AIMC Topic: Spermatogenesis
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Deep-learning-based automated prediction of mouse seminiferous tubule stage by using bright-field microscopy.
Scientific reports
Jul 1, 2025
Infertility is a global issue, and approximately 50% of cases are due to male factors, with defective spermatogenesis being the main one. For studies of spermatogenesis, evaluating the seminiferous tubule stage is essential. However, current evaluati...
The human infertility single-cell testis atlas (HISTA): an interactive molecular scRNA-Seq reference of the human testis.
Andrology
Apr 5, 2024
BACKGROUND: Single-cell RNA-seq (scRNA-Seq) has been widely adopted to study gene expression of the human testis. Several datasets of scRNA-Seq from human testis have been generated from different groups processed with different informatics pipelines...
Deep Learning-Based Spermatogenic Staging in Tissue Sections of Cynomolgus Macaque Testes.
Toxicologic pathology
Mar 11, 2024
The indirect assessment of adverse effects on fertility in cynomolgus monkeys requires that tissue sections of the testis be microscopically evaluated with awareness of the stage of spermatogenesis that a particular cross-section of a seminiferous tu...
Detection of spermatogonial stem/progenitor cells in prepubertal mouse testis with deep learning.
Journal of assisted reproduction and genetics
Mar 30, 2023
PURPOSE: Rapid and easy detection of spermatogonial stem/progenitor cells (SSPCs) is crucial for clinicians dealing with male infertility caused by prepubertal testicular damage. Deep learning (DL) methods may offer visual tools for tracking SSPCs on...
Morphologic Features and Deep Learning-Based Analysis of Canine Spermatogenic Stages.
Toxicologic pathology
Aug 24, 2022
In nonclinical toxicity studies, stage-aware evaluation is often expected to assess drug-induced testicular toxicity. Although stage-aware evaluation does not require identification of specific stages, it is important to understand microscopic featur...
Deep Learning-Based Spermatogenic Staging Assessment for Hematoxylin and Eosin-Stained Sections of Rat Testes.
Toxicologic pathology
Nov 28, 2020
In preclinical toxicology studies, a "stage-aware" histopathological evaluation of testes is recognized as the most sensitive method to detect effects on spermatogenesis. A stage-aware evaluation requires the pathologist to be able to identify the di...
Enhancer recognition and prediction during spermatogenesis based on deep convolutional neural networks.
Molecular omics
Jun 22, 2020
MOTIVATION: enhancers play an important role in the regulation of gene expression during spermatogenesis. The development of ChIP-Chip and ChIP-Seq sequencing technology has enabled researchers to focus on the relationship between enhancers and DNA s...
Multilevel approach to male fertility by machine learning highlights a hidden link between haematological and spermatogenetic cells.
Andrology
Jun 21, 2020
BACKGROUND: Male infertility represents a complex clinical condition requiring an accurate multilevel assessment, in which machine learning technology, combining large data series in non-linear and highly interactive ways, could be innovatively appli...
PrESOgenesis: A two-layer multi-label predictor for identifying fertility-related proteins using support vector machine and pseudo amino acid composition approach.
Scientific reports
Jun 13, 2018
Successful spermatogenesis and oogenesis are the two genetically independent processes preceding embryo development. To date, several fertility-related proteins have been described in mammalian species. Nevertheless, further studies are required to d...
Integrative network and computational toxicology reveal the molecular mechanisms in PFOA-induced spermatogenic disorder.
Journal of environmental management
Jun 1, 2025
Perfluorooctanoic acid (PFOA), a widely used industrial chemical, poses significant environmental and biological toxicity, particularly affecting reproductive health. This study aimed to integrate network toxicology, machine learning, and molecular d...
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