Colorimetric sensing for translational applications: from colorants to mechanisms.

Colorimetric sensing offers instant reporting via visible signals. Versus labor-intensive and instrument-dependent detection methods, colorimetric sensors present advantages including short acquisition time, high throughput screening, low cost, portability, and a user-friendly approach. These advantages have driven substantial growth in colorimetric sensors, particularly in point-of-care (POC) diagnostics. Rapid progress in nanotechnology, materials science, microfluidics technology, biomarker discovery, digital technology, and signal pattern analysis has led to a variety of colorimetric reagents and detection mechanisms, which are fundamental to advance colorimetric sensing applications. This review first summarizes the basic components (e.g., color reagents, recognition interactions, and sampling procedures) in the design of a colorimetric sensing system. It then presents the rationale design and typical examples of POC devices, e.g., lateral flow devices, microfluidic paper-based analytical devices, and wearable sensing devices. Two highlighted colorimetric formats are discussed: combinational and activatable systems based on the sensor-array and lock-and-key mechanisms, respectively. Case discussions in colorimetric assays are organized by the analyte identities. Finally, the review presents challenges and perspectives for the design and development of colorimetric detection schemes as well as applications. The goal of this review is to provide a foundational resource for developing colorimetric systems and underscoring the colorants and mechanisms that facilitate the continuing evolution of POC sensors.

Decoding early stress signaling waves in living plants using nanosensor multiplexing.

Increased exposure to environmental stresses due to climate change have adversely affected plant growth and productivity. Upon stress, plants activate a signaling cascade, involving multiple molecules like H2O2, and plant hormones such as salicylic acid (SA) leading to resistance or stress adaptation. However, the temporal ordering and composition of the resulting cascade remains largely unknown. In this study we developed a nanosensor for SA and multiplexed it with H2O2 nanosensor for simultaneous monitoring of stress-induced H2O2 and SA signals when Brassica rapa subsp. Chinensis (Pak choi) plants were subjected to distinct stress treatments, namely light, heat, pathogen stress and mechanical wounding. Nanosensors reported distinct dynamics and temporal wave characteristics of H2O2 and SA generation for each stress. Based on these temporal insights, we have formulated a biochemical kinetic model that suggests the early H2O2 waveform encodes information specific to each stress type. These results demonstrate that sensor multiplexing can reveal stress signaling mechanisms in plants, aiding in developing climate-resilient crops and pre-symptomatic stress diagnoses.

Single-Molecule Methane Sensing Using Palladium-Functionalized nIR Fluorescent Single-Walled Carbon Nanotubes.

There has been considerable interest in detecting atmospheric and process-associated methane (CH4) at low concentrations due to its potency as a greenhouse gas. Nanosensor technology, particularly fluorescent single-walled carbon nanotube (SWCNT) arrays, is promising for such applications because of their chemical sensitivities at single-molecule detection limits. However, the methodologies for connecting the stochastic molecular fluctuations from gas impingement on such sensors require further development. In this work, we synthesize Pd-conjugated ss(GT)15-DNA-wrapped SWCNTas near-infrared (nIR) fluorescent, single-molecule sensors of CH4. The complexes are characterized using X-ray photoelectron spectroscopy (XPS) and spectrophotometry, demonstrating spectral changes between the Pd2+ and Pd0 oxidation states. The nIR fluctuations generated upon exposure from 8 to 26 ppb of CH4 were separated into high- and low-frequency components. Aggregating the low-frequency components for an array of sensors showed the most consistent levels of detection with a limit of 0.7 ppb. These results advance the hardware and computational methods necessary to apply this approach to the challenge of environmental methane sensing.

In Silico Investigation of the Clinical Translatability of Competitive Clearance Glucose-Responsive Insulins.

