Noise Management by Molecular Networks

Fluctuations in the copy number of key regulatory macromolecules (“noise”) may cause physiological heterogeneity in populations of (isogenic) cells. The kinetics of processes and their wiring in molecular networks can modulate this molecular noise. Here we present a theoretical framework to study the principles of noise management by the molecular networks in living cells. The theory makes use of the natural, hierarchical organization of those networks and makes their noise management more understandable in terms of network structure. Principles governing noise management by ultrasensitive systems, signaling cascades, gene networks and feedback circuitry are discovered using this approach. For a few frequently occurring network motifs we show how they manage noise. We derive simple and intuitive equations for noise in molecule copy numbers as a determinant of physiological heterogeneity. We show how noise levels and signal sensitivity can be set independently in molecular networks, but often changes in signal sensitivity affect noise propagation. Using theory and simulations, we show that negative feedback can both enhance and reduce noise. We identify a trade-off; noise reduction in one molecular intermediate by negative feedback is at the expense of increased noise in the levels of other molecules along the feedback loop. The reactants of the processes that are strongly (cooperatively) regulated, so as to allow for negative feedback with a high strength, will display enhanced noise

History, power, and electricity: American popular magazine accounts of electroconvulsive therapy, 1940–2005

Electroconvulsive therapy (ECT) is a psychiatric treatment that has been in use in the United States since the 1940s. During the whole of its existence, it has been extensively discussed and debated within American popular magazines. While initial reports of the treatment highlighted its benefits to patients, accounts by the 1970s and 1980s were increasingly polarized. This article analyzes the popular accounts over time, particularly the ways in which the debates over ECT have revolved around different interpretations of ECT's history and its power dynamics. © 2008Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57903/1/20283_ftp.pd

Physiological trade-offs associated with fasting weight loss, resistance to exercise and behavioral traits in farmed gilthead sea bream (Sparus aurata) selected by growth

Three gilthead sea bream families representative of slow, intermediate and fast heritable growth in the Spanish PROGENSA (R) selection program were used to uncover the effects of such selection on energy partitioning through measurements of fasting weight loss, swimming performance and behavioral traits in one- and two-year-old fish. Firstly, selection for fast growth significantly increased fasting weight loss and decreased the hormonal ratio of circulating Igf-i/Gh in short-term fasting fish (17 days). This is indicative of a stronger negative energy balance that explains the reduced compensatory growth of fast-growing fish during the subsequent short-term refeeding period (7 days). Selection for fast growth also decreased the critical speed (Ucrit, 6-7 BL sxfffd; 1) at which fish become exhausted in a swim tunnel respirometer. The maximum metabolic rate (MMR), defined as the maximum rate of oxygen consumption during forced exercise, was almost equal in all fish families though the peak was achieved at a lowest speed in the fast-growing family. Since circulating levels of lactate were also slightly decreased in freeswimming fish of this family group, it appears likely that the relative energy contribution of anaerobic metabolism to physical activity was lowered in genetically fast-growing fish. Selection for heritable growth also altered activity behavior because slow-growing families displayed an anticipatory food response associated with more pronounced daily rhythms of physical activity. Also, respiratory frequency and body weight showed and opposite correlation in slow- and fast-growing free-swimming fish as part of the complex trade-offs of growth, behavior and energy metabolism. Altogether, these results indicate that selective breeding for fast growth might limit the anaerobic fitness that would help to cope with limited oxygen availability in a scenario of climate change.We acknowledge the support of Veronica de las Heras and the Animalarium Service of IATS (Felix Alvarez and Jose Ramon Mateo) for their support in fish rearing

The history of attention deficit hyperactivity disorder

The contemporary concept of attention deficit hyperactivity disorder (ADHD) as defined in the DSM-IV-TR (American Psychiatric Association 2000) is relatively new. Excessive hyperactive, inattentive, and impulsive children have been described in the literature since the nineteenth century. Some of the early depictions and etiological theories of hyperactivity were similar to current descriptions of ADHD. Detailed studies of the behavior of hyperactive children and increasing knowledge of brain function have changed the concepts of the fundamental behavioral and neuropathological deficits underlying the disorder. This article presents an overview of the conceptual history of modern-day ADHD

