Evaluation of Alzheimer's disease-associated neuronal thread protein (AD7c-NTP) in urine holds significant potential as a noninvasive and accessible biomarker for the early diagnosis of Alzheimer's disease (AD). In this study, a novel label-free and ultrasensitive electrochemiluminescence (ECL) sensor for detection of AD7c-NTP was designed based on a structurally optimized iridium(III) complex ([(piq)2Ir(CH3CN)2]BF4) as the luminescent probe at a boron-doped diamond (BDD) electrode. After modifying the antibody on the surface of the amino-functionalized BDD electrode, AD7c-NTP molecules were first captured, and then a sandwich immunoassay system was constructed by introducing aptamer-modified gold nanoparticles (AuNPs). Subsequently, [(piq)2Ir(CH3CN)2]BF4 was intercalated into the DNA double-helical structure via electrostatic adsorption, thereby enabling ECL signal detection. Based on the metal-to-ligand charge transfer of iridium complexes at the π-π* energy level and the acceleration of electron transfer from the complexes to the BDD electrode by AuNPs, the established ECL immunosensor exhibited high sensitivity, with a linear range of 0.001-100 ng/mL and an ultralow detection limit of 17.7 fg/mL (S/N = 3). The practicability of the assay was confirmed by the test of AD7c-NTP in human urine, providing valuable information for early screening of AD.

The Golgi apparatus (GA) plays crucial roles in myriad biological processes, and aberrant Golgiphagy has been implicated in a number of pathological settings. Given the lack of suitable imaging tools for Golgiphagy and the propensity of chemical probes to dissipate from stressed organelles, we herein report Golgi-proRed, a pH probe covalently anchored on the GA inner membrane, for imaging of Golgiphagy by red fluorescence triggered upon autophagic delivery of GA into acidic lysosomes. The probe contains a GA-homing entity of blue-to-green fluorescence, a rhodamine-lactam entity that becomes red-emissive in acidic lysosomes, and a moiety of dibenzocyclooctyne (DBCO) for bioorthogonal conjugation with azido-phospholipids metabolically incorporated into the membrane of GA. Upon Golgiphagy, the membrane-anchored probe is codelivered with GA fragments into lysosomes, yielding red fluorescence that serves as the readout of Golgiphagy. The imaging fidelity for Golgiphagy is confirmed by starvation-induced red fluorescence, lysosome-dependent red fluorescence, and lack of such a signal in ATG5-knockout cells deficient in autophagy. With this method, we observed that obvious Golgiphagy occurred in iBMDM cells treated with nigericin and lipopolysaccharides (LPSs) or infected by Listeria monocytogenes. These results show the use of Golgi-proRed for sensitive detection of Golgiphagy in biological events and to screen Golgiphagy-inducing agents.

Serum neurotransmitters (NTs) metabolic network plays a crucial role in bone metabolism. However, due to low concentration, poor chromatographic retention, and limited sensitivity of conventional detection methods, the metabolic characteristics and regulatory mechanisms of the NT metabolic network remain unclear. In this study, a highly specific, sensitive, and accurate strategy integrating d0/d6 DnsCl-based isotope-coded derivatization (ICD) with fragment-imprinted magnetic molecularly imprinted polymers (MMIPs) was established, which enables reliable quantitative determination of 22 NTs (such as HVA, 3-MT, Trpm, Tyr, NAS) in serum. The ICD strategy enhanced chromatographic separation, ionization efficiency, and enabled accurate quantification. The detection sensitivity was enhanced 5.50-346-fold compared with nonderivatized methods. In addition, 4-VP was selected as the optimal functional monomer via molecular docking, and DFT calculations further indicated that the DnsA/4-VP complex is stabilized through the synergistic effects of hydrogen bonding, π-π stacking, and van der Waals forces. The synthesized MMIPs efficiently enriched labeled NTs, with good selectivity (imprinting factors 1.46-2.28), remarkable adsorption capacity (85.0 mg·g-1), and excellent regeneration ability (8 times). This method was further applied to serum samples of ovariectomized postmenopausal osteoporosis rats, and 2 dysregulated metabolic pathways (the Trp metabolic disorder and the Phe/Tyr metabolic disorder) were identified. Longitudinal analysis further identified 7 potential time-dependent biomarkers (such as NAS, Tyr, GABA) associated with bone metabolism. In conclusion, this study developed an integrated approach combining the d0/d6 DnsCl ICD strategy with fragment-imprinted MMIPs to profile the serum NT metabolic network, demonstrating promising application prospects for submetabolome analysis in complex biological matrices.

