Autophagy is a vital cytoprotective pathway against oxidative stress, and the regulatory function of reactive oxygen species (ROS) in autophagy has been thoroughly investigated. However, nitric oxide (NO), a representative reactive nitrogen species, exerts dual contradictory effects on autophagy, and the underlying reason for such discrepancy remains ambiguous. Existing studies indicate that the biological activity of NO is highly dependent on mitochondrial microenvironmental pH; the pH fluctuation during autophagy further modulates NO-mediated protein modification and downstream autophagic signaling. Nevertheless, conventional fluorescent probes can only separately detect NO or mitochondrial pH, lacking the capacity to synchronously track the two parameters in mitochondria, which severely restricts the exploration of the coupling relationship between NO and pH during autophagy. Herein, we constructed a benzindolium-functionalized mitochondria-targeted ratiometric fluorescent probe for simultaneous visualization of mitochondrial NO and pH. The probe possesses donor-acceptor structures whose spectral properties are modulated by ambient pH via protonation and deprotonation, and it only responds to pH variation in the presence of NO, guaranteeing the specificity of dual-parameter imaging. Spectral characterizations confirm the distinct ratiometric fluorescence shifts triggered by NO and pH co-stimulation. Cellular imaging experiments based on rapamycin-induced and ischemia-reperfusion-induced autophagy models demonstrate that autophagy activation is accompanied by upregulated mitochondrial NO and synchronous mitochondrial pH alternation. Distinct from single-analyte probes reported previously, this probe enables real-time synchronous ratiometric imaging of mitochondrial NO and pH in living cells. This work provides a reliable visual tool to monitor the dynamic coupling of NO and mitochondrial pH during autophagy, laying a foundation for further dissecting the disparate regulatory effects of NO on autophagy under varied pathological microenvironments.
Aptamer-based atomic spectroscopy offers high sensitivity and selectivity but is limited by bulky instrumentation. The integration of aptamer-based sensing with microplasma atomic emission spectroscopy (AES) enables a portable and user-friendly platform for real-time field detection. In this study, a dual-signal amplification chemical vapor generation point discharge atomic emission spectroscopy (CVG-PD-AES) platform was developed for highly sensitive, label-free, and separation-free determination of acetamiprid (ACE). The system integrates strand displacement reaction (SDR) amplification with gold filament preconcentration to enhance analytical performance. A thymine-mercury-thymine (T-Hg2+-T) complex was constructed. Upon ACE addition, the acetamiprid-binding aptamer (ABA) preferentially binds to ACE, releasing target DNA to initiate SDR, which induces Hg2+ release. The released Hg2+ is subsequently reduced to Hg0, selectively enriched through gold filament amalgamation, and detected by a miniaturized CVG-PD-AES system. Under optimized conditions, the method achieved an exceptionally low limit of detection (LOD) for ACE at 96 fg/mL, accompanied by high selectivity arising from specific aptamer-target recognition. The developed portable sensing platform was successfully applied to monitor ACE bioaccumulation in the Mori Folium of cultivated traditional Chinese medicinal (TCM) mulberry trees treated with ACE solutions during growth. The platform demonstrated excellent recoveries in real plant residues and exhibited strong potential for practical field applications.
We have developed a novel electrochemical-colorimetric dual-modal sensor based on a metallosalen-based covalent organic framework (Salen-COF) for separate electrochemical quantification of uric acid (UA) and dopamine (DA) and colorimetric screening of their total amount. The Salen-COF was synthesized via a Schiff-base condensation between a bimetallic CuCu-Salen complex and melamine (CuCu-MA-COF), yielding a highly ordered porous architecture featuring atomically dispersed CuCu-N2O2 sites, an extended π-conjugated backbone, and electron-deficient triazine units. This unique combination endows the material with rapid electron transfer kinetics, efficient electrocatalytic capability, and peroxidase (POD)-mimicking enzymatic activity. Leveraging these properties, the resulting electrochemical sensor delivered exceptional performance, giving low limits of detection (LODs) of 0.885 and 1.699 μM within linear ranges from 5 to 50 μM and 80-500 μM for DA, and LODs of 0.991 and 1.637 μM within linear ranges from 5 to 80 μM and 100-500 μM for UA. When simultaneously detecting DA and UA, the electrochemical sensor had the low LODs of 1.375 μM and 1.065 μM within the wide range of 5-500 μM, respectively. Furthermore, the CuCu-MA-COF-based colorimetric sensor showed the low LODs of 10.65 nM and 0.374 μM within the range from 0 to 200 μM for DA and UA, respectively. Critically, this dual-modal sensor demonstrates high selectivity against common interferents, excellent operational stability, outstanding reproducibility, and reliable performance in real-sample analysis, underscoring its strong potential for practical, non-invasive health monitoring in point-of-care settings.
