Evidence map›Paper›PMID 41246491›Full record

ArticleNanophotonics (Berlin, Germany)2025

Diagnostic oriented discrimination of different Shiga toxins via PCA-assisted SERS-based plasmonic metasurface.

Massimo Rippa, Alessia Milano, Valentina Marchesano, Domenico Sagnelli, Bryan Guilcapi, Amalia D'Avino, Giovanna Palermo, Giuseppe Strangi, Luciano Consagra, Maurizio Brigotti and 3 more

Abstract read
In one paragraph

Article in Nanophotonics (Berlin, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Massimo RippaInstitute of Applied Sciences and Intelligent Systems "E. Caianiello" CNR, Pozzuoli, Italy.ORCID https://orcid.org/0000-0002-1993-4589
Alessia MilanoInstitute of Applied Sciences and Intelligent Systems "E. Caianiello" CNR, Pozzuoli, Italy.
Valentina MarchesanoInstitute of Applied Sciences and Intelligent Systems "E. Caianiello" CNR, Pozzuoli, Italy.
Domenico SagnelliInstitute of Applied Sciences and Intelligent Systems "E. Caianiello" CNR, Pozzuoli, Italy.
Bryan GuilcapiInstitute of Applied Sciences and Intelligent Systems "E. Caianiello" CNR, Pozzuoli, Italy.
Amalia D'AvinoInstitute of Applied Sciences and Intelligent Systems "E. Caianiello" CNR, Pozzuoli, Italy.
Giovanna PalermoDepartment of Physics, NLHT-Lab, University of Calabria, Arcavacata, Italy.
Giuseppe StrangiDepartment of Physics, NLHT-Lab, University of Calabria, Arcavacata, Italy.
Luciano ConsagraDipartimento di Scienze Mediche e Chirurgiche, Sede di Patologia Generale, Università di Bologna, Bologna, Italy.
Maurizio BrigottiDipartimento di Scienze Mediche e Chirurgiche, Sede di Patologia Generale, Università di Bologna, Bologna, Italy.
Stefano MorabitoDepartment of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanitá, Rome, Italy.
Joseph ZyssLumière, Matière et Interfaces (LUMIN) Laboratory, Institut D'Alembert, Ecole Normale Supérieure Paris-Saclay, Université Paris Saclay, Gif sur Yvette, France.
Lucia PettiInstitute of Applied Sciences and Intelligent Systems "E. Caianiello" CNR, Pozzuoli, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plasmonic biosensors are powerful platforms for detecting various types of analytes. Specifically, surface-enhanced Raman spectroscopy (SERS) can enable label-free and selective detection. Shiga toxin-producing

Indexed as

metasurfacePCAplasmonicSERSShiga toxin

Identifiers

PMID41246491
PMCPMC12617738

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.