'Paperdemic' during the COVID-19 pandemic

Metacell-based differential expression analysis identifies cell type specific temporal gene response programs in COVID-19 patient PBMCs

By profiling gene expression in individual cells, single-cell RNA-sequencing (scRNA-seq) can resolve cellular heterogeneity and cell-type gene expression dynamics. Its application to time-series samples can identify temporal gene programs active in different cell types, for example, immune cells' responses to viral infection. However, current scRNA-seq analysis has limitations. One is the low number of genes detected per cell. The second is insufficient replicates (often 1-2) due to high experimental cost. The third lies in the data analysis-treating individual cells as independent measurements leads to inflated statistics. To address these, we explore a new computational framework, specifically whether "metacells" constructed to maintain cellular heterogeneity within individual cell types (or clusters) can be used as "replicates" for increasing statistical rigor. Toward this, we applied SEACells to a time-series scRNA-seq dataset from peripheral blood mononuclear cells (PBMCs) after SARS-CoV-2 infection to construct metacells, and used them in maSigPro for quadratic regression to find significantly differentially expressed genes (DEGs) over time, followed by clustering expression velocity trends. We showed that such metacells retained greater expression variances and produced more biologically meaningful DEGs compared to either metacells generated randomly or from simple pseudobulk methods. More specifically, this approach correctly identified the known ISG15 interferon response program in almost all PBMC cell types and many DEGs enriched in the previously defined SARS-CoV-2 infection response pathway. It also uncovered additional and more cell type-specific temporal gene expression programs. Overall, our results demonstrate that the metacell-pseudoreplicate strategy could potentially overcome the limitation of 1-2 replicates.

Publications on COVID-19 in radiology journals in 2020 and 2021: bibliometric citation and co-citation network analysis

OBJECTIVES

The pandemic caused by SARS-CoV-2 has led to the rapid publication of numerous radiology articles, primarily focused on disease diagnosis. The objective of this study is to analyze the intellectual structure of radiology research on COVID-19 using a citation and co-citation analysis.

METHODS

We identified all documents about COVID-19 published in radiology journals included in the Web of Science in the period 2020-2021, conducting a citation analysis. Then we identified all bibliographic references that were cited by these documents, generating a co-citation matrix that was used to perform a co-citation network.

RESULTS

Of the 3418 documents indexed in WoS, 857 were initially "Early Access," 2223 had citations, 393 had more than 20 citations, and 83 had more than 100 citations. The USA had the highest number of publications (32.62%) and China had the highest rate of funded studies (45.38%). The three authors with the most publications were affiliated with Italian institutions, while the five most cited authors were Chinese. A total of 647 publications were co-cited at least 12 times and were published in 206 different journals, with 49% of the documents found in radiology journals. The institutions with the greatest presence among these co-cited articles were Chinese and American.

CONCLUSION

This co-citation analysis is the first to focus exclusively on radiology articles on COVID-19. Our study confirms the existence of interrelated thematic clusters with different specific weights.

KEY POINTS

• As the pandemic caused by SARS-Cov-2 has led to the rapid publication of numerous radiology studies in a short time period, a bibliometric review based on citation and co-citation analysis has been conducted. • The co-citation analysis supported the identification of key themes in the study of COVID-19 in radiology publications. • Many of the most co-cited articles belong to a heterogeneous group of publications, with authors from countries that are far apart and even from different disciplines.