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Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise
In transcriptional regulatory networks (TRNs), a canonical 3-node feed-forward loop (FFL) is hypothesized to evolve to filter out short spurious signals. We test this adaptive hypothesis against a novel null evolutionary model. Our mutational model captures the intrinsically high prevalence of weak affinity transcription factor binding sites. We also capture stochasticity and delays in gene expression that distort external signals and intrinsically generate noise. Functional FFLs evolve readily under selection for the hypothesized function but not in negative controls. Interestingly, a 4-node "diamond" motif also emerges as a short spurious signal filter. The diamond uses expression dynamics rather than path length to provide fast and slow pathways. When there is no idealized external spurious signal to filter out, but only internally generated noise, only the diamond and not the FFL evolves. While our results support the adaptive hypothesis, we also show that non-adaptive factors, including the intrinsic expression dynamics, matter.University of Arizona; Pew Scholarship; John Templeton Foundation [39667]; National Institutes of Health [R35GM118170, R01GM076041]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
Simulations of Oligomeric Intermediates in Prion Diseases
We extend our previous stochastic cellular automata based model for areal
aggregation of prion proteins on neuronal surfaces. The new anisotropic model
allow us to simulate both strong beta-sheet and weaker attachment bonds between
proteins. Constraining binding directions allows us to generate aggregate
structures with the hexagonal lattice symmetry found in recently observed in
vitro experiments. We argue that these constraints on rules may correspond to
underlying steric constraints on the aggregation process. We find that monomer
dominated growth of the areal aggregate is too slow to account for some
observed doubling time-to-incubation time ratios inferred from data, and so
consider aggregation dominated by relatively stable but non-infectious
oligomeric intermediates. We compare a kinetic theory analysis of oligomeric
aggregation to spatially explicit simulations of the process. We find that with
suitable rules for misfolding of oligomers, possibly due to water exclusion by
the surrounding aggregate, the resulting oligomeric aggregation model maps onto
our previous monomer aggregation model. Therefore it can produce some of the
same attractive features for the description of prion incubation time data. We
propose experiments to test the oligomeric aggregation model.Comment: 8 pages, 10 figures For larger versions of several figures, see
http://asaph.ucdavis.edu/~dmobley and click on the prion paper lin
Hsp90 depletion goes wild
Hsp90 reveals phenotypic variation in the laboratory, but is Hsp90 depletion important in the wild? Recent work from Chen and Wagner in BMC Evolutionary Biology has discovered a naturally occurring Drosophila allele that downregulates Hsp90, creating sensitivity to cryptic genetic variation. Laboratory studies suggest that the exact magnitude of Hsp90 downregulation is important. Extreme Hsp90 depletion might reactivate transposable elements and/or induce aneuploidy, in addition to revealing cryptic genetic variation
Complex Adaptations Can Drive the Evolution of the Capacitor [PSI+], Even with Realistic Rates of Yeast Sex
The [PSI+] prion may enhance evolvability by revealing previously cryptic genetic variation, but it is unclear whether such evolvability properties could be favored by natural selection. Sex inhibits the evolution of other putative evolvability mechanisms, such as mutator alleles. This paper explores whether sex also prevents natural selection from favoring modifier alleles that facilitate [PSI+] formation. Sex may permit the spread of “cheater” alleles that acquire the benefits of [PSI+] through mating without incurring the cost of producing [PSI+] at times when it is not adaptive. Using recent quantitative estimates of the frequency of sex in Saccharomyces paradoxus, we calculate that natural selection for evolvability can drive the evolution of the [PSI+] system, so long as yeast populations occasionally require complex adaptations involving synergistic epistasis between two loci. If adaptations are always simple and require substitution at only a single locus, then the [PSI+] system is not favored by natural selection. Obligate sex might inhibit the evolution of [PSI+]-like systems in other species
Assessment of the physical development and metabolic status of children born to women with gestational diabetes
Backgraund: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders found during pregnancy. Currently, it is relevant not only to search optimal target levels of glycemia during pregnancy, but also to study the effect of different glycemia levels on fetal development and further changes in glucose and lipid metabolism in children.Aims: To describe perinatal period, physical development and metabolic status of children born to women with GDM and different glucose levels during pregnancy.Materials and methods: The perinatal period features and anthropometric parameters at birth were evaluated in 300 children born to women with GDM and different levels of glycemia during pregnancy. Over the course two years, 141 children have been evaluated for physical development parameters and glucose and lipid metabolism. Fasting and postprandial glycemia was measured with glucometer for 14 days in 33 children aged 1 to 4 years.Results: The anthropometric parameters of children at birth did not differ from the parameters of the control group (p> 0.05) when during pregnancy fasting blood glucose was less than 5.1 mmol / l and 7.0 mmol / l 1 hour after a meal. The glycemia in women above this level was associated with an increase of frequency and risk of a body mass index, body mass / length ratio and head circumference “above average” in children at birth (p <0.05). With the dynamic control of anthropometric parameters up to 2 years, no differences between the comparison groups were obtained (p> 0.05). The change in metabolic parameters was represented by neonatal hypoglycemia in children of GDM group (GDM group — 23%, control group — 3.5%, p = 0.000002), the least risk of which occurred in group with the lowest fasting and postprandial glycemic values during pregnancy. Fasting glucose, and insulin levels, НOMA index, triglycerides and cholesterol, as well as monitoring fasting and postprandial glycemia for 14 days, were obtained no significant differences between the comparison groups of children (p> 0.05).Conclusions: The lowest risks of neonatal hypoglycemia and anthropometric deviations at birth were associated with the lowest glycemia levels during pregnancy, which correspond to the criteria of the Russian clinical guidelines
