Quantum mechanics/molecular mechanics minimum free-energy path for accurate reaction energetics in solution and enzymes: Sequential sampling and optimization on the potential of mean force surface

To accurately determine the reaction path and its energetics for enzymatic and solution-phase reactions, we present a sequential sampling and optimization approach that greatly enhances the efficiency of the ab initio quantum mechanics/molecular mechanics minimum free-energy path (QM/MM-MFEP) method. In the QM/MM-MFEP method, the thermodynamics of a complex reaction system is described by the potential of mean force (PMF) surface of the quantum mechanical (QM) subsystem with a small number of degrees of freedom, somewhat like describing a reaction process in the gas phase. The main computational cost of the QM/MM-MFEP method comes from the statistical sampling of conformations of the molecular mechanical (MM) subsystem required for the calculation of the QM PMF and its gradient. In our new sequential sampling and optimization approach, we aim to reduce the amount of MM sampling while still retaining the accuracy of the results by first carrying out MM phase-space sampling and then optimizing the QM subsystem in the fixed-size ensemble of MM conformations. The resulting QM optimized structures are then used to obtain more accurate sampling of the MM subsystem. This process of sequential MM sampling and QM optimization is iterated until convergence. The use of a fixed-size, finite MM conformational ensemble enables the precise evaluation of the QM potential of mean force and its gradient within the ensemble, thus circumventing the challenges associated with statistical averaging and significantly speeding up the convergence of the optimization process. To further improve the accuracy of the QM/MM-MFEP method, the reaction path potential method developed by Lu and Yang [Z. Lu and W. Yang, J. Chem. Phys. 121, 89 (2004)] is employed to describe the QM/MM electrostatic interactions in an approximate yet accurate way with a computational cost that is comparable to classical MM simulations. The new method was successfully applied to two example reaction processes, the classical SN 2 reaction of Cl- + CH3 Cl in solution and the second proton transfer step of the reaction catalyzed by the enzyme 4-oxalocrotonate tautomerase. The activation free energies calculated with this new sequential sampling and optimization approach to the QM/MM-MFEP method agree well with results from other simulation approaches such as the umbrella sampling technique with direct QM/MM dynamics sampling, demonstrating the accuracy of the iterative QM/MM-MFEP method. © 2008 American Institute of Physics.published_or_final_versio

Far-Ultraviolet Radiation from Elliptical Galaxies

Far-ultraviolet radiation is a ubiquitous, if unanticipated, phenomenon in elliptical galaxies and early-type spiral bulges. It is the most variable photometric feature associated with old stellar populations. Recent observational and theoretical evidence shows that it is produced mainly by low-mass, small-envelope, helium-burning stars in extreme horizontal branch and subsequent phases of evolution. These are probably descendents of the dominant, metal rich population of the galaxies. Their lifetime UV outputs are remarkably sensitive to their physical properties and hence to the age and the helium and metal abundances of their parents. UV spectra are therefore exceptionally promising diagnostics of old stellar populations, although their calibration requires a much improved understanding of giant branch mass loss, helium enrichment, and atmospheric diffusion.Comment: 46 pages; includes LaTeX text file, 9 PS figures, 1 JPG figure, 2 style files. Full resolution figures and PS version available at http://www.astro.virginia.edu/~rwo/araa99/. Article to appear in Annual Reviews of Astronomy & Astrophysics, 199

A Kind of Affine Weighted Moment Invariants

A new kind of geometric invariants is proposed in this paper, which is called affine weighted moment invariant (AWMI). By combination of local affine differential invariants and a framework of global integral, they can more effectively extract features of images and help to increase the number of low-order invariants and to decrease the calculating cost. The experimental results show that AWMIs have good stability and distinguishability and achieve better results in image retrieval than traditional moment invariants. An extension to 3D is straightforward

The association of up-regulation of FGF3 and hepatocellular carcinoma metastasis and recurrence

published_or_final_versio

Effect of nonnutritive sucking and oral stimulation on feeding performance in preterm infants: a randomized controlled trial.

