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Shengfang Bao, Hua Huang, Yingying Jin, Fei Ding, Zhen Yang, Xuemei Xu, Chenxi Liu, Xiqiong Han, Liping Wang, Jingyi Lu, Jiani Ma, Yanliang Jin Department of Rheumatology & Immunology, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, People’s Republic of ChinaCorrespondence: Yanliang Jin, Email jinyanliang@scmc.com.cnAbstract: Kikuchi-Fujimoto disease (KFD), also known as histiocytic necrotizing lymphadenitis, is a rare, benign, and self-limiting condition characterized by lymph node inflammation. While KFD is rarely associated with ocular manifestations, our case report highlights bilateral optic neuritis in a 13-year-old male patient with KFD. We also provide a comprehensive review of similar cases in the literature.Keywords: Kikuchi-Fujimoto disease, optic neuritis, neuromyelitis optica spectrum disorder, vision deficiency

Spike cameras, leveraging spike-based integration sampling and high temporal resolution, offer distinct advantages over standard cameras. However, existing approaches reliant on spike cameras often assume optimal illumination, a condition frequently unmet in real-world scenarios. To address this, we introduce SpikeNeRF, the first work that derives a NeRF-based volumetric scene representation from spike camera data. Our approach leverages NeRF's multi-view consistency to establish robust self-supervision, effectively eliminating erroneous measurements and uncovering coherent structures within exceedingly noisy input amidst diverse real-world illumination scenarios. The framework comprises two core elements: a spike generation model incorporating an integrate-and-fire neuron layer and parameters accounting for non-idealities, such as threshold variation, and a spike rendering loss capable of generalizing across varying illumination conditions. We describe how to effectively optimize neural radiance fields to render photorealistic novel views from the novel continuous spike stream, demonstrating advantages over other vision sensors in certain scenes. Empirical evaluations conducted on both real and novel realistically simulated sequences affirm the efficacy of our methodology. The dataset and source code are released at https://github.com/BIT-Vision/SpikeNeRF., Comment: Accepted by CVPR 2024

As a bio-inspired vision sensor, the spike camera emulates the operational principles of the fovea, a compact retinal region, by employing spike discharges to encode the accumulation of per-pixel luminance intensity. Leveraging its high temporal resolution and bio-inspired neuromorphic design, the spike camera holds significant promise for advancing computer vision applications. Saliency detection mimics the behavior of human beings and captures the most salient region from the scenes. In this paper, we investigate the visual saliency in the continuous spike stream for the first time. To effectively process the binary spike stream, we propose a Recurrent Spiking Transformer (RST) framework, which is based on a full spiking neural network. Our framework enables the extraction of spatio-temporal features from the continuous spatio-temporal spike stream while maintaining low power consumption. To facilitate the training and validation of our proposed model, we build a comprehensive real-world spike-based visual saliency dataset, enriched with numerous light conditions. Extensive experiments demonstrate the superior performance of our Recurrent Spiking Transformer framework in comparison to other spike neural network-based methods. Our framework exhibits a substantial margin of improvement in capturing and highlighting visual saliency in the spike stream, which not only provides a new perspective for spike-based saliency segmentation but also shows a new paradigm for full SNN-based transformer models. The code and dataset are available at \url{https://github.com/BIT-Vision/SVS}., Comment: Accepted by AAAI 2024

The fusion of a low-spatial-resolution hyperspectral image (LR-HSI) with a high-spatial-resolution multispectral image (HR-MSI) has garnered increasing research interest. However, most fusion methods solely focus on the fusion algorithm itself and overlook the degradation models, which results in unsatisfactory performance in practical scenarios. To fill this gap, we propose physics-inspired degradation models (PIDM) to model the degradation of LR-HSI and HR-MSI, which comprises a spatial degradation network (SpaDN) and a spectral degradation network (SpeDN). SpaDN and SpeDN are designed based on two insights. First, we employ spatial warping and spectral modulation operations to simulate lens aberrations, thereby introducing non-uniformity into the spatial and spectral degradation processes. Second, we utilize asymmetric downsampling and parallel downsampling operations to separately reduce the spatial and spectral resolutions of the images, thus ensuring the matching of spatial and spectral degradation processes with specific physical characteristics. Once SpaDN and SpeDN are established, we adopt a self-supervised training strategy to optimize the network parameters and provide a plug-and-play solution for fusion methods. Comprehensive experiments demonstrate that our proposed PIDM can boost the fusion performance of existing fusion methods in practical scenarios.

Multi-modal large language models(MLLMs) have achieved remarkable progress and demonstrated powerful knowledge comprehension and reasoning abilities. However, the mastery of domain-specific knowledge, which is essential for evaluating the intelligence of MLLMs, continues to be a challenge. Current multi-modal benchmarks for domain-specific knowledge concentrate on multiple-choice questions and are predominantly available in English, which imposes limitations on the comprehensiveness of the evaluation. To this end, we introduce CMMU, a novel benchmark for multi-modal and multi-type question understanding and reasoning in Chinese. CMMU consists of 3,603 questions in 7 subjects, covering knowledge from primary to high school. The questions can be categorized into 3 types: multiple-choice, multiple-response, and fill-in-the-blank, bringing greater challenges to MLLMs. In addition, we propose an evaluation strategy called Positional Error Variance for assessing multiple-choice questions. The strategy aims to perform a quantitative analysis of position bias. We evaluate seven open-source MLLMs along with GPT4-V, Gemini-Pro, and Qwen-VL-Plus. The results demonstrate that CMMU poses a significant challenge to the recent MLLMs. The data and code are available at https://github.com/FlagOpen/CMMU.

Deep priors have emerged as potent methods in hyperspectral image (HSI) reconstruction. While most methods emphasize space-domain learning using image space priors like non-local similarity, frequency-domain learning using image frequency priors remains neglected, limiting the reconstruction capability of networks. In this paper, we first propose a Hyperspectral Frequency Correlation (HFC) prior rooted in in-depth statistical frequency analyses of existent HSI datasets. Leveraging the HFC prior, we subsequently establish the frequency domain learning composed of a Spectral-wise self-Attention of Frequency (SAF) and a Spectral-spatial Interaction of Frequency (SIF) targeting low-frequency and high-frequency components, respectively. The outputs of SAF and SIF are adaptively merged by a learnable gating filter, thus achieving a thorough exploitation of image frequency priors. Integrating the frequency domain learning and the existing space domain learning, we finally develop the Correlation-driven Mixing Domains Transformer (CMDT) for HSI reconstruction. Extensive experiments highlight that our method surpasses various state-of-the-art (SOTA) methods in reconstruction quality and computational efficiency., Comment: 14 pages, 11 figures

Second-order optimizers, maintaining a matrix termed a preconditioner, are superior to first-order optimizers in both theory and practice. The states forming the preconditioner and its inverse root restrict the maximum size of models trained by second-order optimizers. To address this, compressing 32-bit optimizer states to lower bitwidths has shown promise in reducing memory usage. However, current approaches only pertain to first-order optimizers. In this paper, we propose the first 4-bit second-order optimizers, exemplified by 4-bit Shampoo, maintaining performance similar to that of 32-bit ones. We show that quantizing the eigenvector matrix of the preconditioner in 4-bit Shampoo is remarkably better than quantizing the preconditioner itself both theoretically and experimentally. By rectifying the orthogonality of the quantized eigenvector matrix, we enhance the approximation of the preconditioner's eigenvector matrix, which also benefits the computation of its inverse 4-th root. Besides, we find that linear square quantization slightly outperforms dynamic tree quantization when quantizing second-order optimizer states. Evaluation on various networks for image classification demonstrates that our 4-bit Shampoo achieves comparable test accuracy to its 32-bit counterpart while being more memory-efficient. The source code will be made available.

