The combination of diuron (DU) and thidiazuron (TDZ) is commonly used in cotton production for its excellent adaptability to low temperatures, which may lead to increased crop and soil pollution. The simultaneous detection of DU and TDZ poses significant challenges due to their weak and overlapping signals, along with an unclear electrochemical detection mechanism for TDZ. This study developed a dual-channel multifunctional molecularly imprinted electrochemical (MMIP-EC) sensing platform by optimizing the substrate material and MIP layer for high performance. First, amino-functionalized graphene-based poly(pyrrole)-poly(3,4-ethylenedioxythiophene) (NH-rGO/PPy-PEDOT) with high conductivity was synthesized as the substrate. Subsequently, MMIPs were prepared in one step using electropolymerization by introducing chloroauric acid (HAuCl) and bifunctional monomers (dopamine and thiophene). This method not only enhanced specific binding capacity of the MMIP layer but also amplified the signal through the synergistic effect of reduced AuNPs and bifunctional monomers. Furthermore, two independent modules (MMIP-DU and MMIP-TDZ) were integrated into a dual-channel EC platform for simultaneous transmission of DU and TDZ responses to separate windows. Finally, based on high-performance liquid chromatography-mass spectrometry (HPLC-MS) and electrochemical kinetics studies, it was speculated that the electrochemical oxidation of TDZ via the carbonylation of a secondary amine under strongly acidic conditions, followed by hydrolysis to form a carboxyl group, reveals the electrochemical oxidation mechanism of TDZ. The developed sensor exhibited excellent performance in selectivity and sensitivity, with low detection limits of 26.6 pg/mL (DU) and 39.2 pg/mL (TDZ). In conclusion, this sensing platform presents a novel perspective for the cost-effective and highly efficient detection of diverse environmental pollutants.

Traditional electrochemiluminescence (ECL) detection makes it difficult to realize the spatial separation of the sensing and reporting sides, which inevitably causes mutual interference between the target and the luminescent substance. By studying the relationship between the luminol luminescence position and electrode potential in a three-electrode system, this work realized spatial separation of the sensing and reporting sides for the first time. Experimental investigations showed that luminol only emitted ECL signals at electrodes with positive polarity, regardless of whether a positive or negative voltage was applied. Inspired by this, we introduced a carbon vacancy-modified iron single-atom catalyst (V-Fe-N-C SAC) with excellent oxygen reduction reaction (ORR) activity into the working electrode, which can catalyze the reduction of dissolved O to produce abundant reactive oxygen species (ROS). ROS diffused to the surface of the counter electrode to oxidize luminol and produce a high-intensity ECL signal at an ultralow trigger potential. As a proof-of-concept application, a sensitive ECL biosensor with spatial separation of the sensing and reporting sides was first constructed for microcystin-LR (MC-LR) detection. This work solved the interference between the target and luminescent substance in the traditional three-electrode ECL system and improved the detection accuracy and sensitivity. Furthermore, the introduction of single-atom catalysts (SAC) avoided the use of the coreactant HO and the tedious electrochemical oxidation process of luminol, which broadened the application of ECL biosensors.

This study presents the first coupling of miniaturized chip-based supercritical fluid chromatography (SFC) with ion mobility spectrometry (IMS) enabling rapid two-dimensional analysis of moderately polar compounds. For the first time, ionization and analyte transfer at the SFC-IMS interface are achieved solely through eluent decompression in conjunction with a shifted electric IMS inlet potential. This straightforward approach significantly reduces instrumentation complexity and size, promoting system compactness and robustness. The integration of chip-based SFC with IMS enables high-speed separations of complex samples, drastically reducing analysis time while utilizing a detector capable of delivering structural information at a rapid acquisition rate and low cost. Evaluation of the SFC-IMS system as demonstrated through the chiral separation of Tröger's base revealed exceptional repeatability and sensitivity. Short columns and high flow rates resulted in record-speed SFC-IMS analysis in just six seconds. The system was successfully used to analyze a complex mixture containing five isomers, including naloxone and 6-monoacetylmorphine, in just 30 s.

