Synthesis of 12-Connected Three-Dimensional Covalent Organic Framework with lnj Topology.

The structural exploration of three-dimensional covalent organic frameworks (3D COFs) is of great significance to the development of COF materials. Different from structurally diverse MOFs, which have a variety of connectivity (3-24), now the valency of 3D COFs is limited to only 4, 6, and 8. Therefore, the exploration of organic building blocks with higher connectivity is a necessary path to broaden the scope of 3D COF structures. Herein, for the first time, we have designed and synthesized a 12-connected triptycene-based precursor (triptycene-12-CHO) with 12 symmetrical distributions of aldehyde groups, which is also the highest valency reported until now. Based on this unique 12-connected structure, we have successfully prepared a novel 3D COF with lnj topology (termed 3D-lnj-COF). The as-synthesized 3D COF exhibits honeycomb main pores and permanent porosity with a Brunauer-Emmett-Teller surface area of 1159.6 m2 g-1. This work not only provides a strategy for synthesizing precursors with a high connectivity but also provides inspiration for enriching the variety of 3D COFs.

A Self-Adaptive and Regenerable Hydrogel Interfacial Evaporator with Adjustable Evaporation Area for Solar Water Purification.

Solar-driven interfacial evaporation is a potential water purification solution. Here, a novel regenerable hydrogel interfacial evaporator is designed with tunable water production. Such an evaporator is fabricated by readily mixing hydroxypropyl chitosan (HPCS) and dibenzaldehyde-functional poly(ethylene glycol) (DF-PEG) at ambient conditions. Dynamic Schiff base bonds bestow on the HPCS/DF-PEG hydrogel (HDH) evaporator self-adaptivity and pH responsiveness. The as-prepared HDH is enabled to spontaneously change shape to adapt to different molds, endowing the evaporator with adjustable evaporation area. The water production performance of the intelligent evaporator is first evaluated using tunable evaporation index (TEI, the tunable evaporated water mass per hour), which can be altered from 0 kg h-1 to 3.21 kg h-1 under one sun. Besides, the large-scale evaporator can be expediently fabricated by virtue of the self-adaptivity. Benefiting from the pH responsiveness, the HDH evaporator is successfully regenerated with the removal of organic dye by the liquefaction-dialysis-regeneration operations. Meanwhile, the re-created evaporator maintains the self-adaptive characteristic and almost constant water evaporation rate compared to that of the initial evaporator. Therefore, this distinctive concept provides a facile strategy to develop smart and recyclable solar-driven interfacial evaporators for flexible water purification.

Liquid Crystalline Nanoparticles via Polymerization-Induced Self-Assembly: Morphology Evolution and Function Regulation.

Liquid crystalline nanoparticles (LC NPs) are a kind of polymer NPs with LC mesogens, which can form special anisotropic morphologies due to the influence of LC ordering. Owing to the stimuli-responsiveness of the LC blocks, LC NPs show abundant morphology evolution behaviors in response to external regulation. LC NPs have great application potential in nano-devices, drug delivery, special fibers and other fields. Polymerization-induced self-assembly (PISA) method can synthesize LC NPs at high solid content, reducing the harsh demand for reaction solvent of the LC polymers, being a better choice for large-scale production. In this review, we introduced recent research progress of PISA-LC NPs by dividing them into several parts according to the LC mesogen, and discussed the improvement of experimental conditions and the potential application of these polymers.

Transthyretin attenuates TDP-43 proteinopathy by autophagy activation via ATF4 in FTLD-TDP.

