competitive electron-capturing effect of Fc synergistically lead to a further decreased photocurrent, enabling sensitive Hg²⁺ detection. On the other hand, GSH reduces MnO₂ to Mn²⁺, which accelerates the CRISPR/Cas12a cleavage activity to randomly cleave the T-Hg²⁺-T chain; the resultant enhanced photocurrent enables GSH detection. The detection limits are 8.47 × 10^-12 mol L^-1 and 4.83 × 10^-11 mol L^-1 for Hg²⁺ and GSH, respectively. The sensor has been successfully applied to the sequential detection of illegally added Hg²⁺ and the endogenous antioxidant GSH in commercial skin lightening cosmetics.

Reliable ore classification is essential for mineral exploration and intelligent beneficiation and directly determines the efficiency of mineral resource utilization. Conventional single-modal detection methods exhibit inherent deficiencies: laser-induced breakdown spectroscopy (LIBS) can provide elemental fingerprint information but is vulnerable to sample surface contamination, whereas machine vision acquires mineral morphological features yet fails to effectively distinguish minerals with similar chemical compositions. Moreover, existing multimodal fusion frameworks lack adaptive and robust fusion strategies for heterogeneous modal data, severely degrading model stability and classification accuracy under complex industrial mining conditions. To overcome these limitations, this work proposes a micro-destructive ore classification method integrating LIBS elemental spectroscopy and machine vision morphology. A DPSE adaptive multimodal fusion module is developed for one-dimensional heterogeneous concatenated embeddings. Different from vanilla SE and CBAM, DPSE introduces stacked one-dimensional, depthwise-separable convolution layers prior to the attention stage to explicitly extract local cross-modal correlations, together with a post-attention feature-reconstruction branch for dimensional alignment with dual-stream feature extractors, so as to suppress environmental interference and strengthen feature discrimination. Experimental validation on 17 natural mineral types achieves a classification accuracy of 96.13%, outperforming standalone LIBS and machine vision methods by 10.47% and 6.79%, respectively. The proposed method provides an accurate, rapid, and robust in situ mineral analysis strategy for intelligent mining applications.

Immunofluorescence (IF) staining is widely used to visualize biomolecules in cells and tissues. Conventional IF typically relies on fluorophore-conjugated antibodies, whose preparation requires chemical modification procedures that can compromise antibody performance and incur product loss during subsequent purification. In addition, iterative immunostaining depends on harsh stripping or fluorescence-quenching treatments that may damage sample architecture and epitope integrity. Here, we present protease-cleavable nanobody-fluorescent protein fusions (NFPFs) for reversible IF staining. Unlike fluorophore-labeled antibodies, NFPFs are genetically encoded and can be produced without post-synthetic chemical modification. By incorporating a tobacco etch virus (TEV) protease cleavage site between the nanobody and fluorescent protein, we engineered HER2- and EGFR-targeting NFPFs that retained high target specificity and enabled robust, concentration-dependent immunostaining of Capan-1 cells. TEV-mediated cleavage efficiently removed the fluorescent reporter while preserving cellular morphology and antigen accessibility, allowing subsequent staining of targets. Sequential labeling of distinct receptors demonstrated the feasibility of iterative immunostaining within the same specimen. Collectively, NFPFs provide a simple, scalable, and versatile approach for molecular imaging, enabling repeated rounds of immunostaining.

Hydrogen sulfide (H₂S) has garnered increasing attention in recent years, not only as a hazardous environmental pollutant but also as the third endogenous gas signaling molecule, alongside nitric oxide and carbon monoxide. At elevated concentrations, it poses serious threats to human health by irritating the respiratory tract and nervous system, with high-level exposure potentially leading to coma or even death. Conversely, at physiological levels, H₂S participates in a variety of essential biological processes, including cardiovascular regulation, neuroprotection and cellular metabolism. Given this dual nature, reliable monitoring of H₂S concentrations in both biological matrices and environmental samples is of considerable significance. Fluorescent probes have emerged as powerful analytical tools for this purpose, owing to their high sensitivity, excellent spatiotemporal resolution and non-invasive imaging capabilities. By exploiting the intrinsic chemical features of H₂S, such as nucleophilicity, reducing potency and affinity for metal ions, a diverse array of fluorescent sensors has been developed over the past few years. This review aims to provide a systematic overview of recent progress in the design and application of these probes, with particular emphasis on their distinct response mechanisms and their utility in H₂S sensing and bioimaging. Representative examples from each category are discussed, and the strengths and limitations of different strategies are compared. Through this summary, we hope to offer useful insights for the future development of more advanced H₂S probes tailored to specific research or diagnostic needs.

