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Heat stress transcription factors (HSFs) regulate transcriptional response to a large number of environmental influences, such as temperature fluctuations and chemical compound applications. Plant HSFs represent a large and diverse gene family. The HSF members vary substantially both in gene expression patterns and molecular functions. HEATSTER is a web resource for mining, annotating, and analyzing members of the different classes of HSFs in plants. A web-interface allows the identification and class assignment of HSFs, intuitive searches in the database and visualization of conserved motifs, and domains to classify novel HSFs.
Adjuvanted influenza vaccines constitute a key element towards inducing neutralizing antibody responses in populations with reduced responsiveness, such as infants and elderly subjects, as well as in devising antigen-sparing strategies. In particular, squalene-containing adjuvants have been observed to induce enhanced antibody responses, as well as having an influence on cross-reactive immunity. To explore the effects of adjuvanted vaccine formulations on antibody response and their relation to protein-specific immunity, we propose different mathematical models of antibody production dynamics in response to influenza vaccination. Data from ferrets immunized with commercial H1N1pdm09 vaccine antigen alone or formulated with different adjuvants was instrumental to adjust model parameters. While the affinity maturation process complexity is abridged, the proposed model is able to recapitulate the essential features of the observed dynamics. Our numerical results suggest that there exists a qualitative shift in protein-specific antibody response, with enhanced production of antibodies targeting the NA protein in adjuvanted versus non-adjuvanted formulations, in conjunction with a protein-independent boost that is over one order of magnitude larger for squalene-containing adjuvants. Furthermore, simulations predict that vaccines formulated with squalene-containing adjuvants are able to induce sustained antibody titers in a robust way, with little impact of the time interval between immunizations.
An overt pro-inflammatory immune response is a key factor contributing to lethal pneumococcal infection in an influenza pre-infected host and represents a potential target for therapeutic intervention. However, there is a paucity of knowledge about the level of contribution of individual cytokines. Based on the predictions of our previous mathematical modeling approach, the potential benefit of IFN-γ- and/or IL-6-specific antibody-mediated cytokine neutralization was explored in C57BL/6 mice infected with the influenza A/PR/8/34 strain, which were subsequently infected with the Streptococcus pneumoniae strain TIGR4 on day 7 post influenza. While single IL-6 neutralization had no effect on respiratory bacterial clearance, single IFN-γ neutralization enhanced local bacterial clearance in the lungs. Concomitant neutralization of IFN-γ and IL-6 significantly reduced the degree of pneumonia as well as bacteremia compared to the control group, indicating a positive effect for the host during secondary bacterial infection. The results of our model-driven experimental study reveal that the predicted therapeutic value of IFN-γ and IL-6 neutralization in secondary pneumococcal infection following influenza infection is tightly dependent on the experimental protocol while at the same time paving the way toward the development of effective immune therapies.
Multi-view microscopy techniques are used to increase the resolution along the optical axis for 3D imaging. Without this, the resolution is insufficient to resolve subcellular events. In addition, parts of the images of opaque specimens are often highly degraded or masked. Both problems motivate scientists to record the same specimen from multiple directions. The images, then have to be digitally fused into a single high-quality image. Selective-plane illumination microscopy has proven to be a powerful imaging technique due to its unsurpassed acquisition speed and gentle optical sectioning. However, even in the case of multi view imaging techniques that illuminate and image the sample from multiple directions, light scattering inside tissues often severely impairs image contrast.
Here we show that for c-elegans embryos multi view registration can be achieved based on segmented nuclei. However, segmentation of nuclei in high density distribution like c-elegans embryo is challenging. We propose a method which uses 3D Mexican hat filter for preprocessing and 3D Gaussian curvature for the post-processing step to separate nuclei. We used this method successfully on 3 data sets of c-elegans embryos in 3 different views. The result of segmentation outperforms previous methods. Moreover, we provide a simple GUI for manual correction and adjusting the parameters for different data.
We then proposed a method that combines point and voxel registration for an accurate multi view reg- istration of c-elegans embryo, which does not need any special experimental preparation. We demonstrate the performance of our approach on data acquired from fixed embryos of c-elegans worms. This multi step approach is successfully evaluated by comparison to different methods and also by using synthetic data. The proposed method could overcome the typically low resolution along the optical axis and enable stitching to- gether the different parts of the embryo available through the different views. A tool for running the code and analyzing the results is developed.
We calculate ratios of higher-order susceptibilities quantifying fluctuations in the number of net-protons and in the net-electric charge using the Hadron Resonance Gas (HRG) model. We take into account the effect of resonance decays, the kinematic acceptance cuts in rapidity, pseudo-rapidity and transverse momentum used in the experimental analysis, as well as a randomization of the isospin of nucleons in the hadronic phase. By comparing these results to the latest experimental data from the STAR Collaboration, we determine the freeze-out conditions from net-electric charge and net-proton distributions and discuss their consistency.
