Analysis & sensing最新文献

Theranostic systems that integrate diagnostic monitoring and therapeutic intervention within unified platforms represent a transformative approach for precision medicine. While wearable microneedle (MN)-based devices offer an ideal form factor for such systems, their development has been constrained by limitations in molecular recognition specificity, intelligent decision-making capability, and controlled drug release precision. Nucleic acid technology emerges as a comprehensive solution to these challenges, leveraging its inherent programmability and molecular recognition versatility to address all three core theranostic components. This review systematically examines recent advances in nucleic acid-based strategies for intelligent theranostics, focusing on three fundamental modules: (1) in situ monitoring systems employing aptamers, CRISPR mechanisms, and molecular pendulums; (2) decision-making units utilizing threshold-controlled circuits and feedback-regulation networks; and (3) stimulus-responsive drug delivery units featuring programmable release mechanisms for various therapeutic agents. We further highlight integrated nucleic acid-MN platforms that demonstrate closed-loop operation, continuously sensing biomarker fluctuations and triggering precise therapeutic responses. Finally, we discuss prevailing challenges in stability, specificity, and clinical translation, while outlining future research directions aimed at advancing autonomous molecular decision systems for personalized medicine applications. This comprehensive analysis provides foundational insights for developing next-generation intelligent theranostic platforms capable of adaptive, precision healthcare delivery.

The present study reveals the fabrication of transition metal oxides based nanohybrids for the sensitive electroanalytical differentiation of dihydroxybenzene isomers (DHBIs). The Ag-MnCuO nanohybrid is prepared through the facile combustion method and further functionalized by poly-arginine (PA). The prepared nanohybrid is validated through X-ray diffraction, energy-dispersive X-ray analysis, field-emission scanning electron microscopy, and Raman spectroscopy. The glassy carbon electrode is modified with Ag-MnCuO nanohybrid and forms the PA-rGO-Ag-MnCuO, which exhibits superior electrocatalytic activity for the identification of catechol (CE), hydroquinone (HR), and resorcinol (RO). The prepared nanohybrid on the electrode exhibits higher electrochemical properties with a limit of detection for the detection of CE (0.107 μM), HR (0.069 μM), and RO (0.094 μM). The efficiency of the prepared electrode is validated by a remarkable recovery percentage in the market source of DHBI samples. The proposed electrode demonstrates high stability, selectivity, repeatability, reproducibility, and synchronized detection of DHBIs, highlighting its potential for practical use in photochemical and environmental applications.

A new sensing microtiter plate platform enables rapid, one-step, ratiometric fluorescence detection of H₂O₂ using Amplex Red in hydrogel membranes with Cy5-based reference nanoparticles. It offers 3-minute readouts and 10 times lower detection limit than commercial kits while minimizing preparation steps. With enzyme functionalization, the platform supports glucose and lactate detection, offering a simplified yet powerful alternative to multistep assays. More in the Research Article by Axel Duerkop and co-workers.

Plant health monitoring is vital to address global agricultural instability. The emerging non-destructive, portable, wearable chemical sensors provide valuable insights into plant health with faster detection and real-time data. The Review by Yifei Luo, Xiaodong Chen, and co-workers summarizes progress in plant chemical sensing, focusing on key chemicals, materials, and mechanisms, aiming to overcome challenges and advance in-field deployment of these essential tools.

Global crop yields are reduced by ≈20–40% per year due to agricultural pests, whereas there is an urgent requirement to increase the level of food production due to the rapid growth of the world's population. In this regard, Helicoverpa armigera is one of the serious pests as it could damage more than 100 different crops across the world. Detection of pests like Helicoverpa armigera is, therefore, immensely important for the efficient production of food across the globe. Herein, a method has been described for the selective detection of female sex pheromone of pests like Helicoverpa armigera (Hubner) with a suitably functionalized long-period fiber grating (LPFG)-based sensor. LPFG provides a suitable online monitoring platform for the attachment and identification of different chemical moieties needed for the specific detection of the pheromone. Higher-order dispersed cladding mode (DCM) of LPFG has been used for this specific application. The specificity of these sensors has been established, and the detection limit of the developed optical sensors was found to be 7.6 μg L^–1.

