SalivaPrint as a non-invasive diagnostic tool

Eduardo Esteves; Igor Cruz; Ana Cristina Esteves; Marlene Barros; Nuno Rosa

doi:10.5220/0009163506770682

SalivaPrint as a non-invasive diagnostic tool

Eduardo Esteves^*, Igor Cruz, Ana Cristina Esteves, Marlene Barros, Nuno Rosa

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

18 Downloads

Abstract

Currently, the molecular diagnosis is based on the quantification of RNA, proteins and metabolites because they present changes in their quantity related to clinical situations. The same molecules are not generally suitable for early diagnosis or to follow clinical evolution, making necessary strategies to evaluate the complete molecular scenario. There are already experimental strategies that allow the determination of total protein profiles from saliva samples (the SalivaPrint). The goal of this work is to identify a profile of saliva proteins (similar to a fingerprint) and, using computational methods, identify how this profiles changes with age and gender. So far it has been possible to collect 79 samples as well as the metadata associated with each sample using an electronic questionnaire developed by us. A total protein profile was obtained and their association with gender was verified using statistical methods. Currently we are developing the Python scripts for automatic data acquiring and normalization. Total protein profiles annotation on a database (SalivaPrintDB) and their integration with the factors that affects them using machine learning strategies can empower the use of the approach proposed on this work as a tool for monitoring the individual's health status.

Original language	English
Title of host publication	HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
Editors	Federico Cabitza, Ana Fred, Hugo Gamboa
Publisher	SciTePress
Pages	677-682
Number of pages	6
ISBN (Electronic)	9789897583988
ISBN (Print)	9789897583988
DOIs	https://doi.org/10.5220/0009163506770682
Publication status	Published - 1 Jan 2020
Event	13th International Conference on Health Informatics, HEALTHINF 2020 - Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020 - Valletta, Malta Duration: 24 Feb 2020 → 26 Feb 2020

Publication series

Name	HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020

Conference

Conference	13th International Conference on Health Informatics, HEALTHINF 2020 - Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
Country/Territory	Malta
City	Valletta
Period	24/02/20 → 26/02/20

Keywords

Health diagnostic
Machine learning strategies
Saliva diagnostic
Saliva protein profile

Access to Document

10.5220/0009163506770682Licence: CC BY-NC-ND

19557788Final published version, 1.36 MBLicence: CC BY-NC-ND

http://hdl.handle.net/10400.14/32301Licence: CC BY-NC-ND

Cite this

Esteves, E., Cruz, I., Esteves, A. C., Barros, M., & Rosa, N. (2020). SalivaPrint as a non-invasive diagnostic tool. In F. Cabitza, A. Fred, & H. Gamboa (Eds.), HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020 (pp. 677-682). (HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020). SciTePress. https://doi.org/10.5220/0009163506770682

Esteves, Eduardo ; Cruz, Igor ; Esteves, Ana Cristina et al. / SalivaPrint as a non-invasive diagnostic tool. HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020. editor / Federico Cabitza ; Ana Fred ; Hugo Gamboa. SciTePress, 2020. pp. 677-682 (HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020).

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title = "SalivaPrint as a non-invasive diagnostic tool",

abstract = "Currently, the molecular diagnosis is based on the quantification of RNA, proteins and metabolites because they present changes in their quantity related to clinical situations. The same molecules are not generally suitable for early diagnosis or to follow clinical evolution, making necessary strategies to evaluate the complete molecular scenario. There are already experimental strategies that allow the determination of total protein profiles from saliva samples (the SalivaPrint). The goal of this work is to identify a profile of saliva proteins (similar to a fingerprint) and, using computational methods, identify how this profiles changes with age and gender. So far it has been possible to collect 79 samples as well as the metadata associated with each sample using an electronic questionnaire developed by us. A total protein profile was obtained and their association with gender was verified using statistical methods. Currently we are developing the Python scripts for automatic data acquiring and normalization. Total protein profiles annotation on a database (SalivaPrintDB) and their integration with the factors that affects them using machine learning strategies can empower the use of the approach proposed on this work as a tool for monitoring the individual's health status.",

keywords = "Health diagnostic, Machine learning strategies, Saliva diagnostic, Saliva protein profile",

author = "Eduardo Esteves and Igor Cruz and Esteves, {Ana Cristina} and Marlene Barros and Nuno Rosa",

