Kito Nzingha

3.7k total citations · 1 hit paper
8 papers, 1.0k citations indexed

About

Kito Nzingha is a scholar working on Immunology, Epidemiology and Obstetrics and Gynecology. According to data from OpenAlex, Kito Nzingha has authored 8 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Immunology, 1 paper in Epidemiology and 1 paper in Obstetrics and Gynecology. Recurrent topics in Kito Nzingha's work include Immune Cell Function and Interaction (7 papers), Immunotherapy and Immune Responses (7 papers) and T-cell and B-cell Immunology (6 papers). Kito Nzingha is often cited by papers focused on Immune Cell Function and Interaction (7 papers), Immunotherapy and Immune Responses (7 papers) and T-cell and B-cell Immunology (6 papers). Kito Nzingha collaborates with scholars based in United States, Australia and Egypt. Kito Nzingha's co-authors include Sasikanth Manne, E. John Wherry, Mohamed S. Abdel-Hakeem, Jean‐Christophe Beltra, Zeyu Chen, Josephine R. Giles, Makoto Kurachi, Giorgos C. Karakousis, Lynn M. Schuchter and Xiaowei Xu and has published in prestigious journals such as Cell, Immunity and Nature Immunology.

In The Last Decade

Kito Nzingha

8 papers receiving 1.0k citations

Hit Papers

Developmental Relationships of Four Exhausted CD8+ T Cell... 2020 2026 2022 2024 2020 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kito Nzingha United States 7 783 557 214 66 62 8 1.0k
Jean‐Christophe Beltra United States 8 737 0.9× 595 1.1× 195 0.9× 54 0.8× 52 0.8× 9 962
Elien M. Doorduijn Netherlands 10 663 0.8× 496 0.9× 222 1.0× 55 0.8× 41 0.7× 12 867
Sofia Mensurado Portugal 11 905 1.2× 587 1.1× 204 1.0× 89 1.3× 41 0.7× 17 1.2k
Henning Zelba Germany 14 650 0.8× 594 1.1× 180 0.8× 56 0.8× 74 1.2× 23 883
Eunseon Ahn United States 8 675 0.9× 466 0.8× 208 1.0× 43 0.7× 75 1.2× 14 960
Simone L. Park Australia 13 741 0.9× 344 0.6× 230 1.1× 45 0.7× 53 0.9× 16 983
Patrick Roelli Switzerland 7 625 0.8× 418 0.8× 221 1.0× 43 0.7× 92 1.5× 7 852
Hsiao‐Wei Tsao United States 7 626 0.8× 429 0.8× 249 1.2× 62 0.9× 53 0.9× 7 843
Leticia Barba Switzerland 6 676 0.9× 643 1.2× 150 0.7× 38 0.6× 30 0.5× 6 890
Silvia Lorenzi Italy 7 482 0.6× 341 0.6× 180 0.8× 41 0.6× 80 1.3× 8 702

Countries citing papers authored by Kito Nzingha

Since Specialization
Citations

This map shows the geographic impact of Kito Nzingha's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kito Nzingha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kito Nzingha more than expected).

Fields of papers citing papers by Kito Nzingha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kito Nzingha. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kito Nzingha. The network helps show where Kito Nzingha may publish in the future.

Co-authorship network of co-authors of Kito Nzingha

This figure shows the co-authorship network connecting the top 25 collaborators of Kito Nzingha. A scholar is included among the top collaborators of Kito Nzingha based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kito Nzingha. Kito Nzingha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Patel, Ravi K., Oyebola O. Oyesola, Jennifer K. Grenier, et al.. (2024). The gene regulatory basis of bystander activation in CD8 + T cells. Science Immunology. 9(92). eadf8776–eadf8776. 15 indexed citations
2.
Abdel-Hakeem, Mohamed S., Sasikanth Manne, Jean‐Christophe Beltra, et al.. (2021). Epigenetic scarring of exhausted T cells hinders memory differentiation upon eliminating chronic antigenic stimulation. Nature Immunology. 22(8). 1008–1019. 147 indexed citations
3.
Beltra, Jean‐Christophe, Sasikanth Manne, Mohamed S. Abdel-Hakeem, et al.. (2020). Developmental relationships of four exhausted CD8 T cell subsets reveals underlying transcriptional and epigenetic control mechanisms. The Journal of Immunology. 204(1_Supplement). 77.16–77.16. 2 indexed citations
4.
Beltra, Jean‐Christophe, Sasikanth Manne, Mohamed S. Abdel-Hakeem, et al.. (2020). Developmental Relationships of Four Exhausted CD8+ T Cell Subsets Reveals Underlying Transcriptional and Epigenetic Landscape Control Mechanisms. Immunity. 52(5). 825–841.e8. 598 indexed citations breakdown →
5.
Stelekati, Erietta, Zeyu Chen, Sasikanth Manne, et al.. (2018). Long-Term Persistence of Exhausted CD8 T Cells in Chronic Infection Is Regulated by MicroRNA-155. Cell Reports. 23(7). 2142–2156. 71 indexed citations
6.
Smith, Norah L., Ravi K. Patel, Arnold Reynaldi, et al.. (2018). Developmental Origin Governs CD8+ T Cell Fate Decisions during Infection. Cell. 174(1). 117–130.e14. 133 indexed citations
7.
Venturi, Vanessa, Kito Nzingha, Timothy G. Amos, et al.. (2016). The Neonatal CD8+ T Cell Repertoire Rapidly Diversifies during Persistent Viral Infection. The Journal of Immunology. 196(4). 1604–1616. 17 indexed citations
8.
Rudd, Brian D., Vanessa Venturi, Norah L. Smith, et al.. (2013). Acute Neonatal Infections ‘Lock-In’ a Suboptimal CD8+ T Cell Repertoire with Impaired Recall Responses. PLoS Pathogens. 9(9). e1003572–e1003572. 28 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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