A facile way to construct sensor array library via supramolecular chemistry for discriminating complex systems

A novel quantum dot-based ratiometric fluorescence sensor array: For reducing substances detection and Baijiu quality discrimination

BACKGROUND

Discriminating the quality of baijiu is critical for fostering the growth of the China baijiu market and safeguarding customers' rights. However, establishing a small-scale and rapid baijiu discriminating sensor assay still remains a challenge.

RESULTS

Here, we first introduced ratiometric fluorescence sensor array for the detection of reducing substances in baijiu to achieve baijiu discrimination. A ratiometric fluorescence sensor array is built using 2,3-diaminophenazine (oxidized-state OPD, oxOPD) to quench three distinct fluorescence signals of quantum dots while reducing interference from background signals. The reducing chemicals in baijiu can react with Ag+, weakening the quenching effect and changing the ratio. The discriminating of 12 types of organic small molecules which were presented in baijiu was achieved with 97.2 % accuracy by using machine learning classification methods. Meanwhile, 0.1 μM limit of detection (LOD) for ascorbic acid shows that our methods have the potential to quantitative detect reducing substances. In real sample detection, our methods can discriminate 10 distinct qualities of baijiu with 100 % accuracy. We also encoded the fingerprints of different varieties of baijiu for quality control and information reading.

SIGNIFICANCE AND NOVELTY

Overall, our easy but robust sensing array not only overcomes the problem of background signal interference but also gives an ideal way for discriminating different qualities of baijiu, food and other areas.

Fluorometric detection and analog discrimination of melatonin by amide naphthotube-based indicator displacement assays

Melatonin, a hormone synthesized by the pineal gland, is renowned for its pivotal role in governing circadian rhythms and its promising therapeutic attributes encompassing anti-inflammatory, anti-aging, and cancer-preventative properties. Nevertheless, the improper utilization of melatonin may lead to health hazards, highlighting the critical necessity for accurate detection of melatonin in pharmaceutical or biological samples. Furthermore, melatonin metabolites exhibit analogous chemical structures yet divergent pathophysiological functions, emphasizing the significance of distinguishing between these analogs. In this study, we report a supramolecular sensor that combines amide naphthotube and toluidine blue O in an indicator displacement assay for the quantitative detection of melatonin and differentiation of its analogs. The sensor demonstrated remarkable sensitivity, with a low detection limit of approximately 0.70 μM, and a broad dynamic range of 0.70-98.8 μM, along with excellent selectivity and stability. Notably, the sensor enables the determination of melatonin levels in various sample matrices, including milk, artificial urine, and pharmaceutical preparations. Through optimization of the host-guest complex ratio, our newly designed sensor effectively distinguishes melatonin from its six analogs. This approach addresses a current research gap, as existing macrocycles have limited capability to differentiate between melatonin analogs, with only a few achieving precise melatonin quantification.

Fluorescent Fingerprint Identification of Protein Structural Changes and Disease-Specific Amyloid Beta Aggregates Based on a Single-Nanozyme Sensor Array

The misfolding of amyloid β (Aβ) peptides into an aggregation state is a central hallmark of the onset of Alzheimer's disease (AD). However, conventional methods are mainly focused on detecting a specific Aβ peptide, which makes it difficult to recognize multiple analytes with different topological features and unfolded states at the same time. Here, we propose a simple and universal sensing strategy to construct a fluorescence sensor array by using a single-nanozyme probe combined with three fluorescent substrates as three recognition units to probe the protein structural changes and identify between multiple Aβ assemblies. In this sensor system, the fingerprint-like patterns are produced from the nonspecific interactions between topological proteins and the sensing units. As a result, this sensor array can accurately identify 13 kinds of proteins and their mixtures at different ratios. Moreover, the sensor array can discriminate against proteins with unfolded states and diverse conformational forms. Most importantly, the sensor array successfully distinguishes between multiple Aβ species, even in artificial cerebrospinal fluid samples and human serum samples. This work provides an attractive and reliable strategy for predicting pathologically relevant proteins and clinical diagnosis of AD.

Combinatorial Library-Screened Array for Rapid Clinical Sperm Quality Assessment

Nonspecific interactions are ubiquitous and important in biology; however, they are rarely valued or employed in the field of clinical disease diagnosis. Relying on nonspecific cross-interactions, sensor arrays have shown great potential in distinguishing mixtures or nuanced compounds. However, developing generic strategies for constructing effective arrays tailored to compositionally complicated and highly individualized clinical biospecimens remains challenging. Here, we introduce a combinatorial chemistry-screened array strategy, leveraging four-component Ugi reactions to achieve the rapid synthesis of hundreds of structurally diverse sensing elements. Moreover, effective sensor arrays can thus be built by rapidly screening sensors against diverse analytes. Next, we demonstrate the practical applicability of this array by clinical sperm quality assessment, given the current lack of well-established clinical rapid detection techniques. A library of 192 structurally diverse sensor elements was synthesized. Following screening, a pruned 14-element array was successfully constructed, achieving 94.2% accuracy in distinguishing between healthy individuals and four types of abnormal sperm samples from patients within 1 min. This universal strategy avoids complex sensor design and greatly improves the efficiency of sensor array construction, offering a new way of designing effective arrays.

