Efficient and reliable technologies for the on-site detection of illicit drugs are important in drug-facilitated crime investigations. However, the development of such technologies is challenging. Based on the synthetic optimization, introducing a boron ester functional group to the two furanic indicators endows the stimulus-responsive properties synergistically. The ring-opening reaction of the indicators in the presence of amine-containing illicit drugs generated well-known donor-acceptor Stenhouse adducts, accompanied by strong color changes. A small-size and lightweight laminated sensor was integrated based on the outstanding ratiometric variations of the two active furanic indicators. A prototype platform was fabricated equipped with a circuit control, a mini pump, and a signal processing system. A user-friendly detection and efficient screening of amine-containing illicit drugs, including phenethylamines, amphetamines, cathinones, and tryptamines in the liquid states were conducted. The ratiometric response of the sensor was linear in the concentration range of 2.1-10.6 μg·mL-1 for methamphetamine·HCl and methcathinone ·HCl. The detection limits for the two illicit drugs at the sublevel (ng·mL-1) were found to be 8.4 and 9.0 ng·mL-1, respectively. Double-blind field tests and different illicit drugs were evaluated with good screening capability. Successful trials showed the potential applications of the developed prototype platform for efficient and on-site analytical determination.

In the past decade, there have been various advancements to colorimetric sensors to improve their potential applications in food and agriculture. One application of growing interest is sensing foodborne pathogens. There are unique considerations for sensing in the food industry, including food sample destruction, specificity amidst a complex food matrix, and high sensitivity requirements. Incorporating novel technology, such as nanotechnology, microfluidics, and smartphone app development, into colorimetric sensing methodology can enhance sensor performance. Nonetheless, there remain challenges to integrating sensors with existing food safety infrastructure. Recently, increasingly advanced machine learning techniques have been employed to facilitate nondestructive, multiplex detection for feasible assimilation of sensors into the food industry. With its ability to analyze and make predictions from highly complex data, machine learning holds potential for advanced yet practical colorimetric sensing of foodborne pathogens. This article summarizes recent developments and hurdles of machine learning-enabled colorimetric foodborne pathogen sensing. These advancements underscore the potential of interdisciplinary, cutting-edge technology in providing safer and more efficient food systems.

Arsenic, existing in various chemical forms such as arsenate (As(V)) and arsenite (As(III)), demands serious attention in water and environmental contexts due to its significant health risks. It is classified as \"carcinogenic to humans\" by the International Agency for Research on Cancer (IARC) and is listed by the World Health Organization (WHO) as one of the top 10 chemicals posing major public health concerns. This widespread contamination results in millions of people globally being exposed to dangerous levels of arsenic, making it a top priority for the WHO. Chronic arsenic toxicity, known as arsenicosis, presents with specific skin lesions like pigmentation and keratosis, along with systemic manifestations including chronic lung diseases, liver issues, vascular problems, hypertension, diabetes mellitus, and cancer, often leading to fatal outcomes. Therefore, it is crucial to explore novel, cost-effective, and reliable methods with rapid response and improved sensitivities (detection limits). Most of the traditional detection techniques often face limitations in terms of complexity, cost, and the need for sophisticated equipment requiring skilled analysts and procedures, which thereby impedes their practical use, particularly in resource-constrained settings. Colorimetric methods leverage colour changes which are observable and quantifiable using simple instrumentation or even visual inspection. This review explores the colorimetric techniques designed to detect arsenite and arsenate in water. It covers recent developments in colorimetric techniques, and advancements in the role of nanomaterials in colorimetric arsenic detection, followed by discussion on current challenges and future prospects. The review emphasizes efforts to improve sensitivity, selectivity, cost, and portability, as well as the role of advanced materials/nanomaterials to boost the performance of colorimetric assays/sensors towards combatting this pervasive global health concern.

Remote health monitoring and treatment serve as critical drivers for advancing health equity, bridging geographical and socioeconomic disparities, ensuring equitable access to quality healthcare for those in underserved or remote regions. By democratizing healthcare, this approach offers timely interventions, continuous monitoring, and personalized care independent of one\'s location or socioeconomic status, thereby striving for an equitable distribution of health resources and outcomes. Meanwhile, microneedle arrays (MNAs), revolutionize painless and minimally invasive access to interstitial fluid for drug delivery and diagnostics. This paper introduces an integrated theranostic MNA system employing an array of colorimetric sensors to quantitatively measure -pH, glucose, and lactate, alongside a remotely-triggered system enabling on-demand drug delivery. Integration of an ultrasonic atomizer streamlines the drug delivery, facilitating rapid, pumpless, and point-of-care drug delivery, enhancing system portability while reducing complexities. An accompanying smartphone application interfaces the sensing and drug delivery components. Demonstrated capabilities include detecting pH (3 to 8), glucose (up to 16 mm), and lactate (up to 1.6 mm), showcasing on-demand drug delivery, and assessing delivery system performance via a scratch assay. This innovative approach confronts drug delivery challenges, particularly in managing chronic diseases requiring long-term treatment, while also offering avenues for non-invasive health monitoring through microneedle-based sensors.

Frequent blood glucose monitoring is a crucial routine for diabetic patients. Traditional invasive methods can cause discomfort and pain and even pose a risk of infection. As a result, researchers have been exploring noninvasive techniques. However, a limited number of products have been developed for the market due to their high cost. In this study, we developed a low-cost, highly accessible, and noninvasive contact lens-based glucose monitoring system. We functionalized the surface of the contact lens with boronic acid, which has a strong but reversible binding affinity to glucose. To achieve facile conjugation of boronic acid, we utilized a functional coating layer called poly(tannic acid). The functionalized contact lens binds to glucose in body fluids (e.g., tear) and releases it when soaked in an enzymatic cocktail, allowing for the glucose level to be quantified through a colorimetric assay. Importantly, the transparency and oxygen permeability of the contact lens, which are crucial for practical use, were maintained after functionalization, and the lenses showed high biocompatibility. Based on the analysis of colorimetric data generated by the smartphone application and ultraviolet-visible (UV-vis) spectra, we believe that this contact lens has a high potential to be used as a smart diagnostic tool for monitoring and managing blood glucose levels.

