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1. From Hardware Fingerprint to Access Token: Enhancing the Authentication on IoT Devices

Author: Xiao, Yue, He, Yi, Zhang, Xiaoli, Wang, Qian, Xie, Renjie, Sun, Kun, Xu, Ke, Li, Qi, Xiao, Yue, He, Yi, Zhang, Xiaoli, Wang, Qian, Xie, Renjie, Sun, Kun, Xu, Ke, and Li, Qi
Abstract: The proliferation of consumer IoT products in our daily lives has raised the need for secure device authentication and access control. Unfortunately, these resource-constrained devices typically use token-based authentication, which is vulnerable to token compromise attacks that allow attackers to impersonate the devices and perform malicious operations by stealing the access token. Using hardware fingerprints to secure their authentication is a promising way to mitigate these threats. However, once attackers have stolen some hardware fingerprints (e.g., via MitM attacks), they can bypass the hardware authentication by training a machine learning model to mimic fingerprints or reusing these fingerprints to craft forge requests. In this paper, we present MCU-Token, a secure hardware fingerprinting framework for MCU-based IoT devices even if the cryptographic mechanisms (e.g., private keys) are compromised. MCU-Token can be easily integrated with various IoT devices by simply adding a short hardware fingerprint-based token to the existing payload. To prevent the reuse of this token, we propose a message mapping approach that binds the token to a specific request via generating the hardware fingerprints based on the request payload. To defeat the machine learning attacks, we mix the valid fingerprints with poisoning data so that attackers cannot train a usable model with the leaked tokens. MCU-Token can defend against armored adversary who may replay, craft, and offload the requests via MitM or use both hardware (e.g., use identical devices) and software (e.g., machine learning attacks) strategies to mimic the fingerprints. The system evaluation shows that MCU-Token can achieve high accuracy (over 97%) with a low overhead across various IoT devices and application scenarios.
Published: 2024
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2. FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models

Author: Yang, Hongyang, Zhang, Boyu, Wang, Neng, Guo, Cheng, Zhang, Xiaoli, Lin, Likun, Wang, Junlin, Zhou, Tianyu, Guan, Mao, Zhang, Runjia, Wang, Christina Dan, Yang, Hongyang, Zhang, Boyu, Wang, Neng, Guo, Cheng, Zhang, Xiaoli, Lin, Likun, Wang, Junlin, Zhou, Tianyu, Guan, Mao, Zhang, Runjia, and Wang, Christina Dan
Abstract: As financial institutions and professionals increasingly incorporate Large Language Models (LLMs) into their workflows, substantial barriers, including proprietary data and specialized knowledge, persist between the finance sector and the AI community. These challenges impede the AI community's ability to enhance financial tasks effectively. Acknowledging financial analysis's critical role, we aim to devise financial-specialized LLM-based toolchains and democratize access to them through open-source initiatives, promoting wider AI adoption in financial decision-making. In this paper, we introduce FinRobot, a novel open-source AI agent platform supporting multiple financially specialized AI agents, each powered by LLM. Specifically, the platform consists of four major layers: 1) the Financial AI Agents layer that formulates Financial Chain-of-Thought (CoT) by breaking sophisticated financial problems down into logical sequences; 2) the Financial LLM Algorithms layer dynamically configures appropriate model application strategies for specific tasks; 3) the LLMOps and DataOps layer produces accurate models by applying training/fine-tuning techniques and using task-relevant data; 4) the Multi-source LLM Foundation Models layer that integrates various LLMs and enables the above layers to access them directly. Finally, FinRobot provides hands-on for both professional-grade analysts and laypersons to utilize powerful AI techniques for advanced financial analysis. We open-source FinRobot at \url{https://github.com/AI4Finance-Foundation/FinRobot}., Comment: FinRobot Whitepaper V1.0
Published: 2024

3. Systemic Inflammatory Response Syndrome on Admission and Clinical Outcomes After Intracerebral Hemorrhage

Author: Liu,Lijun, Wang,Anxin, Wang,Dandan, Guo,Jiahuan, Zhang,Xiaoli, Zhao,Xingquan, Wang,Wenjuan, Liu,Lijun, Wang,Anxin, Wang,Dandan, Guo,Jiahuan, Zhang,Xiaoli, Zhao,Xingquan, and Wang,Wenjuan
Abstract: Lijun Liu,1,2 Anxin Wang,1,2 Dandan Wang,1,2 Jiahuan Guo,1,2 Xiaoli Zhang,2 Xingquan Zhao,1â 3,&ast; Wenjuan Wang1,2,&ast; 1Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, Peopleâs Republic of China; 2China National Clinical Research Center for Neurological Diseases, Beijing, Peopleâs Republic of China; 3Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, Peopleâs Republic of China&ast;These authors contributed equally to this workCorrespondence: Xingquan Zhao; Wenjuan Wang, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, 119 West Road, South4th Ring, Fengtai District, Beijing, 100070, Peopleâs Republic of China, Tel +86-010-59978330 ; Tel +86-010-59978891, Fax +86-010-67013383, Email zxq@vip.163.com; tong_ttyy@163.comBackground: Since studies on systemic inflammatory response syndrome (SIRS) in patients with acute intracerebral hemorrhage (ICH) are insufficient. This study investigated the associations between SIRS on admission and clinical outcomes after acute ICH.Patients and Methods: The study included 1159 patients with acute spontaneous ICH from January 2014 to September 2016. In accordance with standard criteria, SIRS was defined as two or more of the following: (1) body temperature > 38Â°C or < 36Â°C, (2) respiratory rate > 20 per minute, (3) heart rate > 90 per minute, and (4) white blood cell count > 12,000/Î¼L or < 4000/Î¼L. The clinical outcomes of interest were death and major disability (defined as a modified Rankin Scale of 6 and 3â 5), combined and separate at 1 month, 3 months and 1 year follow-up.Results: SIRS was observed in 13.5% (157/1159) of patients and independently increased the risk of death at 1 month, 3 months, or 1 year: hazard ratio (HR) 2.532 (95% confidence interval [CI] 1.487â 4.311), HR 2.436 (95% CI 1.499â 3.958), HR 2.030 (95% CI 1.343â 3.068), respect
Published: 2023

4. The Concise Guide to PHARMACOLOGY 2023/24: Ion channels

Author: Alexander, Stephen P H, Mathie, Alistair A, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Caceres, Ana I, Catterall, William A, Conner, Alex C, Davies, Paul, De Clerq, Katrien, Delling, Markus, Di Virgilio, Francesco, Falzoni, Simonetta, Fenske, Stefanie, Fortuny-Gomez, Anna, Fountain, Samuel, George, Chandy, Goldstein, Steve A N, Grimm, Christian, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Hu, Meiqin, Ijzerman, Ad P, Jabba, Sairam V, Jarvis, Mike, Jensen, Anders A, Jordt, Sven E, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Liu, Qiang, Lynch, Joseph W, Meades, Jessica, Mehlfeld, Verena, Nicke, Annette, Offermanns, Stefan, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sieghart, Werner, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yang, Fan, Fang, Wei, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen P H, Mathie, Alistair A, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Caceres, Ana I, Catterall, William A, Conner, Alex C, Davies, Paul, De Clerq, Katrien, Delling, Markus, Di Virgilio, Francesco, Falzoni, Simonetta, Fenske, Stefanie, Fortuny-Gomez, Anna, Fountain, Samuel, George, Chandy, Goldstein, Steve A N, Grimm, Christian, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Hu, Meiqin, Ijzerman, Ad P, Jabba, Sairam V, Jarvis, Mike, Jensen, Anders A, Jordt, Sven E, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Liu, Qiang, Lynch, Joseph W, Meades, Jessica, Mehlfeld, Verena, Nicke, Annette, Offermanns, Stefan, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sieghart, Werner, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yang, Fan, Fang, Wei, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and over 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16178. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein‐coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2023

5. The Concise Guide to PHARMACOLOGY 2023/24: Ion channels

Author: Alexander, Stephen P H, Mathie, Alistair A, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Caceres, Ana I, Catterall, William A, Conner, Alex C, Davies, Paul, De Clerq, Katrien, Delling, Markus, Di Virgilio, Francesco, Falzoni, Simonetta, Fenske, Stefanie, Fortuny-Gomez, Anna, Fountain, Samuel, George, Chandy, Goldstein, Steve A N, Grimm, Christian, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Hu, Meiqin, Ijzerman, Ad P, Jabba, Sairam V, Jarvis, Mike, Jensen, Anders A, Jordt, Sven E, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Liu, Qiang, Lynch, Joseph W, Meades, Jessica, Mehlfeld, Verena, Nicke, Annette, Offermanns, Stefan, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sieghart, Werner, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yang, Fan, Fang, Wei, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen P H, Mathie, Alistair A, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Caceres, Ana I, Catterall, William A, Conner, Alex C, Davies, Paul, De Clerq, Katrien, Delling, Markus, Di Virgilio, Francesco, Falzoni, Simonetta, Fenske, Stefanie, Fortuny-Gomez, Anna, Fountain, Samuel, George, Chandy, Goldstein, Steve A N, Grimm, Christian, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Hu, Meiqin, Ijzerman, Ad P, Jabba, Sairam V, Jarvis, Mike, Jensen, Anders A, Jordt, Sven E, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Liu, Qiang, Lynch, Joseph W, Meades, Jessica, Mehlfeld, Verena, Nicke, Annette, Offermanns, Stefan, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sieghart, Werner, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yang, Fan, Fang, Wei, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and over 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16178. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein‐coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2023

6. Ferroptosis as a therapeutic target for inflammation-related intestinal diseases

Author: Zhang, Xiaoli, Ma, Yiming, Lv, Guoqing, Wang, Hongying, Zhang, Xiaoli, Ma, Yiming, Lv, Guoqing, and Wang, Hongying
Abstract: Ferroptosis is an iron-dependent programmed cell death characterized by reactive oxygen species-induced lipid peroxidation and resultant membrane damage. Recent research has elucidated the mechanism of ferroptosis and investigated the relationship between ferroptosis and various diseases, including degenerative diseases, cancer, and inflammation. Ferroptosis is associated with inflammation-related intestinal diseases such as colitis and colitis-associated cancer. New insights into the role of ferroptosis in the pathogenesis of inflammation-related gut diseases have suggested novel therapeutic targets. In this review, we summarize current information on the molecular mechanisms of ferroptosis and describe its emerging role and therapeutic potential in inflammation-related intestinal diseases. Copyright © 2023 Zhang, Ma, Lv and Wang.
Published: 2023

7. Electrochemical Ammonia Synthesis via Nitrogen Reduction Reaction on 1T/2H Mixed-Phase MoSSe Catalyst: Theoretical and Experimental Studies

Author: Sun, Mengjie, Ma, Chaoqun, Ma, Min, Wei, Yanjiao, Dong, Shihua, Zhang, Xiaoli, Tian, Jian, Shao, Minhua, Sun, Mengjie, Ma, Chaoqun, Ma, Min, Wei, Yanjiao, Dong, Shihua, Zhang, Xiaoli, Tian, Jian, and Shao, Minhua
Abstract: Electrocatalytic nitrogen reduction (NRR) is regarded as an energyefficient technology to produce NH3. Nevertheless, achieving high NH3 yield and Faradaic efficiency (FE) under ambient conditions remains a great challenge. Herein, 1T/2H mixedphase MoS0.5Se1.5 (named 1T/2H MoSSe) nanoflower, as an efficient nonnoble metal NRR electrocatalyst, was synthesized by the onestep solvothermal method. 1T/2H MoSSe realizes an excellent NH3 yield of 32.32 mu g h(1) mg(cat.)(1) at0.45 V vs. RHE and an outstanding FE of 12.66% at0.40 V vs. RHE in 0.1 M HCl, which are better than pure MoS2 (NH3 yield: 15.16 mu g h(1) mg(cat.)(1), FE: 0.35%) and MoSe2 (NH3 yield: 26.42 mu g h(1) mg(cat.)(1), FE: 2.75%). Density functional theory (DFT) calculations exhibit that MoSSe catalyst is structurally favorable to the potentialdetermining step (PDS, {*}NHNH2 -> {*}NH2NH2) and thus shows increased NRR activity and selectivity. A promising tactic for the rational design of economical, efficient, and durable NRR electrocatalysts is proposed in this work.
Published: 2023

8. Confidence-aware 3D Gaze Estimation and Evaluation Metric

Author: Zheng, Qiaojie, Zhang, Jiucai, Zhang, Amy, Zhang, Xiaoli, Zheng, Qiaojie, Zhang, Jiucai, Zhang, Amy, and Zhang, Xiaoli
Abstract: Deep learning appearance-based 3D gaze estimation is gaining popularity due to its minimal hardware requirements and being free of constraint. Unreliable and overconfident inferences, however, still limit the adoption of this gaze estimation method. To address the unreliable and overconfident issues, we introduce a confidence-aware model that predicts uncertainties together with gaze angle estimations. We also introduce a novel effectiveness evaluation method based on the causality between eye feature degradation and the rise in inference uncertainty to assess the uncertainty estimation. Our confidence-aware model demonstrates reliable uncertainty estimations while providing angular estimation accuracies on par with the state-of-the-art. Compared with the existing statistical uncertainty-angular-error evaluation metric, the proposed effectiveness evaluation approach can more effectively judge inferred uncertainties' performance at each prediction., Comment: 9 pages 12 figures
Published: 2023

9. Relapse After Drug Withdrawal in Patients with Epilepsy After Two Years of Seizure-Free: A Cohort Study

Author: Zhang,Xiaoli, Zeng,Jiao, Gu,Xin, Zhang,Fan, Han,Yongkai, Zhang,Ping, Wang,Qun, Gu,Renjun, Zhang,Xiaoli, Zeng,Jiao, Gu,Xin, Zhang,Fan, Han,Yongkai, Zhang,Ping, Wang,Qun, and Gu,Renjun
Abstract: Xiaoli Zhang,1,&ast; Jiao Zeng,1,&ast; Xin Gu,1 Fan Zhang,1 Yongkai Han,1 Ping Zhang,1 Qun Wang,2,3 Renjun Gu1 1Department of Neurology, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Peopleâs Republic of China; 2Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, Peopleâs Republic of China; 3China National Clinical Research Center for Neurological Diseases, Beijing, Peopleâs Republic of China&ast;These authors contributed equally to this workCorrespondence: Renjun Gu, Department of Neurology, The Second Affiliated Hospital of Xinxiang Medical University, Qianjin Road, No. 207, Xinxiang, Henan, Peopleâs Republic of China, Tel +86 0373-3373704, Email gurenjun1961@163.com Qun Wang, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Nansihuanxi Road, No. 119, Beijing, Peopleâs Republic of China, Tel +86 010-59975052, Email wangq@ccmu.edu.cnBackground and Study Aims: Antiepileptic drugs are the first choice of treatment for patients with epilepsy. However, the withdrawal of antiepileptic drugs after seizure-free remains a significant focus for the majority of patients with epilepsy and their families. In this study, we evaluated the risk factors associated with relapse after drug withdrawal in patients with seizure free for 2 years. We aimed to guide patients in seizure-free to assess the risk of drug withdrawal.Patients and Methods: Through screening, 452 patients with epilepsy were included in the study.Patients were followed up for at least 2 years or more. Analyzed their clinical data by applying the Ï 2-test, Kaplan-Meier survival analysis and multivariate Cox regression analysis.Results: 423 patients completed follow-up, of which 304 cases recurred (71.9%).Related recurrence factors include age of onset, type of seizure, number of AEDs, seizure-free time before withdrawal, and electroencephalogram (EEG) results before drug withdrawal (P< 0.05). The r
Published: 2023

10. Solar-Synchronous Tides in Mars Thermosphere CO2, Ar, and N2 Densities From MAVEN

Author: National Aeronautics and Space Administration (US), Ministerio de Ciencia e Innovación (España), Forbes, Jeffrey M., Zhang, Xiaoli, Fang, Xiaohua, Benna, Mehdi, González-Galindo, F., Forget, Francois, Millour, Ehouarn, National Aeronautics and Space Administration (US), Ministerio de Ciencia e Innovación (España), Forbes, Jeffrey M., Zhang, Xiaoli, Fang, Xiaohua, Benna, Mehdi, González-Galindo, F., Forget, Francois, and Millour, Ehouarn
Abstract: Measurements of CO2, Ar and N-2 densities from the Neutral Gas and Ion Mass Spectrometer on the Mars Atmosphere and Volatile Evolution Mission (MAVEN) between 150 and 200 km altitude during 2015-2022 are analyzed to reveal diurnal (DW1), semidiurnal (SW2) and terdiurnal (TW3) solar-synchronous tides in Mars thermosphere. Multi-year-mean tidal perturbations on a diurnal- and zonal-mean background, corrected for solar flux variations, are reported as a function of latitude (48 degrees S-48 degrees N), altitude and solar longitude (Ls). The DW1, SW2 and TW3 amplitudes at for example, 180 km altitude are of order 90%-120%, 15%-20%, and less than or similar to 10% for CO2 and Ar, and roughly 2/3 these values for N-2, the latter presumably due to the difference in molecular weight from the other species. Through examination of vertical phase progressions, DW1 is concluded to be mainly excited in situ, but SW2 and TW3 contain significant contributions from tides propagating upward from lower altitudes. By analogy with studies for Earth's thermosphere, the DW1 amplitudes and phases are thought to reflect the combined influences of thermal expansion and vertical winds. Points of agreement and disagreement with DW1, SW2, and TW3 amplitudes and phases derived from the Mars Climate Database are noted and interpreted. © 2023. American Geophysical Union. All Rights Reserved
Published: 2023

11. The Concise Guide to PHARMACOLOGY 2023/24:Ion channels

Author: Alexander, Stephen P H, Mathie, Alistair A, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Caceres, Ana I, Catterall, William A, Conner, Alex C, Davies, Paul, De Clerq, Katrien, Delling, Markus, Di Virgilio, Francesco, Falzoni, Simonetta, Fenske, Stefanie, Fortuny-Gomez, Anna, Fountain, Samuel, George, Chandy, Goldstein, Steve A N, Grimm, Christian, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Hu, Meiqin, Ijzerman, Ad P, Jabba, Sairam V, Jarvis, Mike, Jensen, Anders A, Jordt, Sven E, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Liu, Qiang, Lynch, Joseph W, Meades, Jessica, Mehlfeld, Verena, Nicke, Annette, Offermanns, Stefan, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sieghart, Werner, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yang, Fan, Fang, Wei, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen P H, Mathie, Alistair A, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Caceres, Ana I, Catterall, William A, Conner, Alex C, Davies, Paul, De Clerq, Katrien, Delling, Markus, Di Virgilio, Francesco, Falzoni, Simonetta, Fenske, Stefanie, Fortuny-Gomez, Anna, Fountain, Samuel, George, Chandy, Goldstein, Steve A N, Grimm, Christian, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Hu, Meiqin, Ijzerman, Ad P, Jabba, Sairam V, Jarvis, Mike, Jensen, Anders A, Jordt, Sven E, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Liu, Qiang, Lynch, Joseph W, Meades, Jessica, Mehlfeld, Verena, Nicke, Annette, Offermanns, Stefan, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sieghart, Werner, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yang, Fan, Fang, Wei, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and over 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16178. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2023