Sensitive recognition of enantiomer has aroused extensive interest due to its importance in diverse fields ranging from pharmaceuticals to catalysis and biomedicine. Chiral surface-enhanced Raman scattering (SERS) by chiral plasmonic substrates has emerged as a promising tool for the recognition of enantiomers with high sensitivity as well as molecular fingerprinting capability. However, the impact of the molecular states including surface packing density and configurations of surface-adsorbed chiral molecules on chiral SERS has been largely unexplored. Herein, we demonstrate that chiral SERS by chiral plasmonic nanoparticles (NPs) is sensitively dependent on the molecular coverage of enantiomers. Au helical nanocubes with tunable optical properties and intense near-field enhancements were chosen as the chiral plasmonic substrates for chiral SERS. By changing the concentration and structure of enantiomers, the impact of the molecular states including surface packing density and configurations of enantiomers on chiral SERS is revealed. Finally, we demonstrate the use of achiral molecules as internal molecular spacers for achieving the ultrasensitive detection of enantiomer. The insights gained from this work not only shed light on the underlying mechanisms dictating the chiral SERS by chiral plasmonic NPs but also strongly suggest a promising approach to the sensitive detection of molecular chirality using Raman spectroscopy.

Simultaneous analysis of multiple biomarkers can typically improve the sensitivity and specificity of a disease diagnosis. Low-abundance serum proteins have recently emerged as a novel class of biomarkers for diseases. Due to the low concentration, the low-abundance protein analysis relies on single-molecule immunoassay, which has a very limited dynamic range. As a result, simultaneous analysis of low- and high-abundance protein markers requires multiple instruments, which demands larger sample volumes and is cost-/labor-consuming. To overcome these limitations, we developed a single-molecule imaging technique that can detect low- and high-abundance protein markers simultaneously in one chip. By employing a hybrid biomarker capture strategy that involves both glass surface and bead immobilization, our method greatly extended the detection range of the single-molecule assay. We used the method for pancreatic cancer diagnosis and analyzed three serum biomarkers of different abundances, including LIF, CA19-9, and CA125. Combined analysis of the three biomarkers yielded exceptional sensitivity and specificity (AUC = 0.996), which is better than using any of the markers alone, including CA19-9 that is used in clinical practice (AUC = 0.804). Overall, we demonstrated a simple and cost-effective method that greatly extended the dynamic range of single-molecule imaging while maintaining the sensitivity, which has great potential in various clinical applications.

This study presents an attractive single-component ratiometric fluorescent sensor that utilizes the oxidation of BSA-protected Au nanoclusters (BSA-Au NCs) by -Bromosuccinimide (NBS) to detect catecholamine neurotransmitters and their metabolites, which are critical biomarkers for neurological diseases like neuroblastoma, pheochromocytomas, and paragangliomas. In this detailed sensing platform, NBS induces a noticeable fluorescence change in the emission of BSA- Au NCs, including the extinction of the emission peak at 650 nm and the simultaneous appearance of an emission peak at 450 nm. This shift represents a clear transition in the emission color of the probe from red to blue. The oxidation of Au NCs offers a promising approach for developing a ratiometric probe using a single fluorophore, eliminating the need to combine two individual fluorophores. The presence of neurogenic biomarkers inhibits the oxidation of BSA-Au NCs, varying with the concentration and identity of each analyte, making distinct changes in the spectral profiles along with vivid color variations. Spectral changes and RGB data derived from emission colors were analyzed using machine learning techniques, specifically linear discriminant analysis (LDA) for classification and partial least-squares regression (PLS-R) for multivariate calibration. Results from LDA and PLS-R highlighted the strong potential of the designed sensor for differentiating and quantifying these biomarkers. Furthermore, the successful application of this sensor in detecting and distinguishing these analytes in human urine provides valuable insights for clinical analysis in screening and diagnosing neurological disorders.

