1,121 research outputs found
Helicity at Photospheric and Chromospheric Heights
In the solar atmosphere the twist parameter has the same sign as
magnetic helicity. It has been observed using photospheric vector magnetograms
that negative/positive helicity is dominant in the northern/southern hemisphere
of the Sun. Chromospheric features show dextral/sinistral dominance in the
northern/southern hemisphere and sigmoids observed in X-rays also have a
dominant sense of reverse-S/forward-S in the northern/southern hemisphere. It
is of interest whether individual features have one-to-one correspondence in
terms of helicity at different atmospheric heights. We use UBF \Halpha images
from the Dunn Solar Telescope (DST) and other \Halpha data from Udaipur Solar
Observatory and Big Bear Solar Observatory. Near-simultaneous vector
magnetograms from the DST are used to establish one-to-one correspondence of
helicity at photospheric and chromospheric heights. We plan to extend this
investigation with more data including coronal intensities.Comment: 5 pages, 1 figure, 1 table To appear in "Magnetic Coupling between
the Interior and the Atmosphere of the Sun", eds. S.S. Hasan and R.J. Rutten,
Astrophysics and Space Science Proceedings, Springer-Verlag, Heidelberg,
Berlin, 200
Adaptive Filtering Enhances Information Transmission in Visual Cortex
Sensory neuroscience seeks to understand how the brain encodes natural
environments. However, neural coding has largely been studied using simplified
stimuli. In order to assess whether the brain's coding strategy depend on the
stimulus ensemble, we apply a new information-theoretic method that allows
unbiased calculation of neural filters (receptive fields) from responses to
natural scenes or other complex signals with strong multipoint correlations. In
the cat primary visual cortex we compare responses to natural inputs with those
to noise inputs matched for luminance and contrast. We find that neural filters
adaptively change with the input ensemble so as to increase the information
carried by the neural response about the filtered stimulus. Adaptation affects
the spatial frequency composition of the filter, enhancing sensitivity to
under-represented frequencies in agreement with optimal encoding arguments.
Adaptation occurs over 40 s to many minutes, longer than most previously
reported forms of adaptation.Comment: 20 pages, 11 figures, includes supplementary informatio
Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting
We present an analytical method to quantify clustering in super-resolution
localization images of static surfaces in two dimensions. The method also
describes how over-counting of labeled molecules contributes to apparent
self-clustering and how the effective lateral resolution of an image can be
determined. This treatment applies to clustering of proteins and lipids in
membranes, where there is significant interest in using super-resolution
localization techniques to probe membrane heterogeneity. When images are
quantified using pair correlation functions, the magnitude of apparent
clustering due to over-counting will vary inversely with the surface density of
labeled molecules and does not depend on the number of times an average
molecule is counted. Over-counting does not yield apparent co-clustering in
double label experiments when pair cross-correlation functions are measured. We
apply our analytical method to quantify the distribution of the IgE receptor
(Fc{\epsilon}RI) on the plasma membranes of chemically fixed RBL-2H3 mast cells
from images acquired using stochastic optical reconstruction microscopy (STORM)
and scanning electron microscopy (SEM). We find that apparent clustering of
labeled IgE bound to Fc{\epsilon}RI detected with both methods arises from
over-counting of individual complexes. Thus our results indicate that these
receptors are randomly distributed within the resolution and sensitivity limits
of these experiments.Comment: 22 pages, 5 figure
W2S: Microscopy Data with Joint Denoising and Super-Resolution for Widefield to SIM Mapping
In fluorescence microscopy live-cell imaging, there is a critical trade-off
between the signal-to-noise ratio and spatial resolution on one side, and the
integrity of the biological sample on the other side. To obtain clean
high-resolution (HR) images, one can either use microscopy techniques, such as
structured-illumination microscopy (SIM), or apply denoising and
super-resolution (SR) algorithms. However, the former option requires multiple
shots that can damage the samples, and although efficient deep learning based
algorithms exist for the latter option, no benchmark exists to evaluate these
algorithms on the joint denoising and SR (JDSR) tasks. To study JDSR on
microscopy data, we propose such a novel JDSR dataset, Widefield2SIM (W2S),
acquired using a conventional fluorescence widefield and SIM imaging. W2S
includes 144,000 real fluorescence microscopy images, resulting in a total of
360 sets of images. A set is comprised of noisy low-resolution (LR) widefield
images with different noise levels, a noise-free LR image, and a corresponding
high-quality HR SIM image. W2S allows us to benchmark the combinations of 6
denoising methods and 6 SR methods. We show that state-of-the-art SR networks
perform very poorly on noisy inputs. Our evaluation also reveals that applying
the best denoiser in terms of reconstruction error followed by the best SR
method does not necessarily yield the best final result. Both quantitative and
qualitative results show that SR networks are sensitive to noise and the
sequential application of denoising and SR algorithms is sub-optimal. Lastly,
we demonstrate that SR networks retrained end-to-end for JDSR outperform any
combination of state-of-the-art deep denoising and SR networksComment: ECCVW 2020. Project page: \<https://github.com/ivrl/w2s
Nanoscale glucan polymer network causes pathogen resistance.