The glucose-responsive insulin (GRI) MK-2640 from Merck was a pioneer in its class to enter the clinical stage, having demonstrated promising responsiveness in in vitro and preclinical studies via a novel competitive clearance mechanism (CCM). The smaller pharmacokinetic response in humans motivates the development of new predictive, computational tools that can improve the design of therapeutics such as GRIs. Herein, we develop and use a new computational model, IM3PACT, based on the intersection of human and animal model glucoregulatory systems, to investigate the clinical translatability of CCM GRIs based on existing preclinical and clinical data of MK-2640 and regular human insulin (RHI). Simulated multi-glycemic clamps not only validated the earlier hypothesis of insufficient glucose-responsive clearance capacity in humans but also uncovered an equally important mismatch between the in vivo competitiveness profile and the physiological glycemic range, which was not observed in animals. Removing the inter-species gap increases the glucose-dependent GRI clearance from 13.0% to beyond 20% for humans and up to 33.3% when both factors were corrected. The intrinsic clearance rate, potency, and distribution volume did not apparently compromise the translation. The analysis also confirms a responsive pharmacokinetics local to the liver. By scanning a large design space for CCM GRIs, we found that the mannose receptor physiology in humans remains limiting even for the most optimally designed candidate. Overall, we show that this computational approach is able to extract quantitative and mechanistic information of value from a posteriori analysis of preclinical and clinical data to assist future therapeutic discovery and development.

Colloidal robotics.

Robots have components that work together to accomplish a task. Colloids are particles, usually less than 100 µm, that are small enough that they do not settle out of solution. Colloidal robots are particles capable of functions such as sensing, computation, communication, locomotion and energy management that are all controlled by the particle itself. Their design and synthesis is an emerging area of interdisciplinary research drawing from materials science, colloid science, self-assembly, robophysics and control theory. Many colloidal robot systems approach synthetic versions of biological cells in autonomy and may find ultimate utility in bringing these specialized functions to previously inaccessible locations. This Perspective examines the emerging literature and highlights certain design principles and strategies towards the realization of colloidal robots.

Rational Design and Efficacy of Glucose-Responsive Insulin Therapeutics and Insulin Delivery Systems by Computation Using Connected Human and Rodent Models.

Glucose-responsive insulins (GRIs) use plasma glucose levels in a diabetic patient to activate a specifically designed insulin analogue to a more potent state in real time. Alternatively, some GRI concepts use glucose-mediated release or injection of insulin into the bloodstream. GRIs hold promise to exhibit much improved pharmacological control of the plasma glucose concentration, particularly for the problem of therapeutically induced hypoglycemia. Several innovative GRI schemes are introduced into the literature, but there remains a dearth of quantitative analysis to aid the development and optimization of these constructs into effective therapeutics. This work evaluates several classes of GRIs that are proposed using a pharmacokinetic model as previously described, PAMERAH, simulating the glucoregulatory system of humans and rodents. GRI concepts are grouped into three mechanistic classes: 1) intrinsic GRIs, 2) glucose-responsive particles, and 3) glucose-responsive devices. Each class is analyzed for optimal designs that maintain glucose levels within the euglycemic range. These derived GRI parameter spaces are then compared between rodents and humans, providing the differences in clinical translation success for each candidate. This work demonstrates a computational framework to evaluate the potential clinical translatability of existing glucose-responsive systems, providing a useful approach for future GRI development.

Wearable sensors for monitoring marine environments and their inhabitants.

Human societies depend on marine ecosystems, but their degradation continues. Toward mitigating this decline, new and more effective ways to precisely measure the status and condition of marine environments are needed alongside existing rebuilding strategies. Here, we provide an overview of how sensors and wearable technology developed for humans could be adapted to improve marine monitoring. We describe barriers that have slowed the transition of this technology from land to sea, update on the developments in sensors to advance ocean observation and advocate for more widespread use of wearables on marine organisms in the wild and in aquaculture. We propose that large-scale use of wearables could facilitate the concept of an 'internet of marine life' that might contribute to a more robust and effective observation system for the oceans and commercial aquaculture operations. These observations may aid in rationalizing strategies toward conservation and restoration of marine communities and habitats.

Single-Crystal 2D Covalent Organic Frameworks for Plant Biotechnology.