Adjusting Phenotypes by Noise Control

Genetically identical cells can show phenotypic variability. This is often caused by stochastic events that originate from randomness in biochemical processes involving in gene expression and other extrinsic cellular processes. From an engineering perspective, there have been efforts focused on theory and experiments to control noise levels by perturbing and replacing gene network components. However, systematic methods for noise control are lacking mainly due to the intractable mathematical structure of noise propagation through reaction networks. Here, we provide a numerical analysis method by quantifying the parametric sensitivity of noise characteristics at the level of the linear noise approximation. Our analysis is readily applicable to various types of noise control and to different types of system; for example, we can orthogonally control the mean and noise levels and can control system dynamics such as noisy oscillations. As an illustration we applied our method to HIV and yeast gene expression systems and metabolic networks. The oscillatory signal control was applied to p53 oscillations from DNA damage. Furthermore, we showed that the efficiency of orthogonal control can be enhanced by applying extrinsic noise and feedback. Our noise control analysis can be applied to any stochastic model belonging to continuous time Markovian systems such as biological and chemical reaction systems, and even computer and social networks. We anticipate the proposed analysis to be a useful tool for designing and controlling synthetic gene networks

The study of atmospheric ice-nucleating particles via microfluidically generated droplets

Ice-nucleating particles (INPs) play a significant role in the climate and hydrological cycle by triggering ice formation in supercooled clouds, thereby causing precipitation and affecting cloud lifetimes and their radiative properties. However, despite their importance, INP often comprise only 1 in 10³–10⁶ ambient particles, making it difficult to ascertain and predict their type, source, and concentration. The typical techniques for quantifying INP concentrations tend to be highly labour-intensive, suffer from poor time resolution, or are limited in sensitivity to low concentrations. Here, we present the application of microfluidic devices to the study of atmospheric INPs via the simple and rapid production of monodisperse droplets and their subsequent freezing on a cold stage. This device offers the potential for the testing of INP concentrations in aqueous samples with high sensitivity and high counting statistics. Various INPs were tested for validation of the platform, including mineral dust and biological species, with results compared to literature values. We also describe a methodology for sampling atmospheric aerosol in a manner that minimises sampling biases and which is compatible with the microfluidic device. We present results for INP concentrations in air sampled during two field campaigns: (1) from a rural location in the UK and (2) during the UK’s annual Bonfire Night festival. These initial results will provide a route for deployment of the microfluidic platform for the study and quantification of INPs in upcoming field campaigns around the globe, while providing a benchmark for future lab-on-a-chip-based INP studies

‘Writing Now’

This chapter considers the themes and forms that characterise women’s writing in the new millennium. Post-9/11, self-representation has become a particularly urgent task for Muslim writers such as Monica Ali and Leila Aboulela. A concern with refugees, asylum seekers, and modern forms of slavery becomes increasingly prominent, not only in fiction – for example, Fadia Faqir’s My Name is Salma (2007) and Monica Ali’s In the Kitchen (2009) – but also in the theatre: Kay Adshead’s The Bogus Woman (2000), Sonja Linden’s Crocodile Seeking Refuge (2005), Christine Bacon’s Rendition Monologues (2008), Rukhsana Ahmad and Oladipo Agboluaje’s Footprints in the Sand (2008), Natasha Walter's Motherland (2008), and Gbemisola Ikumelo’s Next Door (2010). The impact of global capitalism, consumerism, and branding are explored in novels such as Scarlett Thomas’ Popco (2004), Ali Smith’s Girl Meets Boy (2007), and Winterson’s The Stone Gods (2007). Ageing is another major theme. Long a pre-occupation of Doris Lessing, it features also in Liz Jensen’s War Crimes for the Home (2002) and Alison Fell’s Tricks of the Light (2003). Anxieties about climate change and environmental apocalypse are addressed through dystopia in Maggie Gee’s The Ice People (1998) and The Flood (2004), Jeanette Winterson’s The Stone Gods (2007), Sarah Hall’s The Carhullen Army (2007), and Liz Jensen’s The Rapture (2009). Following Suniti Namjoshi’s pioneeringly collaborative Building Babel (1996), the use of multimedia in Maya Chowdhry’s digital poetry, Kate Pullinger’s ‘networked’ wikinovel Flight Paths (2005-), and the ‘visual novel’ (an interactive fiction game), gives literature an entirely new shape

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations