Proteolysis-targeting chimeras (PROTACs) are a novel technique for degrading proteins of interest (POIs) by the cellular protein ubiquitination degradation pathway, and this technique has emerged as an innovative strategy for targeting undruggable proteins. Despite significant progress in PROTAC technology, a major challenge remains in the in situ acquisition of concentration-dependent equilibrium profiles and kinetic information on the interaction between POIs and PROTAC molecules and the POI degradation kinetics within living cells. Here, we proposed a novel method for in situ monitoring PROTAC-induced target protein degradation by combining multi-channel fluorescence cross-correlation spectroscopy (FCCS) and protein fusion technology. In this study, ABL1 was used as the target protein. We designed three plasmids encoding fluorescent fusion proteins: a fusion protein comprising SNAP, mCherry, and ABL1; a fusion protein comprising eGFP and E3 ligase VHL; and a fusion protein comprising Halo and ubiquitin. We developed a multi-channel FCCS system and in situ studied the concentration-dependent equilibrium profiles and kinetics of ternary complex formation among PROTACs, ABL1, and VHL; the ubiquitination of ABL1; and PROTAC-induced degradation of ABL1. Furthermore, we propose a new approach for evaluating the efficacy of PROTAC molecules on the basis of the degradation processes of the target protein. The results demonstrated that our method can in real time monitor the formation of the PROTAC-induced ternary complex, the ubiquitination process, and the target protein degradation in living cells; evaluate the efficacy of PROTAC drugs; and will become an efficient platform for studying the pharmacodynamics of PROTAC drugs and developing new PROTAC drugs.

The advent of nucleic-acid-based therapeutics has revived the need to develop efficient capillary gel electrophoresis methods for their rapid, high-resolution analysis. In this paper, we introduce a dual-network hydrogel-based physical copolymer, utilizing the excellent sieving properties of hydroxyethyl cellulose with interpenetrating polyvinylpyrrolidone, which also sufficiently suppresses electroosmotic flow. Boric acid in the background electrolyte served as a cross-linker/stabilizer for the hydroxyethyl cellulose-based separation matrix via the formation of spiroborane bridges. The addition of glycerol significantly increased the resolution of separations. The excellent sieving power of the tetrahydroxyborate-stabilized HEC-PVP physical copolymer is demonstrated by the separation of dsDNA restriction fragments in a wide base pair range of 67 to 10 000, even capable of resolving identical chain length fragments. As a practical example, plasmid DNA integrity monitoring was demonstrated, facilitating the path toward a novel high-resolution separation matrix for gene therapy products in the biopharmaceuticals industry.

Excitation-emission matrix (EEM) fluorescence spectroscopy is widely used for characterizing complex samples in food analysis and environmental monitoring, but its practical deployment is limited by the trade-off between spectral resolution and acquisition speed. High-resolution EEM acquisition is time-consuming, whereas rapid low-resolution measurements lose analytically important spectral details. Herein, we introduce SuperEEM, a chemically constrained super-resolution framework for converting rapidly acquired sparse EEMs into analytically reliable high-resolution EEMs. Unlike generic image super-resolution approaches that mainly optimize visual similarity, SuperEEM couples an EEM-tailored U-Net-GAN architecture with a quantitative-fidelity-oriented loss function to preserve fluorescence intensity, peak topology, and excitation-emission relationships. The analytical reliability of SuperEEM was validated using three representative tasks: polycyclic aromatic hydrocarbon (PAH) quantification, edible oil classification, and beer classification. Compared with LR EEMs, SuperEEM-reconstructed EEMs substantially improved downstream performance, achieving PAH quantification comparable to original HR EEMs and improving classification accuracy from 77.4% to 90.3% for edible oils and from 73.3% to 86.7% for beers. Under the tested instrumental settings, SuperEEM enabled a 14-fold improvement in EEM acquisition efficiency while maintaining analytical reliability. A graphical user interface (GUI) was further developed to support model application, visualization, and result export. These results demonstrate the potential of SuperEEM for rapid, high-throughput fluorescence analysis.

