Donato A. Rivas

2.3k total citations
50 papers, 1.6k citations indexed

About

Donato A. Rivas is a scholar working on Physiology, Molecular Biology and Cell Biology. According to data from OpenAlex, Donato A. Rivas has authored 50 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Physiology, 25 papers in Molecular Biology and 16 papers in Cell Biology. Recurrent topics in Donato A. Rivas's work include Adipose Tissue and Metabolism (28 papers), Muscle metabolism and nutrition (14 papers) and Muscle Physiology and Disorders (12 papers). Donato A. Rivas is often cited by papers focused on Adipose Tissue and Metabolism (28 papers), Muscle metabolism and nutrition (14 papers) and Muscle Physiology and Disorders (12 papers). Donato A. Rivas collaborates with scholars based in United States, Australia and Brazil. Donato A. Rivas's co-authors include Roger A. Fielding, Sarah J. Lessard, John A. Hawley, Ben B. Yaspelkis, Lee M. Margolis, Maurício Morais, Nicholas Rice, Lisa Ceglia, Laurie J. Goodyear and Bess Dawson‐Hughes and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Donato A. Rivas

49 papers receiving 1.6k citations

Peers

Donato A. Rivas
Donato A. Rivas
Citations per year, relative to Donato A. Rivas Donato A. Rivas (= 1×) peers João Pedro Werneck‐de‐Castro

Countries citing papers authored by Donato A. Rivas

Since Specialization
Citations

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

Fields of papers citing papers by Donato A. Rivas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Donato A. Rivas. 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 Donato A. Rivas. The network helps show where Donato A. Rivas may publish in the future.

Co-authorship network of co-authors of Donato A. Rivas

This figure shows the co-authorship network connecting the top 25 collaborators of Donato A. Rivas. A scholar is included among the top collaborators of Donato A. Rivas 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 Donato A. Rivas. Donato A. Rivas 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.
Rocha, Alisson L. da, Ana P. Pinto, Ivo Vieira de Sousa Neto, et al.. (2025). Exhaustive exercise abolishes REV‐ERB‐α circadian rhythm and shifts the kynurenine pathway to a neurotoxic profile in mice. The Journal of Physiology. 603(14). 3923–3944. 1 indexed citations
2.
Pinto, Ana P., Ivo Vieira de Sousa Neto, José Rodrigo Pauli, et al.. (2024). The role of interleukin-10 in mitigating endoplasmic reticulum stress in aged mice through exercise. American Journal of Physiology-Endocrinology and Metabolism. 327(3). E384–E395. 2 indexed citations
3.
Pinto, Ana P., Vítor Rosetto Muñoz, Luciane C. Alberici, et al.. (2022). Combined physical exercise reverses the reduced expression of Bmal1 in the liver of aged mice. Life Sciences. 312. 121175–121175. 9 indexed citations
4.
Pinto, Ana P., Vítor Rosetto Muñoz, Alisson L. da Rocha, et al.. (2022). IL-6 deletion decreased REV-ERBα protein and influenced autophagy and mitochondrial markers in the skeletal muscle after acute exercise. Frontiers in Immunology. 13. 953272–953272. 9 indexed citations
5.
Ceglia, Lisa, Donato A. Rivas, Mathias Schlögl, et al.. (2022). Effect of vitamin D3 vs. calcifediol on VDR concentration and fiber size in skeletal muscle. Journal of Bone and Mineral Metabolism. 41(1). 41–51. 3 indexed citations
6.
Lessard, Sarah J., Tara MacDonald, Myoung Sook Han, et al.. (2018). JNK regulates muscle remodeling via myostatin/SMAD inhibition. Nature Communications. 9(1). 3030–3030. 80 indexed citations
7.
Margolis, Lee M. & Donato A. Rivas. (2018). Potential Role of MicroRNA in the Anabolic Capacity of Skeletal Muscle With Aging. Exercise and Sport Sciences Reviews. 46(2). 86–91. 26 indexed citations
8.
Margolis, Lee M., et al.. (2016). Circulating MicroRNA Are Predictive of Aging and Acute Adaptive Response to Resistance Exercise in Men. The Journals of Gerontology Series A. 72(10). glw243–glw243. 69 indexed citations
9.
Margolis, Lee M., Donato A. Rivas, Andrew Young, et al.. (2016). Prolonged Calorie Restriction Downregulates Skeletal Muscle mTORC1 Signaling Independent of Dietary Protein Intake and Associated microRNA Expression. Frontiers in Physiology. 7. 445–445. 34 indexed citations
10.
Margolis, Lee M. & Donato A. Rivas. (2014). Implications of Exercise Training and Distribution of Protein Intake on Molecular Processes Regulating Skeletal Muscle Plasticity. Calcified Tissue International. 96(3). 211–221. 9 indexed citations
11.
Ceglia, Lisa, Donato A. Rivas, Rachele Pojednic, et al.. (2013). Effects of alkali supplementation and vitamin D insufficiency on rat skeletal muscle. Endocrine. 44(2). 454–464. 13 indexed citations
12.
Ceglia, Lisa, Sathit Niramitmahapanya, Maurício Morais, et al.. (2013). A Randomized Study on the Effect of Vitamin D3Supplementation on Skeletal Muscle Morphology and Vitamin D Receptor Concentration in Older Women. The Journal of Clinical Endocrinology & Metabolism. 98(12). E1927–E1935. 196 indexed citations
13.
Rivas, Donato A., et al.. (2012). Role and potential mechanisms of anabolic resistance in sarcopenia. Journal of Cachexia Sarcopenia and Muscle. 3(3). 157–162. 123 indexed citations
14.
Rivas, Donato A., et al.. (2011). Lipogenic regulators are elevated with age and chronic overload in rat skeletal muscle. Acta Physiologica. 202(4). 691–701. 18 indexed citations
15.
Yaspelkis, Ben B., et al.. (2010). Aerobic training reverses high-fat diet-induced pro-inflammatory signalling in rat skeletal muscle. European Journal of Applied Physiology. 110(4). 779–788. 5 indexed citations
16.
Rivas, Donato A., Ben B. Yaspelkis, John A. Hawley, & Sarah J. Lessard. (2009). Lipid-induced mTOR activation in rat skeletal muscle reversed by exercise and 5′-aminoimidazole-4-carboxamide-1-β-d-ribofuranoside. Journal of Endocrinology. 202(3). 441–451. 50 indexed citations
17.
Yeo, Wee Kian, Sarah J. Lessard, Zhiping Chen, et al.. (2008). Fat adaptation followed by carbohydrate restoration increases AMPK activity in skeletal muscle from trained humans. Journal of Applied Physiology. 105(5). 1519–1526. 54 indexed citations
18.
Bernard, Jeffrey R., et al.. (2006). High-fat feeding effects on components of the CAP/Cbl signaling cascade in Sprague-Dawley rat skeletal muscle. Metabolism. 55(2). 203–212. 10 indexed citations
19.
Bernard, Jeffrey R., et al.. (2005). Chronic aerobic exercise enhances components of the classical and novel insulin signalling cascades in Sprague–Dawley rat skeletal muscle. Acta Physiologica Scandinavica. 183(4). 357–366. 12 indexed citations
20.
Bernard, Jeffrey R., et al.. (2005). Insulin‐stimulated plasma membrane association and activation of Akt2, aPKC ζ and aPKC λ in high fat fed rodent skeletal muscle. The Journal of Physiology. 565(2). 627–636. 12 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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