Nicole M. Ashpole

3.4k total citations
53 papers, 2.4k citations indexed

About

Nicole M. Ashpole is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism and Cellular and Molecular Neuroscience. According to data from OpenAlex, Nicole M. Ashpole has authored 53 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 13 papers in Endocrinology, Diabetes and Metabolism and 12 papers in Cellular and Molecular Neuroscience. Recurrent topics in Nicole M. Ashpole's work include Growth Hormone and Insulin-like Growth Factors (13 papers), Neuroscience and Neuropharmacology Research (10 papers) and Cannabis and Cannabinoid Research (8 papers). Nicole M. Ashpole is often cited by papers focused on Growth Hormone and Insulin-like Growth Factors (13 papers), Neuroscience and Neuropharmacology Research (10 papers) and Cannabis and Cannabinoid Research (8 papers). Nicole M. Ashpole collaborates with scholars based in United States, Hungary and China. Nicole M. Ashpole's co-authors include William E. Sonntag, Andy Hudmon, Anna Csiszár, Zoltán Ungvári, Erik L. Hodges, Péter Tóth, Stefano Tarantini, Yan Han, Zsuzsanna Tucsek and Tripti Gautam and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and The Journal of Physiology.

In The Last Decade

Nicole M. Ashpole

53 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicole M. Ashpole United States 27 828 533 430 413 319 53 2.4k
Moritz Brandt Germany 26 974 1.2× 626 1.2× 517 1.2× 874 2.1× 160 0.5× 80 3.5k
Ami P. Raval United States 34 1.1k 1.4× 581 1.1× 645 1.5× 635 1.5× 267 0.8× 84 3.4k
Peng Shi China 30 814 1.0× 303 0.6× 656 1.5× 292 0.7× 272 0.9× 85 2.9k
Toshifumi Itano Japan 32 1.1k 1.4× 289 0.5× 415 1.0× 730 1.8× 233 0.7× 132 3.0k
Simon McArthur United Kingdom 29 1.6k 1.9× 598 1.1× 473 1.1× 539 1.3× 281 0.9× 57 3.6k
Daniela Giuliani Italy 35 726 0.9× 513 1.0× 555 1.3× 730 1.8× 219 0.7× 127 3.5k
Maja Mustapić United States 33 2.6k 3.1× 800 1.5× 678 1.6× 335 0.8× 228 0.7× 80 4.2k
Weikang Cai United States 26 1.2k 1.5× 1.1k 2.0× 279 0.6× 322 0.8× 423 1.3× 54 2.8k
Bo Bai China 35 987 1.2× 457 0.9× 315 0.7× 715 1.7× 174 0.5× 104 3.1k
K. S. Krabbe Denmark 18 385 0.5× 663 1.2× 306 0.7× 605 1.5× 128 0.4× 23 2.3k

