Trace detection of methane (CH4) and hydrogen (H2) is critical for energy infrastructure monitoring and safety management. However, conventional photoacoustic spectroscopy (PAS) approaches rely primarily on optical absorption and often require carrier gases or complex configurations for H2 detection. Here, we report a hybrid photoacoustic sensing strategy that combines optical absorption-based detection with acoustic property tracking, enabling simultaneous and carrier-gas-free detection of CH4 and H2. In this approach, CH4 is quantified using second harmonic (2f) wavelength modulation spectroscopy, while H2 is detected via first harmonic (1f) frequency tracking based on sound-speed-induced resonance shifts. A multi-pass resonant photoacoustic cell is employed to enhance sensitivity, and in situ temperature compensation is achieved using a fiber Bragg grating (FBG) array to mitigate temperature-dependent variation in the acoustic response. The system achieves minimum detection limits of 17.7 ppb for CH4 and 1.39 ppm for H2 at an integration time of 100 s, without the use of carrier gases. The normalized noise equivalent absorption coefficient for CH4 detection reaches 1.07 × 10-9 cm-1·W·Hz-1/2. This hybrid sensing framework provides a generalizable approach for multi-gas detection by integrating optical and thermodynamic sensing mechanisms, offering a new pathway for high-sensitivity and robust gas analysis in complex environments.

Inflammatory bowel disease (IBD) is a chronic intestinal disorder with increasing incidence globally. Accurate assessment of its progression is essential for clinical management but remains challenging. Herein, we report a GzmA-activatable near-infrared (NIR) nanoprobe IR780 NP@S100 for stage-differential imaging of DSS-induced acute colitis. A molecular precursor, Cys(StBu)-Gly-Phe-Phe-Arg-Lys(IR780)-CBT (IR780-CBT), was designed to prepare the fluorescence-quenched nanoparticle IR780 NP in vitro with a CBT-Cys click reaction. In the presence of granzyme A (GzmA), a serine protease associated with IBD, IR780 NP was disassembled to turn the NIR fluorescence "On". For in vivo application, IR780 NP was encapsulated in Eudragit S100 to afford IR780 NP@S100 which stabilized the nanoparticle in the stomach but specifically released it in the colon. For IBD mouse models at an early stage (day 4) with higher expression of GzmA, IR780 NP showed higher "On" fluorescence in their colons. However, it showed lower "On" fluorescence in the colons of IBD mice at the late stage (day 8). Moreover, IR780 NP enabled fecal fluorescence analysis of IBD, providing a complementary noninvasive readout for monitoring colitis progression. We anticipate that IR780 NP@S100 can be applied for stage-differential imaging of acute colitis in the clinic in the near future.

A novel gas sensing method based on heterodyne Mach-Zehnder interferometric phase-dispersion spectroscopy (HMIPDS) was proposed for the first time in this work. The proposed method employed a heterodyne Mach-Zehnder interferometric configuration to realize gas sensing through cumulative optical phase shifts induced by refractive-index variations during laser-gas interaction. Specifically, the laser beam was divided into a signal arm interacting with the gas medium and a reference arm frequency-shifted by an acousto-optic modulator (AOM) to generate heterodyne interference. The gas-induced optical phase variation was then accurately extracted via quadrature demodulation of the interference signal, thereby enabling quantitative retrieval of gas concentration. Acetylene (C2H2) was used for experimental validation. Experimental results demonstrate the HMIPDS method achieved a detection limit of 708 ppb with an integration time of 500 s, corresponding to an approximately 11-fold improvement in detection sensitivity compared with the conventional WMS-2f detection system (8 ppm at 500 s). Furthermore, the linear dynamic detection range was extended from 0 to 2% for conventional WMS-2f to 0-5%, corresponding to an approximately 2.5-fold enhancement. The proposed HMIPDS method provides a high sensitivity, high stability, and wide dynamic range solution for gas sensing, showing strong potential for high-concentration and ultrasensitive trace gas detection applications.

Probe selection for in vivo chemiluminescence imaging commonly relies on intensity and tissue-overlay measurements performed in vitro, yet these measurements do not reproduce the activation background, probe distribution, and optical environment of a living animal. Here, we test how measurement context affects probe ranking using two ONOO--responsive bicyclic dioxetanes, Probe 1 and Probe 2, that share the same arylboronate trigger and closely related core architecture but emit at different wavelengths. In black 96-well plates after ONOO- activation, the visible-emitting Probe 2 produced approximately 350-fold greater photon output than Probe 1, and Probe 2 retained the larger signal-to-background ratio in a chicken-tissue overlay experiment. These in vitro and ex vivo measurements would both favor Probe 2. In living mice, however, the ranking by analytical contrast changed. Probe 1 afforded a subcutaneous signal-to-background ratio of 489 and produced an approximately 7-fold challenged-to-control contrast in an Escherichia coli-induced peritonitis model, compared with approximately 1.5-fold for Probe 2, the absolute signal difference narrowed to approximately 3-fold. This environment-dependent reordering shows that plate intensity and tissue overlays alone can misrank probes intended for in vivo analysis. Emission wavelength, preactivation background, tissue transmission, and model-specific signal distribution must be evaluated together.

Compound-specific stable isotope analysis (CSIA) is widely used to distinguish sources and transformation pathways of organic compounds. In steroid CSIA each analyte is represented by a single molecular-average isotope value, which can limit discrimination when sources overlap in isotopic composition. This limitation is especially important in anti-doping analysis, where molecular-average δ13C measurements can be inconclusive for compounds whose C-isotope composition falls within the endogenous range. Here, we present an Orbitrap-based method for fragment-resolved intramolecular isotope analysis of steroids. Using urinary androsterone as a model analyte, we measured δ13C values for four diagnostic ions and δD for one fragment following controlled administration of androstenedione and testosterone undecanoate. The resulting multidimensional isotope fingerprints reveal responses not evident from bulk δ13C measurements alone, including cases in which administered androgen lies near the endogenous δ13C range. Time-dependent differences among fragment ions further suggest sensitivity to changes in metabolic routing and pool mixing during steroid transformation. These results establish fragment-resolved isotope analysis by Orbitrap mass spectrometry as a promising extension of conventional steroid CSIA and a potential new tool for forensic steroid source discrimination, with possible applications to environmental steroids and geological sterols and steranes.

Direct proteome analysis of identified neurons in intact brain tissue remains limited by the difficulty of recovering intracellular material while preserving native tissue context and avoiding physical extraction of the intact soma. Here, we establish aspiration patch proteomics as a mass spectrometry (MS)-compatible microsampling strategy for proteome-level analysis of somal cytoplasmic aspirates from fluorescently identified neurons in acute mouse brain slices. The workflow combines patch-pipet aspiration, volatile internal-solution chemistry, minimal-loss bottom-up proteomics, and high-sensitivity capillary electrophoresis (CE)-electrospray ionization (ESI)-MS on a timsTOF platform. Optimization of the patch internal solution revealed a strong trade-off between electrophysiological compatibility and proteomic depth, identifying ammonium bicarbonate as an enabling volatile electrolyte for downstream CE-ESI-MS analysis. Applied to dopaminergic, parvalbumin, and serotonergic neurons, the method identified hundreds to >1000 proteins from optimized single-neuron somal cytoplasmic aspirate measurements while analyzing only ∼0.4% of the processed digest per CE-ESI-MS run. Across neuronal classes, 1894 protein entries were identified and 1703 were quantified, yielding reproducible label-free profiles sufficient to separate biological replicates by neuronal phenotype and distinguish neuronal classes from protein expression alone. These results show that aspiration-based recovery of somal cytoplasm yields sufficient proteomic information for subtype-level single-neuron proteotyping while maintaining intact-tissue targeting and avoiding cell dissociation or physical extraction of the intact soma. Aspiration patch proteomics therefore provides a chemically compatible sampling front end for MS-based analysis of identified neurons in native brain tissue.

DNA aptamers are widely used in the construction of fluorescent sensors, typically employing labelled fluorophores as signaling indicators. However, this covalent labeling approach suffers from several limitations, including complex and costly chemical modification, incompatibility with long aptamer sequences, and susceptibility to false-positive signals. To address these limitations, we constructed a novel aptamer-based fluorescent sensor using Lettuce indicator, a light-up DNA aptamer that adopts a precise three-dimensional structure, which enables it to selectively bind and activate the otherwise non-fluorescent small-molecule fluorophores. In our design, we destabilized Lettuce by fusing it with a target-binding aptamer via a transducer sequence. Upon target binding, structural rearrangement is triggered through the transducer, leading to the folding of Lettuce and restoration of its ability to activate the fluorophore, generating a target-dependent fluorescent signal. Through systematic optimization of the transducer and target-binding aptamer sequences, we created sensors for diverse targets, including small molecules, proteins, and metal ions. These sensors exhibit high signal-to-noise ratios, sensitivity and selectivity, and a wide dynamic range. As a proof-of-concept demonstration, a paper-based test strip for cost-effective and rapid detection of small molecule mycotoxins was developed. This versatile design provides a generalizable platform for the development of aptamer-based sensors, opening the way for future detection of diverse analytes.

