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Updated: Jul 13, 2026

Immunostaining of Whole-Mount Drosophila Testes for 3D Confocal Analysis of Large Spermatocytes

Immunostaining of Whole-Mount Drosophila Testes for 3D Confocal Analysis of Large Spermatocytes

Published on: August 27, 2020

3D+t Multifocal Imaging Dataset of Human Sperm.

Fernando Montoya¹, Andrés Bribiesca-Sánchez^1,2, Paul Hernández-Herrera³

¹Laboratorio de Imágenes y Visión por Computadora, Departamento de Ingeniería Celular y Biocatálisis, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México.

Scientific Data

|May 18, 2025

Summary

This study introduces a new 3D+t dataset of human sperm movement, enabling advanced analysis of flagellar dynamics crucial for understanding fertility. The data aids in developing new diagnostic tools for male fertility assessment.

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Author Spotlight: A Live Cell Imaging Technique to Study Calcium Signaling and Acrosome Exocytosis in Mouse Sperm

Author Spotlight: A Live Cell Imaging Technique to Study Calcium Signaling and Acrosome Exocytosis in Mouse Sperm

Published on: October 13, 2023

Area of Science:

Reproductive Biology
Biophysics
Data Science

Background:

Traditional human fertility assessments often rely on 2D sperm motility or static morphology, limiting dynamic analysis.
Understanding dynamic 3D sperm movement is essential for accurate fertility evaluation.

Purpose of the Study:

To introduce the 3D+t Multifocal Imaging Dataset of Human Sperm (3D-SpermVid).
To provide a comprehensive dataset for analyzing 3D sperm flagellar motility over time.
To facilitate advancements in male fertility diagnostics and understanding sperm behavior.

Main Methods:

Utilized multifocal imaging (MFI) with a piezoelectric focus adjustment system.
Recorded 121 video-microscopy hyperstacks of human sperm under capacitating and non-capacitating conditions.
Captured sperm movement in a volumetric space to enable 3D+t analysis.

Main Results:

Established a novel dataset (3D-SpermVid) of human sperm dynamics.
Enabled detailed observation of 3D sperm flagellar motility patterns.
Provided data for deep learning applications to uncover hidden motility patterns.

Conclusions:

The 3D-SpermVid dataset offers significant potential for advancing male fertility research.
Facilitates the development of novel diagnostic tools for assessing sperm function.
Supports deeper understanding of sperm capacitation and navigation mechanisms.