Countries citing papers authored by Nicole M. Ashpole

Since Specialization
Citations

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

Fields of papers citing papers by Nicole M. Ashpole

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicole M. Ashpole

This figure shows the co-authorship network connecting the top 25 collaborators of Nicole M. Ashpole. A scholar is included among the top collaborators of Nicole M. Ashpole 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 Nicole M. Ashpole. Nicole M. Ashpole 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.
Wilson, Donald A., et al.. (2024). Insulin-like growth factor-1 and cognitive health: Exploring cellular, preclinical, and clinical dimensions. Frontiers in Neuroendocrinology. 76. 101161–101161. 5 indexed citations
2.
Sulochana, Suresh P., Jason J. Paris, John M. Rimoldi, et al.. (2022). Identification of an Orally Bioavailable, Brain-Penetrant Compound with Selectivity for the Cannabinoid Type 2 Receptor. Molecules. 27(2). 509–509. 4 indexed citations
3.
Valcarcel‐Ares, Marta Noa, et al.. (2021). Preclinical and clinical evidence of IGF-1 as a prognostic marker and acute intervention with ischemic stroke. Journal of Cerebral Blood Flow & Metabolism. 41(10). 2475–2491. 30 indexed citations
4.
Tandon, Ritesh, Joshua S. Sharp, Fuming Zhang, et al.. (2020). Effective Inhibition of SARS-CoV-2 Entry by Heparin and Enoxaparin Derivatives. Journal of Virology. 95(3). 191 indexed citations
5.
Radwan, Mohamed O., Nicole M. Ashpole, Masami Otsuka, et al.. (2020). First in class (S,E)-11-[2-(arylmethylene)hydrazono]-PBD analogs as selective CB2 modulators targeting neurodegenerative disorders. Medicinal Chemistry Research. 30(1). 98–108. 10 indexed citations
6.
7.
Pandelides, Zacharias, et al.. (2020). Developmental exposure to cannabidiol (CBD) alters longevity and health span of zebrafish (Danio rerio). GeroScience. 42(2). 785–800. 32 indexed citations
8.
Thornton, Cammi, et al.. (2020). Cannabis constituents reduce seizure behavior in chemically-induced and scn1a-mutant zebrafish. Epilepsy & Behavior. 110. 107152–107152. 29 indexed citations
9.
10.
Muhammad, Ilias, et al.. (2019). 4-O-Methylhonokiol Influences Normal Cardiovascular Development in Medaka Embryo. Molecules. 24(3). 475–475. 3 indexed citations
11.
Menegatti, Ricardo, Luciano M. Lião, Hugo Verli, et al.. (2019). Novel choline analog 2-(4-((1-phenyl-1H-pyrazol-4-yl)methyl)piperazin-1-yl)ethan-1-ol produces sympathoinhibition, hypotension, and antihypertensive effects. Naunyn-Schmiedeberg s Archives of Pharmacology. 392(9). 1071–1083. 3 indexed citations
12.
Hodges, Erik L. & Nicole M. Ashpole. (2019). Aging circadian rhythms and cannabinoids. Neurobiology of Aging. 79. 110–118. 32 indexed citations
13.
Ashpole, Nicole M., Sreemathi Logan, Erik L. Hodges, et al.. (2016). Differential effects of IGF-1 deficiency during the life span on structural and biomechanical properties in the tibia of aged mice. AGE. 38(2). 38–38. 19 indexed citations
14.
Tarantini, Stefano, Zsuzsanna Tucsek, Marta Noa Valcarcel‐Ares, et al.. (2016). Circulating IGF-1 deficiency exacerbates hypertension-induced microvascular rarefaction in the mouse hippocampus and retrosplenial cortex: implications for cerebromicrovascular and brain aging. AGE. 38(4). 273–289. 81 indexed citations
15.
Zhang, Dongmei, M. Caleb Marlin, Zhimin Liang, et al.. (2016). The Protein Tyrosine Phosphatase MEG2 Regulates the Transport and Signal Transduction of Tropomyosin Receptor Kinase A. Journal of Biological Chemistry. 291(46). 23895–23905. 20 indexed citations
16.
17.
Springó, Zsolt, Péter Tóth, Stefano Tarantini, et al.. (2015). Aging Impairs Myogenic Adaptation to Pulsatile Pressure in Mouse Cerebral Arteries. Journal of Cerebral Blood Flow & Metabolism. 35(4). 527–530. 64 indexed citations
18.
Sonntag, William E., F. Deák, Nicole M. Ashpole, et al.. (2013). Insulin-like growth factor-1 in CNS and cerebrovascular aging. Frontiers in Aging Neuroscience. 5. 27–27. 114 indexed citations
19.
Coultrap, Steven J., Rebekah S. Vest, Nicole M. Ashpole, Andy Hudmon, & K. Ulrich Bayer. (2011). CaMKII in cerebral ischemia. Acta Pharmacologica Sinica. 32(7). 861–872. 110 indexed citations
20.
Brittain, Joel M., Liang Chen, Sarah M. Wilson, et al.. (2011). Neuroprotection against Traumatic Brain Injury by a Peptide Derived from the Collapsin Response Mediator Protein 2 (CRMP2). Journal of Biological Chemistry. 286(43). 37778–37792. 77 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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