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The development of an affordable, portable, and instrument-free colorimetric biosensor holds significant importance for routine monitoring and clinical diagnosis. To overcome the limitations that traditional monochromatic colorimetric kits struggle to distinguish subtle color changes with the naked eye, we designed and constructed a portable hydrogel kit for polychromatic semi-quantitative and quantitative sensing analysis. When the actual samples and I- were introduced into a gelatin hydrogel encapsulated with MIL-88A(Fe), Au NRs and oxidase (Au@GM88A/I), a noticeable color change occurred. Additionally, a mathematic model between Hue and multicolor signal was set up for the first time by mobile phone photo technology, successfully applied to the glucose detection in serum. The visual detection had a wide concentration range of 0.02-0.80 mM with a limit of detection down to 0.02 mM. Above all, hydrogel kit prepared with gelatin as a carrier addressed the issues of uneven color and slow response rate commonly seen in gels like sodium alginate and agarose. This improvement would be beneficial for enhancing the accuracy of color captured by mobile phone assisted hydrogel kits, making it a valuable tool for biomarker analysis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

At present, the combination of fingerprint recognition methods and environmentally friendly and economical analytical instruments is becoming increasingly important in the food industry. Herein, a dithiothreitol (DTT)-functionalized CsPbBr 3 -based colorimetric sensor array is developed for qualitatively differentiating multiple food oils. In this sensor array composition, two types of iodides (octadecylammonium iodide (ODAI) and ZnI 2 ) are used as recognition elements, and CsPbBr 3 is used as a signal probe for the sensor array. Different food oils oxidize iodides differently, resulting in different amounts of remaining iodides. Halogen ion exchange occurs between the remaining iodides and CsPbBr 3 , leading to different colors observed under ultraviolet light, enabling a unique fingerprint for each food oil. A total of five food oils exhibit their unique colorimetric array's response patterns and were successfully differentiated by linear discriminant analysis (LDA), realizing 100% classification accuracy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

A rapid user-friendly paper-based test strip using zinc microparticles in conjugation with Griess reagent was developed for nitrite and nitrate detection. Test strips were fabricated using a simple and fast method of step-by-step immersion into reagents so that each strip contained a single detection pad for nitrite detection and another separate pad for nitrate detection. To reduce nitrate to nitrite, zinc microparticles suspended in ethanolic solution of polyvinylpyrrolidone (PVP) were uniformly immobilized on the paper strips that were previously impregnated in the Griess reagent and dried. The Griess reagent components were optimized to reach the highest color intensity. The optimized test strip was able to determine both nitrite and nitrate with respective detection limits of 0.43 and 9.43 mg/kg and a detection time of 60 s. The performance of the new test strips was evaluated for the simultaneous colorimetric detection of nitrite and nitrate in water and different food samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Hydrogen peroxide (H 2 O 2 ) is extensively used in water treatment and food preservation for its pathogen-killing efficacy. Excessive H 2 O 2 intake, however, can lead to poisoning with symptoms such as abdominal pain and breathing difficulties. Additionally, small amounts of H 2 O 2 may be generated during food preservation, necessitating careful control to meet safety regulations. Real-time detection of H 2 O 2 is crucial for process safety and compliance. In this study, a Zr-MOF-based colorimetric fluorescent nanozyme sensor (NH 2 -UiO-67(Zr/Cu)) along with a smartphone-assisted portable device were developed for detecting H 2 O 2 . The sensor, NH 2 -UiO-67(Zr/Cu), combines the stable structural properties of Zr-MOF with ligand-generated fluorescence and exhibits peroxidase-like activity. The sensor demonstrated a detection range of 0-1000 μM, with limits of detection (LOD) of 0.0057 μM for the colorimetric assay and 0.0020 μM for the fluorescence assay. Additionally, we designed and developed a portable, smartphone-assisted device using 3D printing technology. This device offers a detection range of 0-750 μM, with LODs of 0.0093 μM in colorimetric mode and 0.0311 μM in fluorescence mode. The developed colorimetric fluorescent nanozyme sensor and portable device show significant potential for the rapid on-site detection of H 2 O 2 , offering a more convenient and reliable approach for quick identification of analytes in practical applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objectives: The terms 'accuracy' and 'precision' are tightly defined in color science but are often used ambiguously in dental research. This study introduces the visual instrument agreement scale (VIAS), a new method for determining visual-instrumental agreement in dental colorimetry by comparing visually perceived and measured color differences., Materials and Methods: In-vivo tooth color measurements were taken from 16 participants using four intraoral scanners (Primescan, Medit i700, Carestream CS3700, Trios 3) and one spectrophotometer (Vita Easyshade V). Visual shade assessment was also performed by one expert observer using the 3D Master shade guide. Statistical significance testing was conducted using the STRESS index to calculate VIAS, and the F-statistic was used to evaluate device performance., Results: Carestream CS3700 achieved the highest visual-instrumental agreement with a VIAS score of 82 %, performing significantly better than the other devices. Primescan, Medit i700, and Trios 3 showed scores of 76 %, 75 %, and 72 %, respectively, with no significant differences between them. Vita Easyshade V scored 57 %, performing significantly worse than the other devices., Conclusions: The overall performance of the intraoral scanners was strong, with Carestream CS3700 approaching excellent performance. The VIAS method offers a practical, color science-based framework for evaluating visual-instrumental agreement and can be easily replicated using the freely available toolbox., Clinical Significance: Intraoral scanners performed surprisingly better than a spectrophotometer specifically designed for tooth color measurement and which is often regarded as the gold standard. Additionally, VIAS offers a new, scientifically grounded approach for testing visual-instrumental agreement in dental colorimetry., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Sascha Hein reports was provided by University of Leeds. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Monitoring various biomarkers in saliva samples emerges as a dynamic and non-invasive method. However, the high viscosity of saliva presents a distinct challenge when integrating paper-based platforms for on-site analysis. In addressing this challenge, we introduced the capillary-driven microfluidic paper-based analytical devices (μCD-PAD) designed for user-friendly and simultaneous detection of ethanol and tetrahydrocannabinol (THC) in saliva without a sample preparation step. Employing a colorimetric approach, we quantified both analytes. Synthetic salivas of varying viscosity flowed seamlessly to the detection zone without needing a sample preparation step, and no impact on colorimetric detection due to viscosity was observed (RSD <5 %). Within 10 min after the solution reached the detection zone, the device produced a homogeneous color signal, easily analyzed by a smartphone camera. To extend the application for determination to cover a legal limit concentration of ethanol and concentration of salivary THC even 24 h after marijuana consumption, the detection time of 30 min was optimized. Moreover, a saliva sample containing both analytes was used to demonstrate the capability of the developed device to detect ethanol and THC simultaneously. No cross-talk between ethanol and THC occurred and showed recovery in the 98-102 % for ethanol and 95-105 % for THC with acceptable accuracy. This developed device exhibits excellent potential for forensic applications, providing a user-friendly, cost-effective, and real-time screening tool for detecting ethanol and THC in saliva., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Salmonella screening is essential to avoid food poisoning. A simple, fast and sensitive colorimetric biosensor was elaborately developed for Salmonella detection on a microfluidic chip through limiting air chambers for precise air control, switching rotary valves for accurate fluid selection, a convergence-and-divergence passive micromixer and an extrusion-and-suction active micromixer for efficient fluid mixing, and immune gold@platinum palladium nanocatalysts for effective signal amplification. The mixture of bacteria, immune magnetic nanobeads and nanocatalysts was first rapidly mixed to form nanobead-bacteria-nanocatalyst conjugates and magnetically separated for enrichment. After washing with water, the conjugates were used to catalyze colorless substrate and blue product was finally analyzed using ImageJ for quantifying bacterial concentration. The finger-actuated microfluidic chip enabled designated control of designated fluids in designated places towards designated directions by simple press-release operations on designated air chambers without any external power. Under optimal conditions, this sensor could detect Salmonella at 45 CFU/mL in 25 min., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