Accurately estimating scene lighting is critical for applications such as mixed reality. Existing works estimate illumination by generating illumination maps or regressing illumination parameters. However, the method of generating illumination maps has poor generalization performance and parametric models such as Spherical Harmonic (SH) and Spherical Gaussian (SG) fall short in capturing high-frequency or low-frequency components. This paper presents MixLight, a joint model that utilizes the complementary characteristics of SH and SG to achieve a more complete illumination representation, which uses SH and SG to capture low-frequency ambient and high-frequency light sources respectively. In addition, a special spherical light source sparsemax (SLSparsemax) module that refers to the position and brightness relationship between spherical light sources is designed to improve their sparsity, which is significant but omitted by prior works. Extensive experiments demonstrate that MixLight surpasses state-of-the-art (SOTA) methods on multiple metrics. In addition, experiments on Web Dataset also show that MixLight as a parametric method has better generalization performance than non-parametric methods.

Sparse matrix-vector multiplication (SpMV) is a crucial computing kernel with widespread applications in iterative algorithms. Over the past decades, research on SpMV optimization has made remarkable strides, giving rise to various optimization contributions. However, the comprehensive and systematic literature survey that introduces, analyzes, discusses, and summarizes the advancements of SpMV in recent years is currently lacking. Aiming to fill this gap, this paper compares existing techniques and analyzes their strengths and weaknesses. We begin by highlighting two representative applications of SpMV, then conduct an in-depth overview of the important techniques that optimize SpMV on modern architectures, which we specifically classify as classic, auto-tuning, machine learning, and mixed-precision-based optimization. We also elaborate on the hardware-based architectures, including CPU, GPU, FPGA, processing in Memory, heterogeneous, and distributed platforms. We present a comprehensive experimental evaluation that compares the performance of state-of-the-art SpMV implementations. Based on our findings, we identify several challenges and point out future research directions. This survey is intended to provide researchers with a comprehensive understanding of SpMV optimization on modern architectures and provide guidance for future work., Comment: 34 pages, 18 figures, 16 tables

The development of highly efficient and environmentally friendly solvents for dissolving cellulose, which is the most abundant natural polymer on Earth, remains a challenge, hindering its full utilization. Herein, a green protic ionic liquid, 1,1,3,3-tetramethylguanidinium methoxyacetate ([TMGH][MAA]), was found to exhibit attractive capacity to dissolve natural cellulose with an appropriate TMG/MAA molar ratio of 7 : 3 at 80 degrees C. The solubility of cotton linter and ultra-high molecular weight cotton fibers reached 13% (w/w) and 3% (w/w), respectively, surpassing that of most solvent systems currently used for the dissolution of cellulose. The experimental and simulation results verified that the excellent dissolution ability of [TMGH][MAA] for cellulose is mainly attributed to the destruction of the intrinsic hydrogen-bond networks in cellulose by the synergistic interactions of the [TMGH] cations and [MAA] anions with the hydroxyl groups in the cellulose chains, acting as highly efficient "intermolecular scissors". The superiority of this novel dissolution system was further demonstrated by the remarkable comprehensive properties of the regenerated cellulose film including satisfactory thermostability, high transparency, and excellent mechanical properties. Furthermore, the satisfactory recovery performance of this solvent highlights its significant feasibility for large-scale industrial manufacturing. The proposed [TMGH][MAA] in this study exhibits great potential as a next-generation processing solvent for dissolving, and thus processing cellulose, promoting the sustainable development of high-value-added cellulose materials.

Background: Systemic delivery of anti-tumor therapeutic agents to brain tumors is thwarted by the blood-brain barrier (BBB), an organotypic specialization of brain endothelial cells (ECs). A failure of pharmacological compounds to cross BBB is one culprit for the dismal prognosis of glioblastoma (GBM) patients. Identification of novel vascular targets to overcome the challenges posed by the BBB in tumors for GBM treatment is urgently needed. Methods: Temozolomide (TMZ) delivery was investigated in CT2A and PDGFB-driven RCAS/tv-a orthotopic glioma models. Transcriptome analysis was performed on ECs from murine gliomas. Mfsd2a deficient, Cav1 deficient, and Mfsd2a EC-specific inducible mice were developed to study the underlying molecular mechanisms. Results: We demonstrated that inhibiting Wnt signaling by LGK974 could increase TMZ delivery and sensitize glioma to chemotherapy in both murine glioma models. Transcriptome analysis of ECs from murine gliomas revealed that Wnt signaling inhibition enhanced vascular transcytosis as indicated by the upregulation of PLVAP and downregulation of MFSD2A. Mfsd2a deficiency in mice enhances TMZ delivery in tumors, whereas constitutive expression of Mfsd2a in ECs suppresses the enhanced TMZ delivery induced by Wnt pathway inhibition in murine glioma. In addition, Wnt signaling inhibition enhanced caveolin-1 (Cav1)-positive caveolae-mediated transcytosis in tumor ECs. Moreover, Wnt signaling inhibitor or Mfsd2a deficiency fails to enhance TMZ penetration in tumors from Cav1-deficient mice. Conclusions: These results demonstrated that Wnt signaling regulates MFSD2A-dependent TMZ delivery through a caveolae-mediated EC transcytosis pathway. Our findings identify Wnt signaling as a promising therapeutic target to improve drug delivery for GBM treatment.

Immobilizing catalyst system faces the challenge of balancing catalysts stability and exposure of active site in water treatment. In this study, a novel in-situ synthesis of monoclinic phase of titanium dioxide (TiO2(B)) in cellulose-derived carbon aerogel (TCA) is proposed for processing multi-task in water treat-ment. The homogeneous gelation reaction supported the high dispersion of TiO2(B) in carbon skeleton. Meanwhile, TiO2 acts as crosslinker to reinforce cellulose network, then the grain refinement of amor-phous TiO2 is limited to obtain TiO2(B) during carbonization. Benefiting from the reinforced structure, TCA remains the porous structure after carbonization and exposes more adsorption site than carbon aero-gel blended with anatase particles (ACA). The adsorption performance of TCA are 837.3 mg/g, 1156.2 mg/ g and 512.6 mg/g on methylene blue, malachite green and crystal violet, respectively. Compared with ACA, the superior interaction between TiO2 and graphite-like carbon improves the degradation rate of tetracycline from 1.3 x 10-3 min-1 to 8.6 x 10-3 min-1, and maintains the degradation efficiency in 3 rounds cyclic test. Besides, TCA also exhibits nearly twice to ACA on absorption capacity of differentoil. This facile in-situ synthesis method offers a new insight in fabricating carbon aerogel immobilized photocatalysts system for multi-task in water treatment., QC 20221206

Three-dimensional image analyses are required to improve the understanding of the regulation of blood vessel formation and heterogeneity. Currently, quantitation of 3D endothelial structures or vessel branches is often based on 2D projections of the images losing their volumetric information. Here, we developed SproutAngio, a Python-based open-source tool, for fully automated 3D segmentation and analysis of endothelial lumen space and sprout morphology. To test the SproutAngio, we produced a publicly available in vitro fibrin bead assay dataset with a gradually increasing VEGF-A concentration (). We demonstrate that our automated segmentation and sprout morphology analysis, including sprout number, length, and nuclei number, outperform the widely used ImageJ plugin. We also show that SproutAngio allows a more detailed and automated analysis of the mouse retinal vasculature in comparison to the commonly used radial expansion measurement. In addition, we provide two novel methods for automated analysis of endothelial lumen space: (1) width measurement from tip, stalk and root segments of the sprouts and (2) paired nuclei distance analysis. We show that these automated methods provided important additional information on the endothelial cell organization in the sprouts. The pipelines and source code of SproutAngio are publicly available ().

