This study presents a fluorescence-based detection method for and using aptamers and magnetic nanobeads. Fluorescently labeled aptamers served as signal probes, while FeO magnetic nanoparticles immobilized with aptamers were used as capture probes. The signal probe specifically recognized and bound to the captured pathogen, forming a sandwich-type complex with the capture probe. Various parameters such as synthesis conditions of magnetic nanoparticles, amounts of capture probe, avidin, aptamer concentration, fluorescent probe dosage, capture time, incubation duration, and temperature were optimized. Under optimal conditions, both pathogens exhibited linear relationships between fluorescence intensity and concentrations in the range of 10-10 CFU mL. The detection limits were 34.02 CFU mL for and 44.67 CFU mL for . This method was successfully applied to real food samples, yielding results consistent with standard methods. Compared to existing techniques, this approach offers high sensitivity, rapidity, good specificity, and broad application prospects in the prevention and control of foodborne diseases.

We synthesized chrysanthemum-like Fe-Co layered double hydroxide (LDH) nanostructures a hydrothermal method. The as-prepared Fe-Co LDH demonstrates peroxidase-like activity, which catalyzes the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of HO to form oxidized TMB (oxTMB), resulting in a characteristic blue color. Notably, the oxTMB solution demonstrates a significant photothermal effect under 808 nm laser irradiation. This dual-responsive detection system for HO involves both visual analysis (solution color change) and photothermal measurement (temperature variation). Moreover, the enzymatic oxidation of glucose catalyzed by glucose oxidase (GOx) generates HO as one of its products, which enables the development of both visual and photothermal glucose detection methods. Therefore, the synthesized chrysanthemum-like Fe-Co LDH demonstrated excellent dual-mode sensing capabilities, achieving sensitive HO detection within a linear range of 10-1000 µM, with a limit of detection (LOD) of 2.56 µM (based on 3/ criterion). Furthermore, this nanostructured material showed remarkable performance in glucose detection, exhibiting a similar linear range (10-1000 µM) and a comparable LOD of 2.51 µM (3/), through the indirect measurement of enzymatically produced HO. The chrysanthemum-like Fe-Co LDH exhibited enhanced peroxidase-like catalytic activity, which can be attributed to the increased number of accessible active sites within its unique flower-like nanostructure. Moreover, the synthesized nanozyme demonstrates excellent potential for sensitive photothermal glucose detection in food and beverage samples, suggesting promising applications as a versatile sensing platform.

The distribution and occurrence of calcium in different types of urinary stones were investigated using synchrotron radiation micro X-ray fluorescence (SR-µXRF), total reflection X-ray fluorescence (TXRF), and X-ray absorption spectroscopy (XAS). For this purpose, polished cross sectional areas of different urinary stones were prepared, and the elemental mapping of Ca and other related elements was performed. The elemental speciation of Ca was also investigated using X-ray Absorption Spectroscopy (XAS) including X-ray Absorption Near Edge Structure (XANES) and the Extended X-ray Absorption Fine Structure (EXAFS). The XANES results indicate the predominant existence of different ratios of calcium oxalate monohydrate (CaCO·HO) and alpha tri-calcium phosphate (Ca(PO), α-TCP). The distinct features observed in the -space of the EXAFS spectra reflect variations in the Ca-O bond lengths. These differences indicate changes in the local chemical environment, suggesting the presence of multiple calcium compounds in the urinary stones. The obtained results could provide more insight into calcium metabolism and calcium homeostasis in urinary stones. The calcium crystallization in the urinary tract could originate from abnormal processes or dysregulation of calcium in urine and urinary stones.

A polarity-sensitive fluorescent probe based on benzothiadiazole that could precisely target lipid droplets in living HeLa cells was synthesized. Experiments demonstrated that the UV absorption and fluorescence emission wavelengths of BTD-LD significantly red-shifted in different polar solvents as the polarity of the solvents decreased. Noticeable changes in fluorescence intensity enabled the effective detection of microenvironmental polarity changes. Cell colocalization imaging experiments revealed that BTD-LD efficiently penetrated cell membranes and specifically targeted lipid droplets. These results suggested that BTD-LD could precisely detect lipid droplets, which could be applied for studying their functions and disease-related mechanisms.