TAR DNA-binding protein-43 (TDP-43) proteinopathies are accompanied by the pathological hallmark of cytoplasmic inclusions in the neurodegenerative diseases, including frontal temporal lobar degeneration-TDP and amyotrophic lateral sclerosis. We found that transthyretin accumulates with TDP-43 cytoplasmic inclusions in frontal temporal lobar degeneration-TDP human patients and transgenic mice, in which transthyretin exhibits dramatic expression decline in elderly mice. The upregulation of transthyretin expression was demonstrated to facilitate the clearance of cytoplasmic TDP-43 inclusions through autophagy, in which transthyretin induces autophagy upregulation via ATF4. Of interest, transthyretin upregulated ATF4 expression and promoted ATF4 nuclear import, presenting physical interaction. Neuronal expression of transthyretin in frontal temporal lobar degeneration-TDP mice restored autophagy function and facilitated early soluble TDP-43 aggregates for autophagosome targeting, ameliorating neuropathology and behavioural deficits. Thus, transthyretin conducted two-way regulations by either inducing autophagy activation or escorting TDP-43 aggregates targeted autophagosomes, suggesting that transthyretin is a potential modulator therapy for neurological disorders caused by TDP-43 proteinopathy.

The interplay between diabetes Mellitus and soft tissue infections in general surgical patients.

BACKGROUND: Diabetes mellitus (DM) is a worldwide pandemic affecting 500 million people. It is known to be associated with increased susceptibility to soft tissue infections (STI). Despite being a major public health burden, the literature relating the effects of DM and the presentation, severity and healing of STIs in general surgical patients remain limited. METHOD: We conducted a retrospective review of all patients admitted with STI in a tertiary teaching hospital over a 12-month period. Patient demographics and surgical outcomes were collected and analysed. RESULTS: During the study period, 1059 patients were admitted for STIs (88% required surgery). DM was an independent risk factor for LOS. Diabetic patients presented with higher body-mass index (28 vs. 26), larger abscess size (24 vs. 14 cm2) and had a longer length of stay (4.4 days vs. 2.9 days). They also underwent a higher proportion of wide debridement and application of negative pressure wound therapy (42% vs. 35%). More diabetic patients underwent subsequent re-operation within the same sitting (8 vs. 4). Diabetic patients were two times more likely to present with carbuncles (p = 0.02). CONCLUSION: The incidence of STIs among DM patients represent a significant disease burden, surgeons should consider intensive patient counselling and partnering with primary care providers in order to help reduce the incidence of future STI admissions based upon lifestyle modification and glucose control.

Naturally sourced hydrogels: emerging fundamental materials for next-generation healthcare sensing.

The flourishing development of flexible healthcare sensing systems is inseparable from the fundamental materials with application-oriented mechanical and electrical properties. Thanks to continuous inspiration from our Mother Nature, flexible hydrogels originating from natural biomass are attracting growing attention for their structural and functional designs owing to their unique chemical, physical and biological properties. These highly efficient architectural and functional designs enable them to be the most promising candidates for flexible electronic sensing devices. This comprehensive review focuses on the recent advances in naturally sourced hydrogels for constructing multi-functional flexible sensors and healthcare applications thereof. We first briefly introduce representative natural polymers, including polysaccharides, proteins, and polypeptides, and summarize their unique physicochemical properties. The design principles and fabrication strategies for hydrogel sensors based on these representative natural polymers are outlined after the fundamental material properties required in healthcare sensing applications are presented. We then highlight the various fabrication techniques of natural hydrogels for sensing devices, and illustrate the representative examples of wearable or implantable bioelectronics for pressure, strain, temperature, or biomarker sensing in the field of healthcare systems. Finally, concluding remarks on challenges and prospects in the development of natural hydrogel-based flexible sensors are provided. We hope that this review will provide valuable information for the development of next-generation bioelectronics and build a bridge between the natural hydrogels as fundamental matter and multi-functional healthcare sensing as an applied target to accelerate new material design in the near future.

A Versatile Theranostic Nanoplatform with Aggregation-Induced Emission Properties: Fluorescence Monitoring, Cellular Organelle Targeting, and Image-Guided Photodynamic Therapy.

