Nishanth E. Sunny

3.8k total citations · 2 hit papers
47 papers, 3.0k citations indexed

About

Nishanth E. Sunny is a scholar working on Epidemiology, Physiology and Molecular Biology. According to data from OpenAlex, Nishanth E. Sunny has authored 47 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Epidemiology, 22 papers in Physiology and 16 papers in Molecular Biology. Recurrent topics in Nishanth E. Sunny's work include Liver Disease Diagnosis and Treatment (30 papers), Diet, Metabolism, and Disease (15 papers) and Adipose Tissue and Metabolism (13 papers). Nishanth E. Sunny is often cited by papers focused on Liver Disease Diagnosis and Treatment (30 papers), Diet, Metabolism, and Disease (15 papers) and Adipose Tissue and Metabolism (13 papers). Nishanth E. Sunny collaborates with scholars based in United States, Spain and Australia. Nishanth E. Sunny's co-authors include Shawn C. Burgess, Jeffrey D. Browning, Kenneth Cusi, Fernando Bril, Elizabeth J. Parks, Santhosh Satapati, Xiaorong Fu, B.J. Bequette, TianTeng He and Blanka Kucejová and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Cell Metabolism.

In The Last Decade

Nishanth E. Sunny

44 papers receiving 3.0k citations

Hit Papers

Excessive Hepatic Mitochondrial TCA Cycle and Gluconeogen... 2011 2026 2016 2021 2011 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nishanth E. Sunny United States 25 1.7k 1.1k 957 891 377 47 3.0k
Santhosh Satapati United States 18 1.0k 0.6× 1.3k 1.1× 687 0.7× 1.0k 1.1× 404 1.1× 22 2.6k
Gustavo Castaño Argentina 26 2.1k 1.2× 940 0.8× 1.0k 1.0× 472 0.5× 303 0.8× 45 3.2k
Carine Beysen United States 22 707 0.4× 586 0.5× 644 0.7× 591 0.7× 257 0.7× 35 2.0k
Shunhei Yamashina Japan 29 1.7k 1.0× 902 0.8× 418 0.4× 315 0.4× 331 0.9× 70 3.2k
Shi Qi Yang United States 18 2.0k 1.1× 954 0.8× 686 0.7× 639 0.7× 699 1.9× 20 3.2k
Chantal A. Rivera United States 23 1.4k 0.8× 744 0.6× 411 0.4× 443 0.5× 234 0.6× 28 2.4k
Susanne Schuster Germany 20 1.1k 0.6× 977 0.9× 276 0.3× 398 0.4× 234 0.6× 27 2.5k
Alexandra Montagner France 30 638 0.4× 1.4k 1.3× 415 0.4× 660 0.7× 261 0.7× 47 2.8k
Tim Rolph United States 25 795 0.5× 1.4k 1.2× 477 0.5× 535 0.6× 298 0.8× 43 2.6k
Ming Yin United States 24 1.3k 0.7× 1.0k 0.9× 377 0.4× 263 0.3× 297 0.8× 36 3.1k

Countries citing papers authored by Nishanth E. Sunny

Since Specialization
Citations

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

Fields of papers citing papers by Nishanth E. Sunny

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nishanth E. Sunny. 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 Nishanth E. Sunny. The network helps show where Nishanth E. Sunny may publish in the future.

