The efficacy of multiple single nucleotide variants (SNVs) analysis is far from ideal due to the limitations in identification. This study introduced a novel strategy for multiple SNVs analysis at the single particle level, integrating molecular and nanomaterial confinement to significantly accelerate the kinetics of multiplex recognition processes. Leveraging DNA tetrahedra to enhance sample background tolerance, we developed a nano self-assembly approach for the microscopic visualization and single-particle detection of mutations. The incorporation of X-shaped probes on DNA tetrahedra formed high-stability recognition units, which were interconnected via a long-chain confinement mechanism. Upon recognition, the release of the X-probe loop triggered a hybridization chain reaction (HCR) cascade, confined to the surface of gold nanoparticles (AuNPs) to achieve secondary confinement acceleration. Following electrostatic adsorption onto polystyrene (PS) microspheres, the fluorescence signal on AuNPs became microscopically visible. Machine learning algorithms were employed to further enhance the effective discrimination of multiple genomic sites. This work presents a promising and practical approach for multiple SNVs detection with potential applications in genomics and precision medicine.

Microplastic pollution can reshape microbial communities and may facilitate the horizontal dissemination of antimicrobial resistance genes (ARGs) through enrichment effects and intercellular interactions. However, current approaches remain inadequate for high-sensitivity monitoring of ARGs transmission under complex background conditions. Herein, we developed a machine learning–assisted nucleic acid assay integrating tetrahedral DNA scaffold-supported catalytic hairpin assembly (CHA), strand displacement amplification (SDA), and Cas12a-mediated trans-cleavage for ultrasensitive ARGs detection. Furthermore, machine learning was employed to optimize multidimensional signal features and decision thresholds. To evaluate the effect of microplastics on ARGs transfer, a bacterial transfer model was established using Escherichia coli. The proposed method was further validated in complex matrices. The results demonstrated that the CHA-SDA-Cas12a platform combined with machine learning enables sensitive detection of target ARGs and allows traceable monitoring of microplastic-accelerated ARGs dissemination. This provides a promising analytical approach for rapid AMR detection and risk assessment in environment-related samples.

Seafood is a vital component of the global diet, yet it is highly susceptible to contamination by diverse pathogenic microorganisms during production and distribution, posing significant threats to public health. Herein, we report a novel dual-mode sensing array based on screen-printed electrodes (SPEs) for the simultaneous and rapid detection of multiple pathogenic bacteria in aquatic products via synergistic electrochemiluminescence (ECL) and colorimetric readouts. The spatially separated architecture, comprising distinct recognition, ECL, and colorimetric units, effectively circumvents signal interference. A target transduction system is established to recognize different targets and release a universal transducer strand B for following reactions. Upon target binding, AuNPs-H2-GT probes initiate a catalytic hairpin assembly (CHA) cascade, resulting in a dual function: it sequesters Ru(bpy)32+-labeled AuNPs-H1 probes to generate ECL signal, while concurrently releasing GT strands; triggers a hybridization chain reaction with G-quadruplex (G4)-forming hairpins in the separate colorimetric zone, yielding a vivid colorimetric response. By integrating the sensitivity of ECL with the broad linear dynamic range of colorimetry, and utilizing spatial separation to ensure specificity in real samples, this work presents an integrated, cost-effective, and portable platform. It provides a powerful tool for the rapid, visualized, and reliable monitoring of microbial hazards in seafood safety control.

Environmental arsenic exposure and Helicobacter pylori (H. pylori) infection are widespread public health concerns, yet their combined effects on gastric pathophysiology remain poorly understood. This study investigated the impact of H. pylori infection and arsenic co-exposure on gastric barrier integrity, oxidative stress, and serum metabolic profiles using a murine model. Mice were divided into control, single-exposure (arsenic), and multiple exposure group (H. pylori infection and arsenic exposure). Gastric barrier function was assessed via immunofluorescence staining of ZO-1 and occludin proteins. Untargeted metabolomics, including PCA, PLS-DA, and KEGG pathway enrichment analyses, were employed to characterize serum metabolic alterations. Gene expression levels of IL-18, Nrf2, Keap1, Cat, Sod1, and Hmox1 in gastric tissues were quantified by qRT-PCR, with Spearman correlation analysis to evaluate metabolite-gene expression relationships. Fluorescence intensity of ZO-1 and occludin was significantly reduced in H. pylori-infected mice, with further deterioration under arsenic co-exposure. Metabolomic profiling revealed distinct serum metabolic perturbations across groups, with the multiple exposure group exhibiting more pronounced fluctuations in metabolite levels (e.g., lipids, amino acids, and peptides) and greater pathway diversity compared to single exposure groups. qRT-PCR analysis demonstrated synergistic upregulation of oxidative stress (Nrf2, Hmox1) and inflammatory (IL-18) markers in the multiple exposure group. Spearman correlation analysis identified significant associations between specific metabolites (e.g., acylcarnitines, bile acids) and antioxidant gene expression, suggesting bidirectional interactions between systemic metabolism and gastric oxidative responses. This study establishes a murine model of H. pylori infection and arsenic co-exposure, revealing synergistic disruption of gastric barrier function, oxidative homeostasis, and metabolic regulation. These findings provide critical insights into the pathophysiological interplay between microbial infection and environmental toxicants, highlighting potential therapeutic targets for mitigating combined exposure risks.