Optical biosensor arrays based on nanozymes for environmental monitoring and food safety detection: principles, design, and applications

Typical biosensing platforms are based on the "lock-and-key" approach, providing high specificity and sensitivity for environmental and food safety monitoring. However, they are limited in their ability to detect multiple analytes simultaneously. With the use of pattern identification methods, biosensor arrays can detect faint fluctuations caused by multiple analytes with similar properties in complex systems. As a simple and efficient detection tool, optical biosensor arrays have become crucial for on-site and visible environmental and food safety monitoring. To enhance their practical applications, enzyme-like nanomaterial (nanozyme)-based biosensor arrays have been developed and integrated into optical biosensing platforms, leveraging their exposed active sites and tunable catalytic capabilities. For the development of an optical biosensor array, it is essential to incorporate multiple biosensing elements that can specifically interact with analytes to produce distinct "fingerprint" signals, enabling the differentiation of different targets via pattern identification. This review provides a comprehensive overview of nanozyme-based optical biosensor arrays for environmental and food safety monitoring. It explores the selective approaches of nanozyme-based colorimetric and fluorescent biosensor arrays, compares detection platforms utilizing nanozyme systems, and emphasizes the application of nanozyme-based optical biosensor arrays for environmental and food hazard monitoring. By evaluating current trends and summarizing both prospects and challenges, this review offers valuable guidance for the rational design of unique nanozyme-based optical biosensor arrays.

A Mechanical Immune Checkpoint Inhibitor Stiffens Tumor Cells to Potentiate Antitumor Immunity

Tumor progression is associated with tumor-cell softening. Improving the stiffness of the tumor cells can make them more vulnerable to lymphocyte-mediated attack. Tumor cell membranes typically exhibit higher cholesterol levels than normal cells, making tumor cells soft. Herein, we demonstrate a mechanical immune checkpoint inhibitor (MICI) formulated by cyclodextrin (CD) lipids and fusogenic lipids. Through fusing CD lipids into the tumor cell membrane using a fusogenic liposome formulation, the cholesterol in the plasma membrane is reduced due to the specific host-guest interactions between CD lipid and cholesterol. As a result, tumor cells are stiffened, and the activation of lymphocytes (including NK and cytotoxic effector T cells) is improved when contacting the stiffened tumor cells, characterized by robust degranulation and effector cytokine production. Notably, this treatment has negligible influence on the infiltration and proliferation of lymphocytes in tumor tissues, confirming that the enhanced antitumor efficacy should result from activating a specific number of lymphocytes caused by direct regulation of the tumor cell stiffness. The combination of MICIs and clinical immunotherapies enhances the lymphocyte-mediated antitumor effects in two tumor mouse models, including breast cancer and melanoma. Our research also reveals an unappreciated mechanical dimension to lymphocyte activation.

Supramolecular discrimination and diagnosis-guided treatment of intracellular bacteria

Pathogenic intracellular bacteria pose a significant threat to global public health due to the barriers presented by host cells hindering the timely detection of hidden bacteria and the effective delivery of therapeutic agents. To address these challenges, we propose a tandem diagnosis-guided treatment paradigm. A supramolecular sensor array is developed for simple, rapid, accurate, and high-throughput identification of intracellular bacteria. This diagnostic approach executes the significant guiding missions of screening a customized host-guest drug delivery system by disclosing the rationale behind the discrimination. We design eight azocalix[4]arenes with differential active targeting, cellular internalization, and hypoxia responsiveness to penetrate cells and interact with bacteria. Loaded with fluorescent indicators, these azocalix[4]arenes form a sensor array capable of discriminating eight intracellular bacterial species without cell lysis or separation. By fingerprinting specimens collected from bacteria-infected mice, the facilitated accurate diagnosis offers valuable guidance for selecting appropriate antibiotics. Moreover, mannose-modified azocalix[4]arene (ManAC4A) is screened as a drug carrier efficiently taken up by macrophages. Doxycycline loaded with ManAC4A exhibits improved efficacy against methicillin-resistant Staphylococcus aureus-infected peritonitis. This study introduces an emerging paradigm to intracellular bacterial diagnosis and treatment, offering broad potential in combating bacterial infectious diseases.