12. The Concise Guide to PHARMACOLOGY 2023/24:Ion channels

Author: Alexander, Stephen P H, Mathie, Alistair A, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Caceres, Ana I, Catterall, William A, Conner, Alex C, Davies, Paul, De Clerq, Katrien, Delling, Markus, Di Virgilio, Francesco, Falzoni, Simonetta, Fenske, Stefanie, Fortuny-Gomez, Anna, Fountain, Samuel, George, Chandy, Goldstein, Steve A N, Grimm, Christian, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Hu, Meiqin, Ijzerman, Ad P, Jabba, Sairam V, Jarvis, Mike, Jensen, Anders A, Jordt, Sven E, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Liu, Qiang, Lynch, Joseph W, Meades, Jessica, Mehlfeld, Verena, Nicke, Annette, Offermanns, Stefan, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sieghart, Werner, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yang, Fan, Fang, Wei, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen P H, Mathie, Alistair A, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Caceres, Ana I, Catterall, William A, Conner, Alex C, Davies, Paul, De Clerq, Katrien, Delling, Markus, Di Virgilio, Francesco, Falzoni, Simonetta, Fenske, Stefanie, Fortuny-Gomez, Anna, Fountain, Samuel, George, Chandy, Goldstein, Steve A N, Grimm, Christian, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Hu, Meiqin, Ijzerman, Ad P, Jabba, Sairam V, Jarvis, Mike, Jensen, Anders A, Jordt, Sven E, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Liu, Qiang, Lynch, Joseph W, Meades, Jessica, Mehlfeld, Verena, Nicke, Annette, Offermanns, Stefan, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sieghart, Werner, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yang, Fan, Fang, Wei, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and over 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16178. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2023

13. Stable In-hand Manipulation with Finger Specific Multi-agent Shadow Reward

Author: Tao, Lingfeng, Zhang, Jiucai, Zhang, Xiaoli, Tao, Lingfeng, Zhang, Jiucai, and Zhang, Xiaoli
Abstract: Deep Reinforcement Learning has shown its capability to solve the high degrees of freedom in control and the complex interaction with the object in the multi-finger dexterous in-hand manipulation tasks. Current DRL approaches prefer sparse rewards to dense rewards for the ease of training but lack behavior constraints during the manipulation process, leading to aggressive and unstable policies that are insufficient for safety-critical in-hand manipulation tasks. Dense rewards can regulate the policy to learn stable manipulation behaviors with continuous reward constraints but are hard to empirically define and slow to converge optimally. This work proposes the Finger-specific Multi-agent Shadow Reward (FMSR) method to determine the stable manipulation constraints in the form of dense reward based on the state-action occupancy measure, a general utility of DRL that is approximated during the learning process. Information Sharing (IS) across neighboring agents enables consensus training to accelerate the convergence. The methods are evaluated in two in-hand manipulation tasks on the Shadow Hand. The results show FMSR+IS converges faster in training, achieving a higher task success rate and better manipulation stability than conventional dense reward. The comparison indicates FMSR+IS achieves a comparable success rate even with the behavior constraint but much better manipulation stability than the policy trained with a sparse reward.
Published: 2023

14. Curriculum-based Sensing Reduction in Simulation to Real-World Transfer for In-hand Manipulation

Author: Tao, Lingfeng, Zhang, Jiucai, Zheng, Qiaojie, Zhang, Xiaoli, Tao, Lingfeng, Zhang, Jiucai, Zheng, Qiaojie, and Zhang, Xiaoli
Abstract: Simulation to Real-World Transfer allows affordable and fast training of learning-based robots for manipulation tasks using Deep Reinforcement Learning methods. Currently, Sim2Real uses Asymmetric Actor-Critic approaches to reduce the rich idealized features in simulation to the accessible ones in the real world. However, the feature reduction from the simulation to the real world is conducted through an empirically defined one-step curtail. Small feature reduction does not sufficiently remove the actor's features, which may still cause difficulty setting up the physical system, while large feature reduction may cause difficulty and inefficiency in training. To address this issue, we proposed Curriculum-based Sensing Reduction to enable the actor to start with the same rich feature space as the critic and then get rid of the hard-to-extract features step-by-step for higher training performance and better adaptation for real-world feature space. The reduced features are replaced with random signals from a Deep Random Generator to remove the dependency between the output and the removed features and avoid creating new dependencies. The methods are evaluated on the Allegro robot hand in a real-world in-hand manipulation task. The results show that our methods have faster training and higher task performance than baselines and can solve real-world tasks when selected tactile features are reduced.
Published: 2023

15. One-Dimensional Screw-Like MoS2 with Oxygen Partially Replacing Sulfur as an Electrocatalyst for the N2 Reduction Reaction

Author: Chen, Xiaoyue, Ma, Chaoqun, Tan, Zixuan, Wang, Xu, Qian, Xiu, Zhang, Xiaoli, Tian, Jian, Yan, Shihai, Shao, Minhua, Chen, Xiaoyue, Ma, Chaoqun, Tan, Zixuan, Wang, Xu, Qian, Xiu, Zhang, Xiaoli, Tian, Jian, Yan, Shihai, and Shao, Minhua
Abstract: Electrocatalytic nitrogen reduction reaction (NRR) is considered to be an energy-saving method for the production of NH3. However, it is still very challenging to achieve a high NH3 yield and efficiency under ambient conditions. Herein, we for the first time synthesize one-dimensional screw-like MoS2 with oxygen partially replacing sulfur (1D-MoS2-xOy) nanosheets by a one-step solvothermal method as an efficient non-noble metal electrocatalyst for NRR. In a 0.1 M HCl solution, 1D-MoS2-xOy exhibits excellent NRR performance, with a remarkable average ammonia yield rate of 5.56 × 10-8 mol s−1 cm−2 at −0.35 V, and a high Faradaic efficiency of 9.86% at −0.3 V. The isotope labeling experiment proves that the generation of NH3 is completely derived from the feed-in N2. Density functional theory calculations show that MoS2 with oxygen partially replacing sulfur can reduce the Gibbs free energy of the potential determination step (PDS). Besides, the unique screw-like structure can provide more N2 adsorption sites for NRR. This work proposes a promising strategy for the reasonable design of non-precious metal-based NRR electrocatalysts. © 2022 Elsevier B.V.
Published: 2022

16. Enabling Efficient Electrocatalytic Conversion of N2 to NH3 by Ti3C2 MXene Loaded with Semi-Metallic 1T′-MoS2 Nanosheets

Author: Chen, Xiaoyue, Zhang, Songge, Qian, Xiu, Liang, Zhangqian, Xue, Yanjun, Zhang, Xiaoli, Tian, Jian, Han, Ye, Shao, Minhua, Chen, Xiaoyue, Zhang, Songge, Qian, Xiu, Liang, Zhangqian, Xue, Yanjun, Zhang, Xiaoli, Tian, Jian, Han, Ye, and Shao, Minhua
Abstract: Herein, we assemble semi-metallic 1T′ phase MoS2 on the surface Ti3C2 MXene (1T′-MoS2/Ti3C2 composite) by one-step hydrothermal method for nitrogen fixation. 1T′-MoS2/Ti3C2 composites present a high ammonia yield rate of 31.96 µg h−1 mg−1cat. at − 0.95 V vs. RHE and a Faradaic efficiency (FE) of 30.75% at − 0.7 V, which is much better than pure 1T′-MoS2 and pure Ti3C2 MXenes alone. Furthermore, the 1T′-MoS2/Ti3C2 composites exhibit good selectivity and stability with no significant decrease in ammonia yield rate and FE. Density functional theory (DFT) calculations reveal that 1T′-MoS2/Ti3C2 composite makes the activation and further reduction of *N2 more thermodynamically favorable than pure 1T′-MoS2. 15N isotopic labeling experiment confirms that nitrogen in produced ammonia originates from N2 in the electrolyte. © 2022 Elsevier B.V.
Published: 2022

17. Slightly Elevated Lymphocyte to Monocyte Ratio Predicting Favorable Outcomes in Patients with Spontaneous Intracerebral Hemorrhage

Author: Wang,Jinjin, Wang,Wenjuan, Wang,Anxin, Zhang,Xiaoli, Bian,Liheng, Du,Yang, Lu,Jingjing, Zhao,Xingquan, Wang,Jinjin, Wang,Wenjuan, Wang,Anxin, Zhang,Xiaoli, Bian,Liheng, Du,Yang, Lu,Jingjing, and Zhao,Xingquan
Abstract: Jinjin Wang,1,2,&ast; Wenjuan Wang,1,2,&ast; Anxin Wang,1,2 Xiaoli Zhang,1,2 Liheng Bian,1,2 Yang Du,1,2 Jingjing Lu,1,2 Xingquan Zhao1â 4 1Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, Peopleâs Republic of China; 2China National Clinical Research Center for Neurological Diseases, Beijing, Peopleâs Republic of China; 3Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, Peopleâs Republic of China; 4Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, Peopleâs Republic of China&ast;These authors contributed equally to this workCorrespondence: Xingquan Zhao; Jingjing Lu, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, Peopleâs Republic of China, Tel +86-10-59978555, Fax +86-10-83191171, Email zxq@vip.163.com; lujingjing666@gmail.comObjective: This study was designed to determine the association between admission lymphocyte to monocyte ratio (LMR) values and clinical outcomes in patients with spontaneous intracerebral hemorrhage (ICH).Methods: We used a prospective and registry-based database, and ICH patients were consecutively recruited in Beijing Tiantan Hospital between January 2014 and September 2016. All participants were stratified by quartiles of the LMR. Univariable and multivariable logistic regression analyses were plotted to evaluate the association between LMR levels and functional outcomes. KaplanâMeier survival curves and Cox regression analysis were also performed to examine the relevance between different LMR quartiles and case fatality at follow-up.Results: Six hundred and forty patients with spontaneous ICH were finally included in this study. Compared with the patients with LMR values in quartile 1 (Q1), slightly elevated LMR values showed a negative
Published: 2022

18. PCDH19-related epilepsy in mosaic males: The phenotypic implication of genotype and variant allele frequency.

Author: Chen, Yi, Chen, Yi, Yang, Xiaoxu, Chen, Jiaoyang, Yang, Xiaoling, Yang, Ying, Liu, Aijie, Zhang, Xiaoli, Wu, Wenjuan, Sun, Dan, Yang, Zhixian, Jiang, Yuwu, Zhang, Yuehua, Chen, Yi, Chen, Yi, Yang, Xiaoxu, Chen, Jiaoyang, Yang, Xiaoling, Yang, Ying, Liu, Aijie, Zhang, Xiaoli, Wu, Wenjuan, Sun, Dan, Yang, Zhixian, Jiang, Yuwu, and Zhang, Yuehua
Abstract: ObjectiveTo analyze the genotypes and phenotypes of mosaic male patients with PCDH19-related epilepsy (PCDH19-RE) and explore the correlation between genotype, variant allele frequency (VAF), and phenotypic severity.MethodsClinical data and peripheral blood samples of 11 male mosaic patients were collected and analyzed in our study. The VAF of the PCDH19 gene from peripheral blood was quantified using amplicon-based deep sequencing. Additional 20 mosaic male patients with PCDH19-RE were collected from the published literature, with 10 patients whose VAFs of the PCDH19 gene were available for analytic purposes.ResultsIn our cohort of 11 patients, 10 variants were identified, and four were novel. The VAF of the PCDH19 gene from peripheral blood ranged from 27 to 90%. The median seizure onset age was 6 months (range: 4-9 months). Clinical manifestations included cluster seizures (100%), fever sensitivity (73%), focal seizures (91%), developmental delay/intellectual disability (DD/ID, 82%), and autistic features (45%). Thirty-one mosaic male patients collected from our cohort and the literature developed seizures mostly (87%) within one year of age. Variant types included missense variants (42%), truncating variants (52%), splice variants (3%), and whole PCDH19 deletion (3%). Among 21 patients with a definite VAF from our cohort and the literature, nine had a low VAF ( ≤ 50%) and 12 had a high VAF (> 50%). Seventy-five percent of variants from the high VAF group were missense, whereas 89% of those from the low VAF group were truncations. The median seizure onset age was 6 months in the low VAF group and 9 months in the high VAF group (p = 0.018). Forty-four percent (4/9) of patients from the low VAF group achieved seizure-free for ≥1 year, whereas none of the 12 patients from the high VAF group did (p = 0.021). DD/ID was present in 83% (10/12) of the high VAF group and 56% (5/9) of the low VAF group (p = 0.331).ConclusionThe predominant variant types were truncating
Published: 2022

19. Transferability-based Chain Motion Mapping from Humans to Humanoids for Teleoperation

Author: Stanley, Matthew, Jung, Yunsik, Bowman, Michael, Tao, Lingfeng, Zhang, Xiaoli, Stanley, Matthew, Jung, Yunsik, Bowman, Michael, Tao, Lingfeng, and Zhang, Xiaoli
Abstract: Although data-driven motion mapping methods are promising to allow intuitive robot control and teleoperation that generate human-like robot movement, they normally require tedious pair-wise training for each specific human and robot pair. This paper proposes a transferability-based mapping scheme to allow new robot and human input systems to leverage the mapping of existing trained pairs to form a mapping transfer chain, which will reduce the number of new pair-specific mappings that need to be generated. The first part of the mapping schematic is the development of a Synergy Mapping via Dual-Autoencoder (SyDa) method. This method uses the latent features from two autoencoders to extract the common synergy of the two agents. Secondly, a transferability metric is created that approximates how well the mapping between a pair of agents will perform compared to another pair before creating the motion mapping models. Thus, it can guide the formation of an optimal mapping chain for the new human-robot pair. Experiments with human subjects and a Pepper robot demonstrated 1) The SyDa method improves the accuracy and generalizability of the pair mappings, 2) the SyDa method allows for bidirectional mapping that does not prioritize the direction of mapping motion, and 3) the transferability metric measures how compatible two agents are for accurate teleoperation. The combination of the SyDa method and transferability metric creates generalizable and accurate mapping need to create the transfer mapping chain.
Published: 2022

20. A Multi-Agent Approach for Adaptive Finger Cooperation in Learning-based In-Hand Manipulation

Author: Tao, Lingfeng, Zhang, Jiucai, Bowman, Michael, Zhang, Xiaoli, Tao, Lingfeng, Zhang, Jiucai, Bowman, Michael, and Zhang, Xiaoli
Abstract: In-hand manipulation is challenging for a multi-finger robotic hand due to its high degrees of freedom and the complex interaction with the object. To enable in-hand manipulation, existing deep reinforcement learning based approaches mainly focus on training a single robot-structure-specific policy through the centralized learning mechanism, lacking adaptability to changes like robot malfunction. To solve this limitation, this work treats each finger as an individual agent and trains multiple agents to control their assigned fingers to complete the in-hand manipulation task cooperatively. We propose the Multi-Agent Global-Observation Critic and Local-Observation Actor (MAGCLA) method, where the critic can observe all agents' actions globally, and the actor only locally observes its neighbors' actions. Besides, conventional individual experience replay may cause unstable cooperation due to the asynchronous performance increment of each agent, which is critical for in-hand manipulation tasks. To solve this issue, we propose the Synchronized Hindsight Experience Replay (SHER) method to synchronize and efficiently reuse the replayed experience across all agents. The methods are evaluated in two in-hand manipulation tasks on the Shadow dexterous hand. The results show that SHER helps MAGCLA achieve comparable learning efficiency to a single policy, and the MAGCLA approach is more generalizable in different tasks. The trained policies have higher adaptability in the robot malfunction test compared to the baseline multi-agent and single-agent approaches., Comment: Submitted to ICRA 2023
Published: 2022
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21. Effects of Salidroside Combined with Paclitaxel on Proliferation, Migration, and Epithelial Mesenchyme of Colorectal Cancer Cells

Author: Hao,Yanjiao, Li,Zhiyu, Chang,Mingzhi, Zhang,Xiaoli, Hao,Yanjiao, Li,Zhiyu, Chang,Mingzhi, and Zhang,Xiaoli
Abstract: Yanjiao Hao, Zhiyu Li, Mingzhi Chang, Xiaoli Zhang Department of Life Science Research Center, College of Basic Medicine, Hebei North University, Zhangjiakou, Hebei, 075000, Peopleâs Republic of ChinaCorrespondence: Xiaoli Zhang, Department of Life Science Research Center, College of Basic Medicine, Hebei North University, Zhangjiakou, Hebei, 075000, Peopleâs Republic of China, Tel +8618931316301, Email 894915208@qq.comBackground: Colorectal cancer (CRC) is a multifactorial disease and one of the most common malignancies worldwide. Salidroside (Sal) is a plant with a wide range of pharmacological effects and plays an important role in the treatment of many diseases, and is considered a new hope for the treatment of tumors. The purpose of this study was to investigate the effect of the combination of Sal and paclitaxel (Pac) on colorectal cancer cells and its mechanism of action.Methods: The effects of different mass concentrations of Sal, Pac, and the combination intervened in the cells for 48 h were examined using the CCK8 method. The inhibition rate was obtained, and the optimal concentration of the respective drug group was screened. The proliferative capacity of the respective group was obtained. Subsequently, the results of apoptosis, cloning, migration, invasion, and angiogenesis were observed through cell morphological analysis (shape observation and Hoechst staining), colony formation assay, cell scratching assay, Transwell, angiogenesis assay, and protein immunoblotting (Western blotting) to detect the expression of epithelial-mesenchymal transition (EMT)-associated proteins and PI3K pathway-associated proteins.Results: Different concentrations of Sal, Pac, and the combined application had significant effects in inhibiting cells in a concentration-dependent manner. Compared with the control group, the Sal group, the Pac group, and the combination group significantly inhibited the clonal number, migration, invasion, and tube-forming ability of colorectal
Published: 2022

22. The enhanced X-ray Timing and Polarimetry mission – eXTP:an update on its scientific cases, mission profile and development status

