629 research outputs found

    Optimizing information flow in small genetic networks. II: Feed forward interactions

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    Central to the functioning of a living cell is its ability to control the readout or expression of information encoded in the genome. In many cases, a single transcription factor protein activates or represses the expression of many genes. As the concentration of the transcription factor varies, the target genes thus undergo correlated changes, and this redundancy limits the ability of the cell to transmit information about input signals. We explore how interactions among the target genes can reduce this redundancy and optimize information transmission. Our discussion builds on recent work [Tkacik et al, Phys Rev E 80, 031920 (2009)], and there are connections to much earlier work on the role of lateral inhibition in enhancing the efficiency of information transmission in neural circuits; for simplicity we consider here the case where the interactions have a feed forward structure, with no loops. Even with this limitation, the networks that optimize information transmission have a structure reminiscent of the networks found in real biological systems

    Radio Frequency Identification (RFID) Technology at Dell Computer Corporation

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    Radio Frequency Identification (RFID) is a technology that has been in use since the 1940’s; however, practical business applications are more recently being developed. Dell Computers looked at their Xiamen, China manufacturing facility to see if RFID technology could result in improved efficiencies with quick payoff. The resulting scorecard showed areas within their facility that RFID technology could improve

    Information capacity of genetic regulatory elements

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    Changes in a cell's external or internal conditions are usually reflected in the concentrations of the relevant transcription factors. These proteins in turn modulate the expression levels of the genes under their control and sometimes need to perform non-trivial computations that integrate several inputs and affect multiple genes. At the same time, the activities of the regulated genes would fluctuate even if the inputs were held fixed, as a consequence of the intrinsic noise in the system, and such noise must fundamentally limit the reliability of any genetic computation. Here we use information theory to formalize the notion of information transmission in simple genetic regulatory elements in the presence of physically realistic noise sources. The dependence of this "channel capacity" on noise parameters, cooperativity and cost of making signaling molecules is explored systematically. We find that, at least in principle, capacities higher than one bit should be achievable and that consequently genetic regulation is not limited the use of binary, or "on-off", components.Comment: 17 pages, 9 figure

    Optimizing information flow in small genetic networks. I

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    In order to survive, reproduce and (in multicellular organisms) differentiate, cells must control the concentrations of the myriad different proteins that are encoded in the genome. The precision of this control is limited by the inevitable randomness of individual molecular events. Here we explore how cells can maximize their control power in the presence of these physical limits; formally, we solve the theoretical problem of maximizing the information transferred from inputs to outputs when the number of available molecules is held fixed. We start with the simplest version of the problem, in which a single transcription factor protein controls the readout of one or more genes by binding to DNA. We further simplify by assuming that this regulatory network operates in steady state, that the noise is small relative to the available dynamic range, and that the target genes do not interact. Even in this simple limit, we find a surprisingly rich set of optimal solutions. Importantly, for each locally optimal regulatory network, all parameters are determined once the physical constraints on the number of available molecules are specified. Although we are solving an over--simplified version of the problem facing real cells, we see parallels between the structure of these optimal solutions and the behavior of actual genetic regulatory networks. Subsequent papers will discuss more complete versions of the problem

    Thermodynamics of natural images

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    The scale invariance of natural images suggests an analogy to the statistical mechanics of physical systems at a critical point. Here we examine the distribution of pixels in small image patches and show how to construct the corresponding thermodynamics. We find evidence for criticality in a diverging specific heat, which corresponds to large fluctuations in how "surprising" we find individual images, and in the quantitative form of the entropy vs. energy. The energy landscape derived from our thermodynamic framework identifies special image configurations that have intrinsic error correcting properties, and neurons which could detect these features have a strong resemblance to the cells found in primary visual cortex

    International insights into how can we improve children’s emotional wellbeing over primary-secondary school transitions?

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    The transition from primary to secondary school provides children with opportunities and challenges that can impact their emotional experiences. Recognising that to date there is limited research which focuses on children's emotional experiences of primary-secondary school transition, a group of transitions researchers participated in a symposium at the British Psychological Society Psychology of Education Section Conference 2022, addressing this important topic. The purpose of the symposium was to bring together four international studies, which used different research designs to examine children’s emotional well-being over primary-secondary school transition. Through these talks and discussions which occurred during the symposium, current thinking, developments, and practice in this area, in addition to considering some of the challenges and opportunities present within primary-secondary school transitions research, are explored in order to better understand and support children’s emotional wellbeing over primary-secondary school transitions

    Entropy and information in neural spike trains: Progress on the sampling problem

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    The major problem in information theoretic analysis of neural responses and other biological data is the reliable estimation of entropy--like quantities from small samples. We apply a recently introduced Bayesian entropy estimator to synthetic data inspired by experiments, and to real experimental spike trains. The estimator performs admirably even very deep in the undersampled regime, where other techniques fail. This opens new possibilities for the information theoretic analysis of experiments, and may be of general interest as an example of learning from limited data.Comment: 7 pages, 4 figures; referee suggested changes, accepted versio

    Characteristics of patients with chronic back pain who benefit from acupuncture

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    <p>Abstract</p> <p>Background</p> <p>Although many clinicians believe there are clinically important subgroups of persons with "non-specific" low back pain, such subgroups have not yet been clearly identified. As part of a large trial evaluating acupuncture for chronic low back pain, we sought to identify subgroups of participants that were particularly responsive to acupuncture.</p> <p>Methods</p> <p>We performed a secondary analysis of data for the 638 participants in our clinical trial comparing different types of acupuncture to usual care to identify baseline characteristics that predicted responses to individualized, standardized, or simulated acupuncture treatments. After identifying factors that predicted improvements in back-related function or symptoms, we determined if these factors were more likely to predict improvement for those receiving the acupuncture treatments than for those receiving usual care. This was accomplished by testing for an interaction between the prognostic factors and treatment group in four models: functional outcomes (measured by the Roland-Morris Disability Scale) at 8 and 52 weeks post-randomization and symptom outcomes (measured with a numerical rating scale) at 8 and 52 weeks.</p> <p>Results</p> <p>Overall, the strongest predictors of improvement in back function and symptoms were higher baseline levels of these measures, receipt of an acupuncture treatment, and non-use of narcotic analgesics. Benefit from acupuncture compared to usual care was greater with worse pre-treatment levels of back dysfunction (interaction p < 0.004 for the functional outcome, Roland Morris Disability Scale at 8 weeks). No other consistent interactions were observed.</p> <p>Conclusion</p> <p>This secondary analysis found little evidence for the existence of subgroups of patients with chronic back pain that would be especially likely to benefit from acupuncture. However, persons with chronic low back pain who had more severe baseline dysfunction had the most short-term benefit from acupuncture.</p
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