Efficient O2 activation by co-reaction accelerators is instrumental in boosting luminol-O2 electrochemiluminescence (ECL) performance, delivering enhanced emission intensity. However, the operational durability remains fundamentally limited by alkaline-mediated support corrosion and progressive destabilization of active sites during O2 activation, resulting in metal dissolution and structural degradation, which compromises the durability of the ECL system. Herein, fluorine (F)-doped Ni single-atom catalysts (SACs) (NiNFC SACs) were developed as co-reaction accelerators for O2 activation, which significantly enhanced ECL stability. Experimental studies and theoretical calculations reveal that F serves as an electron-buffering site through efficient and concerted electron transfer with Ni during O2 activation to adjust Ni electron density, alleviating the burden on Ni and preserving Ni-N bond stability. Finally, based on the inhibition effect of organic pollutants toward proposed ECL platform, a dual-channel sensor array is constructed to distinguish and simultaneously detect five different ionization potential value organic pollutants with high selectivity. This innovative strategy offers new insights for achieving the stable ECL emission required for practical applications.

High-performance luminescent materials are indispensable for advancing the development of electrochemiluminescence (ECL). In this work, a series of organic small-molecule ECL materials viologens were rationally designed and synthesized, which possess favorable redox activity, superior water solubility, and outstanding luminous efficiency. All prepared samples generate intense annihilation and coreactant-promoted ECL signals. Experimental and theoretical investigations demonstrate that side-substituted groups can greatly modulate the ECL properties. Among them, viologen Nap-Py-2PF6 with a large conjugated framework delivers the highest luminous efficiency, up to 74.36%. Relying on the facile complexation between the probe and uric acid, the established sensing strategy realized ultrasensitive detection of uric acid in real samples. This study pioneers the application of viologen derivatives in ECL sensing and explores their favorable luminescence properties, offering an effective new route for uric acid quantitative analysis.

Cell deformation during microfluidic transport evolves continuously, whereas cell phenotyping commonly relies on geometric descriptors measured at one or a few predefined channel positions. Such fixed-position measurements capture selected deformation states but overlook how the cellular response progresses along the flow path. Combined with high-speed imaging, hyperbolic microchannels capture this progression as a continuous trajectory, enabling the shift from static morphological measurements to a dynamic response analysis. However, cell-to-cell differences in transit velocity cause equivalent image frames to represent different channel positions and hydrodynamic conditions, preventing a direct comparison of frame-indexed deformation trajectories. Here, we develop a trajectory-resolved framework that converts high-speed microfluidic image sequences into position-aligned dynamic cell deformation trajectories and uses deep learning to model their cell line-specific evolution for label-free ovarian cell phenotyping. Geometric and kinematic trajectories were extracted from three ovarian cancer cell lines (A2780, OVCAR-3, and SKOV-3) and one nonmalignant ovarian epithelial cell line (IOSE-80) at three flow rates. The trajectories were reparameterized by the axial position and resampled on a common spatial grid. Class-specific one-dimensional convolutional neural networks predicted downstream trajectories from the inlet state and flow conditions. An unknown cell was classified by comparing its measured trajectory with class-specific predictions, and prediction errors in the width, area, perimeter, and axial velocity were integrated by soft voting. The framework achieved 93.26% accuracy, 94.07% macro precision, 90.25% macro recall, and a 91.85% macro-F1 score on the held-out test data. These results support extending microfluidic cell phenotyping from isolated geometric states to the position-aligned analysis of dynamic deformation trajectories.

Accurate and precise quantification of trace-level cytokines in complex biological matrices remains challenging, limiting their use as longitudinal biomarkers in clinical studies. Here, we present a nanotechnology-enabled surface-enhanced Raman scattering (SERS) platform incorporating an internal standard (IS) for digital, attomolar-level multiplex cytokine quantification. This platform enables precise digital trace-level detection of IL-1β, IL-6, IL-12, and TNF-α. Using an orthogonal recombinant protein IS to correct assay- and SERS-related variability, this platform addresses key barriers to reliable trace-protein measurements and broader clinical adoption. Incorporation of the IS reduced the inter-replicate coefficient of variation from ∼40-60% to 2-3%, and improved accuracy to ∼95-105%, enabling robust cytokine quantification in human plasma. Compared with a widely used clinical electrochemiluminescence (ECL) assay, our internal-standard-integrated chip enables accurate and precise quantification while maintaining multiplex capability, consistently detecting cytokine levels near or below ECL-defined quantification limits. As a proof-of-concept application, we evaluated the platform using plasma samples from individuals with MDD, a clinically relevant context in which aberrant immune activation and low-level inflammation have been implicated. These measurements support the analytical robustness of the internal-standard-integrated digital SERS immunoassay and its potential utility for future longitudinal cytokine monitoring studies in complex samples.

