Daniel J. Cushing

527 total citations
18 papers, 297 citations indexed

About

Daniel J. Cushing is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Daniel J. Cushing has authored 18 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cardiology and Cardiovascular Medicine, 4 papers in Molecular Biology and 3 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Daniel J. Cushing's work include Cardiac electrophysiology and arrhythmias (7 papers), Cardiac Arrhythmias and Treatments (3 papers) and Blood Pressure and Hypertension Studies (3 papers). Daniel J. Cushing is often cited by papers focused on Cardiac electrophysiology and arrhythmias (7 papers), Cardiac Arrhythmias and Treatments (3 papers) and Blood Pressure and Hypertension Studies (3 papers). Daniel J. Cushing collaborates with scholars based in United States, Peru and France. Daniel J. Cushing's co-authors include Raymond J. Lipicky, Eric L. Michelson, Suzanne Oparil, Michael Gralinski, Paul F. Souney, Peter R. Kowey, S. Jamal Mustafa, Marlene L. Cohen, Timothy C. Fagan and Max C. Reif and has published in prestigious journals such as The FASEB Journal, The American Journal of Cardiology and Life Sciences.

In The Last Decade

Daniel J. Cushing

16 papers receiving 282 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel J. Cushing United States	11	216	71	46	41	39	18	297
Brigitte Lecocq France	9	127 0.6×	37 0.5×	12 0.3×	50 1.2×	63 1.6×	15	325
R. Coxon New Zealand	6	324 1.5×	19 0.3×	16 0.3×	37 0.9×	62 1.6×	7	422
Neal Klein United States	10	341 1.6×	34 0.5×	16 0.3×	84 2.0×	51 1.3×	14	477
P. F. Binnion United States	13	208 1.0×	75 1.1×	56 1.2×	57 1.4×	50 1.3×	36	453
Roderick Walden United Kingdom	9	99 0.5×	39 0.5×	11 0.2×	49 1.2×	54 1.4×	35	278
P. D. Verdouw Netherlands	12	190 0.9×	16 0.2×	24 0.5×	44 1.1×	89 2.3×	19	314
B. Pitt United States	10	220 1.0×	48 0.7×	21 0.5×	59 1.4×	23 0.6×	16	298
E Welman United Kingdom	13	207 1.0×	21 0.3×	16 0.3×	55 1.3×	96 2.5×	26	417
Miguel A. Chiong Canada	12	490 2.3×	21 0.3×	30 0.7×	70 1.7×	54 1.4×	30	616
BN Prichard United Kingdom	12	150 0.7×	47 0.7×	10 0.2×	84 2.0×	69 1.8×	17	380

Countries citing papers authored by Daniel J. Cushing

Since Specialization

Citations

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

Fields of papers citing papers by Daniel J. Cushing

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Cushing. 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 Daniel J. Cushing. The network helps show where Daniel J. Cushing may publish in the future.

Co-authorship network of co-authors of Daniel J. Cushing

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

All Works

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18 of 18 papers shown

Cushing, Daniel J., et al.. (2011). Comparative Bioavailability of a Premixed, Ready‐to‐Use Formulation of Intravenous Amiodarone With Traditional Admixture in Healthy Subjects. The Journal of Clinical Pharmacology. 52(2). 214–221. 6 indexed citations

Cushing, Daniel J., et al.. (2011). Pharmacokinetics and platelet aggregation inhibitory effects of a novel intravenous formulation of clopidogrel in humans. Clinical and Experimental Pharmacology and Physiology. 39(1). 3–8. 10 indexed citations

Cushing, Daniel J., et al.. (2010). Reversal of heparin-induced increases in aPTT in the rat by PM102, a novel heparin antagonist. European Journal of Pharmacology. 635(1-3). 165–170. 19 indexed citations

Souney, Paul F., et al.. (2010). PM101: intravenous amiodarone formulation changes can improve medication safety. Expert Opinion on Drug Safety. 9(2). 319–333. 24 indexed citations

Cushing, Daniel J., et al.. (2009). PM101: A cyclodextrin-based intravenous formulation of amiodarone devoid of adverse hemodynamic effects. European Journal of Pharmacology. 607(1-3). 167–172. 23 indexed citations

Cushing, Daniel J., et al.. (2009). Evaluation of the Effects of PM101, a Cyclodextrin-Based Formulation of Intravenous Amiodarone, on Blood Pressure in Healthy Humans. The American Journal of Cardiology. 104(8). 1152–1157. 8 indexed citations

Cushing, Daniel J., et al.. (2009). Comparison of the Cardiac Electrophysiology and General Toxicology of Two Formulations of Intravenous Amiodarone in Dogs. Cardiovascular Toxicology. 9(3). 126–133. 10 indexed citations

Cushing, Daniel J., et al.. (2009). Bioequivalence of 2 Intravenous Amiodarone Formulations in Healthy Participants. The Journal of Clinical Pharmacology. 49(4). 407–415. 10 indexed citations

Cushing, Daniel J., et al.. (2009). The hypotensive effect of intravenous amiodarone is sustained throughout the maintenance infusion period. Clinical and Experimental Pharmacology and Physiology. 37(3). 358–361. 22 indexed citations

10.

Cushing, Daniel J., et al.. (2008). Undergraduate research in neuroscience using SNNAP. The FASEB Journal. 22(S1). 1 indexed citations

11.

Watts, Stephanie W., Gregory D. Fink, Paul J. Silver, & Daniel J. Cushing. (2000). Interaction of the β Adrenergic Receptor Antagonist Bucindolol with Serotonergic Receptors. Journal of Cardiovascular Pharmacology. 35(1). 29–36. 5 indexed citations

12.

DeQuattro, Vincent, et al.. (1999). Effective dose range of Candesartan cilexetil for systemic hypertension. The American Journal of Cardiology. 83(2). 272–275. 12 indexed citations

13.

Oparil, Suzanne, Jon H. Levine, Alan H. Gradman, et al.. (1999). Effects of candesartan cilexetil in patients with severe systemic hypertension. The American Journal of Cardiology. 84(3). 289–293. 48 indexed citations

14.

Reif, Max C., William B. White, Timothy C. Fagan, et al.. (1998). Effects of candesartan cilexetil in patients with systemic hypertension. The American Journal of Cardiology. 82(8). 961–965. 47 indexed citations

15.

Cushing, Daniel J., Melvyn Baez, Jonathan D. Kursar, Kathryn W. Schenck, & Marlene L. Cohen. (1994). Serotonin-induced contraction in canine coronary artery and saphenous vein: Role of a 5-HT1D-like receptor. Life Sciences. 54(22). 1671–1680. 21 indexed citations

16.

Cushing, Daniel J., Jerry W. Misner, & Marlene L. Cohen. (1993). Overview: 5-HT₂Receptor Antagonists for the Treatment of Cardiovascular Disease. 3(5). 569–580.

17.

Hussain, Tahir, et al.. (1991). G Proteins Subserve Relaxations Mediated by Adenosine Receptors in Human Coronary Artery. Journal of Cardiovascular Pharmacology. 18(5). 696–702. 19 indexed citations

18.

Cushing, Daniel J., Mona M. McConnaughey, & S. Jamal Mustafa. (1988). Characterization of adenosine binding sites in bovine testicular tissue using 8-cyclopentyl-1,3-[3H]dipropylxanthine. European Journal of Pharmacology. 152(3). 353–356. 12 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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