In this work, a novel sensitive colorimetric sensor was constructed for the determination of iron(II) (Fe) modifying 3,3',5,5'-tetramethylbenzidine and 3-mercaptopropionic acid on the surface of silver nanoparticles. In the presence of Fe, the modifying groups interacted with Fe, which caused the color of the solution to change, and the absorption peak at 395 nm decreased, while a new absorption peak appeared at 525 nm. This method exhibited good selectivity and sensitivity for the determination of Fe which was found by observing the color of the system with the naked eye and calculating the ratio of and , and the linear range was from 0.5 × 10 M to 1.00 × 10 M and the limit of visual colorimetric detection was 500 nM. This method has great potential for the rapid detection of iron(II) in environmental samples, including successful applications in tap water and lake water analysis.

Rapid and accurate estimation of soil nutrient content is essential for assessing soil fertility, facilitating sustainable nutrient management, and optimizing crop productivity. However, the high dimensionality of spectral data and the limitations of one-dimensional prediction models hinder prediction accuracy and efficiency. We propose a lightweight two-dimensional convolutional neural network, 2D-CTM-CNN, which integrates data compression and reconstruction to solve these problems. The framework transforms one-dimensional visible-near-infrared (VNIR) spectra into a two-dimensional representation and employs a Shapley-weighted 2D-CNN to predict nitrogen (N) and soil organic carbon (SOC). Comparative experiments against partial least squares regression (PLSR), a 1D-CNN, and two state-of-the-art 2D-CNN approaches (2D-GASF-CNN and 2D-MTF-CNN) demonstrate that 2D-CTM-CNN achieves superior performance, with relative prediction deviation (RPD) values exceeding 4 for both N and SOC. Relative to the 1D-CNN, improved by 5.68% for N and 5.56% for SOC, while spectral dimensionality was reduced from 4200 to 54, substantially enhancing computational efficiency. These findings highlight the effectiveness of 2D-CTM-CNN for high-precision soil nutrient prediction, offering a scalable and efficient solution for advancing precision agriculture.

Despite effective screening modalities, cervical cancer remains a leading cause of cancer-related death among women in the United States aged 20 to 39 years old, and incidence is rising in women aged 30-44 years old. Up to 25% of patients who are screened for cervical cancer by testing for human papillomavirus (HPV) do not receive necessary follow-up care with current laboratory-based testing. Applying a user-centered design approach, we surveyed and interviewed practicing clinicians to establish the use case, value proposition, and user requirements of a cervical cancer screening test for use in Indiana, USA. Insights from these stakeholders directly informed design specifications for a point-of-care HPV test capable of providing same-visit results to improve patient follow-up and retention. Guided by these requirements, we designed an isothermal nucleic acid amplification platform suitable for outpatient clinics. The test accepts swabbed endocervical cells, amplifies HPV16 L1 DNA recombinase polymerase amplification, and provides results within 40 minutes on a lateral flow assay. Further, the test achieves a clinically relevant limit of detection of 1000 HPV 16 copies per reaction and verifies swabbing technique and test operation with a sample adequacy control. The test operation was designed for a minimally-trained user and decreases time-sensitive steps that would interfere with clinical flow. By integrating clinician input to inform development decisions, our device is uniquely tailored to meet the context-specific needs of primary care clinics. This work exemplifies how user-centered design can yield novel diagnostic technologies with greater clinical impact and adoption potential.

Pentachloronitrobenzene (PCNB), an organochlorine fungicide, poses a serious threat to the ecological environment and human health owing to its high toxicity and strong bioaccumulation potential. Therefore, establishing a simple and sensitive method for PCNB detection is of great significance for safeguarding public health and public safety. Covalent Organic Frameworks (COFs) possess advantages such as unique structure and excellent performance; when combined with high-sensitivity fluorescence detection technology, they show broad application prospects in pesticide residue detection. In this study, a novel fluorescent probe material (COF) was synthesized at room temperature using melen (ML) and triformylphloroglucinol (Tp) as raw materials. Based on the Inner Filter Effect (IFE) occurring between PCNB and COF, the fluorescence intensity of COF is significantly reduced or even quenched, thereby realizing the quantitative detection of PCNB. Experimental results show that this fluorescent probe exhibits high sensitivity (limit of detection, LOD = 0.46 µM; limit of quantification, LOQ = 1.53 µM), a wide linear range (1.53-40 µM), and good selectivity in PCNB detection. Furthermore, the material has excellent chemical stability and hydrophilicity, providing a new approach for the detection of PCNB in aqueous environments. This study not only expands the application potential of COF materials in the field of pesticide detection but also provides technical references for pesticide residue monitoring and food safety supervision.