Photosensitizers (PSs) play a key role in the photodynamic therapy (PDT) of tumors. However, commonly used PSs are prone to intrinsic fluorescence aggregation-caused quenching and photobleaching; this drawback severely limits the clinical application of PDT, necessitating new phototheranostic agents. Herein, a multifunctional theranostic nanoplatform (named TTCBTA NP) is designed and constructed to achieve fluorescence monitoring, lysosome-specific targeting, and image-guided PDT. TTCBTA with a twisted conformation and D-A structure is encapsulated in amphiphilic Pluronic F127 to form nanoparticles (NPs) in ultrapure water. The NPs exhibit biocompatibility, high stability, strong near-infrared emission, and desirable reactive oxygen species (ROSs) production capacity. The TTCBTA NPs also show high-efficiency photo-damage, negligible dark toxicity, excellent fluorescent tracing, and high accumulation in lysosome for tumor cells. Furthermore, TTCBTA NPs are used to obtain fluorescence images with good resolution of MCF-7 tumors in xenografted BALB/c nude mice. Crucially, TTCBTA NPs present a strong tumor ablation ability and image-guided PDT effect by generating abundant ROSs upon laser irradiation. These results demonstrate that the TTCBTA NP theranostic nanoplatform may enable highly efficient near-infrared fluorescence image-guided PDT.

Structure-transferring edge-enhanced grid dehazing network.

The problem of image dehazing has received a great deal of attention in the computer vision community over the past two decades. Under haze conditions, due to the scattering of water vapor and dust particles in the air, the sharpness of the image is seriously reduced, making it difficult for many computer vision systems, such as those for object detection, object recognition, surveillance, driver assistance, etc. to do further process and operation. However, the previous dehazing methods usually have shortcomings such as poor brightness, color cast, removal of uncleanliness, halos, artifacts, and blurring. To address these problems, we propose a novel Structure-transferring Edge-enhanced Grid Dehazing Network (SEGDNet) in this study. An edge-preserving smoothing operator, a guided filter, is used to efficiently decompose the images into low-frequency image structure and high-frequency edges. The Low-frequency Grid Dehazing Subnetwork (LGDSn) is proposed to effectively preserve the low-frequency structure while dehazing. The High-frequency Edge Enhancement Subnetwork (HEESn) is also proposed to enhance the edges and details while removing the noise. The Low-and-High frequency Fusion Subnetwork (L&HFSn) is used to fuse the low-frequency and high-frequency results to obtain the final dehazed image. The experimental results on synthetic and real-world datasets demonstrate that our method outperforms the state-of-the-art methods in both qualitative and quantitative evaluations.

A Wax-Elastomer Superwetting Membrane with Controllable Permeability: Toward Separating a Crude Oil-in-Water Emulsion from an Oil Field.

Smart superwetting membranes with finely tunable properties have attracted increased attention recently. However, they mostly focus on controllable wettability rather than controllable permeability. Also, the oil/water separation performance is usually tested with laboratory-simulated samples, making it hard for the materials to meet practical applications. Herein, we fabricate thermally responsive superwetting membranes with wax, polystyrene-B-poly(ethylene-ran-butylene)-B-polys (SEBS, a kind of elastomer), and polydopamine (PDA) to realize emulsion separation with controllable permeability. Benefiting from the elasticity of SEBS and the fluidity difference of wax at different temperatures, the pore size of the membrane could be readily tuned, resulting in different permeability. The separation flux is 0 at ambient temperature (pore size 0.394 µm) and is over 100 L m-2 h-1 at a high temperature (pore size 0.477 µm). The membrane could realize the separation of simulated oil-in-water emulsions with efficiency above 99.4%. Furthermore, it successfully achieved crude oil-in-water emulsion separation from the oil field with oil residues of less than 300 mg L-1 in the temperature range of 60-80 °C, which is the actual working temperature adopted in industrial production. Such a polydopamine/wax-SEBS modified membrane with unprecedented controllable permeability can promote the development of the emulsion treatment field and provide a new direction for designing smart superwetting materials.

Co-La-Based Hole-Transporting Layers for Binary Organic Solar Cells with 18.82 % Efficiency.

Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is a widely used hole transporting layer (HTL) in organic solar cells (OSCs), but its acidity severely reduces the stability of devices. Until now, very few HTLs were developed to replace PEDOT:PSS toward stable and high-performance OSCs. Herein, a new cobalt-lanthanum (Co-La) inorganic system was reported as HTL to show a high conversion efficiency (PCE) of 18.82 %, which is among the top PCEs in binary OSCs. Since electron-rich outer shell of La atom can interact with Co atom to form charge transfer complex, the work function and conductivity of the Co-La system could be simultaneously enhanced compared to Co or La-based HTLs. This Co-La system could also be applied into other OSCs to show high performance. All these results demonstrate that binary Co-La systems as HTL can efficiently tackle the issue in hole transporting and show powerful application in OSCs to replace PEDOT:PSS.

Translation-invariant context-retentive wavelet reflection removal network.

It has been widely investigated for images taken through glass to remove unwanted reflections in deep learning. However, none of these methods have bad effects, but they all remove reflections in specific situations, and validate the results with their own datasets, e.g., several local places with strong reflections. These limitations will result in situations where real reflections in the world cannot be effectively eliminated. In this study, a novel Translation-invariant Context-retentive Wavelet Reflection Removal Network is proposed to address this issue. In addition to context and background, low-frequency sub-images still have a small amount of reflections. To enable background context retention and reflection removal, the low-frequency sub-images at each level are performed on the Context Retention Subnetwork (CRSn) after wavelet transform. Novel context level blending and inverse wavelet transform are proposed to remove reflections in low frequencies and retain background context recursively, which is of great help in restoring clean images. High-frequency sub-images with reflections are performed on the Detail-enhanced Reflection layer removal Subnetwork to complete reflection removal. In addition, in order to further separate the reflection layer and the transmission layer better, we also propose Detail-enhanced Reflection Information Transmission, through which the extracted features of reflection layer in high-frequency images can help the CRSn effectively separate the transmission layer and the reflection layer, so as to achieve the effects of removing reflection. The quantitative and visual experimental results on benchmark datasets demonstrate that the proposed method performs better than the state-of-the-art approaches.

Pedestrian detection using a translation-invariant wavelet residual dense super-resolution.

Pedestrian detection is an important research area and technology for car driving, gait recognition, and other applications. Although a lot of pedestrian detection techniques have been introduced, low-resolution imaging devices still exist in real life, so detection in low-resolution images remains a challenging problem. To address this issue, we propose a novel end-to-end Translation-invariant Wavelet Residual Dense Super-Resolution (TiWRD-SR) method to upscale LR images to SR images and then use Yolov4 for detection to address the low detection problem performance on low-resolution images. To make the enlarged SR image not only effectively distinguish the foreground and background of images but also highlight the characteristic structure of pedestrians, we decompose the image into low-frequency and high-frequency parts by stationary wavelet transform (SWT). The high- and low-frequency sub-images are trained through different network structures so that the network can reconstruct the high-frequency image edge information and the low-frequency image structure in a more detailed manner. In addition, a high-to-low branch information transmission (H2LBIT) is proposed to import high-frequency image edge information into the low-frequency network to make the reconstructed low-frequency structure more detailed. In addition, we also propose a novel loss function, which enables the SR network to focus on the reconstruction of image structure in the network by the characteristics of wavelet decomposition, thereby improving its detection performance. The experimental results indicate that the proposed TiWRD-SR can effectively improve detection performance.

Optical molecular imaging and theranostics in neurological diseases based on aggregation-induced emission luminogens.

