Daniel Gonzalez‐Mañán

818 total citations
18 papers, 732 citations indexed

About

Daniel Gonzalez‐Mañán is a scholar working on Nutrition and Dietetics, Epidemiology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Daniel Gonzalez‐Mañán has authored 18 papers receiving a total of 732 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Nutrition and Dietetics, 11 papers in Epidemiology and 6 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Daniel Gonzalez‐Mañán's work include Fatty Acid Research and Health (12 papers), Liver Disease Diagnosis and Treatment (10 papers) and Cholesterol and Lipid Metabolism (5 papers). Daniel Gonzalez‐Mañán is often cited by papers focused on Fatty Acid Research and Health (12 papers), Liver Disease Diagnosis and Treatment (10 papers) and Cholesterol and Lipid Metabolism (5 papers). Daniel Gonzalez‐Mañán collaborates with scholars based in Chile, United Kingdom and Argentina. Daniel Gonzalez‐Mañán's co-authors include Alejandra Espinosa, Luis A. Videla, Rodrigo Valenzuela, Gladys Tapia, Francisca Echeverría, Amanda D’Espessailles, Paola Illesca, Macarena Ortíz, Andrés Bustamante and Nalda Romero and has published in prestigious journals such as PLoS ONE, Free Radical Biology and Medicine and Journal of Nutrition.

In The Last Decade

Daniel Gonzalez‐Mañán

18 papers receiving 721 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Gonzalez‐Mañán Chile 13 319 236 212 207 166 18 732
Paola Illesca Argentina 13 310 1.0× 213 0.9× 260 1.2× 277 1.3× 182 1.1× 20 886
Sandra Soto-Alarcón Chile 8 214 0.7× 126 0.5× 151 0.7× 189 0.9× 121 0.7× 12 575
Lourdes M. Varela Spain 18 144 0.5× 214 0.9× 264 1.2× 174 0.8× 118 0.7× 27 940
M. Cassader Italy 4 561 1.8× 54 0.2× 237 1.1× 255 1.2× 293 1.8× 4 904
Jale Balkan Türkiye 15 132 0.4× 110 0.5× 140 0.7× 236 1.1× 76 0.5× 25 787
José Manuel Lou-Bonafonte Spain 14 92 0.3× 90 0.4× 220 1.0× 83 0.4× 247 1.5× 24 823
Inhae Kang South Korea 13 151 0.5× 105 0.4× 313 1.5× 216 1.0× 77 0.5× 26 766
Arthur D. Hartman United States 15 200 0.6× 143 0.6× 199 0.9× 276 1.3× 108 0.7× 31 805
Guangjie Wu China 16 144 0.5× 88 0.4× 522 2.5× 128 0.6× 161 1.0× 36 959
Sookyoung Jeon United States 13 257 0.8× 104 0.4× 265 1.3× 105 0.5× 163 1.0× 29 852

Countries citing papers authored by Daniel Gonzalez‐Mañán

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Gonzalez‐Mañán

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Gonzalez‐Mañán. 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 Daniel Gonzalez‐Mañán. The network helps show where Daniel Gonzalez‐Mañán may publish in the future.

Co-authorship network of co-authors of Daniel Gonzalez‐Mañán

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Gonzalez‐Mañán. A scholar is included among the top collaborators of Daniel Gonzalez‐Mañán 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 Daniel Gonzalez‐Mañán. Daniel Gonzalez‐Mañán 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
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Barrera, Cynthia, Rodrigo Valenzuela, Miguel Ángel Rincón‐Cervera, et al.. (2020). Iron-induced derangement in hepatic Δ-5 and Δ-6 desaturation capacity and fatty acid profile leading to steatosis: Impact on extrahepatic tissues and prevention by antioxidant-rich extra virgin olive oil. Prostaglandins Leukotrienes and Essential Fatty Acids. 153. 102058–102058. 16 indexed citations
3.
Soto-Alarcón, Sandra, Macarena Ortíz, Francisca Echeverría, et al.. (2019). Docosahexaenoic acid and hydroxytyrosol co‐administration fully prevents liver steatosis and related parameters in mice subjected to high‐fat diet: A molecular approach. BioFactors. 45(6). 930–943. 48 indexed citations
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Echeverría, Francisca, Rodrigo Valenzuela, Alejandra Espinosa, et al.. (2018). Reduction of high-fat diet-induced liver proinflammatory state by eicosapentaenoic acid plus hydroxytyrosol supplementation: involvement of resolvins RvE1/2 and RvD1/2. The Journal of Nutritional Biochemistry. 63. 35–43. 95 indexed citations
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Barrera, Cynthia, Rodrigo Valenzuela, Miguel Ángel Rincón‐Cervera, et al.. (2018). Molecular mechanisms related to the hepatoprotective effects of antioxidant-rich extra virgin olive oil supplementation in rats subjected to short-term iron administration. Free Radical Biology and Medicine. 126. 313–321. 48 indexed citations
8.
Gonzalez‐Mañán, Daniel, et al.. (2018). Anti-oxidative and anti-inflammatory effects of Rosa Mosqueta oil supplementation in rat liver ischemia-reperfusion. Food & Function. 9(9). 4847–4857. 15 indexed citations
9.
Gonzalez‐Mañán, Daniel, et al.. (2017). Rosa Mosqueta Oil Prevents Oxidative Stress and Inflammation through the Upregulation of PPAR-α and NRF2 in C57BL/6J Mice Fed a High-Fat Diet. Journal of Nutrition. 147(4). 579–588. 34 indexed citations
10.
Espinosa, Alejandra, et al.. (2017). Effects of rosa mosqueta oil supplementation in lipogenic markers associated with prevention of liver steatosis. Food & Function. 8(2). 832–841. 10 indexed citations
11.
Hernández‐Rodas, María Catalina, Rodrigo Valenzuela, Francisca Echeverría, et al.. (2017). Supplementation with Docosahexaenoic Acid and Extra Virgin Olive Oil Prevents Liver Steatosis Induced by a High‐Fat Diet in Mice through PPAR‐α and Nrf2 Upregulation with Concomitant SREBP‐1c and NF‐kB Downregulation. Molecular Nutrition & Food Research. 61(12). 116 indexed citations
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Tapia, Gladys, et al.. (2016). n-3 LCPUFA in the reversal of hepatic steatosis: the role of ACOX and CAT-1. Grasas y Aceites. 67(2). e134–e134. 1 indexed citations
14.
D’Espessailles, Amanda, et al.. (2015). Dietary Rosa mosqueta (Rosa rubiginosa) oil prevents high diet-induced hepatic steatosis in mice. Food & Function. 6(9). 3109–3116. 10 indexed citations
15.
Tapia, Gladys, Rodrigo Valenzuela, Alejandra Espinosa, et al.. (2014). N-3long-chain PUFA supplementation prevents high fat diet induced mouse liver steatosis and inflammation in relation to PPAR-α upregulation and NF-κB DNA binding abrogation. Molecular Nutrition & Food Research. 58(6). 1333–1341. 79 indexed citations
16.
Valenzuela, Rodrigo, Alejandra Espinosa, Daniel Gonzalez‐Mañán, et al.. (2012). N-3 Long-Chain Polyunsaturated Fatty Acid Supplementation Significantly Reduces Liver Oxidative Stress in High Fat Induced Steatosis. PLoS ONE. 7(10). e46400–e46400. 93 indexed citations
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Espinosa, Alejandra, et al.. (2005). Prevention of liver steatosis through fish oil supplementation: correlation of oxidative stress with insulin resistance and liver fatty acid content. Archivos Latinoamericanos de Nutrición. 63(1). 29–36. 11 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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