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Spectrally–selective monitoring of ultraviolet radiations (UVR) is of paramount importance across diverse fields, including effective monitoring of excessive solar exposure. Current UV sensors cannot differentiate between UVA, B, and C, each of which has a remarkably different impact on human health. Here we show spectrally selective colorimetric monitoring of UVR by developing a photoelectrochromic ink that consists of a multi-redox polyoxometalate and an e − donor. We combine this ink with simple components such as filter paper and transparency sheets to fabricate low-cost sensors that provide naked-eye monitoring of UVR, even at low doses typically encountered during solar exposure. Importantly, the diverse UV tolerance of different skin colors demands personalized sensors. In this spirit, we demonstrate the customized design of robust real-time solar UV dosimeters to meet the specific need of different skin phototypes. These spectrally–selective UV sensors offer remarkable potential in managing the impact of UVR in our day-to-day life. Current ultraviolet (UV) sensors cannot differentiate between UVA, B and C, each of which has a remarkably different impact on human health. Here the authors show spectrally-selective colorimetric monitoring of ultraviolet radiations by developing a photoelectrochromic ink that consists of a multiredox polyoxometalate and an e – donor.

The global pandemic of coronavirus disease 2019 (COVID-19) highlights the shortcomings of the current testing paradigm for viral disease diagnostics. Here, we report a stepwise protocol for an RNA-extraction-free nano-amplified colorimetric test for rapid and naked-eye molecular diagnosis of COVID-19. The test employs a unique dual-prong approach that integrates nucleic acid (NA) amplification and plasmonic sensing for point-of-care detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a sample-to-assay response time of <1 h. The RNA-extraction-free nano-amplified colorimetric test utilizes plasmonic gold nanoparticles capped with antisense oligonucleotides (ASOs) as a colorimetric reporter to detect the amplified nucleic acid from the COVID-19 causative virus, SARS-CoV-2. The ASOs are specific for the SARS-CoV-2 N-gene, and binding of the ASOs to their target sequence results in the aggregation of the plasmonic gold nanoparticles. This highly specific agglomeration step leads to a change in the plasmonic response of the nanoparticles. Furthermore, when tested using clinical samples, the accuracy, sensitivity and specificity of the test were found to be >98.4%, >96.6% and 100%, respectively, with a detection limit of 10 copies/μL. The test can easily be adapted to diagnose other viral infections with a simple modification of the ASOs and primer sequences. It also provides a low-cost, rapid approach requiring minimal instrumentation that can be used as a screening tool for the diagnosis of COVID-19 at point-of-care settings in resource-poor situations. The colorimetric readout of the test can even be monitored using a handheld optical reader to obtain a quantitative response. Therefore, we anticipate that this protocol will be widely useful for the development of biosensors for the molecular diagnostics of COVID-19 and other infectious diseases. This protocol provides an RNA extraction–free nano-amplified colorimetric test that enables rapid detection of SARS-CoV-2 with the naked eye. The test uses plasmonic gold nanoparticles capped with antisense oligonucleotides as a colorimetric biosensor for point-of-care diagnosis of COVID-19.

This review presents the state-of-the-art of optical sensors for determination of biogenic amines (BAs) in food by publications covering about the last 10 years. Interest in the development of rapid and preferably on-site methods for quantification of BAs is based on their important role in implementation and regulation of various physiological processes. At the same time, BAs can develop in different kinds of food by fermentation processes or microbial activity or arise due to contamination, which induces toxicological risks and food poisoning and causes serious health issues. Therefore, various optical chemosensor systems have been devised that are easy to assemble and fast responding and low-cost analytical tools. If amenable to on-site analysis, they are an attractive alternative to existing instrumental analytical methods used for BA determination in food. Hence, also portable sensor systems or dipstick sensors are described based on various probes that typically enable signal readouts such as photometry, reflectometry, luminescence, surface-enhanced Raman spectroscopy, or ellipsometry. The quantification of BAs in real food samples and the design of the sensors are highlighted and the analytical figures of merit are compared. Future instrumental trends for BA sensing point to the use of cell phone–based fully automated optical evaluation and devices that could even comprise microfluidic micro total analysis systems.