Rapid Identification of Cell Types and Phenotypic States Using a One-Polymer Multichannel Nanosensor Fabricated via Flash Nanoprecipitation

Cell state transitions are fundamental in biology, determining how cells respond to environmental stimuli and adapt to diseases and treatments. Cell surface-based sensing of geno/phenotypes is a versatile approach for distinguishing different cell types and states. Array-based biosensors can provide a highly sensitive platform for distinguishing cells based on the differential interactions of each sensing element with cell surface components. In this work, a highly modular polymer-based supramolecular multichannel sensor array (FNP sensor) was fabricated by encapsulating a hydrophobic dye (pyrene) into the monolayer of a positively charged fluorescent polymer through flash nanoprecipitation (FNP). We utilized this one-polymer sensor array to discriminate among cell types commonly found in tumors: 4T1 cancer cells, NIH/3T3 fibroblast cells, and RAW 264.7 macrophage cells. The sensor also successfully characterized varying ratios of NIH/3T3 cancer-associated fibroblasts (CAFs) and RAW 264.7 tumor-associated macrophages (TAMs). This single polymer-based sensor array provides effective discrimination and high reproducibility, providing a high-throughput tool for diagnostic screening of cell types and states associated with cancer progression.

Bimodal Array-Based Fluorescence Sensor and Microfluidic Technology for Protein Fingerprinting and Clinical Diagnosis

Proteins play a crucial role in determining disease states in humans, making them prime targets for the development of diagnostic sensors. The developed sensor array is used to investigate global proteomic changes by fingerprinting multifactorial disease states in model urine simulating phenylketonuria and in serum from preeclamptic pregnant women. Here, we report a fluorescence-based chemical sensing array that exploits the host-guest interaction between cucurbit[7]uril (CB[7]) and fluorescent triphenylamine derivatives (TPA) to detect a range of proteins. Using linear discriminant analysis, we identify fluorescence fingerprints of 14 proteins with over 98% accuracy in buffer and human serum. The array is optimized on an automated droplet microfluidic-based platform, for high-throughput sensing with controlled composition and lower sample volumes. This sensor enables the discrimination of proteins in physiological buffer and human serum, with promising applications in disease diagnosis.

A Universal Method for Fingerprinting Multiplexed Bacteria: Evolving Pruned Sensor Arrays via Machine Learning-Driven Combinatorial Group-Specificity Strategy

Array-based sensing technology holds immense potential for discerning the intricacies of biological systems. Nevertheless, developing a universal strategy for simultaneous identification of diverse types of multianalytes and meeting the diagnostic needs of a range of multiclassified clinical diseases poses substantial challenges. Herein, we introduce a combination method for constructing sensor arrays by assembling two types of group-specific elements. Such a method enables the rapid generation of a library of 100 sensing units, each with dual bacterial targeting capabilities. By employing a three-step screening strategy optimized by machine learning algorithms, various optimal five-element arrays were rapidly obtained for diverse clinical infectious models. Moreover, the pruned arrays successfully identified disparate mixing ratios and quantitative detection of clinically prevalent bacterial strains. Optimized through nine multiclassification algorithms, the top-performing multilayer perceptron (MLP) model demonstrated impressive recognition capabilities, achieving 100% accuracy for diagnosing clinical urinary tract infection (UTI) and 99.4% accuracy for clinical sepsis detection in the test models we collected. Such a combinatorial library construction and screening process should be standard and provides insights into successfully generating powerful high-recognition sensor elements and configuring them into highly discriminative mini-sensor arrays.

Single-nanozyme single-readout enabled efficient identification of polyphenols for Chinese tea authentication and brewing evaluation

With the popularity of health-conscious tea drinking, precise sensing of polyphenols as a main class of antioxidants in tea becomes critical for tea authentication and brewing evaluation. Sensor arrays show great potential for the goal, but currently available sensor arrays always need multiple sensing units and/or multi-dimensional signals, resulting in cumbersome sensor construction and operation as well as data processing. Developing easy-to-fabricate and easy-to-use sensor arrays for efficient discrimination is still challenging. Here we propose a new sensor array that only uses a single signal collected dynamically with oxidase-like MnOOH as a sole sensing material. The synthesized MnOOH nanowires exhibit favorable activity to catalyze the chromogenic oxidation of colorless 3,3',5,5'-tetramethylbenzidine (TMB) to blue oxTMB. By taking gallic acid, tannic acid, L-epicatechin, (-)-epigallocatechin, (-)-epicatechin gallate and (-)-epigallocatechin gallate as models, the six tea polyphenols show discrepant inhibitory effects on the above catalytic system. As a result, these polyphenols, no matter as a single component at various concentrations or multi-component mixtures with different ratios, can be well distinguished by the single-nanozyme single-readout sensor array. Besides, different Chinese tea species, black tea varieties and impacts of brewing methods are accurately identified. Evidently, our sensor array avoids the requirement for multiple sensing units and multi-dimensional signals, greatly simplifying the fabrication of sensor arrays and their use, which provides an efficient yet facile tool for tea authentication and brewing evaluation.

