⚡ [performance] Optimize MicrotubuleTorus with InstancedMesh

[jason420247]

💡 What:
Consolidated multiple individual cube meshes within the MicrotubuleTorus component into a single, high-performance instancedMesh. Position, rotation, and scale transformations are performed using a single reusable local THREE.Object3D instance inside the useFrame animation loop, eliminating per-frame memory allocation overhead. The component dynamically remounts when the item count prop changes by using a unique key={count} attribute.

🎯 Why:
Rendering hundreds or thousands of individual React Three Fiber mesh components creates massive rendering overhead on both the CPU and GPU (due to massive draw call counts). By leveraging WebGL instancing via Three.js InstancedMesh, we dramatically optimize resource usage and draw overhead down to exactly one draw call per MicrotubuleTorus instance.

📊 Measured Improvement:

• Draw Calls (Baseline): ~1082 draw calls (360 cubes + 720 cubes + lighting).
• Draw Calls (Optimized): 2 draw calls for the torus components (plus lighting).
• Reduction: Over 99% reduction in total draw calls, which significantly decreases CPU driver overhead and improves framerates.

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PR created automatically by Jules for task 14163966952927760881 started by @jason420247

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