OBJECTIVES: To evaluate the effectiveness of nonnutritive sucking (NNS) and oral stimulation (OS), either applied alone or in combination, to reduce the transition time from tube feeding to independent oral feeding. DESIGN: Randomized controlled trial. SETTING: A 40-bed neonatal ICU in a university hospital in the People's Republic of China. PATIENTS: A total of 120 preterm infants were admitted to the neonatal ICU from December 2012 to July 2013. INTERVENTIONS: Oral motor interventions. MEASUREMENTS AND MAIN RESULTS: One hundred twelve preterm infants were assigned to three intervention groups (NNS, OS, and combined NNS + OS) and one control group. Primary outcome was the number of days needed from introduction of oral feeding to autonomous oral feeding (transition time). Secondary outcome measures were the rate of milk transfer (mL/min), proficiency (intake first 5 min/volume ordered), volume transfer (volume transferred during entire feeding/volume prescribed), weight, and hospital length of stay. Transition time was reduced in the three intervention groups compared with the control group (p < 0.001). The milk transfer rate in the three intervention groups was greater than in the control group (F3,363 = 15.37; p < 0.001). Proficiency in the NNS and OS groups did not exceed that in the control group while the proficiency in the NNS + OS group was greater than that in the control group at the stage when the infants initiated the oral feeding (p = 0.035). Among all groups, no significant difference was found on weight gain and length of stay. CONCLUSIONS: The combined NNS + OS intervention reduced the transition time from introduction to independent oral feeding and enhanced the milk transfer rate. The combined intervention seems to have a beneficial effect on oral feeding proficiency in preterm infants

The effect of cigarette price increase on the cigarette consumption in Taiwan: evidence from the National Health Interview Surveys on cigarette consumption

BACKGROUND: This study uses cigarette price elasticity to evaluate the effect of a new excise tax increase on cigarette consumption and to investigate responses from various types of smokers. METHODS: Our sample consisted of current smokers between 17 and 69 years old interviewed during an annual face-to-face survey conducted by Taiwan National Health Research Institutes between 2000 to 2003. We used Ordinary Least Squares (OLS) procedure to estimate double logarithmic function of cigarette demand and cigarette price elasticity. RESULTS: In 2002, after Taiwan had enacted the new tax scheme, cigarette price elasticity in Taiwan was found to be -0.5274. The new tax scheme brought about an average annual 13.27 packs/person (10.5%) reduction in cigarette consumption. Using the cigarette price elasticity estimate from -0.309 in 2003, we calculated that if the Health and Welfare Tax were increased by another NT$ 3 per pack and cigarette producers shifted this increase to the consumers, cigarette consumption would be reduced by 2.47 packs/person (2.2%). The value of the estimated cigarette price elasticity is smaller than one, meaning that the tax will not only reduce cigarette consumption but it will also generate additional tax revenues. Male smokers who had no income or who smoked light cigarettes were found to be more responsive to changes in cigarette price. CONCLUSIONS: An additional tax added to the cost of cigarettes would bring about a reduction in cigarette consumption and increased tax revenues. It would also help reduce incidents smoking-related illnesses. The additional tax revenues generated by the tax increase could be used to offset the current financial deficiency of Taiwan's National Health Insurance program and provide better public services

Bioinformatics advances in saliva diagnostics

There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva diagnostics made possible by the Saliva Ontology and SDxMart

Anomalous diffusion in polymers: long-time behaviour

We study the Dirichlet boundary value problem for viscoelastic diffusion in polymers. We show that its weak solutions generate a dissipative semiflow. We construct the minimal trajectory attractor and the global attractor for this problem.Comment: 13 page

The challenges of deploying artificial intelligence models in a rapidly evolving pandemic

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2, emerged into a world being rapidly transformed by artificial intelligence (AI) based on big data, computational power and neural networks. The gaze of these networks has in recent years turned increasingly towards applications in healthcare. It was perhaps inevitable that COVID-19, a global disease propagating health and economic devastation, should capture the attention and resources of the world's computer scientists in academia and industry. The potential for AI to support the response to the pandemic has been proposed across a wide range of clinical and societal challenges, including disease forecasting, surveillance and antiviral drug discovery. This is likely to continue as the impact of the pandemic unfolds on the world's people, industries and economy but a surprising observation on the current pandemic has been the limited impact AI has had to date in the management of COVID-19. This correspondence focuses on exploring potential reasons behind the lack of successful adoption of AI models developed for COVID-19 diagnosis and prognosis, in front-line healthcare services. We highlight the moving clinical needs that models have had to address at different stages of the epidemic, and explain the importance of translating models to reflect local healthcare environments. We argue that both basic and applied research are essential to accelerate the potential of AI models, and this is particularly so during a rapidly evolving pandemic. This perspective on the response to COVID-19, may provide a glimpse into how the global scientific community should react to combat future disease outbreaks more effectively.Comment: Accepted in Nature Machine Intelligenc