Author: den Herder, Jan-Willem A., Nikzad, Shouleh, Nakazawa, Kazuhiro, Zhang, Shuang Nan, Santangelo, Andrea, Xu, Yupeng, Feroci, Marco, Hernanz, Margarita, Lu, Fangjun, Chen, Yong, Feng, Hua, Nandra, Kirpal, Jiang, Weichun, Svoboda, Jiri, Brandt, Søren, Schanne, Stéphane, Zand, Jean, Michalska, Malgorzata, Bozzo, Enrico, Kalemci, Emrah, Agudo, Ivan, Ahangarianabhari, Mahdi, Aitink-Kroes, Gabby, Ambrosi, Giovanni, Ambrosino, Filippo, An, Zhenghua, Perez Torres, Miguel Angel, Antonelli, Matias, Argan, Andrea, Babinec, Viktor, Baldini, Luca, Barbera, Marco, van Baren, Coen, Baudin, David, Bayer, Jörg, Bellazzini, Ronaldo, Bellutti, Pierluigi, Bertucci, Bruna, Bertuccio, Giuseppe, Bi, Xingzi, Boezio, Mirko, Bonvicini, Valter, Bonvicini, Walter, Bordas, Pol, Borghese, Alice, Borghi, Giacomo, Bouyjou, Florent, Bozkurt, Ayhan, Brez, Alessandro, Brienza, Daniele, Cadoux, Franck, Campana, Riccardo, Cao, Jiewei, Cao, Xuelei, Casares, Jorge, Cavazzuti, Elisabetta, Ceraudo, Francesco, Chen, Tianxiang, Chen, Wen, Chen, Can, Chen, Yupeng, Chen, Xin, Chen, Yehai, Chenevez, Jerome, Cheng, Yaodong, Cirrincione, Daniela, Civitani, Marta, Cong, Min, Zelati, Francesco Coti, Cui, Weiwei, Cui, Tao, Cui, Wei, Dai, Boyu, Dauser, Thomas, De Angelis, Nicolas, De Marco, Barbara, De Rosa, Alessandra, Monte, Ettore Del, Cosimo, Sergio Di, Diebold, Sebastian, Dilillo, Giuseppe, Ding, Fei, Dohnal, Roman, Dong, Zefang, Donnarumma, Immacolata, Dovciak, Michal, Du, Yuanyuan, Ducci, Lorenzo, Evangelista, Yuri, Fan, Qingmei, Favre, Yannick, Ferrés, Patrícia, Fiandrini, Emanuele, Ficorella, Francesco, Fuschino, Fabio, Gálvez, José Luis, Gao, Na, Gao, Min, Ge, Yuqiang, Ge, Mingyu, Gevin, Olivier, Grassi, Marco, Gu, Yudong, Gu, Quanying, Guan, Ju, Guedel, Manuel, Han, Xingbo, Han, Dawei, He, Huilin, He, Junwang, Hedderman, Paul, den Herder, Jan Willem, Hong, Bin, Hormaetxe, Ander, Hou, Dongjie, Hu, Zexun, Hu, Hao, Hu, Qingbao, Hu, Yu, Huang, Yue, Huang, Jiangjiang, Huang, Qiushi, Huo, Jia, Hynek, Richard, Iwasawa, Kazumi, Izzo, Lucca, Ji, Long, Jia, Shumei, Jiang, Bowen, Jiang, Wei, Jiang, Jiechen, Jiang, Xiaowei, Jiao, Yang, Jin, Ge, Jin, Fan, Jose, Jordi, Karas, Vladimir, Kennedy, Thomas, Kirsch, Christian, Kole, Merlin, Komarek, Martin, Kreykenbohm, Ingo, Kuiper, Lucien, Kuvvetli, Irfan, Labanti, Claudio, Latronico, Luca, Laubert, Phillip, Li, Tao, Li, Longhui, Li, Hong, Li, Duo, Li, Wei, Li, Maoshun, Li, Gang, Li, Xiaobo, Li, Chengkui, Li, Bing, Li, Haibo, Liang, Hong, Liao, Qiuyan, Liao, Jinyuan, Limousin, Olivier, Lin, Yanjian, Linares, Manuel, Liu, Rui, Liu, Yichen, Liu, Zhihao, Liu, Hongwei, Liu, Xiaojing, Liu, Xiaohua, Cicero, Ugo Lo, Loehring, Jens, Lombardi, Giovanni, Lorenz, Maximilian, Lu, Bing, Lucchesi, Leonardo, Luo, Tao, Luo, Laidan, Ma, Jia, Ma, Xiang, Macera, Daniele, Malcovati, Piero, Manfreda, Alberto, Paredes, Josep Maria, Marinucci, Andrea, Martindale, Adrian, Meidinger, Norbert, Mele, Filippo, Mendes, Vasco, Meng, Bin, Merkl, Martin, Meuris, Aline, Miniutti, Giovanni, Minuti, Massimo, Morbidini, Alfredo, Morgante, Gianluca, Muleri, Fabio, Munini, Riccardo, Mussolin, Lorenzo, Negri, Barbara, Nie, Jianyin, Novák, Petr, Nowosielski, Witold, Nuti, Alessio, Onat, Ahmet, Orleanski, Piotr, Orsini, Leonardo, Ottensamer, Roland, Ou, Ge, Pacciani, Luigi, Paltani, Stephane, Pan, Teng, Pan, Kai, Pareschi, Giovanni, Patruno, Alessandro, Pepponi, Giancarlo, Perinati, Emanuele, Piazzolla, Raffaele, Picciotto, Antonino, Piemonte, Claudio, Pinchera, Michele, Pliego, Samuel, Poutanen, Juri, Qi, Liqiang, Qi, Fazhi, Qiang, Pengfei, Qiao, Fangjian, Qiao, Zheng, Qiu, Xiangbiao, Qiu, Chengbo, Qu, Jinlu, Rachevski, Alexandre, Rashevskaia, Irina, Rea, Nanda, Ribo, Marc, de la Rie, Rob, Rodriguez, Jerome, Gil, Pablo Rodríguez, Sala, Gloria, Schanz, Thomas, Serafinelli, Roberto, Sgro, Carmelo, Shen, Zhengxiang, Sheng, Lizhi, Shi, Jingyan, Sironi, Giorgia, Skup, Konrad, Song, Liming, Song, Zeyu, Song, Jiangbo, Spandre, Gloria, Spiga, Daniele, Su, Yongquan, Sun, Liang, Sungur, Müberra, Svéda, Libor, Tagliaferri, Gianpiero, Tan, Ying, Tao, Lian, Tcherniak, Denis, Tenzer, Chris, Todaro, Michela, Tolos, Laura, Torok, Gabriel, Torres, Diego F., Trois, Alessio, Turhan, Onur, Uttley, Phil, Vacchi, Andrea, Virgilli, Enrico, Vogel, Channah, Walton, Dave, Wang, Jian, Wang, Xianqi, Wang, Bo, Wang, Langping, Wang, Xiaofeng, Wang, Dianlong, Wang, Yusa, Wang, Juan, Wang, Hao, Wang, Ruijie, Wang, Ping, Wang, Lingjun, Wang, Wenshuai, Wang, Tian, Wang, Haoyu, Wang, Zhanshan, Watts, Anna L., Wen, Xiangyang, Wilms, Jörn, Winter, Berend, Wu, Xin, Wu, Chao, Wu, Zhenyu, Wu, Qiong, Wu, Kaiji, Xiong, Hao, Xiong, Shaolin, Xu, Wei, Xu, Zhao, Xu, Jingjing, Xu, Xiongwei, Xue, Jiadai, Yan, Yongqing, Yan, Xingtao, Yang, Xianghui, Yang, Yanji, Yang, Xiongtao, Yang, Sheng, Yang, Jiawei, Yang, Yingquan, Yi, Shuxu, Yu, Yonggao, Yu, Ke, Zampa, Ganluigi, Zampa, Nicola, Zane, Silvia, Zdziarski, Andrzej A., Zhang, Long, Zhang, Shu, Zhang, Wenda, Zhang, Xiaoli, Zhang, Zhen, Zhang, Jiawei, Zhang, Fan, Zhang, Ziliang, Zhang, Dali, Zhang, Honglin, Zhang, Aimei, Zhang, Tong, Zhang, Hongmei, Zhang, Juan, Zhang, Liang, Zhang, Yueting, Zhao, Li, Zhao, Baosheng, Zhao, Zijian, Zhao, Xiaofan, Zhao, Haisheng, Zhao, Xiaoyun, Zheng, Shijie, Zhou, Yupeng, Zhou, Xiaohong, Zhu, Jiahuan, Zhu, Yuxuan, Zhu, Cheng, Zhu, Zhencai, Zorzi, Nicola, Zwart, Frans, den Herder, Jan-Willem A., Nikzad, Shouleh, Nakazawa, Kazuhiro, Zhang, Shuang Nan, Santangelo, Andrea, Xu, Yupeng, Feroci, Marco, Hernanz, Margarita, Lu, Fangjun, Chen, Yong, Feng, Hua, Nandra, Kirpal, Jiang, Weichun, Svoboda, Jiri, Brandt, Søren, Schanne, Stéphane, Zand, Jean, Michalska, Malgorzata, Bozzo, Enrico, Kalemci, Emrah, Agudo, Ivan, Ahangarianabhari, Mahdi, Aitink-Kroes, Gabby, Ambrosi, Giovanni, Ambrosino, Filippo, An, Zhenghua, Perez Torres, Miguel Angel, Antonelli, Matias, Argan, Andrea, Babinec, Viktor, Baldini, Luca, Barbera, Marco, van Baren, Coen, Baudin, David, Bayer, Jörg, Bellazzini, Ronaldo, Bellutti, Pierluigi, Bertucci, Bruna, Bertuccio, Giuseppe, Bi, Xingzi, Boezio, Mirko, Bonvicini, Valter, Bonvicini, Walter, Bordas, Pol, Borghese, Alice, Borghi, Giacomo, Bouyjou, Florent, Bozkurt, Ayhan, Brez, Alessandro, Brienza, Daniele, Cadoux, Franck, Campana, Riccardo, Cao, Jiewei, Cao, Xuelei, Casares, Jorge, Cavazzuti, Elisabetta, Ceraudo, Francesco, Chen, Tianxiang, Chen, Wen, Chen, Can, Chen, Yupeng, Chen, Xin, Chen, Yehai, Chenevez, Jerome, Cheng, Yaodong, Cirrincione, Daniela, Civitani, Marta, Cong, Min, Zelati, Francesco Coti, Cui, Weiwei, Cui, Tao, Cui, Wei, Dai, Boyu, Dauser, Thomas, De Angelis, Nicolas, De Marco, Barbara, De Rosa, Alessandra, Monte, Ettore Del, Cosimo, Sergio Di, Diebold, Sebastian, Dilillo, Giuseppe, Ding, Fei, Dohnal, Roman, Dong, Zefang, Donnarumma, Immacolata, Dovciak, Michal, Du, Yuanyuan, Ducci, Lorenzo, Evangelista, Yuri, Fan, Qingmei, Favre, Yannick, Ferrés, Patrícia, Fiandrini, Emanuele, Ficorella, Francesco, Fuschino, Fabio, Gálvez, José Luis, Gao, Na, Gao, Min, Ge, Yuqiang, Ge, Mingyu, Gevin, Olivier, Grassi, Marco, Gu, Yudong, Gu, Quanying, Guan, Ju, Guedel, Manuel, Han, Xingbo, Han, Dawei, He, Huilin, He, Junwang, Hedderman, Paul, den Herder, Jan Willem, Hong, Bin, Hormaetxe, Ander, Hou, Dongjie, Hu, Zexun, Hu, Hao, Hu, Qingbao, Hu, Yu, Huang, Yue, Huang, Jiangjiang, Huang, Qiushi, Huo, Jia, Hynek, Richard, Iwasawa, Kazumi, Izzo, Lucca, Ji, Long, Jia, Shumei, Jiang, Bowen, Jiang, Wei, Jiang, Jiechen, Jiang, Xiaowei, Jiao, Yang, Jin, Ge, Jin, Fan, Jose, Jordi, Karas, Vladimir, Kennedy, Thomas, Kirsch, Christian, Kole, Merlin, Komarek, Martin, Kreykenbohm, Ingo, Kuiper, Lucien, Kuvvetli, Irfan, Labanti, Claudio, Latronico, Luca, Laubert, Phillip, Li, Tao, Li, Longhui, Li, Hong, Li, Duo, Li, Wei, Li, Maoshun, Li, Gang, Li, Xiaobo, Li, Chengkui, Li, Bing, Li, Haibo, Liang, Hong, Liao, Qiuyan, Liao, Jinyuan, Limousin, Olivier, Lin, Yanjian, Linares, Manuel, Liu, Rui, Liu, Yichen, Liu, Zhihao, Liu, Hongwei, Liu, Xiaojing, Liu, Xiaohua, Cicero, Ugo Lo, Loehring, Jens, Lombardi, Giovanni, Lorenz, Maximilian, Lu, Bing, Lucchesi, Leonardo, Luo, Tao, Luo, Laidan, Ma, Jia, Ma, Xiang, Macera, Daniele, Malcovati, Piero, Manfreda, Alberto, Paredes, Josep Maria, Marinucci, Andrea, Martindale, Adrian, Meidinger, Norbert, Mele, Filippo, Mendes, Vasco, Meng, Bin, Merkl, Martin, Meuris, Aline, Miniutti, Giovanni, Minuti, Massimo, Morbidini, Alfredo, Morgante, Gianluca, Muleri, Fabio, Munini, Riccardo, Mussolin, Lorenzo, Negri, Barbara, Nie, Jianyin, Novák, Petr, Nowosielski, Witold, Nuti, Alessio, Onat, Ahmet, Orleanski, Piotr, Orsini, Leonardo, Ottensamer, Roland, Ou, Ge, Pacciani, Luigi, Paltani, Stephane, Pan, Teng, Pan, Kai, Pareschi, Giovanni, Patruno, Alessandro, Pepponi, Giancarlo, Perinati, Emanuele, Piazzolla, Raffaele, Picciotto, Antonino, Piemonte, Claudio, Pinchera, Michele, Pliego, Samuel, Poutanen, Juri, Qi, Liqiang, Qi, Fazhi, Qiang, Pengfei, Qiao, Fangjian, Qiao, Zheng, Qiu, Xiangbiao, Qiu, Chengbo, Qu, Jinlu, Rachevski, Alexandre, Rashevskaia, Irina, Rea, Nanda, Ribo, Marc, de la Rie, Rob, Rodriguez, Jerome, Gil, Pablo Rodríguez, Sala, Gloria, Schanz, Thomas, Serafinelli, Roberto, Sgro, Carmelo, Shen, Zhengxiang, Sheng, Lizhi, Shi, Jingyan, Sironi, Giorgia, Skup, Konrad, Song, Liming, Song, Zeyu, Song, Jiangbo, Spandre, Gloria, Spiga, Daniele, Su, Yongquan, Sun, Liang, Sungur, Müberra, Svéda, Libor, Tagliaferri, Gianpiero, Tan, Ying, Tao, Lian, Tcherniak, Denis, Tenzer, Chris, Todaro, Michela, Tolos, Laura, Torok, Gabriel, Torres, Diego F., Trois, Alessio, Turhan, Onur, Uttley, Phil, Vacchi, Andrea, Virgilli, Enrico, Vogel, Channah, Walton, Dave, Wang, Jian, Wang, Xianqi, Wang, Bo, Wang, Langping, Wang, Xiaofeng, Wang, Dianlong, Wang, Yusa, Wang, Juan, Wang, Hao, Wang, Ruijie, Wang, Ping, Wang, Lingjun, Wang, Wenshuai, Wang, Tian, Wang, Haoyu, Wang, Zhanshan, Watts, Anna L., Wen, Xiangyang, Wilms, Jörn, Winter, Berend, Wu, Xin, Wu, Chao, Wu, Zhenyu, Wu, Qiong, Wu, Kaiji, Xiong, Hao, Xiong, Shaolin, Xu, Wei, Xu, Zhao, Xu, Jingjing, Xu, Xiongwei, Xue, Jiadai, Yan, Yongqing, Yan, Xingtao, Yang, Xianghui, Yang, Yanji, Yang, Xiongtao, Yang, Sheng, Yang, Jiawei, Yang, Yingquan, Yi, Shuxu, Yu, Yonggao, Yu, Ke, Zampa, Ganluigi, Zampa, Nicola, Zane, Silvia, Zdziarski, Andrzej A., Zhang, Long, Zhang, Shu, Zhang, Wenda, Zhang, Xiaoli, Zhang, Zhen, Zhang, Jiawei, Zhang, Fan, Zhang, Ziliang, Zhang, Dali, Zhang, Honglin, Zhang, Aimei, Zhang, Tong, Zhang, Hongmei, Zhang, Juan, Zhang, Liang, Zhang, Yueting, Zhao, Li, Zhao, Baosheng, Zhao, Zijian, Zhao, Xiaofan, Zhao, Haisheng, Zhao, Xiaoyun, Zheng, Shijie, Zhou, Yupeng, Zhou, Xiaohong, Zhu, Jiahuan, Zhu, Yuxuan, Zhu, Cheng, Zhu, Zhencai, Zorzi, Nicola, and Zwart, Frans
Abstract: The enhanced X-ray Timing and Polarimetry mission (eXTP) is a flagship observatory for X-ray timing, spectroscopy and polarimetry developed by an International Consortium. Thanks to its very large collecting area, good spectral resolution and unprecedented polarimetry capabilities, eXTP will explore the properties of matter and the propagation of light in the most extreme conditions found in the Universe. eXTP will, in addition, be a powerful X-ray observatory. The mission will continuously monitor the X-ray sky, and will enable multiwavelength and multi-messenger studies. The mission is currently in phase B, which will be completed in the middle of 2022.
Published: 2022

23. Physics-Guided Hierarchical Reward Mechanism for Learning-Based Robotic Grasping

Author: Jung, Yunsik, Tao, Lingfeng, Bowman, Michael, Zhang, Jiucai, Zhang, Xiaoli, Jung, Yunsik, Tao, Lingfeng, Bowman, Michael, Zhang, Jiucai, and Zhang, Xiaoli
Abstract: Learning-based grasping can afford real-time grasp motion planning of multi-fingered robotics hands thanks to its high computational efficiency. However, learning-based methods are required to explore large search spaces during the learning process. The search space causes low learning efficiency, which has been the main barrier to its practical adoption. In addition, the trained policy lacks a generalizable outcome unless objects are identical to the trained objects. In this work, we develop a novel Physics-Guided Deep Reinforcement Learning with a Hierarchical Reward Mechanism to improve learning efficiency and generalizability for learning-based autonomous grasping. Unlike conventional observation-based grasp learning, physics-informed metrics are utilized to convey correlations between features associated with hand structures and objects to improve learning efficiency and outcomes. Further, the hierarchical reward mechanism enables the robot to learn prioritized components of the grasping tasks. Our method is validated in robotic grasping tasks with a 3-finger MICO robot arm. The results show that our method outperformed the standard Deep Reinforcement Learning methods in various robotic grasping tasks.
Published: 2022

24. Multi-Phase Multi-Objective Dexterous Manipulation with Adaptive Hierarchical Curriculum

Author: Tao, Lingfeng, Zhang, Jiucai, Zhang, Xiaoli, Tao, Lingfeng, Zhang, Jiucai, and Zhang, Xiaoli
Abstract: Dexterous manipulation tasks usually have multiple objectives, and the priorities of these objectives may vary at different phases of a manipulation task. Varying priority makes a robot hardly or even failed to learn an optimal policy with a deep reinforcement learning (DRL) method. To solve this problem, we develop a novel Adaptive Hierarchical Reward Mechanism (AHRM) to guide the DRL agent to learn manipulation tasks with multiple prioritized objectives. The AHRM can determine the objective priorities during the learning process and update the reward hierarchy to adapt to the changing objective priorities at different phases. The proposed method is validated in a multi-objective manipulation task with a JACO robot arm in which the robot needs to manipulate a target with obstacles surrounded. The simulation and physical experiment results show that the proposed method improved robot learning in task performance and learning efficiency., Comment: Accepted by the Journal of Intelligent & Robotic Systems
Published: 2022
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25. High-fat diet alleviates colitis by inhibiting ferroptosis via solute carrier family seven member 11