Co-authorship network of co-authors of Nishanth E. Sunny

This figure shows the co-authorship network connecting the top 25 collaborators of Nishanth E. Sunny. A scholar is included among the top collaborators of Nishanth E. Sunny 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 Nishanth E. Sunny. Nishanth E. Sunny 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.
Beckett, Linda M., Emma Shelton, Andrew F. Hill, et al.. (2025). Fluxomics combined with shotgun proteomics reveals a differential response of bovine kidney cells to extracellular palmitic and α-linolenic acid. Physiological Genomics. 57(3). 195–216.
3.
Beckett, Linda M., Nishanth E. Sunny, R.C. Neves, et al.. (2024). Long-chain fatty acids mediate hepatic metabolic flux in preruminating dairy calves fed flaxseed oil, high oleic soybean oil, or milk fat. Journal of Dairy Science. 107(10). 7932–7950. 2 indexed citations
6.
Sunny, Nishanth E., et al.. (2023). Feeding medium-chain fatty acid-rich formula causes liver steatosis and alters hepatic metabolism in neonatal pigs. American Journal of Physiology-Gastrointestinal and Liver Physiology. 325(2). G135–G146. 4 indexed citations
7.
Liu, Hsiao‐Ching, et al.. (2022). Remodeling of Hepatocyte Mitochondrial Metabolism and De Novo Lipogenesis During the Embryonic-to-Neonatal Transition in Chickens. Frontiers in Physiology. 13. 870451–870451. 5 indexed citations
8.
El‐Kadi, Samer W., et al.. (2019). Lipid Intake Enhances Muscle Growth But Does Not Influence Glucose Kinetics in 3-Week-Old Low-Birth-Weight Neonatal Pigs. Journal of Nutrition. 149(6). 933–941. 4 indexed citations
9.
10.
Cusi, Kenneth, Fernando Bril, Diana Barb, et al.. (2018). Effect of canagliflozin treatment on hepatic triglyceride content and glucose metabolism in patients with type 2 diabetes. Diabetes Obesity and Metabolism. 21(4). 812–821. 137 indexed citations
11.
Kalavalapalli, Srilaxmi, Fernando Bril, Jeremy P. Koelmel, et al.. (2018). Pioglitazone improves hepatic mitochondrial function in a mouse model of nonalcoholic steatohepatitis. American Journal of Physiology-Endocrinology and Metabolism. 315(2). E163–E173. 55 indexed citations
12.
Patterson, R. E., Alexander Kirpich, Jeremy P. Koelmel, et al.. (2017). Improved experimental data processing for UHPLC–HRMS/MS lipidomics applied to nonalcoholic fatty liver disease. Metabolomics. 13(11). 38 indexed citations
13.
Satapati, Santhosh, Nishanth E. Sunny, Blanka Kucejová, et al.. (2012). Elevated TCA cycle function in the pathology of diet-induced hepatic insulin resistance and fatty liver. Journal of Lipid Research. 53(6). 1080–1092. 311 indexed citations
14.
Sunny, Nishanth E., Elizabeth J. Parks, Jeffrey D. Browning, & Shawn C. Burgess. (2011). Excessive Hepatic Mitochondrial TCA Cycle and Gluconeogenesis in Humans with Nonalcoholic Fatty Liver Disease. Cell Metabolism. 14(6). 804–810. 497 indexed citations breakdown →
15.
Sunny, Nishanth E. & B.J. Bequette. (2011). Glycerol is a major substrate for glucose, glycogen, and nonessential amino acid synthesis in late-term chicken embryos1,2,3. Journal of Animal Science. 89(12). 3945–3953. 24 indexed citations
16.
Potthoff, Matthew J., Mihwa Choi, TianTeng He, et al.. (2011). FGF15/19 Regulates Hepatic Glucose Metabolism by Inhibiting the CREB-PGC-1α Pathway. Cell Metabolism. 13(6). 729–738. 342 indexed citations
17.
Bequette, B.J., Samer W. El‐Kadi, Nishanth E. Sunny, & G. M. Crovetto. (2010). Intermediary metabolism and neogenesis of nutrients in farm animals.. 99–109. 1 indexed citations
18.
El‐Kadi, Samer W., R.L. Baldwin, K. R. McLeod, Nishanth E. Sunny, & B.J. Bequette. (2009). Glutamate Is the Major Anaplerotic Substrate in the Tricarboxylic Acid Cycle of Isolated Rumen Epithelial and Duodenal Mucosal Cells from Beef Cattle. Journal of Nutrition. 139(5). 869–875. 26 indexed citations
19.
Sunny, Nishanth E. & B.J. Bequette. (2009). Gluconeogenesis differs in developing chick embryos derived from small compared with typical size broiler breeder eggs12. Journal of Animal Science. 88(3). 912–921. 24 indexed citations
20.
El‐Kadi, Samer W., et al.. (2006). Intestinal Protein Supply Alters Amino Acid, but Not Glucose, Metabolism by the Sheep Gastrointestinal Tract. Journal of Nutrition. 136(5). 1261–1269. 48 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026