Carlos Cantu

3.6k total citations · 2 hit papers
18 papers, 3.0k citations indexed

About

Carlos Cantu is a scholar working on Immunology, Hematology and Molecular Medicine. According to data from OpenAlex, Carlos Cantu has authored 18 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 5 papers in Hematology and 4 papers in Molecular Medicine. Recurrent topics in Carlos Cantu's work include Immune Cell Function and Interaction (11 papers), T-cell and B-cell Immunology (6 papers) and Immunotherapy and Immune Responses (4 papers). Carlos Cantu is often cited by papers focused on Immune Cell Function and Interaction (11 papers), T-cell and B-cell Immunology (6 papers) and Immunotherapy and Immune Responses (4 papers). Carlos Cantu collaborates with scholars based in United States, Sweden and Canada. Carlos Cantu's co-authors include Luc Teyton, Paul B. Savage, Albert Bendelac, Dapeng Zhou, Jochen Mattner, Ning Yin, Ying Gao, Randal D. Goff, Timothy Palzkill and Yuval Sagiv and has published in prestigious journals such as Nature, Science and Journal of the American Chemical Society.

In The Last Decade

Carlos Cantu

18 papers receiving 2.9k citations

Hit Papers

Exogenous and endogenous glycolipid antigens activate NKT... 2004 2026 2011 2018 2005 2004 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Carlos Cantu United States 14 2.3k 623 359 219 169 18 3.0k
Ning Yin United States 10 1.7k 0.7× 373 0.6× 259 0.7× 181 0.8× 31 0.2× 15 2.1k
Ravi Malaviya United States 22 1.9k 0.8× 565 0.9× 223 0.6× 172 0.8× 37 0.2× 51 2.8k
Jérôme Le Nours Australia 27 2.4k 1.1× 688 1.1× 560 1.6× 450 2.1× 22 0.1× 48 3.4k
J. Content Belgium 30 1.3k 0.5× 1.4k 2.2× 661 1.8× 707 3.2× 99 0.6× 70 3.1k
Vandana Kalia United States 23 2.6k 1.1× 582 0.9× 943 2.6× 482 2.2× 33 0.2× 57 3.5k
Jean‐François Haeuw France 21 603 0.3× 944 1.5× 289 0.8× 241 1.1× 49 0.3× 35 1.8k
Helen Blanchard Australia 30 1.2k 0.5× 1.5k 2.4× 293 0.8× 366 1.7× 62 0.4× 66 2.7k
Jin Gohda Japan 24 966 0.4× 1.2k 1.9× 388 1.1× 239 1.1× 25 0.1× 48 2.4k
Susanne Kirschnek Germany 23 782 0.3× 1.1k 1.7× 191 0.5× 308 1.4× 47 0.3× 45 1.9k
Fernando Rock United States 15 1.2k 0.5× 772 1.2× 161 0.4× 430 2.0× 59 0.3× 19 2.5k

Countries citing papers authored by Carlos Cantu

Since Specialization
Citations

This map shows the geographic impact of Carlos Cantu'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 Carlos Cantu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlos Cantu more than expected).

Fields of papers citing papers by Carlos Cantu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Carlos Cantu. 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 Carlos Cantu. The network helps show where Carlos Cantu may publish in the future.