An anti-interference colorimetric sensor array (CSA) technique was developed for the qualitative and quantitative detection of target heavy metals in corn oil. This method involves a binding mechanism that triggers changes in atomic energy levels and visible color changes. A custom-built olfactory visualization device was employed to gather spectral data, revealing distinct CSA color difference patterns. Subsequently, three pattern recognition algorithms were used to create an identification model for the target heavy metals. The results showed that the ACO-KNN (Ant Colony Optimization-K-Nearest Neighbor) model outperformed the other models, achieving accuracy rates of 90.28% and 89.58% for the calibration and prediction sets, respectively. The ACO-PLS (Partial Least Square) model was more stable with the lowest root mean square error of prediction (RMSEP), which were 0.1730 and 0.1180, respectively. The limit of detection (LOD) and quantification (LOQ) of Pb and Hg were (0.3, 0.6, 1.1 and 2.2) x 10 -3  mg/L, respectively., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

A point-of-care testing (POCT) platform, i.e., a portable colorimetric immunosensor based on iron oxide magnetic beads and AuNPs, has been developed for detecting leather residues. The immunosensor demonstrates a linear detection range from 1 ng/mL to 10 µg/mL, with a limit of detection (LOD) of 0.985 ng/mL. The sensor exhibits high specificity and repeatability and performs effectively in detecting leather artifacts excavated from Inner Mongolia. Thus, the proposed colorimetric immunosensor not only enables the micro-detection of leather artifacts but also shows significant potential for on-site leather detection at archaeological sites., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Achieving rapid extraction and detection of analytical solutions from plant tissues to circumvent cumbersome procedures and reduce the dependence on detection instruments remains a challenge. Herein, a colorimetric microneedle integrated platform was developed for the rapid extraction and detection of plant fluids for testing purposes. Colorimetric microneedle patches (CMPs) offer a swift and effective method to swiftly extract and detect ascorbic acid (AA) within 10 min from various fruit crops like mango, nectarine, apple, pear, and kiwifruit, facilitated by a smartphone application. CMPs are constructed for the rapid and sensitive analysis of AA with good linearity amid the range 0.05-25 μM and a low limit of detection of 30 nM. The novel CMPs demonstrate significant potential as a rapid detection platform for AA in plants. CMPs offer significant advantages over traditional ultraviolet spectrophotometry, such as simplified operational procedures and accelerated extraction and detection processes. This establishes robust groundwork for conducting in situ extraction and molecular detection of diverse crops across a spectrum of application scenarios.

Detecting glucose levels is crucial for diabetes patients as it enables timely and effective management, preventing complications and promoting overall health. In this endeavor, we have designed a novel, affordable point-of-care diagnostic device utilizing microfluidic principles, a smartphone camera, and established laboratory colorimetric methods for accurate glucose estimation. Our proposed microfluidic device comprises layers of adhesive poly-vinyl films stacked on a poly methyl methacrylate (PMMA) base sheet, with micro-channel contours precision-cut using a cutting printer. Employing the gold standard glucose-oxidase/peroxidase reaction on this microfluidic platform, we achieve enzymatic glucose determination. The resulting colored complex, formed by phenol and 4-aminoantipyrine in the presence of hydrogen peroxide generated during glucose oxidation, is captured at various glucose concentrations using a smartphone camera. Raw images are processed and utilized as input data for a 2-D convolutional neural network (CNN) deep learning classifier, demonstrating an impressive 95% overall accuracy against new images. The glucose predictions done by CNN are compared with ISO 15197:2013/2015 gold standard norms. Furthermore, the classifier exhibits outstanding precision, recall, and F1 score of 94%, 93%, and 93%, respectively, as validated through our study, showcasing its exceptional predictive capability. Next, a user-friendly smartphone application named "GLUCOLENS AI" was developed to capture images, perform image processing, and communicate with cloud server containing the CNN classifier. The developed CNN model can be successfully used as a pre-trained model for future glucose concentration predictions., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Creatinine, an important biomarker for renal functions, is often conventionally estimated using the gold standard Jaffe reaction from blood, which involves the usage of a spectrophotometric measurement, thus restricting its utilization scope in point-of-care settings. Here, we report the development of a method for the single-step quantification of creatinine from whole blood using a paper-based microfluidic device. Our platform uses Whatman filter paper integrated with an LF1 membrane. The on-chip separation of blood plasma is achieved through the LF1 membrane, while the Whatman component of the device contains the embedded reagents for the Jaffe reaction. The combination of two different grades of paper enables a single-step quantification of creatinine as the separated blood plasma traverses to the reaction zone through capillary imbibition. Colorimetric readouts were quantified using an RGB sensor instead of a smartphone, which is highly platform dependent and incurs a relatively higher cost compared to the other components in typical point-of care (POC) devices. Our sensor was integrated within a 3D box, thereby making the detection virtually instrument free and perfectly suited for POC settings. The limit of detection (LOD) of our device was 0.219 mg dL -1 , which falls within the lower range of physiological values. The coefficient of determination ( R 2 ) for the linearity and median accuracy were 0.978 and 94.047%, respectively. The relative standard deviation (RSD) for precision measurements remained below 5% for the developed protocol. Furthermore, we validated the performance of our device with 35 clinical samples in laboratory settings against the gold standard measurements. Our Bland-Altman plot as well as t -test and chi-square test results clearly confirmed the validity of our device within a 95% confidence interval.

Dual-mode-based sensors have drawn a lot of interest due to their high accuracy and sensitivity compared to single-response systems. A simple electrochemical and colorimetric dual-mode sensor based on enzyme-linked immunosorbent assay (ELISA), without complex electrode surface modification, was developed for accurate and sensitive detection of carcinoembryonic antigen (CEA). The target CEA is recognized by an antibody coupled to horseradish peroxidase (HRP), which then oxidizes the substrate 3,3',5,5'-tetramethylbenzidine (TMB) to generate both a colorimetric and an electrochemical signal. A paper-based analysis device (μPAD) with dual-mode homogeneous sensing microfluidic was created; three paper-based detection areas for colorimetric testing, and a two-electrode embedded detection area for electrochemical testing. When applying colorimetric analysis technology, the linear range of CEA detection is 0.6-40 ng mL -1 , and the limit of detection (LOD) is 0.2 ng mL -1 . The linear range is 0.1-40 ng mL -1 and the LOD is 0.03 ng mL -1 by applying electrochemical analysis. The visibility and intuitiveness of colorimetry provide a reference for higher sensitivity and quick response of the electrochemical method. A smartphone application (APP) was also developed to realize the dual extraction of colorimetric signals. The colorimetric detection system based on ELISA can provide a new path for the development of electrochemical sensing and makes it have inherent self-verification and self-correction functions and is expected to provide more reliable and accurate detection results.