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doi = "10.5220/0009163506770682",

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editor = "Federico Cabitza and Ana Fred and Hugo Gamboa",

booktitle = "HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020",

note = "13th International Conference on Health Informatics, HEALTHINF 2020 - Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020 ; Conference date: 24-02-2020 Through 26-02-2020",

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Esteves, E, Cruz, I, Esteves, AC, Barros, M & Rosa, N 2020, SalivaPrint as a non-invasive diagnostic tool. in F Cabitza, A Fred & H Gamboa (eds), HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020. HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020, SciTePress, pp. 677-682, 13th International Conference on Health Informatics, HEALTHINF 2020 - Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020, Valletta, Malta, 24/02/20. https://doi.org/10.5220/0009163506770682

SalivaPrint as a non-invasive diagnostic tool. / Esteves, Eduardo; Cruz, Igor; Esteves, Ana Cristina et al.
HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020. ed. / Federico Cabitza; Ana Fred; Hugo Gamboa. SciTePress, 2020. p. 677-682 (HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - SalivaPrint as a non-invasive diagnostic tool

AU - Esteves, Eduardo

AU - Cruz, Igor

AU - Esteves, Ana Cristina

AU - Barros, Marlene

AU - Rosa, Nuno

PY - 2020/1/1

Y1 - 2020/1/1

N2 - Currently, the molecular diagnosis is based on the quantification of RNA, proteins and metabolites because they present changes in their quantity related to clinical situations. The same molecules are not generally suitable for early diagnosis or to follow clinical evolution, making necessary strategies to evaluate the complete molecular scenario. There are already experimental strategies that allow the determination of total protein profiles from saliva samples (the SalivaPrint). The goal of this work is to identify a profile of saliva proteins (similar to a fingerprint) and, using computational methods, identify how this profiles changes with age and gender. So far it has been possible to collect 79 samples as well as the metadata associated with each sample using an electronic questionnaire developed by us. A total protein profile was obtained and their association with gender was verified using statistical methods. Currently we are developing the Python scripts for automatic data acquiring and normalization. Total protein profiles annotation on a database (SalivaPrintDB) and their integration with the factors that affects them using machine learning strategies can empower the use of the approach proposed on this work as a tool for monitoring the individual's health status.

AB - Currently, the molecular diagnosis is based on the quantification of RNA, proteins and metabolites because they present changes in their quantity related to clinical situations. The same molecules are not generally suitable for early diagnosis or to follow clinical evolution, making necessary strategies to evaluate the complete molecular scenario. There are already experimental strategies that allow the determination of total protein profiles from saliva samples (the SalivaPrint). The goal of this work is to identify a profile of saliva proteins (similar to a fingerprint) and, using computational methods, identify how this profiles changes with age and gender. So far it has been possible to collect 79 samples as well as the metadata associated with each sample using an electronic questionnaire developed by us. A total protein profile was obtained and their association with gender was verified using statistical methods. Currently we are developing the Python scripts for automatic data acquiring and normalization. Total protein profiles annotation on a database (SalivaPrintDB) and their integration with the factors that affects them using machine learning strategies can empower the use of the approach proposed on this work as a tool for monitoring the individual's health status.

KW - Health diagnostic

KW - Machine learning strategies

KW - Saliva diagnostic

KW - Saliva protein profile

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DO - 10.5220/0009163506770682

M3 - Conference contribution

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SN - 9789897583988

T3 - HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020

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BT - HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020

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A2 - Gamboa, Hugo

PB - SciTePress

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Y2 - 24 February 2020 through 26 February 2020

ER -

Esteves E, Cruz I, Esteves AC, Barros M , Rosa N. SalivaPrint as a non-invasive diagnostic tool. In Cabitza F, Fred A, Gamboa H, editors, HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020. SciTePress. 2020. p. 677-682. (HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020). doi: 10.5220/0009163506770682

SalivaPrint as a non-invasive diagnostic tool

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

CIIS: Center for Interdisciplinary Research in Health

Cite this

SalivaPrint as a non-invasive diagnostic tool

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

CIIS: Center for Interdisciplinary Research in Health

Cite this