Molecules chemically synthesized as periodic two-dimensional (2D) frameworks via covalent bonds can form some of the highest-surface area and -charge density particles possible. There is significant potential for applications such as nanocarriers in life sciences if biocompatibility can be achieved; however, significant synthetic challenges remain in avoiding kinetic traps from disordered linking during 2D polymerization of compatible monomers, resulting in isotropic polycrystals without a long-range order. Here, we establish thermodynamic control over dynamic control on the 2D polymerization process of biocompatible imine monomers by minimizing the surface energy of nuclei. As a result, polycrystal, mesocrystal, and single-crystal 2D covalent organic frameworks (COFs) are obtained. We achieve COF single crystals by exfoliation and minification methods, forming high-surface area nanoflakes that can be dispersed in aqueous medium with biocompatible cationic polymers. We find that these 2D COF nanoflakes with high surface area are excellent plant cell nanocarriers that can load bioactive cargos, such as the plant hormone abscisic acid (ABA) via electrostatic attraction, and deliver them into the cytoplasm of intact living plants, traversing through the cell wall and cell membrane due to their 2D geometry. This synthetic route to high-surface area COF nanoflakes has promise for life science applications including plant biotechnology.

In-Vivo fluorescent nanosensor implants based on hydrogel-encapsulation: investigating the inflammation and the foreign-body response.

Nanotechnology-enabled sensors or nanosensors are emerging as promising new tools for various in-vivo life science applications such as biosensing, components of delivery systems, and probes for spatial bioimaging. However, as with a wide range of synthetic biomaterials, tissue responses have been observed depending on cell types and various nanocomponent properties. The tissue response is critical for determining the acute and long term health of the organism and the functional lifetime of the material in-vivo. While nanomaterial properties can contribute significantly to the tissue response, it may be possible to circumvent adverse reactions by formulation of the encapsulation vehicle. In this study, five formulations of poly (ethylene glycol) diacrylate (PEGDA) hydrogel-encapsulated fluorescent nanosensors were implanted into SKH-1E mice, and the inflammatory responses were tracked in order to determine the favorable design rules for hydrogel encapsulation and minimization of such responses. Hydrogels with higher crosslinking density were found to allow faster resolution of acute inflammation. Five different immunocompromised mice lines were utilized for comparison across different inflammatory cell populations and responses. Degradation products of the gels were also characterized. Finally, the importance of the tissue response in determining functional lifetime was demonstrated by measuring the time-dependent nanosensor deactivation following implantation into animal models.

Design of Biodegradable, Climate-Specific Packaging Materials That Sense Food Spoilage and Extend Shelf Life.

The AgriFood systems in tropical climates are under strain due to a rapid increase in human population and extreme environmental conditions that limit the efficacy of packaging technologies to extend food shelf life and guarantee food safety. To address these challenges, we rationally designed biodegradable packaging materials that sense spoilage and prevent molding. We nanofabricated the interface of 2D covalent organic frameworks (COFs) to reinforce silk fibroin (SF) and obtain biodegradable membranes with augmented mechanical properties and that displayed an immediate colorimetric response (within 1 s) to food spoilage, using packaged poultry as an example. Loading COF with antimicrobial hexanal also mitigated biotic spoilage in high-temperature and -humidity conditions, resulting in a four-order of magnitude decrease in the total amount of mold growth in soybeans packaged in silk-COF, when compared to cling film (i.e., polyethylene). Together, the integration of sensing, structural reinforcement, and antimicrobial agent delivery within a biodegradable nanocomposite framework defines climate-specific packaging materials that can decrease food waste and enhance food safety.

Fluids and Electrolytes under Confinement in Single-Digit Nanopores.

Confined fluids and electrolyte solutions in nanopores exhibit rich and surprising physics and chemistry that impact the mass transport and energy efficiency in many important natural systems and industrial applications. Existing theories often fail to predict the exotic effects observed in the narrowest of such pores, called single-digit nanopores (SDNs), which have diameters or conduit widths of less than 10 nm, and have only recently become accessible for experimental measurements. What SDNs reveal has been surprising, including a rapidly increasing number of examples such as extraordinarily fast water transport, distorted fluid-phase boundaries, strong ion-correlation and quantum effects, and dielectric anomalies that are not observed in larger pores. Exploiting these effects presents myriad opportunities in both basic and applied research that stand to impact a host of new technologies at the water-energy nexus, from new membranes for precise separations and water purification to new gas permeable materials for water electrolyzers and energy-storage devices. SDNs also present unique opportunities to achieve ultrasensitive and selective chemical sensing at the single-ion and single-molecule limit. In this review article, we summarize the progress on nanofluidics of SDNs, with a focus on the confinement effects that arise in these extremely narrow nanopores. The recent development of precision model systems, transformative experimental tools, and multiscale theories that have played enabling roles in advancing this frontier are reviewed. We also identify new knowledge gaps in our understanding of nanofluidic transport and provide an outlook for the future challenges and opportunities at this rapidly advancing frontier.