To address the challenges of nonspecific adsorption interference and low mass transfer efficiency encountered by electrochemiluminescence (ECL) sensors in complex biological matrices, this study developed a Mn@CeO2 nanozyme-based sensing interface. The Mn-doped CeO2 enhanced electron transfer efficiency, increased oxygen vacancy concentration, and stabilized the Mn-O-Ce structure, collectively enabling highly efficient peroxidase (POD)-like activity. The design significantly improved ECL reaction efficiency, which simultaneously conferred synergistic antifouling and mass transport enhancing properties. The mesoporous silica nanoparticle on the sensing interface accelerated mass transfer processes, thereby overcoming the limitations of traditional diffusion-controlled kinetics. The Mn@CeO2 nanozyme and mesoporous silica nanoparticle synergistically improved electron transfer and reactant enrichment, thereby significantly enhancing the signal response. Concurrently, a biomimetic anti-fouling coating was introduced at the interface to effectively suppress nonspecific adsorption of interferents. The constructed nanozyme-enhanced ECL sensing platform was demonstrated through the detection of dopamine (DA) as a model neurotransmitter, exhibiting favorable detection performance while maintaining high-accuracy detection in complex biological samples. This strategy offers a novel approach to developing highly sensitive and interference-resistant ECL sensors, with promising applications in disease biomarker monitoring and live physiological sample analysis.

Nucleic acid-based constitutional dynamic networks (CDNs) can mimic biological events while revealing complex biological processes and their functionalities. In this study, we present a novel dual-signal biosensor that leverages a dissipative DNAzyme-driven network for the analysis of mutant targets. A dissipative cycle response to target in single-base resolution was designed based on a DNAzyme-driven network to generate transient fluorescence signals, enabling real-time monitoring of mutant interactions. Meanwhile, a secondary signal mechanism using bipolar electrodes for electrochemiluminescence (ECL) detection was introduced, which provided a cumulative recording of the response events. The dual mechanisms ensured the efficient and specific activation of the dissipative cycle, mimicking SNV-related biological processes and enhancing the sensitivity and selectivity. This biosensing platform demonstrates the potential in advanced analytical applications, including real-time mutant detection and bioprocess simulation, paving the way for innovative diagnostic and research tools in analytical chemistry.

Helicobacter pylori (H. pylori) have garnered increasing attention due to its high infection rate and potential links to a variety of diseases. Achieving a radical cure is of significant importance for public health. However, drug resistance resulting from single nucleotide variations (SNVs) of H. pylori poses a challenge. Accurate identification of these SNVs is essential for effective diagnosis and treatment. In this study, we designed a single-base precision DNA-driven theranostics test strip, and proposed a novel responsive treatment strategy targeting H. pylori. These probes were fixed in separate regions on a carbon-dot-modified strip substrate, onto which samples can be loaded. Two probes loaded with oxytetracycline (OTC) and silver clusters (Ag NCs) that can be activated by either SNV or wild-type (WT) sequences of H. pylori. Fluorescent signals were utilized for genotype identification, while WT or SNV sequences triggered distinct modes of drug release, leading to a multiple treatment. A simulated theranostics assay was conducted on H. pylori-infected mice while the efficacy and impact were thoroughly characterized. Histopathological and immunohistochemical staining results indicated no significant side effects. Further analysis, including 16S rRNA gene sequencing of intestinal microflora and metabolite profiling in the kidney, demonstrated that the combination treatment was both efficient and safe. These findings confirm the potential application of this strategy in medical care.

