Gert Schaart

13.8k total citations · 3 hit papers
147 papers, 10.9k citations indexed

About

Gert Schaart is a scholar working on Physiology, Molecular Biology and Cell Biology. According to data from OpenAlex, Gert Schaart has authored 147 papers receiving a total of 10.9k indexed citations (citations by other indexed papers that have themselves been cited), including 94 papers in Physiology, 68 papers in Molecular Biology and 59 papers in Cell Biology. Recurrent topics in Gert Schaart's work include Adipose Tissue and Metabolism (82 papers), Muscle metabolism and nutrition (40 papers) and Diet and metabolism studies (21 papers). Gert Schaart is often cited by papers focused on Adipose Tissue and Metabolism (82 papers), Muscle metabolism and nutrition (40 papers) and Diet and metabolism studies (21 papers). Gert Schaart collaborates with scholars based in Netherlands, United States and Germany. Gert Schaart's co-authors include Patrick Schrauwen, Matthijs K. C. Hesselink, Joris Hoeks, Wouter D. van Marken Lichtenbelt, René Koopman, Lauren M. Sparks, Jang Hyun Choi, Pontus Boström, Kirsi A. Virtanen and Jun Wu and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.

In The Last Decade

Gert Schaart

146 papers receiving 10.8k citations

Hit Papers

align trajectories

What are hit papers?

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.

Beige Adipocytes Are a Distinct Type of Thermogenic Fat Cell in Mouse and Human

2012 2.6k citations Lauren M. Sparks, Gert Schaart et al. profile →
Short-term cold acclimation improves insulin sensitivity in patients with type 2 diabetes mellitus

2015 449 citations Joris Hoeks, Boudewijn Brans et al. profile →
The Bile Acid Chenodeoxycholic Acid Increases Human Brown Adipose Tissue Activity

2015 343 citations Evie P. M. Broeders, Emmani B. M. Nascimento et al. Cell Metabolism profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gert Schaart Netherlands	50	6.9k	3.9k	2.5k	2.4k	1.5k	147	10.9k
Francesc Villarroya Spain	64	8.2k 1.2×	6.2k 1.6×	4.6k 1.8×	1.2k 0.5×	1.9k 1.3×	308	15.3k
P. Darrell Neufer United States	59	6.2k 0.9×	5.3k 1.4×	1.1k 0.4×	2.9k 1.2×	1.1k 0.7×	142	11.2k
Yu‐Hua Tseng United States	50	10.5k 1.5×	4.7k 1.2×	5.6k 2.2×	1.6k 0.7×	2.6k 1.7×	139	15.1k
Hua Tu China	27	6.0k 0.9×	4.1k 1.1×	3.7k 1.5×	953 0.4×	1.1k 0.7×	86	12.1k
S. Russ Price United States	46	4.4k 0.6×	5.8k 1.5×	988 0.4×	2.2k 0.9×	1.3k 0.8×	128	11.1k
Zhidan Wu United States	35	11.0k 1.6×	11.7k 3.0×	3.7k 1.5×	1.7k 0.7×	874 0.6×	55	18.1k
Paul Cohen United States	48	7.2k 1.1×	3.8k 1.0×	4.4k 1.8×	916 0.4×	1.6k 1.1×	83	12.7k
Wenli Yang China	33	5.1k 0.7×	5.7k 1.5×	2.2k 0.9×	836 0.4×	744 0.5×	100	10.7k
Christian Wolfrum Switzerland	50	4.5k 0.7×	5.2k 1.3×	2.8k 1.1×	714 0.3×	1.2k 0.8×	198	10.9k

Countries citing papers authored by Gert Schaart

Since Specialization

Citations

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

Fields of papers citing papers by Gert Schaart

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gert Schaart

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

All Works

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20 of 20 papers shown

Veeraiah, Pandichelvam, Rubén Zapata‐Pérez, Esther Phielix, et al.. (2025). Carnitine supplementation improves insulin sensitivity and skeletal muscle acetylcarnitine formation in patients with type 2 diabetes. Diabetes Obesity and Metabolism. 27(5). 2864–2877. 2 indexed citations

Vanweert, Froukje, Juho Raiko, Gert Schaart, et al.. (2023). The tissue‐specific metabolic effects of the PPARα agonist ciprofibrate in insulin‐resistant male individuals: a double‐blind, randomized, placebo‐controlled crossover study. Obesity. 31(10). 2493–2504.