Author: Zhang, Xiaoli, Ma, Yiming, Ji, Jiafu, Zhao, Xinhua, Yuan, Junhu, Wang, Hongying, Lv, Guoqing, Zhang, Xiaoli, Ma, Yiming, Ji, Jiafu, Zhao, Xinhua, Yuan, Junhu, Wang, Hongying, and Lv, Guoqing
Abstract: A high-fat diet (HFD) is reported to exacerbate ulcerative colitis by inducing obesity, which conceals the effect of the diet itself. Ferroptosis, a type of regulated cell death induced by lipid hydroperoxides, has recently been reported in colitis. Here, we aimed to determine whether HFD affects ferroptosis and colitis progression in an obesity-independent manner. We subjected male C57BL/6J mice to either an HFD (60% fat diet) or isocaloric control diet (10% fat diet) for 4 weeks, followed by inducing colitis with 2.5% dextran sulfate sodium (DSS). Compared with the isocaloric control diet, non-obesogenic HFD reduced DSS-induced colonic mucosal injury, as shown by disease activity index, colon thickness, inflammatory infiltrations, and mucosal damage index; however, there were no differences in body weight, Lee's index, and omental fat weight between the two groups. HFD mice exhibited decreased lipid peroxidation and ferroptosis markers expression in colon tissues. Furthermore, a lipid mixture protected gut organoids and normal colonic epithelial cells from RSL3-induced ferroptosis. Mechanistically, the lipid mixture prevented glutathione deficiency by upregulating the cysteine transporter, solute carrier family seven member 11. Collectively, these findings suggest that an HFD ameliorates DSS-induced colitis through ferroptosis repression in an obesity-independent manner and provide new evidence to evaluate the effects of an HFD on colitis. © 2022 Elsevier Inc.
Published: 2022

26. One-dimensional screw-like MoS2 with oxygen partially replacing sulfur as an electrocatalyst for the N2 reduction reaction

Author: Chen, Xiaoyue, Ma, Chaoqun, Tan, Zixuan, Wang, Xu, Qian, Xiu, Zhang, Xiaoli, Tian, Jian, Yan, Shihai, Shao, Minhua, Chen, Xiaoyue, Ma, Chaoqun, Tan, Zixuan, Wang, Xu, Qian, Xiu, Zhang, Xiaoli, Tian, Jian, Yan, Shihai, and Shao, Minhua
Abstract: Electrocatalytic nitrogen reduction reaction (NRR) is considered to be an energy-saving method for the production of NH3. However, it is still very challenging to achieve a high NH3 yield and efficiency under ambient conditions. Herein, we for the first time synthesize one-dimensional screw-like MoS2 with oxygen partially replacing sulfur (1D-MoS2-xOy) nanosheets by a one-step solvothermal method as an efficient non-noble metal electrocatalyst for NRR. In a 0.1 M HCl solution, 1D-MoS2-xOy exhibits excellent NRR performance, with a remarkable average ammonia yield rate of 5.56 × 10-8 mol s−1 cm−2 at −0.35 V, and a high Faradaic efficiency of 9.86% at −0.3 V. The isotope labeling experiment proves that the generation of NH3 is completely derived from the feed-in N2. Density functional theory calculations show that MoS2 with oxygen partially replacing sulfur can reduce the Gibbs free energy of the potential determination step (PDS). Besides, the unique screw-like structure can provide more N2 adsorption sites for NRR. This work proposes a promising strategy for the reasonable design of non-precious metal-based NRR electrocatalysts. © 2022 Elsevier B.V.
Published: 2022

27. Enabling efficient electrocatalytic conversion of N2 to NH3 by Ti3C2 MXene loaded with semi-metallic 1T′-MoS2 nanosheets

Author: Chen, Xiaoyue, Zhang, Songge, Qian, Xiu, Liang, Zhangqian, Xue, Yanjun, Zhang, Xiaoli, Tian, Jian, Han, Ye, Shao, Minhua, Chen, Xiaoyue, Zhang, Songge, Qian, Xiu, Liang, Zhangqian, Xue, Yanjun, Zhang, Xiaoli, Tian, Jian, Han, Ye, and Shao, Minhua
Abstract: Herein, we assemble semi-metallic 1T′ phase MoS2 on the surface Ti3C2 MXene (1T′-MoS2/Ti3C2 composite) by one-step hydrothermal method for nitrogen fixation. 1T′-MoS2/Ti3C2 composites present a high ammonia yield rate of 31.96 µg h−1 mg−1cat. at − 0.95 V vs. RHE and a Faradaic efficiency (FE) of 30.75% at − 0.7 V, which is much better than pure 1T′-MoS2 and pure Ti3C2 MXenes alone. Furthermore, the 1T′-MoS2/Ti3C2 composites exhibit good selectivity and stability with no significant decrease in ammonia yield rate and FE. Density functional theory (DFT) calculations reveal that 1T′-MoS2/Ti3C2 composite makes the activation and further reduction of *N2 more thermodynamically favorable than pure 1T′-MoS2. 15N isotopic labeling experiment confirms that nitrogen in produced ammonia originates from N2 in the electrolyte. © 2022 Elsevier B.V.
Published: 2022

28. Heterostructuring 2D TiO2 nanosheets in situ grown on Ti3C2Tx MXene to improve the electrocatalytic nitrogen reduction

Author: Qian, Xiu, Wei, Yanjiao, Sun, Mengjie, Han, Ye, Zhang, Xiaoli, Tian, Jian, Shao, Minhua, Qian, Xiu, Wei, Yanjiao, Sun, Mengjie, Han, Ye, Zhang, Xiaoli, Tian, Jian, and Shao, Minhua
Abstract: In this study, TiO2 nanosheets (NSs) grown in situ on extremely conductive Ti3C2Tx MXene to form TiO2/Ti3C2Tx MXene composites with abundant active sites are proposed to effectively achieve electrocatalytic NH3 synthesis. Electron transfer can be promoted by Ti3C2Tx MXene with high conductivity. Meanwhile, the TiO2 NSs in-situ formation can not only avoid Ti3C2Tx MXene microstacking but also enhance the surface specific area of Ti3C2Tx MXene. The TiO2/Ti3C2Tx MXene catalyst reaches a high Faradaic efficiency (FE) of 44.68% at −0.75 V vs. RHE and a large NH3 yield of 44.17 µg h−1 mg−1cat. at −0.95 V, with strong electrochemical durability. 15N isotopic labeling experiments imply that the N in the produced NH3 originated from the N2 of the electrolyte. DFT calculations were conducted to determine the possible NRR reaction pathways for TiO2/Ti3C2Tx MXene composites. MXene catalysts combined with other materials have been rationally designed for efficient ammonia production under ambient conditions. © 2022 Dalian Institute of Chemical Physics, the Chinese Academy of Sciences
Published: 2022

29. Glutathione Peroxidase 4 as a Therapeutic Target for Anti-Colorectal Cancer Drug-Tolerant Persister Cells

Author: Zhang, Xiaoli, Ma, Yiming, Ma, Jianhui, Yang, Lan, Song, Qingzhi, Wang, Hongying, Lv, Guoqing, Zhang, Xiaoli, Ma, Yiming, Ma, Jianhui, Yang, Lan, Song, Qingzhi, Wang, Hongying, and Lv, Guoqing
Abstract: Background: Despite the effectiveness of chemotherapy and targeted therapy for colorectal cancer, drug resistance drives therapy failure and tumor relapse. Increasing evidence has suggested that cancer cells can enter a reversible drug-tolerant persister state to survive chemotherapy or targeted agents. However, the traits and treatable vulnerabilities of anti-colorectal cancer drug-tolerant persister cells is not yet known. Methods: In this study, we established 5-fluorouracil and AZ628-tolerant persister cell models in two colorectal cancer cell lines, namely HCT116 and SW620, and revealed the characteristics of colorectal cancer persister cells by cell viability assay and flow cytometry. We investigated the efficacy and mechanism of ferroptosis inducers RSL3 and FIN56 on persister cells, which are glutathione peroxidase 4 inhibitors. In the xenograft mouse model, we further evaluated the inhibitory effect of RSL3 on tumor regrowth. Results: Colorectal cancer persister cells, which were enriched in the residual cancer cell population, exhibited reduced drug sensitivity, were largely quiescent and expressed high levels of stem cell-related genes and mesenchymal markers but not epithelial markers. The persister cells were more sensitive and underwent ferroptosis induced by glutathione peroxidase 4 inhibitors. Mechanistically, glutathione peroxidase 4 and ferrous iron, which are pivotal ferroptosis regulators, were upregulated in residual cells or tumors, and were hence potential therapeutic targets of persister cells. In the xenograft model, we confirmed that inhibition of glutathione peroxidase 4 restrained tumor regrowth after discontinuation of anti-cancer drug treatment. Moreover, biopsies obtained from patients with colorectal cancer undergoing neoadjuvant chemoradiotherapy revealed upregulated glutathione peroxidase 4 and ferritin heavy chain 1. High glutathione peroxidase 4 expression correlates with a worse prognosis in colorectal cancer patients. Conclusion
Published: 2022

30. Liver Fibrosis is Associated with Clinical Outcomes in Patients with Intracerebral Hemorrhage

Author: Wang,Jinjin, Bian,Liheng, Wang,Anxin, Zhang,Xiaoli, Wang,Dandan, Jiang,Ruixuan, Wang,Wenjuan, Ju,Yi, Lu,Jingjing, Zhao,Xingquan, Wang,Jinjin, Bian,Liheng, Wang,Anxin, Zhang,Xiaoli, Wang,Dandan, Jiang,Ruixuan, Wang,Wenjuan, Ju,Yi, Lu,Jingjing, and Zhao,Xingquan
Abstract: Jinjin Wang,1,2,&ast; Liheng Bian,1,2,&ast; Anxin Wang,1,2 Xiaoli Zhang,1,2 Dandan Wang,1,2 Ruixuan Jiang,1,2 Wenjuan Wang,1,2 Yi Ju,1,2 Jingjing Lu,1,2 Xingquan Zhao1â 4 1Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, Peopleâs Republic of China; 2China National Clinical Research Center for Neurological Diseases, Beijing, Peopleâs Republic of China; 3Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, Peopleâs Republic of China; 4Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, Peopleâs Republic of China&ast;These authors contributed equally to this workCorrespondence: Xingquan Zhao; Jingjing Lu, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, Peopleâs Republic of China, Email zxq@vip.163.com; lujingjing666@gmail.comBackground: Recent studies have reported the predictive value of liver fibrosis indices for hematoma enlargement in patients with intracerebral hemorrhage (ICH). However, little is known about the precise association between fibrosis and ICH prognosis. Thus, our study was designed to investigate the relevance of liver fibrosis, as evaluated by fibrosis-4 (FIB-4) score and poor outcomes after ICH.Methods: We used data from a prospective, multi-center and registry-based database. In this study, patients were stratified by the higher cut-off value of a FIB-4 score â¥ 2.67. The two groups of patients were then compared with regard to baseline characteristics, ICH severity and follow-up outcomes. We performed univariable and multivariable logistic regression analysis to determine the prognostic value of a FIB-4 score â¥ 2.67 for major disability or death. KaplanâMeier survival curves were used to analyze the association between different FIB-4 scores and
Published: 2022

31. Association Between the Neutrophil-to-Lymphocyte Ratio and Adverse Clinical Prognosis in Patients with Spontaneous Intracerebral Hemorrhage

Author: Du,Yang, Wang,Anxin, Zhang,Jia, Zhang,Xiaoli, Li,Ning, Liu,Xinmin, Wang,Wenjuan, Zhao,Xingquan, Bian,Liheng, Du,Yang, Wang,Anxin, Zhang,Jia, Zhang,Xiaoli, Li,Ning, Liu,Xinmin, Wang,Wenjuan, Zhao,Xingquan, and Bian,Liheng
Abstract: Yang Du,1,2 Anxin Wang,1,2 Jia Zhang,1,2 Xiaoli Zhang,2 Ning Li,1,2 Xinmin Liu,1,2 Wenjuan Wang,1,2 Xingquan Zhao,1â 4 Liheng Bian1,2 1Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, Peopleâs Republic of China; 2China National Clinical Research Center for Neurological Diseases, Capital Medical University, Beijing, Peopleâs Republic of China; 3Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, Peopleâs Republic of China; 4Center of Stroke, Beijing Institute for Brain Disorders, Beijing, Peopleâs Republic of ChinaCorrespondence: Liheng Bian; Xingquan Zhao, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, 119 West Road, South 4th Ring, Fengtai District, Beijing, 100070, Peopleâs Republic of China, Tel +86-10-59975835, Email blh389@hotmail.com; zxq@vip.163.comBackground: The neutrophil-to-lymphocyte ratio (NLR) is an index reflecting the overall inflammatory and stress status of patients with major diseases. Many studies associated the NLR with neurological deterioration and a poor prognosis in the spontaneous intracerebral hemorrhage (ICH). However, most previous studies did not further analyze NLR by stratification, and with a relatively small sample size. Besides, the outcome evaluation mostly focused on short-term prognosis or a single timepoint.Methods: Patientsâ basic characteristics and laboratory examination results, including the NLR were taken at baseline, and data from the 1-year follow-up, including the modified Rankin Scale (mRS) and survival status, was obtained for all patients. Patients included in the study were classified into four groups according to NLR quartiles (Q1-Q4). Logistic regression was used to analyze the relationship between different NLR levels and poor outcomes (mRS 3â 5 and mRS 3â 6).Results: A total of 594 ICH patients were enrolled. Glasgow Coma Scale (GCS), NIH Stroke Scale (NIHSS) an
Published: 2022

32. THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: Ion channels

Author: Alexander, Stephen PH, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W., Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M., Catterall, William A., Conner, Alex C., Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A. N., Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A., Kaczmarek, Leonard K., Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W., Perez‐Reyes, Edward, Plant, Leigh D., Rash, Lachlan, Ren, Dejian, Salman, Mootaz M., Sivilotti, Lucia G., Smart, Trevor G., Snutch, Terrance P., Tian, Jinbin, Trimmer, James S., Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D., Winn, Brenda T., Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen PH, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W., Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M., Catterall, William A., Conner, Alex C., Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A. N., Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A., Kaczmarek, Leonard K., Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W., Perez‐Reyes, Edward, Plant, Leigh D., Rash, Lachlan, Ren, Dejian, Salman, Mootaz M., Sivilotti, Lucia G., Smart, Trevor G., Snutch, Terrance P., Tian, Jinbin, Trimmer, James S., Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D., Winn, Brenda T., Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15539. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein‐coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2021

33. THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: Ion channels

Author: Alexander, Stephen PH, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W., Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M., Catterall, William A., Conner, Alex C., Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A. N., Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A., Kaczmarek, Leonard K., Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W., Perez‐Reyes, Edward, Plant, Leigh D., Rash, Lachlan, Ren, Dejian, Salman, Mootaz M., Sivilotti, Lucia G., Smart, Trevor G., Snutch, Terrance P., Tian, Jinbin, Trimmer, James S., Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D., Winn, Brenda T., Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen PH, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W., Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M., Catterall, William A., Conner, Alex C., Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A. N., Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A., Kaczmarek, Leonard K., Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W., Perez‐Reyes, Edward, Plant, Leigh D., Rash, Lachlan, Ren, Dejian, Salman, Mootaz M., Sivilotti, Lucia G., Smart, Trevor G., Snutch, Terrance P., Tian, Jinbin, Trimmer, James S., Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D., Winn, Brenda T., Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15539. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein‐coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2021

34. THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: Ion channels.

Author: Alexander, Stephen Ph, Alexander, Stephen Ph, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Catterall, William A, Conner, Alex C, Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve AN, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen Ph, Alexander, Stephen Ph, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Catterall, William A, Conner, Alex C, Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve AN, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15539. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2021

35. THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: Ion channels.

Author: Alexander, Stephen Ph, Alexander, Stephen Ph, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Catterall, William A, Conner, Alex C, Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve AN, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen Ph, Alexander, Stephen Ph, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Catterall, William A, Conner, Alex C, Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve AN, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15539. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2021

36. The concise guide to pharmacology 2021/22:Ion channels

Author: Alexander, Stephen Ph, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Catterall, William A, Conner, Alex C, Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A N, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen Ph, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Catterall, William A, Conner, Alex C, Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A N, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15539. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2021

37. Emergence of Klebsiella pneumoniae ST307 Co-Producing CTX-M with SHV and KPC from Paediatric Patients at Shenzhen Children’s Hospital, China

Author: Patil,Sandip, Chen,Hongyu, Guo,Chunna, Zhang,Xiaoli, Ren,Pei-Gen, Francisco,Ngiambudulu M, wen,Feiqiu, Patil,Sandip, Chen,Hongyu, Guo,Chunna, Zhang,Xiaoli, Ren,Pei-Gen, Francisco,Ngiambudulu M, and wen,Feiqiu
Abstract: Sandip Patil,1â 3 Hongyu Chen,4 Chunna Guo,4 Xiaoli Zhang,3 Pei-Gen Ren,1 Ngiambudulu M Francisco,5 Feiqiu Wen2,3 1Shenzhen Institute of Advanced Technology, Shenzhen University Town, Shenzhen, Guangdong Province, Peopleâs Republic of China; 2Department of Haematology and Oncology, Shenzhen Childrenâs Hospital, Shenzhen, Guangdong Province, Peopleâs Republic of China; 3Paediatric Research Institute, Shenzhen Childrenâs Hospital, Shenzhen, Guangdong Province, Peopleâs Republic of China; 4Department of Laboratory Medicine, Shenzhen Childrenâs Hospital, Shenzhen, Guangdong Province, Peopleâs Republic of China; 5Grupo de InvestigaÃ§Ã£o Microbiana e ImunolÃ³gica, Instituto Nacional de InvestigaÃ§Ã£o em SaÃºde (National Institute for Health Research), Luanda, AngolaCorrespondence: Feiqiu WenDepartment of Haematology and Oncology, Shenzhen Childrenâs Hospital, Shenzhen, Guangdong Province, Peopleâs Republic of ChinaTel +86 18938690333Fax +86-755 83009888Email fwen62@163.comAim: We investigated the clonal diversity of carbapenemase-producing Klebsiella pneumoniae isolates from the Shenzhen Childrenâs Hospital, China, and drew conclusions on the clinical and public health impact of these isolates as multidrug-resistant.Methods: From January 2014 to December 2018, a total number of 36 unique carbapenemase-producing clinical isolates of Klebsiella pneumoniae were collected out of 900 clinical isolates in paediatric patients from the Shenzhen Childrenâs Hospital, China. After carbapenemase production confirmation, antimicrobial susceptibility, resistance determinants and phylogenetic relationship were determined.Results: The isolates showed resistance to ceftazidime, ertapenem, ampicillin, cefazolin, ceftriaxone, cefotetan, ticarcillin, cefaclor, cefpodoxime, azlocillin, cefcapene, mezlocillin and ampicillin-sulbactam. Of the 36 Klebsiella pneumoniae carbapenemase genes coding isolates, blaNDM was the mostly detected 50% (n=18) followed by blaKPC and bla
Published: 2021

38. THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: Ion channels

Author: Alexander, Stephen PH, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W., Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M., Catterall, William A., Conner, Alex C., Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A. N., Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A., Kaczmarek, Leonard K., Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W., Perez‐Reyes, Edward, Plant, Leigh D., Rash, Lachlan, Ren, Dejian, Salman, Mootaz M., Sivilotti, Lucia G., Smart, Trevor G., Snutch, Terrance P., Tian, Jinbin, Trimmer, James S., Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D., Winn, Brenda T., Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen PH, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W., Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M., Catterall, William A., Conner, Alex C., Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A. N., Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A., Kaczmarek, Leonard K., Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W., Perez‐Reyes, Edward, Plant, Leigh D., Rash, Lachlan, Ren, Dejian, Salman, Mootaz M., Sivilotti, Lucia G., Smart, Trevor G., Snutch, Terrance P., Tian, Jinbin, Trimmer, James S., Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D., Winn, Brenda T., Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15539. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein‐coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2021

39. THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: Ion channels

Author: Alexander, Stephen PH, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W., Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M., Catterall, William A., Conner, Alex C., Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A. N., Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A., Kaczmarek, Leonard K., Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W., Perez‐Reyes, Edward, Plant, Leigh D., Rash, Lachlan, Ren, Dejian, Salman, Mootaz M., Sivilotti, Lucia G., Smart, Trevor G., Snutch, Terrance P., Tian, Jinbin, Trimmer, James S., Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D., Winn, Brenda T., Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen PH, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W., Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M., Catterall, William A., Conner, Alex C., Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A. N., Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A., Kaczmarek, Leonard K., Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W., Perez‐Reyes, Edward, Plant, Leigh D., Rash, Lachlan, Ren, Dejian, Salman, Mootaz M., Sivilotti, Lucia G., Smart, Trevor G., Snutch, Terrance P., Tian, Jinbin, Trimmer, James S., Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D., Winn, Brenda T., Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15539. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein‐coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2021

40. Bounding-box deep calibration for high performance face detection

Author: Luo, Shi, Li, Xiongfei, Zhang, Xiaoli, Luo, Shi, Li, Xiongfei, and Zhang, Xiaoli
Abstract: Modern convolutional neural networks (CNNs)-based face detectors have achieved tremendous strides due to large annotated datasets. However, misaligned results with high detection confidence but low localization accuracy restrict the further improvement of detection performance. In this paper, the authors first predict high confidence detection results on the training set itself. Surprisingly, a considerable part of them exist in the same misalignment problem. Then, the authors carefully examine these cases and point out that annotation misalignment is the main reason. Later, a comprehensive discussion is given for the replacement rationality between predicted and annotated bounding-boxes. Finally, the authors propose a novel Bounding-Box Deep Calibration (BDC) method to reasonably replace misaligned annotations with model predicted bounding-boxes and offer calibrated annotations for the training set. Extensive experiments on multiple detectors and two popular benchmark datasets show the effectiveness of BDC on improving models' precision and recall rate, without adding extra inference time and memory consumption. Our simple and effective method provides a general strategy for improving face detection, especially for light-weight detectors in real-time situations., Comment: 12 pages, 7 figures, 5 tables, 1 algorithm, 9 equation, 2 definition
Published: 2021
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41. The concise guide to pharmacology 2021/22:Ion channels

Author: Alexander, Stephen Ph, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Catterall, William A, Conner, Alex C, Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A N, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, Zhu, Michael, Alexander, Stephen Ph, Mathie, Alistair, Peters, John A, Veale, Emma L, Striessnig, Jörg, Kelly, Eamonn, Armstrong, Jane F, Faccenda, Elena, Harding, Simon D, Pawson, Adam J, Southan, Christopher, Davies, Jamie A, Aldrich, Richard W, Attali, Bernard, Baggetta, Austin M, Becirovic, Elvir, Biel, Martin, Bill, Roslyn M, Catterall, William A, Conner, Alex C, Davies, Paul, Delling, Markus, Virgilio, Francesco Di, Falzoni, Simonetta, Fenske, Stefanie, George, Chandy, Goldstein, Steve A N, Grissmer, Stephan, Ha, Kotdaji, Hammelmann, Verena, Hanukoglu, Israel, Jarvis, Mike, Jensen, Anders A, Kaczmarek, Leonard K, Kellenberger, Stephan, Kennedy, Charles, King, Brian, Kitchen, Philip, Lynch, Joseph W, Perez-Reyes, Edward, Plant, Leigh D, Rash, Lachlan, Ren, Dejian, Salman, Mootaz M, Sivilotti, Lucia G, Smart, Trevor G, Snutch, Terrance P, Tian, Jinbin, Trimmer, James S, Van den Eynde, Charlotte, Vriens, Joris, Wei, Aguan D, Winn, Brenda T, Wulff, Heike, Xu, Haoxing, Yue, Lixia, Zhang, Xiaoli, and Zhu, Michael
Abstract: The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15539. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
Published: 2021

