C. M. Donovan

3.0k total citations
56 papers, 2.5k citations indexed

About

C. M. Donovan is a scholar working on Physiology, Surgery and Molecular Biology. According to data from OpenAlex, C. M. Donovan has authored 56 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Physiology, 19 papers in Surgery and 17 papers in Molecular Biology. Recurrent topics in C. M. Donovan's work include Muscle metabolism and nutrition (17 papers), Adipose Tissue and Metabolism (15 papers) and Pancreatic function and diabetes (15 papers). C. M. Donovan is often cited by papers focused on Muscle metabolism and nutrition (17 papers), Adipose Tissue and Metabolism (15 papers) and Pancreatic function and diabetes (15 papers). C. M. Donovan collaborates with scholars based in United States, Poland and Canada. C. M. Donovan's co-authors include George A. Brooks, Richard N. Bergman, Alan G. Watts, Michael J. Pagliassotti, Andrea L. Hevener, Kelvin J.A. Davies, Ken D. Sumida, Jeffrey B. Halter, Satoshi Fujita and Maziyar Saberi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Diabetes and Journal of Applied Physiology.

In The Last Decade

C. M. Donovan

53 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
C. M. Donovan United States 27 840 656 607 583 560 56 2.5k
Paige C. Geiger United States 33 1.7k 2.0× 311 0.5× 287 0.5× 554 1.0× 1.6k 2.9× 73 3.3k
Abram Katz Sweden 35 1.6k 1.9× 397 0.6× 128 0.2× 1.0k 1.7× 1.7k 3.1× 117 4.0k
Jeffrey W. Ryder United States 29 1.4k 1.6× 519 0.8× 127 0.2× 508 0.9× 1.6k 2.9× 47 2.9k
R. Favier France 25 831 1.0× 94 0.1× 282 0.5× 524 0.9× 565 1.0× 75 2.0k
Akihiko Ishihara Japan 32 1.5k 1.7× 176 0.3× 133 0.2× 516 0.9× 1.4k 2.4× 165 3.0k
J. M. Overton United States 32 1.3k 1.5× 381 0.6× 1.1k 1.8× 142 0.2× 568 1.0× 74 3.3k
Mary G. Garry United States 33 1.0k 1.2× 565 0.9× 418 0.7× 225 0.4× 1.2k 2.1× 88 3.5k
M. H. Laughlin United States 33 1.1k 1.3× 281 0.4× 82 0.1× 327 0.6× 528 0.9× 93 3.3k
Francisco H. Andrade United States 28 808 1.0× 184 0.3× 120 0.2× 326 0.6× 1.4k 2.5× 66 2.7k
Kenneth A. Dyar Germany 18 1.7k 2.0× 135 0.2× 842 1.4× 487 0.8× 1.7k 3.1× 30 3.3k

Countries citing papers authored by C. M. Donovan

Since Specialization
Citations

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

Fields of papers citing papers by C. M. Donovan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. M. Donovan. 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 C. M. Donovan. The network helps show where C. M. Donovan may publish in the future.