It is a formidable challenge to combine the perform-ance advantages of linear and nonlinear polymer dielectrics for developing all-organic film capacitors with high energy density and low loss. In this work, massively parallel aligned poly(vinylidene fluoride) (PVDF) nanofibrils were in situ fabricated for the first time in the polyethylene (PE) matrix via a multistage stretching technology involving hot stretching and solid-state stretching at an elevated temperature. The largely enhanced interfacial area of PVDF nanofibrils could effectively induce interfacial polarization, imparting PE composite films with a high dielectric constant of 4.50. More interestingly, the nanoconfinement effect of PVDF nanofibrils greatly restricted the migration of free electrons and impurity ions, and an impressive breakdown strength of 624 MV m-1 was obtained. As a result, the as-prepared PE/PVDF composite films exhibited an attractive discharged energy density of as high as 6.4 J cm-3, which was more than 10 times of the conventional counterparts, and outperformed the current linear dielectric polymers. The ingenious structure design of in situ nonlinear dielectric nanofibrils provides a promising approach to maximize the advantageous polarizations and minimize the disadvantageous polarizations in the linear and nonlinear polymer dielectric blends, achieving all-organic polymer dielectric composite films with high energy density and low loss.

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Hsin-Hua Li,1,* Hanoch Livneh,2,* Hua-Lung Huang,3 Yu-Han Wang,4,* Ming-Chi Lu,5,6 Wei-Jen Chen,1,4,7,8 Tzung-Yi Tsai9– 11 1Department of Chinese Medicine, Dalin Tzu Chi Hospital, The Buddhist Tzu Chi Medical Foundation, Chiayi, 62247, Taiwan; 2Rehabilitation Counseling Program, Portland State University, Portland, OR, 97207-0751, USA; 3Department of Rehabilitation, Dalin Tzu Chi Hospital, The Buddhist Tzu Chi Medical Foundation, Chiayi, Taiwan; 4Center of Sports Medicine, Dalin Tzu Chi Hospital, The Buddhist Tzu Chi Medical Foundation, Chiayi, 62247, Taiwan; 5Division of Allergy, Immunology and Rheumatology, Dalin Tzu Chi Hospital, The Buddhist Tzu Chi Medical Foundation, Chiayi, 62247, Taiwan; 6School of Medicine, Tzu Chi University, Hualien, 97004, Taiwan; 7School of Post-Baccalaureate Chinese Medicine, Tzu Chi University, Hualien, 97004, Taiwan; 8Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, 33301, Taiwan; 9Department of Medical Research, Dalin Tzu Chi Hospital, The Buddhist Tzu Chi Medical Foundation, Chiayi, 62247, Taiwan; 10Department of Nursing, Tzu Chi University of Science and Technology, Hualien, 97004, Taiwan; 11Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, 70428, Taiwan*These authors contributed equally to this workCorrespondence: Wei-Jen Chen; Tzung-Yi Tsai, Tel +886-5-2648000-5003 ; +886-5-2648000-3209, Fax +886-5-2648006, Email tough2915@hotmail.com; dm732024@tzuchi.com.twObjective: Sarcopenia is a frequently observed comorbidity of rheumatoid arthritis (RA) due to the chronic activation of the innate immune system. Accumulating evidence has indicated that Chinese herbal medicine (CHM) safely suppresses proinflammatory pathways and controls inflammation-associated disease, but its effect in reducing the risk of developing sarcopenia among RA subjects has not been established. We conducted a population-level cohort s

There are limitations and difficulties in the management of traditional in-person standardized patient (SP) practice. The latest developments in online communication tools and the COVID-19 pandemic have promoted the needs for online clinical skills training objectively. However, existing commercial online platforms may not meet the requests for SP-based medical simulation. This paper described the methodology applied to develop a smartphone-based online platform for the management of clinical skills training and assessment with remote SPs, and aimed to determine whether this new platform is acceptable or useful through a pilot run in September 2020. The post-run survey including questionnaire inspired by technological acceptance model and determinants of the perceived ease of use was used to assess the acceptability and usefulness of the platform. Twenty four-year students of clinical medicine participated in the pilot study with twenty SPs and ten faculties. Data from the post-run survey showed that there was a general recognition that the platform is easy to use among all the users. Two questions regarding the usefulness of the platform showed significant differences between the SPs/faculties and the students. More SPs found the platform useful as a training method than the students did. The faculties showed more attempts than the students to use this platform for clinical skills training in the future. This smartphone-based online platform was widely accepted among the tested students, SPs and faculties, which meets the requests and challenges of the new era. It provides an effective approach for clinical skills training and assessment with remote SPs.

Shengfang Bao,1,&ast; Jingyi Lu,1,&ast; Hua Huang,1 Ying-Ying Jin,1 Fei Ding,1 Zhen Yang,1 Xuemei Xu,1 Chenxi Liu,1 Xi Mo,2 Yanliang Jin1 1Department of Rheumatology & Immunology, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of China; 2Pediatric Translational Medicine Institute, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xi Mo; Yanliang Jin, Email xi.mo@shsmu.edu.cn; jinyanliang@scmc.com.cnObjective: To evaluate the risk of major infections in children with newly diagnosed childhood-onset systemic lupus erythematosus (cSLE).Methods: Predictors of major infections were identified by the multivariable logistic regression. Major infection free was defined as no major infection events within 6 months after the diagnosis of cSLE. The Kaplan–Meier survival plot was performed. A prediction model for major infection events was established and examined by receiver operating characteristic (ROC) curve analysis.Results: A total of 98 eligible patients were recorded in the medical charts. Sixty-three documented events of major infections were found in 60 (61.2%) cSLE patients. Furthermore, 90.5% (57/63) of infection events occurred within the first 6 months after the diagnosis of cSLE. The high SLEDAI (SLEDAI > 10), lupus nephritis and lymphocyte count < 0.8× 109/L were predictors for major infections. The CALL score (Children with high disease activity [SLEDAI > 10], lymphopenia, and LN) was defined by the number of predictors. Patients were then categorized into two groups: low-risk (score 0– 1) and high-risk (score 2– 3). Patients in the high-risk group had higher rates of the major infection occurrence than those in the low-risk group during the 6 months after the diagnosis of the cSLE (P< 0.001) (HR:14.10, 95% CI 8.43

