<｜begin▁of▁sentence｜>### Instruction:
Imagine you're at the laboratory with a network map that resembles patients connected through blood vessels, structured in a peculiar way that resembles a weight with two identical masses joined by a thin bar. This 'blood vessel network' is represented by a barbell graph, where two separate groups of four patients (consider them as clusters where every patient is directly connected to all others in the same cluster), are linked by a 'bloodstream' involving a sequence of two individual connections.

Your task, much like identifying a vein that, if accessed, would affect the circulation between these clusters, is to pinpoint the critical junctions within this network map. Specifically, these junctions are analogous to individuals whose absence would impede the flow of information between the two groups, effectively isolating one cluster from the other—just as the removal of a key blood vessel can lead to isolated regions of circulation.

To extend the metaphor to your field, think of these junctions as 'articulation points' in the graph—the nodes whose 'removal' results in an increase in the number of separate, disconnected patient clusters. Your challenge is to determine which patients (nodes) in the 'barbell graph' consisting of two complete graphs of four individuals connected by a pathway involving two people, serve this critical role.

Just as you meticulously label and handle blood samples following standard protocols, this task requires an equally careful analysis to ensure the network's representation accurately reflects the critical points within it.
### Response:
import networkx as nx

# Create an undirected graph
G = nx.barbell_graph(4, 2)

# Identify the articulation points of the graph
articulation_pts = list(nx.articulation_points(G))

print('Articulation points:', articulation_pts)
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