Near-infrared (NIR) aggregation-induced emission luminogens (AIEgens) are promising reporters for non-invasive imaging of tumor apoptosis, yet existing caspase-3 (Casp-3)-activatable AIEgens still suffer from limited target specificity. To address this challenge, we developed a tandem-targeting NIR AIEgen, Arg-Gly-Asp-Asp-Glu-Val-Asp-Pra-QMT (RGDDEVD-QMT), for specific imaging of Casp-3 activity in vivo. The probe integrates a hydrophilic RGDDEVD-OH peptide substrate (i.e., a tumor-targeting Arg-Gly-Asp (RGD) motif and a Casp-3-cleavable Asp-Glu-Val-Asp (DEVD) segment) with a hydrophobic QMT fluorophore via a propargylglycine (Pra) linker. After selective binding to αvβ3 integrin on tumor cells and subsequent intracellular cleavage by Casp-3, RGDDEVD-QMT is hydrolyzed into a hydrophilic peptide fragment (RGDDEVD-OH) and a hydrophobic fluorophore (QMT-P), the latter self-assembling into nanoparticles that activate pronounced NIR fluorescence (FL) due to the aggregation-induced emission (AIE) effect. This tandem targeting enzyme-mediated aggregation renders 2.1-fold FL signal enhancement of single targeting aggregation in apoptotic 4T1 tumor cells. In vivo FL imaging demonstrates effective accumulation and activation of RGDDEVD-QMT in apoptotic 4T1 tumors, affording a 6.2-fold signal enhancement relative to the control group. Collectively, the tandem-targeting design endows RGDDEVD-QMT with exceptional tumor specificity, deep-tissue penetration, and superior contrast, establishing a broadly applicable platform for real-time appraisal of therapeutic efficacy through direct visualization of tumor apoptosis.
In this study, cobalt phthalocyanine (CoPc) was anchored onto nitrogen and sulfur co-doped graphene oxide (NSG). The obtained nanocomposite exhibited strong catalytic activity in oxygen reduction reaction (ORR), making ORR significantly occur at a less negative potential, which is favorable for biomaterial stability and avoids interference from H2 evolution. At the same time, a stable and easily fixed luminol and aniline copolymer electrochemiluminescent (ECL) luminophore was rationally designed and synthesized through a chemical method, which showed good ECL features. Furthermore, combining it with the NSG-CoPc composite made the ECL signal more stable and boosted the ECL intensity 10-fold. As an application proof of the developed copolymer–NSG-CoPc-dissolved O2 ECL system, the epithelial cell adhesion molecule (EpCAM) was detected after introducing an aptamer for recognition. Consequently, over the range of 1.0 to 10 ng/mL, the logarithm of EpCAM concentration and the ECL response of the resulting sensor displayed a good linear correlation, with a limit of detection of 0.79 pg/mL (S/N = 3). The sensor’s good analytical performance and application potential were further validated by testing its selectivity, reproducibility, stability, and performance with real samples. This work provides a paradigm for improving luminol-based ECL biosensing.
Overactive bladder (OAB) syndrome poses a significant global clinical challenge, underscoring the urgent need for objective and non-invasive diagnostic tools. This study establishes a comprehensive diagnostic framework by integrating multi-omics discovery with a high-throughput tip-enhanced laser desorption ionization mass spectrometry (TELDI-MS) platform. Our investigation commenced with an integrated transcriptomic and metabolomic analysis of bladder tissue and urine in an OAB rat model, which pinpointed dysregulated metabolic pathways. These findings directly informed the subsequent development of a rapid urinary screening method, utilizing a matrix-free LDI-MS platform equipped with fluorinated ethylene propylene-coated silicon nanowire chips (FEP@SiNWs). In a clinical cohort of 520 participants, including healthy controls, OAB patients, and control groups with urinary tract infection (UTI) or mycoplasma infection (MI), nineteen metabolites were verified to be dysregulated in OAB. The implicated pathways, primarily amino acid metabolism, aligned with our prior observations in the rat model. A machine learning model derived from the urinary metabolic profile achieved high diagnostic accuracy in an external validation cohort, correctly classifying 94.5
Temperature is a fundamental biophysical parameter that regulates cellular physiology and immune responses. Fever, a hallmark of infection, profoundly influences host defense, yet its effects on immune regulation remain incompletely defined. Conflicting population-level findings suggest that cellular heterogeneity masks underlying thermal mechanisms, underscoring the need for single-cell resolution. Here, we present an integrated microanalysis platform that combines a transparent indium-tin-oxide (ITO) thermal control module, high-density microwell arrays for single-cell isolation, and antibody-functionalized capture surfaces, enabling precise, real-time control of temperature and quantification of macrophage secretory responses. Using this platform, we show that exposure to fever-range hyperthermia (40 °C) differentially modulates pro-inflammatory cytokine production: Tumor necrosis factor-α (TNF-α) secretion is suppressed, whereas interleukin-1β (IL-1β) responsiveness and the frequency of TNF-α/IL-1β co-secreting cells are increased. These results reveal cytokine-specific thermal sensitivities that are obscured in bulk assays, establish a link between febrile temperature and innate immune regulation, and provide a technological foundation for dissecting how thermal cues shape immune heterogeneity at the single-cell level.