Precise detection of gene expression is crucial for understanding the interactions between organisms and their environment. In this study, we developed a highly sensitive dual-recognition gene detection method based on the CRISPR-Cas12a system and DNA tetrahedron and validated its application in biological samples. By optimizing the Cas12a signal readout system, the method demonstrated excellent sensitivity and stability. Further experiments showed that the method could accurately detect the expression of the LKB1 gene, with good linearity observed in the concentration range of 10 pM to 10nM, and a detection limit as low as 1 pM. Using an arsenic-induced mouse liver injury model, we validated the applicability in complex biological samples and found that this detection system outperformed traditional RT-qPCR in recognizing gene expression differences, offering higher sensitivity and specificity.

AIMS:The emergence of antibiotic-resistant bacteria in recent years has underscored the urgent need for novel, precision-targeted antibacterial strategies. To address this critical challenge, our study designed a responsive antibacterial system that achieves precise bacterial eradication by conjugating antibacterial agents to nucleic acid probes wherein drug release is specifically triggered by extracellular nucleic acids. METHODS AND RESULTS:This innovative design utilizes toehold-mediated strand displacement to enable single-nucleotide precision targeting of bacterial sequences, thereby ensuring highly specific and quantitative drug release. And drug release is specifically triggered by extracellular nucleic acids. Comprehensive evaluations, including bacterial growth inhibition curves, inhibition zone measurements, and fluorescence staining assays, demonstrated the exceptional stability and selectivity. Furthermore, the practicality of this strategy was validated in spiked environmental water samples, where significant antibacterial efficacy was observed, highlighting its real-world applicability. CONCLUSIONS:The assembly, identification, and drug release process of this new antibacterial strategy have been thoroughly verified, showing excellent stability and selectivity, and also having excellent effects on the actual environment.

The precise detection of nucleic acid fine information, including single-nucleotide variants (SNVs), DNA methylation, and RNA dynamic modifications (e.g., m6A), is pivotal for elucidating disease mechanisms, advancing targeted therapies, and enabling early diagnostics. Electrochemiluminescence (ECL) emerges as a transformative technology, leveraging the chemiluminescence phenomenon triggered by electrochemical reactions to achieve high sensitivity, rapid response, and precise spatiotemporal control without external light sources. By integrating with strategies like strand displacement amplification (SDA) and enzyme-mediated reactions, ECL enables single-molecule-level detection of SNVs, DNA methylation, and RNA modifications, offering unparalleled accuracy and signal amplification. This review systematically explores the innovative applications of ECL in probing nucleic acid fine information, detailing its coupling mechanisms and highlighting its potential in disease prevention and personalized medicine. Furthermore, we discuss current challenges and future directions, aiming to catalyze the technological evolution and clinical translation of ECL in molecular diagnostics and precision medicine.

Accurate identification of bases at the single-nucleotide level is crucial for diagnostic and therapeutic strategies. In this study, we present a novel DNA nanostructure designed from a DNA tetrahedron, integrated with four distinct X-shaped structures, to enable precise detection of quartet base genotypes at a single site. The X-shaped structures incorporate strategically placed toehold domains engineered to enhance thermodynamic differences caused by single-base mismatches. These toehold-mediated hybridization reactions reveal the probes upon binding to their complementary targets, supported by the central tetrahedral framework, which provides a stable scaffold for transmitting fluorescence signals. Each vertex of the DNA tetrahedron is carefully conjugated with an X-shaped structure specific to the four possible genotypes, accounting for all potential mutations at a nucleotide site, thus enabling precise sequencing at specific loci. As a demonstration, we applied this strategy to the identification of H. pylori, a pathogen known for its widespread prevalence and growing antibiotic resistance due to single nucleotide variants (SNVs), this innovative DNA tetrahedron probe successfully identifies a key mutation site linked to clarithromycin resistance with high selectivity and stability, suggesting broad application potential. Furthermore, application in clinical samples and microbial genome expands its capacity as an effective and precise sequencing strategy and diagnostic tool.