Selenium (Se) is an essential trace element for humans and the determination of Se(IV) in daily samples is of great significance. A low-cost, easy-used hydride generation-fluorescence colorimetric method was developed for the rapid and selective detection of Se(IV) using a silver-based metal-organic framework (Ag-PMDA) as a substrate. Se(IV) was converted into volatile H2Se via hydride generation. The generated H2Se then reacted with Ag-PMDA-modified test paper, causing the in-situ generation of Ag2Se nanoparticles on its surface. This resulted in a distinct fluorescence quenching and a visible color variation of the test paper. The resulting signal could be directly observed by the naked eye and further quantified using the smartphone RGB mode, which exhibited a linear range of 0-1.0 μg/mL (y = -438.77x+596.77, R2 = 0.9905). By incorporating a TiO2-based preconcentration step, the sensitivity was substantially enhanced, reducing the limit of detection from 0.019 μg/mL to 0.002 μg/mL. The method was successfully applied to the detection of Se(IV) in real water samples and selenium-enriched products, with recoveries ranging from 104 % to 110%. Owing to its simple operation, low cost, good anti-interference capability and portability, this method shows great potential for on-site analysis.
Herein, an electrochemiluminescent (ECL) aptasensor based on porphyrin-based covalent organic framework (TP-COF) was constructed for the ultrasensitive detection of kanamycin (KANA). The ordered porous channels and porphyrin-centered π-conjugated framework of TP-COF optimize the interfacial microenvironment and accelerate electron transfer, facilitate the generation of luminol-derived active intermediates, and remarkably boost ECL emission. The modification of Au NPs on the surface of COF could improve interfacial conductivity and provide anchoring sites for thiolated DNA immobilization. Platinum-copper nanocages (PtCu) were employed as an ECL quencher and assembled onto the electrode via DNA hybridization to generate the initial "light-off" state. Upon target recognition, the aptamer was preferentially bind with KANA to dissociate PtCu from the electrode surface and restore the ECL signal. Under the optimal condition, the sensor exhibited linear response toward KANA over the range of 1.0 × 10-15 to 1.0 × 10-13 mol L-1, with a detection limit of 8.9 × 10-16 mol L-1. In addition, the satisfactory repeatability, stability, and selectivity were achieved. This strategy integrates COF-mediated interfacial regulation, noble-metal-assisted signal amplification, and aptamer-triggered dequenching, offering a promising platform for the ultrasensitive analysis of antibiotic residues.
Short-wave infrared hyperspectral imaging (SWIR-HSI) enables rapid, non-destructive material characterization with high potential for process analytical technology and pharmaceutical screening. Here, we demonstrate high-throughput, full-field SWIR-HSI using Fourier transform spectroscopy (FTS) coupled with deep learning. Conventional FTS typically requires thousands of sampling points over a wide optical path difference (OPD) range to resolve spectral features. By directly processing raw interferograms with deep learning, bypassing conventional Fourier transformation, we achieved 98.9% pixel-level and 100% whole-tablet classification accuracy across 11 over-the-counter pharmaceutical products using only 200 data points acquired over a 10 μm mirror displacement (20 μm OPD). Under challenging independent-lot, multi-day testing conditions, the framework maintained 96.7% pixel-level and 100% whole-tablet accuracy. Latent-space visualizations confirmed that short-range interferograms retain sufficient chemical and physical information for rapid, robust pharmaceutical classification. These findings indicate that deep-learned short-range interferometry offers a promising, vibration-resilient approach for high-throughput, non-destructive quality control of solid dosage pharmaceuticals.
