Database Retrieval Research Articles

Shotgun chemome characterization of Artemisia rupestris L. Using direct infusion-MS/MSALL

In comparison of liquid chromatography, direct infusion is a superior choice to achieve high-throughput measurements. The specificity and selectivity of tandem mass spectrometry (MS/MS) actually result in a so-called MS separation potential when chemical characterization of herbal medicines. Here, a MS/MSALL program was introduced to promote DI–MS/MS to be an eligible tool for shotgun chemome characterization of Artemisia rupestris L. that is currently drawing worldwide interests because of the promising antiviral activity. After MS1 spectral acquisition for the crude extract, the gas phase fractionation concept enabled the precursor ion cohort sequentially entered the collision cell with a stepped unit mass window (step-size as 1 Da) to generate MS2 spectra, thus generating a unique property integrating the advantages of both data-dependent and data-independent acquisition manners. Even though being free of chromatographic separation, spectrometric separations were accomplished for by MS/MSALL program unless the components shared identical nominal molecular weights. Extensive efforts such as the correlations of MS1 signals with MS2 spectra, structural annotations of fragment ion species, information retrieval in some accessible databases, and referring to the literature data, were devoted for chemical characterization, and as a result, 44 compounds, in total, were structurally identified from 50% aqueous methanol exact of A. rupestris, including 8 caffeoyl quinic acid derivatives, 13 flavonoids, 15 monomeric and dimeric sesquiterpenoids, 4 fatty acids, 2 penylpropanoids, along with 2 other compounds. However, isomers were assigned as an isomeric mixture because their precursor ions always co-existed in a single mass window. Above all, DI–MS/MSALL provides an alternative tool for chemome characterization of herbal medicines, in particular when the great measurement workload for a large sample cohort, attributing to the high-throughput advantage.

Evolution of institutional repositories: Managing institutional research output to remove the gap of academic elitism

The article tries to highlight the evolution and conceptual framework of institutional repositories and their impact on the academic and scholarly circles in terms of better visibility, wider audience and earlier communication of research. The characteristics associated with the institutional repositories are also highlighted, which makes them stand out from the crowd in the family of open access scholarly platforms. The study is based on the examination and evaluation of the articles published across various peer-reviewed journals showcasing numerous dimensions of institutional repositories, ranging from their evolution to open scholarly acceptance. A preliminary search on institutional repositories was carried through two well-renowned indexing/abstracting databases of peer-reviewed literature, Clarivate Analytic’s, Web of Science and Elsevier’s Scopus. Search terms like institutional repositories, institutional research output, open access repositories, green open access, open access, open access publishing, open access initiatives, digital libraries, directory of open access repositories, open DOAR and scholarly communication were run across the databases for article retrieval, and the relevant studies were extracted accordingly. To make the study more comprehensive and current, the studies citing the retrieved articles were also consulted. The study reveals that the benefits associated with institutional repositories are manifold. They recounter users with the information which was otherwise unavailable due to the reasons ranging from the non-availability of supplementary information (like unpublished reports and working papers, multimedia and audiovisual items, learning objects, other special item types, bibliographic references, datasets, lecture notes and so forth) to the paywall/subscription models adopted by commercial channels of scholarly communication. Furthermore, the social, research and technological factors tend to be the main motivating factors for their wider acceptance by the scholarly community at global, national, organizational, and individual levels. They enhance the preservation of institutional research output with increased viewership and prestige apart from achieving a potential research impact. They, in a real sense, have abrogated the unilateral assault orchestrated by the commercial publishers on the author community by democratizing their scholarly voices via open and barrierless scholarly platforms. They are the future of the academic output of an institution/author as they perform successfully within the constitutional boundaries of scholarly and academic publishing, thus safeguarding the rights and claims of every academic actor. Given the importance of institutional repositories for a more democratic, barrierless and impactful information communication, they are for sure going beyond various scholarly circles by breaking the traditional and rigid walls of scholarly endeavours. The study presents a useful overview of the progression of the institutional repositories, their intended purpose and how they serve to fill the gaps in scholarly publishing and meet the needs of the wider academic community. The article summarizes in one place a concise overview of the use and impact of institutional repositories. The study is also an eye-opener for scholars interested in the research in the field of institutional repositories.

