Original Research | Open Access
Vol.9 (2023) | Issue-3 | Page No: 107-121
Xiumin Zhang1,2#, Xinyue Lin1,3#, Siman Su1,3#, Wei He3, Yuying Huang4, Chengkuan Zhao3, Xiaoshan Chen3, Jialin Zhong3, Chong Liu3, Wang Chen3, Chengcheng Xu3, Ping Yang5, Man Zhang5, Yanli Lei5*, Shuyao Zhang1,3*
Affiliations + Expand
1.Department of Pharmacology, Shantou University Medical College, Shantou, Guangdong, China
2. Department of Pharmacology, Shantou Central Hospital, Shantou, Guangdong, China
3. Department of Pharmacy, Guangzhou Red Cross Hospital of Jinan University, Guangzhou, Guangdong, China
4. School of Pharmaceutical Sciences, Guizhou Medical University, Guiyang, Guizhou, China
5. Department of Pharmacy, The 2nd People’s hospital of Bijie, Bijie, Guizhou, China
# These authors contributed equally to this work.
* Corresponding Author
Address for correspondence:
Prof. Shuyao Zhang, Department of Pharmacy, Guangzhou Red Cross Hospital of Jinan University, No. 396 Tongfuzhong Road, Haizhu District, Guangzhou 510220, Guangdong, China. E-mail: firstname.lastname@example.org
Prof. Yanli Lei, Department of Pharmacy, The 2nd People’s hospital of Bijie, Beside Caohai Avenue (Tracey Community, Shixi Office), Qixingguan District, Bijie 551700, Guizhou, China. E-mail: email@example.com
Important Dates + Expand
Date of Submission: 17-Aug-2023
Date of Acceptance: 25-Sep-2023
Date of Publication: 09-Oct-2023
OBJECTIVE: To explore the adverse reaction (ADR) signals of five anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs), crizotinib, ceritinib, alectinib, brigatinib, and lorlatinib, based on the FDA adverse event reporting system (FAERS) to provide a reference for safe clinical medication.
METHODS: The ADR reports of the five ALK-TKIs collected in the FAERS database from their inception on 31 December 2022 were analyzed using the proportional reporting ratio (PRR) and Reporting Odds Ratio (ROR) methods, and valid signals were systematically categorized using the thesaurus of the International Medical Dictionary of Terms (MedDRA).
RESULTS: Multiple organs and systems were involved in the ADRs of five kinds of ALK-TKIs, including 324 signals involved in 9754 reports of crizotinib, 208 signals involved in 2195 reports of ceritinib, 207 signals affected in 4353 reports of alectinib, 178 signals involved in 2213 reports of brigatinib and 202 signals involved in 2383 reports of lorlatinib. Forty-seven signals were not listed in the specification and label statement.
CONCLUSION: There are both commonalities and variations among the ADRs of the five types of ALK-TKIs. To ensure patient safety, individual monitoring should be performed according to the patients' condition.
Keywords: Anaplastic lymphoma kinase; Tyrosine kinase inhibitors; Adverse drug reactions; FAERS database; Singal mining; Proportional imbalance method
The anaplastic lymphoma kinase (ALK) gene is one of the common driver genes in patients with non-small cell lung cancer (NSCLC), and 3% to 7% of NSCLC patients carry an ALK fusion, with the EML4-ALK fusion subtype being the most common. The EML4-ALK fusion subtype is the most common., ALK fusion is the second most important pathway in NSCLC after EGFR mutation. For ALK fusion-positive patients with advanced NSCLC, both national and international guidelines recommend ALK tyrosine kinase inhibitor (TKI)-targeted therapy.