Belzutifan, a hypoxia-inducible factor-2α (HIF-2α) inhibitor, represents a breakthrough therapeutic agent for treating von Hippel-Lindau disease-associated tumors and advanced renal cell carcinoma, necessitating precise therapeutic drug monitoring. This work presents the first application of near-infrared carbon dots (NIR-CDs) for belzutifan detection utilizing a dual-mechanism approach combining aggregation-induced quenching and inner filter effect for enhanced analytical performance. The NIR-CDs were synthesized from sulfosalicylic acid and ethylenediamine precursors, exhibiting strong near-infrared emission at 750 nm upon 290 nm excitation with excellent photostability and pH tolerance. The developed fluorometric sensor demonstrated outstanding analytical performance with a linear detection range of 5.0-130.0 ng mL and a limit of detection of 1.35 ng mL, which is approximately 10 to 10 times lower than therapeutic plasma concentrations. Plasma sample analysis showed excellent extraction recovery ranging from 96.6% to 98.1% across three concentration levels with relative standard deviations below 4.27%. The method demonstrated successful clinical validation through analysis of plasma samples from rats, achieving excellent correlation with reference LC-MS/MS methods while providing real-time therapeutic drug monitoring capabilities. This represents the first fluorometric approach for belzutifan quantification and establishes a new paradigm for anticancer drug monitoring that combines the advantages of carbon dot nanotechnology with clinically relevant near-infrared detection, offering significant potential for point-of-care therapeutic drug monitoring in oncology practice.

Fourier transform infrared (FTIR) spectroscopy is widely applied in chemical structure analysis and functional group identification, serving as an essential tool for the investigation of unknown compounds. Traditional rule-based or machine learning approaches in spectral analysis often rely on prominent characteristic peaks, while failing to effectively exploit potential weak features within spectral signals, thereby exhibiting limitations in functional group identification tasks. In this study, we propose a functional group recognition model, LEC-former, which enhances the representation of weak spectral peaks. The model employs a self-attention-based spectral peak coupling encoder to capture long-range dependencies among infrared spectral peaks, while an innovatively designed LEC module enhances fine-grained perception of local features. This enables reinforced representation of weak peaks and effective integration of discrete peak positions, thereby improving the identification of key spectral regions associated with target functional groups. In this study, 23 337 FTIR spectra from the NIST Chemistry WebBook were selected to construct a multi-label functional group recognition task. The proposed model was compared against mainstream machine learning models across multiple evaluation metrics. The results demonstrate that LEC-former achieves significant improvements in functional group recognition accuracy and exhibits outstanding performance in molecular exact match rate.

This review summarizes current evidence on low-cost particulate matter (PM) sensors for indoor and occupational environments and proposes a framework that links performance evaluation, calibration, and uncertainty to decision-making. Results from laboratory and field co-locations are synthesized to define reporting standards-accuracy, precision, dynamic range, detection capability, and temporal response-and to compare calibration strategies. Optical sensors consistently capture temporal dynamics of indoor sources but show mass bias that depends on concentration range, aerosol composition, and humidity. Context-specific reporting, with conditioning on environmental state and source regime, is therefore essential. Calibration practices range from simple linear corrections, often adequate at low to moderate concentrations, to multivariate or nonlinear models incorporating humidity, temperature, or volatile organic compounds, which reduce residual bias under high or mixed-source loadings. A staged quality assurance and quality control workflow-including procurement screening, bench checks, co-location with blocked validation, external validation for transportability, and rotating "gold-node" drift checks-ensures reproducibility and decision-relevant uncertainty. Deployment studies demonstrate that event-aware sensor networks can support targeted ventilation and filtration, reducing exceedance time and cumulative exposure without unnecessary energy use. Standardized reporting tables, model versioning, applicability limits, and anomaly-handling rules further enhance reliability and governance. Overall, low-cost PM sensors can provide decision-relevant data when embedded in calibrated, uncertainty-aware pipelines with explicit scope statements. While reference-grade methods remain necessary for compliance, calibrated networks are well suited to hotspot detection, intervention design, and operational optimization in buildings and workplaces.