Accurate identification of chiral enantiomers is of critical importance in pharmaceutical sciences, as mirror-image isomers often exhibit distinct pharmacological activities and toxicological profiles. Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for discriminating between chiral molecules due to its ability to provide highly specific molecular vibrational fingerprints. However, its practical application is frequently hindered by significant signal variability and limited detection sensitivity. To address these persistent challenges, a novel SERS substrate is developed through the coffee-ring effect (CRE)-driven self-assembly of chiral plasmonic gold-nanorod@silver (AuNR@Ag) core–shell nanostructures. Chiral AuNR@Ag nanostructures are synthesized by immobilizing L-/D-cysteine (Cys) onto AuNR surfaces, followed by the controlled deposition of a silver shell. These nanoparticles subsequently self-assemble into dense, uniform, ring-shaped architectures during droplet evaporation, which generates highly reproducible and intense electromagnetic hotspots. As a proof-of-concept, this platform achieves sensitive enantiomeric discrimination of naproxen with a significant 3- to 4-fold SERS signal contrast and high reproducibility, enabling the quantitative determination of enantiomeric excess (ee). Furthermore, this CRE-driven self-assembly strategy provides a promising and versatile platform for accurate enantioselective sensing of chiral drug enantiomers.
Reliable source-resolved detection of domestic wastewater in receiving waters remains challenging due to strong dilution effects and variable background matrices. Here, we introduce a charge-regulated surface-enhanced Raman spectroscopy (SERS) strategy that employs negatively charged citrate-reduced Ag nanoparticles and positively charged poly(diallyldimethylammonium chloride) (PDDA)-modified Ag nanoparticles to fractionate dissolved organic matter and generate complementary spectral fingerprints. Seven domestic wastewater sources were profiled and diluted in river and lake waters up to 1000× to evaluate the feasibility of this approach for wastewater sources tracking in real receiving waters. SERS spectra acquired from both substrates were embedded using principal component analysis (PCA) and integrated through a multilevel data fusion framework, including feature-level fusion of low-dimensional representations and probability-level fusion of classifier outputs. Model performance was systematically evaluated using multiple conventional machine-learning classifiers to assess robustness across algorithms. The fused models consistently outperformed single-substrate approaches, achieving cross-validated classification accuracies of up to 99.8
Monitoring trace levels of antibiotic residues in food is essential for ensuring food safety. In this work, we developed a highly sensitive photoelectrochemical (PEC) sensor based on a Bi2WO6 nanoflower/Ti3C2-MXene (Bi2WO6/MXene) (three-dimensional/two-dimensional) (3D/2D) heterojunction for detecting tetracycline hydrochloride (TCH). The heterojunction was constructed via a spatial confinement strategy, in which Bi2WO6 nanoflowers were uniformly grown in situ on multilayered MXene nanosheets, forming an intimate interface that enabled efficient charge separation and accelerated interfacial electron transfer. The confined structure effectively reduced the size of Bi2WO6 nanoflowers from 1.5 to 0.5 μm, increased the exposure of reactive sites, and promoted the generation of superoxide radicals (•O2−), which served as the dominant reactive species responsible for TCH oxidation. As a result, the Bi2WO6/MXene heterojunction-based PEC sensor exhibited outstanding analytical performance, with two wide linear ranges of 0.001–10 and 10–100 nM, and an ultralow detection limit of 0.3 pM, outperforming most previously reported PEC sensors.