Co-authorship network of co-authors of Carlos Cantu

This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Cantu. A scholar is included among the top collaborators of Carlos Cantu 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 Carlos Cantu. Carlos Cantu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Brown, Gabrielle, et al.. (2014). “Almost Bleeding to Death”: The Conundrum of Acquired Amegakaryocytic Thrombocytopenia. SHILAP Revista de lepidopterología. 2014. 1–5. 9 indexed citations
2.
Fuchs, Deborah, et al.. (2012). Developmental Differences in Megakaryocyte Size in Infants and Children. American Journal of Clinical Pathology. 138(1). 140–145. 24 indexed citations
3.
Yin, Ning, Randal D. Goff, Dapeng Zhou, et al.. (2009). Alpha Anomers of iGb3 and Gb3 Stimulate Cytokine Production by Natural Killer T Cells. ACS Chemical Biology. 4(3). 191–197. 19 indexed citations
4.
Liu, Yang, Randal D. Goff, Dapeng Zhou, et al.. (2006). A modified α-galactosyl ceramide for staining and stimulating natural killer T cells. Journal of Immunological Methods. 312(1-2). 34–39. 144 indexed citations
5.
Mattner, Jochen, Kristin L. DeBord, Nahed Ismail, et al.. (2006). Correction: Corrigendum: Exogenous and endogenous glycolipid antigens activate NKT cells during microbial infections. Nature. 439(7075). 502–502. 3 indexed citations
6.
Mattner, Jochen, Kristin L. DeBord, Nahed Ismail, et al.. (2005). Exogenous and endogenous glycolipid antigens activate NKT cells during microbial infections. Nature. 434(7032). 525–529. 895 indexed citations breakdown →
7.
Zajonc, Dirk M., Carlos Cantu, Jochen Mattner, et al.. (2005). Structure and function of a potent agonist for the semi-invariant natural killer T cell receptor. Nature Immunology. 6(8). 810–818. 259 indexed citations
8.
Zhou, Dapeng, Jochen Mattner, Carlos Cantu, et al.. (2004). Lysosomal Glycosphingolipid Recognition by NKT Cells. Science. 306(5702). 1786–1789. 780 indexed citations breakdown →
9.
Goff, Randal D., Ying Gao, Jochen Mattner, et al.. (2004). Effects of Lipid Chain Lengths in α-Galactosylceramides on Cytokine Release by Natural Killer T Cells. Journal of the American Chemical Society. 126(42). 13602–13603. 181 indexed citations
10.
Cantu, Carlos & Luc Teyton. (2004). Linking lipid metabolism to immunity: The role of lipid transfer proteins in the selection of iNKT cells.. PubMed. 4(21). 115–7. 1 indexed citations
11.
Zhou, Dapeng, Carlos Cantu, Yuval Sagiv, et al.. (2003). Editing of CD1d-Bound Lipid Antigens by Endosomal Lipid Transfer Proteins. Science. 303(5657). 523–527. 263 indexed citations
12.
Cantu, Carlos, Kamel Benlagha, Paul B. Savage, Albert Bendelac, & Luc Teyton. (2003). The Paradox of Immune Molecular Recognition of α-Galactosylceramide: Low Affinity, Low Specificity for CD1d, High Affinity for αβ TCRs. The Journal of Immunology. 170(9). 4673–4682. 76 indexed citations
13.
Teyton, Luc, Vasso Apostolopoulos, Carlos Cantu, et al.. (2000). Function and Dysfunction of T Cell Receptor: Structural Studies. Immunologic Research. 21(2-3). 325–330. 3 indexed citations
14.
Cantu, Carlos & Timothy Palzkill. (1998). The Role of Residue 238 of TEM-1 β-Lactamase in the Hydrolysis of Extended-spectrum Antibiotics. Journal of Biological Chemistry. 273(41). 26603–26609. 42 indexed citations
15.
Petrosino, Joseph F., Carlos Cantu, & Timothy Palzkill. (1998). β-Lactamases: protein evolution in real time. Trends in Microbiology. 6(8). 323–327. 74 indexed citations
16.
Cantu, Carlos, Wanzhi Huang, & Timothy Palzkill. (1997). Cephalosporin Substrate Specificity Determinants of TEM-1 β-Lactamase. Journal of Biological Chemistry. 272(46). 29144–29150. 55 indexed citations
17.
Cantu, Carlos, Wanzhi Huang, & Timothy Palzkill. (1996). Selection and Characterization of Amino Acid Substitutions at Residues 237-240 of TEM-1 β-Lactamase with Altered Substrate Specificity for Aztreonam and Ceftazidime. Journal of Biological Chemistry. 271(37). 22538–22545. 60 indexed citations
18.
Seryshev, Alexander, Dolores H. Needleman, Carlos Cantu, et al.. (1994). Localization of the high and low affinity [3H]ryanodine binding sites on the skeletal muscle Ca2+ release channel.. Journal of Biological Chemistry. 269(22). 15876–15884. 107 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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