Bootstrapping octagons in reduced kinematics from A2A_2 cluster algebras

Multi-loop scattering amplitudes/null polygonal Wilson loops in ${\mathcal N}=4$ super-Yang-Mills are known to simplify significantly in reduced kinematics, where external legs/edges lie in an $1+1$ dimensional subspace of Minkowski spacetime (or boundary of the $\rm AdS_3$ subspace). Since the edges of a $2n$-gon with even and odd labels go along two different null directions, the kinematics is reduced to two copies of $G(2,n)/T \sim A_{n{-}3}$. In the simplest octagon case, we conjecture that all loop amplitudes and Feynman integrals are given in terms of two overlapping $A_2$ functions (a special case of two-dimensional harmonic polylogarithms): in addition to the letters $v, 1+v, w, 1+w$ of $A_1 \times A_1$, there are two letters $v-w, 1- v w$ mixing the two sectors but they never appear together in the same term; these are the reduced version of four-mass-box algebraic letters. Evidence supporting our conjecture includes all known octagon amplitudes as well as new computations of multi-loop integrals in reduced kinematics. By leveraging this alphabet and conditions on first and last entries, we initiate a bootstrap program in reduced kinematics: within the remarkably simple space of overlapping $A_2$ functions, we easily obtain octagon amplitudes up to two-loop NMHV and three-loop MHV. We also briefly comment on the generalization to $2n$-gons in terms of $A_2$ functions and beyond.Comment: 26 pages, several figures and tables, an ancilary fil

SRDA-Net: Super-Resolution Domain Adaptation Networks for Semantic Segmentation

Recently, Unsupervised Domain Adaptation was proposed to address the domain shift problem in semantic segmentation task, but it may perform poor when source and target domains belong to different resolutions. In this work, we design a novel end-to-end semantic segmentation network, Super-Resolution Domain Adaptation Network (SRDA-Net), which could simultaneously complete super-resolution and domain adaptation. Such characteristics exactly meet the requirement of semantic segmentation for remote sensing images which usually involve various resolutions. Generally, SRDA-Net includes three deep neural networks: a Super-Resolution and Segmentation (SRS) model focuses on recovering high-resolution image and predicting segmentation map; a pixel-level domain classifier (PDC) tries to distinguish the images from which domains; and output-space domain classifier (ODC) discriminates pixel label distributions from which domains. PDC and ODC are considered as the discriminators, and SRS is treated as the generator. By the adversarial learning, SRS tries to align the source with target domains on pixel-level visual appearance and output-space. Experiments are conducted on the two remote sensing datasets with different resolutions. SRDA-Net performs favorably against the state-of-the-art methods in terms of accuracy and visual quality. Code and models are available at https://github.com/tangzhenjie/SRDA-Net

Free-aldehyde neutralized and oligohyaluronan loaded bovine pericardium with improved anti-calcification and endothelialization for bioprosthetic heart valves

The number of patients with valvular heart disease is increasing yearly, and valve replacement is the most effective treatment, during which bioprosthetic heart valves (BHVs) are the most widely used. Commercial BHVs are mainly prepared with glutaraldehyde (Glut) cross-linked bovine pericardial or porcine aortic valves, but the residual free aldehyde groups in these tissues can cause calcification and cytotoxicity. Moreover, insufficient glycosaminoglycans (GAGs) in tissues can further reduce biocompatibility and durability. However, the anti-calcification performance and biocompatibility might be improved by blocking the free aldehyde groups and increasing the GAGs content in Glut-crosslinked tissues. In our study, adipic dihydrazide (ADH) was used to neutralize the residual free aldehyde groups in tissues and provide sites to blind with oligohyaluronan (OHA) to increase the content of GAGs in tissues. The modified bovine pericardium was evaluated for its content of residual aldehyde groups, the amount of OHA loaded, physical/chemical characteristics, biomechanical properties, biocompatibility, and in vivo anticalcification assay and endothelialization effects in juvenile Sprague-Dawley rats. The results showed that ADH could completely neutralize the free aldehyde groups in the Glut-crosslinked bovine pericardium, the amount of OHA loaded increased and the cytotoxicity was reduced. Moreover, the in vivo results also showed that the level of calcification and inflammatory response in the modified pericardial tissue was significantly reduced in a rat subcutaneous implantation model, and the results from the rat abdominal aorta vascular patch repair model further demonstrated the improved capability of the modified pericardial tissues for endothelialization. Furthermore, more α-SMA+ smooth muscle cells and fewer CD68+ macrophages infiltrated in the neointima of the modified pericardial patch. In summary, blocking free-aldehydes and loading OHA improved the anti-calcification, anti-inflammation and endothelialization properties of Glut-crosslinked BHVs and in particularly, this modified strategy may be a promising candidate for the next-generation of BHVs

Multifunctional nanoparticle-VEGF modification for tissue-engineered vascular graft to promote sustained anti-thrombosis and rapid endothelialization