Environmental arsenic contamination is a serious issue that cannot be ignored, since arsenic levels in drinking water frequently exceed safety standards, and there is an increased prevalence of Helicobacter pylori (H. pylori) infection. This results in an increasing population at risk of simultaneous exposure to both harmful agents, yet whether a synergistic interaction exists between them remains unclear. Therefore, this study aims to investigate the combined effects and underlying pathogenic mechanisms of concurrent exposure to these two hazardous factors by establishing a mouse model that is infected with H. pylori and exposed to inorganic arsenic through drinking water. Analysis of intestinal flora revealed significant alterations in the composition, relative abundance (Akkermansia, Faecalibaculum, Ilieibacterium, etc.), and metabolic potential of the intestinal microflora (amino acid metabolism and energy metabolism) in the combinatory exposure group. Non-targeted metabolomics analysis identified that the combinatory exposure group exhibited greater fluctuations in metabolite content, particularly in triacylglycerol, fatty-acid, peptide and amino acid. Moreover, H. pylori infection and arsenic exposure had increased levels of metabolites associated with the intestinal microbiota in their livers (4-Ethylphenyl sulfate and Phenylacetylglycine). Further analysis revealed significant correlations between changes in the intestinal flora and alterations in liver metabolic profiles. Herein, we hypothesize that H. pylori infection may exacerbate the intestinal flora imbalance and hepatic metabolic disturbances caused by arsenic exposure, which may disrupt enterohepatic homeostasis and potentially increase biological susceptibility to heavy metal toxicity.

With the development of gene editing technology, its application in tumor diagnosis is becoming increasingly widespread. The CRISPR/Cas system is an important gene editing tool that can significantly improve the early detection rate and precision diagnosis level, enabling high-throughput and high-sensitivity detection of tumors. This article focuses on CRISPR/Cas system for detecting various tumor-related targets and elaborates on its applications in tumor diagnosis from five aspects: (1) detection of tumor-derived exosomes: by recognizing the surface proteins or nucleic acids of exosomes secreted by tumor cells into blood or other samples through adaptors, the CRISPR system is activated, achieving non-invasive liquid biopsy of tumors; (2) detection of circulating tumor DNA tumor cells disseminate DNA into the circulatory system to trigger nucleic acid reactions involving gene editing enzymes, enabling the monitoring of tumor dynamic states; (3) detection of circulating tumor cells (CTCs): by using aptamers to recognize surface proteins of tumor cells or directly detecting tumor-related nucleic acids, the integrated CRISPR system allows for the detection of circulating tumor cells even in trace amounts, achieving precise diagnosis; (4) detection of tumor markers: high sensitivity is achieved through the coupling of various tumor marker aptamers and gene editing systems; (5) detection and identification of tumor microenvironments: by activating gene editing enzyme activity through differential factors in the tumor tissue microenvironment and triggering nucleic acid reactions, the diagnosis and dynamic monitoring of tumors can be achieved. The progress and bottlenecks of the CRISPR/Cas system in tumor diagnosis in the future are also discussed.

The detection of hydrogen peroxide (H2O2) represents an extensive requirement across various domains, including food, environmental, and medical fields. This study introduces a highly sensitive technique for the quantification of H2O2, integrating the electrochemiluminescence properties of perovskite with bio-catalyzed precipitation. A water-soluble perovskite-based electrochemiluminescence (ECL) biosensing interface was constructed, wherein H2O2 catalyzes a precipitation reaction that leads to the formation of an insoluble precipitate on the electrode surface. This occurrence effectively quenches the electrochemiluminescence signal of the perovskite, thus facilitating the quantitative detection of H2O2. The modified perovskite demonstrated excellent ECL performance, offering a stable signal source, while the bio-catalyzed precipitation reaction significantly amplified the quenching effect, thereby enhancing detection sensitivity. This strategy exhibits excellent stability and sensitivity, presenting a promising method for the detection of hydrogen peroxide, which holds great potential for applications in various fields.

Zero-dimensional (0D) halide perovskites have garnered significant interest due to their novel properties in optoelectronic and energy applications. However, the mechanisms underlying their phase transformations and fluorescence properties remain poorly understood. In this study, we have synthesized a micron-scale 0D perovskite observable under confocal laser scanning microscopy (CLSM). This approach enables us to trace the phase transformation process from 0D to three-dimensional (3D) structures, offering a deeper understanding of the underlying mechanisms. Remarkably, we discovered that this in situ transformation is highly sensitive to water, allowing for label-free fluorescent analysis of trace amounts of water in organic solvents through the phase transformation process. Additionally, we have designed a reusable paper strip for humidity analysis leveraging this sensitivity as an application of the micron scale material. Our findings not only elucidate the physicochemical properties of perovskites but also expand the potential of halide perovskite materials in analytical chemistry.

