Biomarkers in emergency medicine

Researchers navigate the ocean of biomarkers searching for proper targets and optimal utilization of them. Emergency medicine builds up the front line to maximize the utility of clinically validated biomarkers and is the cutting edge field to test the applicability of promising biomarkers emerging from thorough translational researches. The role of biomarkers in clinical decision making would be of greater significance for identification, risk stratification, monitoring, and prognostication of the patients in the critical- and acute-care settings. No doubt basic research to explore novel biomarkers in relation to the pathogenesis is as important as its clinical counterpart. This special issue includes five selected research papers that cover a variety of biomarker- and disease-related topics

Spectral Gap Amplification

A large number of problems in science can be solved by preparing a specific eigenstate of some Hamiltonian H. The generic cost of quantum algorithms for these problems is determined by the inverse spectral gap of H for that eigenstate and the cost of evolving with H for some fixed time. The goal of spectral gap amplification is to construct a Hamiltonian H' with the same eigenstate as H but a bigger spectral gap, requiring that constant-time evolutions with H' and H are implemented with nearly the same cost. We show that a quadratic spectral gap amplification is possible when H satisfies a frustration-free property and give H' for these cases. This results in quantum speedups for optimization problems. It also yields improved constructions for adiabatic simulations of quantum circuits and for the preparation of projected entangled pair states (PEPS), which play an important role in quantum many-body physics. Defining a suitable black-box model, we establish that the quadratic amplification is optimal for frustration-free Hamiltonians and that no spectral gap amplification is possible, in general, if the frustration-free property is removed. A corollary is that finding a similarity transformation between a stoquastic Hamiltonian and the corresponding stochastic matrix is hard in the black-box model, setting limits to the power of some classical methods that simulate quantum adiabatic evolutions.Comment: 14 pages. New version has an improved section on adiabatic simulations of quantum circuit

Parameter Estimation with Mixed-State Quantum Computation

We present a quantum algorithm to estimate parameters at the quantum metrology limit using deterministic quantum computation with one bit. When the interactions occurring in a quantum system are described by a Hamiltonian $H= \theta H_0$, we estimate $\theta$ by zooming in on previous estimations and by implementing an adaptive Bayesian procedure. The final result of the algorithm is an updated estimation of $\theta$ whose variance has been decreased in proportion to the time of evolution under H. For the problem of estimating several parameters, we implement dynamical-decoupling techniques and use the results of single parameter estimation. The cases of discrete-time evolution and reference-frame alignment are also discussed within the adaptive approach.Comment: 12 pages. Improved introduction and technical details moved to Appendi

Necessary Condition for the Quantum Adiabatic Approximation

A gapped quantum system that is adiabatically perturbed remains approximately in its eigenstate after the evolution. We prove that, for constant gap, general quantum processes that approximately prepare the final eigenstate require a minimum time proportional to the ratio of the length of the eigenstate path to the gap. Thus, no rigorous adiabatic condition can yield a smaller cost. We also give a necessary condition for the adiabatic approximation that depends on local properties of the path, which is appropriate when the gap varies.Comment: 5 pages, 1 figur

Quantum Speedup by Quantum Annealing

We study the glued-trees problem of Childs et. al. in the adiabatic model of quantum computing and provide an annealing schedule to solve an oracular problem exponentially faster than classically possible. The Hamiltonians involved in the quantum annealing do not suffer from the so-called sign problem. Unlike the typical scenario, our schedule is efficient even though the minimum energy gap of the Hamiltonians is exponentially small in the problem size. We discuss generalizations based on initial-state randomization to avoid some slowdowns in adiabatic quantum computing due to small gaps.Comment: 7 page

Importance of spinal deformity index in risk evaluation of VCF (vertebral compression fractures) in obese subjects: prospective study.

Introduction Obesity and osteoporosis share many features and recent studies have identified many similarities suggesting common pathophysiological mechanisms. Obesity is associated with a higher risk of non-traumatic fractures despite bone mineral density (BMD) being normal or even increased. Materials and methods 54 obese subjects were analyzed (51 ± 16 years, 10 males, 44 females). Spinal deformity index (SDI) is a semi-quantitative method that may be a surrogate index of bone microarchitecture. SDI index was higher in patients than in controls. In 87.5 % of patients and 10 % of controls we found morphometric vertebral fractures, despite a DEXA Tscore not diagnostic of osteoporosis. Conclusion The objective of this study was to assess in obese patients levels of 25OH vitamin D, parathyroid hormone, serum and urinary calcium (Ca) and phosphorus (P), BMD, and SDI. 87.5 % of the obese subjects present nontraumatic vertebral fractures and reduced bone quality as measured by SDI

A Quantum Approach to Classical Statistical Mechanics

We present a new approach to study the thermodynamic properties of $d$-dimensional classical systems by reducing the problem to the computation of ground state properties of a $d$-dimensional quantum model. This classical-to-quantum mapping allows us to deal with standard optimization methods, such as simulated and quantum annealing, on an equal basis. Consequently, we extend the quantum annealing method to simulate classical systems at finite temperatures. Using the adiabatic theorem of quantum mechanics, we derive the rates to assure convergence to the optimal thermodynamic state. For simulated and quantum annealing, we obtain the asymptotic rates of $T(t) \approx (p N) /(k_B \log t)$ and $\gamma(t) \approx (Nt)^{-\bar{c}/N}$, for the temperature and magnetic field, respectively. Other annealing strategies, as well as their potential speed-up, are also discussed.Comment: 4 pages, no figure

Obesity and sleep disturbance: the chicken or the egg?

Epidemiological studies suggested an association between obesity and sleep disturbances. Obstructive sleep apnea is the most prevalent type of obesity-related sleep disorder that lead to an increased risk for numerous chronic health conditions. In addition the increased visceral adipose tissue might be responsible for the secretion of inflammatory cytokines that could contribute to alter the sleep-wake rhythm. Unhealthy food characterized by high consumption of fat and carbohydrate seems to negatively influence the quality of sleep while diet rich of fiber is associated to more restorative and deeper sleep. Although obesity could cause through several pathogenetic mechanisms an alteration of sleep, it has been reported that subjects suffering from sleep disorders are more prone to develop obesity. Experimental laboratory studies have demonstrated that decreasing either the amount or quality of sleep increase the risk of developing obesity. Experimental sleep restriction also causes physiological, hormonal and food behavioral changes that promote a positive energy balance and a compensatory disproportionate increase in food intake, decrease in physical activity, and weight gain. Thus, the aim of this review is to provide observational evidence on the association of obesity with sleep disturbances and viceversa with emphasis on possible pathophysiological mechanisms (hormonal and metabolic) that link these two pathological conditions