42. Impact of COVID-19 Pandemic on Cardiovascular Testing in Asia

Author: Kudo, T, Lahey, R, Hirschfeld, C, Williams, M, Lu, B, Alasnag, M, Bhatia, M, Henry Bom, H, Dautov, T, Fazel, R, Karthikeyan, G, Keng, F, Rubinshtein, R, Better, N, Cerci, R, Dorbala, S, Raggi, P, Shaw, L, Villines, T, Vitola, J, Choi, A, Malkovskiy, E, Goebel, B, Cohen, Y, Randazzo, M, Pascual, T, Pynda, Y, Dondi, M, Paez, D, Einstein, A, Hinterleitner, G, Lu, Y, Morozova, O, Xu, Z, Lopez-Mattei, J, Parwani, P, Nasery, M, Goda, A, Shirka, E, Benlabgaa, R, Bouyoucef, S, Medjahedi, A, Nailli, Q, Agolti, M, Aguero, R, Alak, M, Alberguina, L, Arroñada, G, Astesiano, A, Norton, C, Benteo, P, Blanco, J, Bonelli, J, Bustos, J, Cabrejas, R, Cachero, J, Campisi, R, Canderoli, A, Carames, S, Carrascosa, P, Castro, R, Cendoya, O, Cognigni, L, Collaud, C, Cortes, C, Courtis, J, Cragnolino, D, Daicz, M, De La Vega, A, De Maria, S, Del Riego, H, Dettori, F, Deviggiano, A, Dragonetti, L, Embon, M, Enriquez, R, Ensinas, J, Faccio, F, Facello, A, Garofalo, D, Geronazzo, R, Gonza, N, Gutierrez, L, Guzzo, M, Hasbani, V, Huerin, M, Jäger, V, Lewkowicz, J, López De Munaín, M, Lotti, J, Marquez, A, Masoli, O, Mastrovito, E, Mayoraz, M, Melado, G, Mele, A, Merani, M, Meretta, A, Molteni, S, Montecinos, M, Noguera, E, Novoa, C, Sueldo, C, Ascani, S, Pollono, P, Pujol, M, Radzinschi, A, Raimondi, G, Redruello, M, Rodríguez, M, Romero, R, Acuña, A, Rovaletti, F, San Miguel, L, Solari, L, Strada, B, Traverso, S, Traverzo, S, Espeche, M, Weihmuller, J, Wolcan, J, Zeffiro, S, Sakanyan, M, Beuzeville, S, Boktor, R, Butler, P, Calcott, J, Carr, L, Chan, V, Chao, C, Chong, W, Dobson, M, Downie, D, Dwivedi, G, Elison, B, Engela, J, Francis, R, Gaikwad, A, Basavaraj, A, Goodwin, B, Greenough, R, Hamilton-Craig, C, Hsieh, V, Joshi, S, Lederer, K, Lee, K, Lee, J, Magnussen, J, Mai, N, Mander, G, Murton, F, Nandurkar, D, Neill, J, O'Rourke, E, O'Sullivan, P, Pandos, G, Pathmaraj, K, Pitman, A, Poulter, R, Premaratne, M, Prior, D, Ridley, L, Rutherford, N, Salehi, H, Saunders, C, Scarlett, 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J., Rubinshtein, Ronen, Better, Nathan, Cerci, Rodrigo Julio, Dorbala, Sharmila, Raggi, Paolo, Shaw, Leslee J., Villines, Todd C., Vitola, João V., Choi, Andrew D., Malkovskiy, Eli, Goebel, Benjamin, Cohen, Yosef A., Randazzo, Michael, Pascual, Thomas N. B., Pynda, Yaroslav, Dondi, Maurizio, Paez, Diana, Einstein, Andrew J., Cerci, Rodrigo, Vitola, Joao V., Hinterleitner, Gerd, Lu, Yao, Morozova, Olga, Xu, Zhuoran, Cohen, Yosef, Choi, Andrew, Lopez-Mattei, Juan, Parwani, Purvi, Nasery, Mohammad Nawaz, Goda, Artan, Shirka, Ervina, Benlabgaa, Rabie, Bouyoucef, Salah, Medjahedi, Abdelkader, Nailli, Qais, Agolti, Mariela, Aguero, Roberto Nicolas, Alak, Maria del Carmen, Alberguina, Lucia Graciela, Arroñada, Guillermo, Astesiano, Andrea, Astesiano, Alfredo, Norton, Carolina Bas, Benteo, Pablo, Blanco, Juan, Bonelli, Juan Manuel, Bustos, Jose Javier, Cabrejas, Raul, Cachero, Jorge, Campisi, Roxana, Canderoli, Alejandro, Carames, Silvia, Carrascosa, Patrícia, Castro, Ricardo, Cendoya, Oscar, Cognigni, Luciano Martin, Collaud, Carlos, Cortes, Claudia, Courtis, Javier, Cragnolino, Daniel, Daicz, Mariana, De La Vega, Alejandro, De Maria, Silvia Teresa, Del Riego, Horacio, Dettori, Fernando, Deviggiano, Alejandro, Dragonetti, Laura, Embon, Mario, Enriquez, Ruben Emilio, Ensinas, Jorge, Faccio, Fernando, Facello, Adolfo, Garofalo, Diego, Geronazzo, Ricardo, Gonza, Natalia, Gutierrez, Lucas, Guzzo, Miguel Angel, Hasbani, Victor, Huerin, Melina, Jäger, Victor, Lewkowicz, Julio Manuel, López De Munaín, Maria Nieves A., Lotti, Jose Maria, Marquez, Alejandra, Masoli, Osvaldo, Masoli, Osvaldo Horacio, Mastrovito, Edgardo, Mayoraz, Matias, Melado, Graciela Eva, Mele, Anibal, Merani, Maria Fernanda, Meretta, Alejandro Horacio, Molteni, Susana, Montecinos, Marcos, Noguera, Eduardo, Novoa, Carlos, Sueldo, Claudio Pereyra, Ascani, Sebastian Perez, Pollono, Pablo, Pujol, Maria Paula, Radzinschi, Alejandro, Raimondi, Gustavo, Redruello, Marcela, Rodríguez, Marina, Rodríguez, Matías, Romero, Romina Lorena, Acuña, Arturo Romero, Rovaletti, Federico, San Miguel, Lucas, Solari, Lucrecia, Strada, Bruno, Traverso, Sonia, Traverzo, Sonia Simona, Espeche, Maria del Huerto Velazquez, Weihmuller, Juan Sebastian, Wolcan, Juan, Zeffiro, Susana, Sakanyan, Mari, Beuzeville, Scott, Boktor, Raef, Butler, Patrick, Calcott, Jennifer, Carr, Loretta, Chan, Virgil, Chao, Charles, Chong, Woon, Dobson, Mark, Downie, D'Arne, Dwivedi, Girish, Elison, Barry, Engela, Jean, Francis, Roslyn, Gaikwad, Anand, Basavaraj, Ashok Gangasandra, Goodwin, Bruce, Greenough, Robert, Hamilton-Craig, Christian, Hsieh, Victar, Joshi, Subodh, Lederer, Karin, Lee, Kenneth, Lee, Joseph, Magnussen, John, Mai, Nghi, Mander, Gordon, Murton, Fiona, Nandurkar, Dee, Neill, Johanne, O'Rourke, Edward, O'Sullivan, Patricia, Pandos, George, Pathmaraj, Kunthi, Pitman, Alexander, Poulter, Rohan, Premaratne, Manuja, Prior, David, Ridley, Lloyd, Rutherford, Natalie, Salehi, Hamid, Saunders, Connor, Scarlett, Luke, Seneviratne, Sujith, Shetty, Deepa, Shrestha, Ganesh, Shulman, Jonathan, Solanki, Vijay, Stanton, Tony, Stuart, Murch, Stubbs, Michael, Swainson, Ian, Taubman, Kim, Taylor, Andrew, Thomas, Paul, Unger, Steven, Upton, Anthony, Vamadevan, Shankar, Van Gaal, 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Ulises, Baric, Ana, Batinic, Tonci, Franceschi, Maja, Paar, Maja Hrabak, Jukic, Mladen, Medakovic, Petar, Persic, Viktor, Prpic, Marina, Punda, Ante, Batista, Juan Felipe, Gómez Lauchy, Juan Manuel, Gutierrez, Yamile Marcos, Menéndez, Rayner, Peix, Amalia, Rochela, Luis, Panagidis, Christoforos, Petrou, Ioannis, Engelmann, Vaclav, Kaminek, Milan, Kincl, Vladimír, Lang, Otto, Simanek, Milan, Abdulla, Jawdat, Bøttcher, Morten, Christensen, Mette, Gormsen, Lars Christian, Hasbak, Philip, Hess, Søren, Holdgaard, Paw, Johansen, Allan, Kyhl, Kasper, Norgaard, Bjarne Linde, Øvrehus, Kristian Altern, Rønnow Sand, Niels Peter, Steffensen, Rolf, Thomassen, Anders, Zerahn, Bo, Perez, Alfredo, Escorza Velez, Giovanni Alejandro, Velez, Mayra Sanchez, Abdel Aziz, Islam Shawky, Abougabal, Mahasen, Ahmed, Taghreed, Allam, Adel, Asfour, Ahmed, Hassan, Mona, Hassan, Alia, Ibrahim, Ahmed, Kaffas, Sameh, Kandeel, Ahmed, Ali, Mohamed Mandour, Mansy, Ahmad, Maurice, Hany, Nabil, Sherif, Shaaban, Mahmoud, 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Chetan, Patel, Tapan, Patel, Ravi, Patel, Shivani, Saxena, Sudhir, Sengupta, Shantanu, Singh, Santosh, Singh, Bhanupriya, Sood, Ashwani, Verma, Atul, Affandi, Erwin, Alam, Padma Savenadia, Edison, Edison, Gunawan, Gani, Hapkido, Habusari, Hidayat, Basuki, Huda, Aulia, Mukti, Anggoro Praja, Prawiro, Djoko, Soeriadi, Erwin Affandi, Syawaluddin, Hilman, Albadr, Amjed, Assadi, Majid, Emami, Farshad, Houshmand, Golnaz, Maleki, Majid, Rostami, Maryam Tajik, Zakavi, Seyed Rasoul, Zaid, Eed Abu, Agranovich, Svetlana, Arnson, Yoav, Bar-Shalom, Rachel, Frenkel, Alex, Knafo, Galit, Lugassi, Rachel, Maor Moalem, Israel Shlomo, Mor, Maya, Muskal, Noam, Ranser, Sara, Shalev, Aryeh, Albano, Domenico, Alongi, Pierpaolo, Arnone, Gaspare, Bagatin, Elisa, Baldari, Sergio, Bauckneht, Matteo, Bertelli, Paolo, Bianco, Francesco, Bonfiglioli, Rachele, Boni, Roberto, Bruno, Andrea, Bruno, Isabella, Busnardo, Elena, Califaretti, Elena, Camoni, Luca, Carnevale, Aldo, Casoni, Roberta, Cavallo, Armando Ugo, Cavenaghi, Giorgio, Chierichetti, Franca, Chiocchi, Marcello, Cittanti, Corrado, Colletta, Mauro, Conti, Umberto, Cossu, Alberto, Cuocolo, Alberto, Cuzzocrea, Marco, De Rimini, Maria Luisa, De Vincentis, Giuseppe, Del Giudice, Eleonora, Del Torto, Alberico, Della Tommasina, Veronica, Durmo, Rexhep, Erba, Paola Anna, Evangelista, Laura, Faletti, Riccardo, Faragasso, Evelina, Farsad, Mohsen, Ferro, Paola, Florimonte, Luigia, Frantellizzi, Viviana, Fringuelli, Fabio Massimo, Gatti, Marco, Gaudiano, Angela, Gimelli, Alessia, Giubbini, Raffaele, Giuffrida, Francesca, Ialuna, Salvatore, Laudicella, Riccardo, Leccisotti, Lucia, Leva, Lucia, Liga, Riccardo, Liguori, Carlo, Longo, Giampiero, Maffione, Margherita, Mancini, Maria Elisabetta, Marcassa, Claudio, Milan, Elisa, Nardi, Barbara, Pacella, Sara, Pepe, Giovanna, Pontone, Gianluca, Pulizzi, Sabina, Quartuccio, Natale, Rampin, Lucia, Ricci, Fabrizio, Rossini, Pierluigi, Rubini, Giuseppe, Russo, Vincenzo, Sacchetti, Gian Mauro, Sambuceti, Gianmario, Scarano, Massimo, Sciagrà, Roberto, Sperandio, Massimiliano, Stefanelli, Antonella, Ventroni, Guido, Zoboli, Stefania, Baugh, Dainia, Chambers, Duane, Madu, Ernest, Nunura, Felix, Asano, Hiroshi, Chimura, Chimura Misato, Fujimoto, Shinichiro, Fujisue, Koichiro, Fukunaga, Tomohisa, Fukushima, Yoshimitsu, Fukuyama, Kae, Hashimoto, Jun, Ichikawa, Yasutaka, Iguchi, Nobuo, Imai, Masamichi, Inaki, Anri, Ishimura, Hayato, Isobe, Satoshi, Kadokami, Toshiaki, Kato, Takao, Kumita, Shinichiro, Maruno, Hirotaka, Mataki, Hiroyuki, Miyagawa, Masao, Morimoto, Ryota, Moroi, Masao, Nagamachi, Shigeki, Nakajima, Kenichi, Nakata, Tomoaki, Nakazato, Ryo, Nanasato, Mamoru, Naya, Masanao, Norikane, Takashi, Ohta, Yasutoshi, Okayama, Satoshi, Okizaki, Atsutaka, Otomi, Yoichi, Otsuka, Hideki, Saito, Masaki, Sakata, Sakata Yasushi, Sarai, Masayoshi, Sato, Daisuke, Shiraishi, Shinya, Suwa, Yoshinobu, Takanami, Kentaro, Takehana, Kazuya, Taki, Junichi, Tamaki, Nagara, Taniguchi, Yasuyo, Teragawa, Hiroki, Tomizawa, Nobuo, Tsujita, Kenichi, Umeji, Kyoko, Wakabayashi, Yasushi, Yamada, Shinichiro, Yamazaki, Shinya, Yoneyama, Tatsuya, Rawashdeh, Mohammad, Batyrkhanov, Daultai, Makhdomi, Khalid, Ombati, Kevin, Alkandari, Faridah, Garashi, Masoud, Coie, Tchoyoson Lim, Rajvong, Sonexay, Kalinin, Artem, Kalnina, Marika, Haidar, Mohamad, Komiagiene, Renata, Kviecinskiene, Giedre, Mataciunas, Mindaugas, Vajauskas, Donatas, Picard, Christian, Karim, Noor Khairiah A., Reichmuth, Luise, Samuel, Anthony, Allarakha, Mohammad Aaftaab, Naojee, Ambedhkar Shantaram, Alexanderson-Rosas, Erick, Barragan, Erika, González-Montecinos, Alejandro Becerril, Cabada, Manuel, Rodriguez, Daniel Calderon, Carvajal-Juarez, Isabel, Cortés, Violeta, Cortés, Filiberto, De La Peña, Erasmo, Gama-Moreno, Manlio, González, Luis, Ramírez, Nelsy Gonzalez, Jiménez-Santos, Moisés, Matos, Luis, Monroy, Edgar, Morelos, Martha, Ornelas, Mario, Ortga Ramirez, Jose Alberto, Preciado-Anaya, Andrés, Preciado-Gutiérrez, Óscar Ulises, Barragan, Adriana Puente, Rosales Uvera, Sandra Graciela, Sandoval, Sigelinda, Tomas, Miguel Santaularia, Sierra-Galan, Lilia M., Siu, Silvia, Vallejo, Enrique, Valles, Mario, Faraggi, Marc, Sereegotov, Erdenechimeg, Ilic, Srdja, Ben-Rais, Nozha, Alaoui, Nadia Ismaili, Taleb, Sara, Pa Myo, Khin Pa, Thu, Phyo Si, Ghimire, Ram Kumar, Rajbanshi, Bijoy, Barneveld, Peter, Glaudemans, Andor, Habets, Jesse, Koopmans, Klaas Pieter, Manders, Jeroen, Pool, Stefan, Scholte, Arthur, Scholtens, Asbjørn, Slart, Riemer, Thimister, Paul, Van Asperen, Erik-Jan, Veltman, Niels, Verschure, Derk, Wagenaar, Nils, Edmond, John, Ellis, Chris, Johnson, Kerryanne, Keenan, Ross, Kueh, Shaw Hua (Anthony), Occleshaw, Christopher, Sasse, Alexander, To, Andrew, Van Pelt, Niels, Young, Calum, Cuadra, Teresa, Roque Vanegas, Hector Bladimir, Soli, Idrissa Adamou, Issoufou, Djibrillou Moussa, Ayodele, Tolulope, Madu, Chibuzo, Onimode, Yetunde, Efros-Monsen, Elen, Forsdahl, Signe Helene, Hildre Dimmen, Jenni-Mari, Jørgensen, Arve, Krohn, Isabel, Løvhaugen, Pål, Bråten, Anders Tjellaug, Al Dhuhli, Humoud, Al Kindi, Faiza, Al-Bulushi, Naeema, Jawa, Zabah, Tag, Naima, Afzal, Muhammad Shehzad, Fatima, Shazia, Younis, Muhammad Numair, Riaz, Musab, Saadullah, Mohammad, Herrera, Yariela, Lenturut-Katal, Dora, Vázquez, Manuel Castillo, Ortellado, José, Akhter, Afroza, Cao, Dianbo, Cheung, Stephen, Dai, Xu, Gong, Lianggeng, Han, Dan, Hou, Yang, Li, Caiying, Li, Tao, Li, Dong, Li, Sijin, Liu, Jinkang, Liu, Hui, Ng, Ming Yen, Sun, Kai, Tang, Gongshun, Wang, Jian, Wang, Ximing, Wang, Zhao-Qian, Wang, Yining, Wang, Yifan, Wu, Jiang, Wu, Zhifang, Xia, Liming, Xiao, Jiangxi, Xu, Lei, Yang, Youyou, Yin, Wu, Yu, Jianqun, Yuan, Li, Zhang, Tong, Zhang, Longjiang, Zhang, Yong-Gao, Zhang, Xiaoli, Zhu, Li, Alfaro, Ana, Abrihan, Paz, Barroso, Asela, Cruz, Eric, Gomez, Marie Rhiamar, Magboo, Vincent Peter, Medina, John Michael, Obaldo, Jerry, Pastrana, Davidson, Pawhay, Christian Michael, Quinon, Alvin, Tang, Jeanelle Margareth, Tecson, Bettina, Uson, Kristine Joy, Uy, Mila, Kostkiewicz, Magdalena, Kunikowska, Jolanta, Bettencourt, Nuno, Cantinho, Guilhermina, Ferreira, Antonio, Syed, Ghulam, Arnous, Samer, Atyani, Said, Byrne, Angela, Gleeson, Tadhg, Kerins, David, Meehan, Conor, Murphy, David, Murphy, Mark, Murray, John, O'Brien, Julie, Bang, Ji-In, Bom, Henry, Cho, Sang-Geon, Hong, Chae Moon, Jang, Su Jin, Jeong, Yong Hyu, Kang, Won Jun, Kim, Ji-Young, Lee, Jaetae, Namgung, Chang Kyeong, So, Young, Won, Kyoung Sook, Majstorov, Venjamin, Vavlukis, Marija, Salobir, Barbara Gužic, Štalc, Monika, Benedek, Theodora, Benedek, Imre, Mititelu, Raluca, Stan, Claudiu Adrian, Ansheles, Alexey, Dariy, Olga, Drozdova, Olga, Gagarina, Nina, Gulyaev, Vsevolod Milyevich, Itskovich, Irina, Karalkin, Anatoly, Kokov, Alexander, Migunova, Ekaterina, Pospelov, Viktor, Ryzhkova, Daria, Saifullina, Guzaliya, Sazonova, Svetlana, Sergienko, Vladimir, Shurupova, Irina, Trifonova, Tatjana, Ussov, Wladimir Yurievich, Vakhromeeva, Margarita, Valiullina, Nailya, Zavadovsky, Konstantin, Zhuravlev, Kirill, Okarvi, Subhani, Saranovic, Dragana Sobic, Keng, Felix, Jason See, Jia Hao, Sekar, Ramkumar, Yew, Min Sen, Vondrak, Andrej, Bejai, Shereen, Bennie, George, Bester, Ria, Engelbrecht, Gerrit, Evbuomwan, Osayande, Gongxeka, Harlem, Vuuren, Magritha Jv, Kaplan, Mitchell, Khushica, Purbhoo, Lakhi, Hoosen, Louw, Lizette, Malan, Nico, Milos, Katarina, Modiselle, Moshe, More, Stuart, Naidoo, Mathava, Scholtz, Leonie, Vangu, Mboyo, Aguadé-Bruix, Santiago, Blanco, Isabel, Cabrera, Antonio, Camarero, Alicia, Casáns-Tormo, Irene, Cuellar-Calabria, Hug, Flotats, Albert, Fuentes Cañamero, Maria Eugenia, García, María Elia, Jimenez-Heffernan, Amelia, Leta, Rubén, Diaz, Javier Lopez, Lumbreras, Luis, Marquez-Cabeza, Juan Javier, Martin, Francisco, Martinez de Alegria, Anxo, Medina, Francisco, Canal, Maria Pedrera, Peiro, Virginia, Pubul-Nuñez, Virginia, Rayo Madrid, Juan Ignacio, Rey, Cristina Rodríguez, Perez, Ricardo Ruano, Ruiz, Joaquín, Hernández, Gertrudis Sabatel, Sevilla, Ana, Zeidán, Nahla, Nanayakkara, Damayanthi, Udugama, Chandraguptha, Simonsson, Magnus, Alkadhi, Hatem, Buechel, Ronny Ralf, Burger, Peter, Ceriani, Luca, De Boeck, Bart, Gräni, Christoph, Juillet de Saint Lager Lucas, Alix, Kamani, Christel H., Kawel-Boehm, Nadine, Manka, Robert, Prior, John O., Rominger, Axel, Vallée, Jean-Paul, Khiewvan, Benjapa, Premprabha, Teerapon, Thientunyakit, Tanyaluck, Sellem, Ali, Kir, Kemal Metin, Sayman, Haluk, Sebikali, Mugisha Julius, Muyinda, Zerida, Kmetyuk, Yaroslav, Korol, Pavlo, Mykhalchenko, Olena, Pliatsek, Volodymyr, Satyr, Maryna, Albalooshi, Batool, Ahmed Hassan, Mohamed Ismail, Anderson, Jill, Bedi, Punit, Biggans, Thomas, Bularga, Anda, Bull, Russell, Burgul, Rajesh, Carpenter, John-Paul, Coles, Duncan, Cusack, David, Deshpande, Aparna, Dougan, John, Fairbairn, Timothy, Farrugia, Alexia, Gopalan, Deepa, Gummow, Alistair, Ramkumar, Prasad Guntur, Hamilton, Mark, Harbinson, Mark, Hartley, Thomas, Hudson, Benjamin, Joshi, Nikhil, Kay, Michael, Kelion, Andrew, Khokhar, Azhar, Kitt, Jamie, Lee, Ken, Low, Chen, Mak, Sze Mun, Marousa, Ntouskou, Martin, Jon, Mcalindon, Elisa, Menezes, Leon, Morgan-Hughes, Gareth, Moss, Alastair, Murray, Anthony, Nicol, Edward, Patel, Dilip, Peebles, Charles, Pugliese, Francesca, Luis Rodrigues, Jonathan Carl, Rofe, Christopher, Sabharwal, Nikant, Schofield, Rebecca, Semple, Thomas, Sharma, Naveen, Strouhal, Peter, Subedi, Deepak, Topping, William, Tweed, Katharine, Weir-Mccall, Jonathan, Abbara, Suhny, Abbasi, Taimur, Abbott, Brian, Abohashem, Shady, Abramson, Sandra, Al-Abboud, Tarek, Al-Mallah, Mouaz, Almousalli, Omar, Ananthasubramaniam, Karthikeyan, Kumar, Mohan Ashok, Askew, Jeffrey, Attanasio, Lea, Balmer-Swain, Mallory, Bayer, Richard R., Bernheim, Adam, Bhatti, Sabha, Bieging, Erik, Blankstein, Ron, Bloom, Stephen, Blue, Sean, Bluemke, David, Borges, Andressa, Branch, Kelley, Bravo, Paco, 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Ami, Janardhanan, Rajesh, Jellis, Christine, Jerome, Scott, Kalra, Dinesh, Kaviratne, Summanther, Kay, Fernando, Kelly, Faith, Khalique, Omar, Kinkhabwala, Mona, Iii, George Kinzfogl, Kircher, Jacqueline, Kirkbride, Rachael, Kontos, Michael, Kottam, Anupama, Krepp, Joseph, Layer, Jay, Lee, Steven H., Leppo, Jeffrey, Lesser, John, Leung, Steve, Lewin, Howard, Litmanovich, Diana, Liu, Yiyan, Magurany, Kathleen, Markowitz, Jeremy, Marn, Amanda, Matis, Stephen E., Mckenna, Michael, Mcrae, Tony, Mendoza, Fernando, Merhige, Michael, Min, David, Moffitt, Chanan, Moncher, Karen, Moore, Warren, Morayati, Shamil, Morris, Michael, Mossa-Basha, Mahmud, Mrsic, Zorana, Murthy, Venkatesh, Nagpal, Prashant, Napier, Kyle, Nelson, Katarina, Nijjar, Prabhjot, Osman, Medhat, Passen, Edward, Patel, Amit, Patil, Pravin, Paul, Ryan, Phillips, Lawrence, Polsani, Venkateshwar, Poludasu, Rajaram, Pomerantz, Brian, Porter, Thomas, Prentice, Ryan, Pursnani, Amit, Rabbat, Mark, Ramamurti, Suresh, Rich, Florence, Luna, Hiram Rivera, Robinson, Austin, Robles, Kim, Rodríguez, Cesar, Rorie, Mark, Rumberger, John, Russell, Raymond, Sabra, Philip, Sadler, Diego, Schemmer, Mary, Schoepf, U. Joseph, Shah, Samir, Shah, Nishant, Shanbhag, Sujata, Sharma, Gaurav, Shayani, Steven, Shirani, Jamshid, Shivaram, Pushpa, Sigman, Steven, Simon, Mitch, Slim, Ahmad, Smith, David, Smith, Alexandra, Soman, Prem, Sood, Aditya, Srichai-Parsia, Monvadi Barbara, Streeter, James, T, Albert, Tawakol, Ahmed, Thomas, Dustin, Thompson, Randall, Torbet, Tara, Trinidad, Desiree, Ullery, Shawn, Unzek, Samuel, Uretsky, Seth, Vallurupalli, Srikanth, Verma, Vikas, Waller, Alfonso, Wang, Ellen, Ward, Parker, Weissman, Gaby, Wesbey, George, White, Kelly, Winchester, David, Wolinsky, David, Yost, Sandra, Zgaljardic, Michael, Alonso, Omar, Beretta, Mario, Ferrando, Rodolfo, Kapitan, Miguel, Mut, Fernando, Djuraev, Omoa, Rozikhodjaeva, Gulnora, Le Ngoc, Ha, Mai, Son Hong, Nguyen, Xuan Canh, Kudo, T, Lahey, R, Hirschfeld, C, Williams, M, Lu, B, Alasnag, M, Bhatia, M, Henry Bom, H, Dautov, T, Fazel, R, Karthikeyan, G, Keng, F, Rubinshtein, R, Better, N, Cerci, R, Dorbala, S, Raggi, P, Shaw, L, Villines, T, 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J., Rubinshtein, Ronen, Better, Nathan, Cerci, Rodrigo Julio, Dorbala, Sharmila, Raggi, Paolo, Shaw, Leslee J., Villines, Todd C., Vitola, João V., Choi, Andrew D., Malkovskiy, Eli, Goebel, Benjamin, Cohen, Yosef A., Randazzo, Michael, Pascual, Thomas N. B., Pynda, Yaroslav, Dondi, Maurizio, Paez, Diana, Einstein, Andrew J., Cerci, Rodrigo, Vitola, Joao V., Hinterleitner, Gerd, Lu, Yao, Morozova, Olga, Xu, Zhuoran, Cohen, Yosef, Choi, Andrew, Lopez-Mattei, Juan, Parwani, Purvi, Nasery, Mohammad Nawaz, Goda, Artan, Shirka, Ervina, Benlabgaa, Rabie, Bouyoucef, Salah, Medjahedi, Abdelkader, Nailli, Qais, Agolti, Mariela, Aguero, Roberto Nicolas, Alak, Maria del Carmen, Alberguina, Lucia Graciela, Arroñada, Guillermo, Astesiano, Andrea, Astesiano, Alfredo, Norton, Carolina Bas, Benteo, Pablo, Blanco, Juan, Bonelli, Juan Manuel, Bustos, Jose Javier, Cabrejas, Raul, Cachero, Jorge, Campisi, Roxana, Canderoli, Alejandro, Carames, Silvia, Carrascosa, Patrícia, Castro, Ricardo, Cendoya, Oscar, Cognigni, Luciano Martin, Collaud, Carlos, Cortes, Claudia, Courtis, Javier, Cragnolino, Daniel, Daicz, Mariana, De La Vega, Alejandro, De Maria, Silvia Teresa, Del Riego, Horacio, Dettori, Fernando, Deviggiano, Alejandro, Dragonetti, Laura, Embon, Mario, Enriquez, Ruben Emilio, Ensinas, Jorge, Faccio, Fernando, Facello, Adolfo, Garofalo, Diego, Geronazzo, Ricardo, Gonza, Natalia, Gutierrez, Lucas, Guzzo, Miguel Angel, Hasbani, Victor, Huerin, Melina, Jäger, Victor, Lewkowicz, Julio Manuel, López De Munaín, Maria Nieves A., Lotti, Jose Maria, Marquez, Alejandra, Masoli, Osvaldo, Masoli, Osvaldo Horacio, Mastrovito, Edgardo, Mayoraz, Matias, Melado, Graciela Eva, Mele, Anibal, Merani, Maria Fernanda, Meretta, Alejandro Horacio, Molteni, Susana, Montecinos, Marcos, Noguera, Eduardo, Novoa, Carlos, Sueldo, Claudio Pereyra, Ascani, Sebastian Perez, Pollono, Pablo, Pujol, Maria Paula, Radzinschi, Alejandro, Raimondi, Gustavo, Redruello, Marcela, Rodríguez, Marina, Rodríguez, Matías, Romero, Romina Lorena, Acuña, Arturo