Six ALK-TKIs are currently approved for marketing, namely, the first-generation ALK-TKI crizotinib, the second-generation ALK-TKIs ceritinib, alectinib, buxtinib, and enzacitinib, and the third-generation ALK-TKI lorlatinib. The efficacy of ALK-TKIs in patients with advanced ALK-positive NSCLC is remarkable, and the rational sequential use of ALK-TKIs can enable long-term survival in most patients. With the extensive and long-term clinical use of ALK-TKIs, adverse drug reactions (ADRs) have gradually been brought to light. The U.S. Food and Drug Administration Adverse Event Reporting System (FAERS), a spontaneous reporting system for recording post-marketing adverse events, is widely used for ADR signal mining studies due to its large amount of data and open access to the public. In this study, based on the FAERS database, we examined and analyzed the ADR information of five foreign-marketed ALK-TKIs, namely, crizotinib, ceritinib, alectinib, buxtitinib, and loratinib, with the aim of providing references for the rational use of medicines in clinics.
Sources and searches
Data for this study were obtained from the FAERS database, and all ADR reports for crizotinib, ceritinib, alectinib, braglatinib, and lorlatinib (Crizotinib 26 August 2011, Ceritinib 29 April 2014, Aleitinib 11 December 2015, Bugatinib 28 April 2017, Loratinib 2 November 2018) since their launch until 31 December 2022 were obtained from the OpenVigil 2.1 public data platform. The drug search names were "crizotinib", "ceritinib", "alectinib", "brigatinib", and lorlatinib". The corresponding "Raw_data" and "Frequentist_methods" data files were downloaded and encoded in "csv" format. The corresponding files "Raw_data" and "Frequentist_methods" were downloaded and saved in "csv" format.
Data cleansing and processing
Nontarget drugs, duplicates, and unidentifiable and blank ADRs were excluded from the reports, and data cleaning was performed to obtain ADR data for target drugs. The screened reports were coded using the Preferred Term (PT) in MedDRA 25.0 and grouped into their respective System Organ Class (SOC) as per MedDRA 25.0. MedDRA is divided into five tiers: system organ class, high-level group terms, high level terms, preferred terms, and lowest level terms.
ADR Signal Mining
The ADR signals of the five ALK-TKls were analyzed using the proportional reporting ratio (PRR) and Reporting Odds Ratio (ROR) methods in the proportional imbalance method. The calculation of the PRR and ROR was based on the proportional imbalance measurement method four-cell table [Table 1], and the specific algorithms are shown in Table 2. ADRs that met the signal requirements of both PRR and ROR were included in the present study. The higher the PRR and ROR values are, the higher the signal strength of the ADR and the the greater the association between the target drug and the target ADR in this study.
Basics of ADR Reporting
After cleaning and screening, a total of 9754 ADR reports of crizotinib, 2195 reports of ceritinib, 4353 reports of alectinib, 2213 reports of buxtitinib, and 2383 reports of loratinib were included in the present study, and the ADR reports of the five ALK-TKIs were predominantly from female patients, with the main age of the patients ranging from 50 to 75 years old, and the sources of the reports were from Europe and the United States. The role of ALK-TKI in the ADRs was most common in the "main suspected drug" category. The role of ALK-TKIs in ADRs was most frequently reported as the "main suspect", as shown in Table 3 and Figure 1.
Organ systems involved in ADR signaling
The ALK-TKI-associated ADR signals were counted and categorized, and each PT was attributed to one master SOC. Crizotinib received 324 signals, involving 24 systems; ceritinib received 208 signals, involving 20 systems; alectinib received 207 signals, involving 24 systems; buxtitinib received 178 signals, involving 23 systems; and loratinib received 202 signals, involving 21 systems. The ADR signals from ALK-TKIs were mainly focused on various types of investigated, including benign, malignant and tumors of unknown nature; respiratory and mediastinal diseases; various neurological diseases; gastrointestinal diseases; systemic diseases and various administration site reactions, the main SOCs involved in the five ALK-TKI-related ADRs were broadly the same, but there were some differences, such as a higher prevalence of loratinib in the psychiatric category and a higher prevalence of crizotinib in eye organ diseases, The detailed SOC distribution is shown in Figure 2.
