163 research outputs found
Symbiotic Epistemologies for Forward-Error Correction
Cyberneticists agree that autonomous configurations are an interesting new topic in the field of software engineering, and leading analysts concur. Given the current status of highly- available epistemologies, computational biologists famously desire the exploration of sensor networks. In order to accomplish this intent, we prove that I/O automata and agents [14] can synchronize to solve this quandary
A hidden Markov model for detecting confinement in single particle tracking trajectories
State-of-the-art single-particle tracking (SPT) techniques can generate long trajectories with high temporal and spatial resolution. This offers the possibility of mechanistically interpreting particle movements and behavior in membranes. To this end, a number of statistical techniques have been developed that partition SPT trajectories into states with distinct diffusion signatures, allowing a statistical analysis of diffusion state dynamics and switching behavior. Here, we develop a confinement model, within a hidden Markov framework, that switches between phases of free diffusion and confinement in a harmonic potential well. By using a Markov chain Monte Carlo algorithm to fit this model, automated partitioning of individual SPT trajectories into these two phases is achieved, which allows us to analyze confinement events. We demonstrate the utility of this algorithm on a previously published interferometric scattering microscopy data set, in which gold-nanoparticle-tagged ganglioside GM1 lipids were tracked in model membranes. We performed a comprehensive analysis of confinement events, demonstrating that there is heterogeneity in the lifetime, shape, and size of events, with confinement size and shape being highly conserved within trajectories. Our observations suggest that heterogeneity in confinement events is caused by both individual nanoparticle characteristics and the binding-site environment. The individual nanoparticle heterogeneity ultimately limits the ability of interferometric scattering microscopy to resolve molecule dynamics to the order of the tag size; homogeneous tags could potentially allow the resolution to be taken below this limit by deconvolution methods. In a wider context, the presented harmonic potential well confinement model has the potential to detect and characterize a wide variety of biological phenomena, such as hop diffusion, receptor clustering, and lipid rafts
Evidence for the intense exchange of MazG in marine cyanophages by horizontal gene transfer
Background: S-PM2 is a phage capable of infecting strains of unicellular cyanobacteria belonging to the genus Synechococcus. S-PM2, like other myoviruses infecting marine cyanobacteria, encodes a number of bacterial-like genes. Amongst these genes is one encoding a MazG homologue that is hypothesized to be involved in the adaption of the infected host for production of progeny phage.
Methodology/Principal Findings: This study focuses on establishing the occurrence of mazG homologues in other cyanophages isolated from different oceanic locations. Degenerate PCR primers were designed using the mazG gene of S-PM2. The mazG gene was found to be widely distributed and highly conserved among Synechococcus myoviruses and podoviruses from diverse oceanic provinces.
Conclusions/Significance: This study provides evidence of a globally connected cyanophage gene pool, the cyanophage mazG gene having a small effective population size indicative of rapid lateral gene transfer despite being present in a substantial fraction of cyanophage. The Prochlorococcus and Synechococcus phage mazG genes do not cluster with the host mazG gene, suggesting that their primary hosts are not the source of the mazG gene
Large Scale Optimization Problems for Central Energy Facilities with Distributed Energy Storage
On large campuses, energy facilities are used to serve the heating and cooling needs of all the buildings, while utilizing cost savings strategies to manage operational cost. Strategies range from shifting loads to participating in utility programs that offer payouts. Among available strategies are central plant optimization, electrical energy storage, participation in utility demand response programs, and manipulating the temperature setpoints in the campus buildings. However, simultaneously optimizing all of the central plant assets, temperature setpoints and participation in utility programs can be a daunting task even for a powerful computer if the desire is real time control. These strategies may be implemented separately across several optimization systems without a coordinating algorithm. Due to system interactions, decentralized control may be far from optimal and worse yet may try to use the same