Sensors & diagnostics最新文献

Milk adulteration remains a significant public health concern in India, where conventional laboratory-based detection methods are often costly, time-consuming, and impractical for field use. This study introduces a novel paper-based microfluidic device designed for rapid, low-cost detection of multiple milk adulterants. The device comprises a 3D-printed strip holder and utilizes gravity-assisted capillary flow through porous paper, eliminating the need for hydrophobic barriers or external power sources. Its modular design allows for easy reuse of the holder while only replacing the paper strip for successive tests. The platform enables visual detection of common adulterants—including neutralizers, starch, hydrogen peroxide, urea, detergents, and boric acid—via reagent-specific colorimetric responses. The device meets the ASSURED criteria of World Health Organization for point-of-care diagnostics, offering a promising tool for decentralized milk quality monitoring and contributing to both consumer safety and improved supply chain transparency in the dairy industry. The device demonstrated a limit of detection (LOD) as low as 0.03% for urea and hydrogen peroxide, outperforming existing paper-based methods. The results were validated across five independent trials per condition, with high reproducibility and minimal cross-reactivity, confirming the diagnostic reliability of the platform.

Iron, particularly redox-active ferrous ions (Fe²⁺), is essential for biological processes. Despite their pivotal roles, analysis of Fe²⁺ ions within individual extracellular vesicles (EVs) has been hindered by the ultralow Fe²⁺ content and substantial heterogeneity of EVs. To address this, we developed a novel approach by integrating an Fe²⁺-specific fluorescent chemosensor (Ac-FluNox) with nano-flow cytometry (nFCM) for precise single-EV Fe²⁺ mapping. Method specificity to Fe²⁺ was validated via Fe²⁺-loaded liposomal models at the single-particle level. Comprehensive profiling of Fe²⁺ distributions in HT-1080-derived EVs under varying ferroptotic stress conditions revealed the striking heterogeneity in Fe²⁺ loading among EVs and a strong positive correlation between EV Fe²⁺ levels and their parental cells. Notably, we identified an EV-mediated Fe²⁺ export mechanism that functionally parallels to ferroportin (FPN)-dependent iron efflux, suggesting EVs may serve as a compensatory iron-release pathway during FPN inhibition. The nFCM platform achieved superior detection sensitivity with high throughput (up to 10⁴ particles per min), providing a powerful analytical tool for investigating EV heterogeneity and Fe²⁺-mediated regulatory networks in iron homeostasis and ferroptosis-related pathologies.

Single extracellular vesicles (EVs) carry molecular signatures from their cell of origin, making them a pivotal non-invasive biomarker for cancer diagnosis and monitoring. However, analyzing the complex data associated with single-EVs, such as fingerprints generated via Surface-enhanced Raman Spectroscopy (SERS), remains challenging. To address this, a thorough comparison of machine learning models' implementations and their accuracy classification optimization is presented. A comprehensive single-EV spectral library collected with a SERS-assisted nanostructured platform including cell lines, healthy controls, and cancer patient samples is used. The performance of different learning models (random forests, support vector machines, convolutional neural networks, and linear regression as reference) was assessed for cancer detection tasks: i) multi-cell line classification and ii) cancerous versus non-cancerous binary classification. To improve their accuracy, we optimized spectra preprocessing, artificially increased the dataset, and implemented feature-driven classification. In sum, these methods enabled more interpretable models to perform on par with the complex one, increasing accuracy up to 12% percent-age points, even with datasets reduced to 66% of the original size. Achieving accuracies of 83% and 91% for Task-i and Task-ii, respectively.

