Evidence map›Paper›PMID 35216421›Full record

ArticleInternational journal of molecular sciences2022

Comparison of Different Mass Spectrometry Workflows for the Proteomic Analysis of Tear Fluid.

Garrett Jones, Tae Jin Lee, Joshua Glass, Grace Rountree, Lane Ulrich, Amy Estes, Mary Sezer, Wenbo Zhi, Shruti Sharma, Ashok Sharma

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
6.8field-weighted citation impact, top 3% 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

23 citing papers in PubMed, 37 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Tear fluid database: a reference website for tear fluid proteomics.Database : the journal of biological databases and curation · 2026
    Article
  6. Review
  7. Tear fluid proteomics: a comparative study of DIA and DDA mass spectrometry.Journal of mass spectrometry and advances in the clinical lab · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Unraveling the Intraday Variations in the Tear Fluid Proteome.Investigative ophthalmology & visual science · 2024
    Article
  17. Article
  18. Intrinsic Disorder in the Human Tear Proteome.Investigative ophthalmology & visual science · 2023
    Article
  19. Article
  20. 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

10 authors at 1 institution in 1 country.

Garrett JonesCenter for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Tae Jin LeeCenter for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Joshua GlassCenter for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Grace RountreeCenter for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Lane UlrichDepartment of Ophthalmology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Amy EstesDepartment of Ophthalmology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Mary SezerDepartment of Ophthalmology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Wenbo ZhiCenter for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Shruti SharmaCenter for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Ashok SharmaCenter for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.ORCID 0000-0001-9597-4374
Augusta University · US

Funding

Module 3: Gene Expression/ProteomicsP30EY031631 · NEI · AUGUSTA UNIVERSITY · PI Xingjun Fan · 2020 to 2026
$3.6M
Proteomic Biomarkers for Glaucomatous Optic NeuropathyR01EY029728 · NEI · AUGUSTA UNIVERSITY · PI SHARMA, ASHOK · 2019 to 2022
$1.5M
NEI NIH HHS P30 EY031631
6 · The paper itself

Abstract

The tear film is a multi-layer fluid that covers the corneal and conjunctival epithelia of the eye and provides lubrication, nutrients, and protection from the outside environment. Tear fluid contains a high concentration of proteins and has thus been recognized as a potential source of biomarkers for ocular disorders due to its proximity to disease sites on the ocular surface and the non-invasive nature of its collection. This is particularly true in the case of dry eye disease, which directly impacts the tear film and its components. Proteomic analysis of tear fluid is challenging mainly due to the wide dynamic range of proteins and the small sample volumes. However, recent advancements in mass spectrometry have revolutionized the field of proteomics enabling unprecedented depth, speed, and accuracy, even with small sample volumes. In this study using the Orbitrap Fusion Tribrid mass spectrometer, we compared four different mass spectrometry workflows for the proteomic analysis of tear fluid collected via Schirmer strips. We were able to establish a method of in-strip protein digestion that identified >3000 proteins in human tear samples from 11 healthy subjects. Our method offers a significant improvement in the number of proteins identified compared to previously reported methods without pooling samples.

Indexed as

AdultBiomarkersDry Eye SyndromesEye ProteinsFemaleHumansMaleMass SpectrometryMiddle AgedProteomicsTearsWorkflowYoung AdultBiomarkersEye Proteinsbiomarkersdry eye diseasemass spectrometryocular surfaceproteomicstear film

Identifiers

PMID35216421
PMCPMC8875482
OpenAlexW4212848637

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.