MicroRNA (miRNA) analysis using organic photoelectrochemical transistor (OPECT) biosensors is often limited by insufficient photoelectric transduction efficiency and weak signal amplification. Herein, we develop a coordination heterojunction photogate-enabled OPECT biosensor combined with enzyme-free catalytic hairpin assembly and hybridization chain reaction (CHA-HCR) cascade amplification for ultrasensitive detection of miRNA-122. Interfacial Cu+-alkyne coordination between Cu2O and Cu-1,4-diethylenylbenzene facilitates charge transfer and photogenerated carrier separation, leading to enhanced photogating efficiency. Meanwhile, target miRNA-122 initiates sequential CHA and HCR reactions, producing extended DNA chains that accumulate at the gate/electrolyte interface and modulate the local charge environment, thereby amplifying the transistor response. The synergistic integration of coordination photogating and nucleic acid cascade amplification significantly improves analytical sensitivity (an ultralow detection limit of 0.26 fM) and selectivity toward miRNA-122. This strategy provides an effective route for constructing high-performance OPECT biosensors and broadens their applications in cancer biomarker detection.

Accurate quantification of 25-hydroxyvitamin D3 (25(OH)D3), the gold-standard biomarker for vitamin D nutritional assessment, still presents considerable analytical challenges. Although 25(OH)D3 exhibits intrinsic photosensitivity and thermal lability, these properties can be effectively managed via standardized light-shielding and inert-atmosphere operations. Key bottlenecks for its immunoassay lie in empirical-driven antibody screening lacking systematic theoretical guidance and poor discrimination of structurally similar vitamin D metabolites. To address these bottlenecks, we explored the molecular-recognition mechanism of high-affinity monoclonal antibody mAb-1F3 toward its hapten using molecular-docking and binding-pocket analysis. Four key amino-acid residues (PHE 52, PHE 91, TYR 32, ILE 100) within the antibody complementarity-determining region form a cooperative binding network for specific recognition of the steroid nucleus and C25-hydroxyl moiety of 25(OH)D3. π-alkyl interactions from PHE 52, PHE 91 and TYR 32 stabilize the hydrophobic steroid skeleton, while ILE 100 forms a conserved hydrogen bond (2.8 Å) to realize specific recognition of the C25-hydroxyl group. This structurally synergistic binding mechanism endows mAb-1F3 with high affinity (IC50 = 24.8 ng/mL) and favorable metabolite-discriminating capability. Guided by this mechanistic insight, recombinant mAb-1F3 was prepared and integrated into a rapid colloidal-gold lateral-flow immunoassay (LFIA). Standard matrix-specific sample extraction procedures were adopted to mitigate matrix interference induced by the high lipophilicity of 25(OH)D3 in complex samples. The LFIA completes the detection within 5 min and shows satisfactory linear consistency with LC-MS/MS in raw milk, dietary supplement, and human serum matrices. This work establishes a structure-driven strategy for rational antibody characterization and design, provides critical mechanistic support for conventional empirical antibody-screening workflows, and facilitates performance improvement of vitamin D immunoanalytical methods.

Metabolite annotation remains a major bottleneck in untargeted metabolomics, limiting biological interpretation of large-scale mass spectrometry data sets. Although substantial advances have been made through spectral libraries, machine learning-based annotation models, and community benchmarking efforts, many recently developed tools remain difficult to incorporate into routine workflows because they are distributed as research-oriented software with complex dependencies and nonstandard interfaces. Here, we present MetaboAnnotate, a web-based framework that uses a large language model (LLM) in a multiagent system to orchestrate multiple metabolite annotation tools through a unified natural-language interface. The system enables users to submit MS/MS spectra and execute multitool annotation workflows without local installation or programming expertise. The current implementation integrates complementary methods, including SIRIUS, FLARE, JESTR, and DiffMS. Evaluation on the CASMI 2016 and CASMI 2022 benchmarks shows that agreement among independent annotation tools substantially reduces false discovery rates and improves annotation accuracy. Application to a fecal metabolomics data set further demonstrates the utility of multitool consensus for identifying high-confidence putative metabolites. MetaboAnnotate is available at: https://hassounlab.cs.tufts.edu/MetaboAnnotate/.

