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3. PackCache: An Online Cost-Driven Data Caching Algorithm in the Cloud

Author

Jiashu Wu, Hao Dai, Yang Wang, Yong Zhang, Dong Huang, and Chengzhong Xu

Subjects
Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Networking and Internet Architecture, Computer Science - Distributed, Parallel, and Cluster Computing, Computational Theory and Mathematics, Hardware and Architecture, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), Distributed, Parallel, and Cluster Computing (cs.DC), Software, Theoretical Computer Science
Abstract

In this paper, we study a data caching problem in the cloud environment, where multiple frequently co-utilised data items could be packed as a single item being transferred to serve a sequence of data requests dynamically with reduced cost. To this end, we propose an online algorithm with respect to a homogeneous cost model, called PackCache, that can leverage the FP-Tree technique to mine those frequently co-utilised data items for packing whereby the incoming requests could be cost-effectively served online by exploiting the concept of anticipatory caching. We show the algorithm is 2\alpha competitive, reaching the lower bound of the competitive ratio for any deterministic online algorithm on the studied caching problem, and also time and space efficient to serve the requests. Finally, we evaluate the performance of the algorithm via experimental studies to show its actual cost-effectiveness and scalability., Comment: Accepted by IEEE Transactions on Computers

Published
2023

6. Joint Semantic Transfer Network for IoT Intrusion Detection

Author

Jiashu Wu, Yang Wang, Binhui Xie, Shuang Li, Hao Dai, Kejiang Ye, and Chengzhong Xu

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, Computer Networks and Communications, Machine Learning (cs.LG), Computer Science Applications, Computer Science - Computers and Society, Artificial Intelligence (cs.AI), Hardware and Architecture, Computers and Society (cs.CY), Signal Processing, Cryptography and Security (cs.CR), Information Systems
Abstract

In this paper, we propose a Joint Semantic Transfer Network (JSTN) towards effective intrusion detection for large-scale scarcely labelled IoT domain. As a multi-source heterogeneous domain adaptation (MS-HDA) method, the JSTN integrates a knowledge rich network intrusion (NI) domain and another small-scale IoT intrusion (II) domain as source domains, and preserves intrinsic semantic properties to assist target II domain intrusion detection. The JSTN jointly transfers the following three semantics to learn a domain-invariant and discriminative feature representation. The scenario semantic endows source NI and II domain with characteristics from each other to ease the knowledge transfer process via a confused domain discriminator and categorical distribution knowledge preservation. It also reduces the source-target discrepancy to make the shared feature space domain-invariant. Meanwhile, the weighted implicit semantic transfer boosts discriminability via a fine-grained knowledge preservation, which transfers the source categorical distribution to the target domain. The source-target divergence guides the importance weighting during knowledge preservation to reflect the degree of knowledge learning. Additionally, the hierarchical explicit semantic alignment performs centroid-level and representative-level alignment with the help of a geometric similarity-aware pseudo-label refiner, which exploits the value of unlabelled target II domain and explicitly aligns feature representations from a global and local perspective in a concentrated manner. Comprehensive experiments on various tasks verify the superiority of the JSTN against state-of-the-art comparing methods, on average a 10.3% of accuracy boost is achieved. The statistical soundness of each constituting component and the computational efficiency are also verified., Comment: Accepted by IEEE Internet of Things Journal

Published
2023

7. Human endoderm stem cells reverse inflammation-related acute liver failure through cystatin SN-mediated inhibition of interferon signaling

Author

Yilin Xu, Jinglin Wang, Haozhen Ren, Hao Dai, Ying Zhou, Xiongzhao Ren, Yang Wang, Sisi Feng, Xiaogang Deng, Jiaying Wu, Tianlong Fu, Tengfei Nie, Haifeng He, Tongkun Wei, Bing Zhu, Lijian Hui, Bin Li, Jing Wang, Hongyan Wang, Luonan Chen, Xiaolei Shi, and Xin Cheng

Subjects
Cell Biology, Molecular Biology
Abstract

Acute liver failure (ALF) is a life-threatening disease that occurs secondary to drug toxicity, infection or a devastating immune response. Orthotopic liver transplantation is an effective treatment but limited by the shortage of donor organs, the requirement for life-long immune suppression and surgical challenges. Stem cell transplantation is a promising alternative therapy for fulminant liver failure owing to the immunomodulatory abilities of stem cells. Here, we report that when transplanted into the liver, human endoderm stem cells (hEnSCs) that are germ layer-specific and nontumorigenic cells derived from pluripotent stem cells are able to effectively ameliorate hepatic injury in multiple rodent and swine drug-induced ALF models. We demonstrate that hEnSCs tune the local immune microenvironment by skewing macrophages/Kupffer cells towards an anti-inflammatory state and by reducing the infiltrating monocytes/macrophages and inflammatory T helper cells. Single-cell transcriptomic analyses of infiltrating and resident monocytes/macrophages isolated from animal livers revealed dramatic changes, including changes in gene expression that correlated with the change of activation states, and dynamic population heterogeneity among these cells after hEnSC transplantation. We further demonstrate that hEnSCs modulate the activation state of macrophages/Kupffer cells via cystatin SN (CST1)-mediated inhibition of interferon signaling and therefore highlight CST1 as a candidate therapeutic agent for diseases that involve over-activation of interferons. We propose that hEnSC transplantation represents a novel and powerful cell therapeutic treatment for ALF.

Published
2023

10. Impaired conjugation boosts CO2 electroreduction by Ni(<scp>ii</scp>) macrocyclic catalysts immobilized on carbon nanotubes

Author

Yanjun Huang, Hao Dai, Dooshaye Moonshiram, Zhuofeng Li, Zhi-Mei Luo, Ji-Hong Zhang, Wenxing Yang, Yong Shen, Jia-Wei Wang, and Gangfeng Ouyang

Subjects
Renewable Energy, Sustainability and the Environment, General Materials Science, General Chemistry
Abstract

Attenuated conjugation in a Ni(ii) catalyst simultaneously facilitates the molecule–support interactions and the intrinsic activity, unexpectedly displaying a superior performance in CO2 electroreduction.

Published
2023

15. MIX-RS: A Multi-Indexing System Based on HDFS for Remote Sensing Data Storage

Author

Jiashu Wu, Jingpan Xiong, Hao Dai, Yang Wang, and Chengzhong Xu

Subjects
FOS: Computer and information sciences, Computer Science - Computers and Society, Multidisciplinary, Computer Science - Databases, Computers and Society (cs.CY), Databases (cs.DB)
Abstract

A large volume of remote sensing (RS) data has been generated with the deployment of satellite technologies. The data facilitates research in ecological monitoring, land management and desertification, etc. The characteristics of RS data (e.g., enormous volume, large single-file size and demanding requirement of fault tolerance) make the Hadoop Distributed File System (HDFS) an ideal choice for RS data storage as it is efficient, scalable and equipped with a data replication mechanism for failure resilience. To use RS data, one of the most important techniques is geospatial indexing. However, the large data volume makes it time-consuming to efficiently construct and leverage. Considering that most modern geospatial data centres are equipped with HDFS-based big data processing infrastructures, deploying multiple geospatial indices becomes natural to optimise the efficacy. Moreover, because of the reliability introduced by high-quality hardware and the infrequently modified property of the RS data, the use of multi-indexing will not cause large overhead. Therefore, we design a framework called Multi-IndeXing-RS (MIX-RS) that unifies the multi-indexing mechanism on top of the HDFS with data replication enabled for both fault tolerance and geospatial indexing efficiency. Given the fault tolerance provided by the HDFS, RS data is structurally stored inside for faster geospatial indexing. Additionally, multi-indexing enhances efficiency. The proposed technique naturally sits on top of the HDFS to form a holistic framework without incurring severe overhead or sophisticated system implementation efforts. The MIX-RS framework is implemented and evaluated using real remote sensing data provided by the Chinese Academy of Sciences, demonstrating excellent geospatial indexing performance., Accepted by Tsinghua Science and Technology

Published
2022

18. Poly-2-oxazoline nanoparticles potentiate effectiveness of vismodegib for breast cancer through improvement in pharmacokinetics and reduction in systemic toxicity

Author

Yanqin Lu, Yiming Yang, Xiaohui Liu, Ning Li, Fen Hu, Bolin Zhang, Hao Dai, Haifeng Cai, and Yan Jinyin Yan

Subjects
General Materials Science
Abstract

Breast cancer is one of the most significant health challenges in the world. Vismodegib has been used for treatment of breast cancer limits the prescriptions of this drug. Therefore, it is of great significance to improve therapeutic effect of vismodegib therapy. This study modified the vismodegib with poly-2-oxazoline (POx) nanoparticles (POx-vismo) and examined the therapeutic potential of this approach for treating breast cancer. After preparation of POx-vismo micelles, they were characterized and loading efficiency, which was also measured by high performance liquid chromatography. The POx-vismo and vismodegib were administered to mice with breast cancer and healthy, respectively. Tumor, forebrain and blood samples were taken for analysis of pharmacokinetics and measurement of toxicity, where the concentration of POx was determined. Pharmacodynamic response was evaluated and Western blot analysis was used to determine the expression of retinoblastoma protein (pRB) and proliferating cell nuclear antigen (PCNA). Compared with traditional vismodegib, POx-vismo significantly improved the delivery efficiency of drugs in central nervous system accompanied with higher level of vismodegib. Administration with POx-vismo greatly improved the pharmacokinetics, diminished the toxicity, and strengthened the efficacy. POx-vismo therapy more effectively suppressed tumor cell growth and decreased pRB expression than oral administration of vismodegib. Collectively, the POx effectively served as a carrier of vismodegib in breast cancer and brain. POx-vismo micelles suppressed breast cell growth with low toxicity and addition of POx can enhance the efficacy of vismodegib for breast cancer and improves pharmacokinetics and pharmacodynamic response. These findings provide a novel insight into the drug therapy against the disorder.