Achieving rapid, cost effective, and intelligent identification and quantification of flavonoids is challenging. For fast and uncomplicated flavonoid determination, a sensing platform of smartphone-coupled colorimetric sensor arrays (electronic noses) was developed, relying on the differential competitive inhibition of hesperidin, nobiletin, and tangeretin on the oxidation reactions of nanozymes with a 3,3',5,5'-tetramethylbenzidine substrate. First, density functional theory calculations predicted the enhanced peroxidase-like activities of CeO 2 nanozymes after doping with Mn, Co, and Fe, which was then confirmed by experiments. The self-designed mobile application, Quick Viewer, enabled a rapid evaluation of the red, green, and blue values of colorimetric images using a multi-hole parallel acquisition strategy. The sensor array based on three channels of CeMn, CeFe, and CeCo was able to discriminate between different flavonoids from various categories, concentrations, mixtures, and the various storage durations of flavonoid-rich Citri Reticulatae Pericarpium through a linear discriminant analysis. Furthermore, the integration of a "segmentation-extraction-regression" deep learning algorithm enabled single-hole images to be obtained by segmenting from a 3 × 4 sensing array to augment the featured information of array images. The MobileNetV3-small neural network was trained on 37,488 single-well images and achieved an excellent predictive capability for flavonoid concentrations (R 2  = 0.97). Finally, MobileNetV3-small was integrated into a smartphone as an application (Intelligent Analysis Master), to achieve the one-click output of three concentrations. This study developed an innovative approach for the qualitative and simultaneous multi-ingredient quantitative analysis of flavonoids., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Heavy metal contamination is an increasing global threat to human and environmental health, particularly in resource-limited areas. Traditional platforms for heavy metal detection are labor intensive and expensive and require lab facilities. While paper-based colorimetric sensors offer a simpler approach, their sensitivity limitations prevent them from meeting legislative requirements for many metals. Existing preconcentration systems, on the other hand, can achieve lower detection limits but typically focus on analyzing only one metal, making comprehensive monitoring difficult. We address these limitations by introducing a low-cost preconcentration system coupled with colorimetric analysis for the simultaneous detection of seven metal ions at low ppb levels without the need for external equipment outside a smartphone. The system achieved detection limits of 15 ppb (Ni(II)), 7 ppb (Cu(II)), 2 ppb (Fe(III)), 20 ppb (Cr(VI)), 13 ppb (Pb(II)), 26 ppb (Hg(II)), and 15 ppb (Mn(II)) with six out of seven limits of detection values falling well below EPA regulatory guidelines for drinking water. The user-friendly Fill, Fold, Photo approach eliminates complex pretreatment steps. Smartphone-based detection offers portable quantification within seconds. Employing masking strategies ensured higher selectivity for each assay on the card, while our packaging protocols enable system stability for over 4 weeks of study, facilitating mass production and deployment within a realistic time frame. To validate the sensor's performance in real-world scenarios, the sensor was tested with environmental water samples. The sensor demonstrated good recovery, ranging from 77% to 94% compared to the standard ICP-MS method. Furthermore, spike recovery analysis confirmed the sensor's accuracy, with a relative standard deviation (RSD) of less than 15%. This technology holds significant promise for future development as a convenient, portable solution for field-based monitoring of a broad spectrum of water contaminants, including pesticides, PFAS, fertilizers, and beyond.

A paper-based colorimetric sensor array mediated by a novel nanozyme (CuCo 2 O 4 ) was developed using a screen-printing technology. The aim was to facilitate the identification of different kinds of alkaloids. Typically, three chromogenic substrates (3,3',5,5'-tetramethylbenzidine, 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid), and o-phenylenediamine) were selected as sensing elements, which can be catalyzed by a CuCo 2 O 4 nanozyme with peroxidase-like activity to yield corresponding oxidized products, thereby inducing color changes. Owing to the varying inhibitory ability of different alkaloids on acetylcholinesterase (AChE), a decrease in choline (Ch) concentration occurs and subsequently results in the restoration of color within the units of sensor array. Color data can be transformed into hue information with a smartphone. The above color variations generated a unique "fingerprint" pattern on five alkaloids (berberine, palmatine, jatrorrhizine, eserine, and harmane), which can be successfully discriminated through linear discriminant analysis in the range 0.2 to 20 µM. Furthermore, the sensor arrays allowed successful discrimination of the above five alkaloids in Chinese herbal medicine samples and recognition of 22 blind samples. This work presents a novel nanozyme-based paper sensor array, which is a user-friendly and reliable platform for probing different alkaloids. In addition, the developed sensing strategy enables the identification of AChE-related diseases, positively contributing to the screening available of AD-associated drugs., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

The development of dual-mode strategies with superior sensitivity and accuracy have garnered increasing attention for researchers in Aflatoxin B1 (AFB1) analysis. Herein, a colorimetric-electrochemiluminescence (ECL) dual-mode biosensor was constructed for onsite and ultrasensitive determination of AFB1. The multi-wall carbon nanotubes (MWCNTs) were integrated with the ZnO metal organic frameworks (MOFs) to accelerate the electron transfer and boost the ECL intensity of g-C 3 N 4 nanoemitters. Through the aptamer-based DNA sandwich assay, the CuO@CuPt nanocomposites were introduced onto the electrode and acted as the dual functional signal nanoprobes. Due to the good spectrum overlap between the CuO@CuPt nanoprobes and g-C 3 N 4 nanosheets, ECL signal could be efficiently quenched. Additionally, the CuO@CuPt nanoprobes show superior catalytic properties towards the TMB and H 2 O 2 colorimetric reactions, and an obvious color alteration from colorless to blue can be observed using the smartphone. Under optimized conditions, a sensitive and accurate dual-mode analysis of the AFB1 was accomplished with the colorimetric detection limit of 3.26 fg/mL and ECL detection limit of 0.971 fg/mL (S/N = 3). This study combines innovative nanomaterial properties of ZnO@MWCNTs, g-C 3 N 4 and CuO@CuPt for ultrasensitive dual-mode detection, which offers new opportunities for the innovative engineering of the dual-mode sensors and demonstrates significant potential in food safety analysis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

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., Competing Interests: Financial support for the development of this product was provided by HueDx,Inc., an early-stage venture-capital-backed company. All authors are employees of the company. The HueDx system, consisting of the color correction pipeline, HueCard(with custom sticker) and HueTools are commercially marketed products. Code for the color correction pipeline cannot be made available publicly due to legal restrictions., (Copyright: © 2024 Menon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Colorimetry is a widely used technique for optical detection in point-of-care testing and on-site detection. Although some studies employ a multiplex approach to analyse coloured solutions, many still analyse one sample at a time. We have prepared a simple and affordable colorimetric assay based on a TCS34725 colour sensor (ams-OSRAM) integrated into an M5Stack module and an RGB LED module both inserted into a 3D printed frame. We found that the colorimetric assay can be easily transferred to a colour sensing platform, and the signal range obtained using the prepared colorimeter is more than 200 times larger than that obtained using digital image colorimetry (DIC) for the same samples containing cholinesterase or urease as a model enzyme providing a change in pH of the processed solution. The assay appears to be ready for practical use.