As environmental and climatic changes intensify, plants and fruits are frequently exposed to abiotic stresses, leading to excessive accumulation of nitric oxide (NO) and disruption of cellular redox homeostasis, so noninvasive monitoring of NO is of great importance. In this study, MX@Fe/NiPor-MOF was constructed at room temperature by assembling a bimetallic porphyrin-based metal-organic framework (Fe/NiPor-MOF) with transition metal carbide nanosheets (MX), and further integrated with screen-printed carbon electrodes (SPCEs) for noninvasive NO detection in plants and fruits. The cooperative interaction between Fe/Ni bimetallic centers enabled efficient electron redistribution, with Ni acting as an electron reservoir to facilitate rapid and reversible Fe2+/Fe3+ redox cycling. Meanwhile, the porous MOF structure and highly conductive MX promoted the exposure of Fe-N4/Ni-N4 active sites and established efficient electron transport pathways. Benefiting from these structural and electronic advantages, the MX@Fe/NiPor-MOF/SPCE electrochemical sensor exhibited excellent electrocatalytic performance toward NO detection, including a wide linear range (0.5-565.5 μM), a low detection limit (0.14 μM), a high sensitivity (1.95 μA·μM-1·cm-2), and excellent anti-interference capability. As a proof of concept, the platform enabled real-time, noninvasive electrochemical monitoring of microscale NO release from plant and fruit tissues subjected to thermal treatment and mechanical wounding. This work highlights the role of bimetallic synergy in enhancing NO electrocatalysis and provides a promising strategy for in situ monitoring of gaseous signaling molecules in plant and fruit tissues.

A novel pulsed discharge photoelectron ionization detector (PDPEID) was developed and evaluated for gas chromatographic detection. The detector is derived from a previously developed pulsed discharge helium ionization detector (PDHID), which uses high-energy photons generated by a pulsed electrical discharge as the ionization source. In the PDPEID, electrons produced from the same discharge are additionally utilized to ionize analytes, thereby significantly enhancing detector response. Because the electron flux generated during discharge is substantially greater than the photon flux, the PDPEID produces a much larger detector signal, with an average response approximately 20-40× higher than that of the PDHID. Although the increased background current results in higher noise levels, the overall sensitivity for n-pentane improved by approximately 1 order of magnitude relative to the PDHID. The photoionization and electron-ionization signals can be temporally resolved because of the large difference in transport velocities between photons and electrons within the detector cell. Electrons generated through photoionization are collected more rapidly than those produced through electron-ionization processes. Consequently, the photoionization signal appears nearly simultaneously with the discharge pulse, whereas the electron-ionization signal is delayed by approximately 40 μs, depending on the applied bias potentials. Because electron-ionization involves lower-energy electrons and electron-capture interactions distinct from those of photoionization, the relative magnitudes of the two signals provide complementary chemical information. The ratio of photoionization to electron-ionization response may therefore provide a useful semiqualitative parameter for differentiating compounds based on ionization potential and electron affinity.