Exosomes are nanoscale vesicles that are attractive for liquid biopsy, but most methods deliver ensemble averages and obscure how surface biomarkers vary across individual vesicles. We develop a single-particle impact electrochemistry (SPIE) assay to profile epithelial cell adhesion molecule (EpCAM) on single exosomes. EpCAM-positive vesicles are labeled with silver nanoparticle-aptamer conjugates. Each labeled exosome yields an silver oxidation spike upon collision with a polarized ultramicroelectrode. Impact frequency reports the abundance of EpCAM-positive exosomes, while the integrated spike charge provides a semiquantitative proxy for per-vesicle EpCAM. Using MCF-7 (EpCAM-high) and HeLa (EpCAM-low) exosomes, we confirm EpCAM-dependent signals and resolve intrapopulation heterogeneity. For serum samples from healthy donors and breast cancer patients at different clinical stages, SPIE reveals stage-dependent increases in both EpCAM-positive exosome counts and per-vesicle EpCAM load, consistent with nanoflow cytometry. This nonoptical platform enables semiquantitative single-exosome protein phenotyping in complex matrices, offering potential for disease-state-associated exosome analysis, clinical research, and future multiplexed profiling.

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics of trace-level samples, such as tens of cells or spatially resolved tissue regions, offers unique biological insights but is often constrained by the requirement for specialized, costly instrumentation. In this study, we developed a scalable workflow for the deep proteomic analysis of low- to ultralow-input samples by systematically optimizing a widely adopted Orbitrap and UHPLC platform to maximize sensitivity, precision, and throughput. This optimized workflow identified over 5600 proteins from 5 ng of peptides and 3400 proteins from 20 sorted cells, achieving a throughput of 30 analyses per day while maintaining deep proteome coverage and high quantitative reproducibility. Furthermore, by applying this method to spatially resolved proteomics, we identified over 6100 proteins from microscale regions of interest (ROIs) within a formalin-fixed, paraffin-embedded (FFPE) tissue. A data-driven normalization strategy was employed to correct for variable cellularity across tissue regions, effectively revealing intratumor heterogeneity and distinct molecular and functional signatures, including pathway activations not apparent in parallel spatial transcriptomic analysis. Ultimately, this accessible, high-performance method substantially lowers the instrumentation barrier for the deep proteomic profiling of trace-level biological samples.

We report the development and demonstration of a simplified and robust photoacoustic (PA) technique by integrating an External Cavity Interband Cascade Laser (EC-ICL) with a dual PA cell configuration for the quantitative characterization of hydrocarbon aerosols in the mid-infrared range of 3.30 to 3.55 μm. The EC-ICL source was selected for its stable optical output, compact design, and low power consumption. By flowing a known gas through one PA cell, a wavelength-dependent transfer function (TF) is established and subsequently used to retrieve absolute absorption coefficients from the analyte aerosol measured in the second PA cell. As a proof of concept, propane was employed as the reference gas and diethyl-hexyl-sebacate (DEHS) aerosols as the analyte. Validation against bulk ellipsometry demonstrates a mean deviation of approximately 2.1% between the photoacoustically derived absorption coefficients and Rayleigh-theory predictions, establishing the quantitative accuracy of the transfer-function methodology. The proposed approach eliminates the need for external power normalization and frequent calibration procedures, providing a practical framework for quantitative mid-infrared aerosol absorption spectroscopy with applications in atmospheric aerosol characterization, source apportionment, and industrial emission monitoring.

Sensitive and selective detection of hydrazine (N2H4) remains a significant challenge for practical gas-phase monitoring. Herein, a functional nanofilm was prepared via an interfacially confined condensation strategy, using tetraphenylaldehyde (TFPE) and acylhydrazide derivatives as the building blocks. Incorporating electron-withdrawing cyano moieties into the acylhydrazone backbone enables the simultaneous formation of both dynamic C═N bonds and conjugated C═C bonds within a single conjugated framework. The designed asymmetric building block, a 1,4-phenylene linker bearing an acylhydrazide and a cyanomethyl group at the para positions, effectively modulates π-electron delocalization and creates cyano-enriched N2H4-reactive sites in the conjugated donor-acceptor (D-A) system, thereby promoting intramolecular charge transfer (ICT) and producing a large Stokes shift. These structural features also significantly influence the fluorescence turn-off sensing of the obtained nanofilms for gaseous N2H4. Performance screening identifies the heterostructural TFPE-CN nanofilm as the optimal candidate, featuring a free-standing, defect-free morphology, a favorable photoluminescence quantum yield of 30.8%, and exceptional stability. Integrated into a home-built portable sensing platform, the TFPE-CN nanofilm enables real-time, in situ detection of N2H4 vapor, delivering ultrahigh sensitivity (detection limit ≈ 130 ppt), rapid response (<11 s), excellent selectivity, and robust stability. This work offers an asymmetric molecular engineering strategy for fabricating interfacial nanofilms and lays a foundation for developing high-performance and portable sensing platforms for N2H4 vapor.