Tumor microenvironment (TME) is characterized by complex cellular composition and high molecular heterogeneity. Characterizing the metabolic interactions between different cells in the TME is important for understanding the molecular signatures of tumors and identifying potential metabolic vulnerabilities for tumor treatment. In this research, we develop a single-cell spatial metabolomics method to profile cell-specific metabolic signatures and cell-cell metabolic interactions using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Different low-molecular-weight metabolites and lipids including glutamate, aspartate, glutamine, taurine, phenylalanine, glutathione, fatty acids, phospholipids, etc. were successfully detected and imaged after optimizing cell culture conductive slides, cell washing, and fixation procedures. Subsequently, we carried out single-cell spatial metabolomics on H460 large-cell lung cancer cells, HT-29 colorectal cancer cells, A549 lung cancer cells, HUH-7 liver cancer cells, and cancer-fibroblasts coculture system. We revealed that the metabolic profiles of both cancer cells and fibroblasts were altered after cell coculture. Glutamate and aspartate significantly increased in fibroblasts after coculture with cancer cells, corresponding to their indispensable roles in the creation of pro-cancer microenvironment. In addition, we discovered that the expressions of fatty acids and phospholipids in tumor cells and fibroblasts were also changed after cell coculture, which is closely related to the competition for energy and nutrient metabolites between different cells. We anticipate this single-cell analysis method to be broadly used in the investigations of diverse cellular models and cell-cell metabolic interactions.

Sugar cane smut disease can greatly decrease both the production and quality of sugar cane, and its early diagnosis is an effective strategy to ensure the quality and increase the income of sugar cane. Therefore, developing high-precision detection methods has major implications for the actual production of sugar cane. Herein, we synthesize bimetallic nanozymes FeO@AuNPs with excellent glucose oxidase-like activity and nitrogen-doped graphdiyne (N-GDY) with excellent conductivity and interfacial loading capacity, which are used as catalysts for biofuel cells and flexible electrode substrates, respectively. An allosteric hairpin-regulated enzymatic cascade nucleic acid amplification strategy is employed to construct a novel biosensing platform for precise and highly sensitive analysis of the pathogen causing sugar cane smut disease, and the catalytic mechanism of the nanozymes is studied. The sugar cane smut pathogen can specifically cause the complementary region of the allosteric hairpin to migrate to form a new functional hairpin. Under the promotion of enzymes, a dual nucleic acid amplification occurs using the new functional hairpin as a template and outputs a large amount of double-stranded products, which are captured by the RCA long chain on the biocathode. At the cathode, DNA double strands are capable of holding a large quantity of Ru[(NH)] through electrostatic attraction. The nanozymes on the anode can catalyze the oxidation of glucose to produce electrons, and AuNPs/N-GDY can efficiently transfer electrons to the cathode to obtain a strong open-circuit voltage signal, which exhibits a strong linear correlation to the pathogen in the range of 0.0001-10000 pM, with a detection limit of 53.29 aM (/ = 3). The sensing platform offers a reliable method that allows highly precise and accurate detection of sugar cane smut disease and has great application and development potential for early identification of smut and on-site rapid detection.

Concentration measurement has important applications in many fields, including pollution assessment in environmental science and drug dosage calculation in biomedical research. In the conventional methods, concentration is determined by measuring absorbance along a fixed long optical path. However, it is not suitable for high-concentration measurement. Herein, we have proposed a few-step variable optical-path-length slope method (fs-VOSM) for ultrabroad dynamic-range concentration measurement. As a proof of the method, we devised an fs-VOSM system in which a reference path is included to enhance the accuracy and repeatability. The measurement is conducted at 5 positions along ultrashort optical path (0-20 μm) for 800 ms. In the measurement of potassium dichromate solution concentration, the fs-VOSM system exhibits a wide dynamic range from 0.879 to 70.726 g/L with coefficient of variation (CV < 1.4%) and high accuracy (relative error within ±3.5%). We prospect that the fs-VOSM can be widely adopted in many advanced instruments such as process analyzer, flow injection analyzer, and turbidity meter.