Genome sequence, transcriptome, and annotation of rodent malaria parasite Plasmodium yoelii nigeriensis N67

BackgroundRodent malaria parasites are important models for studying host-malaria parasite interactions such as host immune response, mechanisms of parasite evasion of host killing, and vaccine development. One of the rodent malaria parasites is Plasmodium yoelii, and multiple P. yoelii strains or subspecies that cause different disease phenotypes have been widely employed in various studies. The genomes and transcriptomes of several P. yoelii strains have been analyzed and annotated, including the lethal strains of P. y. yoelii YM (or 17XL) and non-lethal strains of P. y. yoelii 17XNL/17X. Genomic DNA sequences and cDNA reads from another subspecies P. y. nigeriensis N67 have been reported for studies of genetic polymorphisms and parasite response to drugs, but its genome has not been assembled and annotated.ResultsWe performed genome sequencing of the N67 parasite using the PacBio long-read sequencing technology, de novo assembled its genome and transcriptome, and predicted 5383 genes with high overall annotation quality. Comparison of the annotated genome of the N67 parasite with those of YM and 17X parasites revealed a set of genes with N67-specific orthology, expansion of gene families, particularly the homologs of the Plasmodium chabaudi erythrocyte membrane antigen, large numbers of SNPs and indels, and proteins predicted to interact with host immune responses based on their functional domains.ConclusionsThe genomes of N67 and 17X parasites are highly diverse, having approximately one polymorphic site per 50 base pairs of DNA. The annotated N67 genome and transcriptome provide searchable databases for fast retrieval of genes and proteins, which will greatly facilitate our efforts in studying the parasite biology and gene function and in developing effective control measures against malaria.

Content Based Medical Image Retrieval Based on Salient Regions Combined with Deep Learning

In traditional text based medical image retrieval system, it is hard to find visually similar images in large medical image database. Content-based image retrieval is developed to retrieve similar images and it is based on visual attributes describing the content of an image. Developing a method for content based medical image retrieval is a challenging task. This paper proposed a new method for content-based medical image retrieval based on salient regions and deep learning. The proposed method includes two stages: an offline task to extract local object features and an online task for content-based image retrieval in database. In first stage, we extract local object features of medical image depending on shape, texture and intensity, and features extracted by deep learning applied in saliency of decomposition. Secondly, we make online task for content-based image retrieval in database. The user gives query image as an input and the system will retrieve n top most similar images by similarity comparison with bag of code words feature values obtained in the first stage. Evaluation of the proposed method is based on Precision and Recall values. Our dataset includes 5 groups of medical images with their quality varying from low to high. With the best medical image quality group, the accuray can be 91.61% for Precision and 89.61% for Recall. Comparing the average values with others methods, the results of the proposed method are more than 2 to 5% better.

VESPER: global and local cryo-EM map alignment using local density vectors

An increasing number of density maps of biological macromolecules have been determined by cryo-electron microscopy (cryo-EM) and stored in the public database, EMDB. To interpret the structural information contained in EM density maps, alignment of maps is an essential step for structure modeling, comparison of maps, and for database search. Here, we developed VESPER, which captures the similarity of underlying molecular structures embedded in density maps by taking local gradient directions into consideration. Compared to existing methods, VESPER achieved substantially more accurate global and local alignment of maps as well as database retrieval.

Characteristics of molecular composition and its anti-nutrition of β-conglycinin during flavorzyme proteolysis

β-conglycinin is one of the main protein components in soybean that cause human allergy and it is difficult to eliminate the antigenicity of β-conglycinin using common enzymolysis, the reason of which is not clear. We analyzed the molecular composition, antigenic activity, and sequential epitopes of the hydrolysates of this protein after digestion with flavorzyme using SDS-PAGE, ELISA, MALDI-TOF-MS, and protein and antigen database retrieval. Results showed that α′-and α-subunits of β-conglycinin were nearly completely degraded 10 min after enzymolysis and that the protein retained 92.7% antigenic activity. Newly produced peptides, including those of 35, 23, 17, and 11 ku, were formed. These peptides and the 49 ku β-subunit were not degraded completely even after 150 min of enzymolysis, thus indicating evident resistance to enzymatic hydrolysis. Moreover, the antigenic activity of the protein maintained at 43.5%. Epitope analysis revealed that the newly formed 49, 35, 23, 17, and 11 ku peptides contain twenty seven antigen epitopes, including two from the α-subunit, ten from the α′-subunit, and fifteen from the β-subunit of β-conglycinin. These findings suggest the relationship between existence of anti-enzymolysis fragments and their epitopes and incomplete elimination of antigenicity of β-conglycinin.

