Emerging trends and focus on the link between gut microbiota and type 1 diabetes : A bibliometric and visualization analysis
Copyright © 2023 Guo, Li, Li, Huang and Zhou..
Objective: To conduct the first thorough bibliometric analysis to evaluate and quantify global research regarding to the gut microbiota and type 1 diabetes (T1D).
Methods: A literature search for research studies on gut microbiota and T1D was conducted using the Web of Science Core Collection (WoSCC) database on 24 September 2022. VOSviewer software and the packages Bibliometrix R and ggplot used in RStudio were applied to perform the bibliometric and visualization analysis.
Results: A total of 639 publications was extracted using the terms "gut microbiota" and "type 1 diabetes" (and their synonyms in MeSH). Ultimately, 324 articles were included in the bibliometric analysis. The United States and European countries are the main contributors to this field, and the top 10 most influential institutions are all based in the United States, Finland and Denmark. The three most influential researchers in this field are Li Wen, Jorma Ilonen and Mikael Knip. Historical direct citation analysis showed the evolution of the most cited papers in the field of T1D and gut microbiota. Clustering analysis defined seven clusters, covering the current main topics in both basic and clinical research on T1D and gut microbiota. The most commonly found high-frequency keywords in the period from 2018 to 2021 were "metagenomics," "neutrophils" and "machine learning.".
Conclusion: The application of multi-omics and machine learning approaches will be a necessary future step for better understanding gut microbiota in T1D. Finally, the future outlook for customized therapy toward reshaping gut microbiota of T1D patients remains promising.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:14 |
|---|---|
| Enthalten in: |
Frontiers in microbiology - 14(2023) vom: 08., Seite 1137595 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Guo, Keyu [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Bibliometric analysis |
|---|
| Anmerkungen: |
Date Revised 02.12.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.3389/fmicb.2023.1137595 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM35475744X |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM35475744X | ||
| 003 | DE-627 | ||
| 005 | 20231226062913.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.3389/fmicb.2023.1137595 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1182.xml |
| 035 | |a (DE-627)NLM35475744X | ||
| 035 | |a (NLM)36970681 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Guo, Keyu |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Emerging trends and focus on the link between gut microbiota and type 1 diabetes |b A bibliometric and visualization analysis |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 02.12.2023 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Copyright © 2023 Guo, Li, Li, Huang and Zhou. | ||
| 520 | |a Objective: To conduct the first thorough bibliometric analysis to evaluate and quantify global research regarding to the gut microbiota and type 1 diabetes (T1D) | ||
| 520 | |a Methods: A literature search for research studies on gut microbiota and T1D was conducted using the Web of Science Core Collection (WoSCC) database on 24 September 2022. VOSviewer software and the packages Bibliometrix R and ggplot used in RStudio were applied to perform the bibliometric and visualization analysis | ||
| 520 | |a Results: A total of 639 publications was extracted using the terms "gut microbiota" and "type 1 diabetes" (and their synonyms in MeSH). Ultimately, 324 articles were included in the bibliometric analysis. The United States and European countries are the main contributors to this field, and the top 10 most influential institutions are all based in the United States, Finland and Denmark. The three most influential researchers in this field are Li Wen, Jorma Ilonen and Mikael Knip. Historical direct citation analysis showed the evolution of the most cited papers in the field of T1D and gut microbiota. Clustering analysis defined seven clusters, covering the current main topics in both basic and clinical research on T1D and gut microbiota. The most commonly found high-frequency keywords in the period from 2018 to 2021 were "metagenomics," "neutrophils" and "machine learning." | ||
| 520 | |a Conclusion: The application of multi-omics and machine learning approaches will be a necessary future step for better understanding gut microbiota in T1D. Finally, the future outlook for customized therapy toward reshaping gut microbiota of T1D patients remains promising | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a bibliometric analysis | |
| 650 | 4 | |a gut microbiota | |
| 650 | 4 | |a research focus | |
| 650 | 4 | |a type 1 diabetes | |
| 650 | 4 | |a visualization analysis | |
| 700 | 1 | |a Li, Jiaqi |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Xia |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Juan |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Zhiguang |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Frontiers in microbiology |d 2010 |g 14(2023) vom: 08., Seite 1137595 |w (DE-627)NLM208040617 |x 1664-302X |7 nnns |
| 773 | 1 | 8 | |g volume:14 |g year:2023 |g day:08 |g pages:1137595 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.3389/fmicb.2023.1137595 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 14 |j 2023 |b 08 |h 1137595 | ||