Recently, there has been an explosion of scientific literature describing the use of colorimetry for monitoring the progression or the endpoint result of colorimetric reactions. The availability of inexpensive imaging technology (e.g., scanners, Raspberry Pi, smartphones and other sub-$50 digital cameras) has lowered the barrier to accessing cost-efficient, objective detection methodologies. However, to exploit these imaging devices as low-cost colorimetric detectors, it is paramount that they interface with flexible software that is capable of image segmentation and probing a variety of color spaces (RGB, HSB, Y’UV, L*a*b*, etc.). Development of tailor-made software (e.g., smartphone applications) for advanced image analysis requires complex, custom-written processing algorithms, advanced computer programming knowledge and/or expertise in physics, mathematics, pattern recognition and computer vision and learning. Freeware programs, such as ImageJ, offer an alternative, affordable path to robust image analysis. Here we describe a protocol that uses the ImageJ program to process images of colorimetric experiments. In practice, this protocol consists of three distinct workflow options. This protocol is accessible to uninitiated users with little experience in image processing or color science and does not require fluorescence signals, expensive imaging equipment or custom-written algorithms. We anticipate that total analysis time per region of interest is ~6 min for new users and <3 min for experienced users, although initial color threshold determination might take longer. This protocol provides ImageJ-based workflows for the analysis of images obtained from colorimetric assays. New users can take advantage of a basic workflow; more experienced users can benefit from more advanced analysis procedures.

In recent years, there has been an increase in pesticide use to improve crop production due to the growth of agricultural activities. Consequently, various pesticides have been present in the environment for an extended period of time. This review presents a general description of recent advances in the development of methods for the quantification of pesticides used in agricultural activities. Current advances focus on improving sensitivity and selectivity through the use of nanomaterials in both sensor assemblies and new biosensors. In this study, we summarize the electrochemical, optical, nano-colorimetric, piezoelectric, chemo-luminescent and fluorescent techniques related to the determination of agricultural pesticides. A brief description of each method and its applications, detection limit, purpose—which is to efficiently determine pesticides—cost and precision are considered. The main crops that are assessed in this study are bananas, although other fruits and vegetables contaminated with pesticides are also mentioned. While many studies have assessed biosensors for the determination of pesticides, the research in this area needs to be expanded to allow for a balance between agricultural activities and environmental protection.

Volatile organic compounds (VOCs) in breath can be used as biomarkers to identify early stages of lung cancer. Herein, we report a disposable colorimetric array that has been constructed from diverse chemo-responsive colorants. Distinguishable difference maps were plotted within 4 min for specifically targeted VOCs. Through the consideration of various chemical interactions with VOCs, the arrays successfully discriminate between 20 different volatile organic compounds in breath that are related to lung cancer. VOCs were identified either with the visualized difference maps or through pattern recognition with an accuracy of at least 90%. No uncertainties or errors were observed in the hierarchical cluster analysis (HCA). Finally, good reproducibility and stability of the array was achieved against changes in humidity. Generally, this work provides fundamental support for construction of simple and rapid VOC sensors. More importantly, this approach provides a hypothesis-free array method for breath testing via VOC profiling. Therefore, this small, rapid, non-invasive, inexpensive, and visualized sensor array is a powerful and promising tool for early screening of lung cancer.

This study describes the colorimetric detection of aflatoxin M1 (Afl M1) in milk samples using a microfluidic paper-based analytical device (µPAD). Fabrication of µPADs was done using a simple and quick approach. Each μPAD contained a detection zone and a sample zone interconnected by microchannels. The colorimetric assay was developed using unmodified AuNPs as a probe and 21-mer aptamer as a recognition molecule. The free aptamers were adsorbed onto the surface of AuNPs in absence of Afl M1, even at high salt concentrations. The salt induced aggregation of specific aptamers occurred in presence of Afl M1. Under optimum conditions, the analytical linear range was found to be 1 µM to 1 pM with limit of detection 3 pM and 10 nM in standard buffer and spiked milk samples respectively. The proposed aptamer based colorimetric assay was repeatable, quick, selective, and can be used for on-site detection of other toxins in milk and meat samples.

