Long-term spaceflight induces multisystem stress, including cardiovascular deconditioning, skeletal muscle atrophy, immune suppression, and neuro-ocular syndromes. Current countermeasures reduce symptoms but cannot replicate the synergistic resilience needed for extended missions or critical illness. Hibernating animals, specifically brown bears (Ursus arctos), survive prolonged immobility, starvation, and bradycardia without resultant pathology. This review incorporates adaptations observed in bears and certain torpid species, including reversible insulin resistance, suppression of muscle atrophy genes MuRF1 and Atrogin-1, and maintenance of the heart despite seasonal production decline. The thirteen-lined ground squirrels (Ictidomys tridecemlineatus) maintain retinal structure and synaptic stability throughout torpor, avoiding neuro-ocular complications despite prolonged inactivity. Mechanisms span from RBM3-dependent synaptic maintenance, titin isoform remodeling under the control of RBM20, mTOR and FOXO pathway regulation, remodeled hydrogen sulfide metabolism, and microbiome-mediated nitrogen salvage. These adaptations are different from human adaptation to microgravity and disuse and offer translational candidates for synthetic torpor, probiotic engineering, neuroprotection, and protein-sparing therapy. Hibernators are not passive stress subjects; they perform coordinated anticipatory responses in multiple organs. Comparing these systems in large and small hibernators, we aim to uncover a biologically realistic path to human resilience. These findings guide a shift from reactive, pharmacological measures for preserving human health during space flight, intensive care, and extreme environments towards proactive, biologically initiated measures.

Ocular trauma represents a threat to crew safety and mission performance in space. Microgravity, confined environments, and exposure to particulate matter, chemicals, and mechanical hazards place astronauts at risk for corneal abrasions, open-globe injuries, chemical burns, lens dislocation, retinal detachment, orbital fractures, and barotrauma. Diagnostic capabilities during spaceflight remain limited by resources, lack of specialist expertise, and communication delays with Earth. Artificial intelligence, particularly convolutional neural networks and multimodal models, may help address these gaps through image interpretation, risk stratification, and longitudinal monitoring. Convolutional neural networks can extract hierarchical features from imaging data to identify subtle structural abnormalities, while multimodal models integrate imaging with clinical and environmental parameters to generate more comprehensive assessments. Terrestrial ophthalmology studies demonstrate the potential of these approaches across optical coherence tomography, ultrasound, fundus photography, and anterior-segment imaging. This review examines how these capabilities can be matched to ocular injuries during spaceflight, compares the suitability of different approaches across injury types, and identifies pathways toward autonomous care. Particular emphasis is given to spaceflight-related imaging and physiologic changes, constrained onboard hardware, and integration into workflows that support non-expert crew members. Collectively, these applications may expand diagnostic capabilities and enable earlier, more informed management during long-duration missions.