Marco T. Núñez

6.8k total citations
127 papers, 5.7k citations indexed

About

Marco T. Núñez is a scholar working on Hematology, Nutrition and Dietetics and Genetics. According to data from OpenAlex, Marco T. Núñez has authored 127 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Hematology, 55 papers in Nutrition and Dietetics and 35 papers in Genetics. Recurrent topics in Marco T. Núñez's work include Iron Metabolism and Disorders (61 papers), Trace Elements in Health (54 papers) and Hemoglobinopathies and Related Disorders (35 papers). Marco T. Núñez is often cited by papers focused on Iron Metabolism and Disorders (61 papers), Trace Elements in Health (54 papers) and Hemoglobinopathies and Related Disorders (35 papers). Marco T. Núñez collaborates with scholars based in Chile, United States and Colombia. Marco T. Núñez's co-authors include Miguel Arredondo, Natalia Mena, Victoria Tapia, Jonathan Glass, Pamela J. Urrutia, Pabla Aguirre, Cecilia Hidalgo, Christian González‐Billault, Andrés Esparza and Patricia Muñoz and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Neuroscience.

In The Last Decade

Marco T. Núñez

127 papers receiving 5.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco T. Núñez Chile 41 2.1k 1.8k 1.6k 932 733 127 5.7k
Urs V. Berger United States 42 3.4k 1.7× 2.1k 1.2× 4.0k 2.5× 706 0.8× 1.1k 1.4× 56 9.7k
Evan H. Morgan Australia 49 3.0k 1.5× 4.0k 2.2× 2.2k 1.3× 1.1k 1.2× 2.5k 3.4× 209 8.0k
Bryan Mackenzie United States 32 4.3k 2.1× 3.0k 1.7× 2.0k 1.2× 421 0.5× 1.4k 1.9× 60 7.9k
Jerome A. Roth United States 37 1.2k 0.6× 640 0.4× 1.3k 0.8× 452 0.5× 195 0.3× 121 4.6k
Darius J.R. Lane Australia 38 1.1k 0.5× 774 0.4× 2.1k 1.3× 407 0.4× 327 0.4× 72 4.5k
Joseph R. Prohaska United States 43 5.0k 2.4× 1.4k 0.8× 1.7k 1.0× 641 0.7× 264 0.4× 133 7.2k
Scott Ayton Australia 47 1.6k 0.8× 712 0.4× 3.0k 1.8× 2.6k 2.8× 265 0.4× 129 8.5k
Richard S. Eisenstein United States 34 1.5k 0.7× 1.9k 1.1× 2.2k 1.4× 447 0.5× 953 1.3× 64 4.8k
M C Kennedy United States 36 1.0k 0.5× 785 0.4× 3.0k 1.8× 545 0.6× 238 0.3× 68 5.9k
Yan‐Zhong Chang China 36 749 0.4× 858 0.5× 1.4k 0.9× 437 0.5× 452 0.6× 126 3.8k

Countries citing papers authored by Marco T. Núñez

Since Specialization
Citations

This map shows the geographic impact of Marco T. Núñez'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 Marco T. Núñez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco T. Núñez more than expected).

Fields of papers citing papers by Marco T. Núñez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco T. Núñez. 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 Marco T. Núñez. The network helps show where Marco T. Núñez may publish in the future.

