981 research outputs found

    Optimal Control of Isometric Muscle Dynamics

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    We use an indirect optimal control approach to calculate the optimal neural stimulation needed to obtain measured isometric muscle forces. The neural stimulation of the nerve system is hereby considered to be a control function (input) of the system 'muscle' that solely determines the muscle force (output). We use a well-established muscle  model and experimental data of isometric contractions. The model consists of coupled activation and contraction dynamics described by ordinary differential equations. To validate our results, we perform a comparison with commercial optimal control software

    The COVID-19 outbreak in Germany â Models and Parameter Estimation

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    Since the end of 2019 an outbreak of a new strain of coronavirus, called SARS–CoV–2, is reported from China and later also from other parts of the world. Since 21 January 2020, World Health Organization (WHO) reports daily data on confirmed cases and deaths from both China and other countries [1]. The Johns Hopkins University [2] collects those data from various sources worldwide on a daily basis. For Germany, the Robert–Koch–Institute (RKI) also issues daily reports on the current number of infections and infection related fatal cases and also provides estimates of several disease-related parameters [3]. In this work we present an extended SEIRD–model to describe these disease dynamics in Germany. The model takes into account the susceptible, exposed, infected, recovered and deceased fractions of the population. Epidemiological parameters like the transmission rate, lethality or the detection rate of infected individuals are estimated by fitting the model output to available data. For the parameter estimation itself we compare two methods: an adjoint based approach and a Monte–Carlo based Metropolis algorithm

    Therapeutic limitations in tumor-specific CD8+ memory T cell engraftment

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    BACKGROUND: Adoptive immunotherapy with cytotoxic T lymphocytes (CTL) represents an alternative approach to treating solid tumors. Ideally, this would confer long-term protection against tumor. We previously demonstrated that in vitro-generated tumor-specific CTL from the ovalbumin (OVA)-specific OT-I T cell receptor transgenic mouse persisted long after adoptive transfer as memory T cells. When recipient mice were challenged with the OVA-expressing E.G7 thymoma, tumor growth was delayed and sometimes prevented. The reasons for therapeutic failures were not clear. METHODS: OT-I CTL were adoptively transferred to C57BL/6 mice 21 – 28 days prior to tumor challenge. At this time, the donor cells had the phenotypical and functional characteristics of memory CD8+ T cells. Recipients which developed tumor despite adoptive immunotherapy were analyzed to evaluate the reason(s) for therapeutic failure. RESULTS: Dose-response studies demonstrated that the degree of tumor protection was directly proportional to the number of OT-I CTL adoptively transferred. At a low dose of OT-I CTL, therapeutic failure was attributed to insufficient numbers of OT-I T cells that persisted in vivo, rather than mechanisms that actively suppressed or anergized the OT-I T cells. In recipients of high numbers of OT-I CTL, the E.G7 tumor that developed was shown to be resistant to fresh OT-I CTL when examined ex vivo. Furthermore, these same tumor cells no longer secreted a detectable level of OVA. In this case, resistance to immunotherapy was secondary to selection of clones of E.G7 that expressed a lower level of tumor antigen. CONCLUSIONS: Memory engraftment with tumor-specific CTL provides long-term protection against tumor. However, there are several limitations to this immunotherapeutic strategy, especially when targeting a single antigen. This study illustrates the importance of administering large numbers of effectors to engraft sufficiently efficacious immunologic memory. It also demonstrates the importance of targeting several antigens when developing vaccine strategies for cancer

    Ovine pedomics : the first study of the ovine foot 16S rRNA-based microbiome

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    We report the first study of the bacterial microbiome of ovine interdigital skin based on 16S rRNA by pyrosequencing and conventional cloning with Sanger-sequencing. Three flocks were selected, one a flock with no signs of footrot or interdigital dermatitis, a second flock with interdigital dermatitis alone and a third flock with both interdigital dermatitis and footrot. The sheep were classified as having either healthy interdigital skin (H), interdigital dermatitis (ID) or virulent footrot (VFR). The ovine interdigital skin bacterial community varied significantly by flock and clinical condition. The diversity and richness of operational taxonomic units was greater in tissue from sheep with ID than H or VFR affected sheep. Actinobacteria, Bacteriodetes, Firmicutes and Proteobacteria were the most abundant phyla comprising 25 genera. Peptostreptococcus, Corynebacterium and Staphylococcus were associated with H, ID and VFR respectively. Sequences of Dichelobacter nodosus, the causal agent of ovine footrot, were not amplified due to mismatches in the 16S rRNA universal forward primer (27F). A specific real time PCR assay was used to demonstrate the presence of D. nodosus which was detected in all samples including the flock with no signs of ID or VFR. Sheep with ID had significantly higher numbers of D. nodosus (104-109 cells/g tissue) than those with H or VFR feet

    The influence of ultramafic rocks on microbial communities at the Logatchev Hydrothermal field, located 15°N on the Mid-Atlantic Ridge

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    The ultramafic-hosted Logatchev hydrothermal field (LHF) on the Mid-Atlantic Ridge is characterized by high hydrogen and methane contents in the subseafloor, which support a specialized microbial community of phylogenetically diverse, hydrogen-oxidizing chemolithoautotrophs. We compared the prokaryotic communities of three sites located in the LHF and encountered a predominance of archaeal sequences affiliated with methanogenic Methanococcales at all three. However, the bacterial composition varied in accordance with differences in fluid chemistry between the three sites investigated. An increase in hydrogen seemed to coincide with the diversification of hydrogen-oxidizing bacteria. This might indicate that the host rock indirectly selects this specific group of bacteria. However, next to hydrogen availability further factors are evident (e.g. mixing of hot reduced hydrothermal fluids with cold oxygenated seawater), which have a significant impact on the distribution of microorganism

    Bacterial diversity in snow on North Pole ice floes

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    The microbial abundance and diversity in snow on ice floes at three sites near the North Pole was assessed using quantitative PCR and 454 pyrosequencing. Abundance of 16S rRNA genes in the samples ranged between 43 and 248 gene copies per millilitre of melted snow. A total of 291,331 sequences were obtained through 454 pyrosequencing of 16S rRNA genes, resulting in 984 OTUs at 97 % identity. Two sites were dominated by Cyanobacteria (72 and 61 %, respectively), including chloroplasts. The third site differed by consisting of 95 % Proteobacteria. Principal component analysis showed that the three sites clustered together when compared to the underlying environments of sea ice and ocean water. The Shannon indices ranged from 2.226 to 3.758, and the Chao1 indices showed species richness between 293 and 353 for the three samples. The relatively low abundances and diversity found in the samples indicate a lower rate of microbial input to this snow habitat compared to snow in the proximity of terrestrial and anthropogenic sources of microorganisms. The differences in species composition and diversity between the sites show that apparently similar snow habitats contain a large variation in biodiversity, although the differences were smaller than the differences to the underlying environment. The results support the idea that a globally distributed community exists in snow and that the global snow community can in part be attributed to microbial input from the atmosphere. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00792-014-0660-y) contains supplementary material, which is available to authorized users

    Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

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    The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

    Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

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    The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration
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