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Deep Cross-Organism Generalization of the Physiological Effects of Spaceflight from Mammalian Model Organisms to Humans Cover

Deep Cross-Organism Generalization of the Physiological Effects of Spaceflight from Mammalian Model Organisms to Humans

Gravitational and Space Research
Volume 13 (2025): Issue 1 (January 2025)
By: Konstantinos I. Adamopoulos,  Lauren M. Sanders,  Adrienne Hoarfrost and  Sylvain V. Costes  
Open Access
|Jul 2025

Figures & Tables

Figure 1.

Overall study workflow.
Overall study workflow.

Figure 2.

Heatmap of significantly dysregulated genes in Mus musculus. Genes that are shaded in dark green indicate high up-regulation with a logFC value above 1.5, while genes shaded in light green indicate up-regulation with a logFC value above 1. Genes with a logFC value between −1 and 1 are non-significantly dysregulated. Conversely, genes shaded in dark red represent highly down-regulated genes with a logFC below −1.5. The analyses and results depicted in the Heatmap were conducted with consideration only for the Top 50 differentially expressed genes per study or dataset.
Heatmap of significantly dysregulated genes in Mus musculus. Genes that are shaded in dark green indicate high up-regulation with a logFC value above 1.5, while genes shaded in light green indicate up-regulation with a logFC value above 1. Genes with a logFC value between −1 and 1 are non-significantly dysregulated. Conversely, genes shaded in dark red represent highly down-regulated genes with a logFC below −1.5. The analyses and results depicted in the Heatmap were conducted with consideration only for the Top 50 differentially expressed genes per study or dataset.

Figure 3.

Enriched terms and pathways of dysregulated genes in Mus musculus. Panel a presents the enriched terms of upregulated genes, while panels b and c display the enriched terms of downregulated genes. Corresponding enriched Gene Ontology terms and KEGG pathways are depicted on the right side of each panel, with associated genes shown at the bottom. The dark green color indicates the correlations between genes and enriched terms or pathways.
Enriched terms and pathways of dysregulated genes in Mus musculus. Panel a presents the enriched terms of upregulated genes, while panels b and c display the enriched terms of downregulated genes. Corresponding enriched Gene Ontology terms and KEGG pathways are depicted on the right side of each panel, with associated genes shown at the bottom. The dark green color indicates the correlations between genes and enriched terms or pathways.

Figure 4.

Heatmap of significantly dysregulated genes in Homo sapiens. Genes that are shaded in dark green indicate high up-regulation with a logFC value above 1.5, while genes shaded in light green indicate up-regulation with a logFC value above 1. Genes with a logFC value between −1 and 1 are considered to be non-significantly dysregulated. Conversely, genes shaded in dark red represent highly down-regulated genes with a logFC below −1.5. The analyses and results depicted in the Heatmap were conducted with consideration only for the Top 50 differentially expressed genes per study or dataset.
Heatmap of significantly dysregulated genes in Homo sapiens. Genes that are shaded in dark green indicate high up-regulation with a logFC value above 1.5, while genes shaded in light green indicate up-regulation with a logFC value above 1. Genes with a logFC value between −1 and 1 are considered to be non-significantly dysregulated. Conversely, genes shaded in dark red represent highly down-regulated genes with a logFC below −1.5. The analyses and results depicted in the Heatmap were conducted with consideration only for the Top 50 differentially expressed genes per study or dataset.

Figure 5.

Enriched terms and pathways of dysregulated genes in Homo sapiens. Panel a presents the enriched terms of upregulated genes, while panel b displays the enriched terms of downregulated genes. Corresponding enriched Gene Ontology terms and KEGG pathways are depicted on the right side of each panel, with associated genes shown at the bottom. The dark green color indicates the correlations between genes and enriched terms or pathways.
Enriched terms and pathways of dysregulated genes in Homo sapiens. Panel a presents the enriched terms of upregulated genes, while panel b displays the enriched terms of downregulated genes. Corresponding enriched Gene Ontology terms and KEGG pathways are depicted on the right side of each panel, with associated genes shown at the bottom. The dark green color indicates the correlations between genes and enriched terms or pathways.