The sensitivity and accuracy of photoelectrochemical (PEC) biosensors are often constrained by high electron-hole recombination rates and reliance on a single detection mode. To address this limitation, an ultrasensitive PEC-colorimetric (CM) dual-mode biosensor has been designed based on DNA nanoreactor-programmed modulation of protonated g-C3N4/AuNPs (PCN/AuNPs) Schottky junctions via a target-triggered etching effect. The Schottky junction formed between AuNPs and PCN through electrostatic interactions effectively modulates the energy band structure, thereby enhancing electron-hole separation. Furthermore, the localized surface plasmon resonance (LSPR) effect of AuNPs broadens the light absorption range, enables a highly localized and intensified electromagnetic field, which promotes rapid interfacial charge transfer. Taking carcinoembryonic antigen (CEA) as a model target, a DNA nanoflower-based cascade nanoreactor integrated with glucose oxidase and horseradish peroxidase (DFs@GOx/HRP) is constructed via rolling circle amplification (RCA) with target-specific aptamer programming. Upon recognition of CEA, a sandwich-type composite forms, initiating a cascade catalytic reaction of the nanoreactor using glucose as the substrate to generate oxidized 3,3',5,5'-tetramethylbenzidine (oxTMB), thereby enabling CM detection. In the PEC detection mode, the generated oxTMB under acidic conditions further oxidizes to TMB2+, which etches the AuNPs on the PCN/AuNPs surface, further breaks the Schottky junctions and weakens electrical conductivity, resulting in a decrease in photocurrent. This dual-mode biosensor achieves remarkable detection limits of 16.8 pg mL-1 for PEC and 0.46 ng mL-1 for CM detection along with high specificity. The proposed programmable strategy establishes a universal platform for dual-mode biosensing, facilitating complementary information acquisition from distinct transducers for more comprehensive analytical applications.
Real-time monitoring of dissolved gases in seawater is of critical scientific significance for research on marine ecosystem, global carbon cycle and marine environmental change. We developed a portable cavity-enhanced gas Raman spectroscopy system to enhance the Raman scattering intensities for trace gases detection by extending the photon-gas interaction path based on retro-reflective near concentric cavity. By optimizing the non-resonant multi-reflection optical path, the optical path length between laser and target gas was extended, which effectively strengthened Raman scattering signals. Combined with a hollow fiber membrane as the gas-liquid separation unit, the system realized the in-situ degassing and quantitative detection of dissolved gases in water. Calibrated with standard gases, the limits of detection (LODs) for carbon dioxide (CO2), methane (CH4) and hydrogen (H2) were 0.86 ppm, 0.12 ppm and 0.92 ppm, respectively. For the detection of dissolved gases in actual water, the developed Raman spectroscopy system was applied to detect water samples collected from freshwater of campus lake and coastal seawater of Qingdao. The concentrations of trace extracted gases in lake water/seawater detected by this instrument were 761.2 ppm/636.9 ppm for CO2, 165.6 ppm/1.6 ppm for CH4 and 1.8 ppm/2.1 ppm for H2, respectively. These results indicated that the developed Raman system with sub-ppm sensitivity could satisfy the practical monitoring demands for the lake and seawater, exhibiting excellent rapid real-time monitoring performance in complex water environments. Its practical implementation provides a reliable technical support for marine environmental monitoring, aquatic ecological research and greenhouse gas traceability.
The microplastic (MPs) pollution, especially in the oceans, has a direct impact on seafood products, particularly sea salt. This is a growing concern due to the high daily consumption of salt and the potential adverse health effects associated with MPs exposure. This study presents a rapid, cost-effective, and green approach for MPs-detection in food samples employing stereomicroscopy, smartphone-cameras, image analysis, and Machine-Learning tools. The method integrates accessible image acquisition with open-source software (Ilastik/FIJI) to enable automated detection and measurement of two common morphologies: filaments and fragments, providing a straightforward alternative for laboratories with limited resources. The developed models demonstrated high sensitivity (100% filaments, 76.5% fragments) and acceptable specificity (76.4% filaments, 72.2% fragments), with an average recovery of 108.6% for spiked samples. Upon application to sea salt samples from México, the model identified 1950 ± 354 MPs pieces/kg of salt. Among the detected MPs, filaments were the predominant morphology (1235 ± 263 MPs pieces/kg), while fragment count was 715 ± 167 MPs pieces/kg. Polypropylene, polyethylene, Polyvinyl chloride, and cellophane were confirmed via FTIR analysis. The method was successfully applied to 6 additional food matrices (e.g., sugar, meat tenderizer). The proposed methodology is delimited to the detection of microplastics ≥300 μm (filaments) and ≥200 μm (fragments), and therefore does not account for smaller particles. The proposed method offers a rapid, replicable and accessible alternative that enables high-throughput preliminary microplastic detection while reserving chemical identification for complementary spectroscopic analysis, thus suggesting a potential for routine application in microplastic monitoring.
