Computational free-energy correction strategies and the choice of experimental proton hydration free energy, ΔG(H), are analyzed to investigate the apparent controversy in experimental thermodynamics of ionic hydration. Without corrections, the hydration free-energy (ΔG) calculations match experiments with ΔG(H) = -1064 kJ/mol as reference. Using the Galvani surface potential the resulting (real) ΔG are consistent with ΔG(H) = -1098 kJ/mol. When applying, in an ad hoc manner, the discrete solvent correction, ΔG matching the "consensus" ΔG(H) of -1112 kJ/mol are obtained. This analysis rationalizes reports on ΔG calculations for ions using different experimental references. For neutral amino acid side chains ΔG are independent of the water model, whereas there are large differences in ΔG due to the water model for charged species, suggesting that long-range ordering of water around ions yields an important contribution to the ΔG. These differences are reduced significantly when applying consistent corrections, but to obtain the most accurate results it is recommended to use the water model belonging to the force field.

Concurrent evidence regarding the impact of air pollution on body weight status remains mixed. Future studies should assess the impact of severe air pollution on obesity in developing countries, focus on a homogenous population subgroup, and elucidate the biomedical and psychosocial pathways linking air pollution to body weight.

Binding affinity prediction with implicit solvent models remains a challenge in virtual screening for drug discovery. In order to assess the predictive power of implicit solvent models in docking techniques with Amber scoring, three generalized Born models (GB, GBI, and GBII) available in Dock 6.7 were utilized, for determining the binding affinity of a large set of β-cyclodextrin complexes with 75 neutral guest molecules. The results were compared to potential of mean force (PMF) free energy calculations with four GB models (GB, GB, GBI, and GBII) and to experimental data. Docking results yield similar accuracy to the computationally demanding PMF method with umbrella sampling. Neither docking nor PMF calculations reproduce the experimental binding affinities, however, as indicated by a small Spearman rank order coefficient (∼0.5). The binding energies obtained from GB models were decomposed further into individual contributions of the binding partners and solvent environments and compared to explicit solvent simulations for five complexes allowing for rationalizing the difference between explicit and implicit solvent models. An important observation is that the explicit solvent screens the interaction between host and guest much stronger than GB models. In contrast, the screening in GB models is too strong in solutes, leading to overestimation of short-range interactions and too strong binding. It is difficult to envision a way of overcoming these two opposite effects.

BackgroundPhysical inactivity is a leading cause of morbidity, disability and premature mortality in the U.S. and worldwide. This study aimed to map the prevalence of physical inactivity across U.S. states over the past three decades, and estimate the over-time adjusted changes in the prevalence of physical inactivity in each state.MethodsIndividual-level data (N = 6,701,954) were taken from the 1984–2015 Behavioral Risk Factor Surveillance System (BRFSS), an annually repeated cross-sectional survey of state-representative adult population. Prevalence of self-reported leisure-time physical inactivity was estimated by state and survey year, accounting for the BRFSS sampling design. Logistic regressions were performed to estimate the changes in the prevalence of physical inactivity over the study period for each state, adjusting for individual characteristics including sex, age, race/ethnicity, education, marital status, and employment status.ResultsThe prevalence of leisure-time physical inactivity varied substantially across states and survey years. In general, the adjusted prevalence of physical inactivity gradually declined over the past three decades in a majority of states. However, a substantial proportion of American adults remain physically inactive. Among the 50 states and District of Columbia, 45 had over a fifth of their adult population without any leisure-time physical activity, and 8 had over 30% without physical activity in 2015. Moreover, the adjusted prevalence of physical inactivity in several states (Arizona, North Carolina, North Dakota, Utah, West Virginia, and Wyoming) remained largely unchanged or even increased (Minnesota and Ohio) over the study period.ConclusionsAlthough the prevalence of physical inactivity declined over the past three decades in a majority of states, the rates remain substantially high and vary considerably across states. Closely monitoring and tracking physical activity level using the state physical activity maps can help guide policy and program development to promote physical activity and reduce the burden of chronic disease.

Dietary habits might profoundly impact cognitive functioning among the oldest-old Chinese. This work has limitations pertaining to study design and measure. Future work adopting experimental design and refined dietary measures is warranted to confirm these findings and inform public nutrition practices aiming at preventing cognitive decline among the oldest-old Chinese population.