Laser-induced breakdown spectroscopy (LIBS) exhibits significant potential for the rapid analysis of uranium (U) in molten salts during the electrorefining of spent nuclear fuel. However, its quantitative accuracy, particularly for high-concentration U, is still constrained by inadequacies in data analysis methods. Herein, we proposed a machine-learning (ML)-enhanced LIBS modeling flow, encompassing steps of data preprocessing, feature extraction, and model training, which achieved accurate quantification of high-concentration U (up to 20 wt
Emerging contaminants (ECs), including persistent organic pollutants (POPs), endocrine-disrupting chemicals (EDCs), antibiotics, and microplastics (MPs), are detected in various environmental media at low concentrations, posing potential threats to both ecosystems and human health. Therefore, the development of a variety of rapid, accurate, and sensitive assays for the detection of ECs in the environment is crucial for mitigating and preventing related environmental risks. Traditional methods often require extensive pretreatment and chromatography, making it challenging to perform rapid, real-time monitoring of ECs. The rapid analysis technology has emerged as a crucial method for the real-time, in-situ, rapid, and high-throughput detection of ECs. This approach minimizes the need for manual sample pretreatment and enables the rapid or direct analysis of environmental samples, while maintaining high sensitivity at trace levels. In this review, we focus on online pretreatment technologies, direct injection mass spectrometry techniques, sensor technologies, and spectral analysis methods that eliminate the need for manual pretreatment. We conduct a comprehensive analysis from the perspectives of principles, instrumentation, and advantages. Considering the characteristics of ECs, we examine the limitations of existing technologies and discuss potential future developments. This review provides valuable insights into the evolving landscape of analytical methods for detecting and monitoring ECs.
Conventional DNA biosensors employing "always-on" fluorophores commonly suffer from nonspecific signal activation caused by nuclease-mediated degradation, thereby compromising their detection accuracy. Here, we develop a novel nucleic acid-activatable fluorophore (NAF) that enables precise biomolecule detection and imaging in live cells. NAF achieved a 92-fold fluorescence enhancement via covalent conjugation to DNA, resulting in a remarkably decreased non-specific signal activation in a 10
Single-atom nanozymes (SAzymes) can emulate the metal active sites of natural enzymes with atomic-level precision, holding great promise as the next generation of nanozyme materials. However, the synthesis of SAzyme with high peroxidase-like activity still poses significant challenges. In this work, through precise coordination regulation of SAzymes, axial oxygen-coordinated iron SAzyme (Fe-N3O SAzyme) with high peroxidase-like activity was successfully synthesized. The synthesized Fe-N3O SAzyme shows a maximum reaction rate (Vmax) of approximately 4.5 µM/min, which is approximately 12.7 times higher than that of Fe-N4 with symmetric N-coordination for H2O2 catalytic oxidation. Density functional theory calculations suggest that introducing axial oxygen into the Fe-N3O SAzyme modulates charge distribution and optimizes intermediate adsorption energies, thus reducing the reaction barrier. Due to its excellent peroxidase-like activity, Fe-N3O SAzyme was applied for constructing a colorimetric biosensing platform that can selectively detect and discriminate biothiols (cysteine, homocysteine, and glutathione), enabling in vitro diagnosis. This work paves a new avenue for designing SAzymes with high enzyme-like activity, offering promising potential for advanced disease diagnosis applications.
Precise control over reaction progression is crucial for enhancing the reliability of nanozyme-based colorimetric assays, yet conventional quenching methods often suffer from operational complexity, signal interference, or environmental contamination. To address this limitation, we synthesized photo-responsive graphene quantum dots (GQDs) derived from waste tea biomass. These GQDs exhibit oxidase-mimicking activity exclusively under light irradiation, while the catalytic activity ceases immediately in the dark, enabling real-time modulation of the reaction via simple light switching. Leveraging this light-tunable catalytic system, we discovered that D-penicillamine (DPA) acts as an effective reducing agent, quenching the photo-generated reactive oxygen species and leading to a measurable decrease in colorimetric signal. An accurate and rapid colorimetric sensing platform was developed for DPA detection, exhibiting a broad linear response range from 0.5 to 265 µM and a detection limit as low as 0.34 µM. Successful application in determining DPA content in commercial tablets confirms the potential of the proposed light-controlled nanozymatic reaction switch for practical use.
