Nadia Papini

2.2k total citations
49 papers, 1.7k citations indexed

About

Nadia Papini is a scholar working on Molecular Biology, Physiology and Immunology. According to data from OpenAlex, Nadia Papini has authored 49 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 17 papers in Physiology and 10 papers in Immunology. Recurrent topics in Nadia Papini's work include Glycosylation and Glycoproteins Research (21 papers), Galectins and Cancer Biology (9 papers) and Erythrocyte Function and Pathophysiology (8 papers). Nadia Papini is often cited by papers focused on Glycosylation and Glycoproteins Research (21 papers), Galectins and Cancer Biology (9 papers) and Erythrocyte Function and Pathophysiology (8 papers). Nadia Papini collaborates with scholars based in Italy, United States and United Kingdom. Nadia Papini's co-authors include Bruno Venerando, Guido Tettamanti, Eugenio Monti, A. Petroni, M. Blasevich, Cristina Tringali, Marco Salami, Luigi Anastasia, Claudio Galli and Gian Francesco Montedoro and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Biochemical Journal.

In The Last Decade

Nadia Papini

48 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nadia Papini Italy 23 1.1k 434 382 333 291 49 1.7k
Isabelle Chantret France 24 1.2k 1.1× 235 0.5× 278 0.7× 219 0.7× 176 0.6× 41 2.1k
Masatoshi Beppu Japan 23 684 0.6× 276 0.6× 112 0.3× 113 0.3× 481 1.7× 86 1.6k
Laura Sturla Italy 34 1.1k 1.0× 317 0.7× 230 0.6× 100 0.3× 280 1.0× 79 2.7k
David Fischer United States 19 953 0.9× 208 0.5× 118 0.3× 162 0.5× 190 0.7× 36 1.6k
Soo Jin Kim South Korea 25 1.6k 1.4× 187 0.4× 68 0.2× 633 1.9× 148 0.5× 65 2.5k
Thomas G. Brock United States 32 1.3k 1.2× 726 1.7× 150 0.4× 135 0.4× 780 2.7× 67 3.0k
Jin‐Chul Kim South Korea 27 972 0.9× 430 1.0× 67 0.2× 103 0.3× 81 0.3× 90 2.0k
Boo Ahn Shin South Korea 21 1.2k 1.1× 297 0.7× 57 0.1× 180 0.5× 112 0.4× 41 2.1k
Michael L. Sprengart Singapore 6 1.8k 1.7× 301 0.7× 128 0.3× 206 0.6× 95 0.3× 6 2.5k
I Kudo Japan 16 796 0.7× 324 0.7× 132 0.3× 96 0.3× 210 0.7× 29 1.6k

Countries citing papers authored by Nadia Papini

Since Specialization
Citations

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

Fields of papers citing papers by Nadia Papini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nadia Papini

