Evidence map›Paper›PMID 34764849›Full record

ArticleFrontiers in neuroscience2021

Identification of the Raman Salivary Fingerprint of Parkinson's Disease Through the Spectroscopic- Computational Combinatory Approach.

Cristiano Carlomagno, Dario Bertazioli, Alice Gualerzi, Silvia Picciolini, Michele Andrico, Francesca Rodà, Mario Meloni, Paolo Innocente Banfi, Federico Verde, Nicola Ticozzi and 3 more

2 registry-linked trialsAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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.

NCT05320250 completednot on this map

Raman Spectroscopy Analysis of Saliva and Salivary Extracellular Vesicles as New Biomarkers for Parkinson's Disease and Atypical Parkinsonisms.

TypeobservationalSponsorFondazione Don Carlo Gnocchi ETSRan2021 to 2024Enrolled165ConditionsParkinson's Disease and ParkinsonismArmsSingle saliva collection, Saliva collection, longitudinal
NCT06869135 recruitingnot on this mapstarted 2025, after this paper: background citation

Novel Method for Diagnosis of Neurodegenerative Diseases Based on Saliva Biochemical Profiling

Typeobservational_patient_registrySponsorFondazione Don Carlo Gnocchi ETSRan2025 to 2027Enrolled242ConditionsNeurodegenerative Diseases, Parkinson Disease, Alzheimer Disease, ParkinsonismArmsSaliva collection, longitudinal
3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Utility of Raman Spectroscopy in Pulmonary Medicine.Advances in respiratory medicine · 2024
    Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Raman Spectroscopy as a Tool to Study the Pathophysiology of Brain Diseases.International journal of molecular sciences · 2023
    Review
  14. Review
  15. 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.

Cristiano CarlomagnoIRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
Dario BertazioliUniversità degli Studi di Milano-Bicocca, Milan, Italy.
Alice GualerziIRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
Silvia PiccioliniIRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
Michele AndricoUniversità degli Studi di Milano-Bicocca, Milan, Italy.
Francesca RodàIRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
Mario MeloniIRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
Paolo Innocente BanfiIRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
Federico VerdeLaboratory of Neuroscience, Department of Neurology-Stroke Un, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Nicola TicozziLaboratory of Neuroscience, Department of Neurology-Stroke Un, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Vincenzo SilaniLaboratory of Neuroscience, Department of Neurology-Stroke Un, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Enza MessinaUniversità degli Studi di Milano-Bicocca, Milan, Italy.
Marzia BedoniIRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the wide range of proposed biomarkers for Parkinson's disease (PD), there are no specific molecules or signals able to early and uniquely identify the pathology onset, progression and stratification. Saliva is a complex biofluid, containing a wide range of biological molecules shared with blood and cerebrospinal fluid. By means of an optimized Raman spectroscopy procedure, the salivary Raman signature of PD can be characterized and used to create a classification model. Raman analysis was applied to collect the global signal from the saliva of 23 PD patients and related pathological and healthy controls. The acquired spectra were computed using machine and deep learning approaches. The Raman database was used to create a classification model able to discriminate each spectrum to the correct belonging group, with accuracy, specificity, and sensitivity of more than 97% for the single spectra attribution. Similarly, each patient was correctly assigned with discriminatory power of more than 90%. Moreover, the extracted data were significantly correlated with clinical data used nowadays for the PD diagnosis and monitoring. The preliminary data reported highlight the potentialities of the proposed methodology that, once validated in larger cohorts and with multi-centered studies, could represent an innovative minimally invasive and accurate procedure to determine the PD onset, progression and to monitor therapies and rehabilitation efficacy.

Indexed as

classification modeldeep learningParkinson’s diseaseRaman spectroscopysaliva

Identifiers

PMID34764849
PMCPMC8576466

What OpenQuestion holds

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Registered trials

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.