Antibiotic resistance genes (ARGs) are emerging pollutants that pose significant threats to both the environment and human health. Rapid detection of ARGs is essential for monitoring their levels and controlling their spread. However, traditional detection methods are often time-consuming and require specialized equipment, leading to delays. To address this issue, this study developed a novel method for visual microarray detection of ARGs, including , , , , and . This method employs ARG-specific dual probes combined with silver staining signal cascade amplification technology. A centrifuge-free concentration device has been developed that can directly enrich nucleic acid fragments from environmental samples, with traditional nucleic acid extraction and PCR amplification being eliminated. Using a dual probe combined with silver staining enhancement dual probe amplification technology, rapid high-throughput detection of low-concentration ARG is achieved. No specialized equipment is required, and on-site visual detection of ARG was realized. The detection method can detect target genes (, , , , and ) within a concentration range of 0.411 µg mL to 55.9 µg mL, with the lowest detectable target gene concentration being 0.411 µg mL. This study marks the first integration of a centrifuge-free concentration device, specific dual probes, and silver staining signal cascade amplification technology to establish a rapid visual detection method for ARGs using a microarray. The developed detection method holds significant potential not only for the detection and monitoring of ARGs but also as a prototype for devising future detection strategies.

Microfluidic devices have proven to be a valuable innovation in medical and biological research, offering a fast and efficient platform for testing. Among the materials used for constructing microfluidic channels, off-stoichiometry thiol-ene (OSTE) polymers are especially promising due to their ease of fabrication and lower small-molecule absorption compared to the current gold-standard material, polydimethylsiloxane (PDMS). However, some studies have indicated that there are challenges with binding molecules to the surface thiol groups as they are easily oxidized in air. In this study, a novel linker was synthesized and evaluated for its performance at binding proteins to the surface of OSTE polymer, using a custom-built spectroscopic measurement system. In addition, the results obtained were compared to regular enzyme-linked immunosorbent assay (ELISA) plates and performance of the linker in functionalized microfluidic chips was investigated. Our results indicate that the synthesized linker binds proteins to the OSTE surface and can offer a similar performance to ELISA plates in protein concentration tests highlighting its potential for use in microfluidic chip functionalization.

Correction for 'A microfluidic paper-based analytical device based on a surface-modified screen-printed electrode Pt-Pd/RGO nanocomposite for glucose detection in urine' by Chaozhan Chen , , 2025, , 6326-6335, https://doi.org/10.1039/D5AY00852B.

MALDI MS analysis of liquid biopsy combined with ML enables non-invasive disease screening and monitoring. Here we present an open-source R-based workflow covering all steps from raw data preprocessing to predictive model evaluation. The pipeline is fully customizable and transparent, with validation performed on clinical plasma samples from hemato-oncological patients. This workflow enhances data reproducibility, enables a straightforward end-to-end workflow for liquid biopsy biotyping, and provides a foundation for integrating MALDI MS into routine clinical workflows.

A quick and simple fabrication process of a paper-based device using 3D printing of a polylactic acid polymer as an industrially compostable hydrophobic barrier was developed and applied to determine tin(IV) in canned fruit samples with sappan wood ( Linn.) extract. The analysis protocol is based on the complexation of tin(IV) with brazilein from sappan wood extract. Under optimal conditions, a standard curve was obtained with a linear equation = 7.5322 + 3.4933 and coefficient of determination () of 0.9959. The intra-day and inter-day precision were less than 2.5 ( = 8) and 5.2 ( = 9)% relative standard deviations, respectively for different fruit matrices containing more than 58.5 µg g of tin. The detection limit was 1 mg L. The accuracy of the method was validated using flame atomic absorption spectrophotometry. Statistical analysis indicated no difference ( > 0.05) between the two methods. Greenness of the developed method was evaluated using the Analytical GREEnness (AGREE) software assessment tool.