ADR signal frequency and intensity ranking
A summary of the top 10 ADR signals in terms of frequency and top 10 ADR signals in terms of signal intensity due to the five ALK-TKIs showed that the ADRs with the highest frequency for crizotinib, alectinib, buxtitinib, and lorlatinib were all deaths, as shown in Table 4 and Table 5.
Detection results of overlapping ADRs in the top 50 frequency counts
As ALK-TKI-related ADRs involve a wide range of SOCs and a large number of PTs under each SOC, it is not possible to present the analysis one by one. In this paper, we intend to compare the ADR signals of the top 50 ADRs in the order of frequency count (DE) in five ALK-TKIs (excluding ADRs related to indications and tumour progression) in order to explore the commonalities and characteristics of various ALK-TKI-related ADRs. The top 50 ADRs in terms of frequency were compared with ADRs mentioned in the drug inserts, most of which were mentioned in the drug inserts, and 47 new signals were unearthed, including 5 for crizotinib, 11 for ceritinib, 12 for alectinib, 12 for buxtitinib, and 7 for loratinib in Table 6 (Please locate the Table at the end of the manuscript).
Demographic characteristics of ADR occurrence
In the ADR reports of the five ALK-TKIs included in this study, the sex of the reported patients was predominantly female, except for those whose sex was unknown, which is related to the demographic characteristics of patients with ALK gene rearrangements. Studies have shown that ALK gene rearrangements mostly occur in young and occasional or nonsmoking female patients with adenocarcinoma. The age range of the patients was between 50 and 75 years, which is consistent with the mean age of ALK-positive patients of 63±13 years studied by Mori et al. In terms of the countries from which the reports originated, ADR reports were mainly concentrated in Europe and the United States, while there were relatively few reports in Asia, which may be related to the source of the FAERS database and the countries where ALK-TKIs are marketed.
In addition to gastrointestinal reactions, hepatotoxicity, pulmonary toxicity, cardiotoxicity, and other common adverse effects of targeted therapies, the results of these ADR signals showed that visual toxicity is also a common adverse effect of ALK-TKIs, especially crizotinib, whose ADR frequency ranks in the top 50 signals; impaired visual acuity, blurred vision, light flashes, vitreous mosquitoitis, photophobia, and a few signals are on the list. A phase II clinical trial of crizotinib showed that up to 65% of patients experienced visual disturbances, with photophobia, light flashes, blurred vision, and vitreous mosquitoitis being the main symptoms. Visual disturbances usually occur in the first week of crizotinib treatment, and symptoms tend to occur daily, last up to 1 minute, and usually have little impact on daily activities. The incidence of grade 4 visual field defects with loss of visual acuity is 0.2% in patients treated with crizotinib. Other ALK-TKIs have similar visual toxicity, but the overall incidence is <15%.
Central nervous system (CNS) adverse reactions
Among the top 50 signals related to ADR frequency for the five ALK-TKIs, lorlatinib had the highest number of signals and the highest frequency of neurologically related adverse reactions, including cognitive impairment, memory impairment, peripheral neuropathy, neurological disorders, speech disorders, aphasia, amnesia, carpal tunnel syndrome, cerebral edema, neurotoxicity in all types of neurological disorders, sleep disorders, hallucinations, psychosis in psychiatric categories, visual hallucinations, auditory hallucinations, psychotic disorders, depression, prosopagnosia, affective disorders, and aggression. Studies have shown that NSCLC patients with ALK rearrangements have a higher cumulative risk of developing brain metastases than ALK-negative patients, with cumulative incidence rates of 45.5% and 58.4% over 2 and 3 years, respectively., Loratinib, as a third-generation ALK-TKI, has strong potency to cross the blood‒brain barrier due to the multiple advantages of its small-molecule macrocyclic amide structure.,, The results of the CROWN study showed that for patients with measurable brain metastases at baseline, first-line treatment with lorlatinib resulted in an intracranial objective remission rate (ORR) of 83.3%, compared with 23.3% in the control group, and an intracranial complete remission rate (CR) of 72.2%. In the control group, it was only 7.7%. In patients without brain metastases, first-line treatment with lorlatinib significantly controlled brain metastases, with a 3-year rate of no intracranial progression of 99.1%. Effective control of brain metastases in lung cancer with lorlatinib is accompanied by a number of central nervous system adverse effects. Studies have shown that the incidence of CNS side effects with lorlatinib is 35%, and the median time to first CNS reaction is 1.4 months. CNS reactions mainly manifest as seizures, psychiatric effects, and changes in cognitive function, mood, language, mental status, and sleep status., This suggests that healthcare professionals and family members should pay attention to the patient's mood and behavioral changes.