Following a brief review of current efforts to identify the neuronal correlates of conscious processing (NCCP) an attempt is made to bridge the gap between the material neuronal processes and the immaterial dimensions of subjective experience. It is argued that this "hard problem" of consciousness research cannot be solved by only considering the neuronal underpinnings of cognition. The proposal is that the hard problem can be treated within a naturalistic framework if one considers not only the biological but also the socio-cultural dimensions of evolution. The argument is based on the following premises: perceptions are the result of a constructivist process that depends on priors. This applies both for perceptions of the outer world and the perception of oneself. Social interactions between agents endowed with the cognitive abilities of humans generated immaterial realities, addressed as social or cultural realities. This novel class of realities assumed the role of priors for the perception of oneself and the embedding world. A natural consequence of these extended perceptions is a dualist classification of observables into material and immaterial phenomena nurturing the concept of ontological substance dualism. It is argued that perceptions shaped by socio-cultural priors lead to the construction of a self-model that has both a material and an immaterial dimension. As priors are implicit and not amenable to conscious recollection the perceived immaterial dimension is experienced as veridical and not derivable from material processes—which is the hallmark of the hard problem. These considerations let the hard problem appear as the result of cognitive constructs that are amenable to naturalistic explanations in an evolutionary framework.
PURPOSE: The purpose of this work is to analyze whether the Monte Carlo codes penh, fluka, and geant4/topas are suitable to calculate absorbed doses and fQ/fQ0 ratios in therapeutic high-energy photon and proton beams.
METHODS: We used penh, fluka, geant4/topas, and egsnrc to calculate the absorbed dose to water in a reference water cavity and the absorbed dose to air in two air cavities representative of a plane-parallel and a cylindrical ionization chamber in a 1.25 MeV photon beam and a 150 MeV proton beam - egsnrc was only used for the photon beam calculations. The physics and transport settings in each code were adjusted to simulate the particle transport as detailed as reasonably possible. From these absorbed doses, fQ0 factors, fQ factors, and fQ/fQ0 ratios (which are the basis of Monte Carlo calculated beam quality correction factors kQ,Q0 ) were calculated and compared between the codes. Additionally, we calculated the spectra of primary particles and secondary electrons in the reference water cavity, as well as the integrated depth-dose curve of 150 MeV protons in water.
RESULTS: The absorbed doses agreed within 1.4% or better between the individual codes for both the photon and proton simulations. The fQ0 and fQ factors agreed within 0.5% or better for the individual codes for both beam qualities. The resulting fQ/fQ0 ratios for 150 MeV protons agreed within 0.7% or better. For the 1.25 MeV photon beam, the spectra of photons and secondary electrons agreed almost perfectly. For the 150 MeV proton simulation, we observed differences in the spectra of secondary protons whereas the spectra of primary protons and low-energy delta electrons also agreed almost perfectly. The first 2 mm of the entrance channel of the 150 MeV proton Bragg curve agreed almost perfectly while for greater depths, the differences in the integrated dose were up to 1.5%.
CONCLUSION: penh, fluka, and geant4/topas are capable of calculating beam quality correction factors in proton beams. The differences in the fQ0 and fQ factors between the codes are 0.5% at maximum. The differences in the fQ/fQ0 ratios are 0.7% at maximum.
The differences between contemporary Monte Carlo generators of high energy hadronic interactions are discussed and their impact on the interpretation of experimental data on ultra-high energy cosmic rays (UHECRs) is studied. Key directions for further model improvements are outlined. The prospect for a coherent interpretation of the data in terms of the UHECR composition is investigated.
We present a model for the autonomous and simultaneous learning of active binocular and motion vision. The model is based on the Active Efficient Coding (AEC) framework, a recent generalization of classic efficient coding theories to active perception. The model learns how to efficiently encode the incoming visual signals generated by an object moving in 3-D through sparse coding. Simultaneously, it learns how to produce eye movements that further improve the efficiency of the sensory coding. This learning is driven by an intrinsic motivation to maximize the system's coding efficiency. We test our approach on the humanoid robot iCub using simulations. The model demonstrates self-calibration of accurate object fixation and tracking of moving objects. Our results show that the model keeps improving until it hits physical constraints such as camera or motor resolution, or limits on its internal coding capacity. Furthermore, we show that the emerging sensory tuning properties are in line with results on disparity, motion, and motion-in-depth tuning in the visual cortex of mammals. The model suggests that vergence and tracking eye movements can be viewed as fundamentally having the same objective of maximizing the coding efficiency of the visual system and that they can be learned and calibrated jointly through AEC.