Research hotspots and trends in the field of articular cartilage repair:a visualization analysis / 中国组织工程研究

BACKGROUND:Due to the very limited ability of articular cartilage to repair itself,articular cartilage defects caused by natural degeneration or trauma often cannot be repaired on their own,which triggers or aggravates osteoarthritis and even leads to severe disability.Therefore,the repair treatment after articular cartilage injury has become an urgent clinical problem. OBJECTIVE:To summarize the hot research topics and development trends in the field of articular cartilage repair using bibliometric analysis. METHODS:Literature related to articular cartilage repair was searched from the Web of Science Core Collection from 2000 to 2023,and bibliometric and visualization analyses were carried out using VOSviewer,Citespeace and Bibliometrix R-package. RESULTS AND CONCLUSION:The annual publication volume in the field of articular cartilage repair shows an overall increasing trend,with the United States,China,and Germany being the top three countries in terms of publication volume,and the research institutions focus on universities and hospitals,with Harvard University,New York Hospital for Special Surgery,and Shanghai Jiao Tong University being the top three institutions in terms of publication volume.AMERICAN JOURNAL OF SPORTS MEDICINE is the journal that publishes the most research literature in the field,and BIOMATERIALS is the journal with the highest number of citations in the field."Injectable hydrogels for cartilage and bone tissue engineering"is the most cited document published in the last decade,and the author with the most publications is Madry Henning,an active author in the field.The active authors in this field have formed a number of stable research teams with each other,and the cooperation between different teams needs to be further strengthened.Intra-articular injections,high tibial osteotomies,hydrogels,drug delivery,inflammation,cartilage regeneration,and scaffolds are the current hot topics of research in this field,and the application of 3D printing technology,bio-inks,silk proteins,injectable hydrogels,and exosomes in articular cartilage repair may be the frontier of research in this field.Integrating various innovative technologies and methods for more effective,durable and functional cartilage tissue regeneration and repair,and facilitating the clinical translation of the relevant technologies and methods by conducting more high-quality clinical studies may be the future research trend in this field.

The best practice for microbiome analysis using R

With the gradual maturity of sequencing technology, many microbiome studies have published, driving the emergence and advance of related analysis tools. R language is the widely used platform for microbiome data analysis for powerful functions. However, tens of thousands of R packages and numerous similar analysis tools have brought major challenges for many researchers to explore microbiome data. How to choose suitable, efficient, convenient, and easy-to-learn tools from the numerous R packages has become a problem for many microbiome researchers. We have organized 324 common R packages for microbiome analysis and classified them according to application categories (diversity, difference, biomarker, correlation and network, functional prediction, and others), which could help researchers quickly find relevant R packages for microbiome analysis. Furthermore, we systematically sorted the integrated R packages (phyloseq, microbiome, MicrobiomeAnalystR, Animalcules, microeco, and amplicon) for microbiome analysis, and summarized the advantages and limitations, which will help researchers choose the appropriate tools. Finally, we thoroughly reviewed the R packages for microbiome analysis, summarized most of the common analysis content in the microbiome, and formed the most suitable pipeline for microbiome analysis. This paper is accompanied by hundreds of examples with 10,000 lines codes in GitHub, which can help beginners to learn, also help analysts compare and test different tools. This paper systematically sorts the application of R in microbiome, providing an important theoretical basis and practical reference for the development of better microbiome tools in the future. All the code is available at GitHub github.com/taowenmicro/EasyMicrobiomeR.

Analytical solution of linear multi-compartment models with non-zero initial condition and its implementation with R

The analytical solution for multi-compartment models with a non-zero initial condition is complex because of the inter-compartmental transfer. An elegant solution and its implementation in the ‘wnl' R package can be useful in solving examples of textbooks and developing software of therapeutic drug monitoring, pharmacokinetic simulation, and parameter estimation. This solution uses Laplace transformation, convolution, matrix inversion, and the fact that the general solution of an inhomogeneous ordinary differential equation is the sum of a homogenous and a particular solution, together.

Caffsim: simulation of plasma caffeine concentrations implemented as an R package and Web-applications

Caffeine is a naturally-occurring central nervous system stimulant found in plant constituents including coffee, cocoa beans, and tea leaves. Consumption of caffeine through imbibing caffeinated drinks is rapidly growing among children, adolescents, and young adults, who tend to be more caffeine-sensitive than the rest of the general public; consequently, caffeine-related toxicities among these groups are also growing in number. However, a quantitative and interactive tool for predicting the plasma caffeine concentration that may lead to caffeine intoxication has yet to be developed. Using the previously established population-pharmacokinetic model, we developed “caffsim” R package and its web-based applications using Shiny and EDISON (EDucation-research Integration through Simulation On the Net). The primary aim of the software is to easily predict and calculate plasma caffeine concentration and pharmacokinetic parameters and visualize their changes after single or multiple ingestions of caffeine. The caffsim R package helps understand how plasma caffeine concentration changes over time and how long toxic concentration of caffeine can last in caffeine-sensitive groups. It may also help clinical evaluation of relationship between caffeine intake and toxicities when suspicious acute symptoms occur.