Min Gao,1,2,&ast; Yongwen Li,3,&ast; Hua Huang,4,&ast; Yaguang Fan,3 Ruifeng Shi,4 Lianchun Su,5 Chen Chen,3 Xuanguang Li,4 Guangsheng Zhu,4 Di Wu,4 Peijun Cao,4 Hongyu Liu,3 Jun Chen,3– 5 Shirong Kang1 1Department of Thoracic Surgery, the Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010010, People’s Republic of China; 2Inner Mongolia Medical University, Hohhot, 010010, People’s Republic of China; 3Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China; 4Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, People’s Republic of China; 5Department of Thoracic Surgery, First Affiliated Hospital of Shihezi University School of Medicine, Shihezi, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jun Chen; Shirong Kang, Email huntercj2004@qq.com; bssbzzk2013@163.comBackground: Genetic susceptibilities play a large role in the pathogenesis of lung cancer (LC). The polycomb repressive complex 2 (PRC2) is a conserved chromatin-associated complex that represses gene expression and is crucial for proper organismal development and gene expression patterns. Despite PRC2 dysregulation has been observed in various human cancers, the relationship between PRC2 genes variants and lung cancer risk remains largely unexplored.Methods: To investigate the association between single nucleotide polymorphisms (SNPs) in PRC2 genes and the risk of developing LC, we genotyped blood genomic DNA from 270 LC patients and 452 healthy individuals of Chinese Han ethnicity using the TaqMan™ genotyping technique.Results: We found that rs17171119T>G(adjusted odds ratio (OR) = 0.662, 95% CI: 0.467– 0.938, P < 0.05), rs10898459 T>C(adjusted OR = 0.615, 95% CI: 0.4– 0.947, P < 0.05), and rs1136258 C>T(adjusted OR = 0.273

Xing-Chen Zhou,&ast; Yu-Bo Huang,&ast; Zhen Liu,&ast; Hong-Jiao Wu, Hua-Zhi Huang, Yu Tian, Shuang-Wei Hong, Hui-Jie Hu, Li-Jiang Lv, Zhi-Zhen Lv The Third Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhi-Zhen Lv; Li-Jiang Lv, The Third Clinical Medical College of Zhejiang Chinese Medical University, No. 548, Binwen Road, Hangzhou, 310053, People’s Republic of China, Tel +86 13750821128 ; +86 13958107858, Email lvzhizhen1992@163.com; lvlijiang0288@163.comBackground: Research on the brain mechanisms underlying manual therapy (MT)-induced analgesia has been conducted worldwide. However, no bibliometric analysis has been performed on functional magnetic resonance imaging (fMRI) studies of MT analgesia. To provide a theoretical foundation for the practical application of MT analgesia, this study examined the current incarnation, hotspots, and frontiers of fMRI-based MT analgesia research over the previous 20 years.Methods: All publications were obtained from the Science Citation Index-Expanded (SCI-E) of Web of Science Core Collection (WOSCC). We used CiteSpace 6.1.R3 to analyze publications, authors, cited authors, countries, institutions, cited journals, references, and keywords. We also evaluated keyword co-occurrences and timelines, and citation bursts. The search was conducted from 2002– 2022 and was completed within one day on October 7, 2022.Results: In total, 261 articles were retrieved. The total number of annual publications showed a fluctuating but overall increasing trend. Author B. Humphreys had the highest number of publications (eight articles) and J. E. Bialosky had the highest centrality (0.45). The United States of America (USA) was the country with the most publications (84 articles), accounting for 32.18% of all publications. Output institutions were mainly the University of Zurich, University of S

Qian Zhang,1,2 Pan Fu,2 Zhanglei Cao,2 Hua Huang,3 Qinwen Wen,3 Kaizhe Wang,2 Tong Kong,2 Xiudi Wu,3 Jianping Zheng2 1Jiangxi Key Laboratory for Rare Earths Magnetic Materials and Devices, College of Rare Earths, Jiangxi University of Science and Technology, Ganzhou, 341000, People’s Republic of China; 2Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences (CAS), Ningbo, 315300, People’s Republic of China; 3Department of Rheumatology and Immunology, Ningbo First Hospital, Ningbo, 315010, People’s Republic of ChinaCorrespondence: Jianping Zheng; Xiudi Wu, Tel +86– 18091984088 ; +86– 13857826442, Email zhengjianping@nimte.ac.cn; awu1100@aliyun.comPurpose: Methotrexate (MTX) is used as an anchor drug for the treatment of rheumatoid arthritis (RA) and there may be differences in drug action between genotypes. The purpose of this study was to investigate the relationship between clinical efficacy response and disease activity of MTX monotherapy with methylenetetrahydrofolate reductase (MTHFR) and methionine synthase reductase (MTRR) polymorphisms.Patients and Methods: In the study, a population of 32 patients in East China with early RA fulfilling the diagnostic standards of the American College of Rheumatology (ACR) were enrolled, all of them received MTX monotherapy. Genotyping of patients MTHFR C677T and A1298C, MTRR A66G using tetra-primer ARMS-PCR method and sanger sequencing to verify its accuracy.Results: The distribution of three polymorphic genotypes that were studied is in accordance with the Hardy-Weinberg genetic equilibrium. The patient pathology variables smoke (OR = 0.088, P = 0.037), drink alcohol (OR = 0.039, P = 0.016) and males (OR = 0.088, P = 0.037) were significantly associated with non-response to MTX. Genotype, allele distribution and genetic statistical models were not found to be related to MTX treatment response and disease activity in both the response groups

Hou-Hsun Liao,1– 3 Hsiao-Tien Chen,4 Hanoch Livneh,5 Hua-Lung Huang,6 Ning-Sheng Lai,7,8 Ming-Chi Lu,7,8 Chia-Chou Yeh,1,2,9 Tzung-Yi Tsai3,10,11 1Graduate Institute of Chinese Medicine, School of Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan; 2Department of Chinese Medicine, Dalin Tzuchi Hospital, The Buddhist Tzuchi Medical Foundation, Chiayi, Taiwan; 3Department of Nursing, Tzu Chi University of Science and Technology, Hualien, Taiwan; 4Department of Chinese Medicine, Chi Mei Medical Center, Tainan, Taiwan; 5Rehabilitation Counseling Program, Portland State University, Portland, OR, USA; 6Department of Rehabilitation, Dalin Tzuchi Hospital, The Buddhist Tzuchi Medical Foundation, Chiayi, Taiwan; 7School of Medicine, Tzu Chi University, Hualien, Taiwan; 8Division of Allergy, Immunology and Rheumatology, Dalin Tzuchi Hospital, The Buddhist Tzuchi Medical Foundation, Chiayi, Taiwan; 9School of Post-Baccalaureate Chinese Medicine, Tzu Chi University, Hualien, Taiwan; 10Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; 11Department of Medical Research, Dalin Tzuchi Hospital, The Buddhist Tzuchi Medical Foundation, Chiayi, TaiwanCorrespondence: Chia-Chou Yeh; Tzung-Yi Tsai, Tel +886-5-2648000-8713 ; +886-5-2648000 ext. 3209, Fax +886-5-2648006, Email yehcc0530@gmail.com; dm732024@tzuchi.com.twObjective: Non-steroidal anti-inflammatory drugs (NSAIDs) are frequently used as the first-line agents for the symptomatic relief of rheumatoid arthritis (RA), but it may insidiously provoke the onset of renal diseases, especially chronic kidney disease (CKD). While Chinese herbal medicine (CHM) has become an increasingly popular adjunctive therapy among RA groups, there are currently no available data on the effect of CHM use towards risk of CKD. This study aimed to explore on a population-level whether CHM use decreases sequent CKD risk among them.Methods: In

The spectrum of a kernel matrix significantly depends on the parameter values of the kernel function used to define the kernel matrix. This makes it challenging to design a preconditioner for a regularized kernel matrix that is robust across different parameter values. This paper proposes the Adaptive Factorized Nystr\"om (AFN) preconditioner. The preconditioner is designed for the case where the rank k of the Nystr\"om approximation is large, i.e., for kernel function parameters that lead to kernel matrices with eigenvalues that decay slowly. AFN deliberately chooses a well-conditioned submatrix to solve with and corrects a Nystr\"om approximation with a factorized sparse approximate matrix inverse. This makes AFN efficient for kernel matrices with large numerical ranks. AFN also adaptively chooses the size of this submatrix to balance accuracy and cost.

