Innovative Approach for Human Semen Quality Assessment Based on Volatilomics.
Simonetta CaponeAngiola ForleoAntonio Vincenzo RadognaValentina LongoGiulia MyAlessandra GengaAlessandra FerramoscaGiuseppe GrassiFlavio CasinoPietro Aleardo SicilianoTiziana NotariSebastiana PappalardoMarina PiscopoLuigi MontanoPublished in: Toxics (2024)
The volatilome profile of some biofluids (blood, urine, and human semen) identified by Solid-Phase Microextraction-Gas Chromatography/Mass Spectrometry (SPME-GC/MS) and collected from young men living in two high-pollution areas in Italy, i.e., Land of Fires and Valley of Sacco River, have been coupled to sperm parameters obtained by spermiogram analysis to build general multiple regression models. Panels of volatile organic compounds (VOCs) have been selected to optimize the models and used as predictive variables to estimate the different sperm quality parameters (sperm cell concentration, total and progressive motility/immotile cells, total/head/neck/tail morphology anomalies, semen round cell concentration). The results of the multiple linear regression models based on the different subgroups of data joining VOCs from one/two or three biofluids have been compared. Surprisingly, the models based on blood and urine VOCs have allowed an excellent estimate of spermiogram values, paving the way towards a new method of indirect evaluation of semen quality and preventive screening. The significance of VOCs in terms of toxicity and dangerousness was discussed with the support of chemical databases available online.
Keyphrases
- gas chromatography mass spectrometry
- endothelial cells
- single cell
- cell therapy
- induced apoptosis
- multiple sclerosis
- pluripotent stem cells
- heavy metals
- induced pluripotent stem cells
- risk assessment
- climate change
- oxidative stress
- middle aged
- big data
- dna repair
- quality improvement
- cell cycle arrest
- health information
- cystic fibrosis
- staphylococcus aureus
- mass spectrometry
- optic nerve
- biofilm formation
- high resolution
- data analysis
- neural network