Fluorescence-guided cancer surgery is of considerable current interest in bioanalytical chemistry, engineering, and medicine, but its clinical utility is still hampered by the diffusive (scattering) nature of human tissues and large variations among different patients. Here, we report a new method based on signal-to-noise (contrast-to-noise) ratio (SNR or CNR) imaging for real-time delineation and sharpening of tumor boundaries during image-guided cancer surgery. In particular, we show that in vivo tumor fluorescence signals (both intensity and standard deviation) are strongly correlated with those of the surrounding tissue of the same tissue type and that this relationship is maintained as a function of time for fluorescent tracers such as indocyanine green. This dynamic relationship permits a precise removal of nonspecific background fluorescence from tumor fluorescence. As a result, single-pixel SNR values have been calculated, mapped, and displayed across a large surgical field at 60 frames per second. Pathological validation studies indicate that these SNR values correspond to statistical confidence levels similar (but not identical) to those of normal distributions. When the tumor fluorescence has an SNR of 3, pathological data show a confidence level of approximately 95% in identifying the true tumor lesions. For clinical relevance, we have also carried out first-in-human clinical studies for both oral and esophageal tumors, achieving tumor margin precisions of 1-2 mm with 87.5% histological accuracy and no false positives.

Cell activity is evaluated using the number of colonies formed on a medium or the number of live cells in a suspension or by staining nuclei with fluorescent dyes to determine whether cells are dead. However, the culture methods generally require extended culturing times, and damage to the cell membranes observed using fluorescent dyes is not necessarily related to cell survival or activity. Hence, accurately determining the activities of individual cells is impossible. Therefore, we developed a method for quantitatively evaluating the metabolic activities of single cells by focusing on the optical and chemical properties of formazan dye, i.e., 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). The oxidized form of MTT is soluble and highly permeable to cell membranes, but it is reduced to insoluble MTT formazan upon reaction with intracellular metabolic products. Single-cell observation using dark-field microscopy revealed that insoluble formazan aggregates within the cells formed particles that emitted characteristic scattered light. The formazan-derived scattered light component extracted via peak fitting was related to metabolic activity, demonstrating its usefulness as a parameter indicating the activity of an individual cell. This method enables the real-time evaluation of the activities of single cells, which should lead to not only the acceleration of bacterial screening and microbial control but also the development of antibiotics and suppression of drug-resistant bacteria.

Circulating tumor cells (CTCs) have emerged as critical biomarkers in liquid biopsy for noninvasive tumor diagnosis and real-time monitoring of cancer progression. However, the isolation of CTCs is often required before detection due to their ultralow abundance in peripheral blood. These isolation processes are typically time-consuming and prone to cell loss, which limits the utility of CTC-based liquid biopsy. Herein, we present a DNA network-based diagnostic system that enables specific recognition, selective enrichment, and accurate detection of CTCs directly from blood samples. The DNA network comprises ultralong DNA chains embedded with polyvalent aptamers and fluorescence detection modules. The polyvalent aptamers selectively bind to the epithelial cell adhesion molecule (EpCAM) on a CTC membrane, facilitating their enrichment through base pairing-driven DNA network formation. This system semiquantitatively detects the expression level of cancer-associated microRNA within CTCs using ratiometric fluorescence imaging based on the chemical assembly of two fluorescence modules. In clinical blood samples, this diagnostic system achieves 100% precision and 96% accuracy in distinguishing breast cancer patients from healthy donors, highlighting its promising potential for clinical breast cancer diagnosis.

Circulating tumor cells (CTCs) are crucial for cancer research and clinical applications, with circulating cancer stem cells (cCSCs) being a rare but key subpopulation responsible for metastasis, recurrence, and therapy resistance. Current limitations in efficiently isolating these cells, particularly distinguishing cCSCs from non-stem-like CTCs (nsCTCs), hinder our understanding of cancer progression and precision medicine strategies. Herein, we developed a novel CTC isolation approach that integrates cell metabolic chemical tagging with a lick-andle-loaded M13 age-based surf (CHPhace). The multivalent nature of flexible M13 nanofibers, featuring thousands of modification sites for click reactions, significantly enhances CTC capture across diverse tumor types. Leveraging the unique slow-cycling characteristic of cCSCs, CHPhace demonstrated selective cCSCs isolation through metabolic labeling and demetabolism processes. The robust performance of CHPhace allows efficient isolation of both cCSCs and nsCTCs from complex blood sample matrices, achieving capture efficiencies exceeding 80%. This approach represents a promising tool for advancing our understanding of cancer progression and enhancing precision in clinical diagnosis and cancer prognosis.