Dissolved inorganic carbon (DIC) is a key parameter for characterizing the seawater carbonate system, sediment pore-water biogeochemistry, and nearshore carbon cycling. However, conventional DIC analysis methods usually require milliliter-to tens-of-milliliter-scale samples and are unsuitable for high-resolution analysis of volume-limited samples. Here, we developed a microliter-scale DIC measurement method coupling acidification-purge CO2 extraction with hollow-core-waveguide-based laser absorption spectroscopy. The system integrates a sealed 1.0 mL micro-reaction chamber, a low-dead-volume gas-transfer pathway, an approximately 50 μL hollow-core waveguide (HWG) optical gas cell and employs a mid-infrared CO2 absorption line near 3728.41 cm-1, enabling reliable quantification of DIC in samples as small as 20 μL. A quantitative strategy was established based on Voigt spectral fitting, gas-phase CO2 calibration, BiHill fitting of transient release profiles, liquid-phase DIC calibration, and injection-volume correction. Under optimized acid dosage, carrier-gas flow, bubbling mode, and temperature, the gas-phase detection unit achieved a Gaussian-fit 1σ precision of 0.175 ppmv and an operational 3σ CO2 detection limit of 0.803 ppmv at an averaging time of 1 s, as derived from Allan deviation analysis. The method enabled reliable DIC quantification with the minimum injection volume of 20 μL and achieved an RSD of 0.446% at the recommended 50 μL injection volume. Validation against a TOC-L analyzer and applications to Bohai Bay surface seawater and Aoshan Bay intertidal pore-water samples demonstrated low sample consumption, field-compatible analytical capability in practice, and suitability for high-resolution DIC analysis of marine volume-limited samples.
With the development of agricultural industrialization, compound sodium nitrophenolate (CSN), a broadly used plant growth regulator, is prone to excessive residues in agricultural products arising from overapplication or improper usage. Thus, the preparation of high-efficiency fluorescent sensing systems for fast and precise detection of CSN is extremely meaningful for safeguarding the quality and safety of agricultural commodities. In this research, N,S-doped carbon quantum dots (N,S-CQDs) featuring with green fluorescence emission were successfully synthesized by means of microwave-assisted carbonization. The morphology, crystal structure, and functional group information for the as-prepared N,S-CQDs were systematically characterized. These obtained characterization results indicated that the prepared N,S-CQDs showed a regular sphere shape with the mean diameter of 2.41 nm. Optical property investigations revealed that the N,S-CQDs displayed a maximum emission peak at 520 nm under the excitation of 425 nm, accompanied by a quantum yield of fluorescence of 26.17%. Furthermore, the N,S-CQDs demonstrated excellent optical stability and remarkable resistance to salt interference. Under optimized detection conditions, the N,S-CQDs probe displayed a highly selective fluorescence quenching response toward CSN. Simultaneously, good linear dependence relations were also collected within the concentration ranges of 6-120 μmol/L and 120-360 μmol/L, with a low detection limit value of 0.24 μmol/L. Mechanistic studies on the fluorescence quenching behavior suggested that obvious quenching process was primarily dominated by the combined effect of three factors. Validation experiments conducted on simulated samples and real lettuce samples confirmed that the proposed method could effectively detect CSN residues in actual agricultural samples, manifesting promising application potential.
Self-validated bioanalytical systems based on mechanistically orthogonal dual-mode transduction have attracted considerable interest, yet their development critically depends on multifunctional heterostructure materials that simultaneously enable efficient charge separation and well-resolved dual-emission output. Herein, a dual-mode photoelectrochemical/ratiometric fluorescence (PEC/FL) platform was constructed for sensitive dopamine (DA) determination based on a ternary MXene/Eu,Gd-CQDs/B,GQDs-g-C3N4 heterostructure (MEG). The MXene-mediated cascade interfacial architecture enabled efficient separation and rapid transport of photogenerated charge carriers for PEC signal amplification, while retaining well-resolved and reproducible dual-emission characteristics suitable for ratiometric fluorescence detection. In the PEC mode, the photocurrent increased with DA concentration, giving two separated linear calibration ranges of 0.01-0.20 μM and 10-500 μM, with a limit of detection (LOD) of 2.8 nM. In the FL mode, DA produced a wavelength-dependent ratiometric response dominated by progressive quenching of the 445 nm emission, yielding a concentration-dependent F365/F445 ratiometric response over 0.05-1.0 μM with an LOD of 38 nM. The complementary transduction mechanisms enabled mutual verification between the two modes, thereby reducing the risk of false-positive or false-negative interpretation associated with reliance on a single readout. Both modalities demonstrated excellent selectivity toward DA over common coexisting species, together with satisfactory operational stability and reproducibility. Practical applicability was validated in fetal bovine serum and river water samples, yielding recoveries of 96.8-104.2% with relative standard deviations below 5%. These results demonstrate that the MEG-based dual-readout strategy offers a robust, self-validated approach to reliable bioanalysis in complex matrices, using DA as a model system.