Visual analysis of research progress of Sophorae Tonkinensis Radix et Rhizoma based on CiteSpace

To analyze the study advance of Sophorae Tonkinensis Radix et Rhizoma, this study utilized CiteSpace 5.6.R5 software to conduct bibliometrics analysis on the Chinese literatures of Sophorae Tonkinensis Radix et Rhizoma from 1990 to 2020 included in the CNKI database retrieval platform. The analysis contents involved the number of published papers, co-authors, cooperative institutions, emergence, co-occurrence and clustering of keywords. A total of 808 Chinese literatures were included in the study, of which 17 were published by SUN Rong, the author with the most published papers, and formed a research team centered on SUN Rong; the analysis of the cooperation of publishing institutions showed that the Drug Safety Evaluation Research Center, Shanghai University of Traditional Chinese Medicine was the organization with the largest number of publications, with a total of 29 articles. It also formed a scientific research coorperation institution with Shandong Academy of Traditional Chinese Medicine as the core, and formed a relatively close cooperative network relationship. The analysis of literature keywords showed that the research direction was concentrated on the traditional Chinese medicine of Sophorae Tonkinensis Radix et Rhizoma, pharmacological mechanism, and side effects, active ingredients, etc. Among them, the research on the efficacy and toxicity of the active ingredients of Sophorae Tonkinensis Radix et Rhizoma has become a hot trend.

Relationship between HLA-DRB1 gene polymorphism and breast cancer: A protocol for systematic review and meta-analysis.

Background:Breast cancer is one of the common malignant tumors in women, which seriously affects women's physical and mental health and even life-threatening. The occurrence and development of breast cancer are closely related to genetic factors. Many studies have shown that human leukocyte antigen DRB1 is associated with the development of breast cancer, but lack evidence. This study aims to systematically evaluate the relationship between HLA-DRB1 gene polymorphism and breast cancer.Methods:The retrieval time of this study was from the establishment of the database to February 2021. The retrieval databases included CNKI, Wanfang, VIP and China Biomedical Database, PubMed, Embase, Web of Science, and the Cochrane Library. The retrieval objects were observational studies on the relationship between HLA-DRB1 gene polymorphism and breast cancer (including case--control studies, cross-sectional studies, and cohort studies). The language restrictions were English and Chinese. Two researchers independently extracted the data and assessed the quality of the included studies, and Stata 16.0 software was used for statistical analysis.Results:This study will systematically evaluate the relationship between HLA-DRB1 gene polymorphism and breast cancer based on existing studies.Conclusion:This study will explore the early warning signal of breast cancer genetic susceptibility, and provide evidence-based medical evidence for clarifying the role of HLA-DRB1 gene polymorphism in breast cancer.OSF Registration number:DOI 10.17605/OSF.IO/847FQ

An overview of traditional Chinese medicine therapy for Helicobacter pylori-related gastritis.

Helicobacter pylori-associated gastritis (HPAG) is a common digestive system disease that its therapeutic goal is to eradicate Helicobacter pylori. However, due to the widespread use of antibiotics, problems for example, antibiotic resistance, reinfection, and gastrointestinal side effects have emerged. The solution of above problems provides a broad space for traditional Chinese medicine (TCM) to exert its remarkable advantages on the treatment of HPAG. Extensive database retrieval using platforms not limited to but including Web of Science, SpringerLink, ScienceDirect, Google Scholar, China National Knowledge Infrastructure, Wanfang, and VIP database was performed using keywords such as "Helicobacter pylori-associated gastritis" or "HPAG" or "Helicobacter pylori" or "H. pylori" or "gastritis" and "traditional Chinese medicine" or "TCM" or "herbs" or "Chinese herbal medicine". In addition, related books, PhD, and master's dissertations were also researched to provide a comprehensive review. This review mainly introduces the clinical efficacy of TCM formulas for HPAG, as well as active ingredient and pharmacological mechanisms of herbs. What's more, this review puts forward potential prospects for future research. These research works have shown the therapeutic benefits of TCM in the treatment of HPAG. The development of TCM with more specific functions and practical data will not only become a significant trend in the world market but also have an irreplaceable role in the future treatment of HPAG. More continued researches should be undertaken in the future.