Small-fiber neuropathy (SFN) is a disorder that exclusively affects the small nerve fibers, sparing the large nerve fibers. Thinly myelinated A delta-fibers and unmyelinated C-fibers are damaged, leading to development of neuropathic pain, thermal dysfunction, sensory symptoms, and autonomic disturbances. Although many SFNs are secondary and due to immunological causes or metabolic disturbances, the etiology is unknown in up to half of the patients. Over the years, this proportion of "idiopathic SFN" has decreased, as familial and genetic causes have been discovered, thus shifting a proportion of once "idiopathic" cases to the genetic category. After the discovery of SCN9A-gene variants in 2012, SCN10A and SCN11A variants have been found to be pathogenic in SFN. With improved accessibility of SFN diagnostic tools and genetic tests, many non-SCN variants and genetically inherited systemic diseases involving the small nerve fibers have also been described, but only scattered throughout the literature. There are 80 SCN variants described as causing SFN, 8 genes causing hereditary sensory autonomic neuropathies (HSAN) described with pure SFN, and at least 7 genes involved in genetically inherited systemic diseases associated with SFN. This systematic review aims to consolidate and provide an updated overview on the genetic variants of SFN to date---SCN genes and beyond. Awareness of these genetic causes of SFN is imperative for providing treatment directions, prognostication, and management of expectations for patients and their health-care providers.

Depth completion, aiming to predict dense depth maps from sparse depth measurements, plays a crucial role in many computer vision related applications. Deep learning approaches have demonstrated overwhelming success in this task. However, high-precision depth completion without relying on the ground-truth data, which are usually costly, still remains challenging. The reason lies on the ignorance of 3D structural information in most previous unsupervised solutions, causing inaccurate spatial propagation and mixed-depth problems. To alleviate the above challenges, this paper explores the utilization of 3D perceptual features and multi-view geometry consistency to devise a high-precision self-supervised depth completion method. Firstly, a 3D perceptual spatial propagation algorithm is constructed with a point cloud representation and an attention weighting mechanism to capture more reasonable and favorable neighboring features during the iterative depth propagation process. Secondly, the multi-view geometric constraints between adjacent views are explicitly incorporated to guide the optimization of the whole depth completion model in a self-supervised manner. Extensive experiments on benchmark datasets of NYU-Depthv2 and VOID demonstrate that the proposed model achieves the state-of-the-art depth completion performance compared with other unsupervised methods, and competitive performance compared with previous supervised methods., Comment: 13 pages, 7 figures

Dual-Camera Compressed Hyperspectral Imaging (DCCHI) offers the capability to reconstruct 3D Hyperspectral Image (HSI) by fusing compressive and Panchromatic (PAN) image, which has shown great potential for snapshot hyperspectral imaging in practice. In this paper, we introduce a novel DCCHI reconstruction network, the Intra-Inter Similarity Exploiting Transformer (In2SET). Our key insight is to make full use of the PAN image to assist the reconstruction. To this end, we propose using the intra-similarity within the PAN image as a proxy for approximating the intra-similarity in the original HSI, thereby offering an enhanced content prior for more accurate HSI reconstruction. Furthermore, we aim to align the features from the underlying HSI with those of the PAN image, maintaining semantic consistency and introducing new contextual information for the reconstruction process. By integrating In2SET into a PAN-guided unrolling framework, our method substantially enhances the spatial-spectral fidelity and detail of the reconstructed images, providing a more comprehensive and accurate depiction of the scene. Extensive experiments conducted on both real and simulated datasets demonstrate that our approach consistently outperforms existing state-of-the-art methods in terms of reconstruction quality and computational complexity. Code will be released.

Recently, the mainstream practice for training low-light raw image denoising methods has shifted towards employing synthetic data. Noise modeling, which focuses on characterizing the noise distribution of real-world sensors, profoundly influences the effectiveness and practicality of synthetic data. Currently, physics-based noise modeling struggles to characterize the entire real noise distribution, while learning-based noise modeling impractically depends on paired real data. In this paper, we propose a novel strategy: learning the noise model from dark frames instead of paired real data, to break down the data dependency. Based on this strategy, we introduce an efficient physics-guided noise neural proxy (PNNP) to approximate the real-world sensor noise model. Specifically, we integrate physical priors into neural proxies and introduce three efficient techniques: physics-guided noise decoupling (PND), physics-guided proxy model (PPM), and differentiable distribution loss (DDL). PND decouples the dark frame into different components and handles different levels of noise flexibly, which reduces the complexity of noise modeling. PPM incorporates physical priors to constrain the generated noise, which promotes the accuracy of noise modeling. DDL provides explicit and reliable supervision for noise distribution, which promotes the precision of noise modeling. PNNP exhibits powerful potential in characterizing the real noise distribution. Extensive experiments on public datasets demonstrate superior performance in practical low-light raw image denoising. The code will be available at \url{https://github.com/fenghansen/PNNP}., Comment: Under Review

Spike camera is a new type of bio-inspired vision sensor that records light intensity in the form of a spike array with high temporal resolution (20,000 Hz). This new paradigm of vision sensor offers significant advantages for many vision tasks such as high speed image reconstruction. However, existing spike-based approaches typically assume that the scenes are with sufficient light intensity, which is usually unavailable in many real-world scenarios such as rainy days or dusk scenes. To unlock more spike-based application scenarios, we propose a Recurrent Spike-based Image Restoration (RSIR) network, which is the first work towards restoring clear images from spike arrays under general illumination. Specifically, to accurately describe the noise distribution under different illuminations, we build a physical-based spike noise model according to the sampling process of the spike camera. Based on the noise model, we design our RSIR network which consists of an adaptive spike transformation module, a recurrent temporal feature fusion module, and a frequency-based spike denoising module. Our RSIR can process the spike array in a recursive manner to ensure that the spike temporal information is well utilized. In the training process, we generate the simulated spike data based on our noise model to train our network. Extensive experiments on real-world datasets with different illuminations demonstrate the effectiveness of the proposed network. The code and dataset are released at https://github.com/BIT-Vision/RSIR., Comment: Accepted by ACM MM 2023

The recent neural surface reconstruction by volume rendering approaches have made much progress by achieving impressive surface reconstruction quality, but are still limited to dense and highly accurate posed views. To overcome such drawbacks, this paper pays special attention on the consistent surface reconstruction from sparse views with noisy camera poses. Unlike previous approaches, the key difference of this paper is to exploit the multi-view constraints directly from the explicit geometry of the neural surface, which can be used as effective regularization to jointly learn the neural surface and refine the camera poses. To build effective multi-view constraints, we introduce a fast differentiable on-surface intersection to generate on-surface points, and propose view-consistent losses based on such differentiable points to regularize the neural surface learning. Based on this point, we propose a jointly learning strategy for neural surface and camera poses, named SC-NeuS, to perform geometry-consistent surface reconstruction in an end-to-end manner. With extensive evaluation on public datasets, our SC-NeuS can achieve consistently better surface reconstruction results with fine-grained details than previous state-of-the-art neural surface reconstruction approaches, especially from sparse and noisy camera views.