asset for different goals. In this work, a hierarchal optimization system has been created to coordinate the optimization of the central plant, the battery, participation in demand response programs, and temperature setpoints. In the hierarchal controller, the high level coordinator determines the load allocations across the campus or facility. The coordinator also determines the participation in utility incentive programs. It is shown that these incentive programs can be grouped into reservation programs and price adjustment programs. The second tier of control is split into 3 portions: control of the central energy facility, control of the battery system, and control of the temperature setpoints. The second tier is responsible for converting load allocations into central plant temperature setpoints and flows, battery charge and discharge setpoints, and temperature setpoints, which are delivered to the Building Automation System for execution. It is shown that the whole system can be coordinated by representing the second tier controllers with a smaller set of data that can be used by the coordinating controller. The central plant optimizer must supply an operational domain which constrains how each group of equipment can operate. The high level controller uses this information to send down loadings for each resource a group of equipment in the plant produces or consumes. For battery storage, the coordinating controller uses a simple integrator model of the battery and is responsible for providing a demand target and the amount of participation in any incentive programs. Finally, to perform temperature setpoint optimization a dynamic model of the zone is provided to the coordinating controller. This information is used to determine load allocations for groups of zones. The hierarchal control strategy is successful at optimizing the entire energy facility fast enough to allow the algorithms to control the energy facility, building setpoints, and program bids in real-time
Changes in gene expression in space and time orchestrate environmentally mediated shaping of root architecture
Shaping of root architecture is a quintessential developmental response that involves the concerted action of many different cell types, is highly dynamic and underpins root plasticity. To determine to what extent the environmental regulation of lateral root development is a product of cell type preferential activities, we tracked transcriptomic responses to two different treatments that both change root development in Arabidopsis thaliana, at an unprecedented level of temporal detail. We found that individual transcripts are expressed with a very high degree of temporal and spatial specificity, yet biological processes are commonly regulated, in a mechanism we term response nonredundancy. Using causative gene network inference to compare the genes regulated in different cell types and during responses to nitrogen and a biotic interaction we found that common transcriptional modules often regulate the same gene families, but control different individual members of these families, specific to response and cell type. This reinforces that the activity of a gene cannot be defined simply as molecular function; rather, it is a consequence of spatial location, expression timing and environmental responsiveness
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Hematopoietic Cell Transplantation in Patients With Primary Immune Regulatory Disorders (PIRD): A Primary Immune Deficiency Treatment Consortium (PIDTC) Survey.
Primary Immune Regulatory Disorders (PIRD) are an expanding group of diseases caused by gene defects in several different immune pathways, such as regulatory T cell function. Patients with PIRD develop clinical manifestations associated with diminished and exaggerated immune responses. Management of these patients is complicated; oftentimes immunosuppressive therapies are insufficient, and patients may require hematopoietic cell transplant (HCT) for treatment. Analysis of HCT data in PIRD patients have previously focused on a single gene defect. This study surveyed transplanted patients with a phenotypic clinical picture consistent with PIRD treated in 33 Primary Immune Deficiency Treatment Consortium centers and European centers. Our data showed that PIRD patients often had immunodeficient and autoimmune features affecting multiple organ systems. Transplantation resulted in resolution of disease manifestations in more than half of the patients with an overall 5-years survival of 67%. This study, the first to encompass disorders across the PIRD spectrum, highlights the need for further research in PIRD management
Advancing human health in the decade ahead: pregnancy as a key window for discovery: A Burroughs Wellcome Fund Pregnancy Think Tank.
