Evidence map›Paper›PMID 38203309›Full record

ArticleInternational journal of molecular sciences2023

The Immune Signature of CSF in Multiple Sclerosis with and without Oligoclonal Bands: A Machine Learning Approach to Proximity Extension Assay Analysis.

Lorenzo Gaetani, Giovanni Bellomo, Elena Di Sabatino, Silvia Sperandei, Andrea Mancini, Kaj Blennow, Henrik Zetterberg, Lucilla Parnetti, Massimiliano Di Filippo

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. CSF Proteins Associated With Neuroaxonal Damage in Early Active Multiple Sclerosis.Neurology(R) neuroimmunology & neuroinflammation · 2026
    Article
  2. Article
  3. Integrated multi-omics and machine learning prioritize key immune genes for multiple sclerosis risk prediction.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
  4. Article
  5. Article
  6. Semi-Supervised Learning for Predicting Multiple Sclerosis.Journal of personalized medicine · 2025
    Article
  7. Review
  8. Artificial Intelligence and Multiple Sclerosis.Current neurology and neuroscience reports · 2024
    Review
  9. 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 4 countries.

Lorenzo GaetaniSection of Neurology, Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.ORCID 0000-0003-3967-8954
Giovanni BellomoSection of Neurology, Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.ORCID 0000-0003-0456-5650
Elena Di SabatinoSection of Neurology, Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.
Silvia SperandeiSection of Neurology, Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.
Andrea ManciniSection of Neurology, Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.ORCID 0000-0003-0817-4729
Kaj BlennowInstitute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, 431 41 Mölndal, Sweden.
Henrik ZetterbergInstitute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, 431 41 Mölndal, Sweden.
Lucilla ParnettiSection of Neurology, Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.ORCID 0000-0001-5722-3967
Massimiliano Di FilippoSection of Neurology, Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.
University of Perugia · ITSahlgrenska University Hospital · SEUniversity of Wisconsin–Madison · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early diagnosis of multiple sclerosis (MS) relies on clinical evaluation, magnetic resonance imaging (MRI), and cerebrospinal fluid (CSF) analysis. Reliable biomarkers are needed to differentiate MS from other neurological conditions and to define the underlying pathogenesis. This study aimed to comprehensively profile immune activation biomarkers in the CSF of individuals with MS and explore distinct signatures between MS with and without oligoclonal bands (OCB). A total of 118 subjects, including relapsing-remitting MS with OCB (MS OCB+) (

Indexed as

Multiple SclerosisMultiple Sclerosis, Relapsing-RemittingAxonsBiological AssayHumansOligoclonal BandsOligoclonal Bandsbiomarkerscerebrospinal fluidmachine learningmultiple sclerosisoligoclonal bandsproximity extension assay

Identifiers

PMID38203309
PMCPMC10778830
OpenAlexW4390050793

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.