Image denoising is a fundamental problem in computational photography, where achieving high perception with low distortion is highly demanding. Current methods either struggle with perceptual quality or suffer from significant distortion. Recently, the emerging diffusion model has achieved state-of-the-art performance in various tasks and demonstrates great potential for image denoising. However, stimulating diffusion models for image denoising is not straightforward and requires solving several critical problems. For one thing, the input inconsistency hinders the connection between diffusion models and image denoising. For another, the content inconsistency between the generated image and the desired denoised image introduces distortion. To tackle these problems, we present a novel strategy called the Diffusion Model for Image Denoising (DMID) by understanding and rethinking the diffusion model from a denoising perspective. Our DMID strategy includes an adaptive embedding method that embeds the noisy image into a pre-trained unconditional diffusion model and an adaptive ensembling method that reduces distortion in the denoised image. Our DMID strategy achieves state-of-the-art performance on both distortion-based and perception-based metrics, for both Gaussian and real-world image denoising.The code is available at https://github.com/Li-Tong-621/DMID., Comment: 18 pages,15 figures

Cerebral Cavernous Malformation (CCM) is a brain vascular disease with various neurological symptoms. In this study, we describe the inflammatory profile in CCM and show for the first time the formation of neutrophil extracellular traps (NETs) in rodents and humans with CCM. Through RNA-seq analysis of cerebellum endothelial cells from wild-type mice and mice with an endothelial cell-specific ablation of the Ccm3 gene (Ccm3(iECKO)), we show that endothelial cells from Ccm3(iECKO) mice have an increased expression of inflammation-related genes. These genes encode proinflammatory cytokines and chemokines, as well as adhesion molecules, which promote recruitment of inflammatory and immune cells. Similarly, immunoassays showed elevated levels of these cytokines and chemokines in the cerebellum of the Ccm3(iECKO) mice. Consistently, both flow cytometry and immunofluorescence analysis showed infiltration of different subsets of leukocytes into the CCM lesions. Neutrophils, which are known to fight against infection through different strategies, including the formation of NETs, represented the leukocyte subset within the most pronounced increase in CCM. Here, we detected elevated levels of NETs in the blood and the deposition of NETs in the cerebral cavernomas of Ccm3(iECKO) mice. Degradation of NETs by DNase I treatment improved the vascular barrier. The deposition of NETs in the cavernomas of patients with CCM confirms the clinical relevance of NETs in CCM.

Naïve CD8+ T cells can differentiate into effector (Teff), memory (Tmem) or exhausted (Tex) T cells. These developmental pathways are associated with distinct transcriptional and epigenetic changes that endow cells with different functional capacities and therefore therapeutic potential. The molecular circuitry underlying these developmental trajectories and the extent of heterogeneity within Teff, Tmem and Tex populations remain poorly understood. Here, we used the lymphocytic choriomeningitis virus model of acute-resolving and chronic infection to address these gaps by applying longitudinal single-cell RNA-sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) analyses. These analyses uncovered new subsets, including a subpopulation of Tex cells expressing natural killer cell-associated genes that is dependent on the transcription factor Zeb2, as well as multiple distinct TCF-1+ stem/progenitor-like subsets in acute and chronic infection. These data also revealed insights into the reshaping of Tex subsets following programmed death 1 (PD-1) pathway blockade and identified a key role for the cell stress regulator, Btg1, in establishing the Tex population. Finally, these results highlighted how the same biological circuits such as cytotoxicity or stem/progenitor pathways can be used by CD8+ T cell subsets with highly divergent underlying chromatin landscapes generated during different infections.

Intersection is one of the most challenging scenarios for autonomous driving tasks. Due to the complexity and stochasticity, essential applications (e.g., behavior modeling, motion prediction, safety validation, etc.) at intersections rely heavily on data-driven techniques. Thus, there is an intense demand for trajectory datasets of traffic participants (TPs) in intersections. Currently, most intersections in urban areas are equipped with traffic lights. However, there is not yet a large-scale, high-quality, publicly available trajectory dataset for signalized intersections. Therefore, in this paper, a typical two-phase signalized intersection is selected in Tianjin, China. Besides, a pipeline is designed to construct a Signalized INtersection Dataset (SIND), which contains 7 hours of recording including over 13,000 TPs with 7 types. Then, the behaviors of traffic light violations in SIND are recorded. Furthermore, the SIND is also compared with other similar works. The features of the SIND can be summarized as follows: 1) SIND provides more comprehensive information, including traffic light states, motion parameters, High Definition (HD) map, etc. 2) The category of TPs is diverse and characteristic, where the proportion of vulnerable road users (VRUs) is up to 62.6% 3) Multiple traffic light violations of non-motor vehicles are shown. We believe that SIND would be an effective supplement to existing datasets and can promote related research on autonomous driving.The dataset is available online via: https://github.com/SOTIF-AVLab/SinD, Comment: 8 pages

Low-light raw denoising is an important and valuable task in computational photography where learning-based methods trained with paired real data are mainstream. However, the limited data volume and complicated noise distribution have constituted a learnability bottleneck for paired real data, which limits the denoising performance of learning-based methods. To address this issue, we present a learnability enhancement strategy to reform paired real data according to noise modeling. Our strategy consists of two efficient techniques: shot noise augmentation (SNA) and dark shading correction (DSC). Through noise model decoupling, SNA improves the precision of data mapping by increasing the data volume and DSC reduces the complexity of data mapping by reducing the noise complexity. Extensive results on the public datasets and real imaging scenarios collectively demonstrate the state-of-the-art performance of our method. Our code is available at: https://github.com/megvii-research/PMN., Comment: 9 pages, 8 figures, to be published in ACMMM 2022

The competitive Coding approach (CompCode) is one of the most promising methods for palmprint recognition. Due to its high performance and simple formulation, it has been continuously studied for many years. However, although numerous variations of CompCode have been proposed, a detailed analysis of the method is still absent. In this paper, we provide a detailed analysis of CompCode from the perspective of linear discriminant analysis (LDA) for the first time. A non-trivial sufficient condition under which the CompCode is optimal in the sense of Fisher's criterion is presented. Based on our analysis, we examined the statistics of palmprints and concluded that CompCode deviates from the optimal condition. To mitigate the deviation, we propose a new method called Class-Specific CompCode that improves CompCode by excluding non-palm-line areas from matching. A nonlinear mapping of the competitive code is also applied in this method to further enhance accuracy. Experiments on two public databases demonstrate the effectiveness of the proposed method., Comment: 12 pages, 14 figures

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of $\times$4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution., Comment: Validation code of the baseline model is available at https://github.com/ofsoundof/IMDN. Validation of all submitted models is available at https://github.com/ofsoundof/NTIRE2022_ESR

