Kumar Sambamurti

12.7k total citations · 3 hit papers
130 papers, 10.6k citations indexed

About

Kumar Sambamurti is a scholar working on Physiology, Molecular Biology and Pharmacology. According to data from OpenAlex, Kumar Sambamurti has authored 130 papers receiving a total of 10.6k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Physiology, 46 papers in Molecular Biology and 34 papers in Pharmacology. Recurrent topics in Kumar Sambamurti's work include Alzheimer's disease research and treatments (81 papers), Cholinesterase and Neurodegenerative Diseases (33 papers) and Computational Drug Discovery Methods (17 papers). Kumar Sambamurti is often cited by papers focused on Alzheimer's disease research and treatments (81 papers), Cholinesterase and Neurodegenerative Diseases (33 papers) and Computational Drug Discovery Methods (17 papers). Kumar Sambamurti collaborates with scholars based in United States, Germany and United Kingdom. Kumar Sambamurti's co-authors include Debomoy K. Lahiri, Nigel H. Greig, Miguel A. Pappolla, Lorenzo M. Refolo, Harold W. Holloway, Arnold Brossi, Christopher B. Eckman, David Tweedie, A. Prakasam and Mark P. Mattson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Kumar Sambamurti

128 papers receiving 10.4k citations

Hit Papers

Hypercholesterolemia Accelerates the Alzheimer's Amyloid ... 2000 2026 2008 2017 2000 2005 2009 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Hypercholesterolemia Accelerates the Alzheimer's Amyloid Pathology in a Transgenic Mouse Model
    2000 825 citations Lorenzo M. Refolo, Miguel A. Pappolla et al. Neurobiology of Disease profile →
  2. Selective butyrylcholinesterase inhibition elevates brain acetylcholine, augments learning and lowers Alzheimer β-amyloid peptide in rodent
    2005 645 citations Nigel H. Greig, Harold W. Holloway et al. Proceedings of the National Academy of Sciences profile →
  3. GLP-1 receptor stimulation preserves primary cortical and dopaminergic neurons in cellular and rodent models of stroke and Parkinsonism
    2009 502 citations Yazhou Li, Mark S. Kindy et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kumar Sambamurti United States 53 5.2k 3.7k 2.6k 1.6k 1.5k 130 10.6k
Christopher B. Eckman United States 50 9.3k 1.8× 5.9k 1.6× 2.4k 0.9× 2.3k 1.5× 1.6k 1.0× 78 12.6k
Judes Poirier Canada 48 5.1k 1.0× 2.8k 0.8× 1.2k 0.5× 1.5k 0.9× 623 0.4× 170 8.9k
Sally A. Frautschy United States 61 8.3k 1.6× 5.0k 1.4× 2.4k 0.9× 2.9k 1.8× 826 0.6× 117 15.4k
Fernanda G. De Felice Brazil 55 6.5k 1.3× 3.5k 1.0× 1.5k 0.6× 2.2k 1.4× 601 0.4× 114 10.9k
Tobias Hartmann Germany 59 6.7k 1.3× 5.1k 1.4× 1.2k 0.5× 1.5k 1.0× 765 0.5× 218 12.2k
Miguel A. Pappolla United States 42 4.7k 0.9× 3.0k 0.8× 1.2k 0.5× 933 0.6× 652 0.4× 103 8.3k
Fusheng Yang United States 34 7.7k 1.5× 4.1k 1.1× 2.1k 0.8× 2.6k 1.7× 954 0.6× 56 12.0k
Giulio Maria Pasinetti United States 75 7.0k 1.4× 6.2k 1.7× 2.3k 0.9× 2.6k 1.7× 665 0.4× 326 17.0k
Greg M. Cole United States 58 10.7k 2.1× 5.7k 1.5× 2.8k 1.1× 3.4k 2.2× 1.3k 0.8× 100 16.9k
Kenjiro Ono Japan 52 6.0k 1.1× 3.8k 1.0× 1.9k 0.7× 940 0.6× 1.1k 0.7× 227 10.5k

Countries citing papers authored by Kumar Sambamurti

Since Specialization
Citations

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

Fields of papers citing papers by Kumar Sambamurti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kumar Sambamurti

