On-Demand Opioid Effect Reversal with an Injectable Light-Triggered Polymer-Naloxone Conjugate.

Misuse of opioids can lead to a potential lethal overdose. Timely administration of naloxone is critical for survival. Here, we designed a polymer-naloxone conjugate that can provide on-demand phototriggered opioid reversal. Naloxone was attached to the polymer poly(lactic-co-glycolic acid) via a photocleavable coumarin linkage and formulated as injectable nanoparticles. In the absence of irradiation, the formulation did not release naloxone. Upon irradiation with blue (400 nm) light, the nanoparticles released free naloxone, reversing the effect of morphine in mice. Such triggered events could be performed days and weeks after the initial administration of the nanoparticles and could be performed repeatedly.

Polymeric Prodrugs using Dynamic Covalent Chemistry for Prolonged Local Anesthesia.

Depot-type drug delivery systems are designed to deliver drugs at an effective rate over an extended period. Minimizing initial "burst" can also be important, especially with drugs causing systemic toxicity. Both goals are challenging with small hydrophilic molecules. The delivery of molecules such as the ultrapotent local anesthetic tetrodotoxin (TTX) exemplifies both challenges. Toxicity can be mitigated by conjugating TTX to polymers with ester bonds, but the slow ester hydrolysis can result in subtherapeutic TTX release. Here, we developed a prodrug strategy, based on dynamic covalent chemistry utilizing a reversible reaction between the diol TTX and phenylboronic acids. These polymeric prodrugs exhibited TTX encapsulation efficiencies exceeding 90 % and the resulting polymeric nanoparticles showed a range of TTX release rates. In vivo injection of the TTX polymeric prodrugs at the sciatic nerve reduced TTX systemic toxicity and produced nerve block lasting 9.7±2.0 h, in comparison to 1.6±0.6 h from free TTX. This approach could also be used to co-deliver the diol dexamethasone, which prolonged nerve block to 21.8±5.1 h. This work emphasized the usefulness of dynamic covalent chemistry for depot-type drug delivery systems with slow and effective drug release kinetics.

Engineering Flexible Metal-Phenolic Networks with Guest Responsiveness via Intermolecular Interactions.

Flexible metal-organic materials are of growing interest owing to their ability to undergo reversible structural transformations under external stimuli. Here, we report flexible metal-phenolic networks (MPNs) featuring stimuli-responsive behavior to diverse solute guests. The competitive coordination of metal ions to phenolic ligands of multiple coordination sites and solute guests (e.g., glucose) primarily determines the responsive behavior of the MPNs, as revealed experimentally and computationally. Glucose molecules can be embedded into the dynamic MPNs upon mixing, leading to the reconfiguration of the metal-organic networks and thus changes in their physicochemical properties for targeting applications. This study expands the library of stimuli-responsive flexible metal-organic materials and the understanding of intermolecular interactions between metal-organic materials and solute guests, which is essential for the rational design of responsive materials for various applications.

Role of Molecular Interactions in Supramolecular Polypeptide-Polyphenol Networks for Engineering Functional Materials.

Supramolecular assembly affords the development of a wide range of polypeptide-based biomaterials for drug delivery and nanomedicine. However, there remains a need to develop a platform for the rapid synthesis and study of diverse polypeptide-based materials without the need for employing complex chemistries. Herein, we develop a versatile strategy for creating polypeptide-based materials using polyphenols that display multiple synergistic cross-linking interactions with different polypeptide side groups. We evaluated the diverse interactions operating within these polypeptide-polyphenol networks via binding affinity, thermodynamics, and molecular docking studies and found that positively charged polypeptides (Ka of ∼2 × 104 M-1) and polyproline (Ka of ∼2 × 106 M-1) exhibited stronger interactions with polyphenols than other amino acids (Ka of ∼2 × 103 M-1). Free-standing particles (capsules) were obtained from different homopolypeptides using a template-mediated strategy. The properties of the capsules varied with the homopolypeptide used, for example, positively charged polypeptides produced thicker shell walls (120 nm) with reduced permeability and involved multiple interactions (i.e., electrostatic and hydrogen), whereas uncharged polypeptides generated thinner (10 nm) and more permeable shell walls due to the dominant hydrophobic interactions. Polyarginine imparted cell penetration and endosomal escape properties to the polyarginine-tannic acid capsules, enabling enhanced delivery of the drug doxorubicin (2.5 times higher intracellular fluorescence after 24 h) and a corresponding higher cell death in vitro when compared with polyproline-tannic acid capsules. The ability to readily complex polyphenols with different types of polypeptides highlights that a wide range of functional materials can be generated for various applications.