Investigations of Vacancy-Assisted Selective Detection of NO2 Molecules in Vertically Aligned SnS2.

Two important methods for enhancing gas sensing performance are vacancy/defect and interlayer engineering. Tin sulfide (SnS2) has recently attracted much attention for sensing of the NO2 gas due to its active surface sites and tunable electronic structure. Herein, SnS2 has been synthesized by the chemical vapor deposition (CVD) method followed by nitrogen plasma treatment with different exposure times for fast detection of NO2 molecules. Plasma treatment created a substantial number of surface vacancies on SnS2 flakes, which were controlled by the exposure period to modify the surface of flakes. After 12 min of nitrogen plasma treatment, SnS2 nanoflakes show considerable improvement in NO2 sensing characteristics, including a high sensing response of ∼264% toward 100 ppm NO2 at 120°C. The enhancement in the relative response of the sensor is due to the electronic interaction between NO2 molecules and the S vacancies on the surface of SnS2. Density functional theory (DFT) computations indicate that the S-vacancy defects on the surface dominate the effective NO2 detection and the NO2 adsorption mechanism transition from physisorption to chemisorption. Adsorption kinetics of the NO2 gas over SnS2 nanoflake-based chemiresistor sensors were studied using the Lee and Strano model [ Langmuir 2005, 21(11), 5192-5196]. The irreversible rate of the reaction for various NO2 concentrations exposed to the gas sensor is extracted using this model, which also appropriately describes the response curves. The forward rate constant of the irreversible gas sensor increased with the increase of the N2 plasma treatment time and reached the maximum in the 12 min plasma-treated sample. Through defect engineering, this research may open up new vistas for the design and synthesis of 2D materials with enhanced sensing properties.

Observation and Isochoric Thermodynamic Analysis of Partially Water-Filled 1.32 and 1.45 nm Diameter Carbon Nanotubes.

Recent measurements of fluids under extreme confinement, including water within narrow carbon nanotubes, exhibit marked deviations from continuum theoretical descriptions. In this work, we generate precise carbon nanotube replicates that are filled with water, closed from external mass transfer, and studied over a wide temperature range by Raman spectroscopy. We study segments that are empty, partially filled, and completely filled with condensed water from -80 to 120 °C. Partially filled, nanodroplet states contain submicron vapor-like and liquid-like domains and are analyzed using a Clausius-Clapeyron-type model, yielding heats of condensation of water inside closed 1.32 nm diameter carbon nanotubes (3.32 ± 0.10 kJ/mol and 3.72 ± 0.11 kJ/mol) and 1.45 nm diameter carbon nanotubes (3.50 ± 0.07 kJ/mol) that are lower than the bulk enthalpy of vaporization and closer to the bulk enthalpy of fusion. Favored partial filling fractions are calculated, highlighting the effect of subnanometer changes in confining diameter on fluid properties and suggesting the promise of molecular engineering of nanoconfined liquid/vapor interfaces for water treatment or membrane distillation.

Discretized hexagonal boron nitride quantum emitters and their chemical interconversion.

Quantum emitters in two-dimensional hexagonal boron nitride (hBN) are of significant interest because of their unique photophysical properties, such as single-photon emission at room temperature, and promising applications in quantum computing and communications. The photoemission from hBN defects covers a wide range of emission energies but identifying and modulating the properties of specific emitters remain challenging due to uncontrolled formation of hBN defects. In this study, more than 2000 spectra are collected consisting of single, isolated zero-phonon lines (ZPLs) between 1.59 and 2.25 eV from diverse sample types. Most of ZPLs are organized into seven discretized emission energies. All emitters exhibit a range of lifetimes from 1 to 6 ns, and phonon sidebands offset by the dominant lattice phonon in hBN near 1370 cm-1. Two chemical processing schemes are developed based on water and boric acid etching that generate or preferentially interconvert specific emitters, respectively. The identification and chemical interconversion of these discretized emitters should significantly advance the understanding of solid-state chemistry and photophysics of hBN quantum emission.