Objective: The objective was to compare the colourimetric increment (L*, a*, and b*) of three types of aligners after subjecting them to two stains and to evaluate the initial colourimetric characteristics., Methods: A total of 120 aligners (40 Invisalign®, 40 Spark®, and 40 QuickSmile®) were immersed in two different agents (distilled water and coffee). Measurements were taken using a spectrophotometer before immersion (T0), after 12 hours (T1), and after 7 days (T2). Colour changes (ΔE*) were evaluated based on the International Commission of L'Eclairage, and subsequently converted to National Bureau of Standards units. The measurement was repeated three times. The intraclass correlation coefficient, one-way ANOVA, Tukey's post hoc test, and the independent t test were used (P ≤ .05)., Results: At T0, significant differences were observed for a*: Invisalign® and Spark® tended towards redder tones, whereas Quicksmile® leaned towards greener shades. Regarding b*, all aligners tended towards yellow, with Invisalign® exhibiting the least tendency. No differences were found in water between T1 and T0. In the intervals, T2-T1 and T2-T0, Spark® showed more noticeable changes, whereas for Invisalign® and Quicksmile®, the change was only slight. In coffee, a shift to another colour was detected in T1-T0, T2-T1, and T2-T0 for Invisalign®, whereas for other brands, it was barely noticeable except for T2-T0 in Spark®, where the change was appreciable. In coffee, Invisalign® tended towards darker values (L*), turning redder (a*), and more yellow (b*) in T2-T1 and T2-T0., Conclusions: Invisalign® aligners initially presented a more reddish and less yellowish colour. In water, after 7 days, a noticeable colour change was found for Spark®. In coffee, a greater loss in brightness and a change to red and yellow were observed after 12 hours and 7 days for Invisalign®. This study highlights the importance of considering the impact of coffee on the colouring of aligners, especially with Invisalign®, which shows more noticeable changes., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Orthodontic Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Colorimetric sensors play a crucial role in promoting on-site testing, enabling the detection and/or quantification of various analytes based on changes in color. These sensors offer several advantages, such as simplicity, cost-effectiveness, and visual readouts, making them suitable for a wide range of applications, including food safety and monitoring. A critical component in portable colorimetric sensors involves their integration with color models for effective analysis and interpretation of output signals. The most commonly used models include CIELAB (Commission Internationale de l'Eclairage), RGB (Red, Green, Blue), and HSV (Hue, Saturation, Value). This review outlines the use of color models via digitalization in sensing applications within the food safety and monitoring field. Additionally, challenges, future directions, and considerations are discussed, highlighting a significant gap in integrating a comparative analysis toward determining the color model that results in the highest sensor performance. The aim of this review is to underline the potential of this integration in mitigating the global impact of food spoilage and contamination on health and the economy, proposing a multidisciplinary approach to harness the full capabilities of colorimetric sensors in ensuring food safety., (© 2024 The Author(s). Advanced Materials published by Wiley‐VCH GmbH.)