Bruls, Yvonne M. H., Froukje Vanweert, Ciarán E. Fealy, et al.. (2023). Effect of β2-agonist treatment on insulin-stimulated peripheral glucose disposal in healthy men in a randomised placebo-controlled trial. Nature Communications. 14(1). 173–173. 9 indexed citations

Schrauwen‐Hinderling, Vera B., Johanna A. Jörgensen, Gert Schaart, et al.. (2023). PCr/ATP ratios and mitochondrial function in the heart. A comparative study in humans. Scientific Reports. 13(1). 8346–8346. 9 indexed citations

Gemmink, Anne, Marlies de Ligt, Esther Kornips, et al.. (2022). Effects of SGLT2 inhibitor dapagliflozin in patients with type 2 diabetes on skeletal muscle cellular metabolism. Molecular Metabolism. 66. 101620–101620. 28 indexed citations

Ligt, Marlies de, Julian Mevenkamp, Johanna A. Jörgensen, et al.. (2022). Effects of the sodium-glucose cotransporter 2 inhibitor dapagliflozin on substrate metabolism in prediabetic insulin resistant individuals: A randomized, double-blind crossover trial. Metabolism. 140. 155396–155396. 27 indexed citations

Remie, Carlijn M. E., Kay H. M. Roumans, Emmani B. M. Nascimento, et al.. (2021). Metabolic responses to mild cold acclimation in type 2 diabetes patients. Nature Communications. 12(1). 1516–1516. 20 indexed citations

Grevendonk, Lotte, Niels J. Connell, Christopher McCrum, et al.. (2021). Impact of aging and exercise on skeletal muscle mitochondrial capacity, energy metabolism, and physical function. Nature Communications. 12(1). 4773–4773. 147 indexed citations

Zacharewicz, Evelyn, Marlies de Ligt, Silvie Timmers, et al.. (2021). Resveratrol‐induced remodelling of myocellular lipid stores: A study in metabolically compromised humans. Physiological Reports. 9(2). e14692–e14692. 8 indexed citations

10.

Phielix, Esther, Paul Begovatz, Sofiya Gancheva, et al.. (2019). Athletes feature greater rates of muscle glucose transport and glycogen synthesis during lipid infusion. JCI Insight. 4(21). 8 indexed citations

11.

Nascimento, Emmani B. M., Maurice Konings, Gert Schaart, et al.. (2019). In vitro effects of sitosterol and sitostanol on mitochondrial respiration in human brown adipocytes, myotubes and hepatocytes. European Journal of Nutrition. 59(5). 2039–2045. 8 indexed citations

12.

Broeders, Evie P. M., Emmani B. M. Nascimento, Bas Havekes, et al.. (2015). The Bile Acid Chenodeoxycholic Acid Increases Human Brown Adipose Tissue Activity. Cell Metabolism. 22(3). 418–426. 343 indexed citations breakdown →

13.

Bosma, Madeleen, Matthijs K. C. Hesselink, Lauren M. Sparks, et al.. (2012). Perilipin 2 Improves Insulin Sensitivity in Skeletal Muscle Despite Elevated Intramuscular Lipid Levels. Diabetes. 61(11). 2679–2690. 123 indexed citations

14.

Smeele, Kirsten M., Otto Eerbeek, Anneke Koeman, et al.. (2010). Partial hexokinase II knockout results in acute ischemia–reperfusion damage in skeletal muscle of male, but not female, mice. Pflügers Archiv - European Journal of Physiology. 459(5). 705–712. 8 indexed citations

15.

Bosch, Johan de Vogel‐van den, Joris Hoeks, Silvie Timmers, et al.. (2010). The Effects of Long‐ or Medium‐Chain Fat Diets on Glucose Tolerance and Myocellular Content of Lipid Intermediates in Rats. Obesity. 19(4). 792–799. 18 indexed citations

16.

Smit, Egbert F., Ronny Mohren, Mark V. Boekschoten, et al.. (2009). An 8-Week High-Fat Diet Induces Obesity and Insulin Resistance with Small Changes in the Muscle Transcriptome of C57BL/6J Mice. Lifestyle Genomics. 2(6). 280–291. 36 indexed citations

17.

Remels, A.H.V., Ramon Langen, Patrick Schrauwen, et al.. (2009). Regulation of mitochondrial biogenesis during myogenesis. Molecular and Cellular Endocrinology. 315(1-2). 113–120. 132 indexed citations

18.

Drost, Maarten R., Gert Schaart, Paul van Dijk, et al.. (2007). Both type 1 and type 2a muscle fibers can respond to enzyme therapy in Pompe disease. Muscle & Nerve. 37(2). 251–255. 19 indexed citations

19.

Verdijk, Lex B., René Koopman, Gert Schaart, et al.. (2006). Satellite cell content is specifically reduced in type II skeletal muscle fibers in the elderly. American Journal of Physiology-Endocrinology and Metabolism. 292(1). E151–E157. 377 indexed citations

20.

Hesselink, Matthijs K. C., Gert Schaart, Esther Moonen‐Kornips, et al.. (2004). DGAT1 overexpression in muscle by in vivo DNA electroporation increases intramyocellular lipid content. Journal of Lipid Research. 46(2). 230–236. 40 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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