**Abstract:** Current cellular agriculture (CA) methodologies for cultivated beef production face challenges related to tissue structure and the efficient recapitulation of native muscle fiber organization. This research proposes a novel framework utilizing hyperdimensional computing (HDC) for optimizing the microstructure of 3D cellular scaffolds, specifically targeting enhanced myogenesis and tissue maturity. By representing scaffold geometries and growth factor profiles as high-dimensional vectors and leveraging iterative optimization through a proprietary “Scaffold Resonance” algorithm, this system is projected to increase muscle fiber density and alignment by 30-50% within a 5-year timeframe, significantly reducing production costs and improving the sensory qualities of cultivated beef products.

**Abstract:** This paper introduces a novel framework for predicting and optimizing myogenesis outcomes by integrating heterogeneous data streams – genomic profiles, histological images, biomechanical measurements, and nutrient composition data – through a structured pipeline employing semantic decomposition, logical consistency verification, and a dynamically weighted HyperScore evaluation system. This system bypasses limitations of existing predictive models that rely on single data modalities and provides a robust, quantifiable assessment of myogenesis potential, leading to accelerated drug discovery, personalized regenerative medicine solutions, and enhanced livestock breeding programs.

Background Skeletal muscle comprises 30–40% of a mammal’s body mass, maintaining its integrity through efficient muscle fiber regeneration, which involves myoblast differentiation into myotubes. Previ...

Skeletal muscle formation and regeneration is a tightly regulated process involving extensive transcriptional reprogramming as proliferating myoblasts fuse into mature myotubes. However, a comparative...

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