Thomas Näsström

674 total citations
9 papers, 557 citations indexed

About

Thomas Näsström is a scholar working on Neurology, Physiology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Thomas Näsström has authored 9 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Neurology, 6 papers in Physiology and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Thomas Näsström's work include Parkinson's Disease Mechanisms and Treatments (9 papers), Alzheimer's disease research and treatments (6 papers) and Nerve injury and regeneration (3 papers). Thomas Näsström is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (9 papers), Alzheimer's disease research and treatments (6 papers) and Nerve injury and regeneration (3 papers). Thomas Näsström collaborates with scholars based in Sweden, Germany and Finland. Thomas Näsström's co-authors include Joakim Bergström, Lars Lannfelt, Martin Ingelsson, Tiago F. Outeiro, Therese Fagerqvist, Alex Kasrayan, Per Ola Andersson, Fredrik Nikolajeff, Mikael Karlsson and Luís M. A. Oliveira and has published in prestigious journals such as Journal of Neuroscience, PLoS ONE and Scientific Reports.

In The Last Decade

Thomas Näsström

9 papers receiving 553 citations

Peers

Thomas Näsström
Rosalind F. Roberts United Kingdom
C.B. Lücking France
Alessandra Recchia Italy
Fariba Chegini Australia
Wei-Ping Gai Australia
Matina Maniati Greece
Xuezhi Ouyang Singapore
Marie-Laure Arotçarena France
Jeanna M. Wheeler United States
Sabine Kauffmann Switzerland
Rosalind F. Roberts United Kingdom
Thomas Näsström
Citations per year, relative to Thomas Näsström Thomas Näsström (= 1×) peers Rosalind F. Roberts

Countries citing papers authored by Thomas Näsström

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Näsström

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Näsström

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

All Works

9 of 9 papers shown
1.
Näsström, Thomas, Tobias Dahlberg, Dmitry Malyshev, et al.. (2021). Synthetic NAC 71-82 Peptides Designed to Produce Fibrils with Different Protofilament Interface Contacts. International Journal of Molecular Sciences. 22(17). 9334–9334. 2 indexed citations
2.
Näsström, Thomas, et al.. (2020). A Capped Peptide of the Aggregation Prone NAC 71–82 Amino Acid Stretch of α-Synuclein Folds into Soluble β-Sheet Oligomers at Low and Elevated Peptide Concentrations. International Journal of Molecular Sciences. 21(5). 1629–1629. 7 indexed citations
3.
Näsström, Thomas, Per Ola Andersson, Christian Lejon, & Björn C. G. Karlsson. (2019). Amyloid fibrils prepared using an acetylated and methyl amidated peptide model of the α-Synuclein NAC 71–82 amino acid stretch contain an additional cross-β structure also found in prion proteins. Scientific Reports. 9(1). 15949–15949. 53 indexed citations
4.
Fagerqvist, Therese, Thomas Näsström, Elisabet Ihse, et al.. (2013). Off-pathwayα-synuclein oligomers seem to alterα-synuclein turnover in a cell model but lack seeding capabilityin vivo. Amyloid. 20(4). 233–244. 23 indexed citations
5.
Fagerqvist, Therese, Veronica Lindström, Eva Nordström, et al.. (2013). Monoclonal antibodies selective for α‐synuclein oligomers/protofibrils recognize brain pathology in Lewy body disorders and α‐synuclein transgenic mice with the disease‐causing A30P mutation. Journal of Neurochemistry. 126(1). 131–144. 74 indexed citations
6.
Diógenes, Maria José, Raquel B. Dias, Diogo M. Rombo, et al.. (2012). Extracellular Alpha-Synuclein Oligomers Modulate Synaptic Transmission and Impair LTP Via NMDA-Receptor Activation. Journal of Neuroscience. 32(34). 11750–11762. 219 indexed citations
7.
Welander, Hedvig, Sai Vineela Bontha, Thomas Näsström, et al.. (2011). Gelsolin co-occurs with Lewy bodies in vivo and accelerates α-synuclein aggregation in vitro. Biochemical and Biophysical Research Communications. 412(1). 32–38. 16 indexed citations
8.
Näsström, Thomas, S. Gonçalves, Charlotte Sahlin, et al.. (2011). Antibodies against Alpha-Synuclein Reduce Oligomerization in Living Cells. PLoS ONE. 6(10). e27230–e27230. 52 indexed citations
9.
Näsström, Thomas, Therese Fagerqvist, Mikael Karlsson, et al.. (2010). The lipid peroxidation products 4-oxo-2-nonenal and 4-hydroxy-2-nonenal promote the formation of α-synuclein oligomers with distinct biochemical, morphological, and functional properties. Free Radical Biology and Medicine. 50(3). 428–437. 111 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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