Deep multimodal learning for cross-modal retrieval: One model for all tasks

Abstract We investigate the effectiveness of a successful model in Visual-Question-Answering (VQA) problems as the core component in a cross-modal retrieval system that can accept images or text as queries, in order to retrieve relevant data from a multimodal document collection. To this end, we adapt the VQA model for deep multimodal learning to combine visual and textual representations for information search, and we call this model “Deep Multimodal Embeddings (DME)”. Instead of training the model to answer questions, we supervise DME to classify semantic topics/concepts previously identified in the document collection of interest. In contrast to previous approaches, we found that this model can handle any multimodal query with a single architecture while producing improved or competitive results in all retrieval tasks. We evaluate the model performance with 3 widely known databases for cross-modal retrieval tasks: Wikipedia Retrieval Database, Pascal Sentences, and MIR-Flickr-25k. The results show that the DME model learns effective multimodal representations, resulting in strongly improved retrieval performance, specifically in the top results of the ranked list, which are the most important to users in the most-common scenarios of information retrieval. Our work represents a new baseline for a wide set of different methodologies for cross-modal retrieval.

Mean distance local binary pattern: a novel technique for color and texture image retrieval for liver ultrasound images

A rapid growth in medical ultrasound database makes it difficult for medical practitioners to manage and search relevant data with good efficiency. Hence, a novel image retrieval technique using Mean Distance Local Binary Pattern (Mean Distance LBP) has been proposed for content-based image retrieval. The conventional local binary pattern (LBP) converts every pixel of image into a binary pattern based on their relationship with neighbourhood pixels. The proposed feature descriptor differs from local binary pattern as it transforms the mutual relationship of all neighbouring pixels in a binary pattern based on their standard deviation templates as well as Euclidean distance from the center pixel. Color feature and Gray Level Co-occurrence Matrix have also been used in this work. To prove the excellence of the proposed method, experiments have been conducted on two different databases of natural images and face images. Further, the method is applied on real time ultrasound database for retrieval of liver images from a set of ultrasound images of various organs. The performance has been observed using well-known evaluation measures, precision and recall, and compared with some state-of-art local patterns. Comparison shows a significant improvement in the proposed method over existing methods.

Research and Prospect of Numerical Simulation of River Water Environment

Healthy water environment is the prerequisite for river resource utilization, social and economic development, new urbanization and healthy and happy river construction. Through the literature database retrieval statistics, summarizes the river water environment research to numerical simulation analysis, environmental quality improvement direction. The indicator system, evaluation method and significance of river ecosystem health assessment, and water ecological security assessment are introduced in detail. Finally, the types of river water environment numerical models are summarized, and the advantages and disadvantages of mainstream models and their application conditions and characteristics are compared and analyzed. In order to provide basic reference for river water environment numerical simulation machine watershed ecological environment protection and maintenance.

Methanol Skin Mucus Extract of Mrigal (Cirrhinus mrigala) Fish Peptide Targeting Viral Particles of Infectious Pancreatic Necrosis Virus (IPNV) and Infectious Salmon Anemia Virus (ISAV): an in silico Approach

The teleost fish skin mucus acts as an important physical and biological barrier that prevents fish from the surrounding environment. Many studies reported the presence of various immunological molecules in fish skin mucus that involve in protection against invading microbes. In the present study, the skin mucus proteins of freshwater fish Cirrhinus mrigala (mrigal) were extracted using organic solvent (methanol) and further analyzed by liquid chromatography-tandem mass spectrometry (LC–MS/MS) to identify proteins by database retrieval. LC–MS/MS analysis revealed the presence of diverse proteins in the methanol skin mucus extract. The identified proteins were classified into biological process, cellular process and molecular functions by Gene Ontology (GO) enrichment analysis. A peptide was selected, modelled and compared with other antimicrobial peptides sequences through phylogenetic analysis and showed that the modelled peptide shared high similarity with Arminin-1 of Cnidaria animals. We also investigated the potentiality of the modelled peptide against Infectious Pancreatic Necrosis Virus sub viral particle and Infectious Salmon Anemia Virus hemagglutinin-esterase protein through protein-peptide docking using ClusPro. The docking results confirmed that the modelled peptide has good interactions with viral particles. Therefore, these results suggest that the modelled peptide molecule from C. mrigala methanol skin mucus extract can be further studied that aid in the development of novel peptide candidate for the control of aquaculture viral diseases.