Acetaminophen (APAP) is a widely used antipyretic and analgesic drug, yet its hepatotoxic potential upon overdose is well recognized. Beyond overdose, an insidious risk emerges when APAP is co-administered with other drugs for conditions such as tuberculosis or even the common cold. Such drug–drug interactions can synergistically exacerbate hepatotoxicity even at therapeutic doses, posing a major challenge to clinical drug safety. To address this clinical challenge, we developed a novel near-infrared meso-carboxyl-substituted rhodamine platform (RA-COOH) to construct a fluorogenic probe (RA-COO-Leu) for evaluating leucine aminopeptidase (LAP) activity and monitoring synergistic drug-induced hepatotoxicity. The probe exhibits a rapid (< 10 min) and sensitive response toward LAP both in solution and in living cells. Importantly, RA-COO-Leu not only visualized drug-induced liver injury caused by APAP overdose, but also, revealed that isoniazid (INH) pre-treatment markedly potentiates APAP-induced hepatotoxicity in vivo. Collectively, this study provides a powerful molecular tool for LAP detection and a versatile research platform that can be utilized to elucidate the mechanisms and identify drugs with potential risks for synergistic hepatotoxicity.
Although continuous glucose monitoring (CGM) is essential for precise and personalized diabetes management, conventional approaches rely on invasive finger-prick blood sampling. Furthermore, existing CGM systems suffer from major limitations, including user discomfort, biofouling of implanted sensors, and unstable sensing components. To address these challenges, we present a hollow microneedle-based (MN) biosensor that minimally invasively accesses the interstitial fluid (ISF) for in-situ glucose monitoring. The MN biosensor integrates a miniaturized three-electrode system within the lumen of MNs filled with synthesized vacancy-regulated Prussian blue intercalated thermoplastic graphite composite (GP@PB). The GP@PB composite, prepared through a precipitation-conversion strategy, exhibits hierarchical and hollow morphology that provides a large active surface area and mitigates structural degradation. The sensing interface is further protected by an external MN body and a poly(methyl methacrylate) (PMMA) substrate, both of which greatly improve mechanical robustness and electrochemical stability. The MN biosensor enables real-time and continuous glucose monitoring in ISF with great sensitivity, selectivity, biocompatibility, and long-term reliability. In vivo studies in rat models validate the real-world feasibility of the biosensor by providing dynamic analysis of ISF glucose in response to metabolic variations, showing a strong correlation with gold-standard results measured using commercial devices. This work facilitates the clinical translation of minimally invasive CGM in personalized diabetes management, highlighting the potential of wearable electronics toward chronic disease healthcare.
Mass spectrometry-based targeted quantitation technologies are widely recognized for their high sensitivity, strong specificity, broad dynamic range, and excellent quantitative accuracy, and have been established as a cornerstone technique for discovery, validation, and translation research in the proteomics field. Ongoing advancements in mass spectrometry hardware and software have significantly enhanced targeted proteomics analysis, enabling its application in a wide range of scientific disciplines. However, several technical and methodological challenges remain. Real-time acquisition strategies and algorithms have been developed with increased efficiency and intelligence. These strategies, namely, employing stable isotope triggering, real-time search localization, or retention time (RT) adjustment, have transformed targeted proteomics from a static analytical model into a dynamic and intelligent acquisition framework. This transition enables the detection of more targets per run while enhancing sensitivity, specificity, and quantification accuracy. This review focuses on novel strategies and technologies in mass spectrometry-based targeted proteomics. It provides a systematic description of the underlying principles, applications, and technical challenges of these strategies and technologies, with the intention to provide a comprehensive resource for an in-depth understanding of targeted quantitative proteomics.
Emodin (Emo) is a primary active component of tartary buckwheat and rhubarb. In this study, we aimed to definitively identify the metabolites in rats following the oral administration of Emo. Fifteen metabolites were identified, encompassing three Emo sulfates (M5, M8, and M13), three Emo glucuronides (M3, M6, and M9), two hydroxyl-Emo (M12 and M15), two hydroxyl-Emo sulfates (M4 and M10), two hydroxyl-Emo glucuronides (M7 and M11), one methylated hydroxyl-Emo (M14), as well as di-glucuronyl-Emo (M2) and glucuronyl-Emo sulfate (M1). Emo glucuronides and sulfates were identified via matching with in vitro metabolites. Particularly, M5 was consolidated through scale-up urine collection and chromatographic purification. M12 and M15 were annotated as 4-hydroxyl-Emo and ω-hydroxyl-Emo, respectively, through synthesizing the suspected structures. Four hydroxyl-Emo glucuronides and sulfates were deciphered by comparing with in vitro metabolites of 4-hydroxyl-Emo and ω-hydroxyl-Emo. M1 and M2 were characterized by mapping the fragment ions with the known structures via programming post-collision-induced dissociation energy-resolved MS. M14 was interpreted by comparing nucleophilic capacity within all existing hydroxyl groups. Together, confidence-enhanced identification was achieved for all metabolites, providing pronounced clues to clarify the effective forms in vivo for Emo. Additionally, the flexible workflow is promising for metabolites identification.