Aflatoxin contamination, especially aflatoxin B1 (AFB1), is a major global health concern. There is an urgent need to develop rapid, highly sensitive and specific sensing platforms. In this study, two fluorescence aptasensors were developed for AFB1 detection. The first used quantum dots (QDs) combined with aptamers as molecular recognition elements, along with RecJ_f exonuclease amplification and Fe₃O₄ nanoparticles for magnetic separation. In the absence of AFB1, the aptamer stably hybridizes with the cDNA-QDs conjugate, thereby shielding its 5' end from cleavage by RecJ_f exonuclease. Upon AFB1 binding, the duplex dissociates, exposing the aptamer's 5'-single-stranded region to RecJ_f-mediated hydrolysis-resulting in AFB1 release and enabling catalytic recycling and cascade signal amplification. It achieved a detection range of 0.01-100 ng mL^-1 and a limit of 2.2 pg mL^-1 (3σ/s). To further reduce interference and improve sensitivity, a second sensing system based on upconversion nanomaterials (UCNPs) was developed. This system, also using RecJ_f exonuclease amplification, achieved a broader range of 0.001-100 ng mL^-1 and a lower detection limit of 0.56 pg mL^-1. The QDs-based system required 90 min for detection, whereas the UCNPs-based system achieved detection in just 10 min. The two detection methods, particularly the UCNPs based one, enable specific identification of AFB1. Both aptasensors were successfully applied to the determination of AFB1 in spiked wheat flour and corn flour samples, with recoveries ranging from 89% to 111.6%, demonstrating their applicability to AFB1 analysis in cereal products. By replacing the aptamer, the proposed aptasensor can be further extended for the detection of other biological or chemical targets.

Biomass-based CDs constitute a rapidly developing, eco-friendly category of nanomaterials engineered mainly for ecological biosensing applications. By utilizing organic materials, including crop residues, botanical wastes and discarded food products, as the carbon source or precursor, these CDs offer a green synthesis method that avoids the risk of traditional chemical synthesis. As these green CDs are fabricated from natural precursors, these nanomaterials may contain surface-bound heteroatoms, like sulfur, nitrogen, and phosphorus, derived from their organic feedstocks. Therefore, these functionalized CDs facilitate the quick, easy and highly sensitive identification of environmental pollutants, such as pharmaceutical residues, toxic heavy metals, agricultural pesticides and novel contaminants. The presence of heteroatoms improves their fluorescence properties, selectivity, and interaction with target analytes. Consequently, these CDs exhibit rapid, user-friendly, and sensitive detection of environmental contaminants, including pesticides, heavy metals, antibiotics, and emerging pollutants. From this perspective, green-synthesised CDs are expected to have a substantial long-term impact on environmental monitoring. Their compatibility with portable sensing platforms, suitability for field-deployable platforms, and ability to detect contaminants at trace levels make them promising candidates for next-generation environmental monitoring systems. However, the transformation of these sustainable nanomaterials into practical environmental solutions will require further investigations into their biomass precursors, structural property correlations, and mechanism-driven sensing strategies. Instead of mainly focusing on lower detection limits, future research studies should focus on mechanistic insights, real environmental stability and real-world applicability to enable the practical utilisation of sustainable carbon dot sensing platforms.

