"Proving Variable Independence in a Network Using Markov Blanket"

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Is there a simple (meaning, memorable and not just a lot of crunching through probability formulas) proof that a variable is independent of the other variables in the network, given its Markov blanket?
 
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Were you able to get this yet?

Is "a variable", node A in the Markov blanket? And "the other variables in the network" any node that does not belong to the blanket?

If so, then define independent?
 
--No, I have not yet found this out

--A variable is a node in the Bayesian network, together with its conditional probability table

--"Independent" is used in the standard statistical sense
 
If you get it, let me know. I'd be interested to hear. I'm sure I'll realize it in due time, and get back to you if you don't to me first.