Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation.

BACKGROUND: Successful management of gestational diabetes mellitus (GDM) reduces the risk of morbidity in women and newborns. A woman's blood glucose readings and risk factors are used by clinical staff to make decisions regarding the initiation of pharmacological treatment in women with GDM. Mobile health (mHealth) solutions allow the real-time follow-up of women with GDM and allow timely treatment and management. Machine learning offers the opportunity to quickly analyze large quantities of data to automatically flag women at risk of requiring pharmacological treatment. OBJECTIVE: The aim of this study is to assess whether data collected through an mHealth system can be analyzed to automatically evaluate the switch to pharmacological treatment from diet-based management of GDM. METHODS: We collected data from 3029 patients to design a machine learning model that can identify when a woman with GDM needs to switch to medications (insulin or metformin) by analyzing the data related to blood glucose and other risk factors. RESULTS: Through the analysis of 411,785 blood glucose readings, we designed a machine learning model that can predict the timing of initiation of pharmacological treatment. After 100 experimental repetitions, we obtained an average area under the receiver operating characteristic curve of 0.80 (SD 0.02) and an algorithm that allows the flexibility of setting the operating point rather than relying on a static heuristic method, which is currently used in clinical practice. CONCLUSIONS: Using real-time data collected via an mHealth system may further improve the timeliness of the intervention and potentially improve patient care. Further real-time clinical testing will enable the validation of our algorithm using real-world data.

Behavioural manipulation of insect hosts by Baculoviridae as a process of niche construction.

BACKGROUND: Niche construction has received increasing attention in recent years as a vital force in evolution and examples of niche construction have been identified in a wide variety of taxa, but viruses are conspicuously absent. In this study we explore how niche construction can lead to viruses engineering their hosts (including behavioural manipulation) with feedback on selective pressures for viral transmission and virulence. To illustrate this concept we focus on Baculoviridae, a family of invertebrate viruses that have evolved to modify the feeding behaviour of their lepidopteran hosts and liquefy their cadavers as part of the course of infection. RESULTS: We present a mathematical model showing how niche construction leads to feedback from the behavioural manipulation to the liquefaction of the host, linking the evolution of both of these traits, and show how this association arises from the action of niche construction. Model results show that niche construction is plausible in this system and delineates the conditions under which niche construction will occur. Niche construction in this system is also shown to be sensitive to parameter values that reflect ecological forces. CONCLUSIONS: Our model demonstrates that niche construction can be a potent force in viral evolution and can lead to the acquisition and maintenance of the behavioural manipulation and liquefaction traits in Baculoviridae via the niche constructing effects on the host. These results show the potential for niche construction theory to provide new insights into viral evolution.

The effects of linkage on comparative estimators of selection.

BACKGROUND: A major goal of molecular evolution is to determine how natural selection has shaped the evolution of a gene. One approach taken by methods such as KA/KS and the McDonald-Kreitman (MK) test is to compare the frequency of non-synonymous and synonymous changes. These methods, however, rely on the assumption that a change in frequency of one mutation will not affect changes in frequency of other mutations. RESULTS: We demonstrate that linkage between sites can bias measures of selection based on synonymous and non-synonymous changes. Using forward simulation of a Wright-Fisher process, we show that hitch-hiking of deleterious mutations with advantageous mutations can lead to overestimation of the number of adaptive substitutions, while background selection and clonal interference can distort the site frequency spectrum to obscure the signal for positive selection. We present three diagnostics for detecting these effects of linked selection and apply them to the human influenza (H3N2) hemagglutinin gene. CONCLUSION: Various forms of linked selection have characteristic effects on MK-type statistics. The extent of background selection, hitch-hiking and clonal interference can be evaluated using the diagnostic statistics presented here. The diagnostics can also be used to determine how well we expect the MK statistics to perform and whether one form of the statistic may be preferable to another.

Viral mutation rates: modelling the roles of within-host viral dynamics and the trade-off between replication fidelity and speed.

Many viruses, particularly RNA viruses, mutate at a very high rate per genome per replication. One possible explanation is that high mutation rates are selected to meet the challenge of fluctuating environments, including the host immune response. Alternatively, recent studies argue that viruses evolve under a trade-off between replication speed and fidelity such that fast replication is selected, and, along with it, high mutation rates. Here, in addition to these factors, we consider the role of viral life-history properties: namely, the within-host dynamics of viruses resulting from their interaction with the host. We develop mathematical models incorporating factors occurring within and between hosts, including deleterious and advantageous mutations, host death owing to virulence and clearance of viruses by the host. Beneficial mutations confer both a within-host and a transmission advantage. First, we find that advantageous mutations have only a weak effect on the optimal genomic mutation rate. Second, viral life-history properties have a large effect on the mutation rate. Third, when the speed-fidelity trade-off is included, there can be two locally optimal mutation rates. Our analysis provides a way to consider how life-history properties combine with biochemical trade-offs to shape mutation rates.

Discovery of 4-phenyl-2-phenylaminopyridine based TNIK inhibitors.

