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<p>Microgravity profoundly influences cellular morphology and function, yet ground-based simulation requires systems capable of randomizing the gravity vector. A dual-axis rotating machine (RM), such as a clinostat and random positioning machine (RPM), achieves quasi-isotropic gravitational averaging, but its quantitative optimization remains unclear. Here, a computational–experimental framework was established to evaluate dynamic isotropy of a dual-axis RM. Gravity vector trajectories were simulated across rotation ratios, and five metrics—Spherical Coverage (C), Cumulative Bias (H), Normalized Shannon Entropy (H/Hₘₐₓ), Mean Resultant Length (R), and Degree of Gravity Dispersion (DGD)—were integrated into an isotropy index (Sₒₚₜ). The isotropy peaked within an asynchronous range (4.0:3.8, 4.0:3.6, and 4.0:3.4&#xa0;rpm), where gravity vectors exhibited uniform spherical coverage and minimal bias. To further assess the influence of rotational strength beyond the rotational ratio, an additional experiment was conducted using Huh7 hepatocellular carcinoma spheroids. Under high-speed random rotation (~ 4.0&#xa0;rpm), cells formed compact, circular spheroids, whereas low-speed (~ 1.0&#xa0;rpm) or static cultures produced irregular aggregates. These findings indicate that not only the ratio between dual-axis rotations but also the absolute rotational intensity critically affects isotropy and cellular morphogenesis under simulated microgravity. This integrative framework establishes a quantitative foundation for optimizing dual-axis rotating machines.</p>

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Quantitative and visual evaluation of dynamic isotropy in dual-axis random positioning machine (RPM) or clinostat for ground-based microgravity simulation

  • 期刊论文

  • 发表日期：

    2026年1月27日

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  • Seungkwan Cho,
  • Taehyun Lee,
  • Migyo Shin,
  • Doyong Kim,
  • Tack-Joong Kim,
  • Insu Park,
  • Sangwoo Lee,
  • Han Sung Kim

摘要

Microgravity profoundly influences cellular morphology and function, yet ground-based simulation requires systems capable of randomizing the gravity vector. A dual-axis rotating machine (RM), such as a clinostat and random positioning machine (RPM), achieves quasi-isotropic gravitational averaging, but its quantitative optimization remains unclear. Here, a computational–experimental framework was established to evaluate dynamic isotropy of a dual-axis RM. Gravity vector trajectories were simulated across rotation ratios, and five metrics—Spherical Coverage (C), Cumulative Bias (H), Normalized Shannon Entropy (H/Hₘₐₓ), Mean Resultant Length (R), and Degree of Gravity Dispersion (DGD)—were integrated into an isotropy index (Sₒₚₜ). The isotropy peaked within an asynchronous range (4.0:3.8, 4.0:3.6, and 4.0:3.4 rpm), where gravity vectors exhibited uniform spherical coverage and minimal bias. To further assess the influence of rotational strength beyond the rotational ratio, an additional experiment was conducted using Huh7 hepatocellular carcinoma spheroids. Under high-speed random rotation (~ 4.0 rpm), cells formed compact, circular spheroids, whereas low-speed (~ 1.0 rpm) or static cultures produced irregular aggregates. These findings indicate that not only the ratio between dual-axis rotations but also the absolute rotational intensity critically affects isotropy and cellular morphogenesis under simulated microgravity. This integrative framework establishes a quantitative foundation for optimizing dual-axis rotating machines.