New adverse reactions
The side effects of the five ALK-TKIs noted in the current study were essentially consistent with those in the specification and report, further confirming the credibility of this study. Hepatotoxicity is a common side effect of ALK-TKIs and is also the main reason for discontinuation of the drug during the course of drug treatment. In addition to the reported increases in transaminases and bilirubin, a new ADR of hepatitis was noted in the top 50 signals of crizotinib, ceritinib, and alectinib in the present study, suggesting that ALK-TKIs can induce hepatitis, which should be considered in clinical practice. TKIs can cause hepatitis, which should be taken seriously in clinical practice. The "photosensitivity reaction" signal of buxtitinib was not included in the specification, but a study showed that photosensitivity reactions occurred in 3.7% of patients receiving buxtitinib, of which 0.7% were grade 3-4. In addition, photosensitivity reactions have been reported in patients treated with ceritinib and alectinib. Patients are advised to protect themselves from sunlight while taking these drugs.
Limitations of this study
Analysis of spontaneous presentation systems is an effective method to identify possible ADR signals, and the FAERS database is one of the largest sources of data available, but there are still some limitations in this study. This study was based on the FAERS spontaneous presentation database, and the data came mainly from Europe and the United States, with fewer reports from Asia and possible racial differences from our population. In addition, FAERS is a spontaneous reporting system, and data may be duplicated, missing or misreported, which may introduce bias in statistical analyses and make it impossible to calculate the frequency of ADRs. In addition, the same report may involve multiple drugs or multiple clinical symptoms, which may not be accurately distinguished in the classification of statistics. This study could not reflect the severity of adverse effects or evaluate the differences in adverse effects between doses of the same drug.
This study investigated the adverse effects of ALK-TKIs in real-world trials using the FAERS pharmacovigilance system. The types of ADRs associated with ALK-TKIs are more numerous and affect a wider range of organ systems. The ADRs of the five drugs have both common features and their own individual characteristics. There is a greater risk of CNS toxicity with lorlatinib and visual toxicity with crizotinib, suggesting that patients should be individually monitored during daily treatment to improve drug safety. This study also revealed 47 new ADR signals from ALK-TKIs. The relevant manufacturing departments should strengthen post-marketing surveillance, improve and update the drug specification in a timely manner, and do a good job in related outreach and education to accompany the safe use of the drugs in the clinic.
FINANCIAL SUPPORT AND SPONSORSHIP
This work was supported by the grants from Shantou Medical and Healthcare Science and Technology Programme Project (Shantou Fu Ke  No.5-56) (to Xiumin Zhang), 2022 Bai Qiu En-Qiu Suo-Pharmacy Scientific Research Capacity Building Project (No.Z04JKM2021005) (to Shuyao Zhang), 2022 Guangdong Province Scientific and Technological Innovation Strategy Special ("Big Special + Task List ") Project (Shantou Ke  124, No.STKJ202209072) (to Shuyao Zhang) and Notice on the Approval of the 2023 "Unveiling and Leading" Project (Bikehe Major Special Project  No.2-2) (to Yanli Lei).
CONFLICTS OF INTEREST
The authors declare no conflicts of interest.