Co-authorship network of co-authors of Marco T. Núñez

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

All Works

20 of 20 papers shown
1.
García‐Beltrán, Olimpo, Pamela J. Urrutia, & Marco T. Núñez. (2023). On the Chemical and Biological Characteristics of Multifunctional Compounds for the Treatment of Parkinson’s Disease. Antioxidants. 12(2). 214–214. 14 indexed citations
2.
Aguirre, Pabla, et al.. (2022). Calcium is a noncompetitive inhibitor of DMT1 on the intestinal iron absorption process: empirical evidence and mathematical modeling analysis. American Journal of Physiology-Cell Physiology. 323(6). C1791–C1806. 9 indexed citations
3.
Gerdtzen, Ziomara P., et al.. (2019). Mathematical modeling of the relocation of the divalent metal transporter DMT1 in the intestinal iron absorption process. PLoS ONE. 14(6). e0218123–e0218123. 8 indexed citations
4.
Urrutia, Pamela J., et al.. (2017). Cell death induced by mitochondrial complex I inhibition is mediated by Iron Regulatory Protein 1. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1863(9). 2202–2209. 29 indexed citations
5.
Aguirre, Pabla, et al.. (2016). Parkinson’s Disease: The Mitochondria-Iron Link. Parkinson s Disease. 2016. 1–21. 61 indexed citations
6.
Aguirre, Pabla, et al.. (2016). Neuroprotective Effect of a New 7,8-Dihydroxycoumarin-Based Fe2+/Cu2+ Chelator in Cell and Animal Models of Parkinson’s Disease. ACS Chemical Neuroscience. 8(1). 178–185. 38 indexed citations
7.
Mena, Natalia, et al.. (2015). Mitochondrial iron homeostasis and its dysfunctions in neurodegenerative disorders. Mitochondrion. 21. 92–105. 128 indexed citations
8.
Theil, Elizabeth C., Huijun Chen, Constanza Miranda, et al.. (2012). Absorption of Iron from Ferritin Is Independent of Heme Iron and Ferrous Salts in Women and Rat Intestinal Segments3. Journal of Nutrition. 142(3). 478–483. 84 indexed citations
9.
Muñoz, Pablo, et al.. (2011). Iron Mediates N-Methyl-d-aspartate Receptor-dependent Stimulation of Calcium-induced Pathways and Hippocampal Synaptic Plasticity. Journal of Biological Chemistry. 286(15). 13382–13392. 105 indexed citations
10.
11.
Garri, Carolina, et al.. (2008). Caco-2 Intestinal Epithelial Cells Absorb Soybean Ferritin by μ2 (AP2)-Dependent Endocytosis. Journal of Nutrition. 138(4). 659–666. 99 indexed citations
12.
Arredondo, Miguel, Ronny Martínez, Marco T. Núñez, Manuel Ruz, & Manuel Olivares. (2006). Inhibition of iron and copper uptake by iron, copper and zinc. Biological Research. 39(1). 95–102. 103 indexed citations
13.
Aracena-Parks, Paula, Pabla Aguirre, Pablo Muñoz, & Marco T. Núñez. (2006). Iron and glutathione at the crossroad of redox metabolism in neurons. Biological Research. 39(1). 157–65. 23 indexed citations
14.
Mena, Natalia, et al.. (2006). Iron dyshomeostasis in Parkinson’s disease. PubMed. 205–213. 24 indexed citations
15.
Arredondo, Miguel, Verónica Cambiazo, Lucı́a Tapia, et al.. (2004). Copper overload affects copper and iron metabolism in Hep-G2 cells. American Journal of Physiology-Gastrointestinal and Liver Physiology. 287(1). G27–G32. 37 indexed citations
16.
Rodríguez, Diego A., et al.. (2004). Ethanol increases tumor necrosis factor-alpha receptor-1 (TNF-R1) levels in hepatic, intestinal, and cardiac cells. Alcohol. 33(1). 9–15. 22 indexed citations
17.
Zambrano, Cristian A., José Tomás Egaña, Marco T. Núñez, Ricardo B. Maccioni, & Christian González‐Billault. (2004). Oxidative stress promotes τ dephosphorylation in neuronal cells: the roles of cdk5 and PP1. Free Radical Biology and Medicine. 36(11). 1393–1402. 73 indexed citations
18.
19.
Núñez, Marco T., et al.. (1991). Cl−, Na+, and H+ fluxes during the acidification of rabbit reticulocyte endocytic vesicles. Journal of Bioenergetics and Biomembranes. 23(1). 147–160. 8 indexed citations
20.
Núñez, Marco T., Inês Mendes Pinto, & Jonathan Glass. (1989). Assay and characteristics of the iron binding moiety of reticulocyte endocytic vesicles. The Journal of Membrane Biology. 107(2). 129–135. 21 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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