Separable Microneedle for Integrated Hyperglycemia Sensing and Photothermal Responsive Metformin Release.

Microdevices that offer hyperglycemia monitoring and controllable drug delivery are urgently needed for daily diabetes management. Herein, a theranostic separable double-layer microneedle (DLMN) patch consisting of a swellable GelMA supporting base layer for glycemia sensing and a phase-change material (PCM) arrowhead layer for hyperglycemia regulation has been fabricated. The Cu-TCPP(Fe)/glucose oxidase composite and 3,3',5,5'-tetramethylbenzidine coembedded in the supporting base layer permit a visible color shift at the base surface in the presence of glucose via a cascade reaction, allowing for the in situ detection of glucose in interstitial fluid. The PCM arrowhead layer is encapsulated with water monodispersity melanin nanoparticles from Sepia officinalis and metformin that is imparted with a near-infrared ray photothermal response feature, which is beneficial to the controllable release of metformin for suppression of hyperglycemia. By applying the DLMN patch to the streptozotocin-induced type 2 diabetic Sprague-Dawley rat model, the results demonstrated that it can effectively extract dermal interstitial fluid, read out glucose levels, and regulate hyperglycemia. This DLMN-integrated portable colorimetric sensor and self-regulated glucose level hold great promise for daily diabetes management.

HPRN: Holistic Prior-Embedded Relation Network for Spectral Super-Resolution.

Spectral super-resolution (SSR) refers to the hyperspectral image (HSI) recovery from an RGB counterpart. Due to the one-to-many nature of the SSR problem, a single RGB image can be reprojected to many HSIs. The key to tackle this ill-posed problem is to plug into multisource prior information such as the natural spatial context prior of RGB images, deep feature prior, or inherent statistical prior of HSIs so as to effectively alleviate the degree of ill-posedness. However, most current approaches only consider the general and limited priors in their customized convolutional neural networks (CNNs), which leads to the inability to guarantee the confidence and fidelity of reconstructed spectra. In this article, we propose a novel holistic prior-embedded relation network (HPRN) to integrate comprehensive priors to regularize and optimize the solution space of SSR. Basically, the core framework is delicately assembled by several multiresidual relation blocks (MRBs) that fully facilitate the transmission and utilization of the low-frequency content prior of RGBs. Innovatively, the semantic prior of RGB inputs is introduced to mark category attributes, and a semantic-driven spatial relation module (SSRM) is invented to perform the feature aggregation of clustered similar ranges for refining recovered characteristics. In addition, we develop a transformer-based channel relation module (TCRM), which breaks the habit of employing scalars as the descriptors of channelwise relations in the previous deep feature prior and replaces them with certain vectors to make the mapping function more robust and smoother. In order to maintain the mathematical correlation and spectral consistency between hyperspectral bands, the second-order prior constraints (SOPCs) are incorporated into the loss function to guide the HSI reconstruction. Finally, extensive experimental results on four benchmarks demonstrate that our HPRN can reach the state-of-the-art performance for SSR quantitatively and qualitatively. Furthermore, the effectiveness and usefulness of the reconstructed spectra are verified by the classification results on the remote sensing dataset. Codes are available at https://github.com/Deep-imagelab/HPRN.

Deep Hybrid 2-D-3-D CNN Based on Dual Second-Order Attention With Camera Spectral Sensitivity Prior for Spectral Super-Resolution.

A largely ignored fact in spectral super-resolution (SSR) is that the subsistent mapping methods neglect the auxiliary prior of camera spectral sensitivity (CSS) and only pay attention to wider or deeper network framework design while ignoring to excavate the spatial and spectral dependencies among intermediate layers, hence constraining representational capability of convolutional neural networks (CNNs). To conquer these drawbacks, we propose a novel deep hybrid 2-D-3-D CNN based on dual second-order attention with CSS prior (HSACS), which can excavate sufficient spatial-spectral context information. Specifically, dual second-order attention embedded in the residual block for more powerful spatial-spectral feature representation and relation learning is composed of a brand new trainable 2-D second-order channel attention (SCA) or 3-D second-order band attention (SBA) and a structure tensor attention (STA). Concretely, the band and channel attention modules are developed to adaptively recalibrate the band-wise and interchannel features via employing second-order band or channel feature statistics for more discriminative representations. Besides, the STA is promoted to rebuild the significant high-frequency spatial details for enough spatial feature extraction. Moreover, the CSS is first employed as a superior prior to avoid its effect of SSR quality, on the strength of which the resolved RGB can be calculated naturally through the super-reconstructed hyperspectral image (HSI); then, the final loss consists of the discrepancies of RGB and the HSI as a finer constraint. Experimental results demonstrate the superiority and progressiveness of the presented approach in terms of quantitative metrics and visual effect over SOTA SSR methods.

Microneedle Array Encapsulated with Programmed DNA Hydrogels for Rapidly Sampling and Sensitively Sensing of Specific MicroRNA in Dermal Interstitial Fluid.