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
Xiumin Zhang, Xinyue Lin and Siman Su contributed to the study’s conception and design. Data collection and analysis were performed by Wei He, Yuying Huang, Chengkuan Zhao, Xiaoshan Chen, Jialin Zhong, Chong Liu, Wang Chen, Chengcheng Xu, Ping Yang and Man Zhang. The first draft of the manuscript was written by Yanli Lei and Shuyao Zhang and all authors commented on previous versions of the manuscript. All authors have read and approved the final manuscript.
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Ana Paula Cleto Marolla1, Jaques Waisberg2, Gabriela Tognini Saba2, Demétrius Eduardo Germini2, Maria Aparecida da Silva Pinhal1
Fengyu Zhu1, Yu Liang1, Demeng Chen2, Yang Li1
Kaijun Huang1, Panagiotis J. Vlachostergios1, Wanhua Yang2, Rajeev L. Balmiki3
Krishnamoorthy Deepalakshmi, Sankaran Mirunalini
Nigel P. Murray1,2, Eduardo Reyes1,3, Nelson Orellana1, Cynthia Fuentealba1, Omar Jacob1
Rana I. Mahmood1,2, Mohammed Aldehaim1,3, Fazal Hussain4, Tusneem A. Elhassan4,
Zubeir A. Khan5, Muhammad A. Memon6
Yeling Ouyang1, Xi Chen2, Chunyun Zhang1, Vichitra Bunyamanop1, Jianfeng Guo3
Jing Qi1, Hongwei Yang2, Xin Wang2, Yanyang Tu1
Shuyao Zhang1*, Muyin Sun2*, Yun Yuan3*, Miaojun Wang4*, Yuqi She1*, Li Zhou5, Congzhu Li5, Chen Chen1, Shengqi Zhang4
Zhen Wang1, Hongwei Yang2, Xin Wang2, Liang Wang3, Yingduan Cheng4, Yongsheng Zhang5, Yanyang Tu1,2
Wenjin Shi1, Ding Weng2,3, Wanting Niu2,3
Juan Carlos Lacal1, Ladislav Andera2
Daniel Otero‑Albiol, Blanca Felipe‑Abrio
José M. Santos‑Pereira1, Sandra Muñoz‑Galván2
Manuel P. Jiménez‑García, Eva M. Verdugo‑Sivianes, Antonio Lucena‑Cacace
Marco Perez, Lola Navas, Amancio Carnero
Reecha A. Parikh, Toral P. Kobawala, Trupti I. Trivedi, Mahnaz M. Kazi, Nandita R. Ghosh
Nadia Hindi1,2, Javier Martin‑Broto1,2
Pengxing Zhang1, Hongwei Yang2, Xin Wang2, Liang Wang3, Yingduan Cheng4, Yongsheng Zhang5, Yanyang Tu1,2
Yi‑Zhou Jiang1, Demeng Chen2
Aaron Yun Chen, Glenn D. Braunstein, Megan S. Anselmo, Jair A. Jaboni, Fernando Troy Viloria, Julie A. Neidich, Xiang Li, Anja Kammesheidt
Binliang Liu, Yalan Yang, Zongbi Yi, Xiuwen Guan, Fei Ma
Pablo Reclusa1, Anna Valentino1, Rafael Sirera1,2, Martin Frederik Dietrich3, Luis Estuardo Raez3, Christian Rolfo1
Martin Frederik Dietrich1, Christian Rolfo2, Pablo Reclusa2, Marco Giallombardo2, Anna Valentino2, Luis E. Raez1
Ting Chen1,2, Rongzhang He1,3, Xinglin Hu1,3,4, Weihao Luo1, Zheng Hu1,3, Jia Li1, Lili Duan1, Yali Xie1,2, Wenna Luo1,2, Tan Tan1,2, Di‑Xian Luo1,2
Poonam Sonawane1, Young A. Choi1, Hetal Pandya2, Denise M. Herpai1, Izabela Fokt3,
Waldemar Priebe3, Waldemar Debinski1
Pei Liang, Michael Gao Jr.