The spatial distribution of endogenous small-molecule metabolites is pivotal for understanding living processes, disease mechanisms, and therapeutic principles. However, achieving high-sensitivity spatial metabolomic profiling remains challenging for atmospheric pressure mass spectrometry imaging (AP-MSI) due to low desorption/ionization efficiency, leading to the systematic omission of low-abundance yet biologically vital metabolites from spatial maps. Here, we developed a high-sensitivity MSI platform that integrated a polydopamine/covalent organic framework (PDA/COF) composite substrate with atmospheric pressure laser ablation carbon fiber ionization (LACFI) technology for spatial mapping of endogenous small-molecule metabolites in biological tissues. This substrate employed a polydopamine (PDA) interlayer to guide the ordered assembly of a COF on the substrate. The resulting PDA/COF composite substrate exhibited uniform surface coverage, strong stability, and excellent light absorption, collectively improving the laser desorption/ionization efficiency of metabolites. Moreover, the substrate was simple, easy to use, and cost-effective. Our platform demonstrated a significantly enhanced sensitivity, achieving an improvement of more than 2-fold based on the slope of the linear calibration curve for analysis of metabolites compared with MALDI, DESI, LACFI using copper-coated, graphene oxide, and COF substrate. It also exhibited excellent linear response, wide dynamic range, and broad metabolite coverage. The platform was further applied to map the metabolomes of normal, para-cancerous, and cancerous liver tissues and, through heatmap analysis, clearly revealed the spatial distribution patterns of metabolites such as NAD+ and adenine across these tissue types. This method provides a straightforward, efficient, and robust AP-MSI platform for highly sensitive and comprehensive spatial metabolomics.

Nitric oxide (NO) is an important gaseous signaling molecule involved in vascular regulation, neural transmission, and immune responses. However, its short lifetime, low steady-state concentration, and dynamic release behavior make real-time in situ monitoring challenging, particularly in phototriggered NO release systems. Herein, a dual-functional photoelectrochemical (PEC) platform was developed by integrating a UiO-66 surface layer with a CuPc/SrTiO3 heterojunction photoelectrode for simultaneous NO detection and dynamic monitoring of nitroglycerin-triggered NO release. The CuPc/SrTiO3 heterojunction promotes photogenerated charge separation, while the UiO-66 layer enriches NO through abundant Zr-O active sites, enhancing the interfacial response. Under illumination, nitroglycerin releases NO while the photoelectrode generates a stable photocurrent. The released NO consumes photogenerated holes, producing a concentration-dependent photocurrent decrease, enabling real-time kinetic analysis. The PEC platform exhibited a linear range of 0.063-10 nM, a detection limit of 0.019 nM (S/N = 3), and a quantification limit of 0.063 nM (S/N = 10), with good selectivity, stability, and reproducibility. The platform also enabled continuous monitoring of nitroglycerin-induced NO release in a simulated physiological environment, providing a PEC-based strategy for investigating photoinduced gas generation and release kinetics.

Electrospray ionization (ESI) and laser desorption ionization (LDI) exhibit inherent limitations when applied as standalone ion sources for the mass spectrometric analysis of microplastics (MPs). Herein, we report an ambient laser desorption electrospray ionization mass spectrometry platform, CSAA-LESI-MS, using low-cost, readily available, and eco-friendly calcined sand as the matrix. This system achieves qualitative and quantitative identification of MPs with varied optical and physicochemical characteristics, including strongly and weakly light-absorbing, polar and nonpolar MPs. Efficient ionization of all analyzed polymers was achieved within 1.2 s, affording nanogram-level limits of detection (LODs) and limits of quantification (LOQs) with correlation coefficients (R2) all exceeding 0.98. Seven representative polymer classes, including polyethylene (PE), polypropylene (PP), polyamide 6 (PA6), poly(methyl methacrylate) (PMMA), poly(ethylene terephthalate) (PET), polylactic acid (PLA), and poly(oxymethylene) (POM), yielded abundant, well-resolved backbone-specific fingerprint spectra. A total of 15 suspected particles were further distinguished successfully by PPMC-based spectral matching against polymer reference libraries. The CSAA-LESI-MS method provides a versatile, economical, and precise ambient mass spectrometry approach feasible for environmental MP analysis.

