Keisa W. Mathis

853 total citations
38 papers, 675 citations indexed

About

Keisa W. Mathis is a scholar working on Neurology, Immunology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Keisa W. Mathis has authored 38 papers receiving a total of 675 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Neurology, 11 papers in Immunology and 10 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Keisa W. Mathis's work include Atherosclerosis and Cardiovascular Diseases (10 papers), Vagus Nerve Stimulation Research (8 papers) and Systemic Lupus Erythematosus Research (8 papers). Keisa W. Mathis is often cited by papers focused on Atherosclerosis and Cardiovascular Diseases (10 papers), Vagus Nerve Stimulation Research (8 papers) and Systemic Lupus Erythematosus Research (8 papers). Keisa W. Mathis collaborates with scholars based in United States, Austria and South Korea. Keisa W. Mathis's co-authors include Michael J. Ryan, Patricia E. Molina, Marcia Venegas‐Pont, Elizabeth R. Flynn, Christine Maric‐Bilkan, Patrick Greiffenstein, Curtis Vande Stouwe, Kedra Wallace, Babbette LaMarca and Lei Wang and has published in prestigious journals such as The FASEB Journal, Hypertension and American Journal of Physiology-Endocrinology and Metabolism.

In The Last Decade

Keisa W. Mathis

37 papers receiving 674 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Keisa W. Mathis United States 14 201 181 137 134 109 38 675
Bing‐Hu Li China 17 79 0.4× 210 1.2× 81 0.6× 43 0.3× 54 0.5× 40 668
Justin P. Van Beusecum United States 13 203 1.0× 261 1.4× 200 1.5× 36 0.3× 25 0.2× 30 927
Aynur Kırbaş Türkiye 18 94 0.5× 166 0.9× 106 0.8× 38 0.3× 28 0.3× 55 763
Carol A. Gunnett United States 15 196 1.0× 164 0.9× 166 1.2× 14 0.1× 67 0.6× 19 731
Amanda Genis South Africa 9 117 0.6× 212 1.2× 231 1.7× 24 0.2× 22 0.2× 15 788
Hicham Labazi United States 10 107 0.5× 111 0.6× 219 1.6× 22 0.2× 25 0.2× 25 673
Karine Demuth France 18 68 0.3× 176 1.0× 256 1.9× 387 2.9× 67 0.6× 26 1.1k
Shalini M Krishnan Australia 8 285 1.4× 398 2.2× 227 1.7× 32 0.2× 31 0.3× 9 1.0k
Nobuyuki Banba Japan 18 165 0.8× 246 1.4× 129 0.9× 17 0.1× 28 0.3× 35 978

Countries citing papers authored by Keisa W. Mathis

Since Specialization
Citations

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

Fields of papers citing papers by Keisa W. Mathis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keisa W. Mathis. 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 Keisa W. Mathis. The network helps show where Keisa W. Mathis may publish in the future.

Co-authorship network of co-authors of Keisa W. Mathis

This figure shows the co-authorship network connecting the top 25 collaborators of Keisa W. Mathis. A scholar is included among the top collaborators of Keisa W. Mathis 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 Keisa W. Mathis. Keisa W. Mathis 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.
Robinson, Austin T., et al.. (2023). Supporting and promoting Black physiologists: how can the APS help?. American Journal of Physiology-Heart and Circulatory Physiology. 324(6). H782–H785. 3 indexed citations
2.
Chaudhari, Sarika, et al.. (2023). Targeted stimulation of the vagus nerve reduces renal injury in female mice with systemic lupus erythematosus. Autonomic Neuroscience. 250. 103129–103129.
3.
Su, Dong‐Ming, et al.. (2023). Sex and strain differences in renal hemodynamics in mice. Physiological Reports. 11(6). e15644–e15644. 12 indexed citations
4.
Chaudhari, Sarika, et al.. (2022). Renal TLR-7/TNF-α pathway as a potential female-specific mechanism in the pathogenesis of autoimmune-induced hypertension. American Journal of Physiology-Heart and Circulatory Physiology. 323(6). H1331–H1342. 6 indexed citations
5.
6.
Rodríguez, Rubén, Andrew Lee, Keisa W. Mathis, et al.. (2018). Angiotensin receptor and tumor necrosis factor-α activation contributes to glucose intolerance independent of systolic blood pressure in obese rats. American Journal of Physiology-Renal Physiology. 315(4). F1081–F1090. 5 indexed citations
7.
Chaudhari, Sarika, et al.. (2018). Mechanisms of Sex Disparities in Cardiovascular Function and Remodeling. Comprehensive physiology. 9(1). 375–411. 10 indexed citations
8.
Mathis, Keisa W., Erin B. Taylor, & Michael J. Ryan. (2017). Anti-CD3 antibody therapy attenuates the progression of hypertension in female mice with systemic lupus erythematosus. Pharmacological Research. 120. 252–257. 14 indexed citations
9.
Mathis, Keisa W., et al.. (2017). Cholinergic agonists reduce blood pressure in a mouse model of systemic lupus erythematosus. Physiological Reports. 5(7). e13213–e13213. 24 indexed citations
10.
Mathis, Keisa W.. (2015). An impaired neuroimmune pathway promotes the development of hypertension in systemic lupus erythematosus. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 309(9). R1074–R1077. 13 indexed citations
11.
Mathis, Keisa W., et al.. (2014). Autoimmunity: An Underlying Factor in the Pathogenesis of Hypertension. Current Hypertension Reports. 16(4). 424–424. 12 indexed citations
12.
Mathis, Keisa W., et al.. (2013). The physiological roles of apolipoprotein J/clusterin in metabolic and cardiovascular diseases. Reviews in Endocrine and Metabolic Disorders. 15(1). 45–53. 98 indexed citations
13.
Gilbert, Emily, Keisa W. Mathis, & Michael J. Ryan. (2013). 17β-Estradiol Protects Against the Progression of Hypertension During Adulthood in a Mouse Model of Systemic Lupus Erythematosus. Hypertension. 63(3). 616–623. 22 indexed citations
14.
Mathis, Keisa W., et al.. (2011). Blood pressure in a hypertensive mouse model of SLE is not salt-sensitive. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 301(5). R1281–R1285. 38 indexed citations
15.
16.
Whitaker, Annie M., et al.. (2010). Sympathetic Modulation of the Host Defense Response to Infectious Challenge during Recovery from Hemorrhage. NeuroImmunoModulation. 17(6). 349–358. 3 indexed citations
17.
Mathis, Keisa W. & Patricia E. Molina. (2009). Central acetylcholinesterase inhibition improves hemodynamic counterregulation to severe blood loss in alcohol-intoxicated rats. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 297(2). R437–R445. 10 indexed citations
18.
19.
Greiffenstein, Patrick, Keisa W. Mathis, Curtis Vande Stouwe, & Patricia E. Molina. (2007). Alcohol Binge Before Trauma/Hemorrhage Impairs Integrity of Host Defense Mechanisms During Recovery. Alcoholism Clinical and Experimental Research. 31(4). 704–715. 52 indexed citations
20.
Mathis, Keisa W., Kirsten Zambell, Joseph O. Olubadewo, & Patricia E. Molina. (2006). ALTERED HEMODYNAMIC COUNTER-REGULATION TO HEMORRHAGE BY ACUTE MODERATE ALCOHOL INTOXICATION. Shock. 26(1). 55–61. 25 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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