This figure shows the co-authorship network connecting the top 25 collaborators of Nadia Papini. A scholar is included among the top collaborators of Nadia Papini 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 Nadia Papini. Nadia Papini 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
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Papini, Nadia, Paola Giussani, & Cristina Tringali. (2024). Metformin Lysosomal Targeting: A Novel Aspect to Be Investigated for Metformin Repurposing in Neurodegenerative Diseases?. International Journal of Molecular Sciences. 25(16). 8884–8884. 5 indexed citations
3.
Massaccesi, Luca, Monica Gioia Marazzi, Lorenzo Drago, et al.. (2017). Plasmatic Soluble Receptor for Advanced Glycation End Products as a New Oxidative Stress Biomarker in Patients with Prosthetic-Joint-Associated Infections?. Disease Markers. 2017. 1–7. 11 indexed citations
4.
Massaccesi, Luca, G. Goi, Cristina Tringali, et al.. (2016). Dexamethasone‐Induced Skeletal Muscle Atrophy Increases O‐GlcNAcylation in C2C12 Cells. Journal of Cellular Biochemistry. 117(8). 1833–1842. 30 indexed citations
5.
Mozzi, Alessandra, Matilde Forcella, Alice Riva, et al.. (2015). NEU3 activity enhances EGFR activation without affecting EGFR expression and acts on its sialylation levels. Glycobiology. 25(8). 855–868. 45 indexed citations
6.
Bergante, Sonia, Enrica Torretta, Pasquale Creo, et al.. (2014). Gangliosides as a potential new class of stem cell markers: the case of GD1a in human bone marrow mesenchymal stem cells. Journal of Lipid Research. 55(3). 549–560. 33 indexed citations
7.
Invernizzi, Pietro Luigi, et al.. (2013). Effects of Carnosine and Beta-Alanine Ingestion on Anaerobic Sprint Performance and Peripheral Blood Mononuclear Cell Interleukin-6 and -10 Gene Expression. Advances in Physical Education. 3(4). 197–204. 2 indexed citations
8.
Fanzani, Alessandro, Alessandra Zanola, Nadia Papini, et al.. (2012). Implications for the mammalian sialidases in the physiopathology of skeletal muscle. Skeletal Muscle. 2(1). 23–23. 21 indexed citations
9.
D’Avila, Francesca, Cristina Tringali, Nadia Papini, et al.. (2012). Identification of lysosomal sialidase NEU1 and plasma membrane sialidase NEU3 in human erythrocytes. Journal of Cellular Biochemistry. 114(1). 204–211. 18 indexed citations
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Piccoli, Marco, Erika Conforti, Giuseppe Lamorte, et al.. (2012). The synthetic purine reversine selectively induces cell death of cancer cells. Journal of Cellular Biochemistry. 113(10). 3207–3217. 15 indexed citations
12.
Tringali, Cristina, Federica Cirillo, Giuseppe Lamorte, et al.. (2012). NEU4L sialidase overexpression promotes β‐catenin signaling in neuroblastoma cells, enhancing stem‐like malignant cell growth. International Journal of Cancer. 131(8). 1768–1778. 22 indexed citations
13.
Papini, Nadia, Luigi Anastasia, Cristina Tringali, et al.. (2012). MmNEU3 sialidase over‐expression in C2C12 myoblasts delays differentiation and induces hypertrophic myotube formation. Journal of Cellular Biochemistry. 113(9). 2967–2978. 22 indexed citations
14.
Anastasia, Luigi, Anna Bianchi, Francesca D’Avila, et al.. (2007). Over-expression of mammalian sialidase NEU3 reduces Newcastle disease virus entry and propagation in COS7 cells. Biochimica et Biophysica Acta (BBA) - General Subjects. 1780(3). 504–512. 8 indexed citations
15.
Anastasia, Luigi, Maurilio Sampaolesi, Nadia Papini, et al.. (2006). Reversine-treated fibroblasts acquire myogenic competence in vitro and in regenerating skeletal muscle. Cell Death and Differentiation. 13(12). 2042–2051. 69 indexed citations
16.
Tringali, Cristina, Luigi Anastasia, Nadia Papini, et al.. (2006). Modification of sialidase levels and sialoglycoconjugate pattern during erythroid and erytroleukemic cell differentiation. Glycoconjugate Journal. 24(1). 67–79. 17 indexed citations
17.
Petroni, A., Nadia Papini, M. Blasevich, Patrizia Risé, & C. Galli. (2002). Arachidonate release and c-fos expression in various models of hypoxia and hypoxia–hypoglycemia in retinoic acid differentiated neuroblastoma cells. Neurochemistry International. 40(3). 255–260. 6 indexed citations
18.
Petroni, A., Nadia Papini, M. Blasevich, & C. Galli. (2002). Blockade of a2aadenosine receptors leads to c-fos inhibition in a rat model of brain ischemia. Pharmacological Research. 45(2). 125–128. 11 indexed citations
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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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