Evidence map›Paper›PMID 34876936›Full record

ReviewThe EPMA journal2021

Mass spectrometry analysis of human tear fluid biomarkers specific for ocular and systemic diseases in the context of 3P medicine.

Xianquan Zhan, Jiajia Li, Yuna Guo, Olga Golubnitschaja

Open access · hybridAbstract readReview
In one paragraph

Review in The EPMA journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed, 1 pooled it
19.2field-weighted citation impact, top 1% 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

78 citing papers in PubMed, 1 synthesis or guideline pooled it, 131 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Tear fluid database: a reference website for tear fluid proteomics.Database : the journal of biological databases and curation · 2026
    Article
  11. Smart contact lenses: recent advances and future challenges in eye disease diagnosis and treatment.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
    Review
  12. Article
  13. Article
  14. Review
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  17. Review
  18. Article
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  20. Article

18 more citing papers are in PubMed but not listed here.

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

4 authors at 3 institutions in 2 countries.

Xianquan ZhanShandong Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, 440 Jiyan Road, Jinan, 250117 Shandong China.
Jiajia LiMedical Science and Technology Innovation Center, Shandong First Medical University, 6699 Qingdao Road, Jinan, 250117 Shandong China.
Yuna GuoMedical Science and Technology Innovation Center, Shandong First Medical University, 6699 Qingdao Road, Jinan, 250117 Shandong China.
Olga GolubnitschajaPredictive, Preventive and Personalised (3P) Medicine, Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-University of Bonn, Sigmund-Freud-Str 25, 53105 Bonn, Germany.
Shandong First Medical University · CNShandong Tumor Hospital · CNUniversity Hospital Bonn · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last two decades, a large number of non-communicable/chronic disorders reached an epidemic level on a global scale such as diabetes mellitus type 2, cardio-vascular disease, several types of malignancies, neurological and eye pathologies-all exerted system's enormous socio-economic burden to primary, secondary, and tertiary healthcare. The paradigm change from reactive to predictive, preventive, and personalized medicine (3PM/PPPM) has been declared as an essential transformation of the overall healthcare approach to benefit the patient and society at large. To this end, specific biomarker panels are instrumental for a cost-effective predictive approach of individualized prevention and treatments tailored to the person. The source of biomarkers is crucial for specificity and reliability of diagnostic tests and treatment targets. Furthermore, any diagnostic approach preferentially should be noninvasive to increase availability of the biomaterial, and to decrease risks of potential complications as well as concomitant costs. These requirements are clearly fulfilled by tear fluid, which represents a precious source of biomarker panels. The well-justified principle of a "sick eye in a sick body" makes comprehensive tear fluid biomarker profiling highly relevant not only for diagnostics of eye pathologies but also for prediction, prognosis, and treatment monitoring of systemic diseases. One prominent example is the Sicca syndrome linked to a cascade of severe complications that include dry eye, neurologic, and oncologic diseases. In this review, protein profiles in tear fluid are highlighted and corresponding biomarkers are exemplified for several relevant pathologies, including dry eye disease, diabetic retinopathy, cancers, and neurological disorders. Corresponding analytical approaches such as sample pre-processing, differential proteomics, electrophoretic techniques, high-performance liquid chromatography (HPLC), enzyme-linked immuno-sorbent assay (ELISA), microarrays, and mass spectrometry (MS) methodology are detailed. Consequently, we proposed the overall strategies based on the tear fluid biomarkers application for 3P medicine practice. In the context of 3P medicine, tear fluid analytical pathways are considered to predict disease development, to target preventive measures, and to create treatment algorithms tailored to individual patient profiles.

Indexed as

2D-PAGEAntimicrobial compoundsAutoantibodyBiomarker panelBreast cancerCalgranulinCost-efficacyCOVID-19Diabetic retinopathyDifferential proteomicsDry eyeElectrophoretic techniquesELISAGlaucomaHealthcare economyHPLCIndividualized patient profilingInflammatory cytokinesIn-gel digestionMALDI-TOFMass spectrometry (MS)Meibomian gland dysfunctionMelanomaMicroarraysMMP-9Multiple sclerosisNovel targetsOcular allergyOcular pathologiesPandemicParkinson’s diseasePatternsPersonalized servicesPost-translational modification (PTM)Predictive preventive personalized medicine (3PM/PPPM)Prostate cancerRetinoblastomaS100Sample processingSchirmer testSDS-PAGESicca syndromeSjögren syndromeSocio-economic impactsSub-optimal healthSystemic disordersTear fluidThyroid-associated ophthalmopathy

Identifiers

PMID34876936
PMCPMC8639411
OpenAlexW4200517423

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.