Given the significant and potential fatal implications of glyphosate (GLY) residues on human health and the integrity of ecosystems, their presence has garnered substantial global concern and scrutiny. Herein, we introduced a pioneering colorimetric sensing platform, the first of its kind, based on ternary metal-organic frameworks (ZnCo-ZIFs@MIL-101(Fe)). This innovative platform enabled ultra-sensitive, affordable, portable and rapid on-site detection of GLY. This platform achieved a wider linear range for GLY of 0.02-40 μg/mL with an exhibiting remarkable detection limit of 1 ng/mL, which was attributed to the electronic hybridization of the Fe 3+ , Co 2+ , and Zn 2+ metal centers of ZnCo-ZIFs@MIL-101(Fe), significantly enhancing the composite's catalytic performance. The assay was successfully employed to detect GLY in food and herb samples. Moreover, to meet the demand of in-field detection for GLY, a smartphone detection method based on ZnCo-ZIFs@MIL-101(Fe) with visual, intelligent, and portable features was fabricated. This detection concentration range of GLY was 0-1 μg/mL, and the limit of smartphone detection was 23 ng/mL. Furthermore, this sensor seamlessly integrated with smartphones and paper-based microfluidic chips (μPADs), which constructed a portable test strips-smartphone sensing platform for facilitating real-time and on-site visual quantitative detection of GLY. The detection concentration range was 0-1 μg/mL, and the limit was calculated as low as 75 ng/mL. The assay was highly adaptable in practical applications. In summary, our study paved a novel pathway for the design and utilization of multi-metal MOF nanozymes in on-site pesticide monitoring., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The smartphone-assisted ultrasensitive colorimetric aptasensor based on DNA-encoded porous Ti 3 C 2 nanozyme (Apt-P-Ti 3 C 2 ) was exploited for real-time detection of OA. Porous Ti 3 C 2 (P-Ti 3 C 2 ) MXene with outstanding peroxidase-like activities were crafted using microwave combustion, facilitating the efficient catalysis of chromogenic substrate oxidation by H 2 O 2 . The integration of a considerable number of unsaturated Ti center edges and residual Mn 2+ within the single-layer porous Ti 3 C 2 framework augmented the adsorption capacity of DNA aptamer, thereby yielding a heightened catalytic efficacy of P-Ti 3 C 2 nanoparticles. The enhanced catalytic activity of P-Ti 3 C 2 can be partially diminished through specific recognition of OA. Concurrently, a smartphone platform was integrated for signal reading based on the colorimetric sensing strategy. The smartphone-based biosensor exhibited a reliable and ultrasensitive capability for OA detection with the detection limit of 0.38 ng·mL -1 . It is anticipated that the developed smartphone-based biosensing platform can provide a prospective ultrasensitive detection method for marine algal toxin in food analysis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Ochratoxin A (OTA) poses significant risks to human health, being potentially nephrotoxic, carcinogenic, genotoxic, and immuno-toxic. In this work, we developed a dual-mode aptasensor for OTA analysis, integrating colorimetric, electrochemical, and smartphone-based detection. The bifunctional Fe-MIL-88 metal-organic framework, acting as both a nanozyme capable of catalyzing the 3,3',5,5'-tetramethylbenzidine substrate and an electrochemical signal amplifier, enabled OTA quantification through current response or changes in color and absorbance intensity. Besides, the spatial confinement effect enhances the local concentration of Fe-MIL-88 signal probes through rolling circle amplification reaction, thereby contributing to a substantial enhancement in sensitivity. The proposed technique is simple, disposable, highly sensitive and selective, enabling OTA detection in the range of 1 fg/mL to 250 ng/mL, with a limit of detection of 0.22 fg/mL (3σ rule). Furthermore, we successfully detected OTA in corn, wheat, and red wine samples, with results good concordance with those obtained using commercial enzyme-linked immunoassay kits., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Mercury ions (Hg 2+ ) are highly toxic heavy metals that are commonly found in natural environments. Owning to their non-biodegradability and accumulation in the food chain, the precise detection of trace amounts of Hg 2+ is essential for preventing chronic accumulation and ensuring food safety. In this study, we present a dual-mode paper sensor for simultaneous colorimetric and Surface-Enhanced Raman Spectroscopy (SERS) detection of Hg 2+ in tea, achieving ultrasensitive, rapid, and on-site screening. 4-Mercaptopyridine (4-MPY) was effectively chemisorbed onto the gold nanoparticles (AuNPs), acting as a signal probe for colorimetric methods. Moreover, it can produce plasmonic hot spots for SERS by interacting with the pyridine ring. To enhance the signal intensity of both colorimetry and SERS, a silver shell is in-situ grown on the surface of AuNPs captured on the paper sensor by reduction of Ag + , achieving signal amplification. The visual limit of detection (LOD) for the colorimetric biosensor is 2.5 pM, while the LOD of SERS is 0.48 pM with this dual-mode paper sensor. The sensitivity of both the colorimetric method and SERS was improved by approximately 200 and 500 times, respectively, with the designed signal amplification strategy. The system allows for multiple parallel screening of the same sample, ensuring accurate results without any false-positive or false-negative. This study provides a valuable platform for the accurate detection of various other heavy metal ions and provides effective strategies for improving the performance of colorimetric methods., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This paper presents the development and application of attapulgite/polyimide nanofiber composite aerogels (ATP/PI NFAs) integrated with a range of acid-base indicators, fabricated using electrospinning and freeze-drying technologies. A detailed characterization of the ATP/PI NFAs revealed a 3D multi-level pore structure that enhanced the mass transfer of target gas molecules and their interaction with probe molecules. Utilizing machine learning approaches, we designed an ATP/PI NFAs-based colorimetric sensor array capable of real-time evaluation of balsa fish freshness. Color features sensitive to changes in freshness were selected using principal component analysis and random forest. Partial least squares regression and random forest regression models were established, achieving the prediction of total volatile basic nitrogen content in balsa fish. The system was validated using a national standard method to demonstrate its accuracy and practicality. The combination of advanced ATP/PI NFAs-based colorimetric sensor array with robust machine learning models paves the way for food safety monitoring., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Sucrose, a common sugar primarily derived from sugarcane, is a crucial national strategic resource. However, its yield is significantly affected by various serious diseases, with pokkah boeng disease being one of the most damaging. Therefore, developing a sensitive method for the accurate detection of the pokkah boeng disease pathogen is crucial for ensuring the safety of sugar. This work presents a portable dual-modal detection device, assisted by a smartphone, which is based on MoS 2 @GDY, Mn 3 O 4 @Au nanomenzyme, cross-N DNA framework and Exo III exonuclease-assisted CHA signal amplification technology. The cross-N DNA framework provides many binding sites and is not restricted by AuNPs scattering positions, enhancing the signal output strength of the sensor. Additionally, the detection system incorporates a high-power-density capacitor to further amplify the electrochemical detection signal, increasing sensitivity by 9.1 times. Moreover, the use of electrochemical and colorimetric dual-mode detection effectively avoids mutual interference, reducing the likelihood of false positives from a single signal. Under optimized conditions, the proposed method has a linear range of 0.0001-10,000 pM, and with a detection limit of 6.1 aM (S/N=3). This high-sensitivity, high-reliability portable sensing method shows significant potential for the early detection and real-time on-site monitoring of the pokkah boeng disease pathogen., Competing Interests: Declaration of competing interest The authors declared that they have no conflicts of interest to this work., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Colorimetric sensors have applications in gas monitoring due to their simple and quick detection through visible color changes. However, it remains challenging to prepare colorimetric sensors with high sensitivity. Herein, this work fabricated a biomass-based colorimetric sensing yarn with high sensitivity using anthocyanins as the colorimetric dye and wool powder as an effective ammonia (NH 3 ) adsorbent. The sensitivity of the prepared yarns was evaluated for detection limit and response time. Surprisingly, the addition of 3% wool powder greatly improved the sensitivity of the prepared yarns, with a reduction of both detection limit and responsive time from 100 ppm to 20 ppm, and 2 min to 20 s, respectively when exposed in 150 ppm NH 3 . The prepared yarns also showed good selectivity and reusability. An example of the practical use of colorimetric yarns was presented. This work provides a facile strategy for fabricating wearable devices for toxic gas monitoring with visual output., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Quantitative monitoring of the concentrations of epigallocatechin gallate (EGCG) and cysteine (Cys) is of great significance for promoting human health. In this study, iron/aluminum bimetallic MOF material MIL-53 (Fe, Al) was rapidly prepared under room temperature using a co-precipitation method, followed by investigating the peroxidase-like (POD-like) activity of MIL-53(Fe, Al) using 3,3',5,5'-tetramethylbenzidine (TMB) as a chromogenic substrate. The results showed that the Michaelis -Menten constants of TMB and H 2 O 2 as substrates were 0.167 mM and 0.108 mM, respectively. A colorimetric sensing platform for detecting EGCG and Cys was developed and successfully applied for analysis and quantitative detection using a smartphone. The linear detection range for EGCG was 15∼80 μM (R 2 =0.994) and for Cys was 7∼95 μM (R 2 =0.998). The limits of detection (LOD) were 0.719 μM and 0.363 μM for EGCG and Cys, respectively. This work provides a new and cost-effective approach for the real-time analysis of catechins and amino acids., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Baijiu authenticity has been a frequent problem driven by economic interests in recent years, so it is important to discriminate against baijiu with different origins. Herein, we proposed a simple and efficient esters-targeted colorimetric sensor array mediated by hydroxylamine hydrochloride. Esters undergo a nucleophilic addition reaction with hydroxylamine hydrochloride to form hydroxamic acid, which rapidly forms a purplish red ferric hydroxamate under FeCl 3 ·6H 2 O. Bromophenol blue and rhodamine B enrich the color effects. The array detected 12 esters with a detection limit on the order of 10 -5 of most esters and 16 mixed esters with R 2  > 0.999 and recoveries close to 100%. Otherwise, for discriminating 34 strong-aroma baijius (SABs), the array has an accuracy of 98% according to the origin, and 95% according to the grades, with a response time of 1 min. This study provides a new strategy for authenticity determination and quality control of baijiu., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Oral squamous cell carcinoma (OSCC) is the most common type of head and neck cancers. OSCC constitutes 90% of the head and neck malignancies. The delayed identification of oral cancer is the primary cause of ineffective medical treatment. To address this issue, low-cost, reliable point-of-care devices that can be utilized for large-scale screening, even in low-resource settings, including rural areas and primary healthcare centers, are of great interest. Herein, a comprehensive analysis of numerous salivary biomarkers that exhibit significant variations in concentration between individuals with oral cancer and those without is given. Furthermore, the article explores several point-of-care devices that exhibit potential in the realm of oral cancer detection. The biomarkers are discussed with a focus on their structural characteristics and role in oral cancer progression. The devices based on colorimetry and microfluidics are discussed in detail, considering their compliance with the 'REASSURED' criteria given by the World Health Organization (WHO) and suitability for mass screening in low-resource settings. Finally, the discourse revolves around the fundamental aspects pertaining to the advancement of multiplex, cost-effective point-of-care devices designed for widespread screening purposes.

