Global-Local Stepwise Generative Network for Ultra High-Resolution Image Restoration

While the research on image background restoration from regular size of degraded images has achieved remarkable progress, restoring ultra high-resolution (e.g., 4K) images remains an extremely challenging task due to the explosion of computational complexity and memory usage, as well as the deficiency of annotated data. In this paper we present a novel model for ultra high-resolution image restoration, referred to as the Global-Local Stepwise Generative Network (GLSGN), which employs a stepwise restoring strategy involving four restoring pathways: three local pathways and one global pathway. The local pathways focus on conducting image restoration in a fine-grained manner over local but high-resolution image patches, while the global pathway performs image restoration coarsely on the scale-down but intact image to provide cues for the local pathways in a global view including semantics and noise patterns. To smooth the mutual collaboration between these four pathways, our GLSGN is designed to ensure the inter-pathway consistency in four aspects in terms of low-level content, perceptual attention, restoring intensity and high-level semantics, respectively. As another major contribution of this work, we also introduce the first ultra high-resolution dataset to date for both reflection removal and rain streak removal, comprising 4,670 real-world and synthetic images. Extensive experiments across three typical tasks for image background restoration, including image reflection removal, image rain streak removal and image dehazing, show that our GLSGN consistently outperforms state-of-the-art methods.Comment: submmitted to Transactions on Image Processin

Training semantic long-term memory retrieval transfers to executive function and reading fluency

The retrieval of information from long-term memory is a fundamental cognitive ability, crucial for most aspects of successful human functioning. Whether and how long-term memory retrieval (LTMR) can be improved with training has clear societal importance but also theoretical value for furthering our understanding of underlying mechanisms. Here, we provide electrophysiological evidence for the plasticity of semantic LTMR. Thirty-five university students were randomly assigned to adaptive semantic LTMR training (using a Posner task) or to a non-adaptive version of the training. Before and after training they were assessed on measures of semantic LTMR, working memory, central executive function (interference control, switching), reading fluency, and fluid intelligence. Adaptive LTMR training (relative to non-adaptive training) led to significant improvements in semantic LTMR. The intervention group (in contrast to the control group) also showed a significant reduction in the mean amplitude of the N400 ERP component and 700–1000 ms measured during a semantic LTMR task, suggesting that changes in retrieval occurred at an early/automatic point and retrieval processing in semantic processing. Moreover, transfer effects were observed for switching, working memory and reading fluency, but not for interference control or fluid intelligence. These results point to the plasticity of semantic LTMR, and suggest that improvement in this ability can transfer to other domains for which LTMR is key

Deep interest shifting network with meta embeddings for fresh item recommendation

Nowadays, people have an increasing interest in fresh products such as new shoes and cosmetics. To this end, an E-commerce platform Taobao launched a fresh-item hub page on the recommender system, with which customers can freely and exclusively explore and purchase fresh items, namely, the New Tendency page. In this work, we make a first attempt to tackle the fresh-item recommendation task with two major challenges. First, a fresh-item recommendation scenario usually faces the challenge that the training data are highly deficient due to low page views. In this paper, we propose a deep interest-shifting network (DisNet), which transfers knowledge from a huge number of auxiliary data and then shifts user interests with contextual information. Furthermore, three interpretable interest-shifting operators are introduced. Second, since the items are fresh, many of them have never been exposed to users, leading to a severe cold-start problem. Though this problem can be alleviated by knowledge transfer, we further babysit these fully cold-start items by a relational meta-Id-embedding generator (RM-IdEG). Specifically, it trains the item id embeddings in a learning-to-learn manner and integrates relational information for better embedding performance. We conducted comprehensive experiments on both synthetic datasets as well as a real-world dataset. Both DisNet and RM-IdEG significantly outperform state-of-the-art approaches, respectively. Empirical results clearly verify the effectiveness of the proposed techniques, which are arguably promising and scalable in real-world applications

HemoglobinA1c Is a Risk Factor for Changes of Bone Mineral Density: A Mendelian Randomization Study

BackgroundAs a valuable blood glucose measurement, HemoglobinA1c (HbA1c) is of great clinical value for diabetes. However, in previous observational studies, studies on its effect on bone mineral density (BMD) have different results. This study aimed to use Mendelian randomization (MR) to assess the effect of HbA1c on bone mineral density and fracture risk, and try to further explore whether this association was achieved through glycemic or non-glycemic factors.MethodsTake HbA1c measurement as exposure, and BMD estimated from quantitative heel ultrasounds (eBMD) and bone fractures as outcomes. Two-Sample MR Analysis was conducted to assess the causal effect of HbA1C on heel BMD and risk fracture. Then, we performed the analysis using two subsets of these variants, one related to glycemic measurement and the other to erythrocyte indices.ResultsGenetically increased HbA1C was associated with the lower heel eBMD [odds ratio (OR) 0.91 (95% CI 0.87, 0.96) per %-unit, P = 3 × 10−4(IVW)]. Higher HbA1C was associated with lower heel eBMD when using only erythrocytic variants [OR 0.87 (0.82, 0.93), P=2× 10−5(IVW)]; However, when using only glycemic variants, this casual association does not hold. In further MR analysis, we test the association of erythrocytic traits with heel eBMD.ConclusionOur study revealed the significant causal effect of HbA1c on eBMD, and this causal link might achieve through non-glycemic pathways (erythrocytic indices)