A graphical abstract is available for this content

Circulating cell-free DNA (cfDNA) has been established as a minimally invasive liquid biopsy biomarker with utility in the diagnosis of cancer, monitoring of treatment response, and detection of minimal residual disease. The clinical utility of cfDNA is currently constrained by the low abundance of circulating cfDNA fragments, high fragmentation rates, and short half-life, making it technically challenging to detect in a patient sample. Current molecular approaches for cfDNA detection, including ddPCR and NGS, are time-intensive, expensive, and unsuitable for low-resource settings and point-of-care testing. The CRISPR-Cas system offers a novel and operationally simple approach to cfDNA detection by being single nucleotide specific and compatible with isothermal and amplification-free workflows. In this review, we discuss CRISPR-based assays for cfDNA, beginning from Cas9 enrichment-type assays to promising collateral cleavage platforms employing Cas12a and Cas13a that have countered traditional bottlenecks concerning diagnostic testing. We also provide a comparative analysis of the emerging platforms for key cancer mutations with a discussion around translational scope, including implications from CRISPR-based diagnostic patents. The convergence of sensitivity, speed, multiplexing, and microfluidic integration of CRISPR diagnostics will undoubtedly constitute a next-generation approach for cfDNA analysis, presenting a great promise in impacting precision oncology and increasing access to cancer diagnostics across low-resource settings.

Conjugated microporous polymers (CMPs) possess extended π-conjugation combined with microporosity, enabling amplified sensing response even with ultra-trace solution or vapor-phase analytes, and their high sensing response output was demonstrated with several CMPs. However, CMPs exhibiting tandem detection properties, i.e., sequential detection of multiple analytes, are rarely reported and represent the next generation of CMP chemical sensors offering enhanced sensitivity and specificity. Herein, we report the design and synthesis of a salphen-conjugated microporous polymer (pTPE-salphen) for reversible dual-mode (fluorometric/colorimetric) nanomolar detection of Cu²⁺ ions and tandem capture of cysteine (Cys). pTPE-salphen synthesized via Schiff-base condensation between 1,1,2,2-tetrakis(4-hydroxy-3-formylphenyl)ethene and o-phenylenediamine, emits yellow photoluminescence (PL) at λ^max_Em = 537 nm with a PL quantum yield of 5.41%. pTPE-salphen exhibited remarkable thermal stability up to 425 °C and a fused spherical nanoparticle morphology. pTPE-salphen showed strong PL quenching up to 92% when exposed to Cu²⁺ (50 μM), selectively among other metal ions, due to the ground-state complex formation of Cu²⁺@pTPE-salphen. pTPE-salphen was highly sensitive to Cu²⁺ with a detection limit of 5.69 nM and exhibited a high Stern–Volmer constant (K_SV) value of 8.12 × 10⁶ M⁻¹. Notably, the pTPE-salphen-based paper strip sensor showed appreciable sensitivity up to 10⁻¹¹ M Cu²⁺. In addition, strong colorimetric changes from yellow (R/B is 1.9) to black (R/B is 0.53) were also observed upon the formation of Cu²⁺@pTPE-salphen, and the binding of Cu²⁺ was confirmed by XPS analysis. Interestingly, Cu²⁺@pTPE-salphen exposed to cysteine (Cys) exhibited reversible colorimetric response from black to orange (R/B is 1.8) both in dispersion and paper strip sensors due to the formation of Cys–Cu²⁺@pTPE-salphen where Cys binds with Cu²⁺ anchored on the pore surface of pTPE-salphen, and the entire colorimetric process (yellow ⇌ black ⇌ red) is reversible. The binding of Cys to Cu²⁺ and its tandem capture were systematically studied using XPS and NMR. Such sequential detection and capture (tandem process) of Cu²⁺ and Cys using a conjugated microporous polymer sensor is unique and of high significance in environmental and biological applications.

Few point-of-care (POC) molecular methods exist that are as sensitive as polymerase chain reaction (PCR) while maintaining the simplicity, portability, and robustness for detecting specific nucleic acids in complex sample media. Here, we developed an isothermal nonenzymatic amplification cascade, named sequential nonenzymatic amplification (SENA), and its digital assay version (dSENA), for the ultrasensitive detection of cell-free microRNAs (miRNAs) in diluted human serum with a >95% recovery rate. SENA consists of two layers of DNA circuit-based amplifiers, in which the hybridization chain reaction (HCR) and catalyzed hairpin assembly (CHA) were concatenated to amplify the signals by more than 4000-fold. The sensitivity was further improved in dSENA, where a limit of detection (LOD) down to 5 fM was achieved under the optimized conditions. SENA and dSENA together demonstrated a broad detection dynamic range over 6 logs of analyte concentrations (10 fM – 10 nM), and high specificity for discriminating target miRNAs from point mutations and other interference sequences. dSENA was demonstrated to quantify expression levels of miR-21 and miR-92 in colorectal cancer patient serum with accuracy comparable to RT-PCR. Given its simplicity, compactness, and PCR-like performance, SENA holds great potential in POC miRNA or ssDNA analysis.