A series of compounds based on a 4-phenyl-2-phenylaminopyridine scaffold that are potent and selective inhibitors of Traf2- and Nck-interacting kinase (TNIK) activity are described. These compounds were used as tools to test the importance of TNIK kinase activity in signaling and proliferation in Wnt-activated colorectal cancer cells. The results indicate that pharmacological inhibition of TNIK kinase activity has minimal effects on either Wnt/TCF4/ß-catenin-driven transcription or viability. The findings suggest that the kinase activity of TNIK may be less important to Wnt signaling than other aspects of TNIK function, such as its putative role in stabilizing the TCF4/ß-catenin transcriptional complex.

When will evolution lead to deceptive signaling in the Sir Philip Sidney game?

Sir Philip Sidney games are a widely used model of simple signaling. Johnstone and Grafen [Johnstone, R.A., Grafen, A., 1993. Dishonesty and the handicap principle. Animal Behaviour 46, 759-764] present a version in which the Evolutionarily Stable Strategy (ESS) is for most signalers to "honestly" signal, with a small minority of signalers who "cheat". This model is among the most frequently cited papers on the topic of "dishonest" signaling and supports the view that signals may be "dishonest" as long as they are "honest on average". Using genetic algorithms, we demonstrate that another solution exists to the game, an evolutionarily stable set of Nash equilibria in which members of the set never signal and all donors give their resource. Payoffs to players using this set of strategies is greater those when playing the "dishonest" signaling ESS. We demonstrate that a random population is far more likely to evolve to this non-communicating strategy set than the "dishonest" signaling ESS. We also discuss the dynamics of biological game theory models and the advances of genetic algorithms as a heuristic solution method for these models.

Simulation-based Bayesian Analysis of Complex Data.

Our ability to collect large datasets is growing rapidly. Such richness of data offers great promise in terms of addressing detailed scientific questions in great depth. However, this benefit is not without scientific difficulty: many traditional analysis methods become computationally intractable for very large datasets. However, one can frequently still simulate data from scientific models for which direct calculation is no longer possible. In this paper we propose a Bayesian perspective for such analyses, and argue for the advantage of a simulation-based approximate Bayesian method that remains tractable when tractability of other methods is lost. This method, which is known as "approximate Bayesian computation" [ABC], has now been used in a variety of contexts, such as the analysis of tumor data (a tumor being a complex population of cells), and the analysis of human genetic variation data (which arise from a population of individual people). We review a number of ABC methods, with specific attention to the use of ABC in agent-based models, and give pointers to software that allows straightforward implementation of the ABC approach. In this way we demonstrate the utility of simulation-based analyses of large datasets within a rigorous statistical framework.

Taking the Operant Paradigm into the Field: Associative Learning in Wild Great Tits.

Associative learning is essential for resource acquisition, predator avoidance and reproduction in a wide diversity of species, and is therefore a key target for evolutionary and comparative cognition research. Automated operant devices can greatly enhance the study of associative learning and yet their use has been mainly restricted to laboratory conditions. We developed a portable, weatherproof, battery-operated operant device and conducted the first fully automated colour-associative learning experiment using free-ranging individuals in the wild. We used the device to run a colour discrimination task in a monitored population of tits (Paridae). Over two winter months, 80 individuals from four species recorded a total of 5,128 trials. Great tits (Parus major) were more likely than other species to visit the devices and engage in trials, but there were no sex or personality biases in the sample of great tits landing at the devices and registering key pecks. Juveniles were more likely than adults to visit the devices and to register trials. Individuals that were successful at solving a novel technical problem in captivity (lever-pulling) learned faster than non-solvers when at the operant devices in the wild, suggesting cross-contextual consistency in learning performance in very different tasks. There was no significant effect of personality or sex on learning rate, but juveniles' choice accuracy tended to improve at a faster rate than adults. We discuss how customisable automated operant devices, such as the one described here, could prove to be a powerful tool in evolutionary ecology studies of cognitive traits, especially among inquisitive species such as great tits.

Viral niche construction alters hosts and ecosystems at multiple scales.

The classical picture of viruses focuses on pathogenic viruses damaging the host's cells and physiology and host-pathogen immune coevolution. However, a broader picture of viruses is emerging that includes weakly pathogenic, commensal, or even mutualistic viruses and includes gross behavioural manipulations and viral effects on ecosystems. In this paper, we argue for niche construction as a unifying perspective on viral evolution. As obligate intracellular parasites, viruses are always modifying their environment, and these modifications drive evolutionary feedback between the virus and its environment across multiple scales from cells to ecosystems. We argue that niche construction will provide new insights into viral evolution, and that virology is a powerful source of empirical tests for niche construction.

The effect of exploration on the use of producer-scrounger tactics.