Therapeutic potential and mechanisms of mesenchymal stem cell-derived exosomes as bioactive materials in tendon–bone healing

Abstract Tendon–bone insertion (TBI) injuries, such as anterior cruciate ligament injury and rotator cuff injury, are the most common soft tissue injuries. In most situations, surgical tendon/ligament reconstruction is necessary for treating such injuries. However, a significant number of cases failed because healing of the enthesis occurs through scar tissue formation rather than the regeneration of transitional tissue. In recent years, the therapeutic potential of mesenchymal stem cells (MSCs) has been well documented in animal and clinical studies, such as chronic paraplegia, non-ischemic heart failure, and osteoarthritis of the knee. MSCs are multipotent stem cells, which have self-renewability and the ability to differentiate into a wide variety of cells such as chondrocytes, osteoblasts, and adipocytes. Numerous studies have suggested that MSCs could promote angiogenesis and cell proliferation, reduce inflammation, and produce a large number of bioactive molecules involved in the repair. These effects are likely mediated by the paracrine mechanisms of MSCs, particularly through the release of exosomes. Exosomes, nano-sized extracellular vesicles (EVs) with a lipid bilayer and a membrane structure, are naturally released by various cell types. They play an essential role in intercellular communication by transferring bioactive lipids, proteins, and nucleic acids, such as mRNAs and miRNAs, between cells to influence the physiological and pathological processes of recipient cells. Exosomes have been shown to facilitate tissue repair and regeneration. Herein, we discuss the prospective applications of MSC-derived exosomes in TBI injuries. We also review the roles of MSC–EVs and the underlying mechanisms of their effects on promoting tendon–bone healing. At last, we discuss the present challenges and future research directions. Graphical Abstrac

Photocatalytic and Superhydrophobic Nanoporous Membranes for Emulsion Separation and Removal of Pesticides and Pharmaceutical Products

Metal organic framework (MOF)-derivatives have a larger specific surface area, higher porosity, tunable pore size, higher conductivity, good stability, more exposed active species, etc., but few literature are reported about their application potential in micropollutant separation and removal. In view of this, a robust MOF derivative-based photocatalytic superhydrophobic membrane (D6/TiO2/MoS2/NiCo-NC/PVDF) was successfully fabricated for the first time through solvothermal synthesis and chemical modification, combined with a negative pressure-assisted loading approach. (1) The MoS2-doping strategy effectively avoided the collapse and coarsening of cauliflower-like MOFs during the calcination phase and simultaneously ensured the uniform distribution of metal particles in MOF-derived carbons. (2) The synergistic catalysis of the NiCo-MOF derivative, MoS2, and TiO2 enhanced the transfer efficiency of electrons and free radicals, achieving efficient in situ degradation of pesticides and pharmaceutical and personal care products. (3) The introduction of sodium alginate greatly improved the adhesion between the coating and polyvinylidene fluoride (PVDF) membrane and simultaneously enhanced the growth of MOFs through complexation. (4) The cauliflower-like MOF-derived carbon skeleton with higher surface areas and micronanoporosity combined with a heterogeneous MoS2 structure provided a large specific surface area and enough adsorption sites for various pollutants. High thermal calcination treatment greatly enhanced MOF growth rate, thus resulting in a flaky structure with high regularity and a large specific area. (5) The ultralow surface energy of interlaced siloxane molecules endowed the hybrid membrane with robust superhydrophobicity and superoleophilicity, always maintaining superhydrophobicity after long-time photodegradation. The final membrane achieved continuous emulsion separation and a photocatalytic self-cleaning property. The separation efficiency of the hybrid membrane for emulsions was still up to 97% after reuse for 120 cycles, and it could degrade 86.5% PRO, 90.1% ACE, 92.1% ASP, and 94.3% SMZ, respectively, with the initial concentration of 10 mg/L. The driving forces for oil–water separation and decontamination of the D6/TiO2/MoS2/NiCo-NC/PVDF membrane mainly involved the grasping forces of dodecamethylcyclohexasiloxane, capillary force of inner pores, electrostatic interaction, hydrogen bond interaction, partial p-π conjugation, van der Waals force, and lipophilicity

3D-printed hydrogel particles containing PRP laden with TDSCs promote tendon repair in a rat model of tendinopathy

Abstract Long-term chronic inflammation after Achilles tendon injury is critical for tendinopathy. Platelet-rich plasma (PRP) injection, which is a common method for treating tendinopathy, has positive effects on tendon repair. In addition, tendon-derived stem cells (TDSCs), which are stem cells located in tendons, play a major role in maintaining tissue homeostasis and postinjury repair. In this study, injectable gelatine methacryloyl (GelMA) microparticles containing PRP laden with TDSCs (PRP–TDSC–GM) were prepared by a projection-based 3D bioprinting technique. Our results showed that PRP–TDSC–GM could promote tendon differentiation in TDSCs and reduce the inflammatory response by downregulating the PI3K–AKT pathway, thus promoting the structural and functional repair of tendons in vivo. Graphical Abstrac