<｜begin▁of▁sentence｜>### Instruction:
As a Registered Nurse providing patient care and education under the supervision of healthcare providers, imagine you're overseeing a medical research project focusing on analyzing interconnected networks within the human body. To simulate these networks, you're using a computational tool called NetworkX, commonly employed in various scientific fields.

In this scenario, you're specifically examining a network modeled after the human body's interconnections, represented by an Erdos-Renyi graph with 800 nodes and a probability parameter of 0.3 for edge creation. Now, you're tasked with utilizing the RandomWalkWithJumpSampler function, a tool within NetworkX, to extract a subset of 100 nodes from this network for further analysis.

After sampling these nodes, your next critical step is to determine whether the resulting subset forms a connected graph or not. This information is vital for the research team to understand the cohesive nature of the sampled portion and its implications for broader network analysis within the human body.
### Response:
import networkx as nx
from littleballoffur import RandomWalkWithJumpSampler

G = nx.gnp_random_graph(n=800, p=0.3)

sampler = RandomWalkWithJumpSampler(100, seed=42, p=0.1)

sampler_G = sampler.sample(G)

result = nx.is_connected(sampler_G)

print(result)
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