Helicobacter Pylori infection is drawing increasing attentions in public health, especially the drug resistance problems induced by Single-Nucleotide Variants (SNV). Diagnosis of H. Pylori remains challenging for its requirement in selectivity and sensitivity. Herein an initial check-reexamination strategy is designed for analysis of H. Pylori DNA and SNV. At the first stage, target DNA with all genotypes is captured to form a Y-shaped structure, resulting in an electrochemiluminescence (ECL) signal recovered from quenched states. Then Cas9 assisted cleavage processes are followed to cut off the Y-shaped structure, resulting in corresponding signal decrease. By means of these two stages with different selectivity, both the total amount of H. Pylori DNA and the ratio of SNV can be clarified. To expand its capacity, a large-scale screening assay is carried out on chip. Array detection improves the reliability and the following PCA analysis confirms the otherness. This approach improved the work efficiency and reduced the cost, which may offer an appealing option for the prevention and cure of H. pylori infections in the future.

Single nucleotide polymorphisms (SNPs) present significant challenges in microbial detection and treatment, further raising the demands on sequencing technologies. In response to these challenges, we have developed a novel barcode-based approach for highly sensitive single nucleotide recognition. This method leverages a dual-head folded complementary template probe in conjunction with DNA ligase to specifically identify the target base. Upon recognition, the system triggers rolling circle amplification (RCA) followed by the self-assembly of CdSe quantum dots onto polystyrene microspheres, enabling a single-particle fluorescence readout. This approach allows for precise base identification at individual loci, which are then analyzed using a bio-barcode array to screen for base changes across multiple sites. This method was applied to sequence a drug-resistant mutation site in Helicobacter pylori (H. pylori), demonstrating excellent accuracy and stability. Offering high precision, high sensitivity, and single nucleotide resolution, this approach shows great promise as a next-generation sequencing method.

Tetracyclines are currently the most commonly used class of antibiotics, and their residue issue significantly impacts public health safety. In this study, a surface modification of perovskite with cetyltrimethylammonium bromide led to the generation of stable electrochemiluminescence (ECL) emitters in aqueous systems and improved the biocompatibility of perovskite. A perovskite quantum dot-based ECL sensing strategy was developed. Utilizing the corresponding aptamer of the antibiotics, strain displacement reactions were triggered, disrupting the ECL quenching system composed of perovskite and Ag nanoclusters (Ag NCs) on the electrode surface, generating a signal to achieve quantitative detection of several common tetracycline antibiotics. The perovskite quantum dot provided a strong and stable initial signal, while the efficient catalytic activity of the silver cluster enhanced the recognition sensitivity. Tetracycline, chlortetracycline, and oxytetracycline were used as examples to demonstrate the differentiation and quantitative detection through this method. In addition, the aptasensor exhibited analytical performance with the linear range (0.1-10 μM OTC) and good recovery rates of 94.7% to 101.6% in real samples. This approach has the potential to become a sensitive and practical approach for assessing antibiotic residues.

Helicobacter pylori is closely linked to many gastric diseases such as gastric ulcers and duodenal ulcers. Therefore, biosensing H. pylori has attracted wide attention from both scientists and clinicians. Here, we proposed an electrochemiluminescence (ECL)-based platform that could sensitively detect H. pylori DNA. In this platform, a novel target-cycling synchronized rolling circle amplification was used for signal amplification. Silver nanoclusters (Ag NCs) were synthesized on the circle DNA products, embedding them with the ability to catalyze the electrochemical reduction of K2 S2 O8 , in turn resulting in rapid consumption of the ECL co-reactant near the working electrode, and leading to a decrease in the ECL emission intensity. In addition to its excellent stability and selectivity, the proposed strategy had a low detection limit of 10 pM, an indication that it can be beneficially applied to test biosamples. Furthermore, a biosensing chip was designed to improve the throughput and shed new light on large-scale clinical biosensing applications.

As a crucial indicator in food and water safety testing, the detection of Escherichia coli plays a significant role in maintaining environmental sanitation and promoting public health. Herein, based on the electrochemical activity characteristics of E. coli, we established an enhanced electrochemiluminescence aptasensor for E. coli analysis. This study presents a new method for accurate identification by utilizing a double aptamer recognition system. Specifically, a nano-cadmium sulfide (CdS) modified aptamer was used for primary labeling, while a second aptamer was immobilized on a graphene/chitosan composite electrode for re-capture. The use of two aptamers improves the accuracy of the identification process. Furthermore, the application of an electrode potential facilitates continuous electron transfer between the electrode and electrochemically active microorganisms, resulting in an enhanced electroluminescence signal in relation to the metabolic status. This strategy possesses better sensitivity, accuracy, and stability, demonstrating its potential for E. coli analysis.