Figure 6.

Confusion Matrices of Mus musculus’ classifiers. a) Logistic Regression, b) Decision Tree, c) Neural Network, d) Gaussian Naive Bayes, e) Random Forest, f) SVM Support Vector Machine, SVC (kernel = linear). The y-axis corresponds to the true expression level, while the x-axis corresponds to the predicted expression level. Class 0 represents down-regulated genes, and class 1 represents up-regulated genes.
Confusion Matrices of Mus musculus’ classifiers. a) Logistic Regression, b) Decision Tree, c) Neural Network, d) Gaussian Naive Bayes, e) Random Forest, f) SVM Support Vector Machine, SVC (kernel = linear). The y-axis corresponds to the true expression level, while the x-axis corresponds to the predicted expression level. Class 0 represents down-regulated genes, and class 1 represents up-regulated genes.

Figure 7.

Confusion Matrices of Homo sapiens’ classifiers. a) Logistic Regression, b) Decision Tree, c) Neural Network, d) Gaussian Naive Bayes, e) Random Forest, f) SVM Support Vector Machine, SVC (kernel = linear). The y-axis corresponds to the true expression level, while the x-axis corresponds to the predicted expression level. Class 0 represents down-regulated genes, and class 1 represents up-regulated genes.
Confusion Matrices of Homo sapiens’ classifiers. a) Logistic Regression, b) Decision Tree, c) Neural Network, d) Gaussian Naive Bayes, e) Random Forest, f) SVM Support Vector Machine, SVC (kernel = linear). The y-axis corresponds to the true expression level, while the x-axis corresponds to the predicted expression level. Class 0 represents down-regulated genes, and class 1 represents up-regulated genes.

Figure 8.

Classification reports of a) Mus musculus’ and b) Homo sapiens’ classifiers, c) Classification Report of Transfer Learning application. The classification report for our Transfer Learning model reveals an enhanced accuracy of 71% compared to the NN classifier on the Homo sapiens dataset. The performances of these classifiers were evaluated and compared based on accuracy, recall, and precision metrics.
Classification reports of a) Mus musculus’ and b) Homo sapiens’ classifiers, c) Classification Report of Transfer Learning application. The classification report for our Transfer Learning model reveals an enhanced accuracy of 71% compared to the NN classifier on the Homo sapiens dataset. The performances of these classifiers were evaluated and compared based on accuracy, recall, and precision metrics.

Figure 9.

Confusion Matrices of KNN multi-classifiers and Transfer Learning application. a) KNN multi-classifier on human dataset, b) KNN multi-classifier on mouse dataset, class 0 represents down-regulated genes, class 1 represents non-significantly dysregulated genes, and class 2 represents up-regulated genes. c) Confusion matrix of Transfer Learning application, class 0 represents down-regulated genes, and class 1 represents up-regulated genes. The y-axis corresponds to the true expression level, while the x-axis corresponds to the predicted expression level.
Confusion Matrices of KNN multi-classifiers and Transfer Learning application. a) KNN multi-classifier on human dataset, b) KNN multi-classifier on mouse dataset, class 0 represents down-regulated genes, class 1 represents non-significantly dysregulated genes, and class 2 represents up-regulated genes. c) Confusion matrix of Transfer Learning application, class 0 represents down-regulated genes, and class 1 represents up-regulated genes. The y-axis corresponds to the true expression level, while the x-axis corresponds to the predicted expression level.
DOI: https://doi.org/10.2478/gsr-2025-0003 | Journal eISSN: 2332-7774
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Language: English
Page range: 39 - 50
Published on: Jul 2, 2025
Published by: American Society for Gravitational and Space Research
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
NASA GeneLab,
Spaceflight,
Microgravity,
Space Biology,
Microarrays,
Differential Gene Expression,
Machine Learning,
Classification,
Musculoskeletal System
Related subjects:
Life sciences,
Life sciences, other,
Materials sciences,
Materials sciences, other,
Physics,
Physics, other

© 2025 Konstantinos I. Adamopoulos, Lauren M. Sanders, Adrienne Hoarfrost, Sylvain V. Costes, published by American Society for Gravitational and Space Research
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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