Immunotherapy eliminates diseased cells by precisely activating or enhancing the patient's immune responses, with its efficacy critically dependent on the accurate modulation of immune cell interaction networks with disease-relevant targets. However, existing methodologies for analyzing cell-cell interactions face inherent trade-offs among throughput, efficiency, and cellular compatibility, and transcriptome-based methods for probing interaction states often result in the loss of cell-pair identities. To address these limitations, we have developed ValveCCI-seq, a microfluidic platform that integrates a deterministic cell-pairing module with an in situ sequencing module for high-resolution profiling of cell-cell interactions. The pairing module achieves a throughput of up to 32,000 cell pairs per hour with an efficiency exceeding 86% and is broadly compatible with diverse cell types. The sequencing module enables direct transcriptome profiling of coencapsulated cell pairs within droplets, eliminating the need for postinteraction demulsification and thereby preserving the identities of both interacting cells. Utilizing Jurkat and T2 cells as a model system, ValveCCI-seq revealed gene expression signatures associated with T-cell activation and demonstrated its capability for the precise identification of tumor antigens and their cognate T-cell receptor (TCR) sequences. In conclusion, ValveCCI-seq preserves interacting cell identities and enables high-throughput analysis, potentially facilitating systematic studies of cellular interactions in clinical samples, supporting parallel TCR screening across multiple antigens, and providing a robust framework to advance cell therapy development.

The liquid microjunction surface sampling probe (LMJ-SSP) is a powerful ambient ionization interface for localized extraction and mass spectrometric analysis. However, the low spatial resolution (∼1.0 mm) and the potential for particle-induced clogging can limit its broader application. We integrate computational fluid dynamics (CFD) modeling with experimental measurements to systematically examine how flow direction governs liquid microjunction stability, shear stress distribution, and clogging propensity. A reverse-flow configuration where solvent is introduced through the inner fused-silica capillary and aspirated through the intercapillary annular gap was applied to overcome the limitations of the traditional design. CFD modeling revealed a pronounced reorganization of streamlines, enhanced shear forces at the liquid-surface interface, and suppressed stagnation zones, producing a more confined microjunction meniscus than the normal flow. Experimental clogging tests with silica microspheres (5, 16, 25 μm) and biological debris indicated a roughly 3-fold reduction in clogging potential under reverse flow, consistent with particle-tracking simulations showing outward radial trajectories that help prevent central blockage. Real-world applicability was confirmed through direct analysis of metabolites from Taraxacum officinale pollen and leaf tissues, where reverse flow enabled sampling from complex, particulate-rich surfaces. Together, these findings establish reverse-flow engineering as a robust strategy for enhancing LMJ-SSP performance, providing improved operational stability, reduced clogging, and consistent surface sampling under mass spectrometric operating conditions.

Precise cancer diagnosis boosts survival rates, but liquid biopsy struggles to identify the tumor histotype from a single blood draw. We propose a Homologous Adhesion Identification (HAI) method that enables specific recognition between tumor extracellular vesicles (tEVs) and homologous tumor cell membrane-coated silica microsphere (TMS). The functionalized TMS exhibits an effective HAI property with high binding strength, speed, and biospecificity between tEVs and TMS, and their similar membrane structures facilitate efficient, rapid, and selective cancer diagnosis. The HAI method can effectively distinguish extracellular vesicles from normal and tumor sources and from different tumor histotypes and subtypes using just 10 μL of serum. It is versatile with replaceable cell membranes and lanthanide ions and supports diverse detection techniques like fluorescence, ultraviolet-visible spectrophotometry, electrochemistry, and electrochemiluminescence (ECL), with a minimum detection limit of 10 tEVs/mL. It accurately differentiates healthy and tumor blood samples in five animal models and shows significant potential for rapid cancer classification and therapeutic monitoring in clinical serum testing, both pre- and postoperatively.

