Inert gas clearance from tissue by co-currently and counter-currently arranged microvessels

To elucidate the clearance of dissolved inert gas from tissues, we have developed numerical models of gas transport in a cylindrical block of tissue supplied by one or two capillaries. With two capillaries, attention is given to the effects of co-current and counter-current flow on tissue gas clearance. Clearance by counter-current flow is compared with clearance by a single capillary or by two co-currently arranged capillaries. Effects of the blood velocity, solubility, and diffusivity of the gas in the tissue are investigated using parameters with physiological values. It is found that under the conditions investigated, almost identical clearances are achieved by a single capillary as by a co-current pair when the total flow per tissue volume in each unit is the same (i.e., flow velocity in the single capillary is twice that in each co-current vessel). For both co-current and counter-current arrangements, approximate linear relations exist between the tissue gas clearance rate and tissue blood perfusion rate. However, the counter-current arrangement of capillaries results in less-efficient clearance of the inert gas from tissues. Furthermore, this difference in efficiency increases at higher blood flow rates. At a given blood flow, the simple conduction-capacitance model, which has been used to estimate tissue blood perfusion rate from inert gas clearance, underestimates gas clearance rates predicted by the numerical models for single vessel or for two vessels with co-current flow. This difference is accounted for in discussion, which also considers the choice of parameters and possible effects of microvascular architecture on the interpretation of tissue inert gas clearance

Macrophage migration inhibitory factor downregulation: a novel mechanism of resistance to anti-angiogenic therapy.

Anti-angiogenic therapies for cancer such as VEGF neutralizing antibody bevacizumab have limited durability. While mechanisms of resistance remain undefined, it is likely that acquired resistance to anti-angiogenic therapy will involve alterations of the tumor microenvironment. We confirmed increased tumor-associated macrophages in bevacizumab-resistant glioblastoma patient specimens and two novel glioblastoma xenograft models of bevacizumab resistance. Microarray analysis suggested downregulated macrophage migration inhibitory factor (MIF) to be the most pertinent mediator of increased macrophages. Bevacizumab-resistant patient glioblastomas and both novel xenograft models of resistance had less MIF than bevacizumab-naive tumors, and harbored more M2/protumoral macrophages that specifically localized to the tumor edge. Xenografts expressing MIF-shRNA grew more rapidly with greater angiogenesis and had macrophages localizing to the tumor edge which were more prevalent and proliferative, and displayed M2 polarization, whereas bevacizumab-resistant xenografts transduced to upregulate MIF exhibited the opposite changes. Bone marrow-derived macrophage were polarized to an M2 phenotype in the presence of condition-media derived from bevacizumab-resistant xenograft-derived cells, while recombinant MIF drove M1 polarization. Media from macrophages exposed to bevacizumab-resistant tumor cell conditioned media increased glioma cell proliferation compared with media from macrophages exposed to bevacizumab-responsive tumor cell media, suggesting that macrophage polarization in bevacizumab-resistant xenografts is the source of their aggressive biology and results from a secreted factor. Two mechanisms of bevacizumab-induced MIF reduction were identified: (1) bevacizumab bound MIF and blocked MIF-induced M1 polarization of macrophages; and (2) VEGF increased glioma MIF production in a VEGFR2-dependent manner, suggesting that bevacizumab-induced VEGF depletion would downregulate MIF. Site-directed biopsies revealed enriched MIF and VEGF at the enhancing edge in bevacizumab-naive patients. This MIF enrichment was lost in bevacizumab-resistant glioblastomas, driving a tumor edge M1-to-M2 transition. Thus, bevacizumab resistance is driven by reduced MIF at the tumor edge causing proliferative expansion of M2 macrophages, which in turn promotes tumor growth

Anatomical Network Comparison of Human Upper and Lower, Newborn and Adult, and Normal and Abnormal Limbs, with Notes on Development, Pathology and Limb Serial Homology vs. Homoplasy