Near-Infrared Fluorescent Carbon Nanotube Sensors for the Plant Hormone Family Gibberellins.

Gibberellins (GAs) are a class of phytohormones, important for plant growth, and very difficult to distinguish because of their similarity in chemical structures. Herein, we develop the first nanosensors for GAs by designing and engineering polymer-wrapped single-walled carbon nanotubes (SWNTs) with unique corona phases that selectively bind to bioactive GAs, GA3 and GA4, triggering near-infrared (NIR) fluorescence intensity changes. Using a new coupled Raman/NIR fluorimeter that enables self-referencing of nanosensor NIR fluorescence with its Raman G-band, we demonstrated detection of cellular GA in Arabidopsis, lettuce, and basil roots. The nanosensors reported increased endogenous GA levels in transgenic Arabidopsis mutants that overexpress GA and in emerging lateral roots. Our approach allows rapid spatiotemporal detection of GA across species. The reversible sensor captured the decreasing GA levels in salt-treated lettuce roots, which correlated remarkably with fresh weight changes. This work demonstrates the potential for nanosensors to solve longstanding problems in plant biotechnology.

Molecular Recognition and In Vivo Detection of Temozolomide and 5-Aminoimidazole-4-carboxamide for Glioblastoma Using Near-Infrared Fluorescent Carbon Nanotube Sensors.

There is a pressing need for sensors and assays to monitor chemotherapeutic activity within the human body in real time to optimize drug dosimetry parameters such as timing, quantity, and frequency in an effort to maximize efficacy while minimizing deleterious cytotoxicity. Herein, we develop near-infrared fluorescent nanosensors based on single walled carbon nanotubes for the chemotherapeutic Temozolomide (TMZ) and its metabolite 5-aminoimidazole-4-carboxamide using Corona Phase Molecular Recognition as a synthetic molecular recognition technique. The resulting nanoparticle sensors are able to monitor drug activity in real-time even under in vivo conditions. Sensors can be engineered to be biocompatible by encapsulation in poly(ethylene glycol) diacrylate hydrogels. Selective detection of TMZ was demonstrated using U-87 MG human glioblastoma cells and SKH-1E mice with detection limits below 30 µM. As sensor implants, we show that such systems can provide spatiotemporal therapeutic information in vivo, as a valuable tool for pharmacokinetic evaluation. Sensor implants are also evaluated using intact porcine brain tissue implanted 2.1 cm below the cranium and monitored using a recently developed Wavelength-Induced Frequency Filtering technique. Additionally, we show that by taking the measurement of spatial and temporal analyte concentrations within each hydrogel implant, the direction of therapeutic flux can be resolved. In all, these types of sensors enable the real time detection of chemotherapeutic concentration, flux, directional transport, and metabolic activity, providing crucial information regarding therapeutic effectiveness.

A theory of mechanical stress-induced H2O2 signaling waveforms in Planta.

Recent progress in nanotechnology-enabled sensors that can be placed inside of living plants has shown that it is possible to relay and record real-time chemical signaling stimulated by various abiotic and biotic stresses. The mathematical form of the resulting local reactive oxygen species (ROS) wave released upon mechanical perturbation of plant leaves appears to be conserved across a large number of species, and produces a distinct waveform from other stresses including light, heat and pathogen-associated molecular pattern (PAMP)-induced stresses. Herein, we develop a quantitative theory of the local ROS signaling waveform resulting from mechanical stress in planta. We show that nonlinear, autocatalytic production and Fickian diffusion of H2O2 followed by first order decay well describes the spatial and temporal properties of the waveform. The reaction-diffusion system is analyzed in terms of a new approximate solution that we introduce for such problems based on a single term logistic function ansatz. The theory is able to describe experimental ROS waveforms and degradation dynamics such that species-dependent dimensionless wave velocities are revealed, corresponding to subtle changes in higher moments of the waveform through an apparently conserved signaling mechanism overall. This theory has utility in potentially decoding other stress signaling waveforms for light, heat and PAMP-induced stresses that are similarly under investigation. The approximate solution may also find use in applied agricultural sensing, facilitating the connection between measured waveform and plant physiology.

