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Characterization of Human Semen by GC-MS and VOC Sensor: An Unexplored Approach to the Study on Infertility

Authors :
Vincenzo Zara
A. Forleo
Sara Pinto Provenzano
Valentina Longo
Alessandra Ferramosca
Simonetta Capone
Lamberto Coppola
Pietro Siciliano
Daniela Domenica Montagna
Longo, Valentina
Forleo, Angiola
Pinto Provenzano, Sara
Montagna, Domenica Daniela
Coppola, Lamberto
Zara, Vincenzo
Ferramosca, Alessandra
Siciliano, Pietro
Capone, Simonetta
Source :
Lecture Notes in Electrical Engineering ISBN: 9783030043230, Sensors
Publication Year :
2019
Publisher :
Springer, Cham, 2019.

Abstract

Infertility is one of principal health and social problems of this century. Male factors are involved in half of the cases and often the alteration concerns sperm motility. Seminogram is the gold standard technique for semen analysis, but it presents several limits. For this reason, we propose a new method for discriminating asthenozoospermic samples (low sperm motility) from normozoospermic ones (progressive motility > 32%) based on the never explored analysis of the volatile metabolites in the headspace of human semen sample by Gas Chromatograph (GC) equipped with two detectors: a Mass Spectrometer (MS) and a metal oxide based gas sensor sensitive (MOX) to Volatile Organic Compounds (VOCs). VOC sensor signal profiles (resistance vs. time) showed a higher sensitivity to specific organic classes such as aldehydes and ketones. The sensorgrams were preprocessed and analysed by PLS-DA. The results showed that sensorgrams analysis by suitable bioinformatics techniques has a good discrimination power and could support physiological parameters in human semen assessment. The analysis of the human semen Volatilome may be a proof-of-concept for the development of a novel micro-GC device with a sensor array detector, a potential candidate for infertility assessment in clinical practice.

Details

Language :
English
ISBN :
978-3-030-04323-0
ISBNs :
9783030043230
Database :
OpenAIRE
Journal :
Lecture Notes in Electrical Engineering ISBN: 9783030043230, Sensors
Accession number :
edsair.doi.dedup.....695dc95eeb10146b34678fe9e135d770