407 research outputs found

    A developmental model of ocular dominance column formation on a growing cortex

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    We derive an activity-based developmental model of ocular dominance column formation in primary visual cortex that takes into account cortical growth. The resulting evolution equation for the densities of feedforward afferents from the two eyes exhibits a sequence of pattern forming instabilities as the size of the cortex increases. We use linear stability analysis to investigate the nature of the transitions between successive patterns in the sequence. We show that these transitions involve the splitting of existing ocular dominance (OD) columns, such that the mean width of an OD column is approximately preserved during the course of development. This is consistent with recent experimental observations of postnatal growth in cat

    Stability analysis of non-autonomous reaction-diffusion systems: the effects of growing domains

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    By using asymptotic theory, we generalise the Turing diffusively-driven instability conditions for reaction-diffusion systems with slow, isotropic domain growth. There are two fundamental biological differences between the Turing conditions on fixed and growing domains, namely: (i) we need not enforce cross nor pure kinetic conditions and (ii) the restriction to activator-inhibitor kinetics to induce pattern formation on a growing biological system is no longer a requirement. Our theoretical findings are confirmed and reinforced by numerical simulations for the special cases of isotropic linear, exponential and logistic growth profiles. In particular we illustrate an example of a reaction-diffusion system which cannot exhibit a diffusively-driven instability on a fixed domain but is unstable in the presence of slow growth

    Growing pains in children

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    We review the clinical manifestations of "growing pains", the most common form of episodic childhood musculoskeletal pain. Physicians should be careful to adhere to clear clinical criteria as described in this review before diagnosing a child with growing pain. We expand on current theories on possible causes of growing pains and describe the management of these pains and the generally good outcome in nearly all children

    The clock genes Period 2 and Cryptochrome 2 differentially balance bone formation

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    Background: Clock genes and their protein products regulate circadian rhythms in mammals but have also been implicated in various physiological processes, including bone formation. Osteoblasts build new mineralized bone whereas osteoclasts degrade it thereby balancing bone formation. To evaluate the contribution of clock components in this process, we investigated mice mutant in clock genes for a bone volume phenotype. Methodology/Principal Findings: We found that Per2Brdm1 mutant mice as well as mice lacking Cry2-/- displayed significantly increased bone volume at 12 weeks of age, when bone turnover is high. Per2Brdm1 mutant mice showed alterations in parameters specific for osteoblasts whereas mice lacking Cry2-/- displayed changes in osteoclast specific parameters. Interestingly, inactivation of both Per2 and Cry2 genes leads to normal bone volume as observed in wild type animals. Importantly, osteoclast parameters affected due to the lack of Cry2, remained at the level seen in the Cry2-/- mutants despite the simultaneous inactivation of Per2. Conclusions/Significance: This indicates that Cry2 and Per2 affect distinct pathways in the regulation of bone volume with Cry2 influencing mostly the osteoclastic cellular component of bone and Per2 acting on osteoblast parameters

    Pain and analgesic use associated with skeletal-related events in patients with advanced cancer and bone metastases

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    PURPOSE: Bone metastases secondary to solid tumors increase the risk of skeletal-related events (SREs), including the occurrence of pathological fracture (PF), radiation to bone (RB), surgery to bone (SB), and spinal cord compression (SCC). The aim of this study was to evaluate the impact of SREs on patients' pain, analgesic use, and pain interference with daily functioning. METHODS: Data were combined from patients with solid tumors and bone metastases who received denosumab or zoledronic acid across three identically designed phase 3 trials (N = 5543). Pain severity (worst pain) and pain interference were assessed using the Brief Pain Inventory at baseline and each monthly visit. Analgesic use was quantified using the Analgesic Quantification Algorithm. RESULTS: The proportion of patients with moderate/severe pain and strong opioid use generally increased in the 6 months preceding an SRE and remained elevated, while they remained relatively consistent over time in patients without an SRE. Regression analysis indicated that all SRE types were significantly associated with an increased risk of progression to moderate/severe pain and strong opioid use. PF, RB, and SCC were associated with significantly greater risk of pain interference overall. Results were similar for pain interference with emotional well-being. All SRE types were associated with significantly greater risk of pain interference with physical function. CONCLUSIONS: SREs are associated with increased pain and analgesic use in patients with bone metastases. Treatments that prevent SREs may decrease pain and the need for opioid analgesics and reduce the impact of pain on daily functioning

    Pain and analgesic use associated with skeletal-related events in patients with advanced cancer and bone metastases

