Bioenergetic medicine

Here we discuss a specific therapeutic strategy we call ‘bioenergetic medicine’. Bioenergetic medicine refers to the manipulation of bioenergetic fluxes to positively affect health. Bioenergetic medicine approaches rely heavily on the law of mass action, and impact systems that monitor and respond to the manipulated flux. Since classically defined energy metabolism pathways intersect and intertwine, targeting one flux also tends to change other fluxes, which complicates treatment design. Such indirect effects, fortunately, are to some extent predictable, and from a therapeutic perspective may also be desirable. Bioenergetic medicine-based interventions already exist for some diseases, and because bioenergetic medicine interventions are presently feasible, new approaches to treat certain conditions, including some neurodegenerative conditions and cancers, are beginning to transition from the laboratory to the clinic.

Linked Articles

This article is part of a themed issue on Mitochondrial Pharmacology: Energy, Injury & Beyond. To view the other articles in this issue visit http://dx.doi.org/10.1111/bph.2014.171.issue-8     

Optimization of secondary drying condition for desired residual water content in a lyophilized product using a novel simulation program for pharmaceutical lyophilization

The aim of this study was to optimize the shelf temperature and the drying time, mainly dependent on the residual water content of a lyophilized product using a novel simulation program for the secondary drying of lyophilization. The simulation program was developed based upon heat transfer formulas, two empirical formulas, and a modified Fick’s second law. When a preliminary lyophilization run of secondary drying was carried out, the equilibrium product temperature at the end of secondary drying under various shelf temperatures was accurately predicted by the heat transfer formulas. The apparent diffusion coefficient of water, D_eff, and the apparent equilibrium residual water content, W_e, under the predicted equilibrium product temperature were estimated by two empirical formulas. These estimated D_eff and W_e allow the modified Fick’s second law to predict the residual water content in the lyophilized product. Using the developed simulation program, it was verified that the secondary drying condition to achieve the desired residual water content in the lyophilized product was successfully predicted. Therefore, the simulation program can be used to effectively design the secondary drying condition of lyophilization cycles without a trial and error approach.     

医师多点执业的政策障碍与可行路径

本文讨论了医师多点执业的内涵、该政策实行受阻的原因及对策。目前,我国公立医院的医师是“单位人”,而不是“自由执业者”,医院与医师均缺乏多点执业的动力,需要从立法、制度和政策三个方面来保障医师多点执业。大力发展私立医院、改善医师自由执业的条件是促进医师多点执业的重要前提。该政策的实行需要政府多部门和广大医师的参与,需要通过试点和实践检验做出循证决策。     

Risks,prices, and positions: A social network analysis of illegal drug trafficking in the world-economy

BackgroundIllegal drug prices are extremely high, compared to similar goods. There is, however, considerable variation in value depending on place, market level and type of drugs. A prominent framework for the study of illegal drugs is the “risks and prices” model (Reuter & Kleiman, 1986). Enforcement is seen as a “tax” added to the regular price. In this paper, it is argued that such economic models are not sufficient to explain price variations at country-level. Drug markets are analysed as global trade networks in which a country's position has an impact on various features, including illegal drug prices.MethodologyThis paper uses social network analysis (SNA) to explain price markups between pairs of countries involved in the trafficking of illegal drugs between 1998 and 2007. It aims to explore a simple question: why do prices increase between two countries? Using relational data from various international organizations, separate trade networks were built for cocaine, heroin and cannabis. Wholesale price markups are predicted with measures of supply, demand, risks of seizures, geographic distance and global positioning within the networks. Reported prices (in $US) and purchasing power parity-adjusted values are analysed.ResultsDrug prices increase more sharply when drugs are headed to countries where law enforcement imposes higher costs on traffickers. The position and role of a country in global drug markets are also closely associated with the value of drugs. Price markups are lower if the destination country is a transit to large potential markets. Furthermore, price markups for cocaine and heroin are more pronounced when drugs are exported to countries that are better positioned in the legitimate world-economy, suggesting that relations in legal and illegal markets are directed in opposite directions.ConclusionConsistent with the world-system perspective, evidence is found of coherent world drug markets driven by both local realities and international relations.     

比较“法体系”视角下我国执业药师考试模式探讨

本文基于执业医师考试管理较为成熟,其管理依据为《执业医师法》体系较为完善的原因.两者同属人力资源管理领域,对比研究、探讨当前执业药师考试制度.     