Author: Please verify that the changes made to improve the English still retain your original meaning.Detection of microRNA (miRNA) in dermal interstitial fluid (ISF) has emerged as clinically useful in health status monitoring. However, it remains a great challenge owing to the difficult sampling and low abundance. Here, we report a DNA hydrogel microneedles (MNs) array to realize rapid enrichment and sensitive detection of miRNA in ISF. The MNs' patch consists of methacrylate hyaluronic acid (MeHA) equipped with a smart DNA circuit hydrogels' system (MeHA/DNA), in which an appropriate miRNA input enables triggering a cascading toehold-mediated DNA displacement reaction to catalytically cleave cross-linking points to generate amplified fluorescence (FL) for miRNA detection. The MeHA/DNA-MNs patch with high mechanical strength can extract adequate ISF in a short time (0.97 ± 0.2 mg in 5 min) in vivo because of its supreme water affinity. Additionally, the cascading toehold-mediated DNA displacement signal amplification reaction allows for sensitive detection of the low-abundant miRNAs down to 241.56 pM. The DNA hydrogels' MNs present potential for minimally invasive personalized diagnosis and real-time health monitoring in clinical applications.

Engineering Metal-Organic Framework Hybrid AIEgens with Tumor-Activated Accumulation and Emission for the Image-Guided GSH Depletion ROS Therapy.

Aggregation-induced emission (AIE)-active luminogens (AIEgens) have demonstrated exciting potential for the application in cancer phototheranostics. However, simultaneously achieving tumor-activated bright emission, enhanced reactive oxygen species (ROS) generation, high tumor accumulation, and minimized ROS depletion remains challenging. Here, a metal-organic framework (MOF) hybrid AIEgen theranostic platform is designed, termed A-NUiO@DCDA@ZIF-Cu, composed of an AIEgen-loaded hydrophobic UiO-66 (A-NUiO@DCDA) core and a Cu-doped hydrophilic ZIF-8 (ZIF-Cu) shell. The fluorescence emission and therapeutic ROS activity of AIEgens are restrained during delivery. After uptake by tumor tissues, ZIF-Cu decomposition occurs in response to an acidic tumor microenvironment (TME), and the hydrophobic A-NUiO@DCDA cores self-assemble into large particles, extremely increasing the tumor accumulation of AIEgens. This results in enhanced fluorescence imaging (FLI) and highly improved 1O2 generation ability during photodynamic therapy (PDT). Meanwhile, the released Cu2+ reacts to glutathione (GSH) to generate Cu+, which provides an extra chemodynamic therapy (CDT) function through Fenton-like reactions with overexpressed H2O2, resulting in the GSH depletion-enhanced ROS therapy. As a result of these characteristics, the MOF hybrid AIEgens can selectively kill tumors with excellent efficacy.

A Sample and Detection Microneedle Patch for Psoriasis MicroRNA Biomarker Analysis in Interstitial Fluid.

Skin interstitial fluid (ISF) containing a great variety of molecular biomarkers derived from cells and subcutaneous blood capillaries has recently emerged as a clinically potential component for early diagnosis of a wide range of diseases; however, the minimally invasive sampling and detection of cell-free biomarkers in ISF is still a key challenge. Herein, we developed microneedles (MNs) that consist of gelatin methacryloyl (GelMA) and graphene oxide (GO) for the enrichment and sensitive detection of multiple microRNA (miRNA) biomarkers from skin ISF. The GO-GelMA MNs exhibited robust mechanical properties, fast sampling kinetics, and large swelling capacity, which enabled collecting ISF volume high to 21.34 µL in 30 min, facilitating effective miRNA analysis. It preliminarily realized the sensitive detection of three types of psoriasis-related miRNAs biomarkers either on the patch itself or in solution after release from the hydrogel by combining catalytic hairpin assembly signal amplification reaction. The automated and minimally invasive ISF miRNA detection technology of GO-GelMA MNs has great potential to monitor cell-free clinically informative biomarkers for personalized diagnosis and prognosis.

Programmable Polymeric Microneedles for Combined Chemotherapy and Antioxidative Treatment of Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic inflammatory joint disease. Antioxidative treatment combined with chemotherapy holds great promise for RA treatment, and the ability to efficiently deliver drugs and antioxidants to the RA synovial joint is highly desired. Herein, we developed a programmable polymeric microneedle (MN) platform for transdermal delivery of methotrexate (MTX) and reactive oxygen species (ROS) scavengers for RA treatment. The biodegradable MNs made of polyvinylpyrrolidone (PVP) were incorporated with polydopamine/manganese dioxide (termed PDA@MnO2) and MTX. After insertion into skin tissue, the MNs degraded, thus enabling release of loaded MTX and PDA@MnO2. The PDA@MnO2 could be utilized as an MRI contrast agent in the RA synovial microenvironment. It also acted as a robust antioxidant to remove ROS and decrease RA inflammation, which when combined with the MTX-mediated chemotherapy led to an ideal outcome for RA treatments in a murine model. This work not only represents a valuable MN-assisted RA therapeutic agent transdermal delivery approach but also opens a new avenue for chemotherapy and antioxidative synergistic treatment of RA.