Purpose: The absence of a complete endothelial cell layer is a well-recognized reason leading to small-diameter tissue-engineered vascular graft failure. Here we reported a multifunctional system consisting of chitosan (CS), Arg-Glu-Asp-Val (REDV) peptide, heparin, and vascular endothelial growth factor (VEGF) to achieve sustained anti-thrombosis and rapid endothelialization for decellularized and photo-oxidized bovine internal mammary arteries (DP-BIMA).Methods: CS-REDV copolymers were synthesized via a transglutaminase (TGase) catalyzed reaction. CS-REDV-Hep nanoparticles were formed by electrostatic self-assembly and loaded on the DP-BIMA. The quantification of released heparin and vascular endothelial growth factor was detected. Hemolysis rate, platelets adhesion, endothelial cell (EC) adhesion and proliferation, and MTT assay were performed in vitro. The grafts were then tested in a rabbit abdominal aorta interposition model for 3 months. The patency rates were calculated and the ECs regeneration was investigated by immunofluorescence staining of CD31, CD144, and eNOS antibodies.Results: The nanoparticle-VEGF system (particle size: 61.8 ± 18.3 nm, zeta-potential: +13.2 mV, PDI: .108) showed a sustained and controlled release of heparin and VEGF for as long as 1 month and exhibited good biocompatibility, a lower affinity for platelets, and a higher affinity for ECs in vitro. The nanoparticle-VEGF immobilized BIMA achieved 100% and 83.3% patency in a rabbit abdominal interposition model during 1 and 3 months, respectively, without any thrombogenicity and showed CD31, CD144, eNOS positive cell adhesion as early as 1 day. After 3 months, CD31, CD144, and eNOS positive cells covered almost the whole luminal surface of the grafts.Conclusion: The results demonstrated that the multifunctional nanoparticle-VEGF system can enhance the anti-thrombosis property and promote rapid endothelialization of small-diameter tissue-engineered vascular grafts. Utilizing nanoparticles to combine different kinds of biomolecules is an appropriate technology to improve the long-term patency of small-diameter tissue-engineered vascular grafts

Preliminary study of improving immune tolerance in vivo of bioprosthetic heart valves through a novel antigenic removal method

The durability of bioprosthetic heart valves is always compromised by the inherent antigenicity of biomaterials. Decellularization has been a promising approach to reducing the immunogenicity of biological valves. However, current methods are insufficient in eliminating all immunogenicity from the biomaterials, necessitating the exploration of novel techniques. In this study, we investigated using a novel detergent, fatty alcohol polyoxyethylene ether sodium sulfate (AES), to remove antigens from bovine pericardium. Our results demonstrated that AES treatment achieved a higher pericardial antigen removal rate than traditional detergent treatments while preserving the mechanical properties and biocompatibility of the biomaterials. Moreover, we observed excellent immune tolerance in the in vivo rat model. Overall, our findings suggest that AES treatment is a promising method for preparing biological valves with ideal clinical application prospects

Mechanisms of tumor-associated macrophages affecting the progression of hepatocellular carcinoma

Tumor-associated macrophages (TAMs) are essential components of the immune cell stroma of hepatocellular carcinoma. TAMs originate from monocytic myeloid-derived suppressor cells, peripheral blood monocytes, and kupffer cells. The recruitment of monocytes to the HCC tumor microenvironment is facilitated by various factors, leading to their differentiation into TAMs with unique phenotypes. TAMs can directly activate or inhibit the nuclear factor-κB, interleukin-6/signal transducer and signal transducer and activator of transcription 3, Wnt/β-catenin, transforming growth factor-β1/bone morphogenetic protein, and extracellular signal-regulated kinase 1/2 signaling pathways in tumor cells and interact with other immune cells via producing cytokines and extracellular vesicles, thus affecting carcinoma cell proliferation, invasive and migratory, angiogenesis, liver fibrosis progression, and other processes to participate in different stages of tumor progression. In recent years, TAMs have received much attention as a prospective treatment target for HCC. This review describes the origin and characteristics of TAMs and their mechanism of action in the occurrence and development of HCC to offer a theoretical foundation for further clinical research of TAMs

Feedback Refined Local-Global Network for Super-Resolution of Hyperspectral Imagery

Powered by advanced deep-learning technology, multi-spectral image super-resolution methods based on convolutional neural networks have recently achieved great progress. However, the single hyperspectral image super-resolution remains a challenging problem due to the high-dimensional and complex spectral characteristics of hyperspectral data, which make it difficult for general 2D convolutional neural networks to simultaneously capture spatial and spectral prior information. To deal with this issue, we propose a novel Feedback Refined Local-Global Network (FRLGN) for the super-resolution of hyperspectral image. To be specific, we develop a new Feedback Structure and a Local-Global Spectral block to alleviate the difficulty in spatial and spectral feature extraction. The Feedback Structure can transfer the high-level information to guide the generation process of low-level features, which is achieved by a recurrent structure with finite unfoldings. Furthermore, in order to effectively use the high-level information passed back, a Local-Global Spectral block is constructed to handle the feedback connections. The Local-Global Spectral block utilizes the feedback high-level information to correct the low-level feature from local spectral bands and generates powerful high-level representations among global spectral bands. By incorporating the Feedback Structure and Local-Global Spectral block, the FRLGN can fully exploit spatial-spectral correlations among spectral bands and gradually reconstruct high-resolution hyperspectral images. Experimental results indicate that FRLGN presents advantages on three public hyperspectral datasets