A simple method has been developed for semi-quantitative analysis of the colorimetric output of loop-mediated isothermal amplification (LAMP) using a 3D-printed tube holder with a smartphone and notebook for the detection of Raillietina, which is the cause of Raillietiniasis affecting free-range chicken farming. In this method, a light is directed from a notebook screen to the LAMP products in the tube holder and the color absorption of the LAMP products is measured by using the appropriate smartphone application. It was found that the malachite green dye-coupled LAMP (MaG-LAMP) assay showed the highest sensitivity and specificity for detecting Raillietina without any cross-reaction with other related parasites and hosts. The limit of detection was 10 fg/μL of DNA. A total of 60 fecal samples were infectively confirmed by microscopic examination and the results of microscopy compared with those of MaG-LAMP and triplex PCR assays. Microscopy and MaG-LAMP based on the color absorption demonstrated high agreement in Raillietina detection with kappa = 1. Rapid, simple, cost-effective, and easy interpretation of colorimetric LAMP assays and their high sensitivity make them superior to PCR and morphological investigation, demonstrating the feasibility of this assay in point-of-care screening to support farm management and solve chicken health problems. Our study presents is an alternative diagnostic method using semi-quantitative analysis of colorimetric LAMP based on the differing solution color absorptions between positive and negative reactions for infectious disease diagnosis., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

The real-time monitoring of the pH values of alcoholic beverages was performed with a compact wireless device based on a colorimetric detection method with the Hue (H) as the analytical signal working in a pH range of 2.50-6.50. This device represents the first colorimetric pH meter reported in the literature monitoring in real-time the pH value of colored solutions. This pH meter consists of I) a nitrocellulose membrane impregnated with a pH-sensitive gel; II) a CCD camera for color acquisition; III) an electronic board with the calibration profiles of H vs. pH, and IV) a display to read the measured pH. It was applied to the pH determination of a white wine, a prosecco white wine, and a double malt beer leading to the values of pH wine = 3.30, pH prosecco = 3.33, pH beer = 4.29. The analytical performance is comparable to the glass electrode with an accuracy error ≤ 0.05 pH units., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Given the potential dangers of thiram to food safety, constructing a facile sensor is significantly critical. Herein, we presented a colorimetric sensor based on glutathione‑iron hybrid (GSH-Fe) nanozyme for specific and stable detection of thiram. The GSH-Fe nanozyme exhibits good peroxidase-mimicking activity with comparable Michaelis constant (K m  = 0.551 mM) to the natural enzyme. Thiram pesticides can specifically limit the catalytic activity of GSH-Fe nanozyme via surface passivation, causing the change of colorimetric signal. It is worth mentioning that the platform was used to prepare a portable hydrogel kit for rapid qualitative monitoring of thiram. Coupling with an image-processing algorithm, the colorimetric image of the hydrogel reactor is converted into the data information for accurate quantification of thiram with a detection limit of 0.3 μg mL -1 . The sensing system has good selectivity and high stability, with recovery rates in fruit juice samples ranging from 92.4% to 106.9%., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The detection of ammonia levels in blood is critical for diagnosing and monitoring various medical conditions, including liver dysfunction and metabolic disorders. However, traditional diagnostic methods are slow and cumbersome, often involving multiple contact-based steps such as ammonia separation in alkali conditions followed by distillation or microdiffusion, leading to delays in diagnosis and treatment. Herein, we developed a colorimetric assay capable of rapid detection of ammonia in whole blood or plasma samples, utilizing 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO)-oxidized cellulose nanocrystals (TCNC) coupled with gold nanoparticles (AuNPs). The basis of our assay relies on either (i) the interaction between the carboxylate group ( - COO) of TEMPO and ammonium ions or (ii) the manipulation of AuNPs surface plasmon resonance (SPR) through the formation of Au(NH 3 ) 4 3+ , which displaces a redox mediator, resazurin, resulting in observable multicolor displays at various concentrations of ammonia. The colorimetric assay exhibits a wide linear detection range for dissolved NH 4 + (0.1-37 μM) with a low limit of detection (LOD) of 0.1 μM. Additionally, it effectively measures NH 3(g) concentrations in the range of 0.5-144 μM. The fabricated electrochemical nose (E-nose) device demonstrates excellent analytical performance for plasma ammonia sensing (0.05-256 μM). Experimental results demonstrate a linear detection range suitable for clinical applications, with excellent correlation to standard laboratory methods, offering a practical solution for point-of-care (PoC) testing. We anticipate that this approach can be applied broadly to improve patient monitoring and treatment by providing immediate and accurate ammonia measurements in a clinical setting.

Deferiprone (DFP) is one of the iron-chelating agents used in iron overload therapy for patients with ß-thalassemia major (ß-TM). However, the use of DFP is limited as it experiences a first-pass effect and can potentially cause iron deficiency due to uncontrolled release. Therefore, iron-responsive (NP-IR) DFP nanoparticle innovation was developed to control DFP release. A dissolving microneedle system (NP-IR-DMNs) was used to maximize DFP release. However, in support of this development, validation of analytical methods using spectrophotometry and colorimetrics was carried out. UV-Vis spectrophotometry is an approach that is easy to use, practical, and more cost-effective than others. The DFP levels were determined in normal and iron-overloaded medium solutions with 1%, 2%, and 4% concentrations. In addition, DFP levels were also measured in rat plasma using the colorimetric method with the addition of FeCl 3 reagent to increase sensitivity for the detection of the analyte. The procedures used as guidelines in the validation procedure are The International Council for Harmonization (ICH). As a result, all linear correlation values of medium and plasma ≥ 0.999 were obtained. The LOQ levels obtained were 0.55 µg/mL, 0.44 µg/mL, 0.42 µg/mL, 0.52 µg/mL, and 1.01 µg/mL in plasma, 1% FeSO 4 , 2% FeSO 4 , 4% FeSO 4 , and normal media, respectively. The accuracy and precision were confirmed valid, as all values were within the requirements and did not change during dilution. Then, this approach was successfully applied to determine the levels of DFP in NP-IR integrated into DMNs., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Ketones, such as beta-hydroxybutyrate (BHB), are important metabolites that can be used to monitor for conditions such as diabetic ketoacidosis (DKA) and ketosis. Compared to conventional approaches that rely on samples of urine or blood evaluated using laboratory techniques, processes for monitoring of ketones in sweat using on-body sensors offer significant advantages. Here, we report a class of soft, skin-interfaced microfluidic devices that can quantify the concentrations of BHB in sweat based on simple and low-cost colorimetric schemes. These devices combine microfluidic structures and enzymatic colorimetric BHB assays for selective and accurate analysis. Human trials demonstrate the broad applicability of this technology in practical scenarios, and they also establish quantitative correlations between the concentration of BHB in sweat and in blood. The results represent a convenient means for managing DKA and aspects of personal nutrition/wellness.

A novel microfluidic paper-based analytical device with dual colorimetric and electrochemical detection (dual μPAD) was developed for the assessment of transferrin saturation (TSAT) in samples from ischemic stroke patients. TSAT was calculated from the ratio between transferrin-bound iron, which was colorimetrically measured, and the total iron-binding capacity, which was electrochemically measured. To this end, a μPAD was smartly designed, which integrated both colorimetric and electrochemical detection reservoirs, communicating via a microchannel acting as a chemical reactor, and with preloading/storing capabilities (reagent-free device). This approach allowed the dual and simultaneous determination of both parameters, providing an improvement in the reliability of the results due to an independent signal principle and processing. The μPADs were validated by analyzing a certified reference material, showing excellent accuracy ( E r ≤ 5%) and precision (RSD ≤ 2%). Then they were applied to the analysis of diagnosed serum samples from ischemic stroke patients. The results were compared to those provided by a free-interference method (urea-PAGE). Impressively, both methods exhibited a good correlation ( r = 0.96, p < 0.05) and no significant differences were found between them (slope 1.0 ± 0.1 and the intercept 1 ± 4, p < 0.05), demonstrating the excellent accuracy of our approach during the analysis of complex samples from ischemic stroke patients, using just 90 μL of clinical samples and taking less than 90 min in comparison with the 18 hours required by the urea-PAGE approach. The developed fully integrated colorimetric-electrochemical μPAD is a promising ready to use reagent-free device for the point-of-care testing of TSAT, which can be used to assist physicians in the fast diagnosis and prognosis of ischemic strokes, where the decision-time is crucial for the patient's survival.