Staphylococcus aureus (S. aureus) is a common foodborne pathogen that can cause severe illnesses such as food poisoning and toxic shock syndrome, posing a significant threat to public health. Therefore, rapid and highly sensitive detection of S. aureus is crucial for ensuring food safety. In this study, a Meso-UiO-66(Zr)@PtPdNPs nanozyme with triple enzyme activities was synthesized and combined with the RPA-CRISPR/Cas12a system to construct a novel colorimetric platform for S. aureus detection. This platform utilizes the oxidase and peroxidase activities of Meso-UiO-66(Zr)@PtPdNPs to achieve self-driven catalytic cascade signal amplification without the need for external H2O2. During the assay, RPA first amplifies the target DNA to activate the trans-cleavage function of CRISPR/Cas12a. The activated CRISPR/Cas12a then degrades the magnetic bead probe (SMBs-S2), preventing it from coupling with the nanozyme probe (Meso-UiO-66(Zr)@PtPdNPs-S1). After magnetic separation, the nanozyme in the precipitate efficiently catalyzes the color development of TMB through the OXD-POD cascade effect. The resulting color intensity reflects the S. aureus levels. This biosensor shows excellent sensitivity and specificity by integrating the specific recognition and cleavage capabilities of the CRISPR system with the robust catalytic performance of the nanozyme. It displays a linear range of 1.5 × 101-1.5 × 108 CFU/mL, alongside a 2.6 CFU/mL detection limit. This study provides a novel strategy for the detection of S. aureus in food.
This work develops a high-sensitivity mid-infrared evanescent wave (MIR-EWs) sensing platform based on tellurium chalcogenide tapered fibers. A spatial optical coupling system enables efficient light coupling between the mid-infrared source and the fiber, while tapered chalcogenide fibers strengthen the interaction between the evanescent field and liquid analytes. Label-free and derivatization-free, the platform achieves precise discrimination of glucose (1030 cm-1) and fructose (1060 cm-1) structural isomers. Within 0-2 mol/L, the linear correlation coefficient exceeds 0.98 with negligible cross-interference in mixed-component quantification. Utilizing the 998 cm-1 characteristic peak of sucrose α-1,2-glycosidic bonds, in-situ continuous monitoring of acid-catalyzed hydrolysis is realized. Pseudo-first-order kinetics is accurately identified at high substrate concentrations, with a rate constant of 3.37 × 10-4 min-1. The sensor presents outstanding stability: the repeatability relative standard deviation (RSD) is below 0.4%, temperature-induced RSD within 15-50 °C is less than 0.64%, and stable performance is maintained across pH 1.1-7.2 with an RSD under 0.11% after over 500 min of continuous operation. Combined with the partial least squares regression model, the prediction determination coefficient of sucrose hydrolysis conversion reaches 0.987, with a root mean square error of only 3.60%. This work offers a novel route for in-situ kinetic analysis of liquid-phase reactions and provides a cost-effective, reliable strategy for multicomponent quantification and dynamic monitoring of complex organic systems.