How do the various anatomical parts (modules) of the animal body evolve into very different integrated forms (integration) yet still function properly without decreasing the individual's survival? This long-standing question remains unanswered for multiple reasons, including lack of consensus about conceptual definitions and approaches, as well as a reasonable bias toward the study of hard tissues over soft tissues. A major difficulty concerns the non-trivial technical hurdles of addressing this problem, specifically the lack of quantitative tools to quantify and compare variation across multiple disparate anatomical parts and tissue types. In this paper we apply for the first time a powerful new quantitative tool, Anatomical Network Analysis (AnNA), to examine and compare in detail the musculoskeletal modularity and integration of normal and abnormal human upper and lower limbs. In contrast to other morphological methods, the strength of AnNA is that it allows efficient and direct empirical comparisons among body parts with even vastly different architectures (e.g. upper and lower limbs) and diverse or complex tissue composition (e.g. bones, cartilages and muscles), by quantifying the spatial organization of these parts-their topological patterns relative to each other-using tools borrowed from network theory. Our results reveal similarities between the skeletal networks of the normal newborn/adult upper limb vs. lower limb, with exception to the shoulder vs. pelvis. However, when muscles are included, the overall musculoskeletal network organization of the upper limb is strikingly different from that of the lower limb, particularly that of the more proximal structures of each limb. Importantly, the obtained data provide further evidence to be added to the vast amount of paleontological, gross anatomical, developmental, molecular and embryological data recently obtained that contradicts the long-standing dogma that the upper and lower limbs are serial homologues. In addition, the AnNA of the limbs of a trisomy 18 human fetus strongly supports Pere Alberch's ill-named "logic of monsters" hypothesis, and contradicts the commonly accepted idea that birth defects often lead to lower integration (i.e. more parcellation) of anatomical structures

The continuum limit of the static-light meson spectrum

We investigate the continuum limit of the low lying static-light meson spectrum using Wilson twisted mass lattice QCD with N_f = 2 dynamical quark flavours. We consider three values of the lattice spacing a ~ 0.051 fm, 0.064 fm, 0.080 fm and various values of the pion mass in the range 280 MeV < m_PS < 640 MeV. We present results in the continuum limit for light cloud angular momentum j = 1/2, 3/2, 5/2 and for parity P = +, -. We extrapolate our results to physical quark masses, make predictions regarding the spectrum of B and B_s mesons and compare with available experimental results.Comment: 18 pages, 3 figure

Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating

Spatial and topological organization of DNA chains induced by gene co-localization

Transcriptional activity has been shown to relate to the organization of chromosomes in the eukaryotic nucleus and in the bacterial nucleoid. In particular, highly transcribed genes, RNA polymerases and transcription factors gather into discrete spatial foci called transcription factories. However, the mechanisms underlying the formation of these foci and the resulting topological order of the chromosome remain to be elucidated. Here we consider a thermodynamic framework based on a worm-like chain model of chromosomes where sparse designated sites along the DNA are able to interact whenever they are spatially close-by. This is motivated by recurrent evidence that there exists physical interactions between genes that operate together. Three important results come out of this simple framework. First, the resulting formation of transcription foci can be viewed as a micro-phase separation of the interacting sites from the rest of the DNA. In this respect, a thermodynamic analysis suggests transcription factors to be appropriate candidates for mediating the physical interactions between genes. Next, numerical simulations of the polymer reveal a rich variety of phases that are associated with different topological orderings, each providing a way to increase the local concentrations of the interacting sites. Finally, the numerical results show that both one-dimensional clustering and periodic location of the binding sites along the DNA, which have been observed in several organisms, make the spatial co-localization of multiple families of genes particularly efficient.Comment: Figures and Supplementary Material freely available on http://dx.doi.org/10.1371/journal.pcbi.100067

Estimation of the solubility parameters of model plant surfaces and agrochemicals: a valuable tool for understanding plant surface interactions