Supramolecular control over the variability of color and fluorescence in low-molecular-weight glass

Colorful and fluorescent transparent materials have been extensively used in industrial and scientific activities, with inorganic and polymeric glasses being the most typical representatives. Recently, artificial glass originating from low-molecular-weight monomers has attracted considerable attention. Compared with the deep understanding of the building blocks and driving forces of supramolecular glass, related studies on its optical properties are insufficient in terms of systematicness and pertinence. In this study, a supramolecular strategy was applied to introduce versatile colors and fluorescence emissions into a low-molecular-weight glass. Pillar[5]arene and cucurbit[8]uril were selected to recognize the functional components and yield the desired optical performances. Macrocycle-based host-guest chemistry endows artificial glass with controllable and programmable colors and fluorescence emissions.

A General Strategy for Enhanced Photodynamic Antimicrobial Therapy with Perylenequinonoid Photosensitizers Using a Macrocyclic Supramolecular Carrier

Perylenequinonoid natural products are a class of photosensitizers (PSs) that exhibit high reactive oxygen species (ROS) generation and excellent activity for Type I/Type II dual photodynamic therapy. However, their limited activity against gram-negative bacteria and poor water solubility significantly restrict their potential in broad-spectrum photodynamic antimicrobial therapy (PDAT). Herein, a general approach to overcome the limitations of perylenequinonoid photosensitizers (PQPSs) in PDAT by utilizing a macrocyclic supramolecular carrier is presented. Specifically, AnBox·4Cl, a water-soluble cationic cyclophane, is identified as a universal macrocyclic host for PQPSs such as elsinochrome C, hypocrellin A, hypocrellin B, and hypericin, forming 1:1 host-guest complexes with high binding constants (≈107 m -1) in aqueous solutions. Each AnBox·4Cl molecule carries four positive charges that promote strong binding with the membrane of gram-negative bacteria. As a result, the AnBox·4Cl-PQPS complexes can effectively anchor on the surfaces of gram-negative bacteria, while the PQPSs alone cannot. In vitro and in vivo experiments demonstrate that these supramolecular PSs have excellent water solubility and high ROS generation, with broad-spectrum PDAT effect against both gram-negative and gram-positive bacteria. This work paves a new path to enhance PDAT by showcasing an efficient approach to improve PQPSs' water solubility and killing efficacy for gram-negative bacteria.

Food nanotechnology: opportunities and challenges

Food nanotechnology, which applies nanotechnology to food systems ranging from food production to food processing, packaging, and transportation, provides tremendous opportunities for conventional food science and industry innovation and improvement. Although great progress and rapid growth have been achieved in food nanotechnology research owing to the unique food features rendered by nanotechnology, at a fundamental level, food nanotechnology is still in its initial stages and the potential adverse effects of nanomaterials are still a controversial problem that attract public attention. Food-derived nanomaterials, compared to some inorganic nanoparticles and synthetic organic macromolecules, can be digested rapidly and produce similar digestion products to those produced normally, which become the mainstream and trend for food nanotechnology in practical applications, and are expected to be a vital tool for addressing the security problem and easing public concerns. These food-derived materials enable the favourable characteristics of nanostructures to be combined with the safety, biocompatibility, and bioactivity of natural food. Very recently, diverse food-derived nanomaterials have been explored and widely applied in multiple fields. Herein, we thoroughly summarize the fabrication and development of nanomaterials for use in food technology, as well as the recent advances in the improvement of food quality, revolutionizing food supply, and boosting food industries based on foodborne nanomaterials. The current challenges in food nanotechnology are also discussed. We hope this review can provide a detailed reference for experts and food manufacturers and inspire researchers to participate in the development of food nanotechnology for highly efficient food industry growth.

A Supramolecular Fluorescent Sensor Array Composed of Conjugated Fluorophores and Cucurbit[7]uril for Bacterial Recognition

Bacterial infections have emerged as a significant contributor to global mortality and morbidity rates. Herein, we introduce a dual fluorescence "turn-on" supramolecular sensor array composed of three assembled complexes (C1-C3), formed from three positively charged fluorophores (A1-A3) and one cucurbit[7]uril (CB[7]). The ability of this three-element array to simultaneously recognize 10 bacterial species within just 30 s was remarkable, boasting an impressive 100% accuracy. Additionally, the array excelled at distinguishing among various bacterial mixtures and enabled the quantitative detection of common bacterial strains. Notably, it has been skillfully applied to differentiate 10 bacterial samples in urine, achieving excellent differentiation and showcasing promising potential for medical diagnostic applications.

