This work aims at describing the diversity of osteomyelitis of the jaw (OJ) and at assessing the relevance of a new method designed to avoid salivary contamination during bone sampling in order to improve microbiological analysis and clinical decision-making. We reviewed medical and microbiological data of patients with a suspected OJ based on clinical and/or CT-scan signs and at least one bone sample made for microbiological analysis. During the study period, a new procedure for intraoral bone sampling was elaborated by surgeons and infectious diseases specialists authoring this article (based on stratified samples, cleaning of the surgical site and change of instruments between each sample). A comparison of the microbiological analyses between the two procedures was performed. From 2012 to 2017, 56 patients were included. Median age was 58 years (11-90), sex ratio: 1.24. Main risk factors were having a dental disease (n = 24) or cancer (n = 21). Nineteen patients with the new sample procedure were compared to 37 patients with standard procedure, especially non-cancer patients (n = 16 and 19, respectively). With the new procedure, a median of 3 (1-7) microorganisms per sample was recovered, vs. 7 (1-14) with the former (p < 0.001), a significant decrease of the microbial density was observed for all types of microbes, especially in deeper samples and cultures were more frequently sterile. The way sampling is managed deeply influences microbiological analysis. This strategy facilitates the distinction between pathogens and contaminants and should constitute the first step toward an evidence-based antimicrobial strategy for OJ.

A classical computer with N bits (transistors), has $2^N$ possible states, and the computation process consists in switching on or off certain transistors according to a prescribed program. In contrast, the quantum computer with N qubits (spins) is characterized by $2^N$ quantum amplitudes, which are continuous complex variables. Thus, a toy quantum computer with, say, 50 qubits will be characterized at any given moment by $2^{50} = 1125899906842624$ continuous parameters, which we should be able to manipulate at will. However the number of qubits needed to have a useful machine (i.e. one that can compete with your laptop in factoring very large numbers) is estimated to be $10^3$−$10^5$. The number of continuous variables describing the state of such an apparatus at any given moment is at least $2^{1000}$ (~$10^{300}$) which is much, much greater than the number of particles in the entire Universe (only ~$10^{80}$)! Thus the answer to the question in the title is: As soon as the physicists and engineers will learn to control this quantity of continuous parameters!In recent years the trend is to advertise as quantum computers circuits made from truly quantum devices based on Josephson junctions at liquid helium temperatures, an approach that was initially started by the D-wave company, followed and developed by IBM, Google, Microsoft, and others. This is not going to be the quantum computer everyone was talking about during the last 20 years, as it will not be able to factor large numbers by Shor's algorithm. It will not and cannot compute anything at all, except its own ground state, a process labeled as "quantum annealing". After initial preparation, any system, whether classical or quantum, at low temperature will relax to its ground state. Calculating the ground state of a more or less complex quantum system, either analytically or numerically, is usually impossible – this is what originally inspired Feynman's idea of quantum computing. However, we can measure some properties of this ground state. (The full characterization of the ground state requires measuring $2^N$ parameters).It is not entirely clear what will be the possible practical use of such systems. However, such modeling might provide some additional knowledge on the behavior of large and complicated quantum systems.