  Conditions on the generator of a Markov process to control the fluctuations
of its bridges are found. In particular, continuous time random walks on graphs
and gradient diffusions are considered. Under these conditions, a concentration
of measure inequality for the marginals of the bridge of a gradient diffusion
and refined large deviation expansions for the tails of a random walk on a
graph are derived. In contrast with the existing literature about bridges, all
the estimates we obtain hold for non asymptotic time scales. New concentration
of measure inequalities for pinned Poisson random vectors are also established.
The quantities expressing our conditions are the so called \textit{reciprocal
characteristics} associated with the Markov generator.