Surface-enhanced Raman scattering (SERS) has emerged as a potent spectroscopic technique for the detection of single cells. However, it is difficult to achieve label-free detection at the single-cell level in dynamic liquids because nanoprobe aggregation in biological fluids and the low combination of nanoprobes and cells reduce the sensitivity of SERS detection. Herein, a dynamic liquid integrated single-cell SERS (DLISC-SERS) platform is developed for the label-free detection of single cancer cells. DLISC-SERS consists of three components, including a twisted mixing microfluidic chip to achieve an efficient combination of nanoprobes and cells, a commercial coaxial needle to accomplish 3D dynamic liquid focusing by annular sheath flow, and a quartz capillary to offer a SERS detection area with low noise. The mixing intensity of the twisted mixing microfluidic chip is almost 3.67-fold higher than that of straight mixing. The multifunctionally modified nanoprobe, Ag NSs@PEG@3COOH, can be stably dispersed in biological fluids for at least 30 min. The segment weighting similarity-based KNN model can classify single-cell spectra with sensitivity, specificity, and accuracy up to 100, 99.4, and 99.5%, respectively. The accuracy of the model for three-way classification is 95.2%. The DLISC-SERS platform is a powerful tool for detecting cancer cells at the single-cell level.

The preconcentration and isolation of per- and polyfluoroalkyl substances (PFAS) remain challenging due to their varying chain lengths and diverse headgroup chemical functionalities. These substances are persistent and occur in the environment at low parts-per-trillion concentration levels, necessitating the use of efficient and selective sorbents that can enhance their preconcentration from the targeted sample prior to instrumental analysis. This study, for the first time, evaluates the use of a polymeric ionic liquid (PIL) consisting of 1-(9-carboxy-nonyl)-3-vinylimidazolium bromide [CCOOHVim] [Br] ionic liquid (IL) monomer and 1,12-di(3-vinylimidazolium)dodecane bromide ([C(Vim)]2[Br]) IL cross-linker for the simultaneous separation and preconcentration of 15 anionic PFAS. The PIL was immobilized on a thin film microextraction device to improve preconcentration, extraction, and desorption kinetics. The addition of competing anions to the desorption solution was critical to ensure the quantitative desorption of the anionic PFAS by an ion exchange mechanism. Partition coefficient calculations revealed a balanced extraction coverage for short- and long-chain PFAS in ultrapure water, while in solutions at high ionic strength, short-chain PFAS tend to display less affinity for the sorbent compared to long-chain PFAS. Kinetic studies showed that less hydrophobic PFAS (perfluorobutanoic acid (PFBA)-perfluorohexanoic acid (PFHxA)) reached equilibrium faster and the extraction followed a pseudo-second order model with values up to 0.9874. The applicability of the PIL-thin film microextraction (TFME) device for quantitative analysis was demonstrated by a calibration curve in a concentration range from 1 ng L to 2500 ng L, which showed good accuracy (70-130%), precision (<20%), and limits of quantification from 1 ng L to 50 ng L.

HS and SO have been considered as important gaseous signaling molecules in biological systems, functioning as regulatory roles in many physiological processes of organisms. To better understand the crosstalk and synergetic effects between HS and SO in biological systems, developing a single fluorescent probe for dual-channel fast detection of HS and SO is highly urgent. We herein report a simple strategy to develop multifunctional near-infrared (NIR) fluorescent probes for simultaneous identification of HS and SO. Based on the idea of modulating the reactivity of the benzopyrylium core with electron donors, two new NIR fluorescent probes ( and ) were synthesized and evaluated. The probe could not only rapidly sense HS and SO with different fluorescence signals but also be used as a reversible probe to investigate the flux of HO and SO. Moreover, was successfully applied in visualizing HS and SO in living cells and mice. These results suggest that could serve as a useful tool in understanding the complex relationships between HS and SO in biological systems.