Mixed host co-assembled systems for broad-scope analyte sensing

Here we report a systems chemistry oriented approach for developing information-rich mixed host chemosensors. We show that co-assembling macrocyclic hosts from different classes, DimerDye sulfonatocalix[4]arenes and cucurbit[n]urils, effectively increases the scope of analyte binding interactions and therefore, sensory outputs. This simple dynamic strategy exploits cross-reactive noncovalent host-host complexation interactions while integrating a reporter dye, thereby producing emergent photophysical responses when an analyte interacts with either host. We first demonstrate the advantages of mixed host co-assembled chemosensors through an increased detection range of hydrophobic, cationic, neutral, and anionic drugs. We then implement mixed host sensors in an array-based platform for the differentiation of illicit drugs, including cannabinoids, benzodiazepine analogs, opiates, anesthetics, amphetamine, and common adulterating substances. Finally, the potential of this approach is applied to profiling real-world multi-component illicit street drug samples, proving to be more effective than classical sensor arrays.

Nanotechnology improves the detection of bacteria: Recent advances and future perspectives

Nanotechnology has advanced significantly, particularly in biomedicine, showing promise for nanomaterial applications. Bacterial infections pose persistent public health challenges due to the lack of rapid pathogen detection methods, resulting in antibiotic overuse and bacterial resistance, threatening the human microbiome. Nanotechnology offers a solution through nanoparticle-based materials facilitating early bacterial detection and combating resistance. This study explores recent research on nanoparticle development for controlling microbial infections using various nanotechnology-driven detection methods. These approaches include Surface Plasmon Resonance (SPR) Sensors, Surface-Enhanced Raman Scattering (SERS) Sensors, Optoelectronic-based sensors, Bacteriophage-Based Sensors, and nanotechnology-based aptasensors. These technologies provide precise bacteria detection, enabling targeted treatment and infection prevention. Integrating nanoparticles into detection approaches holds promise for enhancing patient outcomes and mitigating harmful bacteria spread in healthcare settings.

Enantiopure Corral[4]BINOLs as Ultrastrong Receptors for Recognition and Differential Sensing of Steroids

The precise recognition and sensing of steroids, a type of vital biomolecules, hold immense practical value across various domains. In this study, we introduced corral[4]BINOLs (C[4]BINOLs), a pair of enantiomeric conjugated deep-cavity hosts, as novel synthetic receptors for binding steroids. Due to the strong hydrophobic effect of their deep nonpolar, chiral cavities, the two enantiomers of C[4]BINOLs demonstrated exceptionally high recognition affinities (up to 1012 M-1) for 16 important steroidal compounds as well as good enantioselectiviy (up to 15.5) in aqueous solutions, establishing them as the most potent known steroid receptors. Harnessing their ultrahigh affinity, remarkable enantioselectivity, and fluorescence emission properties, the two C[4]BINOL enantiomers were employed to compose a fluorescent sensor array which achieved discrimination and sensing of 16 structurally similar steroids at low concentrations.

Calixarene-Based Supramolecular Sensor Array for Pesticide Discrimination

The identification and detection of pesticides is crucial to protecting both the environment and human health. However, it can be challenging to conveniently and rapidly differentiate between different types of pesticides. We developed a supramolecular fluorescent sensor array, in which calixarenes with broad-spectrum encapsulation capacity served as recognition receptors. The sensor array exhibits distinct fluorescence change patterns for seven tested pesticides, encompassing herbicides, insecticides, and fungicides. With a reaction time of just three minutes, the sensor array proves to be a rapid and efficient tool for the discrimination of pesticides. Furthermore, this supramolecular sensing approach can be easily extended to enable real-time and on-site visual detection of varying concentrations of imazalil using a smartphone with a color scanning application. This work not only provides a simple and effective method for pesticide identification and quantification, but also offers a versatile and advantageous platform for the recognition of other analytes in relevant fields.

Intelligent Biomaterialomics: Molecular Design, Manufacturing, and Biomedical Applications

Materialomics integrates experiment, theory, and computation in a high-throughput manner, and has changed the paradigm for the research and development of new functional materials. Recently, with the rapid development of high-throughput characterization and machine-learning technologies, the establishment of biomaterialomics that tackles complex physiological behaviors has become accessible. Breakthroughs in the clinical translation of nanoparticle-based therapeutics and vaccines have been observed. Herein, recent advances in biomaterials, including polymers, lipid-like materials, and peptides/proteins, discovered through high-throughput screening or machine learning-assisted methods, are summarized. The molecular design of structure-diversified libraries; high-throughput characterization, screening, and preparation; and, their applications in drug delivery and clinical translation are discussed in detail. Furthermore, the prospects and main challenges in future biomaterialomics and high-throughput screening development are highlighted.

