28 research outputs found

    Disposable sensors in diagnostics, food and environmental monitoring

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    Disposable sensors are low‐cost and easy‐to‐use sensing devices intended for short‐term or rapid single‐point measurements. The growing demand for fast, accessible, and reliable information in a vastly connected world makes disposable sensors increasingly important. The areas of application for such devices are numerous, ranging from pharmaceutical, agricultural, environmental, forensic, and food sciences to wearables and clinical diagnostics, especially in resource‐limited settings. The capabilities of disposable sensors can extend beyond measuring traditional physical quantities (for example, temperature or pressure); they can provide critical chemical and biological information (chemo‐ and biosensors) that can be digitized and made available to users and centralized/decentralized facilities for data storage, remotely. These features could pave the way for new classes of low‐cost systems for health, food, and environmental monitoring that can democratize sensing across the globe. Here, a brief insight into the materials and basics of sensors (methods of transduction, molecular recognition, and amplification) is provided followed by a comprehensive and critical overview of the disposable sensors currently used for medical diagnostics, food, and environmental analysis. Finally, views on how the field of disposable sensing devices will continue its evolution are discussed, including the future trends, challenges, and opportunities

    Wearable aptamer-field-effect transistor sensing system for noninvasive cortisol monitoring.

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    Wearable technologies for personalized monitoring require sensors that track biomarkers often present at low levels. Cortisol—a key stress biomarker—is present in sweat at low nanomolar concentrations. Previous wearable sensing systems are limited to analytes in the micromolar-millimolar ranges. To overcome this and other limitations, we developed a flexible field-effect transistor (FET) biosensor array that exploits a previously unreported cortisol aptamer coupled to nanometer-thin-film In2O3 FETs. Cortisol levels were determined via molecular recognition by aptamers where binding was transduced to electrical signals on FETs. The physiological relevance of cortisol as a stress biomarker was demonstrated by tracking salivary cortisol levels in participants in a Trier Social Stress Test and establishing correlations between cortisol in diurnal saliva and sweat samples. These correlations motivated the development and on-body validation of an aptamer-FET array–based smartwatch equipped with a custom, multichannel, self-referencing, and autonomous source measurement unit enabling seamless, real-time cortisol sweat sensing

    Multifunctional, inexpensive, and reusable nanoparticle-printed biochip for cell manipulation and diagnosis

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    Isolation and characterization of rare cells and molecules from a heterogeneous population is of critical importance in diagnosis of common lethal diseases such as malaria, tuberculosis, HIV, and cancer. For the developing world, point-of-care (POC) diagnostics design must account for limited funds, modest public health infrastructure, and low power availability. To address these challenges, here we integrate microfluidics, electronics, and inkjet printing to build an ultra–low-cost, rapid, and miniaturized lab-on-a-chip (LOC) platform. This platform can perform label-free and rapid single-cell capture, efficient cellular manipulation, rare-cell isolation, selective analytical separation of biological species, sorting, concentration, positioning, enumeration, and characterization. The miniaturized format allows for small sample and reagent volumes. By keeping the electronics separate from microfluidic chips, the former can be reused and device lifetime is extended. Perhaps most notably, the device manufacturing is significantly less expensive, time-consuming, and complex than traditional LOC platforms, requiring only an inkjet printer rather than skilled personnel and clean-room facilities. Production only takes 20 min (vs. up to weeks) and $0.01—an unprecedented cost in clinical diagnostics. The platform works based on intrinsic physical characteristics of biomolecules (e.g., size and polarizability). We demonstrate biomedical applications and verify cell viability in our platform, whose multiplexing and integration of numerous steps and external analyses enhance its application in the clinic, including by nonspecialists. Through its massive cost reduction and usability we anticipate that our platform will enable greater access to diagnostic facilities in developed countries as well as POC diagnostics in resource-poor and developing countries

    Epidermis‐Inspired Wearable Piezoresistive Pressure Sensors Using Reduced Graphene Oxide Self‐Wrapped Copper Nanowire Networks

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    Wearable piezoresistive sensors are being developed as electronic skins (E-skin) for broad applications in human physiological monitoring and soft robotics. Tactile sensors with sufficient sensitivities, durability, and large dynamic ranges are required to replicate this critical component of the somatosensory system. Multiple micro/nanostructures, materials, and sensing modalities have been reported to address this need. However, a trade-off arises between device performance and device complexity. Inspired by the microstructure of the spinosum at the dermo epidermal junction in skin, a low-cost, scalable, and high-performance piezoresistive sensor is developed with high sensitivity (0.144 kPa-1 ), extensive sensing range ( 0.1-15 kPa), fast response time (less than 150 ms), and excellent long-term stability (over 1000 cycles). Furthermore, the piezoresistive functionality of the device is realized via a flexible transparent electrode (FTE) using a highly stable reduced graphene oxide self-wrapped copper nanowire network. The developed nanowire-based spinosum microstructured FTEs are amenable to wearable electronics applications

    Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets

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    Radiomic features are being increasingly studied for clinical applications. We aimed to assess the agreement among radiomic features when computed by several groups by using different software packages under very tightly controlled conditions, which included standardized feature definitions and common image data sets. Ten sites (9 from the NCI\u27s Quantitative Imaging Network] positron emission tomography–computed tomography working group plus one site from outside that group) participated in this project. Nine common quantitative imaging features were selected for comparison including features that describe morphology, intensity, shape, and texture. The common image data sets were: three 3D digital reference objects (DROs) and 10 patient image scans from the Lung Image Database Consortium data set using a specific lesion in each scan. Each object (DRO or lesion) was accompanied by an already-defined volume of interest, from which the features were calculated. Feature values for each object (DRO or lesion) were reported. The coefficient of variation (CV), expressed as a percentage, was calculated across software packages for each feature on each object. Thirteen sets of results were obtained for the DROs and patient data sets. Five of the 9 features showed excellent agreement with CV < 1%; 1 feature had moderate agreement (CV < 10%), and 3 features had larger variations (CV ≄ 10%) even after attempts at harmonization of feature calculations. This work highlights the value of feature definition standardization as well as the need to further clarify definitions for some features
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