Sensors & diagnostics最新文献

In this paper, we describe the development of a novel approach to monitor local tissue ischemia associated with pressure ulcer using an optical fibre carbon dioxide sensor. Carbon dioxide (CO₂) is a potential biomarker for local tissue ischemia associated with pressure ulcer (PU) formation. Skin CO₂ measurement during loading could provide an earlier indicator for pressure induced tissue damage. This study presents a reflection mode optical fibre CO₂ sensor (OFCS) that was fabricated and evaluated for measuring skin CO₂ during mechanical loading. The optical fibre tip was coated with organically modified silica gel (ormosil) film (thickness 7.23 ± 0.52 μm) containing thymol blue using a dip coating process. Thymol blue has an absorption peak at a wavelength of ~600 nm with an amplitude proportional to CO₂ concentration. The OFCS had a typical response time of approximately 60 seconds and a recovery time of 400 seconds for a 0–5.5% CO₂ range. OFCSs were tested on the human skin of six healthy volunteers with corresponding CO₂ peak values ranging from 145 ppm to 429 ppm with a percent error range of 6–32.2%. The increase in CO₂ emitted from the skin during loading offers future promise for alerting the early stage of PU formation.

At present, micro-respirometry for measuring total viable count, O₂ μR-TVC, is based on the time taken, TT, for an inoculum to significantly reduce the dissolved O₂ level (typically from 21% to ≤ 10.5%). Here, a simple kinetic model relevant to μR-TVC is presented which describes the growth of the bacteria from an initial inoculum, N_o, to a maximum level, N_max, and concomitant consumption of O₂ and generation of CO₂, in which the half-way time point, , corresponds to N_max/N_o = 0.5, at which point %O₂ = %CO₂ = 10.5%. The model shows that it is not possible to reduce the TT in O₂ μR-TVC below , as TT increases above with increasing sensitivity of the O₂ sensor. In contrast, the same model shows that if a CO₂ sensor is used instead, TT can be reduced significantly below and consequently CO₂ μR-TVC could be made much faster than conventional O₂ μR-TVC. To test this model prediction, a range of colourimetric CO₂ sensors of varying sensitivity, α, were prepared and used to make CO₂ μR-TVC measurements. The results confirm that the greater the sensitivity of the sensor, the shorter the TT, as predicted by the kinetic model. Two CO₂ indicators, one of moderate sensitivity and one of high sensitivity were used to generate straight-line log(CFU mL⁻¹) vs. TT calibration plots, which can then be used to determine the unknown TVCs of subsequent samples. The future of CO₂ μR-TVC as a possible new, faster alternative to conventional O₂ μR-TVC is discussed briefly.

Pathogenic bacteria, such as methicillin-resistant Staphylococcus aureus (MRSA), pose significant challenges to public health due to their resistance to conventional antibiotics. Early and accurate identification of bacterial species and discrimination of their strains is critical for guiding effective treatments and infection control. In this study, we develop a polymer-phage sensor platform that integrates polymer-based fluorescence sensing with phage-host specificity for bacterial identification. The sensor successfully differentiates three bacterial species (S. aureus, E. coli, and B. subtilis) and closely related strains of S. aureus (methicillin-sensitive Staphylococcus aureus (MSSA) and MRSA) with high classification accuracy (94–100%) and correct unknown identification rates (94–100%) under optimized conditions. By leveraging phage-host interactions and polymer binding properties, the polymer-phage sensor overcomes the limitations of traditional “lock-and-key” biosensors, offering enhanced specificity and reliability. This platform's rapid response time and adaptability make it a promising tool for clinical diagnostics and public health applications, particularly in combating antibiotic-resistant bacteria.

Chronic wounds pose serious health and economic challenges. A low calcium (Ca²⁺) ion concentration during the early stage often indicates infections. Holographic hydrogel sensors offer label-free sensing platforms, providing real-time and continuous detections of analytes upon diffractive wavelength changes detectable by the naked eye or spectrophotometers, improving the Ca²⁺ ion concentration quantification accessibility. Herein, we present a holographic Ca²⁺ ion bandage sensor using carboxylate-containing hydrogels on polydimethylsiloxane (PDMS) substrates for real-time wound-healing assessment through smartphone readout. Simulations are conducted to investigate the effects of mechanical strength on sensitivity. The holographic Ca²⁺ ion sensor replays blueshifts of 35 nm (hue value change of 7) with 0–4 mmol L⁻¹ Ca²⁺ ions, changing colors from dark red to red within 7 minutes. It can accurately and stably (over 24 hours) measure Ca²⁺ ions when bent. The stiffness of PDMS was tuned to balance comfort and sensitivity. In point-of-care settings, holographic bandage sensors, comprising the holographic hydrogel sensor, a backing layer, and a dark cotton layer, can continuously monitor Ca²⁺ ions over 10 hours via a smartphone application using hue values. A guiding square in the application assists users in capturing pictures within the inherently narrow viewing angle range of 20–33°. This holographic Ca²⁺ ion bandage sensor facilitates personalized wound assessment through colorimetric interrogation via smartphone readout.

The reproducibility of enzyme-based biosensors remains a critical challenge, particularly in clinical and wearable applications. Here, we present a novel one-pot polydopamine (PDA)-assisted immobilization strategy for pyrroloquinoline quinone-dependent glucose dehydrogenase (PQQ-GDH) on graphite electrodes to address the limitations of conventional layer-by-layer (LbL) methods. The (PQQ-GDH/PDA)_OPA/G platform demonstrated a uniform and nanostructured enzyme–polymer matrix, confirmed by SEM and spectroscopic characterization, resulting in enhanced surface coverage and enzyme stabilization. Electrochemical analyses revealed an onset potential of +0.19 ± 0.01 V and a maximum current of 0.87 ± 0.08 μA in the presence of glucose. Amperometric calibration yielded a linear range of 0.4–1.2 mM, a sensitivity of 0.47 μA mM⁻¹, and a low detection limit of 26 ± 2 μM. Michaelis–Menten kinetic analysis provided an I_max of 1.13 ± 0.07 μA and a K^app_M of 3.11 ± 0.59 mM. Reproducibility was excellent, with relative standard deviations below 8% for all key parameters. The biosensor retained full functionality under physiological conditions (pH 7.2, 37 °C) and exhibited high selectivity against common interferents, including dopamine, uric acid, and ascorbic acid, with signal variations below 5%. Remarkably, the sensor maintained stable responses in artificial serum for over 67 days, confirming its long-term operational stability. These findings highlight the one-pot PDA-based approach as a scalable, reproducible, and biocompatible platform for next-generation glucose biosensors suitable for real-world biomedical monitoring.

Correction for ‘Highly sensitive urine glucose detection with graphene field-effect transistors functionalized with electropolymerized nanofilms’ by Gonzalo E. Fenoy et al., Sens. Diagn., 2022, 1, 139–148, https://doi.org/10.1039/D1SD00007A.

Metabolomics allows the analysis of metabolites in biological samples to identify biomarkers associated with metabolic processes, and among these volatile organic compounds (VOCs) have emerged as a significant component in non-invasive diagnostics playing a crucial role in understanding physiological and pathological conditions. The changes in metabolic pathways that occur in biological systems during disease states result in the generation of VOCs as end products or intermediate products. These are then transported to the lungs via the circulatory system and presented into breath at the alveolar membrane. This direct link between metabolic changes and exhaled VOCs has driven growing interest in breathomics, a non-invasive approach to disease diagnosis and monitoring. Among numerous gas sensing technologies that have been explored, electrochemical sensors have demonstrated high sensitivity, cost-effectiveness, real-time monitoring, and miniaturization capabilities. In this work, we have developed a ferrocene (Fc) encapsulated zeolitic imidazole framework −8 (ZIF-8) for the detection of 4 physiologically relevant VOCs: ethanol, isopropanol, acetic acid, acetone, utilizing chronoamperometry as the transduction principle. The material characterization was performed using X-ray photoelectron spectroscopy, powder X-ray diffraction, field emission scanning electron microscopy, energy-dispersive X-ray analysis, and thermogravimetric analysis to confirm the morphological properties of Fc@ZIF-8. The dose-dependent response curves were established for each VOC, demonstrating linearity and the sensor's detection capabilities. Additionally, the sensor's accuracy was confirmed with spike and recovery experiments, achieving recovery rates within the CLSI guideline range of 80–120%.

Correction for ‘3D-printed electrochemical cells for multi-point aptamer-based drug measurements’ by John Mack et al., Sens. Diagn., 2024, 3, 1533–1541, https://doi.org/10.1039/D4SD00192C.

For several years now, the development of rapid, sensitive, portable and inexpensive early diagnosis techniques has been the focus of increasing attention in the healthcare field, for both primary care and emergency medicine. We have previously demonstrated the proof-of-concept of a patented microfluidic biochip integrating a giant magnetoresistance (GMR)-based sensor, placed on either side of the channel, allowing for the one-by-one dynamic detection of single magnetically labeled biological targets, in a continuous flow mode. In this article, we implemented this two-stage GMR sensor to improve the readiness level of this technology and move towards point-of-care (POC) analysis. We used semi-complex culture medium samples spiked with a murine cancer cell line, pre-labeled with functionalized magnetic particles, to evaluate the biochip performances in detail. The quantitative detection of target cells in low concentrated samples was achieved, with a sensitivity of 5 × 10² cells per mL at a 2 mL per hour flow rate and good specificity, even after addition of irrelevant cells to the sample. Finally, we demonstrated that these performances are competitive with existing techniques such as ELISA tests and flow cytometry analysis, paving the way for new GMR-based POC tests.

Breast cancer occurs when cells grow abnormally and form tumors. It is currently one of the most prevalent cancers in women, and it is known to cause serious detrimental effects if not detected on time. Thus, early detection and screening may tremendously contribute to a patient's medical treatment. The boom in cancer diagnostics resulted from the demand to overcome the limitations of bulky and time-consuming conventional detection methods. The new and advanced methods are simpler, faster and easily deployable. This review elucidates various techniques used for breast cancer detection, which include optical, electrochemical, mechanical, electrical, thermal and color- and breath-based methods. An overview of different techniques is presented with additional information related to the available commercial options. This review also presents the integration of artificial intelligence and Internet of Things into futuristic diagnostic techniques. The unmet needs and challenges are also discussed. Overall, this review is a comprehensive package for researchers who want to dive into the advances of breast cancer diagnostics.