Rapid quantification of hazardous trace metals in waste oil remains challenging because of the high viscosity and severe matrix effects of oily substrates. Here, we developed a quantum dot-enhanced double-pulse laser-induced breakdown spectroscopy (DP-QDELIBS) platform for ultrasensitive and matrix-tolerant metal analysis in waste oil. AgNC@AgAux core-shell quantum dots were used as an interfacial enhancement layer to improve laser energy coupling and initial plasma formation, and a second laser pulse was introduced to reheat the primary plasma and further amplify metal emission. Compared with conventional single-pulse LIBS, DP-QDELIBS achieved signal enhancement factors of up to 47 for Mg emission lines. Ablation morphology analysis indicated that the enhancement was associated with porous microstructures generated by intensified interfacial charge transfer and localized plasma expansion. Under optimized conditions, the method showed good linearity for representative metals, with coefficients of determination above 0.97 and limits of detection of 0.02 ppm for Mg, 0.06 ppm for Ca, 0.05 ppm for Cr, and 0.05 ppm for Ba. Analysis of real industrial waste-oil samples, including engine oils and brake fluids, showed strong agreement with inductively coupled plasma optical emission spectrometry (R2 > 0.97). These results demonstrate the potential of DP-QDELIBS for rapid screening of hazardous metals in complex oily wastes and for waste-oil risk assessment and management.
Based on the well matching between the emission of gold nanoclusters (AuNCs) and the absorption of ruthenium complex-doped magnetic silica nanoparticles (Fe3O4@Ru(bpy)32+@SiO2, simply as Fe3O4@Ru@SiO2), these two nanoparticles were employed as the energy donor and acceptor, respectively, to develop a signal-on electrochemiluminescence resonance energy transfer (ECL-RET) biosensor for the sensitive and selective detection of hepatitis B virus (HBV) DNA (chosen as a model target). Two DNAs (H1 and H2) capable of hybridizing with the target DNA were designed and modified on the nanoparticles to form Fe3O4@Ru@SiO2-H1 and AuNCs-H2. In the presence of target DNA, a hybridization cascade brought AuNCs into close proximity with Fe3O4@Ru@SiO2, the non-radiative energy transfer process allows the energy of AuNCs to be transferred to Fe3O4@Ru@SiO2, resulting in enhanced ECL from Fe3O4@Ru@SiO2. Magnetic separation technology was integrated to effectively remove interfering substances from complex matrices, further improving detection specificity. Under optimized conditions, the enhanced ECL intensity (ΔI) showed a good linear correlation with the logarithmic concentration of HBV DNA from 1.0 fM to 1.0 nM, with a detection limit of 0.33 fM. The proposed biosensor has been successfully applied for the detection of HBV DNA in clinical serum samples with satisfactory results. This study provides a promising strategy for nucleic acid analysis and demonstrates the great potential of the ECL-RET platform in clinical diagnostics and highly sensitive biomarker detection.
Circulating tumor cells (CTCs) are clinically important liquid biopsy biomarkers for cancer diagnosis, therapeutic monitoring, and prognosis. However, their extremely low abundance and pronounced phenotypic heterogeneity remain significant challenges for reliable detection and characterization. Herein, a dual-mode microfluidic platform integrated with photoelectrochemical (PEC) aptasensing and fluorescence imaging for the in-situ capture, identification, and phenotypic discrimination of CTCs directly from whole blood was developed. In this system, tumor cells were labeled with a near-infrared fluorescent probe (BDP-DNBS) and subsequently processed within a microfluidic chip for enrichment and on-chip analysis. A Bi2S3/Sb2S3/AuNPs nanocomposite was employed as the photoactive element to generate a sensitive PEC response, while subtype-specific aptamers were employed for the selective recognition of different hepatocellular carcinoma cell lines. This design allows simultaneous fluorescence visualization and PEC quantification within a single integrated platform. In spiked whole blood samples containing 200 cells mL−1, the PEC measurements yielded 140 ± 6 cells mL−1 for HepG2 and 146 ± 8 cells mL−1 for Huh7. Correspondingly, fluorescence imaging provided values of 137 ± 4 and 144 ± 7 cells mL−1, respectively. The strong agreement between the two detection modes demonstrates the robustness and analytical reliability of the proposed platform. Overall, this work presents a multimodal microfluidic sensing strategy for the analysis of heterogeneous liver cancer cells and offers a promising approach for blood-based CTC detection and phenotypic profiling in hepatocellular carcinoma.
