Protein profile analysis of tear fluid with hyphenated HPLC-UV LED-induced fluorescence detection for the diagnosis of dry eye syndrome

Sphurti S. Adigal; Sulatha V. Bhandary; Nagaraj Hegde; V. R. Nidheesh; Reena V. John; Alisha Rizvi; Sajan D. George; V. B. Kartha; Santhosh Chidangil

doi:10.1039/d3ra04389d

Protein profile analysis of tear fluid with hyphenated HPLC-UV LED-induced fluorescence detection for the diagnosis of dry eye syndrome

Sphurti S. Adigal, Sulatha V. Bhandary, Nagaraj Hegde, V. R. Nidheesh, Reena V. John, Alisha Rizvi, Sajan D. George, V. B. Kartha, Santhosh Chidangil^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

Tear fluid contains organic and inorganic constituents, variations in their relative concentrations could provide valuable information and can be useful for the detection of several ophthalmological diseases. This report describes the application of the lab-assembled light-emitting diode (LED)-based high-performance liquid chromatography system for protein profiling of tear fluids to diagnose dry eye disease. Principal Component Analysis (PCA), match/no-match, and Artificial Neural Network (ANN) based binary classification of protein profile data were performed for disease diagnosis. Results from the match/no-match test of the protein profile data showed 94.4% sensitivity and 87.8% specificity. ANN with the leaving one out procedure has given 91.6% sensitivity and 93.9% specificity.

Original language	English
Pages (from-to)	22559-22568
Number of pages	10
Journal	RSC Advances
Volume	13
Issue number	32
DOIs	https://doi.org/10.1039/d3ra04389d
Publication status	Published - 26-07-2023

All Science Journal Classification (ASJC) codes

General Chemistry
General Chemical Engineering

Access to Document

10.1039/d3ra04389d

Cite this

@article{ee8a31ef01cb47e0b4780efd2da678e4,

title = "Protein profile analysis of tear fluid with hyphenated HPLC-UV LED-induced fluorescence detection for the diagnosis of dry eye syndrome",

abstract = "Tear fluid contains organic and inorganic constituents, variations in their relative concentrations could provide valuable information and can be useful for the detection of several ophthalmological diseases. This report describes the application of the lab-assembled light-emitting diode (LED)-based high-performance liquid chromatography system for protein profiling of tear fluids to diagnose dry eye disease. Principal Component Analysis (PCA), match/no-match, and Artificial Neural Network (ANN) based binary classification of protein profile data were performed for disease diagnosis. Results from the match/no-match test of the protein profile data showed 94.4\% sensitivity and 87.8\% specificity. ANN with the leaving one out procedure has given 91.6\% sensitivity and 93.9\% specificity.",

author = "Adigal, \{Sphurti S.\} and Bhandary, \{Sulatha V.\} and Nagaraj Hegde and Nidheesh, \{V. R.\} and John, \{Reena V.\} and Alisha Rizvi and George, \{Sajan D.\} and Kartha, \{V. B.\} and Santhosh Chidangil",

note = "Funding Information: The authors are thankful to VGST (GRD No. 459), Govt. of Karnataka, for sanctioning a grant to establish an HPLC facility under the scheme Centre of Excellence in Science. Ms Sphurti S. Adigal is thankful to Manipal Academy of Higher Education for the Dr TMA Pai PhD Scholarship. The authors are also thankful to the Department of Ophthalmology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal. Publisher Copyright: {\textcopyright} 2023 The Royal Society of Chemistry.",

year = "2023",

month = jul,

day = "26",

doi = "10.1039/d3ra04389d",

language = "English",

volume = "13",

pages = "22559--22568",

journal = "RSC Advances",

issn = "2046-2069",

publisher = "Royal Society of Chemistry",

number = "32",

}

TY - JOUR

T1 - Protein profile analysis of tear fluid with hyphenated HPLC-UV LED-induced fluorescence detection for the diagnosis of dry eye syndrome

AU - Adigal, Sphurti S.

AU - Bhandary, Sulatha V.

AU - Hegde, Nagaraj

AU - Nidheesh, V. R.

AU - John, Reena V.

AU - Rizvi, Alisha

AU - George, Sajan D.

AU - Kartha, V. B.

AU - Chidangil, Santhosh

N1 - Funding Information: The authors are thankful to VGST (GRD No. 459), Govt. of Karnataka, for sanctioning a grant to establish an HPLC facility under the scheme Centre of Excellence in Science. Ms Sphurti S. Adigal is thankful to Manipal Academy of Higher Education for the Dr TMA Pai PhD Scholarship. The authors are also thankful to the Department of Ophthalmology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal. Publisher Copyright: © 2023 The Royal Society of Chemistry.

PY - 2023/7/26

Y1 - 2023/7/26

N2 - Tear fluid contains organic and inorganic constituents, variations in their relative concentrations could provide valuable information and can be useful for the detection of several ophthalmological diseases. This report describes the application of the lab-assembled light-emitting diode (LED)-based high-performance liquid chromatography system for protein profiling of tear fluids to diagnose dry eye disease. Principal Component Analysis (PCA), match/no-match, and Artificial Neural Network (ANN) based binary classification of protein profile data were performed for disease diagnosis. Results from the match/no-match test of the protein profile data showed 94.4% sensitivity and 87.8% specificity. ANN with the leaving one out procedure has given 91.6% sensitivity and 93.9% specificity.

AB - Tear fluid contains organic and inorganic constituents, variations in their relative concentrations could provide valuable information and can be useful for the detection of several ophthalmological diseases. This report describes the application of the lab-assembled light-emitting diode (LED)-based high-performance liquid chromatography system for protein profiling of tear fluids to diagnose dry eye disease. Principal Component Analysis (PCA), match/no-match, and Artificial Neural Network (ANN) based binary classification of protein profile data were performed for disease diagnosis. Results from the match/no-match test of the protein profile data showed 94.4% sensitivity and 87.8% specificity. ANN with the leaving one out procedure has given 91.6% sensitivity and 93.9% specificity.

UR - https://www.scopus.com/pages/publications/85169290107

UR - https://www.scopus.com/inward/citedby.url?scp=85169290107&partnerID=8YFLogxK

U2 - 10.1039/d3ra04389d

DO - 10.1039/d3ra04389d

M3 - Article

AN - SCOPUS:85169290107

SN - 2046-2069

VL - 13

SP - 22559

EP - 22568

JO - RSC Advances

JF - RSC Advances

IS - 32

ER -

Protein profile analysis of tear fluid with hyphenated HPLC-UV LED-induced fluorescence detection for the diagnosis of dry eye syndrome

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this