Site-Selective Coordination Assembly of Dynamic Metal-Phenolic Networks.

Coordination states of metal-organic materials are known to dictate their physicochemical properties and applications in various fields. However, understanding and controlling coordination sites in metal-organic systems is challenging. Herein, we report the synthesis of site-selective coordinated metal-phenolic networks (MPNs) using flavonoids as coordination modulators. The site-selective coordination was systematically investigated experimentally and computationally using ligands with one, two, and multiple different coordination sites. Tuning the multimodal Fe coordination with catechol, carbonyl, and hydroxyl groups within the MPNs enabled the facile engineering of diverse physicochemical properties including size, selective permeability (20-2000 kDa), and pH-dependent degradability. This study expands our understanding of metal-phenolic chemistry and provides new routes for the rational design of structurally tailorable coordination-based materials.

Robust and Versatile Coatings Engineered via Simultaneous Covalent and Noncovalent Interactions.

Interfacial modular assembly has emerged as an adaptable strategy for engineering the surface properties of substrates in biomedicine, photonics, and catalysis. Herein, we report a versatile and robust coating (pBDT-TA), self-assembled from tannic acid (TA) and a self-polymerizing aromatic dithiol (i.e., benzene-1,4-dithiol, BDT), that can be engineered on diverse substrates with a precisely tuned thickness (5-40 nm) by varying the concentration of BDT used. The pBDT-TA coating is stabilized by covalent (disulfide) bonds and supramolecular (π-π) interactions, endowing the coating with high stability in various harsh aqueous environments across ionic strength, pH, temperature (e.g., 100 mM NaCl, HCl (pH 1) or NaOH (pH 13), and water at 100 °C), as well as surfactant solution (e.g., 100 mM Triton X-100) and biological buffer (e.g., Dulbecco's phosphate-buffered saline), as validated by experiments and simulations. Moreover, the reported pBDT-TA coating enables secondary reactions on the coating for engineering hybrid adlayers (e.g., ZIF-8 shells) via phenolic-mediated adhesion, and the facile integration of aromatic fluorescent dyes (e.g., rhodamine B) via π interactions without requiring elaborate synthetic processes.

Luminescent Metal-Phenolic Networks for Multicolor Particle Labeling.

The development of fluorescence labeling techniques has attracted widespread interest in various fields, including biomedical science as it can facilitate high-resolution imaging and the spatiotemporal understanding of various biological processes. We report a supramolecular fluorescence labeling strategy using luminescent metal-phenolic networks (MPNs) constructed from metal ions, phenolic ligands, and common and commercially available dyes. The rapid labeling process (<5 min) produces ultrathin coatings (≈10 nm) on diverse particles (e.g., organic, inorganic, and biological entities) with customized luminescence (e.g., red, blue, multichromatic, and white light) simply through the selection of fluorophores. The fluorescent coatings are stable at pH values from 1 to 8 and in complex biological media owing to the dominant π interactions between the dyes and MPNs. These coatings exhibit negligible cytotoxicity and their strong fluorescence is retained even when internalized into intracellular compartments. This strategy is expected to provide a versatile approach for fluorescence labeling with potential in diverse fields across the physical and life sciences.

Ordered Mesoporous Metal-Phenolic Network Particles.

Mesoporous metal-organic networks have attracted widespread interest owing to their potential applications in diverse fields including gas storage, separations, catalysis, and drug delivery. Despite recent advances, the synthesis of metal-organic networks with large and ordered mesochannels (>20 nm), which are important for loading, separating, and releasing macromolecules, remains a challenge. Herein, we report a templating strategy using sacrificial double cubic network polymer cubosomes (Im3̅m) to synthesize ordered mesoporous metal-phenolic particles (meso-MPN particles) with a large-pore (∼40 nm) single cubic network (Pm3̅m). We demonstrate that the large-pore network and the phenolic groups in the meso-MPN particles enable high loadings of various proteins (e.g., horseradish peroxidase (HRP), bovine hemoglobin, immunoglobulin G, and glucose oxidase (GOx)), which have different shapes, charges, and sizes (i.e., molecular weights spanning 44-160 kDa). For example, GOx loading in the meso-MPN particles was 362 mg g-1, which is ∼6-fold higher than the amount loaded in commercially available SiO2 particles with an average pore size of 50 nm. Furthermore, we show that HRP, when loaded in the meso-MPN particles (486 mg g-1), retained ∼82% activity of free HRP in solution and can be recycled at least five times with a minimal (∼13%) decrease in HRP activity, which exceeds HRP performance in 50 nm pore SiO2 particles (∼36% retained activity and ∼30% activity loss when recycled five times). Considering the wide selection of naturally abundant polyphenols (>8000 species) and metal ions available, the present cubosome-enabled strategy is expected to provide new avenues for designing a range of meso-MPN particles for various applications.