Published
2022

22. Adaptive Bi-Recommendation and Self-Improving Network for Heterogeneous Domain Adaptation-Assisted IoT Intrusion Detection

Author

Jiashu Wu, Yang Wang, Hao Dai, Chengzhong Xu, and Kenneth B. Kent

Subjects
Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Cryptography and Security, Computer Networks and Communications, Machine Learning (cs.LG), Computer Science Applications, Computer Science - Networking and Internet Architecture, Computer Science - Computers and Society, Hardware and Architecture, Computers and Society (cs.CY), Signal Processing, Cryptography and Security (cs.CR), Information Systems
Abstract

As Internet of Things devices become prevalent, using intrusion detection to protect IoT from malicious intrusions is of vital importance. However, the data scarcity of IoT hinders the effectiveness of traditional intrusion detection methods. To tackle this issue, in this paper, we propose the Adaptive Bi-Recommendation and Self-Improving Network (ABRSI) based on unsupervised heterogeneous domain adaptation (HDA). The ABRSI transfers enrich intrusion knowledge from a data-rich network intrusion source domain to facilitate effective intrusion detection for data-scarce IoT target domains. The ABRSI achieves fine-grained intrusion knowledge transfer via adaptive bi-recommendation matching. Matching the bi-recommendation interests of two recommender systems and the alignment of intrusion categories in the shared feature space form a mutual-benefit loop. Besides, the ABRSI uses a self-improving mechanism, autonomously improving the intrusion knowledge transfer from four ways. A hard pseudo label voting mechanism jointly considers recommender system decision and label relationship information to promote more accurate hard pseudo label assignment. To promote diversity and target data participation during intrusion knowledge transfer, target instances failing to be assigned with a hard pseudo label will be assigned with a probabilistic soft pseudo label, forming a hybrid pseudo-labelling strategy. Meanwhile, the ABRSI also makes soft pseudo-labels globally diverse and individually certain. Finally, an error knowledge learning mechanism is utilised to adversarially exploit factors that causes detection ambiguity and learns through both current and previous error knowledge, preventing error knowledge forgetfulness. Holistically, these mechanisms form the ABRSI model that boosts IoT intrusion detection accuracy via HDA-assisted intrusion knowledge transfer., Accepted by IEEE Internet of Things Journal

Published
2023

23. Output Prediction of Helical Microfiber Temperature Sensors in Cycling Measurement by Deep Learning

Author

Minghui Chen, Jinjin Han, Juan Liu, Fangzhu Zheng, Shihang Geng, Shimeng Tang, Zhijun Wu, Jixiong Pu, Xining Zhang, and Hao Dai

Subjects
Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials
Abstract

The inconsistent response curve of delicate micro/nanofiber (MNF) sensors during cycling measurement is one of the main factors which greatly limit their practical application. In this paper, we proposed a temperature sensor based on the copper rod-supported helical microfiber (HMF). The HMF sensors exhibited different light intensity-temperature response relationships in single-cycle measurements. Two neural networks, the deep belief network (DBN) and the backpropagation neural network (BPNN), were employed respectively to predict the temperature of the HMF sensor in different sensing processes. The input variables of the network were the sensor geometric parameters (the microfiber diameter, wrapped length, coiled turns, and helical angle) and the output optical intensity under different working processes. The root mean square error (RMSE) and Pearson correlation coefficient (R) were used to evaluate the predictive ability of the networks. The DBN with two restricted Boltzmann machines (RBMs) provided the best temperature prediction results (RMSE and R of the heating process are 0.9705 °C and 0.9969, while the values of RMSE and R of the cooling process are 0.786 6 °C and 0.997 7, respectively). The prediction results obtained by the optimal BPNN (five hidden layers, 10 neurons in each layer, RMSE=1.126 6 °C, R=0.995 7) were slightly inferior to those obtained by the DBN. The neural network could accurately and reliably predict the response of the HMF sensor in cycling operation, which provided the possibility for the flexible application of the complex MNF sensor in a wide sensing range.

Published
2023

24. Accounting for Polychromatic Light in Virtual Shack-Hartmann Wavefront Sensing

Author

Xian Yue, Yaliang Yang, Hao Dai, Shen Chen, Chao Geng, and Yudong Zhang

Subjects
Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials
Abstract

Virtual Shack-Hartmann wavefront sensing (vSHWS) has some significant advantages and is promising for aberration measurement in the field of biomedical optical imaging. The illumination sources used in vSHWS are almost broadband, but are treated as monochromatic sources (only using center wavelength) in current data processing, which may cause errors. This work proposed a data processing method to take into account the multiple wavelengths of the broadband spectrum, named multiple-wavelength centroid-weighting method. Its feasibility was demonstrated through a series of simulations. A wavefront generated with a set of statistical human ocular aberrations was used as the target wavefront to evaluate the performance of the proposed and current methods. The results showed that their performance was very close when used for the symmetrical, but the wavefront error of the proposed method was much smaller than that of the current method when used for the asymmetrical spectrum, especially for the broader spectrum. These results were also validated by using 20 sets of clinical human ocular aberrations including normal and diseased eyes. The proposed method and the obtained conclusions have important implications for the application of vSHWS.

Published
2023

26. Energy Attenuation Prediction of Dye-Doped PMMA Microfibers by Backpropagation Neural Network

Author

Hang Yu, Juan Liu, Jinjin Han, Minghui Chen, Mingjun Ke, Zhili Lin, Zhijun Wu, Jixiong Pu, Xining Zhang, and Hao Dai

Subjects
energy attenuation prediction, Applied optics. Photonics, QC350-467, Optics. Light, Electrical and Electronic Engineering, Backpropagation neural network, dye-doped polymer microfiber, Atomic and Molecular Physics, and Optics, TA1501-1820
Abstract

To figure out the energy attenuation of micro/nanofibers (MNFs) more flexibly and conveniently, a backpropagation neural network (BPNN) is proposed to forecast the output intensity of rhodamine B (RhB) doped polymer microfibers (PMFs). According to the diameter, doping concentration, and propagation distance (L), we realize the L-dependence of output energy predictions for the excitation light (IE) and fluorescence (IF) of the doped PMFs. Hundreds of propagation distance-intensity data pairs acquired from dozens of RhB doped PMFs are used for the BPNN training. The prediction ability of the model is evaluated by the root-mean-square error (RMSE), the mean absolute percentage error (MAPE), and R2. The output intensity prediction performance of BPNN is compared with the traditional exponential-fitting (EF) method. The prediction results indicate that the two-hidden-layer network with one and seventeen neurons respectively provides the best performance. After training, BPNN gives a good intensity prediction for both the IE (RMSE = 3.16×10−2, MAPE = 7.3%, and R2 = 0.9802) and the IF (RMSE = 0.91×10−2, MAPE = 0.89%, and R2 = 0.9696) from the output end of the PMF with different diameters and doping concentrations. The energy losses of the two kinds of light from different doped PMFs are also calculated based on the predicted values, which are similar to the ones obtained from the EF method. The approach based on the BPNN prediction for the energy attenuation of the PMFs shows superiority in flexibility and applicability toward the traditional methods, which could promote the optimal design of the MNF devices and the practical application.

Published
2022

27. Active nanomaterials containing YAPTAZ reshape tumor immune microenvironment and enhance sensitivity of triple-negative breast cancer to immunotherapy

Author

Xiaohui Liu, Yiming Yang, Yanqin Lu, Ning Li, Fen Hu, Bolin Zhang, Hao Dai, Haifeng Cai, and Jinyin Yan

Subjects
General Materials Science
Abstract

The present study designed a new type of active nanomaterials containing Yes-associated protein and transcriptional coactivator with PDZ-binding motif (YAPTAZ) to investigate its role in tumor immune microenvironment and treatment sensitivity in triple-negative breast cancer (TNBC). Three groups were established in this study, namely; blank control group (saline), YAPTAZ group and YAPTAZ-loaded active nanomaterial group. For in vitro assays, the functional role of active nanomaterials containing YAPTAZ in MDA-MB-231 cell proliferation, apoptosis, migration and invasion was analyzed by MTT assay, flow cytometry, scratch test and Transwell assay, respectively. For in vivo assays, tumor xenotransplantation experiment was performed to observe the effect of active nanomaterials containing YAPTAZ on treatment of TNBC. Administration of active nanomaterials containing YAPTAZ decreased proliferation, invasion and migration of TNBC cells, and promoted apoptosis, thereby enhancing the sensitivity of TNBC cells to treatments. The active nanomaterials were characterized by large surface area, high dispersion, specific adhesion function, tumor affinity and adhesion, when prolonging drug’s circulation time. The findings from our study highlight the potential for targeted active nanomaterials containing YAPTAZ for TNBC treatment, providing a new interventional therapy for TNBC.