Divalent Metal Cation Optical Sensing Using Single-Walled Carbon Nanotube Corona Phase Molecular Recognition.

Colloidal single-walled carbon nanotubes (SWCNTs) offer a promising platform for the nanoscale engineering of molecular recognition. Optical sensors have been recently designed through the modification of noncovalent corona phases (CPs) of SWCNTs through a phenomenon known as corona phase molecular recognition (CoPhMoRe). In CoPhMoRe constructs, DNA CPs are of great interest due to the breadth of the design space and our ability to control these molecules with sequence specificity at scale. Utilizing these constructs for metal ion sensing is a natural extension of this technology due to DNA's well-known coordination chemistry. Additionally, understanding metal ion interactions of these constructs allows for improved sensor design for use in complex aqueous environments. In this work, we study the interactions between a panel of 9 dilute divalent metal cations and 35 DNA CPs under the most controlled experimental conditions for SWCNT optical sensing to date. We found that best practices for the study of colloidal SWCNT analyte responses involve mitigating the effects of ionic strength, dilution kinetics, laser power, and analyte response kinetics. We also discover that SWCNT with DNA CPs generally offers two unique sensing states at pH 6 and 8. The combined set of sensors in this work allowed for the differentiation of Hg2+, Pb2+, Cr2+, and Mn2+. Finally, we implemented Hg2+ sensing in the context of portable detection within fish tissue extract, demonstrating nanomolar level detection.

Emergent microrobotic oscillators via asymmetry-induced order.

Spontaneous oscillations on the order of several hertz are the drivers of many crucial processes in nature. From bacterial swimming to mammal gaits, converting static energy inputs into slowly oscillating power is key to the autonomy of organisms across scales. However, the fabrication of slow micrometre-scale oscillators remains a major roadblock towards fully-autonomous microrobots. Here, we study a low-frequency oscillator that emerges from a collective of active microparticles at the air-liquid interface of a hydrogen peroxide drop. Their interactions transduce ambient chemical energy into periodic mechanical motion and on-board electrical currents. Surprisingly, these oscillations persist at larger ensemble sizes only when a particle with modified reactivity is added to intentionally break permutation symmetry. We explain such emergent order through the discovery of a thermodynamic mechanism for asymmetry-induced order. The on-board power harvested from the stabilised oscillations enables the use of electronic components, which we demonstrate by cyclically and synchronously driving a microrobotic arm. This work highlights a new strategy for achieving low-frequency oscillations at the microscale, paving the way for future microrobotic autonomy.

Universal Kinetic Mechanism Describing CO2 Photoreductive Yield and Selectivity for Semiconducting Nanoparticle Photocatalysts.

Photocatalytic conversion of CO2 to generate high-value and renewable chemical fuels and feedstock presents a sustainable and renewable alternative to fossil fuels and petrochemicals. Currently, there is a dearth of kinetic understanding to inform better catalyst design, especially at uniform reaction conditions across diverse catalytic species. In this work, we investigate 12 active, stable, and unique but common nanoparticle photocatalysts for CO2 reduction at room temperature and low partial pressure in aqueous phase: TiO2, SnO2, and SiC deposited with silver, gold, and platinum. Our analysis reveals a single consistent chemical kinetic mechanism, which accurately describes the yield and selectivity of all single-carbon containing (C1) products obtained in spite of the diverse catalysts employed. Formaldehyde is predicted as the first product in the reaction network and we report, to the best of our knowledge, the highest selectivity to date toward formaldehyde during CO2 photoreduction when compared against all other C1 products (∼80%) albeit at low CO2 conversion (<0.5 µmol gcat-1 h-1, <16.8 nmol m-2 h-1). Further, we observe a volcano-like relationship between the electron-transfer rate of a given photocatalyst for CO2 reduction and the net rate at which reduced products are produced in the reaction mixture taking into account unfavorable product oxidation. We establish an empirical upper limit for the maximum rate of production of CO2 reduction products for any nanoparticle photocatalyst in the absence of a hole-scavenging agent. These results form the basis for the design and optimization of the next generation of highly efficiency and active photocatalysts for CO2 reduction.