Adrian Newman‐Tancredi

11.9k total citations
241 papers, 9.8k citations indexed

About

Adrian Newman‐Tancredi is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Psychiatry and Mental health. According to data from OpenAlex, Adrian Newman‐Tancredi has authored 241 papers receiving a total of 9.8k indexed citations (citations by other indexed papers that have themselves been cited), including 194 papers in Cellular and Molecular Neuroscience, 149 papers in Molecular Biology and 34 papers in Psychiatry and Mental health. Recurrent topics in Adrian Newman‐Tancredi's work include Neurotransmitter Receptor Influence on Behavior (161 papers), Receptor Mechanisms and Signaling (138 papers) and Neuroscience and Neuropharmacology Research (100 papers). Adrian Newman‐Tancredi is often cited by papers focused on Neurotransmitter Receptor Influence on Behavior (161 papers), Receptor Mechanisms and Signaling (138 papers) and Neuroscience and Neuropharmacology Research (100 papers). Adrian Newman‐Tancredi collaborates with scholars based in France, Poland and Netherlands. Adrian Newman‐Tancredi's co-authors include Didier Cussac, Mark J. Millan, Valérie Audinot, Mark J. Millan, Jean‐Michel Rivet, Alain P. Gobert, Ronan Depoortère, Mark S. Kleven, F. Lejeune and Laurent Bardin and has published in prestigious journals such as Scientific Reports, Biochemical Journal and Brain Research.

In The Last Decade

Adrian Newman‐Tancredi

238 papers receiving 9.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Adrian Newman‐Tancredi France	56	6.8k	4.6k	1.6k	1.4k	1.0k	241	9.8k
Ángel Pazos Spain	48	7.3k 1.1×	4.2k 0.9×	944 0.6×	2.1k 1.5×	1.6k 1.5×	168	10.7k
Ben H.C. Westerink Netherlands	56	6.3k 0.9×	3.6k 0.8×	726 0.5×	905 0.7×	1.3k 1.2×	180	9.1k
Claude de Montigny Canada	61	8.1k 1.2×	4.6k 1.0×	1.9k 1.2×	3.0k 2.2×	1.7k 1.6×	154	12.1k
Bryan K. Yamamoto United States	52	5.8k 0.9×	2.3k 0.5×	530 0.3×	1.1k 0.8×	883 0.8×	148	8.7k
Mark J. Millan France	47	4.5k 0.7×	2.8k 0.6×	805 0.5×	705 0.5×	735 0.7×	122	6.6k
Stephen J. Peroutka United States	56	7.4k 1.1×	5.0k 1.1×	2.4k 1.5×	1.3k 0.9×	852 0.8×	156	12.2k
Maurizio Raiteri Italy	56	8.7k 1.3×	6.1k 1.3×	685 0.4×	881 0.6×	1.2k 1.2×	273	11.3k
Frank P. Bymaster United States	57	6.6k 1.0×	5.0k 1.1×	3.1k 2.0×	3.1k 2.3×	1.6k 1.5×	141	12.7k
Jos Prickaerts Netherlands	62	3.7k 0.5×	5.1k 1.1×	896 0.6×	2.8k 2.0×	1.6k 1.6×	239	11.7k
Guy A. Higgins Canada	60	5.9k 0.9×	3.8k 0.8×	842 0.5×	1.2k 0.8×	1.6k 1.6×	153	9.1k

Countries citing papers authored by Adrian Newman‐Tancredi

Since Specialization

Citations

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

Fields of papers citing papers by Adrian Newman‐Tancredi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Adrian Newman‐Tancredi. 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 Adrian Newman‐Tancredi. The network helps show where Adrian Newman‐Tancredi may publish in the future.

Co-authorship network of co-authors of Adrian Newman‐Tancredi

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

All Works

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20 of 20 papers shown

Śniecikowska, Joanna, Monika Głuch‐Lutwin, Adam Bucki, et al.. (2025). Discovery of NLX-266, an Orally Available and Metabolically Stable ERK1/2-Biased 5-HT_1AR Agonist with Superior Antidepressant and Antiparkinsonian Activity. Journal of Medicinal Chemistry. 68(9). 9706–9722.

Xin, Tao, et al.. (2025). Acute administration of NLX-101, a Serotonin 1A receptor agonist, improves auditory temporal processing during development in a mouse model of Fragile X Syndrome. Journal of Neurodevelopmental Disorders. 17(1). 1–1. 1 indexed citations

Vahid-Ansari, Faranak, et al.. (2024). Rapid reorganization of serotonin projections and antidepressant response to 5-HT1A-biased agonist NLX-101 in fluoxetine-resistant cF1ko mice. Neuropharmacology. 261. 110132–110132. 4 indexed citations

Depoortère, Ronan, Andrew C. McCreary, Benjamin Vidal, et al.. (2024). Pharmacodynamic, pharmacokinetic and rat brain receptor occupancy profile of NLX-112, a highly selective 5-HT1A receptor biased agonist. Naunyn-Schmiedeberg s Archives of Pharmacology. 398(1). 991–1002. 1 indexed citations

Papp, Mariusz, Piotr Gruca, Ewa Litwa, et al.. (2024). The 5-HT1A receptor biased agonists, NLX-204 and NLX-101, like ketamine, elicit rapid-acting antidepressant activity in the rat chronic mild stress model via cortical mechanisms. Journal of Psychopharmacology. 38(7). 661–671. 8 indexed citations