Published
2022

29. Interferon‐α promotes MHC I antigen presentation of islet β cells through STAT1‐IRF7 pathway in type 1 diabetes

Author

Hemin Jiang, Yue Li, Min Shen, Yucheng Liang, Yu Qian, Hao Dai, Kuanfeng Xu, Xinyu Xu, Hui Lv, Jie Zhang, Tao Yang, and Qi Fu

Subjects
Antigen Presentation, Interferon Regulatory Factor-7, Histocompatibility Antigens Class I, Immunology, Intracellular Signaling Peptides and Proteins, Interferon-alpha, Islets of Langerhans, Mice, Diabetes Mellitus, Type 1, STAT1 Transcription Factor, Mice, Inbred NOD, Animals, Humans, Immunology and Allergy
Abstract

Type 1 diabetes (T1D) is a T cell-mediated autoimmune disease. Increased incidence of T1D was reported in patients receiving IFN-α treatment. However, the exact mechanisms of IFN-α that facilitate the pathogenesis of T1D are not fully understood. To explore the mechanism of IFN-α on the immune system and islets, non-obese diabetic (NOD) mice were injected with IFN-α and the progression of autoimmune insulitis was assessed by haematoxylin and eosin (HE) staining, immunohistochemical and flow cytometry analysis. Transcriptional profiling of islets treated with IFN-α was explored by RNA-seq. IFN-α induced antigen presentation was evaluated by qRT-PCR, western blot and immunofluorescence, and key transcription factors were inhibited by small interfering RNAs (siRNAs). Our data show that IFN-α contributed to the progression of autoimmune insulitis in NOD mice by promoting the proliferation of CD8+ T cells. IFN-α upregulated antigen presentation related genes MHC I, TAP1, B2M, PSMB8, NLRC5 and transcriptional regulator STAT1, STAT2, IRF7 at a time and dose-dependent manner. The silence of STAT1 or STAT2 both weakened IFN-α-induced increase of antigen presenting related molecules. IRF7 was also merely influenced by STAT1 silence. The knockdown of IRF7 decreased the IFN-α induced expressions of TAP1, PSMB8 and MHC I and prevented the expression of STAT2 but not STAT1. Our study demonstrated that STAT1-IRF7-MHC I complex axis were crucial for IFN-α signalling in islets, and created positive feedback through IRF7-STAT2 cascade amplifying signals which accelerated the process of T1D.

Published
2022

30. Constructing a metabolic integral score model for the quantification of metabolic dysfunction and tendency

Author

Hao Dai, Qi Fu, Kuanfeng Xu, Min Sun, Sania M. Kasyanju, Yun Shi, and Tao Yang

Subjects
Blood Glucose, Metabolic Syndrome, Cross-Sectional Studies, Nutrition and Dietetics, Endocrinology, Diabetes and Metabolism, Humans, Medicine (miscellaneous), Waist Circumference, Cardiology and Cardiovascular Medicine, Body Mass Index
Abstract

The binary nature of metabolic syndrome (MetS) cannot quantitatively describe the severity of metabolic abnormalities. We aim to establish a metabolic integral score (MIS) model to quantify the severity and polarity of metabolic disorders and their relationship with insulin sensitivity and secretion.We performed factor analysis on 9950 participants from a cross-sectional study conducted in China. The MIS model was established using 10 variables including body mass index (BMI), waist circumference, hip circumference, glycosylated hemoglobin (HbA1c), fasting and 2-h plasma glucose (FPG, 2h-PG), systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein (HDL) and triglyceride (TG) levels. Four common factors were identified as "glucose factor," "obesity factor," "blood pressure factor," and "lipid factor," respectively, in MIS model (KMO = 0.755, P 0.001). MIS = 0.433 × Factor 1 + 0.267 × Factor 2 + 0.172 × Factor 3 + 0.128 × Factor 4. Insulin sensitivity and β-cell function decreased with the increase of MIS (P 0.001). We classified four metabolic tendencies according to factor quartiles. Individuals in Tendency 1 (severe hyperglycemia) had the worst β-cell function. Tendency 3 (severe hypertension) had the best insulin sensitivity. Tendency 4 (severe dyslipidemia) had preferable β-cell function (P 0.05).Our MIS model provides a quantitative scoring system to assess various patterns of metabolic abnormality that indicate different underlying pathophysiology.

Published
2022

32. New-and-Old Concrete Interface Shearing Strength Test and Shear Slip Behavior Analysis

Author

Wei Guo Zhang, Wen Hao Dai, and Bao Chang Liu

Subjects
Mechanics of Materials, Mechanical Engineering, General Materials Science, Condensed Matter Physics
Abstract

To explore the influence of different factors on the shear resistance of the fiber-reinforced Engineered Cementitious Composite (ECC) and ordinary concrete interface, the influence rule of rib width, rib height, and planting bars ratio on the interface shear strength of steel fiber-reinforced ECC and ordinary concrete was investigated by orthogonal experimental design. The experimental results show the rib width is the most important factor affecting the shear strength of the interface, and the ratio of planting bars minimally influences the shear strength of the interface. The order of main influence factors of shear resistance of interface can be arranged as follows: rib width→rib height→planting bars ratio. Experimental process and load-displacement curve show the failure of the double-sided shear specimen with ribs or planting bars has certain plastic failure characteristics, which extends the failure time of the specimens.

Published
2022

33. Isolation, characterization, immunoregulatory, and antioxidant activities of polysaccharides from Morinda officinalis fermented by Bacillus sp. DU-106

Author

Dong Peng, Zhi-feng Luo, Wen-hao Dai, Bing Du, and Pan Li

Subjects
Engineering (miscellaneous), Food Science, Biotechnology
Abstract

Morinda officinalis (M. officinalis) polysaccharides are valuable ingredients with various bioactive functions. This work aimed to investigate whether fermentation could enhance the bioactivities of M. officinalis polysaccharides. A strain of Bacillus sp. DU-106 was introduced to ferment M. officinalis. Two polysaccharides (namely NMP-1 and FMP-1) were isolated from raw M. officinalis and fermented M. officinalis, respectively. The structure, immunoregulatory, and antioxidant activities of NMP-1 and FMP-1 were investigated. Bacillus sp. DU-106 fermentation changed the monosaccharide composition and conformation of M. officinalis polysaccharides. After fermentation, FMP-1 dramatically stimulated IL-1β secretion in RAW 264.7 macrophages. In vitro, Bacillus sp. DU-106 fermentation of M. officinalis enhanced the DPPH radical, hydroxyl radical, and superoxide anion scavenging activities. In vivo, FMP-1 extended the lifespan and ameliorated oxidative injury of Caenorhabditis elegans. Collectively, Bacillus sp. DU-106 fermentation significantly enhanced the immunoregulatory and antioxidant activities of M. officinalis polysaccharides.

Published
2022

35. InI3-catalyzed polyene cyclization of allenes and its application in the total synthesis of seven abietane-type diterpenoids

Author

Chen-Yu Huo, Tian-Lu Zheng, Wei-Hao Dai, Zi-Hao Zhang, Jin-Da Wang, Dao-Yong Zhu, Shao-Hua Wang, Xiao-Ming Zhang, and Xue-Tao Xu

Subjects
General Chemistry
Abstract

A polyene cyclization mode using the allene group as the initiator has been successfully developed, and its potential utility has been well demonstrated by the collective synthesis of seven abietane-type diterpenoids.

Published
2022

37. Influence of early colorectal cancer component on the positive margins after endoscopic resection: a retrospective study

Author

Qing-Wei Zhang, Zi-Hao Dai, Xiao-Yi Wang, Yun-Jie Gao, Zhi-Zheng Ge, and Xiao-Bo Li

Subjects
Adenoma, Male, Cancer Research, Early colorectal cancer, Hot snare polypectomy, Margins of Excision, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Middle Aged, Endoscopic submucosal dissection, Logistic Models, Oncology, Endoscopic mucosal resection, Genetics, Humans, Female, Intestinal Mucosa, Colorectal Neoplasms, Vertical margin, Carcinoma in Situ, RC254-282, Aged, Retrospective Studies, Research Article
Abstract

Background Endoscopic treatment methods for early colorectal cancer (ECRC) mainly depend on the size and morphology. It is unclear whether different endoscopic resection methods could achieve curative resection for ECRC confined in the mucosa. The study was designed to compare the rate of positive vertical margin (VM) of ECRC with advanced adenomas (AAs) including adenoma > 1 cm, villous adenoma, high-grade intraepithelial neoplasia/dysplasia stratified by different endoscopic resection methods. Methods Rate of positive VM for 489 ECRCs including Intramucosal (pTis) and superficial submucosal invasion (pT1) carcinomas were compared with those of 753 AAs stratified by different endoscopic resection methods using Chi-squared test. Multivariate logistic model was performed to investigate the risk factors of positive VM for different endoscopic resection methods. Results The pTis ECRC exhibited a similar rate of positive VM as that of AAs for en bloc hot snare polypectomy (HSP, 0% Vs. 0.85%, P = 0.617), endoscopic mucosal resection (EMR, 0.81% vs. 0.25%, P = 0.375) and endoscopic submucosal dissection (ESD, 1.82% Vs. 1.02%, P = 0.659). The pTis carcinoma was not found to be a risk factor for positive VM by en bloc EMR (P = 0.349) or ESD (P = 0.368). The en bloc resection achieved for pT1a carcinomas exhibited similar to positive VM achieved through ESD (2.06% Vs. 1.02%, P = 1.000) for AAs. Nonetheless, EMR resulted in higher risk of positive VM (5.41% Vs. 0.25%, P en bloc EMR (odds ratio = 23.90, P = 0.005) but not ESD (OR = 2.96, P = 0.396). Conclusion Collectively, the pTis carcinoma was not found to be a risk factor for positive VM resected by en bloc HSP, EMR or ESD. Additionally, ESD may be preferred over EMR for pT1a carcinomas with lower rate of positive VM.

