Darcy Kahn

1.0k total citations
18 papers, 619 citations indexed

About

Darcy Kahn is a scholar working on Physiology, Molecular Biology and Epidemiology. According to data from OpenAlex, Darcy Kahn has authored 18 papers receiving a total of 619 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Physiology, 8 papers in Molecular Biology and 8 papers in Epidemiology. Recurrent topics in Darcy Kahn's work include Adipose Tissue and Metabolism (11 papers), Adipokines, Inflammation, and Metabolic Diseases (7 papers) and Sphingolipid Metabolism and Signaling (5 papers). Darcy Kahn is often cited by papers focused on Adipose Tissue and Metabolism (11 papers), Adipokines, Inflammation, and Metabolic Diseases (7 papers) and Sphingolipid Metabolism and Signaling (5 papers). Darcy Kahn collaborates with scholars based in United States, Germany and United Kingdom. Darcy Kahn's co-authors include Bryan C. Bergman, Paul S. MacLean, Leigh Perreault, Anna A. Kerege, Sean A. Newsom, Allison Strauss, Kathleen A. Harrison, Matthew R. Jackman, Simona Zarini and Jonathan A. Schoen and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Clinical Endocrinology & Metabolism and Diabetes.

In The Last Decade

Darcy Kahn

18 papers receiving 614 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Darcy Kahn United States 10 360 193 140 89 86 18 619
Lauren M. Sparks United States 17 499 1.4× 169 0.9× 178 1.3× 63 0.7× 81 0.9× 41 823
Saori Kakehi Japan 16 379 1.1× 224 1.2× 181 1.3× 61 0.7× 144 1.7× 56 682
Elad Shemesh Israel 9 274 0.8× 116 0.6× 172 1.2× 56 0.6× 87 1.0× 19 556
Ana I. Castro Spain 15 536 1.5× 179 0.9× 108 0.8× 81 0.9× 238 2.8× 26 783
Mette P. Sonne Denmark 13 388 1.1× 169 0.9× 114 0.8× 51 0.6× 61 0.7× 18 624
Antônio Calixto Brazil 11 280 0.8× 89 0.5× 181 1.3× 73 0.8× 97 1.1× 16 531
Isabel Viola Wagner Germany 16 423 1.2× 147 0.8× 189 1.4× 55 0.6× 165 1.9× 29 925
Sabrina Maestrini Italy 15 279 0.8× 198 1.0× 115 0.8× 73 0.8× 139 1.6× 23 831
Sune Jauffred Denmark 4 373 1.0× 152 0.8× 260 1.9× 40 0.4× 74 0.9× 6 821
Brooks P. Leitner United States 12 487 1.4× 173 0.9× 194 1.4× 38 0.4× 64 0.7× 28 776

Countries citing papers authored by Darcy Kahn

Since Specialization
Citations

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

Fields of papers citing papers by Darcy Kahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Darcy Kahn