Expanding single-tube multiplexing beyond the number of fluorescence channels on a real-time PCR instrument is a persistent challenge for point-of-care testing (POCT). Here, we break this barrier by leveraging melting temperature (Tm) as an extra information dimension. By employing a probe-cleavage-mediated reporter-duplex strategy, we circumvent the conventional limitation that hydrolyzed TaqMan probes cannot participate in postamplification melting analysis. Two FAM-labeled probes, each containing an engineered 5'-terminal nontarget extension, generate cleavage-dependent reporter amplicons with distinctly different melting temperatures (ΔTm = 10.3 °C), enabling precise differentiation between BV (72.5 °C) and BY (82.8 °C) within a single optical channel. Combined with a lyophilized-bead cartridge that automates nucleic acid release (4 min) and an ultrafast PCR run (16 min), the platform detects eight targets─seven respiratory pathogens (SARS-CoV-2, influenza A H1N1/H3N2/H5N1 clade 2.3.4.4b, influenza B Victoria/Yamagata, and Mycoplasma pneumoniae) plus one internal control (B2M)─using only six optical channels. The assay achieves a limit of detection of 5 copies per reaction (R2 > 0.97, amplification efficiency 96-104%) with no cross-reactivity against 55 nontarget microorganisms, and intra/inter-assay CVs < 5%. The lyophilized beads remain stable for 12 months at 25 °C (ΔCt < 1.5). In 272 clinical throat swabs, the system shows 100% agreement with single-plex qPCR. Mixed BV/BY infections produce two distinct melting peaks, with the low-abundance peak detectable down to a 400:1 ratio under the tested conditions. This six-channel ultrafast PCR system reliably detects eight targets in one tube within 20 min without extra hardware, providing a generic strategy for higher-order multiplexing in point-of-care settings.

Biomass-burning aerosols contain complex mixtures of soot carbon (SC), brown carbon (BrC), organic carbon (OC), and inorganic (IN) constituents whose spatial distributions within individual particles strongly influence aerosol optical properties, atmospheric chemistry, and climate impacts. Scanning transmission X-ray microscopy (STXM) coupled with near-edge X-ray absorption fine structure spectroscopy (STXM/NEXAFS) is widely used to characterize the composition and mixing state of individual particles; however, existing approaches cannot explicitly distinguish SC from BrC because both exhibit strong aromatic π*C═C absorption at 285.4 eV. Here, a novel X-ray spectromicroscopic method at the carbon K-edge is introduced to resolve SC and BrC at the nanoscale within individual particles. The approach exploits differences between the aromatic π*C═C transition at 285.4 eV and the soot-specific σ*Graphitic-like(GL) transition at 307.0 eV. Analysis of STXM/NEXAFS spectra of biomass-burning particles, laboratory-generated BrC proxies, tar balls, and soot reference particles demonstrates that the relative intensities of these transitions provide a robust basis for differentiating SC and BrC. An integrated peak ratio and a simplified four-energy Soot Index (SI) were developed to classify particle components and generate spatially resolved maps of SC, BrC, OC, and IN at the nanoscale. The SI reproduces classifications obtained from full spectral deconvolution while enabling rapid, pixel-resolved chemical imaging. Application of this method reveals substantial variability in the internal distributions of SC and BrC within biomass-burning particles and demonstrates that conventional STXM mapping approach frequently classifies BrC-rich regions as elemental carbon. The new analytical framework expands the capabilities of X-ray spectromicroscopy for atmospheric aerosol characterization and provides improved particle-resolved constraints on aerosol composition, mixing state, and morphology.

Rapid and accurate genotyping of Bordetella pertussis (BP) is essential for guiding antimicrobial therapy and epidemiological surveillance. However, existing genotyping methods often involve multistep workflows and postamplification handling, increasing the risk of aerosol contamination and limiting their applicability in resource-limited settings. Here, we present a closed-tube, one-pot strategy that integrates loop-mediated isothermal amplification (LAMP) with an enzyme-free catalytic hairpin assembly (CHA) circuit for the simultaneous detection and genotyping of wild-type BP and the antibiotic-resistance A2047G mutant. In this platform, LAMP provides rapid and efficient isothermal amplification, while the CHA circuit directly converts amplification products into fluorescence signals and enables single-nucleotide discrimination through sequence-specific recognition, thereby improving genotyping accuracy without increasing assay complexity. The integrated assay combines rapid detection, high specificity, and a simple closed-tube workflow with minimal instrumentation requirements, making it well suited for point-of-care testing and applications in resource-limited settings.