Published
2022

38. Single-cell entropy network detects the activity of immune cells based on ribosomal protein genes

Author

Qiqi, Jin, Chunman, Zuo, Haoyue, Cui, Lin, Li, Yiwen, Yang, Hao, Dai, and Luonan, Chen

Subjects
Structural Biology, Genetics, Biophysics, Biochemistry, Computer Science Applications, Biotechnology
Abstract

We developed a new computational method, Single-Cell Entropy Network (SCEN) to analyze single-cell RNA-seq data, which used the information of gene-gene associations to discover new heterogeneity of immune cells as well as identify existing cell types. Based on SCEN, we defined association-entropy (AE) for each cell and each gene through single-cell gene co-expression networks to measure the strength of association between each gene and all other genes at a single-cell resolution. Analyses of public datasets indicated that the AE of ribosomal protein genes (RP genes) varied greatly even in the same cell type of immune cells and the average AE of RP genes of immune cells in each person was significantly associated with the healthy/disease state of this person. Based on existing research and theory, we inferred that the AE of RP genes represented the heterogeneity of ribosomes and reflected the activity of immune cells. We believe SCEN can provide more biological insights into the heterogeneity and diversity of immune cells, especially the change of immune cells in the diseases.

Published
2022

39. Coevolutionary insights between promoters and transcription factors in the plant and animal kingdoms

Author

Jing-Song, Zhang, Hai-Quan, Wang, Jie, Xia, Kun, Sha, Shu-Tao, He, Hao, Dai, Xiao-Hu, Hao, Yi-Wei, Zhou, Qiu, Wang, Ke-Ke, Ding, Zhang-Lei, Ju, Wen, Wang, and Luo-Nan, Chen

Subjects
Birds, Gene Expression Regulation, Ecology, Animals, Animal Science and Zoology, Promoter Regions, Genetic, Ecology, Evolution, Behavior and Systematics, Transcription Factors
Abstract

The divergence and continuous evolution of plants and animals contribute to ecological diversity. Promoters and transcription factors (TFs) are key determinants of gene regulation and transcription throughout life. However, the evolutionary trajectories and relationships of promoters and TFs are still poorly understood. Here, we conducted extensive analysis of large-scale multi-omics sequences in 420 animal species and 223 plant species spanning nearly a billion years of evolutionary history. Results showed that promoter GC-content and TF isoelectric points, as features/signatures that accompany long biological evolution, exhibited increasing growth in animal cells but a decreasing trend in plant cells. Furthermore, the evolutionary trajectories of promoter and TF signatures in the animal kingdom provided further evidence that Mammalia as well as Aves evolved directly from the ancestor Reptilia. The strong correlation between promoter and TF signatures indicates that promoters and TFs formed antagonistic coevolution in the animal kingdom, but mutualistic coevolution in the plant kingdom. The distinct coevolutionary patterns potentially drive the plant-animal divergence，divergent evolution and ecological diversity.动物和植物从原始的单细胞生物（绿色鞭毛生物）分化（diverge）并各自持续地演化（evolve），促成了地球上自然生态的多样性（diversity）。在真核生物（eukaryotes）的基因转录（transcription）和调控（regulation）过程中，启动子（promoters）和转录因子（transcription factors）以及它们的相互作用扮演着决定性作用。然而，启动子和转录因子分子的演化轨迹及演化模式目前尚不清楚。通过在跨度大约为十亿年的演化历程上的420个动物物种，223个植物物种基因组和蛋白组序列分析和理化性质分析表明：（1）序列的GC含量（GC-content）和蛋白质的等电点（isoelectric points）可分别作为基因的启动子和转录因子的演化特征印记（signatures）；（2）在动物界，启动子的GC含量和转录因子的等电点，在漫长的演化历程中，表现出同步的持续增长；（3）在植物界，启动子的GC含量和转录因子的等电点，则表现出同步的降低趋势。启动子和转录因子的演化轨迹为“哺乳动物和鸟类一样，都是从爬行动物直接演化而来”提供了新的证据。通过分析启动子和转录因子之间相互作用的理化特征，以及它们之间演化轨迹的强相关性和显著性，表明启动子和转录因子在动物界呈现拮抗的共演化（antagonistic coevolution），而在植物界则呈现互利的共演化（mutualistic coevolution）。该研究为探究启动子与转录因子间的相互作用机理，进一步理解动植物的分化、趋异演化及生态多样性提供了新的洞见。.

Published
2022

41. Care patterns and Traditional Chinese Medicine constitution as factors of depression and anxiety in patients with systemic sclerosis: A cross-sectional study during the COVID-19 pandemic

Author

Qi Kong, Li-Ming Chen, Zong-Hao Dai, Yun-Zhe Tang, Yu-Yang Zhou, Wen-Zhen Tu, Yin-Huan Zhao, and Jia-Qian Zhang

Subjects
Cellular and Molecular Neuroscience, Cognitive Neuroscience, Sensory Systems
Abstract

ObjectiveCare patterns and Traditional Chinese Medicine (TCM) constitution affects the emotion and health of patients with systemic sclerosis (SSc) while the prevalence of COVID-19 may aggravate such patients’ emotion and health. We investigated the depression and anxiety levels of patients with SSc during the pandemic to identify the correlation between care patterns, TCM constitution, and patients’ emotion.Materials and methodsThis was a cross-sectional study. Patients with SSc and healthy individuals were surveyed using the patient health questionnaire-9, generalized anxiety disorder-7, and constitution in Chinese medicine questionnaire and a modified care pattern questionnaire. Factors correlated with depression and anxiety were screened using univariate and multivariate logistic regression analyses.ResultsA total of 273 patients with SSc and 111 healthy individuals were included in the analysis. The proportion of patients with SSc who were depressed was 74.36%, who had anxiety was 51.65%, and who experienced disease progression during the pandemic was 36.99%. The proportion of income reduction in the online group (56.19%) was higher than that in the hospital group (33.33%) (P = 0.001). Qi-deficiency [adjusted odds ratio (OR) = 2.250] and Qi-stagnation (adjusted OR = 3.824) constitutions were significantly associated with depression. Remote work during the outbreak (adjusted OR = 1.920), decrease in income (adjusted OR = 3.556), and disease progression (P = 0.030) were associated with the occurrence of depression.ConclusionChinese patients with SSc have a high prevalence of depression and anxiety. The COVID-19 pandemic has changed the care patterns of Chinese patients with SSc, and work, income, disease progression, and change of medications were correlates of depression or anxiety in patients with SSc. Qi-stagnation and Qi-deficiency constitutions were associated with depression, and Qi-stagnation constitution was associated with anxiety in patients with SSc.Trial registrationhttp://www.chictr.org.cn/showproj.aspx?proj=62301, identifier ChiCTR2000038796.

Published
2023

42. Long non-coding RNA AGAP2-AS1 promotes cell proliferation and invasion through regulating miR-193a-3p/LOXL4 axis in laryngeal squamous cell carcinoma

Author

Pengyu Ren, Xiaorong Niu, Ruimin Zhao, Junsong Liu, Wanli Ren, Hao Dai, Jiayu Chen, Jinfeng Yan, Baiya Li, Yuan Shao, Yanxia Bai, and Peng Han

Subjects
Squamous Cell Carcinoma of Head and Neck, Cell Biology, Gene Expression Regulation, Neoplastic, Protein-Lysine 6-Oxidase, MicroRNAs, Cell Movement, Head and Neck Neoplasms, Cell Line, Tumor, Humans, RNA, Long Noncoding, Molecular Biology, Developmental Biology, Cell Proliferation, Research Paper
Abstract

Laryngeal squamous cell carcinoma (LSCC) is an aggressive malignancy with highly mortality rate. Long non-coding RNA (lncRNA) AGAP2-AS1 is an identified oncogene in several types of cancers. However, the role of AGAP2-AS1 in LSCC remains unclear. The expression levels of AGAP2-AS1 in LSCC tissues and cell lines were measured using qRT-PCR. AGAP2-AS1 was knocked down in LSCC cells through transfection with siRNA-AGAP2-AS1. Cell proliferation and invasion were detected using MTT and transwell assays. Dual-luciferase reporter gene assay was performed to confirm the interaction with AGAP2-AS1 and downstream genes. Our results showed that AGAP2-AS1 expression was remarkably increased in human LSCC tissues and cell lines. Knockdown of AGAP2-AS1 significantly inhibited the proliferation and invasion of LSCC cells. In addition, AGAP2-AS1 sponged miR-193a-3p and regulated its expression in LSCC cells. Inhibition of miR-193a-3p reversed the effects of AGAP2-AS1 knockdown on LSCC cells. Furthermore, Lysyl oxidase-like 4 (LOXL4) was a target gene of miR-193a-3p and the role of miR-193a-3p was mediated by LOXL4. In conclusion, these findings suggest that knockdown of AGAP2-AS1 inhibited the proliferation and invasion of LSCC cells through regulating the miR-193a-3p/LOXL4 axis.

