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Record W3180412704 · doi:10.3389/fnins.2021.706105

Mapping Knowledge Structure and Research Frontiers of Ultrasound-Induced Blood-Brain Barrier Opening: A Scientometric Study

2021· article· en· W3180412704 on OpenAlexaboutno aff
Haiyang Wu, Yan Zhou, Lixia Xu, Linjian Tong, Yulin Wang, Baolong Liu, Hua Yan, Zhiming Sun

Bibliographic record

VenueFrontiers in Neuroscience · 2021
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsnot available
FundersNatural Science Foundation of Tianjin City
KeywordsWeb of scienceData scienceMedicineLibrary scienceComputer sciencePathologyMeta-analysis

Abstract

fetched live from OpenAlex

Background: Among the effective approaches developed for blood-brain barrier (BBB) opening, ultrasound is recognized as a non-invasive technique that can induce localized BBB opening transiently and repeatedly. This technique has aroused broad attention from researchers worldwide, and numerous articles have been published recently. However, no existing study has systematically examined this field from a scientometric perspective. The aim of this study was to summarize the knowledge structure and identify emerging trends and potential hotspots in this field. Methods: Publications related to ultrasound-induced BBB opening published from 1998 to 2020 were retrieved from Web of Science Core Collection. The search strategies were as follows: topic: (“blood brain barrier” OR “BBB”) AND topic: (ultrasound OR ultrason* OR acoustic* OR sonopora*). The document type was set to articles or reviews with language restriction to English. Three different analysis tools including one online platform, VOS viewer1.6.16, and CiteSpace V5.7.R2 software were used to conduct this scientometric study. Results: A total of 1,201 valid records were included in the final analysis. The majority of scientific publication was produced by authors from North America, Eastern Asia, and Western Europe. Ultrasound in Medicine and Biology was the most prominent journal. The USA, China, and Canada were the most productive countries. Hynynen K, and Mcdannold N were key researchers with considerable academic influence. According to analysis of keywords, four main research directions were identified: cluster 1 (microbubbles study), cluster 2 (management of intracranial tumors), cluster 3 (ultrasound parameters and mechanisms study), and cluster 4 (treatment of neurodegenerative diseases). The current research hotspot has shifted from the basic research of ultrasound and microbubbles to management of intracranial tumors and neurodegenerative diseases. Burst detection analysis showed that Parkinson's disease, doxorubicin, gold nanoparticle, glioblastoma, gene therapy, and Alzheimer's disease may continue to be the research frontiers. Conclusion: Ultrasound-induced BBB opening research is in a period of robust development. This study is a starting point, providing a comprehensive overview, development landscape, and future opportunities of this technology, which standout as a useful reference for researchers and decision makers interested in this area.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.008
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.302
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations54
Published2021
Admission routes1
Has abstractyes

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