Amine gases have emerged as critical biomarkers for evaluating aquatic product spoilage, among which trimethylamine (TMA) is highly representative owing to its tight correlation with the seafood decay process. Accurate and sensitive detection of TMA under practical conditions is thus of great significance for seafood quality monitoring and food safety control. Nevertheless, conventional TMA gas sensors frequently encounter drawbacks including high operating temperature, insufficient sensitivity, slow response kinetics, and unsatisfactory stability. In this study, a Bi2O3/Bi2Sn2O7 heterojunction gas-sensitive material was rationally synthesized via a facile hydrothermal route, which displayed outstanding specific response toward TMA gas at room temperature. Sensing performance evaluations revealed a response value of 4.8 toward 100 ppm TMA, a low detection limit of 1 ppm, and rapid response/recovery characteristics (28 s/15 s), coupled with superior cycling repeatability and long-term stability. The gas-sensing mechanism was systematically explored by combining microscopic characterization and electrical analysis, while density functional theory (DFT) calculations further clarified the adsorption behavior and charge transfer process at the material–gas interface. Finally, a prototype TMA detection device was developed based on the as-prepared heterojunction, which can effectively identify the spoilage degree of aquatic products including fish, shrimp and shellfish, and precisely capture trace TMA released during the initial spoilage stage to realize early warning for aquatic product quality. This work provides a promising room-temperature sensing strategy and lays a solid foundation for the safety supervision and quality assessment of aquatic food.
ML-210 is a GPX-4 inhibitor with potential therapeutic relevance in cancer therapies. However, no validated (bio)analytical methods for its quantification have been reported, limiting its pharmacokinetic and stability investigations. This study describes the development and validation of complementary analytical and bioanalytical methods for the quantification of ML-210 in formulation and biological matrices. An HPLC-UV method was developed for the quantification of ML-210 in intravenous formulations, while a HPLC-MS/MS method was established for its analysis in DMEM culture medium and mouse plasma. Methods were validated according to ICH Q2(R1) and FDA bioanalytical guidelines. The HPLC-UV method demonstrated high specificity, confirmed by forced degradation studies, with accuracy ranging from 98.4% to 108.4% and precision within acceptable limits (intra-day RSD ≤ 0.9%, inter-day RSD ≤ 3.3%). The HPLC-MS/MS method met regulatory criteria for selectivity, sensitivity, carryover, accuracy (89.6-106.7%), precision (RSD ≤ 9.6%), and linearity (R2 ≥ 0.9994) in both matrices. Matrix effects and recoveries showed RSD values below 15%. ML-210 remained stable for at least 6 months at -20°C in both matrices and for approximately 2 h in mouse plasma in vitro at 37°C. The validated HPLC-MS/MS method was applied to an in vivo pharmacokinetic study following intravenous administration in mice (5 mg/kg), revealing a rapid decline in plasma concentration and an elimination half-life of approximately 300 min. These validated methods provide a reliable analytical platform for the quantification of ML-210 in formulation and biological studies, supporting future pharmacokinetic and preclinical investigations.
Herein, we report a rationally designed dual-mode lateral flow assay (LFA) biosensor for the visual detection of microRNA-21 (miRNA-21), a critical breast cancer biomarker. The platform utilizes a synergistic readout of colorimetric signals from gold nanoparticles (AuNPs) and fluorescent signals from quantum dot nanobeads (QDNBs). Upon the specific introduction of target miRNA-21, the conformation of optimized hairpin nucleic acid probes conjugated on the nanomaterials is disrupted. This structural transition exposes capture sites, generating an AuNP-mediated colorimetric signal and a restored QDNBs fluorescence signal on the test lines by mitigating the inner filter effect (IFE) between them. Compared with conventional single-signal or amplification-dependent miRNA sensors, the proposed LFA integrates amplification-free target recognition, complementary AuNP-based colorimetric and QDNB-based fluorescent readouts, and IFE-regulated fluorescence recovery on a single strip, enabling visual screening and smartphone-assisted semi-quantitative analysis without complex instrumentation. Under optimal conditions, both the colorimetric and fluorescent readouts display broad linear correlations with miRNA-21 concentrations (5-1000 nM and 2.5-1000 nM, respectively), the limits of detection (LOD) of 1.599 nM and 1.354 nM. Furthermore, the platform demonstrates remarkable specificity against homologous miRNAs and robust stability. In spiked human serum, the assay achieves satisfactory recovery rates (91.8%-113.2%) with relative standard deviations (RSDs) below 6.0%. Furthermore, a preliminary evaluation using serum samples from five breast cancer patients and five healthy individuals showed clearly distinguishable colorimetric and fluorescent responses between the two groups, supporting the effectiveness of the proposed probe for miRNA-21 detection in real serum samples. These results indicate the potential of the dual-signal LFA platform for further clinical application.
