Journal of Human Reproductive Science
Home Ahead of Print Current Issue Archives
   Bookmark this page Print this page Email this page Small font sizeDefault font size Increase font size    Users online: 164

ORIGINAL ARTICLE Table of Contents   
Year : 2021  |  Volume : 14  |  Issue : 2  |  Page : 129-136
Assessment and establishment of correlation between reactive oxidation species, citric acid, and fructose level in infertile male individuals: A machine-learning approach

1 Department of Studies in Zoology, University of Mysore, Mysore, Karnataka, India
2 Department of Genetics and Genomics, University of Mysore, Mysore, Karnataka, India

Correspondence Address:
Prof. Suttur S Malini
Department of Studies in Zoology, University of Mysore, Mysore - 570 006, Karnataka
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jhrs.jhrs_26_21

Rights and Permissions

Background: Biochemical complexity of seminal plasma and obesity has an important role in male infertility (MI); so far, it has not been possible to provide evidence of clinical significance for all of them. Aims: Our goal here is to evaluate the correlation between biochemical markers with semen parameters, which might play a role in MI. Study Setting and Design: We enlisted 100 infertile men as patients and 50 fertile men as controls to evaluate the sperm parameters and biochemical markers in ascertaining MI. Materials and Methods: Semen analyses, seminal fructose, citric acid, and reactive oxidation species (ROS) were measured in 100 patients and 50 controls. Statistical Analysis: Descriptive statistics, an independent t-test, Pearson correlation, and machine-learning approaches were used to integrate the various biochemical and seminal parameters measured to quantify the inter-relatedness between these measurements. Results: Pearson correlation results showed a significant positive correlation between body mass index (BMI) and fructose levels. Citric acid had a positive correlation with sperm count, morphology, motility, and volume but displayed a negative correlation with BMI and basal metabolic rate (BMR). However, BMI and BMR had a positive correlation with ROS. Sperm count, morphology, and motility were negative correlations with ROS. The machine-learning approach detected that pH was the most critical parameter with an inverse effect on citric acid, and BMI and motility were the most critical parameter for ROS. Conclusion: We recommend that evaluation of biochemical markers of seminal fluid may benefit in understanding the etiology of MI based on the functionality of accessory glands and ROS levels.

Print this article  Email this article

  Similar in PUBMED
    Search Pubmed for
    Search in Google Scholar for
  Related articles
   Citation Manager
  Access Statistics
   Reader Comments
   Email Alert *
   Add to My List *
 * Requires registration (Free)

 Article Access Statistics
    PDF Downloaded171    
    Comments [Add]    
    Cited by others 4    

Recommend this journal