Co-authorship network of co-authors of C. M. Donovan

This figure shows the co-authorship network connecting the top 25 collaborators of C. M. Donovan. A scholar is included among the top collaborators of C. M. Donovan 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 C. M. Donovan. C. M. Donovan 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.
Sumida, Ken D., et al.. (2024). Enhanced glucose production in norepinephrine and palmitate stimulated hepatocytes following endurance training. Frontiers in Physiology. 15. 1514082–1514082.
2.
3.
Donovan, C. M. & Alan G. Watts. (2014). Peripheral and Central Glucose Sensing In Hypoglycemic Detection. Physiology. 29(5). 314–324. 66 indexed citations
4.
Oh, Young Taek, et al.. (2011). Continuous 24-h nicotinic acid infusion in rats causes FFA rebound and insulin resistance by altering gene expression and basal lipolysis in adipose tissue. American Journal of Physiology-Endocrinology and Metabolism. 300(6). E1012–E1021. 31 indexed citations
5.
Watts, Alan G. & C. M. Donovan. (2009). Sweet talk in the brain: Glucosensing, neural networks, and hypoglycemic counterregulation. Frontiers in Neuroendocrinology. 31(1). 32–43. 139 indexed citations
6.
Matveyenko, Aleksey V., et al.. (2007). Portal vein hypoglycemia is essential for full induction of hypoglycemia-associated autonomic failure with slow-onset hypoglycemia. American Journal of Physiology-Endocrinology and Metabolism. 293(3). E857–E864. 19 indexed citations
7.
Fujita, Satoshi, et al.. (2007). Hypoglycemic detection at the portal vein is mediated by capsaicin-sensitive primary sensory neurons. American Journal of Physiology-Endocrinology and Metabolism. 293(1). E96–E101. 42 indexed citations
8.
Sumida, Ken D., et al.. (2005). Impact of flow rate on lactate uptake and gluconeogenesis in glucagon-stimulated perfused livers. American Journal of Physiology-Endocrinology and Metabolism. 290(1). E185–E191. 9 indexed citations
9.
Sumida, Ken D., et al.. (2005). Lactate delivery (not oxygen) limits hepatic gluconeogenesis when blood flow is reduced. American Journal of Physiology-Endocrinology and Metabolism. 290(1). E192–E198. 7 indexed citations
10.
Sumida, Ken D., et al.. (2004). Effect of Endurance Training and Fasting on Renal Gluconeogenic Enzymes in the Rat. International Journal of Sport Nutrition and Exercise Metabolism. 14(3). 323–332. 3 indexed citations
11.
Hevener, Andrea L., Richard N. Bergman, & C. M. Donovan. (2001). Hypoglycemic Detection Does Not Occur in the Hepatic Artery or Liver. Diabetes. 50(2). 399–403. 47 indexed citations
12.
Donovan, C. M. & Michael J. Pagliassotti. (2000). Quantitative assessment of pathways for lactate disposal in skeletal muscle fiber types. Medicine & Science in Sports & Exercise. 32(4). 772–777. 53 indexed citations
13.
Donovan, C. M. & Ken D. Sumida. (1997). Training enhanced hepatic gluconeogenesis: the importance for glucose homeostasis during exercise. Medicine & Science in Sports & Exercise. 29(5). 628–634. 23 indexed citations
14.
Sumida, Ken D., et al.. (1995). Training suppresses hepatic lactate dehydrogenase activity without altering the isoenzyme profile. Medicine & Science in Sports & Exercise. 27(4). 507???511–507???511. 5 indexed citations
15.
Sumida, Ken D., et al.. (1993). 795 HEPATIC LDH ACTIVITY AND ISOENZYME PATTERNS FOLLOWING ENDURANCE TRAINING. Medicine & Science in Sports & Exercise. 25(Supplement). S142–S142. 1 indexed citations
16.
Donovan, C. M., Patricia Cane, & Richard N. Bergman. (1991). Search for the Hypoglycemia Receptor Using the Local Irrigation Approach. Advances in experimental medicine and biology. 291. 185–196. 14 indexed citations
17.
Donovan, C. M., et al.. (1991). Importance of hepatic glucoreceptors in sympathoadrenal response to hypoglycemia. Diabetes. 40(1). 155–158. 20 indexed citations
18.
Pagliassotti, Michael J. & C. M. Donovan. (1990). Role of cell type in net lactate removal by skeletal muscle. American Journal of Physiology-Endocrinology and Metabolism. 258(4). E635–E642. 46 indexed citations
19.
Donovan, C. M. & John A. Faulkner. (1987). Plasticity of skeletal muscle: regenerating fibers adapt more rapidly than surviving fibers. Journal of Applied Physiology. 62(6). 2507–2511. 26 indexed citations
20.
Donovan, C. M. & George A. Brooks. (1983). Endurance training affects lactate clearance, not lactate production. American Journal of Physiology-Endocrinology and Metabolism. 244(1). E83–E92. 296 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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