On the statistical mechanics of prion diseases
We simulate a two-dimensional, lattice based, protein-level statistical
mechanical model for prion diseases (e.g., Mad Cow disease) with concommitant
prion protein misfolding and aggregation. Our simulations lead us to the
hypothesis that the observed broad incubation time distribution in
epidemiological data reflect fluctuation dominated growth seeded by a few
nanometer scale aggregates, while much narrower incubation time distributions
for innoculated lab animals arise from statistical self averaging. We model
`species barriers' to prion infection and assess a related treatment protocol.Comment: 5 Pages, 3 eps figures (submitted to Physical Review Letters
The month of July: an early experience with pandemic influenza A (H1N1) in adults with cystic fibrosis
<p>Abstract</p> <p>Background</p> <p>Pandemic Influenza A (H1N1) 2009 is a novel viral infection that emerged in March 2009. This is the first report addressing the clinical course of patients with cystic fibrosis (CF) and H1N1 infection.</p> <p>Methods</p> <p>All patients with an influenza-like illness (ILI) attending our adult centre during July 2009 were identified. Baseline respiratory function, nutritional status, approach to management and short-term clinical course were recorded.</p> <p>Results</p> <p>Most patients experienced a mild course and were able to be managed with antiviral agents as an outpatient. Robust infection control policies were implemented to limit transmission of H1N1 infection within our CF centre. Patients with severe lung disease, poor baseline nutritional reserve and presenting with more than 48 hours of ILI experienced a more severe course. Prompt antiviral therapy within the first 48 hours of illness may have been important in improving outcomes.</p> <p>Conclusions</p> <p>This observational study demonstrates that most adults with CF with H1N1 infection had mild clinical courses and recovered rapidly.</p
Ab initio atomistic thermodynamics and statistical mechanics of surface properties and functions
Previous and present "academic" research aiming at atomic scale understanding
is mainly concerned with the study of individual molecular processes possibly
underlying materials science applications. Appealing properties of an
individual process are then frequently discussed in terms of their direct
importance for the envisioned material function, or reciprocally, the function
of materials is somehow believed to be understandable by essentially one
prominent elementary process only. What is often overlooked in this approach is
that in macroscopic systems of technological relevance typically a large number
of distinct atomic scale processes take place. Which of them are decisive for
observable system properties and functions is then not only determined by the
detailed individual properties of each process alone, but in many, if not most
cases also the interplay of all processes, i.e. how they act together, plays a
crucial role. For a "predictive materials science modeling with microscopic
understanding", a description that treats the statistical interplay of a large
number of microscopically well-described elementary processes must therefore be
applied. Modern electronic structure theory methods such as DFT have become a
standard tool for the accurate description of individual molecular processes.
Here, we discuss the present status of emerging methodologies which attempt to
achieve a (hopefully seamless) match of DFT with concepts from statistical
mechanics or thermodynamics, in order to also address the interplay of the
various molecular processes. The new quality of, and the novel insights that
can be gained by, such techniques is illustrated by how they allow the
description of crystal surfaces in contact with realistic gas-phase
environments.Comment: 24 pages including 17 figures, related publications can be found at
http://www.fhi-berlin.mpg.de/th/paper.htm
Investigating the conformational stability of prion strains through a kinetic replication model
Prion proteins are known to misfold into a range of different aggregated forms, showing different phenotypic and pathological states. Understanding strain specificities is an important problem in the field of prion disease. Little is known about which PrP(Sc) structural properties and molecular mechanisms determine prion replication, disease progression and strain phenotype. The aim of this work is to investigate, through a mathematical model, how the structural stability of different aggregated forms can influence the kinetics of prion replication. The model-based results suggest that prion strains with different conformational stability undergoing in vivo replication are characterizable in primis by means of different rates of breakage. A further role seems to be played by the aggregation rate (i.e. the rate at which a prion fibril grows). The kinetic variability introduced in the model by these two parameters allows us to reproduce the different characteristic features of the various strains (e.g., fibrils' mean length) and is coherent with all experimental observations concerning strain-specific behavior
Routine laboratory parameters to support decision on parenteral nutrition in palliative care
IntroductionParenteral nutrition (PN) is widely used in palliative care (PC), but there is limited evidence to support its use at the end of life (EOL). This aim of this was to investigate the relationship between routine laboratory parameters and survival in patients receiving PN, and to develop a decision tree model to support clinicians decide whether to start or forgo PN.MethodsThe laboratory parameters of 113 patients with advanced diseases who were admitted to a specialized palliative care unit (PCU) were analyzed at two points in time: T0 = before PN, T1 = two weeks after initiation of PN. Univariate Mann-Whitney U-tests and multivariate linear regression models, as well as a decision tree analysis were computed; all in relation to survival time.ResultsThe final regression model was significant with p = 0.001 (adjusted R2 = 0.15) and included two predictors for survival time after PN initiation: the CRP/albumin ratio and urea at T1 (ps = 0.019). Decision tree analysis revealed three important predictors for classification of survival time after PN initiation: CRP, urea, and LDH (all at T0).DiscussionThe decision tree model may help to identify patients likely to benefit from PN, thus supporting the clinical decision whether or not to start PN
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