A modulation mechanism for comprehensive two-dimensional liquid chromatography (LC × LC), termed FBF-VAST (forward-backward-flushing valve-assisted selectivity tuning), is introduced. This technique enables modulation using a simple system configuration centered around a 4-port valve. The concept lies in periodic forward-backward flushing of the first-dimension (1D) column, enabling synchronized analyte holding and release with a stepped-gradient transferred to the second dimension (2D). The modulation period (PM) is defined by the forward- and backward-flushing durations (tfwd + tbwd), with the net injection window (Δtnet = tfwd - tbwd) delivering analyte fractions into the 2D-column. These processes were simulated using advection-dispersion equations modified to include analyte retention, resulting in solvent and analyte space-time profiles, along with animations that illustrate the modulation mechanism. A unique selectivity-tuning effect was demonstrated through the 1D-column simulation and LC × LC experiments using two C18 columns operated under a unified binary gradient for red wine sample separation, yielding 27-55 separated peaks of interest. The selectivity can be effectively adjusted solely by tuning the Valve A timing (tfwd) or gradient steepness─without altering mobile phase composition or stationary phase chemistry. Repeatability studies showed %RSDs of peak areas within 5.28-11.77% (n = 6). In addition, the method enabled backflushing for online 1D-column cleaning, which may extend column life and improve robustness. This cost-effective and tunable LC × LC strategy offers enhanced control over chromatographic selectivity and long-term stability, all within a simplified instrumental design.

Although several methods have been developed for the detection of total per- and polyfluoroalkyl substances (PFAS), most of them are not applicable for rapid site characterization. We report a combustion-gas analytical approach for PFAS, offering a simple, robust, and field-deployable method for PFAS screening in soil. We demonstrate that PFAS with varying functional groups and structures are combusted to SiF4 and HF, whereas inorganic fluorine forms only HF. This distinction overcomes a major challenge of inorganic fluorine interference in total PFAS analysis, as SiF4 can be selectively quantified by FTIR. We then applied the method to PFAS measurement in soil samples. Soil was extracted with basic methanol, which further minimized interference from inorganic fluorine and enabled semiquantitative detection, and the extracts were combusted for analysis. The method detection limits ranged from 13 to 16 μgPFAS/gsoil for three PFAS, with relative standard deviations of 34-47% at concentrations near the detection limit, indicating the current applicability of the method as a screening tool rather than quantitation, pending further process development. The developed screening method and tool has the capability to directly screen for PFAS at contaminated sites, which often have total PFAS concentrations between 10 and >100 μg/g.

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder, and diagnosis typically occurs after substantial neuronal loss, underscoring the need for biomarkers capable of detecting early pathological changes. The endocannabinoids anandamide (AEA) and 2-arachidonoylglycerol (2-AG) have been proposed as potential PD biomarkers; however, only their free fractions are biologically active. In this study, an in vivo solid-phase microextraction (SPME) method was developed to quantify free and total concentrations of AEA and 2-AG in rat brain under conditions of negligible depletion. Under these conditions, the SPME probe functions analogously to a sensor, extracting only minute amounts of analyte without perturbing the equilibrium between free and matrix-bound species. Extractions were performed at equilibrium, and experimentally determined distribution constants in PBS were used to calculate free concentrations. Matrix-binding percentages exceeded 99% for both analytes and were used alongside with free concentration measurements to estimate total concentration levels. In vivo analyses in a 6-OHDA rat model of PD revealed significant elevated striatal AEA levels in lesioned animals relative to controls, supporting its potential as a biomarker of early neurochemical alterations. In contrast, ex vivo SPME extractions in dissected brain did not show increased AEA levels in the PD group, indicating loss of physiologically relevant information post-mortem. Although 2-AG was not detected in vivo, it was quantified ex vivo, suggesting limited active release under the examined conditions. Overall, these findings highlight the capability of in vivo SPME to capture changes in heavily bound hydrophobic neurochemicals, thereby supporting its application in studies of endocannabinoid dysregulation.

The COVID-19 pandemic has accelerated interest in immuno-multiple reaction monitoring (immuno-MRM) for peptide quantification, with early efforts focusing on SARS-CoV-2 biomarker detection in clinical nasopharyngeal swabs. However, the emergence of mRNA vaccines has created a new and pressing need for robust methods to quantify antigen expression. Here, we present an optimized immuno-MRM method targeting the SARS-CoV-2 spike fusion peptide SFIEDLLFNK, designed and validated to quantify antigen expression following mRNA or plasmid transfection. This method offers high sensitivity, precision, and linearity across a broad dynamic range, enabling an accurate assessment of protein translation in vitro. In addition to measuring antigen levels, analysis of the flow-through provides insight into host cell proteomic responses, supporting the comprehensive characterization of mRNA vaccine efficacy and safety. This dual-function workflow serves as a powerful tool for vaccine development, quality control, and regulatory evaluation of RNA-based therapeutics.