Polyphenol-Mediated Assembly of Proteins for Engineering Functional Materials.

Functional materials composed of proteins have attracted much interest owing to the inherent and diverse functionality of proteins. However, establishing general techniques for assembling proteins into nanomaterials is challenging owing to the complex physicochemical nature and potential denaturation of proteins. Here, a simple, versatile strategy is introduced to fabricate functional protein assemblies through the interfacial assembly of proteins and polyphenols (e.g., tannic acid) on various substrates (organic, inorganic, and biological). The dominant interactions (hydrogen-bonding, hydrophobic, and ionic) between the proteins and tannic acid were elucidated; most proteins undergo multiple noncovalent stabilizing interactions with polyphenols, which can be used to engineer responsiveness into the assemblies. The proteins retain their structure and function within the assemblies, thereby enabling their use in various applications (e.g., catalysis, fluorescence imaging, and cell targeting).

Engineering Biocoatings To Prolong Drug Release from Supraparticles.

Supraparticles (SPs) assembled from smaller colloidal nanoparticles can serve as depots of therapeutic compounds and are of interest for long-term, sustained drug release in biomedical applications. However, a key challenge to achieving temporal control of drug release from SPs is the occurrence of an initial rapid release of the loaded drug (i.e., "burst" release) that limits sustained release and potentially causes burst release-associated drug toxicity. Herein, a biocoating strategy is presented for silica-SPs (Si-SPs) to reduce the extent of burst release of the loaded model protein lysozyme. Specifically, Si-SPs were coated with a fibrin film, formed by enzymatic conversion of fibrinogen into fibrin. The fibrin-coated Si-SPs, FSi-SPs, which could be loaded with 7.9 ± 0.9 µg of lysozyme per SP, released >60% of cargo protein over a considerably longer period of time of >20 days when compared with the uncoated Si-SPs that released the same amount of the cargo protein, however, within the first 3 days. Neurotrophins that support the survival and differentiation of neurons could also be loaded at ∼7.3 µg per SP, with fibrin coating also delaying neurotrophin release (only 10% of cargo released over 21 days compared with 60% from Si-SPs). In addition, the effects of incorporating a hydrogel-based system for surgical delivery and the opportunity to control drug release kinetics were investigated-an alginate-based hydrogel scaffold was used to encapsulate FSi-SPs. The introduction of the hydrogel further extended the initial release of the encapsulated lysozyme to ∼40 days (for the same amount of cargo released). The results demonstrate the increasing versatility of the SP drug delivery platform, combining large loading capacity with sustained drug release, that is tailorable using different modes of controlled delivery approaches.

Relative contributions of formants to the intelligibility of sine-wave sentences in Mandarin Chinese.

Early sine-wave speech (SWS) studies showed that the first three formants contain sufficient intelligibility information. The present work assessed the relative perceptual contributions of the first three formants. Mandarin sentences were edited to generate two SWS conditions: removal of one of the first three formant trajectories, and preservation of only one formant trajectory. In addition, SWS synthesis was implemented in the absence of sine-wave amplitude modulation. The results consistently showed that the trajectory of the second formant contributed the most to intelligibility, and the effect of amplitude modulation was smaller than that of the formant number.

Validation of Cross-Individual Pain Assessment with Individual Recognition Model from Electroencephalogram.

Cross-individual pain assessment models based on electroencephalography (EEG) allow pain assessment in individuals who cannot report pain (e.g., unresponsive patients). The main obstacle to the generalisation of pain assessment models is the individual variation of brain responses to pain. Hence, we took the individual variation into account in cross-individual model development. We developed two convolutional neural networks (CNN) sharing an encoder architecture. One CNN predicts pain, while the other predicts the identity of an individual. We performed a leave-one-out (LOO) test with the exclusion of each subject and applied evidence accumulation to it for validating the pain prediction model's performance, where the binary classifier involves the states of pain (Hot) and resting state (Eyes-open). The mean accuracy produced by the LOO tests was 57.81% (max: 73.33%), and the mean accuracy of evidence accumulation achieved 69.75% (max: 100.00%). The individual recognition model achieved an accuracy of 99.63%. Nevertheless, when we acquired the most similar subject to a novel subject using the individual recognition model, where the most similar subject was used to train a subject-wise pain prediction model. The accuracy of predicting the pain-related conditions of the novel subject by the subject-wise model was only 53.73% (max: 79.50%). Therefore, the approach to utilising the features related to individual variation extracted by the CNN model needs more investigation for improving cross-individual pain assessment.Clinical relevance- This model can be applied to assess pain from EEG signals at the bedside with future improvement, which can help caretakers of unresponsive patients.