In spectral imaging, an optical system generates two mutually dependent kinds of crosstalk on an image sensor: spectral crosstalk (i.e., spectral mixing) between fluorescences of different dyes and spatial crosstalk (i.e., image artifacts) between fluorescences from different emission points in the field of view of the sensor. Therefore, an algorithm to cancel both kinds of crosstalk simultaneously (i.e., simultaneous spectral unmixing and image-artifact reduction) is proposed. The algorithm is based on the assumption that a crosstalk matrix (i.e., point-spread functions, PSFs) consisting of all crosstalk ratios is constant regardless of the causes of both kinds of crosstalk. By applying the algorithm to a nine-wavelength-band measurement of four-capillary electrophoretic separation of STR-PCR (short tandem repeat-polymerase chain reaction) products labeled with six dyes, true peaks of each of the dyes were obtained, while false peaks due to spatial crosstalk were reduced below the lower limit of detection in electropherograms. As a result, effective sensitivity and effective dynamic range were improved by 2 orders of magnitude. Moreover, it became possible to perform robust human identification of on-site-collected trace samples containing template DNA at any concentration in a 3-order concentration range by a single STR-PCR and a single electrophoretic separation.

Untargeted liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is a powerful tool for comprehensive chemical analysis. Such techniques allow the detection and quantification of thousands of compounds in a sample. However, the complexity and variability in the data can introduce significant errors, impacting the reliability of the results. This study investigates ensemble averaging to mitigate these errors and improve signal-to-noise (S/N) ratios, feature detection, and data quality. In this work, 256 LC-qTOF/MS data sets from the analysis of Morning Glory seeds were averaged to generate merged data sets. The numbers of the pooled data sets in the merged files were varied, and the number of features, the S/N ratio, the accuracy and precision of the accurate masses, relative intensities, and migration time were examined. It was proved that ensemble averaging allows an increase in the S/N up to a factor of 10, and the relative standard deviation of the accurate masses and retention time decreased by a factor of 10. Moreover, the average number of features mined per data set increased from 1192 ± 129 with the original data set to 4408 when all data sets were averaged into one. Using known target compounds, ensemble averaging benefits on quantitative analysis were investigated. The measured and theoretical relative intensities between the [M+1]+H, [M+2]+H, and [M+3]+H and [M]+H isotopes of known alkaloids were used. The standard deviation decreased by up to a factor of 10, and the absolute error between theoretical and experimental relative intensities was below 3%, making the theoretical isotopic pattern a valid criterion for confirming a putative molecular formula. Using a targeted approach to recover quantitative data from the original data sets from information in the merged data sets provides an accurate quantitative means. Peak lists from the merged data sets and quantitative information from the original data sets were fused to obtain a robust clustering approach that allows recognizing features (adducts, isotopes, and fragments) generated by a common chemical in the ionization chamber. Two hundred and four clusters were obtained, characterized by two or more features with migration times that differ by less than 0.05 min and with similar response patterns.

The CRISPR/Cas12a system is an emerging enzymatic tool for the development of enzyme-linked immunosorbent assay (ELISA) methods, owing to its robust signal amplification capability. Currently, most CRISPR/Cas12a-based ELISA approaches rely on strategies that convert target detection into nucleic acid analysis. This report presents a novel enzymatic cascade reaction for signal transduction and amplification in the development of a CRISPR/Cas12a-based ELISA method, utilizing β-galactosidase (β-gal)-mediated activation of the CRISPR/Cas12a system. Carbendazim (CBD), a widely used and versatile broad-spectrum benzimidazole fungicide, was chosen as the model analyte. In the absence of CBD, streptavidin-labeled β-gal is captured by a biotinylated secondary antibody immobilized on the microplate. The captured β-gal catalyzes the hydrolysis of -aminophenyl β-D-galactopyranoside to generate -aminophenol. This compound subsequently facilitates the decomposition of MnO nanosheets, leading to the generation of Mn ions. The Mn ions modulate the activity of the CRISPR/Cas12a system, thus producing high fluorescence in the detection solution. In the presence of CBD, the amount of β-gal captured on the microplate is reduced, thereby preventing effective cleavage of the reporter molecule by Cas12a, which results in a low fluorescence signal. After systematically optimizing experimental conditions, the developed method successfully detected CBD, demonstrating high sensitivity, selectivity, and applicability in complex food matrices. In comparison to the traditional nucleic acid-activated CRISPR/Cas12a-based ELISA method, our approach, which integrates β-gal-mediated, Mn-activated CRISPR/Cas12a cascade reactions into ELISA, exhibits superior analytical performance, thereby broadening the applicability of CRISPR/Cas12a for sensitive and convenient small-molecule analysis.