Ammonia (NH₃) is an important resource that is used as a raw material in the production of fertilizers and fuels. It is generated from animal excrement and plant decomposition. Because NH₃ is highly toxic, a high-sensitivity and responsivity method for its visual detection is required. Fluorescent dyes that respond to NH₃ have been developed for visual detection. However, ultraviolet irradiation is required to confirm changes in their fluorescence colors. Herein, the visualization of gaseous NH₃ under natural light using an ionic liquid–based pH-responsive dye is reported. The dye is synthesized using trihexyl(tetradecyl)phosphonium (P_66,614) and bromocresol purple (BCP). In addition, a [P₆₆₆₁₄]₂[BCP] thin film that exhibits a visible response to gaseous NH₃ is synthesized, manifested as a color change from yellow to dark blue. Additionally, it exhibits sensitivity with a limit of detection of 66 ppm, repeatability for >100 exposure cycles, and a rapid response to gaseous NH₃. To demonstrate practical applicability, gaseous NH₃ emitted from food is detected using the thin film. The thin film responds to trace amounts of NH₃ released from pork, which is visible as a color change from yellow to blue. Thus, [P₆₆₆₁₄]₂[BCP] has good application potential as a gaseous NH₃ sensor.

Sweat uric acid (UA) monitoring using wearable electrochemical biosensors is an emerging noninvasive strategy for chronic disease management. However, for current sweat UA biosensors, sweat collection is inefficient, and environmental factors can cause the leakage and degradation of uricase. Herein, this study proposed a new flexible wearable microsystem, integrated with a wireless potentiostat device and a mobile application, for real-time sweat UA monitoring. A tree-inspired microfluidic chip is fabricated to collect and transport sweat, and a uricase@FSiO₂ electrochemical sensor is developed to sense sweat UA. Benefiting from hydrophilic FSiO₂ framework modification, the high activity of uricase coated on our sensor is maintained for up to 21 days. The wearable microsystem exhibited efficient sweat collection and excellent UA monitoring performance, with high sensitivity, strong selectivity against interferents, and robust stability. This study provides efficient and cost-effective strategies for the development of electroanalytical devices for UA monitoring.

Structure-switching aptamers are utilized in various applications and have increasingly been translated into electrochemical biosensors, largely thanks to post-SELEX sequence engineering through computational and enzymatic approaches. In the context of sequence engineering, it is envisioned that folding and binding thermodynamics could likewise contribute to accelerating translation of aptamers into sensors. Herein, this is explored by first characterizing a series of quinine-binding aptamers using the biophysical methods isothermal titration calorimetry and nano differential scanning calorimetry. The folding and binding thermodynamics obtained are compared with the resulting analytical performance when aptamers are adapted into sensors. The findings show that the magnitude of sensor response is strongly correlated with aspects of the binding and unfolding thermodynamics of the aptamer as measured in solution. Using a similar approach, a recently reported adenosine monophosphate aptamer is successfully engineered to support electrochemical sensing. It is envisioned that relying on solution-based biophysical methods will further improve post-SELEX sequence engineering.

Laser-induced breakdown spectroscopy (LIBS) is a rapid, accurate technique for material analysis, offering real-time, minimally destructive, and in situ detection capabilities with broad application potential. LIBS extends its applications across various fields, from geology to biomedicine. However, barriers like matrix effects, reproducibility, self-absorption, and spectral noise often restrict the proper interpretation of the spectra. This review paper examines literature from 2015 to 2025, focusing on the evolution of machine learning (ML) and deep learning (DL) techniques, in LIBS analysis. It evaluates the advancement of these techniques, assessing both the qualitative and quantitative performance of LIBS analysis. These observations support the complementary roles of ML and DL methodologies. ML captures general patterns, while DL, through convolutional neural networks (CNNs), excels at identifying high-level features. This literature review reveals that no single ML or DL tool consistently provides optimal solutions for LIBS applications. The analysis pipeline needs to be tailored based on the LIBS data and the goal of the study. Designing such a framework requires the incorporation of preprocessing techniques to enhance the quality of raw signals. This step should then be followed by integrating the data into predictive models, whether ML or DL, to accomplish tasks like classification or concentration prediction.

An azobenzene-based tripodal sensor leverages the photoswitching property by undergoing reversible cis–trans photoisomerization where the two isomers of a sensor demonstrate differential binding affinities toward a series of biologically important nucleotides. This difference in binding behavior enables biologically important analytes, namely ATP, ADP, GTP, UMP, UTP, CTP, and inorganic phosphates to be detected and discriminated based on their interaction patterns with each isomeric form of the photoswitchable sensor, which can be reversibly tuned by light. The differential interactions of the two photoisomeric probes are clearly apparent based on their UV-vis spectral responses, followed by the multivariate analysis of the spectral data in two and three dimensions. These results showcase the potential of the azobenzene-based tripodal photoswitch that could double up as tunable molecular sensors upon photoisomerization, paving the way for their applications in biological sensing and analytical chemistry.