Biomolecular condensates as dynamic regulators of musculoskeletal homeostasis, disease, and therapeutic challenges

Engineering notes

Key topics: autonomous driving. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Abstract Biomolecular condensates are membraneless assemblies that concentrate proteins, nucleic acids, and other biomolecules into dynamic cellular compartments. Liquid-liquid phase separation (LLPS) is one important route by which such condensates form, particularly when multivalent interactions generate liquid-like, reversible assemblies. However, not every condensate or disease-associated assembly should be explained solely by LLPS. In the musculoskeletal system, condensates have been linked to transcription, signal transduction, RNA metabolism, stress responses, tissue development, homeostasis, and mechanoadaptation. Genetic mutations, altered post-translational modifications, and environmental stress can disturb these assemblies, but the evidence does not always establish whether condensates are causal drivers of disease or downstream responses to injury. This review examines how biomolecular condensates and LLPS-related mechanisms have been implicated in osteoporosis, osteoarthritis, skeletal muscle atrophy, bone and soft tissue sarcomas, and neuromusculoskeletal diseases. We focus on the strength of the available evidence, distinguish correlative observations from causal mechanisms where possible, and discuss how condensates may connect non-coding genetic variants, mechanical cues, metabolic signals, and disease phenotypes. We also assess the translational potential and limitations of condensate-based biomarkers, therapies that target pathological condensates, and phase-separation-inspired delivery systems. A central message is that biomolecular condensates offer a useful framework for musculoskeletal biology, but clinical translation will require disease-specific targets, human-relevant models, selective delivery, and rigorous tests of causality.

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