Wenxiu Zhao1, Yvonne Li2, Xun Zhang1
Andrew Fesler1, Hua Liu1, Ning Wu1,2, Fei Liu3, Peixue Ling3, Jingfang Ju1,3
Simona Gurzu1,2,3, Marius Alexandru Beleaua1, Laura Banias2, Ioan Jung1
Liyuan Zhou1,2, Yujun Li1,2, Changchen Hu3, Binquan Wang1,2
Jeremy A. Hengst1,2, Taryn E. Dick1,2, Arati Sharma1, Kenichiro Doi3, Shailaja Hegde4, Su‑Fern Tan5, Laura M. Geffert1,2, Todd E. Fox5, Arun K. Sharma1, Dhimant Desai1, Shantu Amin1, Mark Kester5, Thomas P. Loughran5, Robert F. Paulson4, David F. Claxton6, Hong‑Gang Wang3, Jong K. Yun1,2
Feng Yu1, Bangxing Hong1, Xiao‑Tong Song1,2,3
Yasar Ahmed1, Nemer Osman1, Rizwan Sheikh2, Sarah Picardo1, Geoffrey Watson1
Hatel Rana Moonat, Gangxiong Huang, Pooja Dhupkar, Keri Schadler, Nancy Gordon,
Tongwei Wu, Xiao Yang, Min An, Wenqin Luo, Danxian Cai, Xiaolong Qi
Xiao Liang1, Fang‑Fang Yin1,2, Yilin Liu1, Brian Czito2, Manisha Palta2, Mustafa Bashir3, Jing Cai1,2
Xiaofeng Zhu1, Yu Lei1, Dandan Zheng1, Sicong Li1, Vivek Verma1, Mutian Zhang1, Qinghui Zhang1, Xiaoli Tang2, Jun Lian2, Sha X. Chang2, Haijun Song3, Sumin Zhou1, Charles A. Enke1
Wang Qu, Ma Fei, Binghe Xu
Yanlan Li1,2*, Zheng Hu1*, Yufang Yin3, Rongzhang He1, Jian Hu1, Weihao Luo1, Jia Li1, Gebo Wen2, Li Xiao1, Kai Li1, Duanfang Liao4, Di-Xian Luo1,5
Xiaoshan Xu1, Hongwei Yang2, Xin Wang2, Yanyang Tu1
Lei Zhang1,2, Yawei Zhang2, You Zhang1,2,3, Wendy B. Harris1,2, Fang‑Fang Yin1,2,4, Jing Cai1,4,5, Lei Ren1,2
Yasuka Azuma1,2, Masako Mizuno‑Kamiya3, Eiji Takayama1, Harumi Kawaki1, Toshihiro Inagaki4, Eiichi Chihara2, Yasunori Muramatsu5, Nobuo Kondoh1
Yi‑Rong Xiang, Li Liu
Kazunori Hamamura1, Koichi Furukawa2
Qing‑Hao Zhu1*, Qing‑Chao Shang1*, Zhi‑Hao Hu1*, Yuan Liu2, Bo Li1, Bo Wang1, An‑Hui Wang1
Nadège Dubois1, Sharon Berendsen2, Aurélie Henry1,2, Minh Nguyen1, Vincent Bours1,
Pierre Alain Robe1,2
Toshihiro Inagaki1,2, Masako Mizuno‑Kamiya3, Eiji Takayama1, Harumi Kawaki1, Eiichi Chihara4, Yasunori Muramatsu5, Shinichiro Sumitomo5, Nobuo Kondoh1
Anjali Geethadevi1, Ansul Sharma2, Manish Kumar Sharma3, Deepak Parashar1
Ernest K. Amankwah
Xiaohui Xu1, Zilong Dang2, Taoli Sun3, Shengping Zhang1, Hongyan Zhang1
Javier de la Rosa*, Alejandro Urdiciain*, Juan Jesús Aznar‑Morales, Bárbara Meléndez1,
Juan A. Rey2, Miguel A. Idoate3, Javier S. Castresana