Background Most aerial plant parts are covered with a hydrophobic lipid-rich cuticle, which is the interface between the plant organs and the surrounding environment. Plant surfaces may have a high degree of hydrophobicity because of the combined effects of surface chemistry and roughness. The physical and chemical complexity of the plant cuticle limits the development of models that explain its internal structure and interactions with surface-applied agrochemicals. In this article we introduce a thermodynamic method for estimating the solubilities of model plant surface constituents and relating them to the effects of agrochemicals. Results Following the van Krevelen and Hoftyzer method, we calculated the solubility parameters of three model plant species and eight compounds that differ in hydrophobicity and polarity. In addition, intact tissues were examined by scanning electron microscopy and the surface free energy, polarity, solubility parameter and work of adhesion of each were calculated from contact angle measurements of three liquids with different polarities. By comparing the affinities between plant surface constituents and agrochemicals derived from (a) theoretical calculations and (b) contact angle measurements we were able to distinguish the physical effect of surface roughness from the effect of the chemical nature of the epicuticular waxes. A solubility parameter model for plant surfaces is proposed on the basis of an increasing gradient from the cuticular surface towards the underlying cell wall. Conclusions The procedure enabled us to predict the interactions among agrochemicals, plant surfaces, and cuticular and cell wall components, and promises to be a useful tool for improving our understanding of biological surface interactions

LHC Discovery Potential for Non-Standard Higgs Bosons in the 3b Channel

In a variety of well motivated models, such as two Higgs Doublet Models (2HDMs) and the Minimal Supersymmetric Standard Model (MSSM), there are neutral Higgs bosons that have significantly enhanced couplings to b-quarks and tau leptons in comparison to those of the SM Higgs. These so called non-standard Higgs bosons could be copiously produced at the LHC in association with b quarks, and subsequently decay into b-quark pairs. However, this production channel suffers from large irreducible QCD backgrounds. We propose a new search strategy for non-standard neutral Higgs bosons at the 7 TeV LHC in the 3b's final state topology. We perform a simulation of the signal and backgrounds, using state of the art tools and methods for different sets of selection cuts, and conclude that neutral Higgs bosons with couplings to b-quarks of about 0.3 or larger, and masses up to 400 GeV, could be seen with a luminosity of 30 fb^{-1}. In the case of the MSSM we also discuss the complementarity between the 3b channel and the inclusive tau pair channel in exploring the supersymmetric parameter space.Comment: 14 pages, 3 figures, 4 tables, references added, published versio

Can computational efficiency alone drive the evolution of modularity in neural networks?

Some biologists have abandoned the idea that computational efficiency in processing multipart tasks or input sets alone drives the evolution of modularity in biological networks. A recent study confirmed that small modular (neural) networks are relatively computationally-inefficient but large modular networks are slightly more efficient than non-modular ones. The present study determines whether these efficiency advantages with network size can drive the evolution of modularity in networks whose connective architecture can evolve. The answer is no, but the reason why is interesting. All simulations (run in a wide variety of parameter states) involving gradualistic connective evolution end in non-modular local attractors. Thus while a high performance modular attractor exists, such regions cannot be reached by gradualistic evolution. Non-gradualistic evolutionary simulations in which multi-modularity is obtained through duplication of existing architecture appear viable. Fundamentally, this study indicates that computational efficiency alone does not drive the evolution of modularity, even in large biological networks, but it may still be a viable mechanism when networks evolve by non-gradualistic means

Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science

Abstract Background Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts. Methods We used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts. Results The CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct. Conclusion The CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.http://deepblue.lib.umich.edu/bitstream/2027.42/78272/1/1748-5908-4-50.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/2/1748-5908-4-50-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/3/1748-5908-4-50-S3.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/4/1748-5908-4-50-S4.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/5/1748-5908-4-50.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/6/1748-5908-4-50-S2.PDFPeer Reviewe