Classification of Tonic Pain Experience based on Phase Connectivity in the Alpha Frequency Band of the Electroencephalogram using Convolutional Neural Networks.

The complexity of brain activity involved in the generation of the experience of pain makes it hard to identify neural markers able to predict pain states. The within and between subjects variability of pain hinders the predictive potential of machine learning models trained across participants. This challenge can be tackled by implementing deep learning classifiers based on convolutional neural networks (CNNs). We targeted phase-based connectivity in the alpha band recorded with electroencephalography (EEG) during resting states and sensory conditions (eyes open [O] and closed [C] as resting states, and warm [W] and hot [H] water as sensory conditions). Connectivity features were extracted and re-organized as square matrices, because CNNs are effective in detecting the patterns from 2D data. To assess the classifier performance we implemented two complementary approaches: we 1) trained and tested the classifier with data from all participants, and 2) using a leave-one-out approach, that is excluding one participant at a time during training while using their data as a test set. The accuracy of binary classification between pain condition (H) and eyes open resting state (O) was 94.16% with the first approach, and 61.01 % with the leave-one-out approach. Clinical relevance-Further validation of the CNN classifier may help caregivers track the rehabilitation of chronic pain patients and dynamically modify the therapy. Further refinement of the model may allow its application in critical care setting with unresponsive patients to identify pain-like states otherwise incommunicable to medical personnel.

Assembly of Bioactive Nanoparticles via Metal-Phenolic Complexation.

The integration of bioactive materials (e.g., proteins and genes) into nanoparticles holds promise in fields ranging from catalysis to biomedicine. However, it is challenging to develop a simple and broadly applicable nanoparticle platform that can readily incorporate distinct biomacromolecules without affecting their intrinsic activity. Herein, a metal-phenolic assembly approach is presented whereby diverse functional nanoparticles can be readily assembled in water by combining various synthetic and natural building blocks, including poly(ethylene glycol), phenolic ligands, metal ions, and bioactive macromolecules. The assembly process is primarily mediated by metal-phenolic complexes through coordination and hydrophobic interactions, which yields uniform and spherical nanoparticles (mostly <200 nm), while preserving the function of the incorporated biomacromolecules (siRNA and five different proteins used). The functionality of the assembled nanoparticles is demonstrated through cancer cell apoptosis, RNA degradation, catalysis, and gene downregulation studies. Furthermore, the resulting nanoparticles can be used as building blocks for the secondary engineering of superstructures via templating and cross-linking with metal ions. The bioactivity and versatility of the platform can potentially be used for the streamlined and rational design of future bioactive materials.

Development and Validation of a Three-Gene-Based Prognostic Model for Predicting the Overall Survival of Head and Neck Squamous Cell Carcinoma Through Bioinformatics Analysis.

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancer worldwide and seriously threats public health safety. Despite the improvement of diagnostic and treatment methods, the overall survival for advanced patients has not improved yet. This study aimed to sort out prognosis-related molecular biomarkers for HNSCC and establish a prognostic model to stratify the risk hazards and predicate the prognosis for these patients, providing a theoretical basis for the formulation of individual treatment plans. We firstly identified differentially expressed genes (DEGs) between HNSCC tissues and normal tissues via joint analysis based on GEO databases. Then a total of 11 hub genes were selected for single-gene prognostic analysis to identify the prognostic genes. Later, the clinical information and transcription information of HNSCC were downloaded from the TCGA database. With the application of least absolute shrinkage and selection operator (LASSO) algorithm analyses for the prognostic genes on the TCGA cohort, a prognostic model consisting of three genes (COL4A1, PLAU and ITGA5) was successfully established and the survival analyses showed that the prognostic model possessed a robust performance in the overall survival prediction. Afterward, the univariate and multivariate regression analysis indicated that the prognostic model could be an independent prognostic factor. Finally, the predicative efficiency of this model was well confirmed in an independent external HNSCC cohort.

Polyphenol-Based Nanoparticles for Intracellular Protein Delivery via Competing Supramolecular Interactions.