5-Aminosalicylic acid (5-ASA), a common anti-inflammatory, is an emerging contaminant due to its widespread presence in aquatic environments and ecological risks. Developing sensing platforms for its trace detection is essential for environmental monitoring. This study developed a highly selective molecularly imprinted polymer (MIP) combined with reduced graphene oxide (rGO) for electrochemical detection of 5-ASA. A Deep Eutectic Solvent (DES), chosen for its eco-friendliness and excellent solvating ability, served as the functional medium to improve the imprinting process. The synthesis was suggested by molecular dynamics (MD) simulations and Quantum Theory of Atoms in Molecules (QTAIM) theory, which identified an optimal molar ratio of 3 : 1 : 3 for choline chloride : caffeic acid : ethylene glycol. The MIP/rGO sensor exhibited excellent analytical capabilities, including a wide linear range (0.3-700 μM) and a low detection limit (0.15 μM). It also demonstrated high selectivity against interferents and was effectively used on water samples, confirming its reliability as a sensor for pharmaceutical residues in water systems.

Determining the higher order structure (HOS) of proteins and protein complexes is central to understanding their functions, dynamics, and interactions. Traditional structural biology approaches, such as X-ray crystallography and nuclear magnetic resonance, provide high-resolution snapshots but often require large amounts of homogeneous samples and may miss dynamic or heterogeneous states. Mass spectrometry (MS) has become an indispensable tool for sensitive and rapid analysis of intact proteins and assemblies under native or near-native conditions. This review discusses the major MS-based strategies for probing HOS. Native mass spectrometry (nMS) preserves non-covalent interactions and exhibits characteristic charge-state distributions that report on folding, while native top-down fragmentation and ion mobility spectrometry provide sequence-specific and conformation-specific information. Hydrogen-deuterium exchange MS measures backbone amide exchange rates to map regions of solvent accessibility, ligand binding, and allosteric regulation in solution. Covalent labeling MS irreversibly modifies solvent-accessible side chains, allowing epitope mapping and detection of subtle conformational changes, while fast photochemical oxidation of proteins offers microsecond snapshots of transient structures. Chemical cross-linking MS applies bifunctional reagents to capture proximity between residues or subunits, providing distance restraints for integrative modeling and proteome-wide interaction mapping. We outline recent advances in instrumentation, software, labeling chemistry and in-cell techniques across these modalities, and we illustrate their applications to characterizing membrane proteins, large assemblies, therapeutic antibodies, intrinsically disordered proteins, and protein-ligand complexes. Together, these tools offer complementary insights into HOS that are reshaping structural biology, biopharmaceutical development and mechanistic studies.

Ambient ionization mass spectrometry (AIMS) enables direct analysis of samples under open-air conditions with little or no pretreatment. Among AIMS techniques, plasma-based ionization has attracted particular attention because atmospheric-pressure plasmas can generate reagent ions, metastable species, radicals, photons, and gas streams that support rapid desorption and ionization of solid, liquid, gaseous, and heterogeneous surface samples. Representative sources include direct analysis in real time (DART), desorption atmospheric-pressure chemical ionization (DAPCI), flowing atmospheric-pressure afterglow (FAPA), plasma-assisted desorption/ionization (PADI), dielectric barrier discharge ionization (DBDI), and low-temperature plasma (LTP). This review critically examines plasma-based AIMS from the perspectives of discharge mechanism, ionization pathway, source architecture, and analytical performance. Rather than simply listing individual applications, we compare how different plasma-generation strategies influence reagent-ion chemistry, thermal effects, fragmentation, matrix tolerance, quantitative capability, and suitability for field deployment. Applications in environmental analysis, forensic analysis, explosive detection, pharmaceutical screening, food safety, biological analysis, and materials characterization are discussed with attention to both analytical value and remaining limitations. Plasma-based AIMS has strong potential for high-throughput screening and on-site testing, but routine implementation requires improved mechanistic understanding, source standardization, quantitative robustness, matrix-effect control, and integration with portable MS and validated data-analysis workflows. Future development should move beyond stand-alone application demonstrations toward fit-for-purpose, reproducible, and validated analytical platforms.