Gianluigi Forloni

23.1k total citations · 1 hit paper
368 papers, 16.0k citations indexed

About

Gianluigi Forloni is a scholar working on Molecular Biology, Physiology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Gianluigi Forloni has authored 368 papers receiving a total of 16.0k indexed citations (citations by other indexed papers that have themselves been cited), including 161 papers in Molecular Biology, 145 papers in Physiology and 109 papers in Cellular and Molecular Neuroscience. Recurrent topics in Gianluigi Forloni's work include Alzheimer's disease research and treatments (125 papers), Prion Diseases and Protein Misfolding (84 papers) and Neuroscience and Neuropharmacology Research (47 papers). Gianluigi Forloni is often cited by papers focused on Alzheimer's disease research and treatments (125 papers), Prion Diseases and Protein Misfolding (84 papers) and Neuroscience and Neuropharmacology Research (47 papers). Gianluigi Forloni collaborates with scholars based in Italy, United States and United Kingdom. Gianluigi Forloni's co-authors include Mario Salmona, Fabrizio Tagliavini, Claudia Balducci, Nadia Angeretti, Roberto Chiesa, Orso Bugiani, Diego Albani, Laura Colombo, Tiziana Borsello and Pietro Veglianese and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Advanced Materials.

In The Last Decade

Gianluigi Forloni

362 papers receiving 15.8k citations

Hit Papers

Neurotoxicity of a prion protein fragment 1993 2026 2004 2015 1993 250 500 750

Peers

Gianluigi Forloni
Elizabeth Head United States
Thomas Wısnıewskı United States
Bruce A. Yankner United States
Dale E. Bredesen United States
Hui Zheng United States
Michael P. Vitek United States
Guojun Bu United States
Sam Gandy United States
Huaxi Xu United States
Elizabeth Head United States
Gianluigi Forloni
Citations per year, relative to Gianluigi Forloni Gianluigi Forloni (= 1×) peers Elizabeth Head

Countries citing papers authored by Gianluigi Forloni

Since Specialization
Citations

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

Fields of papers citing papers by Gianluigi Forloni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gianluigi Forloni

This figure shows the co-authorship network connecting the top 25 collaborators of Gianluigi Forloni. A scholar is included among the top collaborators of Gianluigi Forloni 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 Gianluigi Forloni. Gianluigi Forloni 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.
Forloni, Gianluigi. (2025). Doxycycline: An essential tool for Alzheimer’s disease. Biomedicine & Pharmacotherapy. 188. 118159–118159. 3 indexed citations
2.
Chiesa, Roberto, Luana Fioriti, Gianluigi Forloni, & Claudia Balducci. (2025). Role of prion protein in mediating the synaptotoxic effects of tau oligomers: Implications for Alzheimer’s disease and related tauopathies. Neural Regeneration Research.
3.
Calabrò, Marco, Chiara Fabbri, Siegfried Kasper, et al.. (2025). A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors. Psychiatric Genetics. 35(2). 17–25. 2 indexed citations
4.
Vitola, Pietro La, Laura Brunelli, Edoardo Micotti, et al.. (2024). Transcriptomic and metabolomic changes might predict frailty in SAMP8 mice. Aging Cell. 23(10). e14263–e14263. 5 indexed citations
5.
Orsini, Franca, Massimiliano De Paola, Rosaria Pascente, et al.. (2024). SARS-CoV-2 Nucleocapsid Protein Induces Tau Pathological Changes That Can Be Counteracted by SUMO2. International Journal of Molecular Sciences. 25(13). 7169–7169. 3 indexed citations
6.
Boeri, Lucia, et al.. (2023). Development of an Induced Pluripotent Stem Cell-Based Liver-on-a-Chip Assessed with an Alzheimer’s Disease Drug. ACS Biomaterials Science & Engineering. 9(7). 4415–4430. 17 indexed citations
7.
Forloni, Gianluigi. (2023). Alpha Synuclein: Neurodegeneration and Inflammation. International Journal of Molecular Sciences. 24(6). 5914–5914. 54 indexed citations
8.
Musardo, Stefano, Silvia Pelucchi, Laura D’Andrea, et al.. (2022). The development of ADAM10 endocytosis inhibitors for the treatment of Alzheimer’s disease. Molecular Therapy. 30(7). 2474–2490. 23 indexed citations
9.
Calabrò, Marco, Chiara Fabbri, Siegfried Kasper, et al.. (2021). Research Domain Criteria (RDoC): A Perspective to Probe the Biological Background behind Treatment Efficacy in Depression. Current Medicinal Chemistry. 28(22). 4296–4320. 2 indexed citations
10.
Fabbri, Chiara, Siegfried Kasper, Alexander Kautzky, et al.. (2020). A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping. Translational Psychiatry. 10(1). 50–50. 35 indexed citations
11.
Paldino, Emanuela, Claudia Balducci, Pietro La Vitola, et al.. (2019). Neuroprotective Effects of Doxycycline in the R6/2 Mouse Model of Huntington’s Disease. Molecular Neurobiology. 57(4). 1889–1903. 40 indexed citations
12.
Vismara, Irma, Simonetta Papa, Emanuele Mauri, et al.. (2019). Selective Modulation of A1 Astrocytes by Drug-Loaded Nano-Structured Gel in Spinal Cord Injury. ACS Nano. 14(1). 360–371. 110 indexed citations
14.
Papa, Simonetta, Filippo Rossi, Irma Vismara, Gianluigi Forloni, & Pietro Veglianese. (2019). Nanovector-Mediated Drug Delivery in Spinal Cord Injury: A Multitarget Approach. ACS Chemical Neuroscience. 10(3). 1173–1182. 21 indexed citations
15.
Mancini, Simona, Claudia Balducci, Edoardo Micotti, et al.. (2017). Multifunctional liposomes delay phenotype progression and prevent memory impairment in a presymptomatic stage mouse model of Alzheimer disease. Journal of Controlled Release. 258. 121–129. 39 indexed citations
16.
Crisafulli, Concetta, Luigi Donato, Marco Calabrò, et al.. (2016). Role of neurodevelopment involved genes in psychiatric comorbidities and modulation of inflammatory processes in Alzheimer's disease. Journal of the Neurological Sciences. 370. 162–166. 13 indexed citations
17.
Gallucci, Maurizio, Fausta Ongaro, Silvia Meggiolaro, et al.. (2010). Factors related to disability: Evidence from the “Treviso Longeva (TRELONG) Study”. Archives of Gerontology and Geriatrics. 52(3). 309–316. 18 indexed citations
18.
Albani, Diego, Sara Batelli, Marzia Pesaresi, et al.. (2007). A novel PSENEN mutation in a patient with complaints of memory loss and a family history of dementia. Alzheimer s & Dementia. 3(3). 235–238. 8 indexed citations
19.
Cella, Silvano G., Vittorio Locatelli, Tiziana Mennini, et al.. (1990). Deprivation of Growth Hormone-Releasing Hormone Early in the Rat’s Neonatal Life Permanently Affects Somatotropic Function. Endocrinology. 127(4). 1625–1634. 38 indexed citations
20.

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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