Evaluation of Smeared Constitutive Laws for Tensile Concrete to Predict the Cracking of RC Beams under Torsion with Smeared Truss Model

In this study, the generalized softened variable angle truss-model (GSVATM) is used to predict the response of reinforced concrete (RC) beams under torsion at the early loading stages, namely the transition from the uncracked to the cracked stage. Being a 3-dimensional smeared truss model, the GSVATM must incorporate smeared constitutive laws for the materials, namely for the tensile concrete. Different smeared constitutive laws for tensile concrete can be found in the literature, which could lead to different predictions for the torsional response of RC beams at the earlier stages. Hence, the GSVATM is used to check several smeared constitutive laws for tensile concrete proposed in previous studies. The studied parameters are the cracking torque and the corresponding twist. The predictions of these parameters from the GSVATM are compared with the experimental results from several reported tests on RC beams under torsion. From the obtained results and the performed comparative analyses, one of the checked smeared constitutive laws for tensile concrete was found to lead to good predictions for the cracking torque of the RC beams regardless of the cross-section type (plain or hollow). Such a result could be useful to help with choosing the best constitutive laws to be incorporated into the smeared truss models to predict the response of RC beams under torsion.     

Analysis of medical malpractice claims to improve quality of care: Cautionary remarks

Medical malpractice claims can be analysed to gain insights aimed at improving quality of care. However, using medical malpractice claims in medical research raises epistemological and methodological concerns related to certain features of the litigation process. Medical research should therefore approach medical malpractice claims with caution. Taking one recent study as a an example, this article insists on three areas of concern: (a) the quantity of legal materials available for analysis; (b) the content of the legal materials available for analysis; and (c) the ways in which the content of the legal materials should be analysed and the types of inferences that it can support. The article concludes with general recommendations for future medical research that would incorporate medical malpractice claims. These recommendations centre around recognizing the qualitative dimension of legal reasoning.     