Depoortère, Ronan, Laurent Bardin, & Adrian Newman‐Tancredi. (2024). Fentanyl dose-sparing in polyarthritic rats requires full agonism at 5-HT1A receptors: Comparison between NLX-112, (±)8-OH-DPAT, and buspirone. Journal of Opioid Management. 20(4). 269–274. 1 indexed citations

Vidal, Benjamin, et al.. (2023). Multimodal imaging study of the 5-HT1A receptor biased agonist, NLX-112, in a model of L-DOPA-induced dyskinesia. NeuroImage Clinical. 39. 103497–103497. 5 indexed citations

Depoortère, Ronan, Jack Bergman, Patrick M. Beardsley, et al.. (2022). NLX-112, a highly selective 5-HT1A receptor biased agonist, does not exhibit misuse potential in male rats or macaques. Neuropharmacology. 210. 109025–109025. 1 indexed citations

Pilar-Cuéllar, Fuencisla, et al.. (2022). Molecular Signaling Mechanisms for the Antidepressant Effects of NLX-101, a Selective Cortical 5-HT1A Receptor Biased Agonist. Pharmaceuticals. 15(3). 337–337. 8 indexed citations

10.

Depoortère, Ronan, Agnès L. Auclair, & Adrian Newman‐Tancredi. (2020). NLX-101, a highly selective 5-HT1A receptor biased agonist, mediates antidepressant-like activity in rats via prefrontal cortex 5-HT1A receptors. Behavioural Brain Research. 401. 113082–113082. 14 indexed citations

11.

Śniecikowska, Joanna, Monika Głuch‐Lutwin, Adam Bucki, et al.. (2020). Discovery of Novel pERK1/2- or β-Arrestin-Preferring 5-HT _1A Receptor-Biased Agonists: Diversified Therapeutic-like versus Side Effect Profile. Journal of Medicinal Chemistry. 63(19). 10946–10971. 23 indexed citations

12.

Śniecikowska, Joanna, Monika Głuch‐Lutwin, Adam Bucki, et al.. (2019). Novel Aryloxyethyl Derivatives of 1-(1-Benzoylpiperidin-4-yl)methanamine as the Extracellular Regulated Kinases 1/2 (ERK1/2) Phosphorylation-Preferring Serotonin 5-HT_1A Receptor-Biased Agonists with Robust Antidepressant-like Activity. Journal of Medicinal Chemistry. 62(5). 2750–2771. 29 indexed citations

13.

Iderberg, Hanna, Andrew C. McCreary, Mark A. Varney, M. Angela Cenci, & Adrian Newman‐Tancredi. (2015). Activity of serotonin 5-HT1A receptor ‘biased agonists’ in rat models of Parkinson's disease and l-DOPA-induced dyskinesia. Neuropharmacology. 93. 52–67. 57 indexed citations

14.

Becker, Guillaume, Nathalie Streichenberger, Thierry Billard, Adrian Newman‐Tancredi, & Luc Zimmer. (2014). A Postmortem Study to Compare Agonist and Antagonist 5‐HT_1A Receptor‐binding Sites in Alzheimer's Disease. CNS Neuroscience & Therapeutics. 20(10). 930–934. 17 indexed citations

15.

Lemoine, Laëtitia, Guillaume Becker, Bernard Vacher, et al.. (2012). Radiosynthesis and Preclinical Evaluation of¹⁸F-F13714 as a Fluorinated 5-HT_1AReceptor Agonist Radioligand for PET Neuroimaging. Journal of Nuclear Medicine. 53(6). 969–976. 20 indexed citations

16.

Berrocoso, Esther, J.A. Micó, Olivier Vitton, et al.. (2011). Evaluation of milnacipran, in comparison with amitriptyline, on cold and mechanical allodynia in a rat model of neuropathic pain. European Journal of Pharmacology. 655(1-3). 46–51. 46 indexed citations

17.

Lemoine, Laëtitia, Mathieu Verdurand, Bernard Vacher, et al.. (2008). Synthesis, fluorine-18 labelling and radiopharmacological evaluation of F15599, a novel 5-HT1A receptor agonist. 49(6). 463–70. 4 indexed citations

18.

Cosi, Cristina, et al.. (2006). Partial agonist properties of the antipsychotics SSR181507, aripiprazole and bifeprunox at dopamine D2 receptors: G protein activation and prolactin release. European Journal of Pharmacology. 535(1-3). 135–144. 70 indexed citations

19.

Millan, Mark J., Mauricette Brocco, Jean‐Michel Rivet, et al.. (2000). S18327 (1-[2-[4-(6-fluoro-1, 2-benzisoxazol-3-yl)piperid-1-yl]ethyl]3-phenyl imidazolin-2-one), a novel, potential antipsychotic displaying marked antagonist properties at alpha(1)- and alpha(2)-adrenergic receptors: II. Functional profile and a multiparametric comparison with haloperidol, clozapine, and 11 other antipsychotic agents.. PubMed. 292(1). 54–66. 46 indexed citations

20.

Newman‐Tancredi, Adrian, Valérie Audinot, Vincent Jacques, J.‐L. PEGLION, & Mark J. Millan. (1995). [3H](+)S 14297: A novel, selective radioligand at cloned human dopamine D3 receptors. Neuropharmacology. 34(12). 1693–1696. 9 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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