Individuals foraging in groups can use two different tactics for obtaining food resources. Individuals can either search for food sources themselves (producing) or they can join food discoveries of others (scrounging). In this study we use a genetic algorithm in a spatially explicit producer-scrounger game to explore how individuals compromise between exploration (an important axis of animal personality) and scrounging and how characteristics of the environment affect this compromise. Agents varied in exploration and scrounging and a genetic algorithm searched for the optimal combination of exploration and scrounging. The foraging environments featured different levels of patch richness, predation and patch density. Our simulations show that under conditions of low patch densities slow exploring scroungers were favored whereas high patch density favored fast exploring individuals that either produced (at low patch richness) or scrounged (at high patch richness). In high predation environments fast exploring individuals were selected for but only at low to intermediate patch densities. Predation did not affect scrounging behavior. We did not find a divergence of exploration 'types' within a given environment, but there was a general association between exploration and scrounging across different environments: high rates of scrounging were observed over nearly the full spectrum of exploration values, whereas high rates of producing were only observed at high exploration values, suggesting that cases in which slow explorers start producing should be rare. Our results indicate that the spatial arrangement of food resources can affect the optimal social attraction rules between agents, the optimality of foraging tactic and the interaction between both.

Cytokine production by peripheral blood mononuclear cells of women with a history of preterm birth.

Preterm birth is associated with elevated production of pro-inflammatory cytokines such as TNFalpha at the maternal-fetal interface. Previous studies have suggested that women with a history of preterm birth produce aberrantly strong inflammatory responses to bacterial lipopolysaccharide (LPS). However many intrauterine infections in women are associated with pathogens including Ureaplasma urealyticum, Mycoplasma hominis and Streptococcus agalactiae (group B streptococcus) that contain pro-inflammatory factors other than LPS. We evaluated whether peripheral blood leukocytes from women with a history of preterm birth produce elevated amounts of TNFalpha upon stimulation with pathogens associated with preterm birth and if pre-treatment with aspirin, an anti-inflammatory medication, decreases the ex vivo production of this cytokine. Heat-killed bacteria elicited increased TNFalpha production from leukocytes in a dose-dependent manner, but no differences in TNFalpha production between leukocytes from women with preterm birth and control women with term birth were detected. In women who consumed aspirin each day for one week, TNFalpha production was increased in leukocytes from control women stimulated with Escherichia coli and U. urealyticum, but was reduced or unchanged in leukocytes from women with preterm birth. Similar trends were observed for a subset of samples stimulated with U. urealyticum and assayed for IL-6, IL-10, IL-1beta and TNFalpha by bead array. We conclude that leukocytes from women with a history of preterm birth do not have elevated pro-inflammatory responses to pathogens, and that reproductive history is associated with different effects of aspirin on pro-inflammatory cytokine production.

Effect of aspirin treatment on TNFalpha production by women with a history of preterm birth.

Lipopolysaccharide (LPS)-stimulated TNFalpha production is reported to be greater for whole blood (WB) cultures prepared from patients with a history of preterm birth than cultures obtained from women with a history of term birth. The objectives of this study were (1) to determine if there is a similar differential responsiveness for peripheral blood mononuclear leukocytes (PBML) and (2) to determine if treatment with aspirin influences LPS-stimulated TNFalpha production in these patients. WB and PBML were obtained from women with a history of preterm delivery before 32 weeks (cases; n=5) and age- and race-matched controls (n=5) with a history of uncomplicated term delivery. WB and PBML were cultured and stimulated with LPS. All participants then took aspirin daily for 1 week and responsiveness of PBML and WB cultures to LPS was retested. The history of preterm labor was found to have no effect on LPS-stimulated TNFalpha production in cultures of WB or PBML. Aspirin treatment enhanced LPS-stimulated TNFalpha production by PBML from controls but not cases. We conclude that endotoxin responsiveness of women with a history of preterm birth is similar to that of women with a history of term birth in terms of in vitro TNFalpha production. Aspirin increases TNFalpha production by PBML in control women but not in women with a history of preterm birth. The divergent responses to aspirin treatment in patients with and without prior preterm labor may reflect differential regulation of cytokine production by prostaglandins in women with preterm labor associated with infection or inflammation.

The use of cDNA microarray to identify differentially expressed labor-associated genes within the human myometrium during labor.

OBJECTIVE: Microarray technology was used to comprehensively analyze gene expression during human labor in the myometrium. STUDY DESIGN: cDNA micro-array was used to compare the transcriptomes of myometrium obtained from patients in spontaneous labor and those not in labor. Expression of four labor-specific genes was confirmed in the myometrium obtained from patients in spontaneous labor using RT-PCR, Northern blot analysis, and in-situ hybridization. RESULTS: Of the >6000 cDNAs evaluated, 56 were found to be differentially expressed during labor. The labor-specific expression of 4 genes was confirmed using RT-PCR and Northern blot analysis. The relative increased expression of thrombospondin-1 in myometrium obtained from patients in spontaneous labor was also confirmed using in-situ hybridization. CONCLUSION: cDNA microarray was used to identify 56 differentially expressed genes in myometrium obtained from patients in spontaneous labor. The up-regulation of four genes was confirmed by multiple methods. Elucidation of the role(s) of the genes identified by microarray should improve our understanding of normal labor physiology and may ultimately lead to more effective treatments for abnormal labor.