Akiko Sasaki1, Yuko Tsunoda2, Kanji Furuya3, Hideto Oyamada1, Mayumi Tsuji1, Yuko Udaka1, Masahiro Hosonuma1, Haruna Shirako1, Nana Ichimura1, Yuji Kiuchi1
Hui Liu1, Hongwei Yang2, Xin Wang3, Yanyang Tu1
Xiaoshan Xu, Zhen Wang, Nan Liu, Pengxing Zhang, Hui Liu, Jing Qi, Yanyang Tu
Lei Zhang1,2, Fang‑Fang Yin1,2,3, Brittany Moore1,2, Silu Han1,2, Jing Cai1,2,4
Sulin Zeng1,2, Wen H. Shen2, Li Liu1
Yanhua Mou1, Quan Wang1, Bin Li1,2
Raquel Luque Caro, Carmen Sánchez Toro, Lucia Ochoa Vallejo
Shazima Sheereen1, Flora D. Lobo1, Waseemoddin Patel2, Shamama Sheereen3,
Abhishek Singh Nayyar4, Mubeen Khan5
Feiyifan Wang1, Christopher J. Pirozzi2, Xuejun Li1
Jian‑Hong Zhong1,2, Kang Chen1, Bhavesh K. Ahir3, Qi Huang4, Ye Wu4, Cheng‑Cheng Liao1, Rong‑Rong Jia1, Bang‑De Xiang1,2, Le‑Qun Li1,2
Antonio Lucena‑Cacace1,2,3, Amancio Carnero1,2
Michael Zhang, Kelvin Zheng, Muhammad Choudhury, John Phillips, Sensuke Konno
Ajay Sasidharan, Rahul Krishnatry
Leping Liu1, Xuejun Li1,2
Gerard Cathal Millen1, Karen A. Manias1,2, Andrew C. Peet1,2, Jenny K. Adamski1
Ge Ren1,2,3, Yawei Zhang1,2, Lei Ren1,2
Qing Du1, Xiaoying Ji2, Guangjing Yin3, Dengxian Wei3, Pengcheng Lin1, Yongchang Lu1,
Yugui Li3, Qiaohong Yang4, Shizhu Liu5, Jinliang Ku5, Wenbin Guan6, Yuanzhi Lu7
Lei Zhang1, Guoyu Qiu2, Xiaohui Xu2, Yufeng Zhou3, Ruiming Chang4
Aanchal Tandon, Bharadwaj Bordoloi, Safia Siddiqui, Rohit Jaiswal
Dongni Ren1, Xin Wang2, Yanyang Tu1,2
Xipeng Wang1,2, Mitsuteru Yokoyama2, Ping Liu3
Xiaohui Xu1, Guoyu Qiu1, Lupeng Ji2, Ruiping Ma3, Zilong Dang4, Ruling Jia1, Bo Zhao1
Mansoor C. Abdulla
Guru Prasad Sharma1, Anjali Geethadevi2, Jyotsna Mishra3, G. Anupa4, Kapilesh Jadhav5,
K. S. Vikramdeo6, Deepak Parashar2
Ge Zengzheng1, Huang-Sheng Ling2, Ming-Feng Li2, Xu Xiaoyan1, Yao Kai1, Xu Tongzhen3,
Ge Zengyu4, Li Zhou5
Guoyu Qiu1, Xiaohui Xu1, Lupeng Ji2, Ruiping Ma3, Zilong Dang4, Huan Yang5
Steven Lehrer1, Peter H. Rheinstein2
Umair Ali Khan Saddozai1, Qiang Wang1, Xiaoxiao Sun1, Yifang Dang1, JiaJia Lv1,2, Junfang Xin1, Wan Zhu3, Yongqiang Li1, Xinying Ji1, Xiangqian Guo1
Elias Adikwu, Nelson Clemente Ebinyo, Beauty Tokoni Amgbare
Zengzheng Ge1, Xiaoyan Xu1, Zengyu Ge2, Shaopeng Zhou3, Xiulin Li1, Kai Yao1, Lan Deng4
