Author

Andrea Truini

Sapienza University of RomeORCID 0000-0002-2630-7647Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:electronic health records· 2 Organism:rat· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Anthony Edward PickeringiD· 2 shared Anthony James BlockeeliD· 2 shared James DunhamiD· 2 shared Rolf‐Detlef TreedeiD· 2 shared André MourauxiD· 1 shared Anna C. SalesiD· 1 shared Caterina Maria LeoneiD· 1 shared Jeffrey L. KrajewskiiD· 1 shared

Activity by Year

2021-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersNeuroscience

Anthony Edward PickeringORCID

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2 papers

Recent·Most cited

NeurosciencePainPeer-reviewedOct 20, 2025

Preclinical assay of the effects of lacosamide, pregabalin and tapentadol on the rat N1 spinal somatosensory evoked potential.

Kenneth A Steel, James Dunham, Caterina Maria Leone…·Anthony Edward Pickering

This study assesses the effects of lacosamide, pregabalin, and tapentadol on the rat spinal N1 somatosensory evoked potential to evaluate their analgesic mechanisms.

DOI 10.1097/j.pain.0000000000003810

ratelectronic health records

𝕏 PostBluesky

NeurosciencebioRxivPreprintAug 10, 2021

Trial by trial, machine learning approach identifies temporally discrete Aδ- and C-fibre mediated laser evoked potentials that predict pain behaviour in rats.

Anna C. Sales, Anthony James Blockeel, John R. Huxter…·Anthony Edward Pickering

The paper uses machine learning to analyze single-trial laser evoked potentials (LEPs) in rats, identifying distinct Aδ- and C-fibre mediated responses that predict pain behavior.

2 citations

ratelectronic health records

𝕏 PostBluesky