Passive Remote Sensing of Ice Cloud Properties at Terahertz Wavelengths Based on Genetic Algorithm

Ice clouds play a critical role in the balance of the earth–atmosphere radiation system, but there are some limitations in the existing remote sensing methods for ice clouds. Terahertz wave is expected to be the best waveband for retrieving ice clouds, with terahertz wavelengths in the order of the size of typical ice cloud particles. An inversion method for the remote sensing of ice clouds at terahertz wavelengths based on genetic algorithm is proposed in this paper. First, suitable channel sets in the terahertz band, which are mainly a combination of absorption lines and window regions, are determined. Then, to improve the efficiency of the generation of the retrieval database, based on the brightness temperature simulated by the atmospheric radiative transfer simulator (ARTS) for different cloud parameters, a fast forward operator is constructed using three-dimensional interpolation to simulate the brightness temperature difference between clear sky and a cloudy scene. Finally, an inversion model to retrieve the ice cloud base height, the effective particle diameter and the ice water path is established based on the genetic algorithm, and an analysis of the inversion errors is performed. The results show that the forward operator, constructed by the nearest interpolation, can accurately calculate the brightness temperature difference at a high speed. The proposed inversion method at terahertz wavelengths based on the genetic algorithm can achieve the expected scientific requirement. The absolute error of the cloud height is around 0.2 km, and the absolute error of the low ice water path (below 20 g/m2) is small, while the relative error of the high ice water path is generally maintained at around 10%, and the absolute error of the effective particle diameter is mostly around 4 μm.

Acesso aos serviços de saúde no Brasil por mulheres transexuais: uma revisão integrativa

O objetivo do estudo foi analisar a produção científica brasileira sobre o acesso aos serviços de saúde por mulheres transexuais na atenção primária do SUS. Trata-se de uma revisão integrativa da literatura, realizada no período de janeiro de 2020 a janeiro de 2021, nas bases de dados Medical Literature Analysis and Retrieval System Online, Scientific Electronic Library Online, Literatura Latino-Americana e do Caribe em Ciências da Saúde, Cumulative Index to Nursing and Allied Health Literature e Banco de Dados em Enfermagem, com recorte temporal de 2013 a 2020 e selecionados a partir da questão norteadora: Como se dá o acesso aos serviços de saúde na atenção primária do SUS por mulheres transexuais? A amostra foi composta por onze artigos. Os estudos apontaram barreiras na implementação das políticas voltadas para a população trans, como, dentre outros entraves, o desrespeito ao nome social dentro das unidades de saúde. Além disso, a concentração da maior parte dos estudos na região Sudeste, prejudica uma visão geral do acesso no Brasil. A produção científica analisada evidenciou as lacunas existentes no acesso e a necessidade de instruir os profissionais de saúde da atenção primária do SUS acerca das necessidades das mulheres trans.

A Heterogeneous Geospatial Data Retrieval Method Using Knowledge Graph

Information resources have increased rapidly in the big data era. Geospatial data plays an indispensable role in spatially informed analyses, while data in different areas are relatively isolated. Therefore, it is inadequate to use relational data in handling many semantic intricacies and retrieving geospatial data. In light of this, a heterogeneous retrieval method based on knowledge graph is proposed in this paper. There are three advantages of this method: (1) the semantic knowledge of geospatial data is considered; (2) more information required by users could be obtained; (3) data retrieval speed can be improved. Firstly, implicit semantic knowledge is studied and applied to construct a knowledge graph, integrating semantics in multi-source heterogeneous geospatial data. Then, the query expansion rules and the mappings between knowledge and database are designed to construct retrieval statements and obtain related spatial entities. Finally, the effectiveness and efficiency are verified through comparative analysis and practices. The experiment indicates that the method could automatically construct database retrieval statements and retrieve more relevant data. Additionally, users could reduce the dependence on data storage mode and database Structured Query Language syntax. This paper would facilitate the sharing and outreach of geospatial knowledge for various spatial studies.

A computational framework of host-based drug repositioning for broad-spectrum antivirals against RNA viruses

SummaryRNA viruses are responsible for many zoonotic diseases that post great challenges for public health. Effective therapeutics against these viral infections remain limited. Here, we deployed a computational framework for host-based drug repositioning to predict potential antiviral drugs from 2,352 approved drugs and 1,062 natural compounds embedded in herbs of traditional Chinese medicine. By systematically interrogating public genetic screening data, we comprehensively cataloged host dependency genes (HDGs) that are indispensable for successful viral infection corresponding to 10 families and 29 species of RNA viruses. We then utilized these HDGs as potential drug targets and interrogated extensive drug-target interactions through database retrieval, literature mining, and de novo prediction using artificial intelligence-based algorithms. Repurposed drugs or natural compounds were proposed against many viral pathogens such as coronaviruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), flaviviruses, and influenza viruses. This study helps to prioritize promising drug candidates for in-depth evaluation against these virus-related diseases.

