Evidence map›Paper›PMID 34071694›Full record

ArticleSensors (Basel, Switzerland)2021

Design of an Innovative Methodology for Cerebrospinal Fluid Analysis: Preliminary Results.

Tommaso Schirinzi, Alberto Cordella, Nicola Biagio Mercuri, Arnaldo D'Amico, Andrea Palombi, Alessandro Zompanti, Simone Grasso, Giorgio Pennazza, Marco Santonico

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 46% of its field
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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
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

9 authors at 3 institutions in 2 countries.

Tommaso SchirinziDepartment of Systems Medicine, University of Roma Tor Vergata, 00133 Rome, Italy.
Alberto CordellaIRCCS Fondazione Santa Lucia, Via Ardeatina 306, 00179 Rome, Italy.
Nicola Biagio MercuriDepartment of Systems Medicine, University of Roma Tor Vergata, 00133 Rome, Italy.ORCID 0000-0001-6700-7491
Arnaldo D'AmicoDepartment of Electronic Engineering, University of Roma Tor Vergata, 00133 Rome, Italy.
Andrea PalombiDepartment of Electronic Engineering, University of Roma Tor Vergata, 00133 Rome, Italy.
Alessandro ZompantiDepartment of Engineering, Campus Bio-Medico, University of Rome Italy, 00128 Rome, Italy.ORCID 0000-0001-5986-4426
Simone GrassoDepartment of Science and Technology for Humans and the Environment, Campus Bio-Medico, University of Rome Italy, 00128 Rome, Italy.ORCID 0000-0003-0507-7966
Giorgio PennazzaDepartment of Engineering, Campus Bio-Medico, University of Rome Italy, 00128 Rome, Italy.ORCID 0000-0003-4843-9445
Marco SantonicoDepartment of Science and Technology for Humans and the Environment, Campus Bio-Medico, University of Rome Italy, 00128 Rome, Italy.
Università Campus Bio-Medico · ITUniversity of Rome Tor Vergata · ITFondazione Santa Lucia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cerebrospinal fluid (CSF) analysis supports diagnosis of neurodegenerative diseases (NDs), however a number of issues limits its potentialities in clinical practice. Here, a newly developed technique for fluid voltammetry, relying on a simple sensor (BIOsensor-based multisensorial system for mimicking Nose, Tongue and Eyes, BIONOTE), was used to test the applicability for CSF analysis. BIONOTE was initially calibrated on an artificial CSF-like solution and then applied on human CSF, either immediately after collection or after refrigerated storage. Following optimization, it was used to evaluate 11 CSF samples correlating the electrochemical dataset with CSF routine parameters and biomarkers of neurodegeneration. Multivariate data analysis was performed for model elaboration and calibration using principal component analysis and partial least squares discriminant analysis. BIONOTE presented a high capacity to predict both physiological and pathological constituents of artificial CSF. It differentiated distinct fresh human CSF samples well but lost accuracy after refrigerated storage. The electrochemical analysis-derived data correlated with either CSF routine cytochemical indexes or a biomarker of neurodegeneration. BIONOTE resulted as being a reliable system for electrochemical analysis of CSF. The CSF fingerprint provided by the sensor has shown itself to be sensitive to CSF modification, thus it is potentially representative of CSF alteration. This result opens the way to its testing in further study addressed at assessing the clinical relevance of the methodology. Because of its advantages due to the ease and rapidity of the methodology, a validation study is now required to translate the technique into clinical practice and improve diagnostic workup of NDs.

Indexed as

Biosensing TechniquesNeurodegenerative DiseasesBiomarkersDiscriminant AnalysisHumansBiomarkersbiomarkersCSFelectrochemical analysisneurodegenerative diseasesvoltammetry

Identifiers

PMID34071694
PMCPMC8198196
OpenAlexW3165784391

What OpenQuestion 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 OpenQuestion graph.