Noise-driven growth rate gain in clonal cellular populations

Cellular populations in both nature and the laboratory are composed of phenotypically heterogeneous individuals that compete with each other resulting in complex population dynamics. Predicting population growth characteristics based on knowledge of heterogeneous single-cell dynamics remains challenging. By observing groups of cells for hundreds of generations at single-cell resolution, we reveal that growth noise causes clonal populations of Escherichia coli to double faster than the mean doubling time of their constituent single cells across a broad set of balanced-growth conditions. We show that the population-level growth rate gain as well as age structures of populations and of cell lineages in competition are predictable. Furthermore, we theoretically reveal that the growth rate gain can be linked with the relative entropy of lineage generation time distributions. Unexpectedly, we find an empirical linear relation between the means and the variances of generation times across conditions, which provides a general constraint on maximal growth rates. Together, these results demonstrate a fundamental benefit of noise for population growth, and identify a growth law that sets a “speed limit” for proliferation.Cell growth is an important physiological process that underlies the fitness of organisms. In exponentially growing cell populations, proliferation is usually quantified using the bulk population growth rate, which is assumed to represent the average growth rate of single cells within a population. In addition, basic growth laws exist that relate ribosome function and metabolic efficiency, macromolecular composition, and cell size of the culture as a whole to the bulk population growth rate (1–3). Population growth rate is therefore a quantity of primary importance that reports cellular physiological states and fitness.However, at the single-cell level, growth-related parameters such as the division time interval and division cell size are heterogeneous even in a clonal population growing at a constant rate (4–9). Such “growth noise” causes concurrently living cells to compete within the population for representation among its future descendants. For example, if two sibling cells born from the same mother cell had different division intervals, the faster dividing sibling is likely to have more descendants in the future population compared with its slower dividing sister, despite the fact that progenies of both siblings may proliferate equally well (Fig. 1). Intrapopulation competition complicates single-cell analysis because any growth-correlated quantities measured over the population deviate from intrinsic single-cell properties (10–12). In the case of the toy model described in Fig. 1, cells are assumed to determine their generation times (division interval) randomly by roll of a dice. The mean of intrinsic cellular generation time is thus (1 + 2 +  ?  + 6)/6 = 3.5 h, but population doubling time, which is the time required for a population to double the number of cells, is in fact 3.2 h. This counterintuitive result is a direct consequence of growth noise in a population. Indeed, as we will see, the population doubling time can only equal the mean generation time when no variability of generation time exists at the single-cell level. Population growth rate is determined not only by an average of single cells but also by the details of heterogeneity within a population. Therefore, understanding how population growth rates and other properties arise from single-cell heterogeneity poses a fundamental challenge to single-cell biology.Open in a separate windowFig. 1.Competition within a population caused by growth noise and its consequence to population growth rate. (A) Toy model of cell proliferation. Here, we consider a model of cell proliferation in which all of the cells in a population determine their generation time (interdivision time) randomly by throwing a dice to learn the consequences of intrapopulation growth noise. In this setting, cells can take either of the six possible choices of generation time, τ=1,2,⋯,6 h, with the equal probability of 1/6. The mean generation time is thus ?τ?_g= 3.5 h. (B) Example of pedigree tree showing competition between sibling cells. In this tree, two sibling cells were born from the common mother cell at t = 0 h, and divided with different generation times (sibling cell 1: τ_s1 = 5 h; and sibling cell 2: τ_s2 = 2 h). The descendant cells from the both sibling cells follow the same rule of cell divisions irrespectively of the ancestral generation time. The difference of generation time between the sibling cells 1 and 2 was caused just by chance, but the expected number of descendant cells becomes larger for the fast dividing sibling cell. The ratio of the expected number of descendant cells from those sibling cells at a certain future time point is ?N₁?/?N₂? = e^{?Λ_p(τ_s1?τ_s2)}, where Λ_p is the population growth rate. (C) Growth of cell population. When all of the cells in the population follow the same division rule in A, the number of cells in the population grows exponentially. The rate of this exponential growth is the “population growth rate,” Λ_p. The time required for the population to double the number of cells is the “population doubling time,” T_d, i.e., N(t) = N(0)2^t/T_d. Therefore, T_d = ln2/Λ_p. An interesting consequence of stochasticity in generation time is that population doubling time becomes smaller than the mean generation time, i.e., T_d <?τ?_g. In the case of the dice population, T_d = 3.187 h, which is indeed smaller than ?τ?_g= 3.5 h.A classical study of theoretical and experimental microbiology attempted to reveal the discrepancies between mean cellular generation times and population doubling times in real bacterial populations (13). Experimental methods and techniques available at that time, however, hampered reliable tests. Recently, the techniques of single-cell time-lapse microscopy have advanced to a great extent, revealing the heterogeneous and stochastic nature of single-cell dynamics quantitatively (14). With the aid of microfluidic platforms, tracking single cells over many generations in controlled constant or changing environments has also become feasible, providing insights into the mechanisms of cell size homeostasis and stress responses (3, 6, 7, 9, 15–22).In this study, through microfluidics time-lapse microscopy and single-cell analysis on large-scale, single-cell lineage trees, we reveal that clonal populations of Escherichia coli indeed grow with a doubling time that is smaller than the mean doubling time of their constituent cells under broad, balanced-growth conditions. We show that the observed growth rate gains and population age structures are predictable from cellular generation time distributions based on a simple age-structured population model. Furthermore, we reveal unique features of long single-cell lineages within populations in competition, and provide a history-based formulation that connects growth rate gain with a measure of statistical deviation between isolated and competing lineages. Finally, we demonstrate a linear relation between the means and the variances of generation time across conditions, which constrains the maximum growth rate of this organism.     

How main-chains of proteins explore the free-energy landscape in native states

Understanding how a single native protein diffuses on its free-energy landscape is essential to understand protein kinetics and function. The dynamics of a protein is complex, with multiple relaxation times reflecting a hierarchical free-energy landscape. Using all-atom molecular dynamics simulations of an α/β protein (crambin) and a β-sheet polypeptide (BS2) in their “native” states, we demonstrate that the mean-square displacement of dihedral angles, defined by 4 successive C^α atoms, increases as a power law of time, t^α, with an exponent α between 0.08 and 0.39 (α = 1 corresponds to Brownian diffusion), at 300 K. Residues with low exponents are located mainly in well-defined secondary elements and adopt 1 conformational substate. Residues with high exponents are found in loops/turns and chain ends and exist in multiple conformational substates, i.e., they move on multiple-minima free-energy profiles.