Acrylamide (AA) and N(6)-carboxymethyllysine (CML) are representative hazardous compounds generated during the Maillard reaction in food processing. Their combined toxicity raises significant concerns about food safety. This study developed a novel approach integrating deep learning models (Cellpose and ResNet18) with cellular fluorescence imaging to enhance the efficiency and accuracy of combined toxicity screening. Cellpose was employed for automated cell segmentation to generate single-cell image datasets. Subsequently, the ResNet18 deep learning model was trained directly on these single-cell images for 200 epochs to perform end-to-end prediction of synergy scores, successfully achieving accurate predictions for previously unseen AA/CML concentration combinations. To provide biological interpretation, CellProfiler was utilized to extract comprehensive, explicit cellular phenotypic features from the same images. This methodology overcomes the limitations of conventional toxicity screening approaches in simultaneous multi-parameter detection, offering an efficient, rapid screening strategy that establishes a direct correlation between cellular phenotype and combined toxicity effects.
Nicosulfuron, a sulfonylurea herbicide, is primarily used to control annual weeds in corn fields in China. Residues of nicosulfuron in soil can easily cause phytotoxicity in subsequent crops, such as wheat and cabbage. It has become urgent for growers to analyze nicosulfuron residue in soil and plan subsequent crops based on the results of this analysis. In this study, rabbit monoclonal antibodies with high sensitivity and specificity were prepared by using single B-cell technology based on the synthesized haptens from our previous study. Rapid analysis methods using enzyme-linked immunosorbent assay (ELISA) and lateral flow immunochromatography assay (LFIA) were established to detect nicosulfuron in soil and agricultural products with ultra-sensitivity. The linear detection range of ELISA was 0.09770–5.808 ng/mL, with a half-maximum inhibitory concentration (IC50) of 0.753 ng/mL. LFIA achieved semi-quantitative analysis with a detection limit of 1.25 ng/mL and a cut-off value of 5 ng/mL. Spike recovery and real samples analysis indicated that results obtained from the immunoassay and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) were consistent. Molecular docking simulations revealed that antibody 6D8 formed multiple hydrogen bonds (SER-433 and SER-466) and hydrophobic interactions with nicosulfuron through its complementarity-determining regions (CDRs), thus achieving high specificity and strong binding force. The two complementary immunoassays developed in this study are important for the rapid analysis of nicosulfuron in environmental samples, and for guiding the correct and rational use of this herbicide.
Exhaled nitric oxide (NO) is a key biomarker of respiratory diseases and has been widely applied in clinical practice. New development of simple, rapid, and effective methods for on-site detection of exhaled NO is highly needed. In the present study, we developed a wearable breath sampling method for on-site NO detection by integrating amlodipine (AML) -modified paper strips and a cooling device into a common KN95 mask. Exhaled vapor was condensed to a wet paper strip that was pre-deposited on AML to selectively capture trace NO from exhaled breath via a chemical reaction to form dehydro AML, which can be directly detected by paper spray ionization coupled with miniature mass spectrometry. The analytical performance of the proposed method was systematically evaluated, including a low detection limit ( 8.0 ppbv), excellent linearity (R² > 0.98), good reproducibility (RSD < 15
Chemical signaling molecules mediate intercellular communication and physiological regulation, and their precise spatiotemporal control is critical for investigating cellular stimulus-response behavior. However, conventional delivery methods remain limited in achieving quantitatively controlled release at the single-cell level. Dopamine (DA) is a key neurotransmitter in neuronal signaling, yet its stimulus–response dynamics at the single-cell level remain to be elucidated. Herein, we report a strategy for the in situ electrochemical generation and electrically controlled release of DA. The DA precursor molecule 3,4-dimethoxyphenylethylamine (DMPEA) was immobilized on the inner wall of an Au-coated micropipette, electrochemically converted into DA, and then released in a controlled manner under a negative potential. The release process followed first-order kinetics. Coupled with single-cell calcium imaging, this localized DA release was shown to induce significant Ca2+ influx in individual hippocampal neurons. This strategy enables localized, temporally controlled, and dose-regulated delivery of DA, and provides a versatile platform for the in-situ generation and precise release of other neurotransmitters, signaling molecules, and small molecule drugs.
