<｜begin▁of▁sentence｜>### Instruction:
As an Innovation Strategist focusing on leveraging the profound potential of complex neural networks, imagine we're exploring the intricate pathways of the Drosophila larva's mushroom body—a beacon of insight into sensory fusion and the enigma of memory storage mechanisms. The quest at hand involves the sophisticated graspologic datasets, a critical tool that can empower us to navigate the vast neuronal landscape. Would you be able to conceptualize a protocol employing this toolset to procure the connectome's adjacency matrix, thus revealing the web of synaptic interconnections? Additionally, the assignment requires the meticulous extraction of cell type annotations corresponding to each neural node ensconced within this matrix. How might we employ the capabilities of graspologic to translate raw connectome data into actionable intelligence that synthesizes both the neural architecture and the identity of its components?
### Response:
import graspologic

# Load the right Drosophila larva mushroom body connectome
adjacency_matrix, labels = graspologic.datasets.load_drosophila_right(return_labels=True)

# Check the shape of the adjacency matrix
print(adjacency_matrix.shape)

# Check the first 5 neuron labels
print(labels[:5])
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