Optical molecular imaging and image-guided theranostics benefit from special and specific imaging agents, for which aggregation-induced emission luminogens (AIEgens) have been regarded as good candidates in many biomedical applications. They display a large Stokes shift, high quantum yield, good biocompatibility, and resistance to photobleaching. Neurological diseases are becoming a substantial burden on individuals and society that affect over 50 million people worldwide. It is urgently needed to explore in more detail the brain structure and function, learn more about pathological processes of neurological diseases, and develop more efficient approaches for theranostics. Many AIEgens have been successfully designed, synthesized, and further applied for molecular imaging and image-guided theranostics in neurological diseases such as cerebrovascular disease, neurodegenerative disease, and brain tumor, which help us understand more about the pathophysiological state of brain through noninvasive optical imaging approaches. Herein, we focus on representative AIEgens investigated on brain vasculature imaging and theranostics in neurological diseases including cerebrovascular disease, neurodegenerative disease, and brain tumor. Considering different imaging modalities and various therapeutic functions, AIEgens have great potential to broaden neurological research and meet urgent needs in clinical practice. It will be inspiring to develop more practical and versatile AIEgens as molecular imaging agents for preclinical and clinical use on neurological diseases.

Catechol Moiety Integrated Tri-Aryl Type AIEgen for Visual and Quantitative Boronic Acid Detection.

Novel functional AIEgen based on three compact bound aryl skeletons is designed and synthesized. This tri-aryl type luminogen (TA-Catechol) embedded with catechol moiety responds rapidly to series of boronic acids. Real-time visual and quantitative dual-mode detection method is established for the first time with modest precision and low detection limit (8.0 µM). Detailed mechanistic discussion identifies tetra-coordinated boronic species as the key intermediate within sensing procedure. Wide range of organic boronic acids compatible with this strategy is displayed which is promising in high throughput screening technology. Furthermore, solid-state sensing capability of TA-Catechol is also demonstrated.

Antimicrobial Lignin-Based Polyurethane/Ag Composite Foams for Improving Wound Healing.

Antimicrobial materials are an urgent need for modern wound care in the clinic. Although traditional polyurethane foams have proven to be clinically valuable for wound treatment, their petroleum-originated preparation and bioinert nature have restricted their efficacy in biomedical applications. Here, we propose a simple one-step foaming method to prepare lignin-based polyurethane foams (LPUFs) in which fully biobased polyether polyols partially replace traditional petroleum-based raw materials. The trace amount of phenolic hydroxyl groups (about 4 mmol) in liquefied lignin acts as a direct reducing agent and capping agent to silver ions (less than 0.3 mmol), in situ forming silver nanoparticles (Ag NPs) within the LPUF skeleton. This newly proposed lignin polyurethane/Ag composite foam (named as Ag NP-LPUF) shows improved mechanical, thermal, and antibacterial properties. It is worth mentioning that the Ag NP-LPUF exhibits more than 99% antibacterial rate against Escherichia coli within 1 h and Staphylococcus aureus within 4 h. Evaluations in mice indicate that the antimicrobial composite foams can effectively promote wound healing of full-thickness skin defects. As a proof of concept, this antibacterial and biodegradable foam exhibits significant potential for clinical translation in wound care dressings.

Person Re-Identification with Improved Performance by Incorporating Focal Tversky Loss in AGW Baseline.

Person re-identification (re-ID) is one of the essential tasks for modern visual intelligent systems to identify a person from images or videos captured at different times, viewpoints, and spatial positions. In fact, it is easy to make an incorrect estimate for person re-ID in the presence of illumination change, low resolution, and pose differences. To provide a robust and accurate prediction, machine learning techniques are extensively used nowadays. However, learning-based approaches often face difficulties in data imbalance and distinguishing a person from others having strong appearance similarity. To improve the overall re-ID performance, false positives and false negatives should be part of the integral factors in the design of the loss function. In this work, we refine the well-known AGW baseline by incorporating a focal Tversky loss to address the data imbalance issue and facilitate the model to learn effectively from the hard examples. Experimental results show that the proposed re-ID method reaches rank-1 accuracy of 96.2% (with mAP: 94.5) and rank-1 accuracy of 93% (with mAP: 91.4) on Market1501 and DukeMTMC datasets, respectively, outperforming the state-of-the-art approaches.

Vision-Based Learning from Demonstration System for Robot Arms.