Romero, Rovaletti, Federico, San Miguel, Lucas, Solari, Lucrecia, Strada, Bruno, Traverso, Sonia, Traverzo, Sonia Simona, Espeche, Maria del Huerto Velazquez, Weihmuller, Juan Sebastian, Wolcan, Juan, Zeffiro, Susana, Sakanyan, Mari, Beuzeville, Scott, Boktor, Raef, Butler, Patrick, Calcott, Jennifer, Carr, Loretta, Chan, Virgil, Chao, Charles, Chong, Woon, Dobson, Mark, Downie, D'Arne, Dwivedi, Girish, Elison, Barry, Engela, Jean, Francis, Roslyn, Gaikwad, Anand, Basavaraj, Ashok Gangasandra, Goodwin, Bruce, Greenough, Robert, Hamilton-Craig, Christian, Hsieh, Victar, Joshi, Subodh, Lederer, Karin, Lee, Kenneth, Lee, Joseph, Magnussen, John, Mai, Nghi, Mander, Gordon, Murton, Fiona, Nandurkar, Dee, Neill, Johanne, O'Rourke, Edward, O'Sullivan, Patricia, Pandos, George, Pathmaraj, Kunthi, Pitman, Alexander, Poulter, Rohan, Premaratne, Manuja, Prior, David, Ridley, Lloyd, Rutherford, Natalie, Salehi, Hamid, Saunders, Connor, Scarlett, Luke, Seneviratne, Sujith, Shetty, Deepa, Shrestha, Ganesh, Shulman, Jonathan, Solanki, Vijay, Stanton, Tony, Stuart, Murch, Stubbs, Michael, Swainson, Ian, Taubman, Kim, Taylor, Andrew, Thomas, Paul, Unger, Steven, Upton, Anthony, Vamadevan, Shankar, Van Gaal, William, Verjans, Johan, Voutnis, Demetrius, Wayne, Victor, Wilson, Peter, Wong, David, Wong, Kirby, Younger, John, Feuchtner, Gudrun, Mirzaei, Siroos, Weiss, Konrad, Maroz-Vadalazhskaya, Natallia, Gheysens, Olivier, Homans, Filip, Moreno-Reyes, Rodrigo, Pasquet, Agnès, Roelants, Veronique, Van De Heyning, Caroline M., Ríos, Raúl Araujo, Soldat-Stankovic, Valentina, Stankovic, Sinisa, Albernaz Siqueira, Maria Helena, Almeida, Augusto, Alves Togni, Paulo Henrique, Andrade, Jose Henrique, Andrade, Luciana, Anselmi, Carlos, Araújo, Roberta, Azevedo, Guilherme, Bezerra, Sabbrina, Biancardi, Rodrigo, Grossman, Gabriel Blacher, Brandão, Simone, Pianta, Diego Bromfman, Carreira, Lara, Castro, Bruno, Chang, Tien, Cunali, Fernando, Cury, Roberto, Dantas, Roberto, de Amorim Fernandes, Fernando, De Lorenzo, Andrea, De Macedo Filho, Robson, Erthal, Fernanda, Fernandes, Fabio, Fernandes, Juliano, De Souza, Thiago Ferreira, Alves, Wilson Furlan, Ghini, Bruno, Goncalves, Luiz, Gottlieb, Ilan, Hadlich, Marcelo, Kameoka, Vinícius, Lima, Ronaldo, Lima, Adna, Lopes, Rafael Willain, Machado e Silva, Ricardo, Magalhães, Tiago, Silva, Fábio Martins, Mastrocola, Luiz Eduardo, Medeiros, Fábio, Meneghetti, José Claudio, Naue, Vania, Naves, Danilo, Nolasco, Roberto, Nomura, Cesar, Oliveira, Joao Bruno, Paixao, Eduardo, De Carvalho, Filipe Penna, Pinto, Ibraim, Possetti, Priscila, Quinta, Mayra, Nogueira Ramos, Rodrigo Rizzo, Rocha, Ricardo, Rodrigues, Alfredo, Rodrigues, Carlos, Romantini, Leila, Sanches, Adelina, Santana, Sara, Sara da Silva, Leonardo, Schvartzman, Paulo, Matushita, Cristina Sebastião, Senra, Tiago, Shiozaki, Afonso, Menezes de Siqueira, Maria Eduarda, Siqueira, Cristiano, Smanio, Paola, Soares, Carlos Eduardo, Junior, José Soares, Bittencourt, Marcio Sommer, Spiro, Bernardo, Mesquita, Cláudio Tinoco, Torreao, Jorge, Torres, Rafael, Uellendahl, Marly, Monte, Guilherme Urpia, Veríssimo, Otávia, Cabeda, Estevan Vieira, Pedras, Felipe Villela, Waltrick, Roberto, Zapparoli, Marcello, Naseer, Hamid, Garcheva-Tsacheva, Marina, Kostadinova, Irena, Theng, Youdaline, Abikhzer, Gad, Barette, Rene, Chow, Benjamin, Dabreo, Dominique, Friedrich, Matthias, Garg, Ria, Hafez, Mohammed Nassoh, Johnson, Chris, Kiess, Marla, Leipsic, Jonathon, Leung, Eugene, Miller, Robert, Oikonomou, Anastasia, Probst, Stephan, Roifman, Idan, Small, Gary, Tandon, Vikas, Trivedi, Adwait, White, James, Zukotynski, Katherine, Canessa, Jose, Muñoz, Gabriel Castro, Concha, Carmen, Hidalgo, Pablo, Lovera, Cesar, Massardo, Teresa, Vargas, Luis Salazar, Abad, Pedro, Arturo, Harold, Ayala, Sandra, Benitez, Luis, Cadena, Alberto, Caicedo, Carlos, Moncayo, Antonio Calderón, Gomez, Sharon, Gutierrez Villamil, Claudia T., Jaimes, Claudia, Londoño, Juan, Londoño Blair, Juan Luis, Pabon, Luz, Pineda, Mauricio, Rojas, Juan Carlos, Ruiz, Diego, Escobar, Manuel Valencia, Vasquez, Andres, Vergel, Damiana, Zuluaga, Alejandro, Gamboa, Isabel Berrocal, Castro, Gabriel, González, Ulises, Baric, Ana, Batinic, Tonci, Franceschi, Maja, Paar, Maja Hrabak, Jukic, Mladen, Medakovic, Petar, Persic, Viktor, Prpic, Marina, Punda, Ante, Batista, Juan Felipe, Gómez Lauchy, Juan Manuel, Gutierrez, Yamile Marcos, Menéndez, Rayner, Peix, Amalia, Rochela, Luis, Panagidis, Christoforos, Petrou, Ioannis, Engelmann, Vaclav, Kaminek, Milan, Kincl, Vladimír, Lang, Otto, Simanek, Milan, Abdulla, Jawdat, Bøttcher, Morten, Christensen, Mette, Gormsen, Lars Christian, Hasbak, Philip, Hess, Søren, Holdgaard, Paw, Johansen, Allan, Kyhl, Kasper, Norgaard, Bjarne Linde, Øvrehus, Kristian Altern, Rønnow Sand, Niels Peter, Steffensen, Rolf, Thomassen, Anders, Zerahn, Bo, Perez, Alfredo, Escorza Velez, Giovanni Alejandro, Velez, Mayra Sanchez, Abdel Aziz, Islam Shawky, Abougabal, Mahasen, Ahmed, Taghreed, Allam, Adel, Asfour, Ahmed, Hassan, Mona, Hassan, Alia, Ibrahim, Ahmed, Kaffas, Sameh, Kandeel, Ahmed, Ali, Mohamed Mandour, Mansy, Ahmad, Maurice, Hany, Nabil, Sherif, Shaaban, Mahmoud, Flores, Ana Camila, Poksi, Anne, Knuuti, Juhani, Kokkonen, Velipekka, Larikka, Martti, Uusitalo, Valtteri, Bailly, Matthieu, Burg, Samuel, Deux, Jean-François, Habouzit, Vincent, Hyafil, Fabien, Lairez, Olivier, Proffit, Franck, Regaieg, Hamza, Sarda-Mantel, Laure, Tacher, Vania, Schneider, Roman P., Ayetey, Harold, Angelidis, George, Archontaki, Aikaterini, Chatziioannou, Sofia, Datseris, Ioannis, Fragkaki, Christina, Georgoulias, Panagiotis, Koukouraki, Sophia, Koutelou, Maria, Kyrozi, Eleni, Repasos, Evangelos, Stavrou, Petros, Valsamaki, Pipitsa, Gonzalez, Carla, Gutierrez, Goleat, Maldonado, Alejandro, Buga, Klara, Garai, Ildiko, Maurovich-Horvat, Pál, Schmidt, Erzsébet, Szilveszter, Balint, Várady, Edit, Banthia, Nilesh, Bhagat, Jinendra Kumar, Bhargava, Rishi, Bhat, Vivek, Choudhury, Partha, Chowdekar, Vijay Sai, Irodi, Aparna, Jain, Shashank, Joseph, Elizabeth, Kumar, Sukriti, Girijanandan Mahapatra, Prof Dr, Mitra, Deepanjan, Mittal, Bhagwant Rai, Ozair, Ahmad, Patel, Chetan, Patel, Tapan, Patel, Ravi, Patel, Shivani, Saxena, Sudhir, Sengupta, Shantanu, Singh, Santosh, Singh, Bhanupriya, Sood, Ashwani, Verma, Atul, Affandi, Erwin, Alam, Padma Savenadia, Edison, Edison, Gunawan, Gani, Hapkido, Habusari, Hidayat, Basuki, Huda, Aulia, Mukti, Anggoro Praja, Prawiro, Djoko, Soeriadi, Erwin Affandi, Syawaluddin, Hilman, Albadr, Amjed, Assadi, Majid, Emami, Farshad, Houshmand, Golnaz, Maleki, Majid, Rostami, Maryam Tajik, Zakavi, Seyed Rasoul, Zaid, Eed Abu, Agranovich, Svetlana, Arnson, Yoav, Bar-Shalom, Rachel, Frenkel, Alex, Knafo, Galit, Lugassi, Rachel, Maor Moalem, Israel Shlomo, Mor, Maya, Muskal, Noam, Ranser, Sara, Shalev, Aryeh, Albano, Domenico, Alongi, Pierpaolo, Arnone, Gaspare, Bagatin, Elisa, Baldari, Sergio, Bauckneht, Matteo, Bertelli, Paolo, Bianco, Francesco, Bonfiglioli, Rachele, Boni, Roberto, Bruno, Andrea, Bruno, Isabella, Busnardo, Elena, Califaretti, Elena, Camoni, Luca, Carnevale, Aldo, Casoni, Roberta, Cavallo, Armando Ugo, Cavenaghi, Giorgio, Chierichetti, Franca, Chiocchi, Marcello, Cittanti, Corrado, Colletta, Mauro, Conti, Umberto, Cossu, Alberto, Cuocolo, Alberto, Cuzzocrea, Marco, De Rimini, Maria Luisa, De Vincentis, Giuseppe, Del Giudice, Eleonora, Del Torto, Alberico, Della Tommasina, Veronica, Durmo, Rexhep, Erba, Paola Anna, Evangelista, Laura, Faletti, Riccardo, Faragasso, Evelina, Farsad, Mohsen, Ferro, Paola, Florimonte, Luigia, Frantellizzi, Viviana, Fringuelli, Fabio Massimo, Gatti, Marco, Gaudiano, Angela, Gimelli, Alessia, Giubbini, Raffaele, Giuffrida, Francesca, Ialuna, Salvatore, Laudicella, Riccardo, Leccisotti, Lucia, Leva, Lucia, Liga, Riccardo, Liguori, Carlo, Longo, Giampiero, Maffione, Margherita, Mancini, Maria Elisabetta, Marcassa, Claudio, Milan, Elisa, Nardi, Barbara, Pacella, Sara, Pepe, Giovanna, Pontone, Gianluca, Pulizzi, Sabina, Quartuccio, Natale, Rampin, Lucia, Ricci, Fabrizio, Rossini, Pierluigi, Rubini, Giuseppe, Russo, Vincenzo, Sacchetti, Gian Mauro, Sambuceti, Gianmario, Scarano, Massimo, Sciagrà, Roberto, Sperandio, Massimiliano, Stefanelli, Antonella, Ventroni, Guido, Zoboli, Stefania, Baugh, Dainia, Chambers, Duane, Madu, Ernest, Nunura, Felix, Asano, Hiroshi, Chimura, Chimura Misato, Fujimoto, Shinichiro, Fujisue, Koichiro, Fukunaga, Tomohisa, Fukushima, Yoshimitsu, Fukuyama, Kae, Hashimoto, Jun, Ichikawa, Yasutaka, Iguchi, Nobuo, Imai, Masamichi, Inaki, Anri, Ishimura, Hayato, Isobe, Satoshi, Kadokami, Toshiaki, Kato, Takao, Kumita, Shinichiro, Maruno, Hirotaka, Mataki, Hiroyuki, Miyagawa, Masao, Morimoto, Ryota, Moroi, Masao, Nagamachi, Shigeki, Nakajima, Kenichi, Nakata, Tomoaki, Nakazato, Ryo, Nanasato, Mamoru, Naya, Masanao, Norikane, Takashi, Ohta, Yasutoshi, Okayama, Satoshi, Okizaki, Atsutaka, Otomi, Yoichi, Otsuka, Hideki, Saito, Masaki, Sakata, Sakata Yasushi, Sarai, Masayoshi, Sato, Daisuke, Shiraishi, Shinya, Suwa, Yoshinobu, Takanami, Kentaro, Takehana, Kazuya, Taki, Junichi, Tamaki, Nagara, Taniguchi, Yasuyo, Teragawa, Hiroki, Tomizawa, Nobuo, Tsujita, Kenichi, Umeji, Kyoko, Wakabayashi, Yasushi, Yamada, Shinichiro, Yamazaki, Shinya, Yoneyama, Tatsuya, Rawashdeh, Mohammad, Batyrkhanov, Daultai, Makhdomi, Khalid, Ombati, Kevin, Alkandari, Faridah, Garashi, Masoud, Coie, Tchoyoson Lim, Rajvong, Sonexay, Kalinin, Artem, Kalnina, Marika, Haidar, Mohamad, Komiagiene, Renata, Kviecinskiene, Giedre, Mataciunas, Mindaugas, Vajauskas, Donatas, Picard, Christian, Karim, Noor Khairiah A., Reichmuth, Luise, Samuel, Anthony, Allarakha, Mohammad Aaftaab, Naojee, Ambedhkar Shantaram, Alexanderson-Rosas, Erick, Barragan, Erika, González-Montecinos, Alejandro Becerril, Cabada, Manuel, Rodriguez, Daniel Calderon, Carvajal-Juarez, Isabel, Cortés, Violeta, Cortés, Filiberto, De La Peña, Erasmo, Gama-Moreno, Manlio, González, Luis, Ramírez, Nelsy Gonzalez, Jiménez-Santos, Moisés, Matos, Luis, Monroy, Edgar, Morelos, Martha, Ornelas, Mario, Ortga Ramirez, Jose Alberto, Preciado-Anaya, Andrés, Preciado-Gutiérrez, Óscar Ulises, Barragan, Adriana Puente, Rosales Uvera, Sandra Graciela, Sandoval, Sigelinda, Tomas, Miguel Santaularia, Sierra-Galan, Lilia M., Siu, Silvia, Vallejo, Enrique, Valles, Mario, Faraggi, Marc, Sereegotov, Erdenechimeg, Ilic, Srdja, Ben-Rais, Nozha, Alaoui, Nadia Ismaili, Taleb, Sara, Pa Myo, Khin Pa, Thu, Phyo Si, Ghimire, Ram Kumar, Rajbanshi, Bijoy, Barneveld, Peter, Glaudemans, Andor, Habets, Jesse, Koopmans, Klaas Pieter, Manders, Jeroen, Pool, Stefan, Scholte, Arthur, Scholtens, Asbjørn, Slart, Riemer, Thimister, Paul, Van Asperen, Erik-Jan, Veltman, Niels, Verschure, Derk, Wagenaar, Nils, Edmond, John, Ellis, Chris, Johnson, Kerryanne, Keenan, Ross, Kueh, Shaw Hua (Anthony), Occleshaw, Christopher, Sasse, Alexander, To, Andrew, Van Pelt, Niels, Young, Calum, Cuadra, Teresa, Roque Vanegas, Hector Bladimir, Soli, Idrissa Adamou, Issoufou, Djibrillou Moussa, Ayodele, Tolulope, Madu, Chibuzo, Onimode, Yetunde, Efros-Monsen, Elen, Forsdahl, Signe Helene, Hildre Dimmen, Jenni-Mari, Jørgensen, Arve, Krohn, Isabel, Løvhaugen, Pål, Bråten, Anders Tjellaug, Al Dhuhli, Humoud, Al Kindi, Faiza, Al-Bulushi, Naeema, Jawa, Zabah, Tag, Naima, Afzal, Muhammad Shehzad, Fatima, Shazia, Younis, Muhammad Numair, Riaz, Musab, Saadullah, Mohammad, Herrera, Yariela, Lenturut-Katal, Dora, Vázquez, Manuel Castillo, Ortellado, José, Akhter, Afroza, Cao, Dianbo, Cheung, Stephen, Dai, Xu, Gong, Lianggeng, Han, Dan, Hou, Yang, Li, Caiying, Li, Tao, Li, Dong, Li, Sijin, Liu, Jinkang, Liu, Hui, Ng, Ming Yen, Sun, Kai, Tang, Gongshun, Wang, Jian, Wang, Ximing, Wang, Zhao-Qian, Wang, Yining, Wang, Yifan, Wu, Jiang, Wu, Zhifang, Xia, Liming, Xiao, Jiangxi, Xu, Lei, Yang, Youyou, Yin, Wu, Yu, Jianqun, Yuan, Li, Zhang, Tong, Zhang, Longjiang, Zhang, Yong-Gao, Zhang, Xiaoli, Zhu, Li, Alfaro, Ana, Abrihan, Paz, Barroso, Asela, Cruz, Eric, Gomez, Marie Rhiamar, Magboo, Vincent Peter, Medina, John Michael, Obaldo, Jerry, Pastrana, Davidson, Pawhay, Christian Michael, Quinon, Alvin, Tang, Jeanelle Margareth, Tecson, Bettina, Uson, Kristine Joy, Uy, Mila, Kostkiewicz, Magdalena, Kunikowska, Jolanta, Bettencourt, Nuno, Cantinho, Guilhermina, Ferreira, Antonio, Syed, Ghulam, Arnous, Samer, Atyani, Said, Byrne, Angela, Gleeson, Tadhg, Kerins, David, Meehan, Conor, Murphy, David, Murphy, Mark, Murray, John, O'Brien, Julie, Bang, Ji-In, Bom, Henry, Cho, Sang-Geon, Hong, Chae Moon, Jang, Su Jin, Jeong, Yong Hyu, Kang, Won Jun, Kim, Ji-Young, Lee, Jaetae, Namgung, Chang Kyeong, So, Young, Won, Kyoung Sook, Majstorov, Venjamin, Vavlukis, Marija, Salobir, Barbara Gužic, Štalc, Monika, Benedek, Theodora, Benedek, Imre, Mititelu, Raluca, Stan, Claudiu Adrian, Ansheles, Alexey, Dariy, Olga, Drozdova, Olga, Gagarina, Nina, Gulyaev, Vsevolod Milyevich, Itskovich, Irina, Karalkin, Anatoly, Kokov, Alexander, Migunova, Ekaterina, Pospelov, Viktor, Ryzhkova, Daria, Saifullina, Guzaliya, Sazonova, Svetlana, Sergienko, Vladimir, Shurupova, Irina, Trifonova, Tatjana, Ussov, Wladimir Yurievich, Vakhromeeva, Margarita, Valiullina, Nailya, Zavadovsky, Konstantin, Zhuravlev, Kirill, Okarvi, Subhani, Saranovic, Dragana Sobic, Keng, Felix, Jason See, Jia Hao, Sekar, Ramkumar, Yew, Min Sen, Vondrak, Andrej, Bejai, Shereen, Bennie, George, Bester, Ria, Engelbrecht, Gerrit, Evbuomwan, Osayande, Gongxeka, Harlem, Vuuren, Magritha Jv, Kaplan, Mitchell, Khushica, Purbhoo, Lakhi, Hoosen, Louw, Lizette, Malan, Nico, Milos, Katarina, Modiselle, Moshe, More, Stuart, Naidoo, Mathava, Scholtz, Leonie, Vangu, Mboyo, Aguadé-Bruix, Santiago, Blanco, Isabel, Cabrera, Antonio, Camarero, Alicia, Casáns-Tormo, Irene, Cuellar-Calabria, Hug, Flotats, Albert, Fuentes Cañamero, Maria Eugenia, García, María Elia, Jimenez-Heffernan, Amelia, Leta, Rubén, Diaz, Javier Lopez, Lumbreras, Luis, Marquez-Cabeza, Juan Javier, Martin, Francisco, Martinez de Alegria, Anxo, Medina, Francisco, Canal, Maria Pedrera, Peiro, Virginia, Pubul-Nuñez, Virginia, Rayo Madrid, Juan Ignacio, Rey, Cristina Rodríguez, Perez, Ricardo Ruano, Ruiz, Joaquín, Hernández, Gertrudis Sabatel, Sevilla, Ana, Zeidán, Nahla, Nanayakkara, Damayanthi, Udugama, Chandraguptha, Simonsson, Magnus, Alkadhi, Hatem, Buechel, Ronny Ralf, Burger, Peter, Ceriani, Luca, De Boeck, Bart, Gräni, Christoph, Juillet de Saint Lager Lucas, Alix, Kamani, Christel H., Kawel-Boehm, Nadine, Manka, Robert, Prior, John O., Rominger, Axel, Vallée, Jean-Paul, Khiewvan, Benjapa, Premprabha, Teerapon, Thientunyakit, Tanyaluck, Sellem, Ali, Kir, Kemal Metin, Sayman, Haluk, Sebikali, Mugisha Julius, Muyinda, Zerida, Kmetyuk, Yaroslav, Korol, Pavlo, Mykhalchenko, Olena, Pliatsek, Volodymyr, Satyr, Maryna, Albalooshi, Batool, Ahmed Hassan, Mohamed Ismail, Anderson, Jill, Bedi, Punit, Biggans, Thomas, Bularga, Anda, Bull, Russell, Burgul, Rajesh, Carpenter, John-Paul, Coles, Duncan, Cusack, David, Deshpande, Aparna, Dougan, John, Fairbairn, Timothy, Farrugia, Alexia, Gopalan, Deepa, Gummow, Alistair, Ramkumar, Prasad Guntur, Hamilton, Mark, Harbinson, Mark, Hartley, Thomas, Hudson, Benjamin, Joshi, Nikhil, Kay, Michael, Kelion, Andrew, Khokhar, Azhar, Kitt, Jamie, Lee, Ken, Low, Chen, Mak, Sze Mun, Marousa, Ntouskou, Martin, Jon, Mcalindon, Elisa, Menezes, Leon, Morgan-Hughes, Gareth, Moss, Alastair, Murray, Anthony, Nicol, Edward, Patel, Dilip, Peebles, Charles, Pugliese, Francesca, Luis Rodrigues, Jonathan Carl, Rofe, Christopher, Sabharwal, Nikant, Schofield, Rebecca, Semple, Thomas, Sharma, Naveen, Strouhal, Peter, Subedi, Deepak, Topping, William, Tweed, Katharine, Weir-Mccall, Jonathan, Abbara, Suhny, Abbasi, Taimur, Abbott, Brian, Abohashem, Shady, Abramson, Sandra, Al-Abboud, Tarek, Al-Mallah, Mouaz, Almousalli, Omar, Ananthasubramaniam, Karthikeyan, Kumar, Mohan Ashok, Askew, Jeffrey, Attanasio, Lea, Balmer-Swain, Mallory, Bayer, Richard R., Bernheim, Adam, Bhatti, Sabha, Bieging, Erik, Blankstein, Ron, Bloom, Stephen, Blue, Sean, Bluemke, David, Borges, Andressa, Branch, Kelley, Bravo, Paco, Brothers, Jessica, Budoff, Matthew, Bullock-Palmer, Renée, Burandt, Angela, Burke, Floyd W., Bush, Kelvin, Candela, Candace, Capasso, Elizabeth, Cavalcante, Joao, Chang, Donald, Chatterjee, Saurav, Chatzizisis, Yiannis, Cheezum, Michael, Chen, Tiffany, Chen, Jennifer, Chen, Marcus, Clarcq, James, Cordero, Ayreen, Crim, Matthew, Danciu, Sorin, Decter, Bruce, Dhruva, Nimish, Doherty, Neil, Doukky, Rami, Dunbar, Anjori, Duvall, William, Edwards, Rachael, Esquitin, Kerry, Farah, Husam, Fentanes, Emilio, Ferencik, Maros, Fisher, Daniel, Fitzpatrick, Daniel, Foster, Cameron, Fuisz, Tony, Gannon, Michael, Gastner, Lori, Gerson, Myron, Ghoshhajra, Brian, Goldberg, Alan, Goldner, Brian, Gonzalez, Jorge, Gore, Rosco, Gracia-López, Sandra, Hage, Fadi, Haider, Agha, Haider, Sofia, Hamirani, Yasmin, Hassen, Karen, Hatfield, Mallory, Hawkins, Carolyn, Hawthorne, Katie, Heath, Nicholas, Hendel, Robert, Hernandez, Phillip, Hill, Gregory, Horgan, Stephen, Huffman, Jeff, Hurwitz, Lynne, Iskandrian, Ami, Janardhanan, Rajesh, Jellis, Christine, Jerome, Scott, Kalra, Dinesh, Kaviratne, Summanther, Kay, Fernando, Kelly, Faith, Khalique, Omar, Kinkhabwala, Mona, Iii, George Kinzfogl, Kircher, Jacqueline, Kirkbride, Rachael, Kontos, Michael, Kottam, Anupama, Krepp, Joseph, Layer, Jay, Lee, Steven H., Leppo, Jeffrey, Lesser, John, Leung, Steve, Lewin, Howard, Litmanovich, Diana, Liu, Yiyan, Magurany, Kathleen, Markowitz, Jeremy, Marn, Amanda, Matis, Stephen E., Mckenna, Michael, Mcrae, Tony, Mendoza, Fernando, Merhige, Michael, Min, David, Moffitt, Chanan, Moncher, Karen, Moore, Warren, Morayati, Shamil, Morris, Michael, Mossa-Basha, Mahmud, Mrsic, Zorana, Murthy, Venkatesh, Nagpal, Prashant, Napier, Kyle, Nelson, Katarina, Nijjar, Prabhjot, Osman, Medhat, Passen, Edward, Patel, Amit, Patil, Pravin, Paul, Ryan, Phillips, Lawrence, Polsani, Venkateshwar, Poludasu, Rajaram, Pomerantz, Brian, Porter, Thomas, Prentice, Ryan, Pursnani, Amit, Rabbat, Mark, Ramamurti, Suresh, Rich, Florence, Luna, Hiram Rivera, Robinson, Austin, Robles, Kim, Rodríguez, Cesar, Rorie, Mark, Rumberger, John, Russell, Raymond, Sabra, Philip, Sadler, Diego, Schemmer, Mary, Schoepf, U. Joseph, Shah, Samir, Shah, Nishant, Shanbhag, Sujata, Sharma, Gaurav, Shayani, Steven, Shirani, Jamshid, Shivaram, Pushpa, Sigman, Steven, Simon, Mitch, Slim, Ahmad, Smith, David, Smith, Alexandra, Soman, Prem, Sood, Aditya, Srichai-Parsia, Monvadi Barbara, Streeter, James, T, Albert, Tawakol, Ahmed, Thomas, Dustin, Thompson, Randall, Torbet, Tara, Trinidad, Desiree, Ullery, Shawn, Unzek, Samuel, Uretsky, Seth, Vallurupalli, Srikanth, Verma, Vikas, Waller, Alfonso, Wang, Ellen, Ward, Parker, Weissman, Gaby, Wesbey, George, White, Kelly, Winchester, David, Wolinsky, David, Yost, Sandra, Zgaljardic, Michael, Alonso, Omar, Beretta, Mario, Ferrando, Rodolfo, Kapitan, Miguel, Mut, Fernando, Djuraev, Omoa, Rozikhodjaeva, Gulnora, Le Ngoc, Ha, Mai, Son Hong, and Nguyen, Xuan Canh
Abstract: Background: The coronavirus disease-2019 (COVID-19) pandemic significantly affected management of cardiovascular disease around the world. The effect of the pandemic on volume of cardiovascular diagnostic procedures is not known. Objectives: This study sought to evaluate the effects of the early phase of the COVID-19 pandemic on cardiovascular diagnostic procedures and safety practices in Asia. Methods: The International Atomic Energy Agency conducted a worldwide survey to assess changes in cardiovascular procedure volume and safety practices caused by COVID-19. Testing volumes were reported for March 2020 and April 2020 and were compared to those from March 2019. Data from 180 centers across 33 Asian countries were grouped into 4 subregions for comparison. Results: Procedure volumes decreased by 47% from March 2019 to March 2020, showing recovery from March 2020 to April 2020 in Eastern Asia, particularly in China. The majority of centers cancelled outpatient activities and increased time per study. Practice changes included implementing physical distancing and restricting visitors. Although COVID testing was not commonly performed, it was conducted in one-third of facilities in Eastern Asia. The most severe reductions in procedure volumes were observed in lower-income countries, where volumes decreased 81% from March 2019 to April 2020. Conclusions: The COVID-19 pandemic in Asia caused significant reductions in cardiovascular diagnostic procedures, particularly in low-income countries. Further studies on effects of COVID-19 on cardiovascular outcomes and changes in care delivery are warranted.
Published: 2021