Accurate and effective detection is essential to against bacterial infection and contamination. Novel biosensors, which detect bacterial bioproducts and convert them into measurable signals, are attracting attention. We developed an artificial intelligence (AI)-assisted smartphone-based colorimetric biosensor for the visualized, rapid, sensitive detection of pathogenic bacteria by measuring the bacteria secreted hyaluronidase (HAase). The biosensor consists of the chlorophenol red-β-D-galactopyranoside (CPRG)-loaded hyaluronic acid (HA) hydrogel as the bioreactor and the β-galactosidase (β-gal)-loaded agar hydrogel as the signal generator. The HAase degrades the bioreactor and subsequently determines the release of CPRG, which could further react with β-gal to generate signal colors. The self-developed YOLOv5 algorithm was utilized to analyze the signal colors acquired by smartphone. The biosensor can provide a report within 60 min with an ultra-low limit of detection (LoD) of 10 CFU/mL and differentiate between gram-positive (G+) and gram-negative (G-) bacteria. The proposed biosensor was successfully applied in various areas, especially the evaluation of infections in clinical samples with 100% sensitivity. We believe the designed biosensor has the potential to represent a new paradigm of "ASSURED" bacterial detection, applicable for broad biomedical uses., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relatinships which may be considered as potential competing interests: Danyang Li has a patent licensed to the Seventh Affiliated Hospital of Sun Yat-sen University., (Copyright © 2024 Elsevier B.V. All rights reserved.)

A colorimetric sensing method based on a paper-based vapor-test kit was successfully developed for the selective and sensitive real-time monitoring of formalin in food samples. The device was specifically designed to efficiently extract and detect formalin simultaneously. A microcentrifuge tube was used as the sample solution container, with the inner cap serving as the reaction and detection zone. Formalin was converted into gaseous formaldehyde through controlled heating, which was then extracted and collected on a filter paper coated with Nash's reagent. The color change on paper was used for formalin quantification using a smartphone for detection and image analysis. Under optimal conditions, our method provided a linear range of 0.5-75 mg L -1 with a detection limit of 0.11 mg L -1 . This method effectively determined formalin in fresh food and vegetable samples, with recoveries ranging from 92 to 111%, demonstrating comparable accuracy to the standard method for practical food quality control and safety., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Monitoring chemical levels is crucial for safeguarding both the environment and public health. Elevated levels of ammonia, for instance, can harm both humans and aquatic ecosystems, often indicating contamination from agriculture, industry, or sewage. Developing portable, high-resolution, and affordable methods for in situ monitoring of ammonia is thus imperative. Plasmonic sensors offer a promising solution, detecting ammonia by correlating changes in their optical response to the target analyte's concentration. While they are highly sensitive and can be fabricated in a variety of portable and user-friendly formats, some still require reagents or expensive optical equipment, which hinder their widespread adoption. Here, we present a self-assembled nanoplasmonic colorimetric sensor capable of directly detecting ammonia concentrations in aqueous matrices. The proposed sensor exploits the plasmonic resonance of the nanostructures to transduce changes in the chemical environment into alterations in color, offering a label-free method for real-time analysis. The sensor is fabricated using a self-assembling technique compatible with low-cost mass production based on aluminum and aluminum oxide, ensuring affordability and avoiding the use of other toxic chemicals. We developed a model to predict ammonia concentrations based on visible color change of the sensor, achieving a detection limit of 8.5 ppm. Furthermore, to address the need for on-site detection, we integrated smartphone technology for real-time color change analysis, eliminating the need for expensive, bulky optical instruments. Indeed, our approach offers a cost-effective, portable, and user-friendly solution for ammonia detection in water without the need for chemical reagents or spectrometers, making it ideal for field applications. Interestingly, this platform extends its applicability beyond ammonia detection, enabling the monitoring of various chemicals using a smartphone, without the need for any additional costly equipment.

Lateral flow assay (LFA) color signal quantification methods were developed by utilizing both International Commission on Illumination (CIE) LAB (CIELAB) color space and grayscale intensity differences. The CIELAB image processing procedure included calibration, test, control band detection, and color difference calculation, which can minimize the noise from the background. The LFA platform showcases its ability to accurately discern relevant colorimetric signals. The rising occurrence of infectious outbreaks from foodborne pathogens like Salmonella typhimurium presents significant economic, healthcare, and public health risks. The study introduces an aptamer-based lateral flow (ABLF) platform by using inkjet printing for specially detecting S. typhimurium. The ABLF utilized gold-decorated polystyrene microparticles, functionalized with specific S. typhimurium aptamers (Ps-AuNPs-ssDNA). The platform demonstrates a detection limit of 10 2 CFU mL -1 in buffer solutions and 10 3 CFU mL -1 in romaine lettuce tests. Furthermore, it sustained performance for over 8 weeks at room temperature. The ABLF platform and analysis methods are expected to effectively resolve the low-sensitivity problems of the former LFA systems and to bridge the gap between lab-scale platforms to market-ready solutions by offering a simple, cost-effective, and consistent approach to detecting foodborne pathogens in real samples., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

One challenge for gas sensors is humidity interference, as dynamic humidity conditions can cause unpredictable fluctuations in the response signal to analytes, increasing quantitative detection errors. Here, we introduce a concept: Select humidity sensors from a pool to compensate for the humidity signal for each gas sensor. In contrast to traditional methods that extremely suppress the humidity response, the sensor pool allows for more accurate gas quantification across a broader range of application scenarios by supplying customized, high-dimensional humidity response data as extrinsic compensation. As a proof-of-concept, mitigation of humidity interference in colorimetric gas quantification was achieved in three steps. First, across a ten-dimensional variable space, an algorithm-driven high-throughput experimental robot discovered multiple local optimum regions where colorimetric humidity sensing formulations exhibited high evaluations on sensitivity, reversibility, response time, and color change extent for 10-90% relative humidity (RH) in room temperature (25 °C). Second, from the local optimum regions, 91 sensing formulations with diverse variables were selected to construct a parent colorimetric humidity sensor array as the sensor pool for humidity signal compensation. Third, the quasi-optimal sensor subarrays were identified as customized humidity signal compensation solutions for different gas sensing scenarios across an approximately full dynamic range of humidity (10-90% RH) using an ingenious combination optimization strategy, and two accurate quantitative detections were attained: one with a mean absolute percentage error (MAPE) reduction from 4.4 to 0.75% and the other from 5.48 to 1.37%. Moreover, the parent sensor array's excellent humidity selectivity was validated against 10 gases. This work demonstrates the feasibility and superiority of robot-assisted construction of a customizable parent colorimetric sensor array to mitigate humidity interference in gas quantification.