Robotic arms have been widely used in various industries and have the advantages of cost savings, high productivity, and efficiency. Although robotic arms are good at increasing efficiency in repetitive tasks, they still need to be re-programmed and optimized when new tasks are to be deployed, resulting in detrimental downtime and high cost. It is therefore the objective of this paper to present a learning from demonstration (LfD) robotic system to provide a more intuitive way for robots to efficiently perform tasks through learning from human demonstration on the basis of two major components: understanding through human demonstration and reproduction by robot arm. To understand human demonstration, we propose a vision-based spatial-temporal action detection method to detect human actions that focuses on meticulous hand movement in real time to establish an action base. An object trajectory inductive method is then proposed to obtain a key path for objects manipulated by the human through multiple demonstrations. In robot reproduction, we integrate the sequence of actions in the action base and the key path derived by the object trajectory inductive method for motion planning to reproduce the task demonstrated by the human user. Because of the capability of learning from demonstration, the robot can reproduce the tasks that the human demonstrated with the help of vision sensors in unseen contexts.

De Novo Design of Entropy-Driven Polymers Resistant to Bacterial Attachment via Multicomponent Reactions.

Nonbactericidal polymers that prevent bacterial attachment are important for public health, environmental protection, and avoiding the generation of superbugs. Here, inspired by the physical bactericidal process of carbon nanotubes and graphene derivatives, we develop nonbactericidal polymers resistant to bacterial attachment by using multicomponent reactions (MCRs) to introduce molecular "needles" (rigid aliphatic chains) and molecular "razors" (multicomponent structures) into polymer side chains. Computer simulation reveals the occurrence of spontaneous entropy-driven interactions between the bacterial bilayers and the "needles" and "razors" in polymer structures and provides guidance for the optimization of this type of polymers for enhanced resistibility to bacterial attachment. The blending of the optimized polymer with commercially available polyurethane produces a film with remarkably superior stability of the resistance to bacterial adhesion after wear compared with that of commercial mobile phone shells made by the Sharklet technology. This proof-of-concept study explores entropy-driven polymers resistant to bacterial attachment via a combination of MCRs, computer simulation, and polymer chemistry, paving the way for the de novo design of nonbactericidal polymers to prevent bacterial contamination.

The Hantzsch Reaction in Polymer Chemistry: From Synthetic Methods to Applications.

The Hantzcsh reaction is a robust four-component reaction for the efficient generation of 1,4-dihydropyridine (1,4-DHP) derivatives. Recently, this reaction has been introduced into polymer chemistry in order to develop polymers having 1,4-DHP structures in the main and/or side chains. The 1,4-DHP groups confer new properties/functions to the polymers. This mini-review summarizes the recent studies on the development of new functional polymers by using the Hantzsch reaction. Several synthetic approaches, including polycondensation, post-polymerization modification (PPM), monomer to polymer strategy, and one-pot strategy are introduced; different applications (protein conjugation, formaldehyde detection, drug carrier, and anti-bacterial adhesion) of the resulting polymers are emphasized. Meanwhile, the future development of the Hantzsch reaction in exploring new functional polymers is also discussed.

Recent Advances on Fabrication of Polymeric Composites Based on Multicomponent Reactions for Bioimaging and Environmental Pollutant Removal.

As the core of polymer chemistry, manufacture of functional polymers is one of research hotspots over the past several decades. Various polymers are developed for diverse applications due to their tunable structures and unique properties. However, traditional step-by-step preparation strategies inevitably involve some problems, such as separation, purification, and time-consuming. The multicomponent reactions (MCRs) are emerging as environmentally benign synthetic strategies to construct multifunctional polymers or composites with pendant groups and designed structures because of their features, such as efficient, fast, green, and atom economy. This mini review summarizes the latest advances about fabrication of multifunctional fluorescent polymers or adsorptive polymeric composites through different MCRs, including Kabachnik-Fields reaction, Biginelli reaction, mercaptoacetic acid locking imine reaction, Debus-Radziszewski reaction, and Mannich reaction. The potential applications of these polymeric composites in biomedical and environmental remediation are also highlighted. It is expected that this mini-review will promote the development preparation and applications of functional polymers through MCRs.