43. The Wave Origins of Longitudinal Structures in ExoMars Trace Gas Orbiter (TGO) Aerobraking Densities

Author: National Aeronautics and Space Administration (US), Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), European Commission, Forbes, Jeffrey M., Bruinsma, Sean, Zhang, Xiaoli, Forget, François, Marty, Jean-Charles, Millour, Ehouarn, González-Galindo, F., National Aeronautics and Space Administration (US), Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), European Commission, Forbes, Jeffrey M., Bruinsma, Sean, Zhang, Xiaoli, Forget, François, Marty, Jean-Charles, Millour, Ehouarn, and González-Galindo, F.
Abstract: The nature and origins of longitudinal density structures in Mars’ thermosphere between 100 and 120 km altitude, and −30° and −75° latitude around winter solstice (Ls = 70–122°), as measured by the accelerometer on the ExoMars Trace Gas Orbiter (TGO) Mission, are investigated. The methodology consists of deducing the responsible waves by comparing the observed longitude versus local time phase progressions of the structures with those of probable candidate waves in the Mars Climate Database (MCD) climatology. The observed wave-1, wave-2, and wave-3 structures are interpreted as originating mainly from SPW1; (SPW2, S0, DE1); and (SPW3, DE2), respectively, where SPWm denotes a stationary planetary wave with zonal wavenumber s = m, S0 is the zonally symmetric semidiurnal tide, and DE1(DE2) are the eastward-propagating diurnal tides with s = −1(−2). All of these waves exist in the MCD with amplitudes as large as those observed, although not wholly in the narrow height-latitude regime accessed by TGO. This disparity between the MCD and TGO amplitude structures is hypothesized to result from the extreme intrusion of the polar-region eastward winter jet into the thermosphere in the MCD. The winter polar jet blocks poleward expansion of DE1 and DE2 beyond −30° latitude, and also impacts the structures of SPW2, S0 and SPW3 that arise from in situ nonlinear interaction between DE1 and DE2, respectively, with the diurnal migrating tide (DW1). © 2021. American Geophysical Union. All Rights Reserved.
Published: 2021

44. The Help of HPV Integration Testing to Avoid the Misdiagnosis of a Patient with Stage Ia1 Cervical Cancer: A Case Report and Literature Review

Author: Li,Jialu, Zhang,Xiaoli, Wang,Pengpeng, Li,Weiping, Li,Jialu, Zhang,Xiaoli, Wang,Pengpeng, and Li,Weiping
Abstract: Jialu Li,1 Xiaoli Zhang,2 Pengpeng Wang,3 Weiping Li4 1Department of Obstetrics and Gynecology, The Second School of Clinical Medicine, Southern Medical University, Hainan Hospital of PLA General Hospital, Hainan, Peopleâs Republic of China; 2Department of Obstetrics and Gynecology, Three Medical Center, Chinese PLA General Hospital, Beijing, Peopleâs Republic of China; 3MyGenostics Inc., Beijing, Peopleâs Republic of China; 4Department of Obstetrics and Gynecology, Seven Medical Center, Chinese PLA General Hospital, Beijing, Peopleâs Republic of ChinaCorrespondence: Weiping LiDepartment of Obstetrics and Gynecology, Seven Medical Center, Chinese PLA General Hospital, Beijing, Peopleâs Republic of ChinaEmail liweiping258@sina.comAbstract: Screening and prevention in the early stage of cervical cancer could improve the 5-year survival rate of cervical cancer by up to 90%. The occurrence rate of human papillomavirus (HPV) integration has gradually increased with the development of cervical lesions. Here, we report the case of a 43-year-old woman diagnosed with chronic cervicitis based on cervical biopsy results. After medical consultation, surgery was recommended to the patient considering her 64 HPV integration sites and other biochemical and clinical test results. The pathology result of the conical biopsy obtained during operation confirmed that both her cervix and the glands had high-grade squamous intraepithelial lesion or cervical intraepithelial neoplasia III (HSIL/CIN III). The patient underwent uterectomy and bilateral salpingectomy and was discharged thereafter. The diagnosis of the patient was revised to stage Ia1 cervical cancer. The number of HPV integration sites is suggested to be an auxiliary indicator in the early screening of cervical cancer for predicting high-grade CIN and invasive cervical cancer.Keywords: HPV DNA, DNA methylation detection, cervical cancer, precancerous lesion of cervical cancer
Published: 2021

45. Machine learning based in situ quality estimation by molten pool condition-quality relations modeling using experimental data

Author: Jamnikar, Noopur, Liu, Sen, Brice, Craig, Zhang, Xiaoli, Jamnikar, Noopur, Liu, Sen, Brice, Craig, and Zhang, Xiaoli
Abstract: The advancement of machine learning promises the ability to accelerate the adoption of new processes and property designs for metal additive manufacturing. The molten pool geometry and molten pool temperature are the significant indicators for the final part's geometric shape and microstructural properties for the Wire-feed laser direct energy deposition process. Thus, the molten pool condition-property relations are of preliminary importance for in situ quality assurance. To enable in situ quality monitoring of bead geometry and characterization properties, we need to continuously monitor the sensor's data for molten pool dimensions and temperature for the Wire-feed laser additive manufacturing (WLAM) system. We first develop a machine learning convolutional neural network (CNN) model for establishing the correlations from the measurable molten pool image and temperature data directly to the geometric shape and microstructural properties. The multi-modality network receives both the camera image and temperature measurement as inputs, yielding the corresponding characterization properties of the final build part (e.g., fusion zone depth, alpha lath thickness). The performance of the CNN model is compared with the regression model as a baseline. The developed models enable molten pool condition-quality relations mapping for building quantitative and collaborative in situ quality estimation and assurance framework., Comment: 23 pages. arXiv admin note: substantial text overlap with arXiv:2103.11588
Published: 2021

46. Comprehensive process-molten pool relations modeling using CNN for wire-feed laser additive manufacturing

Author: Jamnikar, Noopur, Liu, Sen, Brice, Craig, Zhang, Xiaoli, Jamnikar, Noopur, Liu, Sen, Brice, Craig, and Zhang, Xiaoli
Abstract: Wire-feed laser additive manufacturing (WLAM) is gaining wide interest due to its high level of automation, high deposition rates, and good quality of printed parts. In-process monitoring and feedback controls that would reduce the uncertainty in the quality of the material are in the early stages of development. Machine learning promises the ability to accelerate the adoption of new processes and property design in additive manufacturing by making process-structure-property connections between process setting inputs and material quality outcomes. The molten pool dimensional information and temperature are the indicators for achieving the high quality of the build, which can be directly controlled by processing parameters. For the purpose of in situ quality control, the process parameters should be controlled in real-time based on sensed information from the process, in particular the molten pool. Thus, the molten pool-process relations are of preliminary importance. This paper analyzes experimentally collected in situ sensing data from the molten pool under a set of controlled process parameters in a WLAM system. The variations in the steady-state and transient state of the molten pool are presented with respect to the change of independent process parameters. A multi-modality convolutional neural network (CNN) architecture is proposed for predicting the control parameter directly from the measurable molten pool sensor data for achieving desired geometric and microstructural properties. Dropout and regularization are applied to the CNN architecture to avoid the problem of overfitting. The results highlighted that the multi-modal CNN, which receives temperature profile as an external feature to the features extracted from the image data, has improved prediction performance compared to the image-based uni-modality CNN approach., Comment: 23 pages
Published: 2021

47. Wide Aspect Ratio Matching for Robust Face Detection

Author: Luo, Shi, Li, Xiongfei, Zhang, Xiaoli, Luo, Shi, Li, Xiongfei, and Zhang, Xiaoli
Abstract: Recently, anchor-based methods have achieved great progress in face detection. Once anchor design and anchor matching strategy determined, plenty of positive anchors will be sampled. However, faces with extreme aspect ratio always fail to be sampled according to standard anchor matching strategy. In fact, the max IoUs between anchors and extreme aspect ratio faces are still lower than fixed sampling threshold. In this paper, we firstly explore the factors that affect the max IoU of each face in theory. Then, anchor matching simulation is performed to evaluate the sampling range of face aspect ratio. Besides, we propose a Wide Aspect Ratio Matching (WARM) strategy to collect more representative positive anchors from ground-truth faces across a wide range of aspect ratio. Finally, we present a novel feature enhancement module, named Receptive Field Diversity (RFD) module, to provide diverse receptive field corresponding to different aspect ratios. Extensive experiments show that our method can help detectors better capture extreme aspect ratio faces and achieve promising detection performance on challenging face detection benchmarks, including WIDER FACE and FDDB datasets., Comment: 18 pages, 8 figures, 3 tables
Published: 2021

48. Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis

Author: Li, Fengting, Liu, Xuankai, Zhang, Xiaoli, Li, Qi, Sun, Kun, Li, Kang, Li, Fengting, Liu, Xuankai, Zhang, Xiaoli, Li, Qi, Sun, Kun, and Li, Kang
Abstract: Deep neural networks (DNNs) have been applied in a wide range of applications,e.g.,face recognition and image classification; however,they are vulnerable to adversarial examples. By adding a small amount of imperceptible perturbations,an attacker can easily manipulate the outputs of a DNN. Particularly,the localized adversarial examples only perturb a small and contiguous region of the target object,so that they are robust and effective in both digital and physical worlds. Although the localized adversarial examples have more severe real-world impacts than traditional pixel attacks,they have not been well addressed in the literature. In this paper,we propose a generic defense system called TaintRadar to accurately detect localized adversarial examples via analyzing critical regions that have been manipulated by attackers. The main idea is that when removing critical regions from input images,the ranking changes of adversarial labels will be larger than those of benign labels. Compared with existing defense solutions,TaintRadar can effectively capture sophisticated localized partial attacks, e.g.,the eye-glasses attack,while not requiring additional training or fine-tuning of the original model's structure. Comprehensive experiments have been conducted in both digital and physical worlds to verify the effectiveness and robustness of our defense.
Published: 2021

49. A Physics-Informed Machine Learning Model for Porosity Analysis in Laser Powder Bed Fusion Additive Manufacturing

Author: Liu, Rui, Liu, Sen, Zhang, Xiaoli, Liu, Rui, Liu, Sen, and Zhang, Xiaoli
Abstract: To control part quality, it is critical to analyze pore generation mechanisms, laying theoretical foundation for future porosity control. Current porosity analysis models use machine setting parameters, such as laser angle and part pose. However, these setting-based models are machine dependent, hence they often do not transfer to analysis of porosity for a different machine. To address the first problem, a physics-informed, data-driven model (PIM), which instead of directly using machine setting parameters to predict porosity levels of printed parts, it first interprets machine settings into physical effects, such as laser energy density and laser radiation pressure. Then, these physical, machine independent effects are used to predict porosity levels according to pass, flag, fail categories instead of focusing on quantitative pore size prediction. With six learning methods evaluation, PIM proved to achieve good performances with prediction error of 10$\sim$26%. Finally, pore-encouraging influence and pore-suppressing influence were analyzed for quality analysis., Comment: 14 pages
Published: 2021

50. Research Progress on Regulating LncRNAs of Hepatocellular Carcinoma Stem Cells

Author: Zhang,Xiaoli, Zhu,Ying, Zhang,Xiaoli, and Zhu,Ying
Abstract: Xiaoli Zhang, Ying Zhu Liver Disease Center of Integrated Traditional Chinese and Western Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, People’s Republic of ChinaCorrespondence: Ying Zhu Email zhuyingsh52@126.comAbstract: Hepatocellular carcinoma (HCC) is one of the most prevalent malignancies around the world. The self-renewal, proliferation, differentiation, and tumorigenic potential of liver cancer stem cells (LCSCs) may account for the high recurrence rate and the refractory feature of HCC. Despite extensive researches, the underlying regulatory mechanism of LCSCs has not been fully disclosed. Long nonprotein coding RNAs (lncRNAs) may exert an essential role in regulating various biological functions of LCSCs, such as maintaining the stemness of cancer stem cells (CSCs) and promoting tumor development. Therefore, it is highly critical to determine which lncRNAs can control LCSCs functions and understand how LCSCs are regulated by lncRNAs. Herein, we summarized lncRNAs and the main signaling pathways involved in the regulation of LCSCs found in recent years. Moreover, we shed light on the existence of the network system of lncRNAs and LCSCs, which may provide valuable clues on targeting LCSCs.Keywords: hepatocellular carcinoma, HCC, liver cancer stem cells, LCSCs, long nonprotein coding RNAs, lncRNAs, signaling pathways, network
Published: 2021

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