Hierarchical matrices provide a powerful representation for significantly reducing the computational complexity associated with dense kernel matrices. For general kernel functions, interpolation-based methods are widely used for the efficient construction of hierarchical matrices. In this paper, we present a fast hierarchical data reduction (HiDR) procedure with $O(n)$ complexity for the memory-efficient construction of hierarchical matrices with nested bases where $n$ is the number of data points. HiDR aims to reduce the given data in a hierarchical way so as to obtain $O(1)$ representations for all nearfield and farfield interactions. Based on HiDR, a linear complexity $\mathcal{H}^2$ matrix construction algorithm is proposed. The use of data-driven methods enables {better efficiency than other general-purpose methods} and flexible computation without accessing the kernel function. Experiments demonstrate significantly improved memory efficiency of the proposed data-driven method compared to interpolation-based methods over a wide range of kernels. Though the method is not optimized for any special kernel, benchmark experiments for the Coulomb kernel show that the proposed general-purpose algorithm offers competitive performance for hierarchical matrix construction compared to several state-of-the-art algorithms for the Coulomb kernel., Comment: 26 pages, 20 figures

Jinwen Xia,1,2 Quhui Wang,1 Fei Ju,3 Xiang Luo,3 Feng Wang,4 Youlang Zhou,3 Hua Huang,5 Hua Wang,1,2 Xingli Bao6 1Department of Breast and Thyroid Surgery, Affiliated Hospital of Nantong University, Nantong, People’s Republic of China; 2Clinical Medicine, Medical College, Nantong University, Nantong, People’s Republic of China; 3Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, People’s Republic of China; 4Department of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong, People’s Republic of China; 5Department of Pathology, Affiliated Hospital of Nantong University, Nantong, People’s Republic of China; 6Department of Medical Equipment, Affiliated Hospital of Nantong University, Nantong, People’s Republic of ChinaCorrespondence: Hua Wang, Department of Breast and Thyroid Surgery, Affiliated Hospital of Nantong University, No. 20, Xisi Road, Chongchuan District, Nantong City, Jiangsu Province, 226001, People’s Republic of China, Tel +86 137 062 92250, Email wanghua12083@163.comPurpose: Multiple reports have demonstrated that highly expressed chloride intracellular channel 1 (CLIC1) exists in a range of malignant tumors and is involved in proliferation, invasion, and migration of cancer cells. There are few studies on CLIC1 and breast cancer (BC). The purpose of this research was to evaluate the expression level of CLIC1 in BC and its impact on prognosis of BC patients.Patients and Methods: Differences in CLIC1 expression levels in 25 pairs of BC and corresponding paracancerous specimens were tested by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot (WB). Immunohistochemistry (IHC) was performed to discuss the relevance between CLIC1 expression in BC tissue chips and clinicopathological parameters of BC patients. The effect of CLIC1 expression on patient prognosis was evaluated by Kaplan–Meier survival

De-Bin Liu,1,&ast; You-Fu He,2– 4,&ast; Gui-Jian Chen,1 Hua Huang,1 Xu-Ling Xie,1 Wan-Jun Lin,1 Zhi-Jian Peng1 1Department of Cardiology, The Second People’s Hospital of Shantou, Shantou, Guangdong Province, People’s Republic of China; 2Department of Cardiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou Province, People’s Republic of China; 3Guizhou Provincial Cardiovascular Disease Clinical Medicine Research Center, Guiyang, Guizhou Province, People’s Republic of China; 4Medical College, Guizhou University, Guiyang, Guizhou Province, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhi-Jian Peng, Department of Cardiology, The Second People’s Hospital of Shantou, Shantou, 515000, Guangdong Province, People’s Republic of China, Tel +86 18316056382, Fax +86-754 88983534, Email 983247770@qq.comBackground: Aortic dissection (AD) is a rare and lethal disorder with its genetic basis remains largely unknown. Many studies have confirmed that circRNAs play important roles in various physiological and pathological processes. However, the roles of circRNAs in AD are still unclear and need further investigation. The present study aimed to elucidate the underlying molecular mechanisms of circRNAs regulation in AD based on the circRNA-associated competing endogenous RNA (ceRNA) network.Methods: Expression profiles of circRNAs (GSE97745), miRNAs (GSE92427), and mRNAs (GSE52093) were downloaded from Gene Expression Omnibus (GEO) databases, and the differentially expressed RNAs (DERNAs) were subsequently identified by bioinformatics analysis. CircRNA–miRNA–mRNA ceRNA network, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to predict the potential functions of circRNA-associated ceRNA network. RNA was isolated from human arterial blood samples after which qRT-PCR was performed to confirm the DERNAs.Results: We identified 14 (5 up-reg

Han Cen,1– 3 Qin-Wen Wen,4 Han-Qing Zhang,4 Hang Yu,4 Zhen Zeng,2 Ting Jin,2 Ting-Hui Wang,4 Wen Qin,4 Hua Huang,4 Xiu-Di Wu4 1Institute of Geriatrics, The Affiliated Hospital of Medical School, Ningbo University, Ningbo, Zhejiang, People’s Republic of China; 2Department of Preventive Medicine, Medical School of Ningbo University, Ningbo, Zhejiang, People’s Republic of China; 3Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, People’s Republic of China; 4Department of Rheumatology, Ningbo First Hospital, Ningbo Hospital of Zhejiang University, Ningbo, Zhejiang, People’s Republic of ChinaCorrespondence: Xiu-Di Wu, Department of Rheumatology, Ningbo First Hospital, Ningbo Hospital of Zhejiang University, 59 Liuting Road, Ningbo, Zhejiang, 315010, People’s Republic of China, Tel +86 574 87085588, Fax +86 574 87291583, Email awu1100@aliyun.comPurpose: To investigate the associations between genetic polymorphisms within transporter genes and clinical response to methotrexate (MTX) in Chinese rheumatoid arthritis (RA) patients.Patients and Methods: A total of 100 RA patients receiving MTX were prospectively followed up for approximately 3 months to determine the clinical response based on several criteria, including European League Against Rheumatism (EULAR) good and moderate response, disease activity score in 28 joint counts – erythrocyte sedimentation rate (DAS28-ESR) low disease activity (LDA), change in DAS28-ESR (ΔDAS28-ESR) and ΔDAS28-ESR > 0.6. Fifty-four single nucleotide polymorphisms (SNPs) within seven transporter genes, including SLC19A1, ABCB1, ABCC1∼ 4 and ABCG2, were genotyped.Results: Multivariable analysis revealed that SLC19A1 rs12659 and rs3788200, ABCC2 rs3740066, rs4148396 and rs717620 were significantly associated with EULAR good and moderate response, and ABCC2 rs3740066 and rs717620 were significantly associated with DAS28-ESR LDA, and ABCB1 rs1128503, rs4148737 and