In this study, we describe a rapid and high-throughput smartphone-based digital colorimetric method for determining urea in milk. A compact and cost-effective 3D-printed image box microplate-based system was designed to measure multiple samples simultaneously, using minimal sample and reagent volumes. The apparatus was applied for the quantification of urea in milk based on its reaction with p -dimethylaminobenzaldehyde (DMAB). The predictive performance of calibration was evaluated using RGB and different colour models (CMYK, HSV, and CIELAB), with the average blue (B) values of the RGB selected as the analytical signal for urea quantification. Under optimized conditions, a urea concentration linear range from 50 to 400 mg L -1 was observed, with a limit of detection (LOD) of 15 mg L -1 . The values found with the smartphone-based DIC procedure are in good agreement with spectrophotometric (spectrophotometer and microplate treader) and reference method (mid-infrared spectroscopy) values. This proposed approach offers an accessible and efficient solution for digital image colorimetry, with potential applications for various target analytes in milk and other fields requiring high-throughput colorimetric analysis.

Chronic kidney disease (CKD) is a widespread condition with considerable health and economic impacts globally. However, existing methodologies for serum creatinine assessment often involve prolonged wait times and sophisticated equipment, such as spectrometers, hindering real-time diagnosis and care. Innovative solutions like point-of-care (POC) devices are emerging to address these challenges. In this context, there is a recognized need for remote, regular, automated, and low-cost analysis of serum creatinine levels, given its role as a critical parameter for CKD diagnosis and management. This study introduces a miniaturized system with integrated heater elements designed for precise serum creatinine measurement. The system operates based on the Jaffe method and accurate serum creatinine measurement within a microreservoir chip. Smartphone-based image processing using the hue-saturation-value (HSV) color space was applied to captured images of microreservoirs. The creatinine analyses were conducted in serum with a limit of detection of ~ 0.4 mg/dL and limit of quantification of ~ 1.3 mg/dL. Smartphone-based image processing employing the HSV color space outperformed spectrometric analysis for creatinine measurement conducted in serum. This pioneering technology and smartphone-based processing offer the potential for decentralized renal function testing, which could significantly contribute to improved patient care. The miniaturized system offers a low-cost alternative ($87 per device), potentially reducing healthcare expenditures (~ $0.5 per test) associated with CKD diagnosis and management. This innovation could greatly improve access to diagnosis and monitoring of CKD, especially in regions where access to sophisticated laboratory equipment is limited., (© 2024. The Author(s).)

Sensor array methods have received much attention in recent years. In this study, a colorimetric sensor array consisting of three kinds of steel slag-based composites (including porphyrin-functionalized non-magnetic steel slag (NMSS-Por), alkali-excited steel slag (A-SS), and platinum modified steel slag (ALANH-Pt)) was developed for the detection and recognition of tetracycline antibiotics (TCs) such as tetracycline (TC), oxytetracycline (OTC) and doxycycline (DOX). Linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA) showed that the colorimetric sensor array has excellent recognition ability for TCs. The detection limits of this sensor array for TC, OTC, and DOX were 0.059 μM, 0.111 μM and 0.118 μM, respectively, which provided higher sensitivity compared to the colorimetric sensors composed of a single steel slag-based composite material. At the same time, the array sensor has anti-interference ability, and this study provides a new application route for steel slag.

Foodborne pathogens have a substantial bearing on food safety and environmental health. The development of automated, portable and compact devices is essential for the on-site and rapid point-of-care testing (POCT) of bacteria. Here, this work developed a micro-automated microfluidic device for detecting bacteria, such as Escherichia coli (E. coli) O157:H7, using a seashell-like microfluidic chip (SMC) as an analysis and mixing platform. The automated device integrates a colorimetric/fluorescent system for the metabolism of copper (Cu 2+ ) by E. coli affecting o-phenylenediamine (OPD) for concentration analysis. A smartphone was used to read the RGB data of the chip reaction reservoir to detect colorimetric and fluorescence patterns in the concentration range of 10 2 -10 6  CFU mL -1 . The automated device overcomes the low efficiency and tedious steps of traditional detection and enables high-precision automated detection that can be applied to POCT in the field, providing an ideal solution for broadening the application of E. coli detection., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Intelligent colorimetric freshness indicator is a low-cost way to intuitively monitor the freshness of fresh food. A colorimetric strip sensor array was prepared by p -dimethylaminocinnamaldehyde (PDL)-doped poly(vinyl alcohol) (PVA) and chitosan (Chit) for the quantitative analysis of indole, which is an indicator of shrimp freshness. As a result of indole simulation, the array strip turned from faint yellow to pink or mulberry color with the increasing indole concentration, like a progress bar. The indicator film exhibited excellent permeability, mechanical and thermal stability, and color responsiveness to indole, which was attributed to the interactions between PDL and Chit/PVA. Furthermore, the colorimetric strip sensor array provided a good relationship between the indole concentration and the color intensity within a range of 50-350 ppb. The pathogens and spoilage bacteria of shrimp possessed the ability to produce indole, which caused the color changes of the strip sensor array. In the shrimp freshness monitoring experiment, the color-changing progress of the strip sensor array was in agreement with the simulation and could distinguish the shrimp freshness levels. The image classification system based on deep learning were developed, the accuracies of four DCNN algorithms are above 90%, with VGG16 achieving the highest accuracy at 97.89%. Consequently, a "progress bar" strip sensor array has the potential to realize nondestructive, more precise, and commercially available food freshness monitoring using simple visual inspection and intelligent equipment identification.

Hyperuricemia (HUA) has gradually become a public health burden as an independent risk factor for a variety of chronic diseases. Herein, a user-friendly point-of-care (POC) detection system (namely "Smart-HUA-Monitor") based on smartphone-assisted paper-based microfluidic is proposed for colorimetric quantification of HUA urinary markers, including uric acid (UA), creatinine (CR) and pH. The detection limits of UA and CR were 0.0178 and 0.5983 mM, respectively, and the sensitivity of pH were 0.1. The method was successfully validated in artificial urine samples and 100 clinical samples. Bland-Altman plots showed a high consistency between μPAD and the testing instruments (HITACHI 7600 Automatic Analyzer, URIT-500B Urine Analyzer and AU5800B automatic biochemical analyzer) in hospital. Smart-HUA-Monitor provides an accurate quantitative, rapid, low-cost and reliable tool for the monitoring and early diagnosis of HUA urine indicators., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: The monkeypox virus (MPXV) is a linear double-stranded DNA virus with a large genome that causes tens of thousands of infections and hundreds of deaths in at least 40 countries and regions worldwide. Therefore, timely and accurate diagnostic testing could be an important measure to prevent the ongoing spread of MPXV and widespread epidemics., Results: Here, we designed multiple sets of primers for the target region of MPXV for loop-mediated isothermal amplification (LAMP) detection and identified the optimal primer set. Then, the specificity in fluorescent LAMP detection was verified using the plasmids containing the target gene, pseudovirus and other DNA/RNA viruses. We also evaluated the sensitivity of the colorimetric LAMP detection system using the plasmid and pseudovirus samples, respectively. Besides, we used monkeypox pseudovirus to simulate real samples for detection. Subsequent to the establishment and introduction of a magnetic beads (MBs)-based nucleic acid extraction technique, an integrated device was developed, characterized by rapidity, high sensitivity, and remarkable specificity. This portable system demonstrated a visual detection limit of 137 copies/mL, achieving sample-to-answer detection within 1 h., Significance: The device has the advantages of integration, simplicity, miniaturization, and visualization, which help promote the realization of accurate, rapid, portable, and low-cost testing. Meanwhile, this platform could facilitate efficient, cost-effective and easy-operable point-of-care testing (POCT) in diverse resource-limited settings in addition to the laboratory., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)