Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
TNF and Increased Intracellular Iron Alter Macrophage Polarization to a Detrimental M1 Phenotype in the Injured Spinal Cord
2014532 citationsAntje Kroner, Andrew D. Greenhalgh et al.Neuronprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Juan G. Zarruk
Since
Specialization
Citations
This map shows the geographic impact of Juan G. Zarruk'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 Juan G. Zarruk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Juan G. Zarruk more than expected).
This network shows the impact of papers produced by Juan G. Zarruk. 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 Juan G. Zarruk. The network helps show where Juan G. Zarruk may publish in the future.
Co-authorship network of co-authors of Juan G. Zarruk
This figure shows the co-authorship network connecting the top 25 collaborators of Juan G. Zarruk.
A scholar is included among the top collaborators of Juan G. Zarruk 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 Juan G. Zarruk. Juan G. Zarruk is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Díaz-Quijano, Fredi Alexander, et al.. (2013). Asociación entre factores socioeconómicos y mortalidad intrahospitalaria por accidente cerebrovascular isquémico en una cohorte hospitalaria de Colombia, 2003-2006. Intellectum (Universidad de La Sabana). 33(6). 439–444.9 indexed citations
9.
Díaz-Quijano, Fredi Alexander, et al.. (2013). [Correlation between socioeconomic factors and in-hospital mortality from ischemic stroke in a hospital cohort in Colombia, 2003-2006].. PubMed. 33(6). 439–44.1 indexed citations
10.
David, Samuel, Juan G. Zarruk, & Nader Ghasemlou. (2012). Inflammatory Pathways in Spinal Cord Injury. International review of neurobiology. 106. 127–152.73 indexed citations
López‐Jaramillo, Patricio, Federico Silva, Paul Anthony Camacho, et al.. (2006). Metabolic syndrome and pre-eclampsia: contributions realized by the research Institute of the Colombian Cardiovascular Foundation. Revista Colombiana de Cardiología. 13(2). 73–78.1 indexed citations
16.
Zarruk, Juan G., et al.. (2006). ÓXIDO NÍTRICO, FUNCIÓN ENDOTELIAL Y TRASTORNO DEPRESIVO MAYOR. Revista Med. 14(1). 19–26.1 indexed citations
17.
Zarruk, Juan G., et al.. (2006). Enfermedad cerebrovascular en Colombia. Revista Colombiana de Cardiología. 13(2). 85–89.25 indexed citations
Zarruk, Juan G., et al.. (2006). Estudio de correlación entre marcadores de inflamación y grosor íntima media carotídeo, en pacientes con ataque cerebrovascular isquémico Análisis submuestral del proyecto multicéntrico: prevalencia de factores de riesgo para enfermedad cerebrovascular isquémica aguda -estudio frec VI.
20.
Zarruk, Juan G., et al.. (2005). El papel del sistema serotoninérgico central en la etiopatogenia del síncope neurocardiogénico. Medunab. 8(3). 197–201.
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.