Crystal R. Montgomery‑Goecker1, Andrew A. Martin2, Charles F. Timmons3, Dinesh Rakheja3, Veena Rajaram3, Hung S. Luu3
Elias Adikwu, Nelson Clemente Ebinyo, Loritta Wasini Harris
Ling Wang1,2, Run Wan1,2, Cong Chen1,2, Ruiliang Su1,2, Yumin Li1,2
Priyanka Priyaarshini1, Tapan Kumar Sahoo2
Debasish Mishra1, Gopal Krushna Ray1, Smita Mahapatra2, Pankaj Parida2
Yang Li1, Zhenfan Huang2, Haiping Jiang3
Srigopal Mohanty1, Yumkhaibam Sobita Devi2, Nithin Raj Daniel3, Dulasi Raman Ponna4,
Ph. Madhubala Devi5, Laishram Jaichand Singh2
Xiaohui Xu1, Zilong Dang2, Lei Zhang3, Lingxue Zhuang4, Wutang Jing5, Lupeng Ji6, Guoyu Qiu1
Debasish Mishra1, Dibyajyoti Sahoo1, Smita Mahapatra2, Ashutosh Panigrahi3
Nadeema Rafiq1, Tauseef Nabi2, Sajad Ahmad Dar3, Shahnawaz Rasool4
Palash Kumar Mandal1, Anindya Adhikari2, Subir Biswas3, Amita Giri4, Arnab Gupta5,
Seyyed Majid Bagheri1,2, Davood Javidmehr3, Mohammad Ghaffari1, Ehsan Ghoderti‑Shatori4
Mun Kyoung Kim1, Aidin Iravani2, Matthew K. Topham2,3
Yan Liu1,2,3,4#, Chen Cui1,2,3,4#, Jidong Liu1,2,3,4, Peng Lin1,2,3,4,Kai Liang1,2,3,4, Peng Su5, Xinguo Hou1,2,3,4, Chuan Wang1,2,3,4, Jinbo Liu1,2,3,4, Bo Chen6, Hong Lai1,2,3,4, Yujing Sun1,2,3,4* and Li Chen 1,2,3,4*
Zhiyu Xia1,2, Haotian Tian1, Lei Shu1,2, Guozhang Tang3, Zhenyu Han4, Yangchun Hu1*, Xingliang Dai1*
Jianfeng Xu1,2, Hanwen Zhang1,2, Xiaohui Song1,2, Yangong Zheng3, Qingning Li1,2,4*
Bowen Hu1#, Lingyu Du2#, Hongya Xie1, Jun Ma1, Yong Yang1*, Jie Tan2*
Umair Ali Khan Saddozai, Zhendong Lu, Fengling Wang, Muhammad Usman Akbar, Saadullah Khattak, Muhammad Badar, Nazeer Hussain Khan, Longxiang Xie, Yongqiang Li, Xinying Ji, Xiangqian Guo
Suxia Hu, Abdusemer Reyimu, Wubi Zhou, Xiang Wang, Ying Zheng, Xia Chen, Weiqiang Li, Jingjing Dai
Yuting Chen, Yuzhen Rao, Zhiyu Zeng, Jiajie Luo, Chengkuan Zhao, Shuyao Zhang
Jun Li, Ziyong Wang, Qilin Wang
Jinghua Qi1,2, Hangping Chen3，Huaqing Lin2,4，Hongyuan Chen1,2,5* and Wen Rui2,3,5,6*
Xingli Qi1,2, Huaqing Lin2,3, Wen Rui2,3,4,5 and Hongyuan Chen1,2,3
Yulou Luo1, Lan Chen2, Ximing Qu3, Na Yi3, Jihua Ran4, Yan Chen3,5*
Min Jiang1#, Rui Zheng1#, Ling Shao1, Ning Yao2, Zhengmao Lu1*
Qiaoxin Lin1, Bin Liang1, Yangyang Li2, Ling Tian3*, Dianna Gu1*
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