This figure shows the co-authorship network connecting the top 25 collaborators of Darcy Kahn. A scholar is included among the top collaborators of Darcy Kahn 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 Darcy Kahn. Darcy Kahn 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
1.
McKenna, Colleen F., Karin A. Zemski Berry, Matthew M. Robinson, et al.. (2024). Intramuscular diacylglycerol accumulates with acute hyperinsulinemia in insulin-resistant phenotypes. American Journal of Physiology-Endocrinology and Metabolism. 327(2). E183–E193. 1 indexed citations
2.
Broussard, Josiane L., Simona Zarini, Joseph T. Brozinick, et al.. (2024). Combined diet and exercise training decreases serum lipids associated with insulin resistance. Obesity. 32(12). 2334–2344. 4 indexed citations
3.
4.
Zarini, Simona, Karin A. Zemski Berry, Darcy Kahn, et al.. (2023). Deoxysphingolipids: Atypical Skeletal Muscle Lipids Related to Insulin Resistance in Humans That Decrease Insulin Sensitivity In Vitro. Diabetes. 72(7). 884–897. 1 indexed citations
5.
Kahn, Darcy & Bryan C. Bergman. (2022). Keeping It Local in Metabolic Disease: Adipose Tissue Paracrine Signaling and Insulin Resistance. Diabetes. 71(4). 599–609. 21 indexed citations
6.
Kahn, Darcy, Simona Zarini, Karin Zemski Berry, et al.. (2022). Quantifying the inflammatory secretome of human intermuscular adipose tissue. Physiological Reports. 10(16). e15424–e15424. 29 indexed citations
7.
Bodkin, Stephan G., Andrew C. Smith, Bryan C. Bergman, et al.. (2022). Utilization of Mid-Thigh Magnetic Resonance Imaging to Predict Lean Body Mass and Knee Extensor Strength in Obese Adults. SHILAP Revista de lepidopterología. 3. 4 indexed citations
8.
Kahn, Darcy, Simona Zarini, Karin Zemski Berry, et al.. (2022). Exploring Visceral and Subcutaneous Adipose Tissue Secretomes in Human Obesity: Implications for Metabolic Disease. Endocrinology. 163(11). 47 indexed citations
9.
Kahn, Darcy, Leigh Perreault, Simona Zarini, et al.. (2020). Subcellular localisation and composition of intramuscular triacylglycerol influence insulin sensitivity in humans. Diabetologia. 64(1). 168–180. 17 indexed citations
10.
Foright, Rebecca M., Ginger C. Johnson, Darcy Kahn, et al.. (2020). Compensatory eating behaviors in male and female rats in response to exercise training. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 319(2). R171–R183. 17 indexed citations
11.
Sachs, Stephan, Simona Zarini, Darcy Kahn, et al.. (2019). Intermuscular adipose tissue directly modulates skeletal muscle insulin sensitivity in humans. American Journal of Physiology-Endocrinology and Metabolism. 316(5). E866–E879. 133 indexed citations
12.
Cree‐Green, Melanie, Bryan C. Bergman, Eda Cengiz, et al.. (2019). Metformin Improves Peripheral Insulin Sensitivity in Youth With Type 1 Diabetes. The Journal of Clinical Endocrinology & Metabolism. 104(8). 3265–3278. 72 indexed citations
13.
Sergi, Domenico, Amanda C. Morris, Darcy Kahn, et al.. (2018). Palmitic acid triggers inflammatory responses in N42 cultured hypothalamic cells partially via ceramide synthesis but not via TLR4. Nutritional Neuroscience. 23(4). 321–334. 49 indexed citations
14.
Perreault, Leigh, Sean A. Newsom, Allison Strauss, et al.. (2018). Intracellular localization of diacylglycerols and sphingolipids influences insulin sensitivity and mitochondrial function in human skeletal muscle. JCI Insight. 3(3). 132 indexed citations
15.
Newsom, Sean A., Leigh Perreault, Anna A. Kerege, et al.. (2018). Metabolomic Signatures of Insulin Resistance in Human Skeletal Muscle Are Exacerbated with Insulin Stimulation. Diabetes. 67(Supplement_1). 1 indexed citations
16.
Foright, Rebecca M., David M. Presby, Vanessa D. Sherk, et al.. (2018). Is regular exercise an effective strategy for weight loss maintenance?. Physiology & Behavior. 188. 86–93. 83 indexed citations
17.
Zarini, Simona, Leigh Perreault, Sean A. Newsom, et al.. (2018). Deoxysphingolipids—Novel Skeletal Muscle Lipids Related to Insulin Resistance in Humans That Decrease Insulin Sensitivity In Vitro. Diabetes. 67(Supplement_1). 1 indexed citations
18.
Sergi, Domenico, et al.. (2016). Palmitic acid induces inflammation in hypothalamic neurons via ceramide synthesis. Proceedings of The Nutrition Society. 75(OCE2). 1 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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