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    PURPOSE: Bone metastases secondary to solid tumors increase the risk of skeletal-related events (SREs), including the occurrence of pathological fracture (PF), radiation to bone (RB), surgery to bone (SB), and spinal cord compression (SCC). The aim of this study was to evaluate the impact of SREs on patients' pain, analgesic use, and pain interference with daily functioning. METHODS: Data were combined from patients with solid tumors and bone metastases who received denosumab or zoledronic acid across three identically designed phase 3 trials (N = 5543). Pain severity (worst pain) and pain interference were assessed using the Brief Pain Inventory at baseline and each monthly visit. Analgesic use was quantified using the Analgesic Quantification Algorithm. RESULTS: The proportion of patients with moderate/severe pain and strong opioid use generally increased in the 6 months preceding an SRE and remained elevated, while they remained relatively consistent over time in patients without an SRE. Regression analysis indicated that all SRE types were significantly associated with an increased risk of progression to moderate/severe pain and strong opioid use. PF, RB, and SCC were associated with significantly greater risk of pain interference overall. Results were similar for pain interference with emotional well-being. All SRE types were associated with significantly greater risk of pain interference with physical function. CONCLUSIONS: SREs are associated with increased pain and analgesic use in patients with bone metastases. Treatments that prevent SREs may decrease pain and the need for opioid analgesics and reduce the impact of pain on daily functioning

    Quantifying trends in disease impact to produce a consistent and reproducible definition of an emerging infectious disease.

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    The proper allocation of public health resources for research and control requires quantification of both a disease's current burden and the trend in its impact. Infectious diseases that have been labeled as "emerging infectious diseases" (EIDs) have received heightened scientific and public attention and resources. However, the label 'emerging' is rarely backed by quantitative analysis and is often used subjectively. This can lead to over-allocation of resources to diseases that are incorrectly labelled "emerging," and insufficient allocation of resources to diseases for which evidence of an increasing or high sustained impact is strong. We suggest a simple quantitative approach, segmented regression, to characterize the trends and emergence of diseases. Segmented regression identifies one or more trends in a time series and determines the most statistically parsimonious split(s) (or joinpoints) in the time series. These joinpoints in the time series indicate time points when a change in trend occurred and may identify periods in which drivers of disease impact change. We illustrate the method by analyzing temporal patterns in incidence data for twelve diseases. This approach provides a way to classify a disease as currently emerging, re-emerging, receding, or stable based on temporal trends, as well as to pinpoint the time when the change in these trends happened. We argue that quantitative approaches to defining emergence based on the trend in impact of a disease can, with appropriate context, be used to prioritize resources for research and control. Implementing this more rigorous definition of an EID will require buy-in and enforcement from scientists, policy makers, peer reviewers and journal editors, but has the potential to improve resource allocation for global health

    In Situ Spatiotemporal Mapping of Flow Fields around Seeded Stem Cells at the Subcellular Length Scale

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    A major hurdle to understanding and exploiting interactions between the stem cell and its environment is the lack of a tool for precise delivery of mechanical cues concomitant to observing sub-cellular adaptation of structure. These studies demonstrate the use of microscale particle image velocimetry (μ-PIV) for in situ spatiotemporal mapping of flow fields around mesenchymal stem cells, i.e. murine embryonic multipotent cell line C3H10T1/2, at the subcellular length scale, providing a tool for real time observation and analysis of stem cell adaptation to the prevailing mechanical milieu. In the absence of cells, computational fluid dynamics (CFD) predicts flow regimes within 12% of μ-PIV measures, achieving the technical specifications of the chamber and the flow rates necessary to deliver target shear stresses at a particular height from the base of the flow chamber. However, our μ-PIV studies show that the presence of cells per se as well as the density at which cells are seeded significantly influences local flow fields. Furthermore, for any given cell or cell seeding density, flow regimes vary significantly along the vertical profile of the cell. Hence, the mechanical milieu of the stem cell exposed to shape changing shear stresses, induced by fluid drag, varies with respect to proximity of surrounding cells as well as with respect to apical height. The current study addresses a previously unmet need to predict and observe both flow regimes as well as mechanoadaptation of cells in flow chambers designed to deliver precisely controlled mechanical signals to live cells. An understanding of interactions and adaptation in response to forces at the interface between the surface of the cell and its immediate local environment may be key for de novo engineering of functional tissues from stem cell templates as well as for unraveling the mechanisms underlying multiscale development, growth and adaptation of organisms
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