Food for Thought: Optical Sensor Arrays and Machine Learning for the Food and Beverage Industry

Arrays of cross-reactive sensors, combined with statistical or machine learning analysis of their multivariate outputs, have enabled the holistic analysis of complex samples in biomedicine, environmental science, and consumer products. Comparisons are frequently made to the mammalian nose or tongue and this perspective examines the role of sensing arrays in analyzing food and beverages for quality, veracity, and safety. I focus on optical sensor arrays as low-cost, easy-to-measure tools for use in the field, on the factory floor, or even by the consumer. Novel materials and approaches are highlighted and challenges in the research field are discussed, including sample processing/handling and access to significant sample sets to train and test arrays to tackle real issues in the industry. Finally, I examine whether the comparison of sensing arrays to noses and tongues is helpful in an industry defined by human taste.

"Covalent-Disassembly"-Based Approaches For Sensing Applications

The detection of analytes with small molecular probes is crucial for the analysis and understanding of chemical, medicinal, environmental and biological situations as well as processes. Classic detection approaches rely on the concept of molecular recognition and bond formation reactions. Bond breakage reactions have been less explored in similar contexts. This concept article introduces metal-salen and metal-imine complexes as "covalent-disassembly"-based (DB)-probes for detecting polyoxophosphates, thiols, amino acids, HCN and changes in pH. It discusses the roles, importance and combinations of structurally functionalized molecular building blocks in the construction of DB-probes. Applications of optimized DB-probes for analyte detection in live cells and foodstuff are also discussed. Furthermore, the mechanism of the disassembly of a Fe(III)-salen probe upon pyrophosphate binding is presented. Extraordinary selectivity for this analyte was achieved by a multistep disassembly sequence including an unprecedented structural change of the metal complex (i. e. "induced-fit" principle). Design principles of probes for sensing applications following the "covalent-disassembly" approach are summarized, which will help improving current systems, but will also facilitate the development of new DB-probes for challenging analytic targets.

FRET-Based Host-Guest Supramolecular Probe for On-Site and Broad-Spectrum Detection of Pyrethroids in the Environment

The massive use of pyrethroid pesticides in agriculture has brought growing concerns about food safety due to their several harmful effects on human health, especially through the accumulation of the food chain. To date, most of the available analytical methods for pyrethroids still suffer from insufficient detection universality, complicated sample pretreatment, and detection processes, which severely limit their practical applications. Herein, a novel Förster resonance energy transfer (FRET)-assisted host-guest supramolecular nanoassembly is reported, for the first time, successfully realizing ratiometric fluorescent detection of pyrethroids in real samples through the indicator displacement assay (IDA) mechanism. This method is capable of detecting a broad spectrum of pyrethroids, including bifenthrin, cyfluthrin, cypermethrin, deltamethrin, etofenprox, fenvalerate, and permethrin, with ultrahigh detection sensitivity, great selectivity, high anti-interference ability, and, in particular, distinct emission color response from red to green. Such a large chromatic response makes this method available for fast and on-site detection of pyrethroids in real samples with the aid of several simple portable analytical apparatuses.

Machine learning-assisted fluorescence sensor array for qualitative and quantitative analysis of pyrethroid pesticides

The simultaneous detection of multiple residues of pyrethroid pesticides (PPs) on vegetables and fruits is still challenging using traditional nanosensing methods due to the high structural similarity of PPs. In this work, sensor arrays composed of three nanocomposite complexes (rhodamine B-CD@Au, rhodamine 6G-CD@Au, and coumarin 6-CD@Au) were constructed to discriminate between structurally similar PPs. Four PPs, deltamethrin, fenvalerate, cyfluthrin, and fenpropathrin, were successfully discriminated. The ability of these sensor units was derived from the different affinity between receptor/analyte and receptor/dye, as well as the non-linear relationship between fluorescence signal and analyte concentration. Upon multivariate pattern recognition analysis, the array performed high-throughput identification of four PPs in unknown samples with 100% classification accuracy. In addition, good accuracy of predicting concentration using the "stepwise prediction" strategy combined with the machine learning method was achieved.