To address the relatively low sensitivity of current redox reagent-mediated magnetic relaxation sensing methods, we present a novel Ag+-mediated magnetic sensing platform that enhances the sensitivity by three orders of magnitude. The new sensing platform is based on Ag+-catalyzed oxidation of Mn2+ to KMnO4, accompanied by a distinct color change, which facilitates colorimetric detection. In the case of insufficient Ag+ ions, MnO2 is an additional oxidation product and the KMnO4/MnO2 ratio is dependent on the concentration of Ag+. When combined with a specific quantity of reducing agent, both KMnO4 and MnO2 are reduced to Mn2+ with a large relaxivity, and the concentration of Mn2+ in the resultant solution inversely correlates with the amount of KMnO4 since KMnO4 consumes more reductant during reduction. Consequently, the transverse relaxation rate of the solution exhibits a negative correlation with the Ag+ concentration. Thus, by coupling this Ag+-mediated Mn2+ to KMnO4 transformation with reactions that modulate Ag+ concentration, a dual-mode sensing platform for magnetic relaxation and colorimetry can be realized. Herein, we take H2O2 as an example to verify the detection performance of this sensing platform since H2O2 can oxidize Ag0 in Ag@Fe3O4 nanoparticles to Ag+. Experimental findings demonstrate detection limits of 10 nM and 20 nM for the magnetic relaxation and colorimetry modes, respectively, affirming the excellent sensitivity and the potential practical application of this strategy.

As a popular nutritional enhancer, casein phosphopeptides (CPPs) have attracted growing attention in food industry. However, conventional methods for CPPs detection are usually less precise or requires expensive instruments. Herein, a nanozyme-based colorimetric method was developed to achieve the quantitative detection of CPPs in food samples. This method is based on a facilely fabricated peroxidase-like nanozyme (Fe@UiO-66), which combines the specific binding of CPPs, as well as the nanozyme-catalyzed colorimetric sensing that can be easily detected by spectrometer. The method displayed good quantitative ability toward CPPs with the linear range of 2-30 μg/mL, the low limit of detection of 0.267 μg/mL and limit of quantification of 1.335 μg/mL. We highlighted the specificity, anti-interference and practicability of this method, by investigating the performances toward food samples. Besides, a smartphone-based colorimetric sensing platform was also established, which is conducive to the portable detection. The developed nanozyme-based colorimetric sensing method provides a promising strategy for CPPs detection in food samples.

Nanozyme-based colorimetric sensing has drawn immense attention due to the rapid development of nanozyme in recent years. However, the selectivity of nanozyme-based colorimetric sensing greatly limits its subsequent practical application. It is well known that sample pretreatment can not only improve selectivity by eliminating the sample matrix interference, but also improve sensitivity by enriching trace targets. Based on the easy facile surface modification properties of nanozyme, we rationally designed nanozyme combined with sample pretreatment for colorimetric biosensing, through separation and enrichment, thereby improving the selectivity and sensitivity of the nanozyme colorimetric biosensing. As a proof of concept, the detection of Hg2+ by nanozyme-based colorimetric sensing was used as an example. Magnetic peroxidase-like nanozyme Fe3S4 was designed and synthesized. The selectivity is improved by the specific adsorption of S-Hg bond and the interference elimination after magnetic separation. In addition, the sensitivity is improved by magnetic solid-phase extraction enrichment. Our established colorimetric sensing based on Fe3S4 nanozyme integrated sample pretreatment with an enrichment factor of 100 and the limit of detection (LOD) is 26 nM. In addition, this strategy was successfully applied to detect Hg2+ in environmental water samples. Overall, the strategy showed good selectivity and sensitivity, providing a new practical method for the application of nanozyme-based biosensing in sample pretreatment.

We present here the encapsulation of a spin crossover complex C1 [FeII(L)] (L: 4-amino-, 2-(2-pyridinylmethylene)hydrazide) inside MOF-808(Zr), a chemically robust Metal-Organic Framework. The compound C1⊂MOF-808 retains its crystallinity as well as a partial porosity compared to pristine MOF and shows solvatochromism under Volatile Organic compounds (VOCs) sorption associated to a spin state change of the guest complex. More specifically, this compound shows an interesting reversible color change under formaldehyde and formic acid vapor sorption and can therefore be considered as a new kind of optical VOCs chemosensor, opening new doors for developing a broad range of VOCs optical sensors.

In this study, a porous coordination network zirconium-porphyrin-based nanoparticle with oxygen vacancies (OVs) was prepared using acetic acid and benzoic acid as modulators via a simple hydrothermal method. The presence of OVs was confirmed by various characterization methods and was found to enhance oxygen uptake and activation. This resulted in the generation of more reactive peroxyl radicals (•O2 -) and led to an improved oxidase (OXD) mimetic activity. Additionally, it promoted 2,2\'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) oxidation, with a low Km value of 0.07 mM and a high Vmax of 1.47 × 10-7 M·s-1. As aflatoxin B1 (AFB1) inhibits the Pt@PCN-222-ABTS nanozyme system, a colorimetric probe for AFB1 detection was constructed. The limit of detection (LOD) was 0.074 µg·L-1. This research presents a novel approach for designing a nanozymatic-based colorimetric method to analyze trace AFB1 residues in food.