Applying Code Transform Model to Newly Generated Program for Improving Execution Performance

The existing programs inside the voice assistant machine prompt human-machine interaction in response to a request from a user. However, the crucial problem is that the machine often may not give a proper answer to the user or cannot work out the existing program execution efficiently. Therefore, this study proposes a novel transform method to replace the existing programs (called sample programs in this paper) inside the machine with newly generated programs through code transform model GPT-2 that can reasonably solve the problem mentioned above. In essence, this paper introduces a theoretical estimation in statistics to infer at least a number of generated programs as required so as to guarantee that the best one can be found within them. In addition, the proposed approach not only imitates a voice assistant system with filtering redundant keywords or adding new keywords to complete keyword retrieval in semantic database but also checks code similarity and verifies the conformity of the executive outputs between sample programs and newly generated programs. According to code checking and program output verification, the processes can expedite transform operations efficiently by removing the redundant generated programs and finding the best-performing generated program. As a result, the newly generated programs outperform the sample programs because the proposed approach reduces the number of code lines by 32.71% and lowers the program execution time by 24.34%, which is of great significance.

Extreme Lake-Effect Snow from a GPM Microwave Imager Perspective: Observational Analysis and Precipitation Retrieval Evaluation.

This study focuses on the ability of the Global Precipitation Measurement (GPM) passive microwave sensors to detect and provide quantitative precipitation estimates (QPE) for extreme lake-effect snowfall events over the U.S. lower Great Lakes region. GPM Microwave Imager (GMI) high-frequency channels can clearly detect intense shallow convective snowfall events. However, GMI Goddard Profiling (GPROF) QPE retrievals produce inconsistent results when compared with the Multi-Radar Multi-Sensor (MRMS) ground-based radar reference dataset. While GPROF retrievals adequately capture intense snowfall rates and spatial patterns of one event, GPROF systematically underestimates intense snowfall rates in another event. Furthermore, GPROF produces abundant light snowfall rates that do not accord with MRMS observations. Ad hoc precipitation-rate thresholds are suggested to partially mitigate GPROF's overproduction of light snowfall rates. The sensitivity and retrieval efficiency of GPROF to key parameters (2-m temperature, total precipitable water, and background surface type) used to constrain the GPROF a priori retrieval database are investigated. Results demonstrate that typical lake-effect snow environmental and surface conditions, especially coastal surfaces, are underpopulated in the database and adversely affect GPROF retrievals. For the two presented case studies, using a snow-cover a priori database in the locations originally deemed as coastline improves retrieval. This study suggests that it is particularly important to have more accurate GPROF surface classifications and better representativeness of the a priori databases to improve intense lake-effect snow detection and retrieval performance.

Effectiveness and safety of different doses of tenecteplase in the treatment of acute ischemic stroke: A protocol for systematic review and meta-analysis.

Background:Tenecteplase is a modified recombinant tissue-plasminogen activator, which is effective and safe in the treatment of acute ischemic stroke. However, the therapeutic dose of tenecteplase has been controversial. The purpose of this study is to systematically investigate the efficacy and safety of different doses of tenecteplase thrombolytic therapy for acute ischemic stroke.Methods:Computer retrieval of English databases (PubMed, EMBASE, Web of Science, the Cochrane Library) and Chinese databases (CNKI, Wanfang, Viper, and Chinese Biomedical Database) is conducted for a randomized controlled clinical study on thrombolytic treatment of acute ischemic stroke with different doses of tenecteplase from the establishment of the database to October 2020. Two researchers independently conduct data extraction and literature quality evaluation on the quality of the included studies, and meta-analysis is conducted on the included literatures using RevMan5.3 software.Outcome:In this study, National Institute of Health Stroke Scale (NIHSS) score, Modified Rankin Scale (mRS) score scale, symptomatic intracranial hemorrhage (SICH) incidence, All-cause mortality, and so on are used to evaluate the efficacy and safety of tenecteplase thrombolytic therapy in acute ischemic stroke with different doses.Conclusion:This study will provide reliable evidence-based evidence for the clinical application of different doses of tenecteplase in thrombolytic therapy for acute ischemic stroke.OSF Registration number:DOI 10.17605/OSF.IO/2MPCW.