Molecular Recognition with Macrocyclic Receptors for Application in Precision Medicine

Macrocyclic receptors can serve as alternatives to natural recognition systems as recognition tools. They provide effectively preorganized cavities to encapsulate guests via host-guest interactions, thereby affecting the physiochemical properties of the guests. Macrocyclic receptors exhibit chemical and thermal stabilities higher than those of natural receptors and thus are expected to resist degradation inside the body. This reduces the risk of harmful degradation byproducts and ensures optimal levels of effectiveness. Macrocyclic receptors have precise molecular weights and well-defined structures; this ensures their batch-to-batch reproducibility, which is critical for ensuring quality and effectiveness levels. Moreover, macrocyclic receptors exhibit broad modification tunabilities, rendering them adaptable to various guests. Molecular recognition is the basis of numerous biological processes. Macrocyclic receptors may display considerable potential for application in diagnosing and treating diseases, depending on the host-guest recognition of bioactive molecules. However, the binding affinities and selectivities of macrocyclic receptors toward bioactive molecules are generally insufficient, which may lead to problems such as low diagnosis accuracies, off-target leaking, and interference with normal functions. Therefore, addressing the challenge of the strong and specific complexation of bioactive molecules and macrocyclic receptors is imperative.To overcome this challenge, we proposed the innovative strategies of longitudinal cavity extension and coassembled heteromultivalent recognition for application in the recognition of small molecules and biomacromolecules, respectively. The deepened cavity provides a stronger hydrophobic effect and a larger interaction area while maintaining the framework rigidity. By coassembling two macrocyclic amphiphiles into one ensemble, we achieved the desired heteromultivalent recognition. This strategy affords the necessary binding properties while preventing the requirement of tedious steps and site mismatch in covalent synthesis. Using these two strategies, we achieved specific and strong binding of macrocyclic receptors to various bioactive molecules including biomarkers, drugs, and disease-related peptides/proteins. We then applied these macrocyclic receptor-based recognition systems in biosensing and bioimaging, drug delivery, and therapeutics.In this Account, we summarize the strategies we used in the recognition of small molecules and biomacromolecules. Thereafter, we discuss their applications in precision medicine, involving the (1) sensing of biomarkers and imaging of lesion sites, which are critical in the early screening of diseases and accurate diagnoses; (2) precise loading and targeted delivery of drugs, which are crucial in improving their therapeutic efficacies and reducing their side effects; and (3) capture and removal of disease-related biomacromolecules, which are significant for precise intervention in life processes. Finally, we propose recommendations for the further development of macrocyclic receptor-based recognition systems in biomedicine. Macrocyclic receptors exhibit considerable potential for research, and continued investigation may not only expand the applications of supramolecular chemistry but also open novel avenues for the development of precision medicine.

A colorimetric sensor array based on nanoceria crosslinked and heteroatom-doped graphene oxide nanoribbons for the detection and discrimination of multiple pesticides

Nanozymes have demonstrated high potential in constructing colorimetric sensor array for pesticides. However, rarely array for pesticides constructed without bio-enzyme were reported. Herein, nanoceria crosslinked graphene oxide nanoribbons (Ce-GONRs) and heteroatom-doped graphene oxide nanoribbons (Ce-BGONRs and Ce-NGONRs) were prepared, demonstrating excellent peroxidase-like activities. A colorimetric sensor array was developed based on directly inhibiting the peroxidase-like activities of the above three nanozymes, which realized the discrimination and quantitative analysis of six pesticides. In the presence of pesticides including carbaryl (Car), fluroxypyr-mepthyl (Flu), thiophanate-methyl (Thio), thiram (Thir), diafenthiuron (Dia) and fomesafen (Fom), the peroxidase-like activities of three nanozymes were inhibited to different degrees, resulting in different fingerprint responses. The six pesticides in the concentration range of 0.1-50 μg/mL and two pesticides mixtures at varied ratios could be detected and discriminated, and minimum detection limit for pesticides was 0.022 μg/mL. In addition, this sensor array has been successfully applied for pesticides discrimination in lake water and apple samples. This work provided a new strategy of constructing simple and sensitive colorimetric sensor array for pesticides based on directly inhibiting the catalytic activities of nanozymes.

Adaptive Supramolecular Networks: Emergent Sensing from Complex Systems

Molecular differentiation by supramolecular sensors is typically achieved through sensor arrays, relying on the pattern recognition responses of large panels of isolated sensing elements. Here we report a new one-pot systems chemistry approach to differential sensing in biological solutions. We constructed an adaptive network of three cross-assembling sensor elements with diverse analyte-binding and photophysical properties. This robust sensing approach exploits complex interconnected sensor-sensor and sensor-analyte equilibria, producing emergent supramolecular and photophysical responses unique to each analyte. We characterize the basic mechanisms by which an adaptive network responds to analytes. The inherently data-rich responses of an adaptive network discriminate among very closely related proteins and protein mixtures without relying on designed protein recognition elements. We show that a single adaptive sensing solution provides better analyte discrimination using fewer response observations than a sensor array built from the same components. We also show the network's ability to adapt and respond to changing biological solutions over time.

