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Shed tears for diagnostics

Prashar, Anjali.

Shed tears for diagnostics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Shed tears for diagnosticsby Anjali Prashar.
Author:	Prashar, Anjali.
Published:	Singapore :Springer Singapore :2019.
Description:	xxi, 166 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Tears.
Online resource:	https://doi.org/10.1007/978-981-13-7169-1
ISBN:	9789811371691$q(electronic bk.)

Shed tears for diagnostics
Prashar, Anjali.

Shed tears for diagnostics[electronic resource] /by Anjali Prashar. - Singapore :Springer Singapore :2019. - xxi, 166 p. :ill., digital ;24 cm.

Chapter 1. Introduction -- Chapter 2. Collection methods -- Chapter 3. Composition of tears -- Chapter 4. Tear profile of contact lens users -- Chapter 5. Cry baby: Tear profile of infants -- Chapter 6. Tear off the disease -- Chapter 7. Factors affecting tear health -- Chapter 8. Artificial tears -- Chapter 9. Proposed diagnostic comprehensive tear panels -- Chapter 10. Microfluidics in tear analysis -- Chapter 11. News bulletins -- Chapter 12. Bibliograpy.

This book covers a wide range of topics concerning human tear based science, starting from basics such as the normal composition of tears and moving up to novel disease detection platforms. The entire approach is pioneering, as tears are beginning to be recognized as the most invaluable non-invasive tool in diagnostics. Interestingly, the concept is not restricted to ocular diseases: In recent years, tear diagnostics is increasingly being tapped even for cancer detection. Hopefully, non-invasive tear diagnostics will eventually replace today's invasive disease detection and monitoring techniques. Previous literature on tear diagnostics has been restricted to scientific journal articles, most of which dealt with a single tear constituent, such as a protein. This book offers a far more comprehensive and handy 'reference guide,' presenting both basic and advanced information and data. Accordingly, it will be useful for researchers in academia and the pharmaceutical industry, as well as healthcare professionals and diagnostic kit developers.

ISBN: 9789811371691$q(electronic bk.)

Standard No.: 10.1007/978-981-13-7169-1doiSubjects--Topical Terms:

847863
Tears.

LC Class. No.: QP231 / .P73 2019

Dewey Class. No.: 612.847

Shed tears for diagnostics
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245 1 0 $a Shed tears for diagnostics $h [electronic resource] / $c by Anjali Prashar.
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300 $a xxi, 166 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1. Introduction -- Chapter 2. Collection methods -- Chapter 3. Composition of tears -- Chapter 4. Tear profile of contact lens users -- Chapter 5. Cry baby: Tear profile of infants -- Chapter 6. Tear off the disease -- Chapter 7. Factors affecting tear health -- Chapter 8. Artificial tears -- Chapter 9. Proposed diagnostic comprehensive tear panels -- Chapter 10. Microfluidics in tear analysis -- Chapter 11. News bulletins -- Chapter 12. Bibliograpy.
520 $a This book covers a wide range of topics concerning human tear based science, starting from basics such as the normal composition of tears and moving up to novel disease detection platforms. The entire approach is pioneering, as tears are beginning to be recognized as the most invaluable non-invasive tool in diagnostics. Interestingly, the concept is not restricted to ocular diseases: In recent years, tear diagnostics is increasingly being tapped even for cancer detection. Hopefully, non-invasive tear diagnostics will eventually replace today's invasive disease detection and monitoring techniques. Previous literature on tear diagnostics has been restricted to scientific journal articles, most of which dealt with a single tear constituent, such as a protein. This book offers a far more comprehensive and handy 'reference guide,' presenting both basic and advanced information and data. Accordingly, it will be useful for researchers in academia and the pharmaceutical industry, as well as healthcare professionals and diagnostic kit developers.
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650 2 4 $a Ophthalmology. $3 274149
650 2 4 $a Diabetes. $3 274215
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856 4 0 $u https://doi.org/10.1007/978-981-13-7169-1
950 $a Biomedical and Life Sciences (Springer-11642)