Colorimetric sensing, which transduces environmental changes into visible color changes, provides a simple yet powerful detection mechanism that is well-suited to the development of low-cost and low-power sensors. A new approach in colorimetric sensing exploits the structural color of photonic crystals (PCs) to create environmentally-influenced color-changeable materials. PCs are composed of periodic dielectrics or metallo-dielectric nanostructures that affect the propagation of electromagnetic waves (EM) by defining the allowed and forbidden photonic bands. Simultaneously, an amazing variety of naturally occurring biological systems exhibit iridescent color due to the presence of PC structures throughout multi-dimensional space. In particular, some kinds of the structural colors in living organisms can be reversibly changed in reaction to external stimuli. Based on the lessons learned from natural photonic structures, some specific examples of PCs-based colorimetric sensors are presented in detail to demonstrate their unprecedented potential in practical applications, such as the detections of temperature, pH, ionic species, solvents, vapor, humidity, pressure and biomolecules. The combination of the nanofabrication technique, useful design methodologies inspired by biological systems and colorimetric sensing will lead to substantial developments in low-cost, miniaturized and widely deployable optical sensors.

Microfluidic paper-based analytical devices (µPADs) are an attractive format for colorimetric nucleic acid amplification tests (NAATs) because they enable low-cost, portable diagnostics in resource-limited settings. However, researchers often optimize colorimetric assays in liquid reactions in tubes before translating them to µPADs. Since both formats require separate instruments for incubation and real-time sensing, direct comparison of reactions between the two formats is difficult. To address these cross-platform limitations, we developed ThermiQuant™ AquaStream, a portable benchtop device (15 × 20 × 16 cm, ~ 5 kg; cost: USD 327) that supports seamless colorimetric loop-mediated isothermal amplification (LAMP) reactions in both µPADs and tubes under a common workflow. The system enables real-time reaction tracking (every 30 seconds) through onboard image processing, precise isothermal control (±0.5 °C) using a repurposed consumer-grade sous-vide heater, and medium-throughput (24 tubes or 42 µPADs). Testing with synthetic SARS-CoV-2 orf7ab DNA fragments demonstrated a limit of detection corresponding to a 95% probability of detection (LOD95) of 110 copies per reaction in tube (22 copies/µL) and 39 copies per reaction in µPADs (5 copies/µL), estimated using probit regression. In both formats the limit of quantification (LOQ), defined as the lowest concentration yielding a coefficient of variation (CV) of quantification time (Tq) ≤ 10%, was 250 copies/reaction resulting in a strong linear (R 2 = 0.98 & R 2 = 0.96 respectively for tube and µPADs) standard calibration curves. ThermiQuant™ AquaStream provides an affordable and versatile benchtop platform capable of supporting both tube- and µPAD-based colorimetric LAMP assays, serving as a proof-of-concept research tool for assay development and molecular diagnostics in One Health settings such as clinics, farms, and field environments.

Color correction is an important methodology where a digital image’s colors undergo a transformation to more accurately represent their appearance using a predefined set of illumination conditions. Colorimetric measurements in diagnostics are sensitive to very small changes in colors and therefore require consistent, reproducible illumination conditions to produce accurate results, making color correction a necessity. This paper presents an image color correction pipeline developed by HueDx, Inc., using transfer algorithms that improve upon existing methodologies and demonstrates real-world applications of this pipeline in colorimetric clinical chemistry using a smartphone enabled, paper-based total protein diagnostic assay. Our pipeline is able to compensate for a variety of illumination conditions to provide consistent imaging for quantitative colorimetric measurements using white-balancing, multivariate gaussian distributions and histogram regression via dynamic, non-linear interpolating lookup tables. We empirically demonstrate that each point in the color correction pipeline provides a theoretical basis for achieving consistent and precise color correction. To show this, we measure color difference with deltaE (ΔE00), alongside quantifying performance of the HueDx color correction system, including the phone hardware, color sticker manufacturing quality and software correction capabilities. The results show that the HueDx color correction system is capable of restoring images to near-imperceptible levels of difference independent of their original illumination conditions including brightness and color temperature. Comparisons drawn from the paper-based total protein assay calibrated and quantified with and without using the HueDx color correction pipeline show that the coefficient of variation in precision testing is almost twice as high without color-correcting. Limits of blank, detection and quantitation were also higher without color-correction. Overall, we were able to demonstrate the HueDx platform improves reading and outcome of the total protein diagnostic assay and is useful for the development of smartphone-based quantitative colorimetric diagnostic assays for point-of-care testing.