The determination of heavy metals and rare earth elements (REEs) in environmental and biological objects is important for biomonitoring. The composition of whole blood provides information about the general condition of the body and its environment. The limits of detection (LODs) of analytes provided by inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma optical emission spectrometry (ICP-OES), in some cases, are insufficient to detect trace amounts of analytes. In this work, a new method for human whole blood analysis is proposed. Graphene oxide (GO) obtained by microwave exfoliation of graphite oxide was used for the preconcentration of analytes from human whole blood samples. This method allows for a significant reduction in matrix effects and the sampling dilution factor. Sorption preconcentration allows to improve LODs of analytes by an average 13 times compared to sample preparation procedures with acid digestion. The LODs of the analytes from 3 to 1000 ng L for ICP-MS and from 100 to 10 000 ng L were obtained for ICP-OES analysis with preconcentration. The developed method allows for the quantitative determination of 25 analytes (Be, Cr, Cu, Hf, In, Pb, Sn, Ti, Zr and REEs). The analyte recoveries ranged from 75% to 114%. The use of GO for sorption preconcentration of analytes provides a significant improvement in the LODs of analytes and allows for obtaining a more detailed information on the composition of whole blood during ICP-MS and ICP-OES analyses.

Water-soluble poly[3-(4-trimethylphosphinobutyl)thiophene bromide] (PTB), which has a phosphonium group at the end of its side chain and selectively recognizes and separates Gram-positive bacteria, was synthesized. Modifying its terminal group with an ethyl substitution greatly altered the bacterial response, notably causing abnormal fibrosis in Gram-negative .

Osteomyelitis is a complex infection requiring prolonged antibiotic treatment. Treatment failure can lead to poor functional outcomes, reduced quality of life, and significant healthcare burdens. The therapeutic efficacy in the treatment of bone and joint infection is influenced not only by the sensitivity of antibiotics to the causative microorganisms but also by the level of antibiotic exposure at the infection site. Consequently, a thorough investigation into the penetration process and extent of antibiotics at the infection site holds significant importance. Current vancomycin detection methods primarily focus on plasma and other body fluids, while research on drug concentrations in bone tissue remains scarce. To address this gap, this study aims to establish a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analytical method for accurate quantification of vancomycin concentrations in human plasma and bone tissue. The separation was completed in 7.5 min on a BEH C18 column (2.1 × 50 mm, 3.5 µm), and gradient elution was performed in a mobile phase consisting of 0.1% formic acid acetonitrile and 0.1% formic acid water at a flow rate of 0.3 mL min. The standard curve demonstrates linearity within the range of 1-100 µg mL for plasma (1-200 µg g for bone), with intra-day and inter-day bias and variation ≤15%. This analytical method has been successfully implemented in a clinical study for the determination of vancomycin in plasma and bone tissues of actual patients, following systemic administration during osteomyelitis debridement surgery.

This review comprehensively examines organic-based probes used in chemosensors and biosensors, focusing on their chemical and crystal structures and their effects on performance. It emphasizes the significant role of organic molecules used as probes, which often serve as the primary sources of optical properties such as fluorescence emission in metal complex or supramolecules such as metal-organic frameworks (MOFs) the antenna effect. The review's scope covers a wide range of organic-containing materials, from fundamental small organic molecules to complex supramolecular structures, polymers, MOFs, and covalent organic frameworks (COFs). The inclusion of organic components notably enhances the performance of these systems; low detection limit and provides high sensitivity and selectivity. Ultimately, these materials offer multifunctionality, acting as effective probes and preconcentration materials, adsorbents, and pseudo-stationary phases. The integration of materials science, sustainable design, and advanced data analytics is shaping the next generation of high-performance, innovative, and ecologically friendly sensors and biosensors. Continuous interdisciplinary collaboration among chemists, engineers, biologists, computer scientists, and data scientists will be essential to transform these concepts into viable, scalable solutions that improve human health, animal welfare, and environmental sustainability.

Generally, trace amounts of water in organic solvents are deadly to chemical production and laboratory chemical reactions. Thus, a novel derivative of 1,8-naphthalimide (NPP-N+) was designed and synthesized for detecting water content in water-miscible organic solvents. NPP-N+ features a donor-π-acceptor (D-π-A) structure, where strong intramolecular charge transfer (ICT) and suppressed twisted intramolecular charge transfer (TICT) in aqueous media lead to stronger fluorescence in water than in organic solvents. The experimental results show that the detection limits of NPP-N+ for water in ethanol (EtOH), tetrahydrofuran (THF), dimethyl sulfoxide (DMSO), acetone, and ,-dimethylformamide (DMF) are 0.99%, 0.75%, 0.50%, 1.77%, and 0.35% respectively, indicating that NPP-N+ exhibited excellent fluorescent sensitivity to water in organic solvents. In addition, the potential of NPP-N+ for the quantitative detection of moisture content in medical alcohol samples and the natural absorbent DMSO was successfully demonstrated.