Sijia Ge,1,* Hua Huang,2,* Wei Huang,1 Ran Ji,1 Jing Chen,1 Shuzhen Wu,1 Liyang Wang,1 Tianxin Huang,1 Yu Sheng,1 Haiou Yan,1 Cuihua Lu,1 Lin Ma3 1Department of Gastroenterology, Affiliated Hospital of Nantong University, Jiangsu, People’s Republic of China; 2Department of Pathology, Affiliated Hospital of Nantong University, Jiangsu, People’s Republic of China; 3Department of Gastroenterology, Affiliated Haian Hospital of Nantong University, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lin MaDepartment of Gastroenterology, Affiliated Haian Hospital of Nantong University, Nantong, 226600, Jiangsu, People’s Republic of China, Email 1908397778@qq.comCuihua LuDepartment of Gastroenterology, Affiliated Hospital of Nantong University, Nantong, 226001, Jiangsu, People’s Republic of China, Email lch670608@sina.comBackground: As hepatocellular carcinoma (HCC) having the second-highest mortality rate globally, the early diagnosis and prognosis of HCC have always been the focus of various studies. Although PSME4 has been reported to be closely related to several malignancies, its role in HCC remains unclear.Materials and Methods: The TCGA-LIHC database and HCC tissues were used to explore the expression of PSME4 in HCC. Gene set enrichment analysis (GSEA) was used to forecast the biological behavior of HCC cells that PSME4 might be involved in regulation. In addition, CCK-8, colony formation and flow cytometry assays were used to explore the effect of PSME4 on HCC cells. Furthermore, the underlying PSME4-related signaling pathways in HCC were further confirmed using GSEA.Results: We found that the expression of PSME4 in HCC tissues was significantly higher than that in adjacent normal tissues, and patients with high PSME4 expression have a poor prognosis. CCK-8, colony formation and flow cytometry assays shown that knockdown of PSME4 inhibits HCC cell proliferation of HCC ce

Yong-Guang Wei, Cheng-Kun Yang, Zhong-Liu Wei, Xi-Wen Liao, Yong-Fei He, Xin Zhou, Hua-Sheng Huang, Chen-Lu Lan, Chuang-Ye Han, Tao Peng Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People’s Republic of ChinaCorrespondence: Tao PengDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Shuang Yong Road 6, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of ChinaTel +86-771-5356528Fax +86-771-5350031Email pengtaogmu@163.comBackground: The protein high-mobility group AT-hook 1 (HMGA1) has been demonstrated that modulated cellular proliferation, invasion, and apoptosis with a poor prognosis in miscellaneous carcinomas. However, the mechanism of circumstantial carcinogenesis and association with the immune microenvironment of HMGA1 in hepatocellular carcinoma (HCC) had not been extensively explored.Methods: The gene expression, clinicopathological correlation, and prognosis analysis were performed in the data obtained from TCGA. The results were further validated by ICGC and GEO database and external validation cohort from Guangxi. The HMGA1 protein expression was further examined in the HPA database. Biological function analyses were conducted by GSEA, STRING database, and Coexpedia online tool. Using TIMER and CIBERSORT method, the relationship between immune infiltrate and HMGA1 was investigated.Results: In HCC, HMGA1 had much higher transcriptional and proteomic expression than in corresponding paraneoplastic tissue. Patients with high HMGA1 expression had a poor prognosis and unpromising clinicopathological features. High HMGA1 expression was closely related to the cell cycle, tumorigenesis, substance metabolism, and immune processes by regulating complex signaling pathways. Notably, HMGA1 may be associated with TP53 mutational carcinogenesis. Moreover, increased HMGA1 expression may lead to an increase i

Gliomas are brain tumors characterized by an immunosuppressive microenvironment. Immunostimulatory agonistic CD40 antibodies (αCD40) are in clinical development for solid tumors, but are yet to be evaluated for glioma. Here, we demonstrate that systemic delivery of αCD40 in preclinical glioma models induces the formation of tertiary lymphoid structures (TLS) in proximity of meningeal tissue. In treatment-naïve glioma patients, the presence of TLS correlates with increased T cell infiltration. However, systemic delivery of αCD40 induces hypofunctional T cells and impairs the response to immune checkpoint inhibitors in pre-clinical glioma models. This is associated with a systemic induction of suppressive CD11b+ B cells post-αCD40 treatment, which accumulate in the tumor microenvironment. Our work unveils the pleiotropic effects of αCD40 therapy in glioma and reveals that immunotherapies can modulate TLS formation in the brain, opening up for future opportunities to regulate the immune response., These authors contributed equally: Luuk van Hooren, Alessandra Vaccaro

Interconnectivity is the key characteristic of bone tissue engineering scaffold modulating cell migration, blood vessels invasion and transport of nutrient and waste. However, efforts and understanding of the interconnectivity of porous Mg is limited due to the diverse architectures of pore struts and pore size distribution of Mg scaffold systems. In this work, biomimetic hierarchical porous Mg scaffolds with tailored interconnectivity as well as pore size distribution were prepared by template replication of infiltration casting. Mg scaffold with better interconnectivity showed lower mechanical strength. Enlarging interconnected pores would enhance the interconnectivity of the whole scaffold and reduce the change of ion concentration, pH value and osmolality of the degradation microenvironment due to the lower specific surface area. Nevertheless, the degradation rates of five tested Mg scaffolds were no different because of the same geometry of strut unit. Direct cell culture and evaluation of cell density at both sides of four typical Mg scaffolds indicated that cell migration through hierarchical porous Mg scaffolds could be enhanced by not only bigger interconnected pore size but also larger main pore size. In summary, design of interconnectivity in terms of pore size distribution could regulate mechanical strength, microenvironment in cell culture condition and cell migration potential, and beyond that it shows great potential for personalized therapy which could facilitate the regeneration process. © 2021

BACKGROUND: Tumor vessels in glioma are molecularly and functionally abnormal, contributing to treatment resistance. Proteins differentially expressed in glioma vessels can change vessel phenotype and be targeted for therapy. ELTD1 (Adgrl4) is an orphan member of the adhesion G-protein-coupled receptor family upregulated in glioma vessels, and has been suggested as a potential therapeutic target. However, the role of ELTD1 in regulating vessel function in glioblastoma is poorly understood. METHODS: ELTD1 expression in human gliomas and its association with patient survival was determined using tissue microarrays and public databases. The role of ELTD1 in regulating tumor vessel phenotype was analyzed using orthotopic glioma models and ELTD1 -/- mice. Endothelial cells isolated from murine gliomas were transcriptionally profiled to determine differentially expressed genes and pathways. The consequence of ELTD1-deletion on glioma immunity was determined by treating tumor bearing mice with PD-1-blocking antibodies. RESULTS: ELTD1 levels were upregulated in human glioma vessels, increased with tumor malignancy, and were associated with poor patient survival. Progression of orthotopic gliomas was not affected by ELTD1-deletion, however, tumor vascular function was improved in ELTD1 -/- mice. Bioinformatic analysis of differentially expressed genes indicated increased inflammatory response and decreased proliferation in tumor endothelium in ELTD1 -/- mice. Consistent with an enhanced inflammatory response, ELTD1-deletion improved T-cell infiltration in GL261-bearing mice after PD-1 checkpoint blockade. CONCLUSION: Our data demonstrate that ELTD1 participates in inducing vascular dysfunction in glioma, and suggests that targeting of ELTD1 may normalize the vessels and improve the response to immunotherapy.

This paper studies theoretically and empirically the relationship among shareholding structure, the private benefit of control and incentive intensity. By integrating the principal–agent theory and the market competition theory into the three-stage dynamic game model, we built the dual principal–agent relationship including both ‘shareholder-manager’ and ‘controlling shareholders-small and medium shareholders’. Empirically, the panel data of 1971 listed enterprises in China from the year 2007 to 2014 are analysed in order to justify the theoretical results by using twoway fixed effect model, dynamic panel model, and threshold regression model. It is shown that for enterprise managers, the higher their ability level and risk aversion, the stronger their incentive intensity will be. However, for shareholders, the private benefit of control and the incentive intensity show a non-linear relationship with the change of ownership concentration.