Developing nanozyme-based sensors enables the upcycling of waste printed circuit boards (WPCBs) into functional sensing materials, offering both environmental sustainability and practical analytical capabilities. However, unlike natural enzymes with inherent target recognition, nanozymes often lack molecular selectivity, limiting their broader sensing applications. Moreover, developing waste-derived nanozymes with target recognition abilities presents considerable obstacles due to their uncontrolled and underexplored surface functionalities. In this study, we developed pyrophosphate (PPi)-responsive carbon nanozymes (CNZs) derived from WPCBs and investigated their intrinsic target-binding behavior. The peroxidase-mimicking CNZs were synthesized via simple carbonization of non-metallic fractions of WPCBs, followed by refluxing in alkaline solutions. Notably, the peroxidase-mimicking activity of CNZs was significantly suppressed by PPi, an important anionic biomarker in physiological processes and disease monitoring. Kinetic studies and comparative assays revealed the inhibition mechanism underlying the unique interaction between PPi and WPCB-derived CNZs. Upon the H₂O₂–CNZ complex formation, PPi subsequently interacts with the active carbonyl sites (CO) on the CNZ surface, resulting in target-responsive inhibition. Built upon this unique binding behavior, the CNZ-based system achieved highly sensitive and selective colorimetric PPi sensing with a detection limit of 8.7 nM, with negligible interference even from structurally similar phosphate analogs. This work not only demonstrates the feasibility of converting waste into functional enzyme mimics, but also highlights a strategy for achieving intrinsic molecular selectivity in nanozyme-based sensors without relying on external recognition elements.

The rate-limiting step in a recently reported glucose sensor strip incorporating a water-soluble quinone mediator with high enzyme reactivity was proposed to be substrate diffusion. This mechanism is expected to lead to sensors requiring smaller mediator amounts but possessing higher sensitivity and a wider measurement range than conventional sensor strips containing mediators with low enzyme reactivity. A general finite element method-based simulation model for mediator-type enzyme electrodes was employed in this study to obtain the concentration distribution profiles of this specific glucose sensor strip and clarify its action mechanism. The obtained profiles showed that the mediator forms a very thin diffusion layer on the electrode surface and that the diffusion layer of the substrate gradually covers the entire solution. The results of this study confirmed that the rate-limiting step of the glucose sensor strip is substrate diffusion.

Co(II) and Cr(III) salicylidene Schiff base-based complexes as novel ionophores were evaluated for the fabrication of bromide-selective electrodes. By incorporating a cation excluder along with various plasticizers (dibutyl phthalate, dioctyl phthalate, 1-chloronapthalene), optimized sensors (CoC7 and CrC7) exhibiting near-Nernstian slopes being 59.4 ± 0.07 and 59.2 ± 0.04 mV decade⁻¹, with a broad linear range (1 × 10⁻² to 6.0 × 10⁻⁷ and 1 × 10⁻² to 8.7 × 10⁻⁷ mol L⁻¹), with low detection limits (5.5 ± 0.13 × 10⁻⁷ and 6.5 ± 0.07 × 10⁻⁷ mol L⁻¹) respectively, were successfully designed. Selectivity coefficient values of order 10⁻¹ or less indicate that the proposed electrodes have superior selectivity for bromide ions over various interfering anions. The developed bromide electrodes demonstrated robust performance within a pH range of 4.0 to 9.0, as well as showing a sufficient shelf life (4 and 5 weeks) with up to 20% (v/v) non-aqueous tolerance and quick response times (12 and 16 s). These electrodes also served as indicator electrodes in the potentiometric titration of bromide ions against AgNO₃ and were used in the determination of bromide ion concentration in water samples.