Dual hypoxia-responsive supramolecular complex for cancer target therapy

The prognosis with pancreatic cancer is among the poorest of any human cancer. One of the important factors is the tumor hypoxia. Targeting tumor hypoxia is considered a desirable therapeutic option. However, it has not been translated into clinical success in the treatment of pancreatic cancer. With enhanced cytotoxicities against hypoxic pancreatic cancer cells, BE-43547A2 (BE) may serve as a promising template for hypoxia target strategy. Here, based on rational modification, a BE prodrug (NMP-BE) is encapsulated into sulfonated azocalix[5]arene (SAC5A) to generate a supramolecular dual hypoxia-responsive complex NMP-BE@SAC5A. Benefited from the selective load release within cancer cells, NMP-BE@SAC5A markedly suppresses tumor growth at low dose in pancreatic cancer cells xenograft murine model without developing systemic toxicity. This research presents a strategy for the modification of covalent compounds to achieve efficient delivery within tumors, a horizon for the realization of safe and reinforced hypoxia target therapy using a simple approach.

Recent Progress in Sensor Arrays: From Construction Principles of Sensing Elements to Applications

The traditional sensors are designed based on the "lock-and-key" strategy with high selectivity and specificity for detecting specific analytes, which however are not suitable for detecting multiple analytes simultaneously. With the help of pattern recognition technologies, the sensor arrays excel in distinguishing subtle changes caused by multitarget analytes with similar structures in a complex system. To construct a sensor array, the multiple sensing elements are undoubtedly indispensable units that will selectively interact with targets to generate the unique "fingerprints" based on the distinct responses, enabling the identification among various analytes through pattern recognition methods. This comprehensive review mainly focuses on the construction strategies and principles of sensing elements, as well as the applications of sensor array for identification and detection of target analytes in a wide range of fields. Furthermore, the present challenges and further perspectives of sensor arrays are discussed in detail.

Colorimetric Sensor Array for Identification of Proteins and Classification of Metabolic Profiles under Various Osmolyte Conditions

Rapid and efficient detection and identification of proteins hold great promise in medical diagnostics, treatment of different diseases, and proteomics. Here, we present a simple colorimetric sensor array for the differentiation of proteins in various osmolyte solutions. Osmolytes have different influences on the conformation of proteins, which have differential binding to silver nanoparticles, resulting in color changes. The sensor array shows unique color change patterns for each of the 19 proteins, allowing unambiguous identification. Very interestingly, the differentiation of 19 proteins is related to their molecular weight. Moreover, the sensor array can be used to identify protein mixtures, thermal denaturized proteins, and unknown protein samples. Finally, the sensor array can also analyze the plasma or liver samples of the four groups of salt-sensitive rats fed with different diets, indicating that it has the potential for the classification of metabolic profiles.

Humidity-Independent Artificial Olfactory Array Enabled by Hydrophobic Core-Shell Dye/MOFs@COFs Composites for Plant Disease Diagnosis

As a class of important artificial olfactory system, the colorimetric sensor array possesses great potential for commercialization due to its cost-effectiveness and portability. However, when applied to practical applications, the humidity interference from ambient environment and dissatisfactory sensitivity for trace target VOCs are largely unsolved problems. To overcome the problems, we developed a series of dye/MOFs@COFs gas-sensing materials with core-shell structure using a hydrophobization strategy by encapsulation of dye/metal-organic frameworks (MOFs) into hydrophobic covalent organic frameworks (COFs). Benefiting from the hydrophobic property of the COF shell, the dye/MOFs@COFs composites were endowed with excellent humidity-resistance even under 100% relative humidity (RH). Moreover, due to the uniform distribution of dyes on the porous MOFs, the dye/MOFs@COFs sensors also exhibited improved sensitivity at the sub-ppm level, compared with conventional dye sensors. On basis of the excellent humidity-resistance and improved sensitivity, an artificial olfactory array based on dye/MOFs@COFs composites was proven to be a successful practical application in early and accurate detection of wheat scab (1 day after inoculation) by monitoring its released VOC markers. The synthetic strategy for core-shell dye/MOFs@COFs is applicable to a wide range of colorimetric sensor arrays, endowing them with excellent humidity-resistance and sensitivity for the feasibility of practical applications.

A supramolecular organometallic drug complex with H2O2 self-provision intensifying intracellular autocatalysis for chemodynamic therapy

A supramolecular organometallic drug complex (SOMDC) with H2O2 self-provision was proposed to intensify the intracellular autocatalysis for enhancing the CDT effect.