Biology subjects

Karouia, F.

Publications and source records attributed to Karouia, F..

4 recordsLinked to original sources

bioRxiv2026

A systematic imputation framework for sparse, multimodal space biology datasets: application to retinal imaging and omics from the RR9 mission

Missing data is a fundamental challenge in space biology, where high experimental costs, limited sample availability, and tissue allocation constraints produce datasets that are sparse, multimodal, and heterogeneous. We present a systematic four-stage framework for diagnosing, implementing, and validating data imputation strategies tailored to these characteristics, and demonstrate its application to retinal imaging and omics data from the NASA Rodent Research 9 (RR9) mission. Using logistic regression-based missingness diagnosis, we identify a Missing At Random (MAR) mechanism driven by experimental design constraints across nine assay modalities. We implement and optimize three imputation strategies: K-Nearest Neighbors (KNN), Multiple Imputation by Chained Equations with weak ElasticNet regularization (MICE-Elastic), and a per-column hybrid strategy, evaluated against a random sample imputer baseline. Validation across seven complementary metrics including supervised classification, unsupervised clustering, correlation structure preservation, masked value recovery, cross-dataset generalization, and permutation testing reveals that MICE-Elastic and the Hybrid strategy preserve genuine biological signal in both RNA-seq and TUNEL modalities, while KNN and the random sample imputer do not despite achieving comparable cross-validation accuracy. A critical finding is that imputation substantially improves supervised classification performance while consistently degrading unsupervised clustering structure, a trade-off researchers must understand before applying these methods. This framework provides practical, actionable guidance for space biologists and data scientists managing sparse multimodal datasets, and represents a foundational step toward digital twin development for space medicine.

bioinformatics↗

bioRxiv2026

Cross-Species Adaptation of RETFound for Rodent OCT Age Estimation Reveals Strong CNN Baselines in Data-Scarce Space Biology

Space-biology imaging studies are often constrained by severe data scarcity, limiting the development of robust machine-learning biomarkers. Rodent spaceflight and space-analog datasets provide an important preclinical setting for testing transfer-learning strategies, but the extent to which human retinal foundation models can generalize to rodent optical coherence tomography (OCT) remains unclear. Here, we benchmark cross-species adaptation of RETFound, a human retinal Vision Transformer pretrained on 1.6 million retinal images, for chronological age prediction from Brown Norway rat OCT B-scans in the NASA Open Science Data Repository dataset OSD-679. We adapted RETFound using Low-Rank Adaptation (LoRA) and evaluated performance on control animals under matched 3-fold rat-level cross-validation. We compared RETFound+LoRA with a strong ImageNet-pretrained Xception baseline under matched protocols and included a scratch/random ViT as a supplementary negative-control architecture check. Metrics included mean absolute error (MAE), R2, and inter-eye mean absolute difference (MAD). RETFound+LoRA achieved MAE = 26.20 {+/-} 5.03 days with R2 = 0.744 {+/-} 0.049. However, Xception performed better in the primary benchmark (MAE = 19.01 {+/-} 7.67 days, R2 = 0.853 {+/-} 0.082), and the matched-fold comparison favored Xception, although this result should be interpreted cautiously given the small number of folds. Inter-eye consistency was maintained across the matched control evaluation, and saliency maps localized model attention to anatomically plausible inner retinal regions. Together, these results show that human retinal foundation models can transfer to rodent OCT in a scientifically useful way, but also that strong CNN baselines may outperform transformer-based models in small-sample cross-species settings. This preprint provides a reproducible benchmark and baseline framework for future retinal biomarker development in space biology. Significance StatementSpace-biology imaging studies are intrinsically data-limited. This preprint provides a reproducible cross-species benchmark for adapting Earth-trained retinal models to rodent OCT under small-sample conditions, highlights the value of strong CNN baselines, and offers a reusable starting point for future retinal biomarker development in space-relevant datasets.

bioinformatics↗

bioRxiv2025

Microgravity Remodels Longevity Networks in Astronaut PBMCs: Integrated Findings of Telomere Elongation, DNA Repair Responses, and miRNA Suppression

Microgravity provides a unique environment for elucidating the fundamental mechanisms of human aging. In the Microgravity Associated Genetics (MESSAGE) Science Mission--Turkiyes first human space biology experiment--we performed an integrative analysis of telomere dynamics, transcriptomic remodeling, and microRNA regulation in peripheral blood mononuclear cells (PBMCs) collected before launch (L-7day), after suborbital ascent (L+3hrs), and during days 4-10 aboard the International Space Station (ISS). Spaceflight induced a striking early elongation of telomeres, accompanied by transcriptional activation of DNA repair, oxidative stress mitigation, mitochondrial homeostasis, and immune regulatory pathways. Concurrently, microgravity triggered robust suppression of longevity-associated microRNAs, including members of the miR-17-92, miR29, and miR34 families, suggesting coordinated epigenetic reprogramming of genome stability and stress responses. Notably, the adaptor protein gene AP2A1, recently implicated in cellular rejuvenation and mechanotransductive aging processes, emerged as a consistently microgravity-responsive hub, linking cytoskeletal signaling to telomere maintenance and DNA repair networks. Together, these findings reveal that short-duration spaceflight initiates a multi-layered molecular longevity program in human immune cells, characterized by telomere extension, stabilization of genome maintenance pathways, and suppression of aging-associated miRNA regulators. This systems-level view provides foundational insight into how human biology adapts to short-term microgravity exposure and identifies AP2A1-centered networks as promising targets for enhancing astronaut health and performance and ultimately understanding terrestrial aging.

molecular biology↗

bioRxiv2024

Spaceflight alters host-gut microbiota interactions

The rodent habitat on the International Space Station has provided crucial insights into the impact of spaceflight on mammals, including observation of symptoms characteristic of liver disease, insulin resistance, osteopenia and myopathy. Although these physiological responses can involve the microbiome when observed on Earth, changes in host-microbiota interactions during spaceflight are still being elucidated. Here, NASA GeneLab multiomic data from the Rodent Research 6 mission are used to determine changes to gut microbiota and murine host colon and liver gene expression after 29 and 56-days of spaceflight. Using hybrid amplicon and whole metagenome sequencing analysis, significant spaceflight-associated alterations to 42 microbiome species were identified. These included relative reductions of bacteria associated with bile acid and butyrate metabolism, such as Extibacter muris and Dysosmobacter welbionis. Functional prediction suggested over-representation of fatty acid and bile acid metabolism, extracellular matrix interactions, and antibiotic resistance genes within the gut microbiome, while host intestinal and hepatic gene expression described corresponding changes to host bile acid and energy metabolism, and immune suppression from spaceflight. Taken together, these changes imply that interactions at the host-gut microbiome interface contribute to spaceflight pathology and highlight how these interactions might critically influence human health and the feasibility of long-duration spaceflight.

genomics↗