Published
2023

44. Restored UBE2C expression in islets promotes β-cell regeneration in mice by ubiquitinating PER1

Author

Hemin Jiang, Shuai Zheng, Yu Qian, Yuncai Zhou, Hao Dai, Yucheng Liang, Yunqiang He, Rui Gao, Hui Lv, Jie Zhang, Zhiqing Xia, Wenxuan Bian, Tao Yang, and Qi Fu

Abstract

Background The limited proliferation capacity of β-cells contributes to insulin insufficiency, which promotes the onset of diabetes. β-cells secrete multiple beneficial substances, except for insulin; therefore, the regeneration mechanism of β-cells requires further study. Previously, ubiquitin-binding enzyme 2C (UBE2C) was reported to be downstream of the key β-cell transcription factor NKX6.1, but the specific function and mechanism of UBE2C in pancreatic islets remain unknown. Methods We performed islet perfusion, immunofluorescence staining, and transmission electron microscopy (TEM) to examine the role of UBE2C in mice with a Cre-loxP-constructed β-cell-specific knockout (βUbe2cKO) or overexpression through lentivirus infusion within the pancreatic ducts. Single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq, tandem mass tag (TMT) quantification proteomics, immunoprecipitation, and immunoblotting were conducted to explore the mechanisms by which UBE2C regulates β-cell proliferation. Results We discovered that ubiquitin-conjugating enzyme E2C (UBE2C) was highly expressed in a β-cell subgroup, which exhibited active proliferation capacity. We confirmed that UBE2C promotes β-cell compensatory proliferation by activating cell cycle renewal during a high-fat diet (HFD) and weaning. Consequently, β-cell-specific Ube2c knockout (βUbe2cKO) mice developed typical type 2 diabetes owing to β-cell loss caused by insulin insufficiency. Mechanistically, UBE2C combines with CUL1 to regulate PER1 degradation through ubiquitination. Notably, restored Ube2c expression in islets activated β-cell regeneration in streptozotocin (STZ)-induced diabetic mice, and alleviated diabetic hyperglycaemia and glucose intolerance. Conclusion This study indicates that UBE2C positively regulates β-cell proliferation by promoting ubiquitination and degradation of the biological clock suppressor PER1. The UBE2C-mediated beneficial effects on β-cells suggest a promising application in the treatment of diabetic patients with β-cell deficiency.