This figure shows the co-authorship network connecting the top 25 collaborators of Kumar Sambamurti. A scholar is included among the top collaborators of Kumar Sambamurti 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 Kumar Sambamurti. Kumar Sambamurti 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.
Olsén, Thomas, Amany Elshorbagy, Jay E. Johnson, et al.. (2025). Sulfur amino acids, metabolic health and beyond: Recent advances, translational implications, and future research considerations. Analytical Biochemistry. 709. 116008–116008.
2.
Oleinik, Natalia V., Paramita Chakraborty, Silvia G. Vaena, et al.. (2025). Alzheimer's Disease–Associated Amyloid-β Precursor Protein Prevents Aging Stress–Induced Mitophagy and Fumarate Depletion to Improve Antitumor Immunity. Cancer Research. 85(19). 3791–3811. 1 indexed citations
3.
4.
Pöeggeler, Burkhard, Sandeep Kumar Singh, Kumar Sambamurti, & Miguel A. Pappolla. (2023). Nitric Oxide as a Determinant of Human Longevity and Health Span. International Journal of Molecular Sciences. 24(19). 14533–14533. 6 indexed citations
5.
6.
Greig, Nigel H., David Tweedie, Lital Rachmany, et al.. (2014). Incretin mimetics as pharmacological tools to elucidate and as a new drug strategy to treat traumatic brain injury. PMC. 25 indexed citations
7.
Pinnix, Inga, Jorge Ghiso, Miguel A. Pappolla, & Kumar Sambamurti. (2013). Major Carboxyl Terminal Fragments Generated by γ-Secretase Processing of the Alzheimer Amyloid Precursor Are 50 and 51 Amino Acids Long. American Journal of Geriatric Psychiatry. 21(5). 474–483. 11 indexed citations
8.
Li, Yazhou, Mark S. Kindy, Brandon K. Harvey, et al.. (2009). GLP-1 receptor stimulation preserves primary cortical and dopaminergic neurons in cellular and rodent models of stroke and Parkinsonism. Proceedings of the National Academy of Sciences. 106(4). 1285–1290. 502 indexed citations breakdown →
9.
Prakasam, A., et al.. (2008). An Increase in Aβ42 in the Prefrontal Cortex is Associated with a Reversal-Learning Impairment in Alzheimers Disease Model Tg2576 APPsw Mice. Current Alzheimer Research. 5(4). 385–391. 25 indexed citations
10.
Sambamurti, Kumar, et al.. (2007). Amyloid Precursor Protein Metabolism in Retinal Degeneration. Investigative Ophthalmology & Visual Science. 48(13). 26–26. 1 indexed citations
11.
Sambamurti, Kumar, Anitha Suram, Chitra Venugopal, et al.. (2006). A Partial Failure of Membrane Protein Turnover May Cause Alzheimers Disease: A New Hypothesis. Current Alzheimer Research. 3(1). 81–90. 49 indexed citations
12.
Brown, James A., Catherine Theisler, Simone Silberman, et al.. (2004). Differential Expression of Cholesterol Hydroxylases in Alzheimer's Disease. Journal of Biological Chemistry. 279(33). 34674–34681. 230 indexed citations
13.
Lahiri, Debomoy K., Kumar Sambamurti, De‐Mao Chen, et al.. (2003). Glucagon‐like peptide‐1 decreases endogenous amyloid‐β peptide (Aβ) levels and protects hippocampal neurons from death induced by Aβ and iron. Journal of Neuroscience Research. 72(5). 603–612. 300 indexed citations
14.
Pinnix, Inga, Han W. Tun, Arati Sridharan, et al.. (2001). A Novel γ-Secretase Assay Based on Detection of the Putative C-terminal Fragment-γ of Amyloid β Protein Precursor. Journal of Biological Chemistry. 276(1). 481–487. 126 indexed citations
15.
Refolo, Lorenzo M., Miguel A. Pappolla, Brian Malester, et al.. (2000). Hypercholesterolemia Accelerates the Alzheimer's Amyloid Pathology in a Transgenic Mouse Model. Neurobiology of Disease. 7(4). 321–331. 825 indexed citations breakdown →
16.
Sambamurti, Kumar, Daniel Sevlever, Lawrence M. Refolo, et al.. (1999). Glycosylphosphatidylinositol-anchored Proteins Play an Important Role in the Biogenesis of the Alzheimer's Amyloid β-Protein. Journal of Biological Chemistry. 274(38). 26810–26814. 45 indexed citations
17.
Lahiri, Debomoy K., Martin R. Farlow, Kumar Sambamurti, & C. Nall. (1997). The effect of tacrine and leupeptin on the secretion of the beta-amyloid precursor protein in HeLa cells. Life Sciences. 61(20). 1985–1992. 10 indexed citations
18.
Refolo, Lorenzo M., Kumar Sambamurti, Spiros Efthimiopoulos, Miguel A. Pappolla, & Nikolaos K. Robakis. (1995). Evidence that secretase cleavage of cell surface Alzheimer amyloid precursor occurs after normal endocytic internalization. Journal of Neuroscience Research. 40(5). 694–706. 51 indexed citations
19.
Efthimiopoulos, Spiros, Kevin M. Felsenstein, Kumar Sambamurti, Nikolaos K. Robakis, & Lorenzo M. Refolo. (1994). Study of the phorbol ester effect on Alzheimer amyloid precursor processing: Sequence requirements and involvement of a Cholera toxin sensitive protein. Journal of Neuroscience Research. 38(1). 81–90. 29 indexed citations
20.
Anderson, John P., Fred Esch, Pamela S. Keim, et al.. (1991). Exact cleavage site of Alzheimer amyloid precursor in neuronal PC-12 cells. Neuroscience Letters. 128(1). 126–128. 173 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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