Intracellular delivery of proteins is a promising strategy for regulating cellular behavior and therefore has attracted interest for biomedical applications. Despite the emergence of various nanoparticle-based intracellular delivery approaches, it remains challenging to engineer a versatile delivery system capable of responding to various physiological triggers without the need for complex chemical synthesis of the delivery system. Herein, we develop a template-mediated supramolecular assembly strategy to synthesize protein-polyphenol nanoparticles (NPs) capable of endosomal escape and subsequent protein release in the cytosol. These NPs are stable in serum and undergo surface charge reversal from negative to positive in acidic environments, leading to spontaneous endosomal escape. In the cytosol, endogenous small peptides and amino acids with relatively high charge densities, such as glutathione, trigger NP disassembly through competitive supramolecular interactions, thereby releasing functional bioactive proteins, as validated using cytochrome C and ß-galactosidase. The versatility of the present strategy in terms of nanoparticle size, protein type, and functional protein delivery makes this a promising platform for potential application in the field of protein therapeutics.

Particle engineering enabled by polyphenol-mediated supramolecular networks.

We report a facile strategy for engineering diverse particles based on the supramolecular assembly of natural polyphenols and a self-polymerizable aromatic dithiol. In aqueous conditions, uniform and size-tunable supramolecular particles are assembled through π-π interactions as mediated by polyphenols. Owing to the high binding affinity of phenolic motifs present at the surface, these particles allow for the subsequent deposition of various materials (i.e., organic, inorganic, and hybrid components), producing a variety of monodisperse functional particles. Moreover, the solvent-dependent disassembly of the supramolecular networks enables their removal, generating a wide range of corresponding hollow structures including capsules and yolk-shell structures. The versatility of these supramolecular networks, combined with their negligible cytotoxicity provides a pathway for the rational design of a range of particle systems (including core-shell, hollow, and yolk-shell) with potential in biomedical and environmental applications.

Upconversion Nanoparticle Powered Microneedle Patches for Transdermal Delivery of siRNA.

Microneedles (MNs) permit the delivery of nucleic acids like small interfering RNA (siRNA) through the stratum corneum and subsequently into the skin tissue. However, skin penetration is only the first step in successful implementation of siRNA therapy. These delivered siRNAs need to be resistant to enzymatic degradation, enter target cells, and escape the endosome-lysosome degradation axis. To address this challenge, this article introduces a nanoparticle-embedding MN system that contains a dissolvable hyaluronic acid (HA) matrix and mesoporous silica-coated upconversion nanoparticles (UCNPs@mSiO2 ). The mesoporous silica (mSiO2 ) shell is used to load and protect siRNA while the upconversion nanoparticle (UCNP) core allows the tracking of MN skin penetration and NP diffusion through upconversion luminescence imaging or optical coherence tomography (OCT) imaging. Once inserted into the skin, the HA matrix dissolves and UCNPs@mSiO2 diffuse in the skin tissue before entering the cells for delivering the loaded genes. As a proof of concept, this system is used to deliver molecular beacons (MBs) and siRNA targeting transforming growth factor-beta type I receptor (TGF-ßRI) that is potentially used for abnormal scar treatment.

Spray Assembly of Metal-Phenolic Networks: Formation, Growth, and Applications.

Hybrid conformal coatings, such as metal-phenolic networks (MPNs) that are constructed from the coordination-driven assembly of natural phenolic ligands, are of interest in areas including biomedicine, separations, and energy. To date, most MPN coatings have been prepared by immersing substrates in solutions containing the phenolic ligands and metal ions, which is a suitable method for coating small or flexible objects. In contrast, more industrially relevant methods for coating and patterning large substrates, such as spray assembly, have been explored to a lesser extent toward the fabrication of MPNs, particularly regarding the effect of process variables on MPN growth. Herein, a spray assembly method was used to fabricate MPN coatings with various phenolic building blocks and metal ions and their formation and patterning were explored for different applications. Different process parameters including solvent, pH, and metal-ligand pair allowed for control over the film properties such as thickness and roughness. On the basis of these investigations, a potential route for the formation of spray-assembled MPN films was proposed. Conditions favoring the formation of bis complexes could produce thicker coatings than those favoring the formation of mono or tris complexes. Finally, the spray-assembled MPNs were used to generate superhydrophilic membranes for oil-water separation and colorless films for UV shielding. The present study provides insights into the chemistry of MPN assembly and holds promise for advancing the fabrication of multifunctional hybrid materials.