Published
2023

46. Empagliflozin in Patients with Chronic Kidney Disease

Author

Herrington, William G, Staplin, Natalie, Wanner, Christoph, Green, Jennifer B, Hauske, Sibylle J, Emberson, Jonathan R, Preiss, David, Judge, Parminder, Mayne, Kaitlin J, Ng, Sarah Y A, Sammons, Emily, Zhu, Doreen, Hill, Michael, Stevens, Will, Wallendszus, Karl, Brenner, Susanne, Cheung, Alfred K, Liu, Zhi-Hong, Li, Jing, Hooi, Lai Seong, Liu, Wen, Kadowaki, Takashi, Nangaku, Masaomi, Levin, Adeera, Cherney, David, Maggioni, Aldo P, Pontremoli, Roberto, Deo, Rajat, Goto, Shinya, Rossello, Xavier, Tuttle, Katherine R, Steubl, Dominik, Petrini, Michaela, Massey, Dan, Eilbracht, Jens, Brueckmann, Martina, Landray, Martin J, Baigent, Colin, Haynes, Richard, The EMPA-KIDNEY Collaborative Group: Colin Baigent, Martin J Landray, Christoph Wanner, William G Herrington, Richard Haynes, Jennifer B Green, Sibylle J Hauske, Martina Brueckmann, Mark Hopley, Maximillian von-Eynatten, Jyothis George, Susanne Brenner, Alfred K Cheung, David Preiss, Zhi-Hong Liu, Jing Li, Laiseong Hooi, Wen Liu, Takashi Kadowaki, Masaomi Nangaku, Adeera Levin, David Cherney, Roberto Pontremoli, Aldo P Maggioni, Natalie Staplin, Jonathan Emberson, Stefan Hantel, Shinya Goto, Rajat Deo, Katherine R Tuttle, Michael Hill, Parminder Judge, Kaitlin J Mayne, Sarah Y A Ng, Xavier Rossello, Emily Sammons, Doreen Zhu, Peter Sandercock, Rudolf Bilous, Charles Herzog, Paul Whelton, Janet Wittes, Derrick Bennett, Patricia Achiri, Chrissie Ambrose, Cristina Badin, Jill Barton, Richard Brown, Andy Burke, Sebastian Butler, Rejive Dayanandan, Pia Donaldson, Robert Dykas, Lucy Fletcher, Kate Frederick, Hannah Kingston, Mo Gray, Emily Harding, Akiko Hashimoto, Lyn Howie, Susan Hurley, Ryonfa Lee, Nik Luker, Kevin Murphy, Mariko Nakahara, John Nolan, Michelle Nunn, Sorcha Mulligan, Akiko Omata, Sandra Pickworth, YanRu Qiao, Shraddha Shah, Karen Taylor, Alison Timadjer, Monique Willett, Liz Wincott, Qin Yan, Hui Yu, Louise Bowman, Fang Chen, Robert Clarke, Michelle Goonasekera, Waseem Karsan, Marion Mafham, Christina Reith, Mohammed Zayed, Ritva Ellison, Rowan Moys, Will Stevens, Kevin Verdel, Karl Wallendszus, Chris Bowler, Anna Brewer, Andy Measor, Guanguo Cui, Charles Daniels, Angela Field, Bob Goodenough, Ashley Lawson, Youcef Mostefai, Dheeptha Radhakrishnan, Samee Syed, Shuang Xia, Ruth Adewuyi-Dalton, Thomas Arnold, Anne-Marie Beneat, Anoushka Bhatt, Chloe Bird, Andrew Breach, Laura Brown, Mark Caple, Tatyana Chavagnon, Karen Chung, Sarah Clark, Luminita Condurache, Katarzyna Eichstadt, Marta Espino Obrero, Scarlett Forest, Helen French, Nick Goodwin, Andrew Gordon, Joanne Gordon, Cat Guest, Tina Harding, Michal Hozak, Matthew Lacey, David MacLean, Louise Messinger, Stewart Moffat, Martin Radley, Claire Shenton, Sarah Tipper, Jon Tyler, Lesley Weaving, James Wheeler, Elissa Williams, Tim Williams, Hamish Woodhouse, Angela Chamberlain, Jo Chambers, Joanne Davies, Denise Donaldson, Pati Faria-Shayler, Denise Fleming-Brown, Jennifer Ingell, Carol Knott, Anna Liew, Helen Lochhead, Juliette Meek, Isabel Rodriguez-Bachiller, Andrea Wilson, Patrick Zettergren, Rach AitSadi, Ian Barton, Alex Baxter, Yonghong Bu, Lukasz Danel, Sonja Grotjahn, Rijo Kurien, Michael Lay, Archie Maskill, Aleksandra Murawska, Rachel Raff, Allen Young, Rebecca Sardell, Vladimir Cejka, Marcela Fajardo-Moser, Christian Hartner, Doris Poehler, Janina Renner, Franziska Scheidemantel, Miya Bryant, Anita Hepditch, Cassandra Johnson, Erin Latore, Yolanda Miller, Lauren Price, Merilee Whalen, Ashleigh Wheeler, Jenny Ingell, Yu An, Yinghua Chen, Peiling Chen, Hao Dai, Hong Du, Fang Feng, Qing Guo, Libo Hou, Wuhanbilige Hundei, Binbin Jin, Yan Li, Jiamin Liu, Xia Song, Yanping Wang, Yanwu Yu, Ning Zhang, Lingshan Zhao, Hui Zhong, Cheng Beng Goh, Ye Mun Low, Soon Yi Sor, Farah Hanis Zulkipli, Sarojini Sivanandam, Natsuki Arai, Ai Fukasawa, Mizue Furukawa, Keisuke Habuki, Shoko Hayashi, Wakako Isari, Saki Kanegae, Maria Kawai, Reiki Kobayashi, Takako Kuramae, Chika Kuribayashi, Sawako Maeno, Satoshi Masumoto, Tomoko Morisaki, Minoru Oda, Kazue Sawada, Kenta Sugamori, Ayana Tatsuzawa, Aiko Tomita, Kazuyuki Yuasa, Hiroko Inazawa, Amanda Axler, Kerri Gallo, Ester Baldini, Barbara Bartolomei Mecatti, Francesca Bianchini, Martina Ceseri, Laura Cipressa, Gianna Fabbri, Andrea Lorimer, Donata Lucci, Sharang Ghavampour, Anja Knoppe, Hans Schmidt-Gurtler, Hubert Dumann, Sybille Merscher, Margret Patecki, Georg Rainer Schlieper, Anke Torp, Bianca Weber, Maja Zietz, Bernd Hohenstein, Urs Benck, Diliana Draganova, Thomas Weinreich, Lothar Wolf, Jasmine Gaidu, Hanna Reiner, Mandy Visnjic, Daniel Steffl, Marie Breitenfeldt, Annette Kraemer-Guth, Christine Braun, Simone Hagge, Michael Schomig, Stephan Matthias, Dominik Stoffler, Beate Schumacher, Thomas Sitter, Louise Fuessl, Julia Krappe, Jerome Loutan, Volker Vielhauer, Luciano Andriaccio, Magdalena Maurer, Bernhard Winkelmann, Martin Dursch, Linda Seifert, Linda Tenbusch, Julia Weinmann-Menke, Simone Boedecker, Wiebke Kaluza-Schilling, Daniel Kraus, Carina Krieger, Margit Schmude, Anne Schreiber, Ewelina Eckrich, Diethelm Tschope, Abdulwahab Arbi, Young Lee-Barkey, Bernd Stratmann, Natalie Prib, Sina Rolfsmeier, Irina Schneider, Lars Rump, Johannes Stegbauer, Christine Pötz, Mara Schemmelmann, Claudia Schmidt, Michael Koch, Sendogan Aker, Annika Küpper, Manuela Martin, Thiemo Pfab, Christian Albert, Michael Haase, Barbara Zander, Claudia Schneider-Danwitz, Wolfgang Seeger, Wolf-Adam Seeger, Britta Zemann, Christoph Stellbrink, Kristin Marx, Ekaterina Stellbrink, Britta Brettschneider, Stephanie Watson, Marion Iselt, Gerhard Klausmann, Inga-Nadine Kummer, Auguste Kutschat, Simone Streitenberger, Matthias Girndt, Silke Markau, Ina Girakossyan, Claudia Hanf, Joachim Beige, Ralph Wendt, Ulrike Schmidt, Andreas Schneider, Roland Veelken, Claudia Donhauser, Luis Becker, Nexhat Miftari, Ricarda Wolfling, Sarah Morlok, Christian Hugo, Alexander Paliege, Jens Passauer, Julian Stumpf, Annegret Fleischer, Kerstin Haaser, Bernhard Kraemer, Jan Jochims, Bernd Kruger, Claudia Foellinger, Anastassiya Reisler, Frank Strutz, Stefan Haack, Ursula Hohenstatt, Martin Busch, Konstantin Herfurth, Gunter Wolf, Rainer Paul, Hermann Haller, Jessica Kaufeld, Jan Menne, Elisabeth Bahlmann-Kroll, Angela Bergner, Horst Weihprecht, Aydin Er, Florian Sonntag, Elif Turan, Michael Wittmann, Franziska Klauser, Eva Voigt, Volker Schettler, Egbert Schulz, Madlen Rohnstock, Elke Schettler, Bernd Schroppel, Rene van Erp, Martin Kachele, Ulla Ludwig, Lena Schulte-Kemna, Waltraud Kmietschak, Elke Preiss, Martina Ruocco, Gunnar Heine, Martin Brzoska, Sebastian Gabel, Christina Büttner, Asma Sabarai, Bernhard Banas, Tobias Bergler, Yvonne Ehrl, Franz Putz, Antonia Schuster, Stefanie Kuhn, Torsten Schramm, Stefan Degenhardt, Gerhard Schmidt, Lea Weiland, Ulrike Giebeln-Hudnell, Jan Kielstein, Gabriele Eden, Brigitte Fuchs, Gina Morig, Manuela Winkler, Harald Darius, Charalampos Kriatselis, Carl-Philipp Roesch, Astrid Maselli, Dominik Alscher, Markus Ketteler, Moritz Schanz, Severin Schricker, Bianka Rettenmaier, Andrea Schwab, Pablo Pergola, Irene Leal, Melissa Cagle, Anna Romo, Anthony Torres, Sucharit Joshi, Kulli Barrett, Alexis Africano, Vicki Dodds, Dorleena Gowen, Ashlee Morris, Juan Fernandez, Guillermo Jimenez, Ricardo Viera, Kendaling Bruce, Ryan Barrios, Maylin Garcia, Kerelyn Garcia, Iradis Leal, David Tietjen, David Bains, Carlo Castillo, Genielle Brewer, Justin Davis, Natalie Freking, Brittany Golson, Sally Ham, Jesslyn Roesch, Pusadee Suchinda, Shameem Beigh, Usah Lilavivat, Joyce Bilton, Kim Bocchicchia, Jeffrey Turner, Neera Dahl, Aldo Peixoto, Yasemin Kavak, Lauren Liberti, Hari Nair, Nicolas Page, Stephanie Rosenberg, Kathryn Simmons, Tamara Isakova, Rebecca Frazier, Rupal Mehta, Anand Srivastava, Patrick Fox, Jonathan Hecktman, Alexander Hodakowski, Carlos Martinez, Rachel Phillips, Alexis Stevenson, Reem Mustafa, Kyle Jansson, Cassandra Kimber, Jason Stubbs, Ahmad Tuffaha, Sri Yarlagadda, Debbie Griffin, Elisabeth Laundy, Zhuo Tang, Radica Alicic, Ann Cooper, Lisa Davis, Ashwini Gore, Rebecca Goldfaden, Leslie Harvill, Lisa Hichkad, Barry Johns, Thomas Jones, Kayla Merritt, Jennifer Sheldon, Jennifer Stanfield, Lindsay Alexander, Kaitlyn Preston, Lindsey Wood, Rajesh Pradhan, Roger DeRaad, Kelli McIntosh, Louis Raymond, Michael Shepperd, Susan McLaughlin, Mary Seifert, Andrew Shepherd, Joseph Aiello, William Durham, Laurie Loudermilk, John Manley, Sabrina Burnette, Stephanie Evans, Tara Johnson, Lance Sloan, Judy Ann Acosta, Stacy Gillham, Katia Sloan, SueAnn Squyres, Michael Rocco, Amret Hawfield, Ben Bagwell, Lauren Richmond, Joseph Soufer, Subha Clarke, Amanda Aliu, Kristine Calabrese, Amanda Davis, Veronica Poma, Tracy Spinola, James Magee, Ricardo Silva, Rushab Choksi, Lorraine Dajani, John Evans, Anil George, Prasanth Krish, Gerard Martins, Mae Sheikh-Ali, David Sutton, Freda Driver, Abraham Hanburry, Laura Hume, Amber Hurst, Matthew Taddeo, Marla Turner, Veronica Yousif, Srinivasan Beddhu, Laith Al-Rabadi, Nikita Abraham, Amalia Caamano, Judy Carle, Victoria Gonce, Kaitlyn Staylor, Na Zhou, Shweta Bansal, Manoj Bhattarai, Kumar Sharma, Subrata Debnath, Aliseiya Garza, Chakradhar Velagapudi, Sergio Rovner, Javier Almeida, Pablo Casares, Verlaine Stewart-Ray, Rene Almaraz, Renata Dayrell, Ana Moncada, Ricardo Pulido, Roxana Rodriquez, Wasim Deeb, Kathryn DeGoursey, Rodel Gloria, Trevor Greene, Robert Miller, Edward Pereira, Miguel Roura, Debbie Domingo, Sasha Dorestin, William Hodge, Cathy Jackson, Deborah Lund, Katrina Taylor, Kenneth Boren, Brittany Cleveland, Sandra Gaiser, Mandeep Sahani, Logan Aldrich, Exodus Edmerson, Edmond Limon, Cole Valletta, Patricia Vasquez, Christopher Provenzano, Navkiranjot Brar, Heather Henderson, Bellovich Keith, Qur Khai, Quresh Khairullah, Gail Makos, Joel Topf, Sherry Gasko, Rosemarie Henschel, Kaitlin Knapp, Teresa Kozlowski, Paula LaFleur, Ashwathy Varughese, Hui Xue, Patricia Wu, Olga Arechiga, Shan Darbeau, Michael Fechter, Stephanie Martinez, Lenita Hanson, Nyla Cooper, Arelis Madera, Jay Cadorna, Rita Sheridan, Helen Sparks, Bradley Eilerman, Susanne Bodine, Wael Eid, Rebecca Flora, Amber Avery, Cashmere Hardy, Mihaela Biscoveanu, Steven Nagelberg, Tracey Cummins, Frederic Rahbari-Oskoui, Anju Oommen, Zohreh Forghani, Stacie Hitchcock, Darya Hosein, Diane Watkins, Minesh Patel, Anthony Lambert, Elizabeth Newman, Autumn Wood, Tammy Ross, Stephany Topping, Jeffrey Mulhern, Lorna Murphy, Ann Vasseur, Gregory Greenwood, Alexander Hadley, Denise Laurienti, Christopher Marshall, Nicholas McLean, Scott Satko, Brandy Caudill, Jacob Maris, Janice Rogers, Cindy Vanhoy, George Thomas, Georges Nakhoul, John O'Toole, Jonathan Taliercio, Leslie Cooperman, Marina Markovic, Barbara Tucky, Devasmita Dev, Alia Hasan, Hima Yalamanchili, Namita