Recent revolutionary advances at the intersection of medicine, omics, data sciences, computing, epidemiology, and related technologies inspire us to ponder their impact on health. Their potential impact is particularly germane to the biology of pregnancy and perinatal medicine, where limited improvement in health outcomes for women and children has remained a global challenge. We assembled a group of experts to establish a Pregnancy Think Tank to discuss a broad spectrum of major gestational disorders and adverse pregnancy outcomes that affect maternal-infant lifelong health and should serve as targets for leveraging the many recent advances. This report reflects avenues for future effects that hold great potential in 3 major areas: developmental genomics, including the application of methodologies designed to bridge genotypes, physiology, and diseases, addressing vexing questions in early human development; gestational physiology, from immune tolerance to growth and the timing of parturition; and personalized and population medicine, focusing on amalgamating health record data and deep phenotypes to create broad knowledge that can be integrated into healthcare systems and drive discovery to address pregnancy-related disease and promote general health. We propose a series of questions reflecting development, systems biology, diseases, clinical approaches and tools, and population health, and a call for scientific action. Clearly, transdisciplinary science must advance and accelerate to address adverse pregnancy outcomes. Disciplines not traditionally involved in the reproductive sciences, such as computer science, engineering, mathematics, and pharmacology, should be engaged at the study design phase to optimize the information gathered and to identify and further evaluate potentially actionable therapeutic targets. Information sources should include noninvasive personalized sensors and monitors, alongside instructive "liquid biopsies" for noninvasive pregnancy assessment. Future research should also address the diversity of human cohorts in terms of geography, racial and ethnic distributions, and social and health disparities. Modern technologies, for both data-gathering and data-analyzing, make this possible at a scale that was previously unachievable. Finally, the psychosocial and economic environment in which pregnancy takes place must be considered to promote the health and wellness of communities worldwide
Synchronous shedding of multiple bat paramyxoviruses coincides with peak periods of Hendra virus spillover
Within host-parasite communities, viral co-circulation and co-infections of hosts are the norm, yet studies of significant emerging zoonoses tend to focus on a single parasite species within the host. Using a multiplexed paramyxovirus bead-based PCR on urine samples from Australian flying foxes, we show that multi-viral shedding from flying fox populations is common. We detected up to nine bat paramyxoviruses shed synchronously. Multi-viral shedding infrequently coalesced into an extreme, brief and spatially restricted shedding pulse, coinciding with peak spillover of Hendra virus, an emerging fatal zoonotic pathogen of high interest. Such extreme pulses of multi-viral shedding could easily be missed during routine surveillance yet have potentially serious consequences for spillover of novel pathogens to humans and domestic animal hosts. We also detected co-occurrence patterns suggestive of the presence of interactions among viruses, such as facilitation and cross-immunity. We propose that multiple viruses may be interacting, influencing the shedding and spillover of zoonotic pathogens. Understanding these interactions in the context of broader scale drivers, such as habitat loss, may help predict shedding pulses of Hendra virus and other fatal zoonoses
One origin for metallo-β-lactamase activity, or two? An investigation assessing a diverse set of reconstructed ancestral sequences based on a sample of phylogenetic trees
This work was supported by BBSRC (grant BB/F016778/1)Bacteria use metallo-β-lactamase enzymes to hydrolyse lactam rings found in many antibiotics, rendering them ineffective. Metallo-β-lactamase activity is thought to be polyphyletic, having arisen on more than one occasion within a single functionally diverse homologous superfamily. Since discovery of multiple origins of enzymatic activity conferring antibiotic resistance has broad implications for the continued clinical use of antibiotics, we test the hypothesis of polyphyly further; if lactamase function has arisen twice independently, the most recent common ancestor (MRCA) is not expected to possess lactam-hydrolysing activity. Two major problems present themselves. Firstly, even with a perfectly known phylogeny, ancestral sequence reconstruction is error prone. Secondly, the phylogeny is not known, and in fact reconstructing a single, unambiguous phylogeny for the superfamily has proven impossible. To obtain a more statistical view of the strength of evidence for or against MRCA lactamase function, we reconstructed a sample of 98 MRCAs of the metallo-β-lactamases, each based on a different tree in a bootstrap sample of reconstructed phylogenies. InterPro sequence signatures and homology modelling were then used to assess our sample of MRCAs for lactamase functionality. Only 5 % of these models conform to our criteria for metallo-β-lactamase functionality, suggesting that the ancestor was unlikely to have been a metallo-β-lactamase. On the other hand, given that ancestral proteins may have had metallo-β-lactamase functionality with variation in sequence and structural properties compared with extant enzymes, our criteria are conservative, estimating a lower bound of evidence for metallo-β-lactamase functionality but not an upper bound.Publisher PDFPeer reviewe
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