Jain, Lesley McNeil, Eric Wines, Jean Park, Adline Ghazi, Mia Hamm, Tejas Patel, Amy Mottl, Emily Chang, Vimal Derebail, Emmie Cole, Anne Froment, Sara Kelley, Jordan Osmond Foster, Vahid Mahabadi, Golriz Jafari, Anita Kamarzarian, Wendy Arriaga, Daisy Arteaga, Rosario Machicado, Genesis Naverrete, Prashant Kumar, Imran Nazeer, Karina Urquia, Tammi Glider, Vickie Jones, Savannah Rucker, Jennifer Wiley, Rahul Pandey, Jesus Arroyo, Harish Pariani, Mohammad Ahmad, Shahin Mozaffari, Erika Perez, Matthew Budoff, Sion Roy, Divya Birudaraju, Ahmed Ghanem, Sajad Hamal, Stephen Aronoff, Elisa Joye Petr, Richard Sachson, Jaime Wiebel, Sana Akram, Laurie Jones, Curtis Knight, Maurie Tarlac, Shahbaz Ahmed, Harold Szerlip, Akinwande Akinfolarin, Ankit Mehta, Shana Camp, Cindy Castro, Zanaida Cooper, Jessica Terry, Ahmed Awad, Bhavya Kothapalli, Ryan Lustig, Serine Alfaress, Hyder Jasim, Mary Parrigon, Dennis Karounos, Sadiq Ahmed, Maggie Berry, Ruth Oremus, Carlos Hernandez-Cassis, Elias Ugwu, Nazia Junejo, Nancy Suazo, Mark Segal, Amir Kazory, Sherry Brown, Tristan Daniels, Sofia Dayi, Renee Hogan, Kathy McCray, Jennifer Stickley, Mahboob Rahman, Mirela Dobre, Lavinia Negrea, Aparna Padiyar, Nishigandha Pradhan, Arash Rashidi, Nagaraju Sarabu, Vicki Donley, Tricia Young, Godson Oguchi, Judepatricks Onyema, Kahla Damianik, Jack Dienes, Judith Plummer-Morgan, Marilyn Roman, Mauver Skipper, Stacey-Ann Villaruel, Krystle Williams, Danny Sugimoto, Jeffrey Dugas, Ismeal Ahmed, Jamie Bhairoo, Dolores Rijos, Huzaifa Salim, Madita Gavrila, Kathryn Lafferty, Ria Rabara, Sally Ruse, Maria Weetman, James Bushnell, Albert Power, Alison Jenkins, Stefanie Jones, Amanda Scott, Cath Byrne, Mark Jesky, Alison Cowley, Emma McHaffie, Holly Waterfall, Jo Taylor, Laura Bough, Thomas Phillips, Barbara Winter-Goodwin, Sui Phin Kon, Iain MacDougall, Eirini Lioudaki, Sapna Shah, Claire Sharpe, Francisco Aguilar, Abegail Hernandez Pena, Conception Pugay, Amelia Te, Hugh Finn, Wasim Hanif, Samiul Mostafa, Alice Aitken, Katharine Draxlbauer, Evelina Grobovaite, Jennifer Kearney, Theresa McCarthy, Giorgio Gentile, Duncan Browne, Palanichamy Chellamuthu, Tabinda Dugal, Terri Chant, Laura Jones, Emily Laity, Megan Miners, James Muir, Elizabeth Swanson, Andrew Frankel, James Tomlinson, Marlon Alegata, Rashid Almasarwah, Anthoula Apostolidi, Maria Vourvou, Thomas Walters, Maarten Taal, Hari Dukka, Nitin Kolhe, Carly McDonald, Kelly White, Shiva Ugni, Smita Gunda, Rotimi Oluyombo, Vicki Brindle, Ping Coutts, Tracy Fuller, Evelyn Nadar, Suresh Ramadoss, Nichola Motherwell, Susannah Pajak, Louise Tonks, Sunil Bhandari, Richard Bodington, Adil Hazara, Dominic Fellowes, Christopher Wong, Christopher Goldsmith, Sherald Barnes, Ann Bennett, Claire Burston, Samantha Hope, Nicola Hunt, Lini Kurian, Richard Fish, Daniela Farrugia, Judy Lee, Emma Sadler, Hannah Turner, Christopher Hill, Henry Brown, Agnes Masengu, Peter Maxwell, Nina Bleakley, Hugh Murtagh, William Petchey, Vivian Yiu, Joanne Kellett, Angharad Williams, Helen Clarke, Victoria Carnall, Sarah Benyon, Caroline Blake, Stephanie Estcourt, Jane Piper, Neal Morgan, Carolyn Hutchinson, Teresa McKinley, Alastair Woodman, Judi Graham, Niall Leonard, John Smyth, Vicki Adell, Samantha Hagan, Ben Caplin, Amin Oomatia, Eleanor Damian, Toluleyi Sobande, Tim Doulton, Michael Delaney, Mahmoud Montasser, Jenny Hansen, David Loader, Angela Moon, Frances Morris, Smeeta Sinha, Chukwuma Chukwu, Amy Hudson, Diane Campbell, Melanie Kershaw, Stephanie Whittaker, Ayesha Irtiza-Ali, Farid Ghalli, Heba Nosseir, Allison Leslie, Kate Trivedi, Donald Fraser, Mohammad Alhadj Ali, Sian Griffin, Farah Latif, Justyna Witczak, Alexa Wonnacott, Lynda Jeffers, Yvette Webley, Paul Phelan, Eve Miller-Hodges, Ailsa Geddes, Margaret Glenwright, Amy Hunter, Thomas Pickett, Jim Moriarty, Linda Hill, Amanda Tyler, Waqar Ayub, Gail Evans, Sue Hewins, Davina Hewitt, Kerry Read, Samira Bell, Leanne Cosgrove, Rachel Craik, Shona Murray, Nitin Bhandary, Holly Coles, Rashmi Easow, Maya Joseph, Arif Khwaja, Yvonne Jackson, Angeline Mbuyisa, Rachel Sellars, Nihil Chitalia, Cynthia Mohandas, Anca Gherman, Charlotte Kamundi, Olumide Olufuwa, Kieran McCafferty, Adedolapo Adeleke, Cara Healy, Damini Jeyarajah, Edward Kinsella-Perks, Richard Smith, Brian Camilleri, Carol Buckman, Jenny Finch, Vanessa Rivers, Andrew Connor, Sheila Carr, Lisa Shainberg, Andrew Lewington, Richard Baker, Suzannah Dorey, Kay Tobin, Rosalyn Wheatley, Debasish Banerjee, Richard Hull, Sharirose Abat, Riny Paul, Mahzuz Karim, Zay Htet, Saad Tufail, Ravi Varma, Karen Convery, Deirdre Fottrell-Gould, Lisa Hudig, Emily Tropman, Thahir Abdul-Samad, Anne Grace, Marie Phipps, Rebecca Suckling, Subash Somalanka, Bhrigu Sood, Pauline Swift, Sarah Acheampong, Kwame Ansu, Martia Augustin, Anna Sampson, Lynn Vinall, Kim Wren, Shamila Wanninayake, Nicholas Wooding, Heather Edwards, Lydia Owen, Stephanie Bolton, Marion Carson, Michael Matthews, Nigel Brunskill, Jorge Jesus-Silva, Alex Howson, Mary Quashie-Akponeware, Hilary Tindall, Chidambaram Nethaji, Helen Eldon, Rajan Patel, Patrick Mark, Alastair Rankin, Michael Sullivan, Kirsty Forsyth, Rowan McDougall, Tanaji Dasgupta, Louisa Davies, Maggie Ryder, Philip Grimmer, Clare Macdonald, Mary Webster, Newcastle Newcastle, Timothy Ellam, Edwin Wong, Christine Meshykhi, Andrea Webster, Peter Wilson, Enric Vilar, Jocelyn Berdeprado, Eunice Doctolero, Lily Wilkinson, Frank McCarroll, Hesham Ammar, Ying Kuan, Conor Moran, Girish Shivashankar, Ryan Campbell, Deborah Glowski, Paula McDermott, Amar Ali, Zuber Patel, Christine Bond, Gillian Whalley, Haitao Zhang, Liu Yang, Lihua Zhang, Tingting Kan, Ling Zhu, Jinghong Zhao, Weiping Hou, Jing Wu, Hong Cheng, Weijing Bian, Zhirui Zhao, Fengmin Shao, Huixia Cao, Xiaojing Jiao, Peiyuan Niu, Jianying Niu, Yu Chen, Lihong Zhang, Shenglang Zhu, Haiyan Lin, Shaopeng Yao, Jiehui Chen, Ying Jiang, Ying Hu, Huaying Xiao, Fuye Yang, Xinzhou Zhang, Baochun Guo, Qiu Jin, Lixia Liu, Xiangcheng Xiao, Yanyun Xie, Ting Meng, Chuanwen Xu, Jie Huang, Yanmei Xu, Weixin Kong, Xiaoliang Wang, Qianpan Liu, Xueying Wang, Ming Gao, Xiumei Hu, Ying 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Maki, Muto, Masahiro, Nakata, Masami, Nakata, Junichiro, Nishida, Yuya, Nohara, Nao, Ogihara, Takeshi, Sato, Daisuke, Sato, Junko, Sato, Hiroaki, Suzuki, Yusuke, Suzuki, Ruka, Suzuki, Hitoshi, Takagi, Miyuki, Tamura, Yoshifumi, Uchida, Toyoyoshi, Ueda, Seiji, Asawa, Miki, Miyaji, Minako, Nagashima, Eri, Shibata, Yoshie, Yanagisawa, Eri, Yamauchi, Toshimasa, Hirakawa, Yosuke, Nishi, Hiroshi, Shojima, Nobuhiro, Horikawa, Satoko, Nakayama, Yukiko, Yamada, Naoko, Omori, Yuki, Yano, Shintaro, Ioka, Miyabi, Kuwabara, Nahoko, Nagano, Remi, Nozawa, Megumi, Osawa, Yumi, Maegawa, Hiroshi, Kume, Shinji, Araki, Shinichi, Miyazawa, Itsuko, Morino, Katsutaro, Kawai, Ikuko, Sobata, Masumi, Takaoka, Motoko, Iwaita, Yasushi, Udagawa, Takashi, Inamori, Ami, Kawase, Aya, Yamanaka, Aya, Shimano, Hitoshi, Fujita, Akiko, Iwasaki, Hitoshi, Kai, Hirayasu, Osaki, Yoshinori, Saito, Chie, Sekiya, Motohiro, Tsunoda, Ryoya, Yamagata, Kunihiro, Nakamura, Rikako, Yamada, Aiko, Ohsugi, Mitsuru, Awazawa, Motoharu, Bouchi, Ryotaro, Hashimoto, Shota, Hashimoto, Makiko, Hisatake, Tomoko, Ihana, Noriko, Ishizuka, Koko, Izumi, Kazuo, Kajio, Hiroshi, Kobayashi, Michi, Kodani, Noriko, Maruyama, Koji, Matsumoto, Michihiro, Matsushita, Maya, Nakamura, Tomoka, Sugiyama, Takehiro, Tanabe, Akiyo, Terakawa, Aiko, Ueki, Kojiro, Orimo, Yuko, Ozawa, Takako, Takahira, Eriko, Yamasaki, Yoshimitsu, Haneda, Masakazu, Tomita, Tadahiro, Akimoto, Saori, Fujimoto, Akihiro, Ishihara, Kenji, Murakami, Chiho, Nishiyama, Akiyo, Toyonaga, Yukiko, Uozumi, Kana, Yamaji, Yukihiro, Shigehara, Tetsuya, Okajyo, Jun, Shimizu, Yukihiro, Iwasaki, Shingo, Fukao, Yuki, Furusho, Megumi, Nunokawa, Shintaro, Katagiri, Hideki, Izumi, Tomohito, Kaneko, Keizo, Kodama, Shinjiro, Miyazaki, Mariko, Munakata, Yuichiro, Nagasawa, Tasuku, Oe, Yuji, Sugawara, Hiroto, Takahashi, Kei, Hirata, Kazushige, Inomata, Keiko, Otomo, Shoko, Uchida, Taeko, Yamashita, Chigusa, Kiyosue, Arihiro, Tamura, Ryota, Dube, Francoi, Bolduc, Marilene, Talbot, Marie-Christine, Cham, Leslie, Lai, Vesta, Tse, Josephine, Jolly, Shivinder, Duck, Tabbatha, Lyle, Scott, Epp, Rachel, Galloway, Camille, Haskett, Susan, Matvienko, Elizabeta, Paulsen, Liam, Moist, Louise, Lozon, Zabrina, Ramsey, Tina, Whitmore, Brittany, Al-Zeer, Bader, Macleod, Paula, O'Sullivan, Aoife, Sheriff, Zainab, Tholl, Sam, Pandey, Amritanshu, Armstrong, Samantha, Gebeyehu, Bethelihem, Toth, Patrick, Goldenberg, Ronald, Jahangiriesmaili, Mahsa, Sanguila, Shariff, Suresh, Neethi, Talsania, Tanvi, Zalunardo, Nadia, Agharazii, Mohsen, Roussel, Marie-Pier, Saillant, Annie, Samson, France, Bajaj, Harpreet, Bhavsar, Miken, Dhall, Parul, Dhillon, Gagandeep, Grewal, Bhupinder, Nimbkar, Taniya, Madore, Francoi, Marcotte, Guylaine, Steen, Oren, Bullen, Mathura, Raguwaran, Shayani, Valleteau, Andre, Langlois, Marie-France, Brown, Christine, Steele, Andrew, Garrity, Melissa, Ghate, Taneera, Robinson, Holly, Tolibas, Michael, Tailor, Chetna, Elliott, Lauren, McClary-Wright, Christine, Boreky, Fadia, Fikry, Sameh, Ali, Ayesha, Barot, Chintankumar, Basily, Wagdy, Saram, Thisun, Varad, Vinay, Khandwala, Hasnain, Aguilera, Alex, Alvarez, Patricia, Gill, Balwinder, Huda, Nazihah, Navivala, Aamir, Pinto, Daniel, Bevilacqua, Micheli, Fung, Elaine, Hernandez, Geraldine, Mann, Puneet, Saini, Jaskiran, Rabasa-Lhoret, Remi, Bovan, Danijela, Devaux, Marie, Barnini, Cecilia, Leoncini, Giovanna, Manco, Luca, Nobili, Giulia, Piemontese, Matteo, Aucella, Filippo, Grifa, Rachele, Totaro, Francesco, La Manna, Gaetano, Capelli, Irene, Cianciolo, Giuseppe, Lerario, Sarah, Zappulo, Fulvia, Rosati, Alberto, Fani, Filippo, Spatoliatore, Giuseppe, Gesualdo, Loreto, Pesce, Francesco, Russo, Maria, Zippo, Maria, Cafiero, Cesira, Motta, Daria, Bianco, Simona, Bilucaglia, Donatella, Messa, Piergiorgio, Pavone, Laura, Tripodi, Federica, Vettoretti, Simone, Fioretto, Paola, Carraro, Gianni, Farnia, Filippo, Postal, Anna, D'Amelio, Alessandro, Cardone, Antonio, Piccinni, Giovanni, Aloisi, Annalisa, Scolari, Francesco, Alberici, Federico, Guerini, Alice, Saccà, Chiara, Salviani, Chiara, Zani, Roberta, DE NICOLA, Luca, Garofalo, Carlo, Elena Liberti, Maria, Minutolo, Roberto, Pennino, Luigi, Polese, Lucio, Mené, Paolo, Barberi, Simona, Falcone, Clorinda, Russo, Francesco, Caroppo, Maurizio, Santorelli, Gennaro, Rivera, Rodolfo, Santoro, Domenico, Giuffrida, Alfio, Zirino, Fortunata, Calvi, Cristina, Estienne, Luca, Gambaro, Giovanni, Gangemi, Concetta, Ortalda, Vittorio, Pessolano, Giuseppina, Grandaliano, Giuseppe, Baccaro, Rocco, Ferraro, Pietro, Mangiacapra, Roberto, Melandri, Marco, Foligno, Nadia, Quartagno, Rita, Vezzoli, Giuseppe, Brioni, Elena, and Group, EMPA-KIDNEY Collaborative

Subjects
chronic renal disease, empagliflozin, empa-kidney, General Medicine
Abstract

Background The effects of empagliflozin in patients with chronic kidney disease who are at risk for disease progression are not well understood. The EMPA-KIDNEY trial was designed to assess the effects of treatment with empagliflozin in a broad range of such patients. Methods We enrolled patients with chronic kidney disease who had an estimated glomerular filtration rate (eGFR) of at least 20 but less than 45 ml per minute per 1.73 m2 of body-surface area, or who had an eGFR of at least 45 but less than 90 ml per minute per 1.73 m2 with a urinary albumin-to-creatinine ratio (with albumin measured in milligrams and creatinine measured in grams) of at least 200. Patients were randomly assigned to receive empagliflozin (10 mg once daily) or matching placebo. The primary outcome was a composite of progression of kidney disease (defined as end-stage kidney disease, a sustained decrease in eGFR to Results A total of 6609 patients underwent randomization. During a median of 2.0 years of follow-up, progression of kidney disease or death from cardiovascular causes occurred in 432 of 3304 patients (13.1%) in the empagliflozin group and in 558 of 3305 patients (16.9%) in the placebo group (hazard ratio, 0.72; 95% confidence interval [CI], 0.64 to 0.82; PConclusions Among a wide range of patients with chronic kidney disease who were at risk for disease progression, empagliflozin therapy led to a lower risk of progression of kidney disease or death from cardiovascular causes than placebo. (Funded by Boehringer Ingelheim and others; EMPA-KIDNEY ClinicalTrials.gov number, NCT03594110. opens in new tab; EudraCT number, 2017-002971-24. opens in new tab.)

Published
2023

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