Successful defence of plants against colonisation by fungal pathogens depends on the ability to prevent initial penetration of the plant cell wall. Here we report that the pathogen-induced (1,3)-β-glucan cell wall polymer callose, which is deposited at sites of attempted penetration, directly interacts with the most prominent cell wall polymer, the (1,4)-β-glucan cellulose, to form a three-dimensional network at sites of attempted fungal penetration. Localisation microscopy, a super-resolution microscopy technique based on the precise localisation of single fluorescent molecules, facilitated discrimination between single polymer fibrils in this network. Overexpression of the pathogen-induced callose synthase PMR4 in the model plant Arabidopsis thaliana not only enlarged focal callose deposition and polymer network formation but also resulted in the exposition of a callose layer on the surface of the pre-existing cellulosic cell wall facing the invading pathogen. The importance of this previously unknown polymeric defence network is to prevent cell wall hydrolysis and penetration by the fungus. We anticipate our study to promote nanoscale analysis of plant-microbe interactions with a special focus on polymer rearrangements in and at the cell wall. Moreover, the general applicability of localisation microscopy in visualising polymers beyond plant research will help elucidate their biological function in complex networks
Single Molecule Fluorescence Image Patterns Linked to Dipole Orientation and Axial Position: Application to Myosin Cross-Bridges in Muscle Fibers
Photoactivatable fluorescent probes developed specifically for single molecule detection extend advantages of single molecule imaging to high probe density regions of cells and tissues. They perform in the native biomolecule environment and have been used to detect both probe position and orientation.Fluorescence emission from a single photoactivated probe captured in an oil immersion, high numerical aperture objective, produces a spatial pattern on the detector that is a linear combination of 6 independent and distinct spatial basis patterns with weighting coefficients specifying emission dipole orientation. Basis patterns are tabulated for single photoactivated probes labeling myosin cross-bridges in a permeabilized muscle fiber undergoing total internal reflection illumination. Emitter proximity to the glass/aqueous interface at the coverslip implies the dipole near-field and dipole power normalization are significant affecters of the basis patterns. Other characteristics of the basis patterns are contributed by field polarization rotation with transmission through the microscope optics and refraction by the filter set. Pattern recognition utilized the generalized linear model, maximum likelihood fitting, for Poisson distributed uncertainties. This fitting method is more appropriate for treating low signal level photon counting data than χ(2) minimization.Results indicate that emission dipole orientation is measurable from the intensity image except for the ambiguity under dipole inversion. The advantage over an alternative method comparing two measured polarized emission intensities using an analyzing polarizer is that information in the intensity spatial distribution provides more constraints on fitted parameters and a single image provides all the information needed. Axial distance dependence in the emission pattern is also exploited to measure relative probe position near focus. Single molecule images from axial scanning fitted simultaneously boost orientation and axial resolution in simulation
Bright ligand-activatable fluorescent protein for high-quality multicolor live-cell super-resolution microscopy
We introduce UnaG as a green-to-dark photoswitching fluorescent protein capable of high-quality super-resolution imaging with photon numbers equivalent to the brightest photoswitchable red protein. UnaG only fluoresces upon binding of a fluorogenic metabolite, bilirubin, enabling UV-free reversible photoswitching with easily controllable kinetics and low background under Epi illumination. The on- and off-switching rates are controlled by the concentration of the ligand and the excitation light intensity, respectively, where the dissolved oxygen also promotes the off-switching. The photo-oxidation reaction mechanism of bilirubin in UnaG suggests that the lack of ligand-protein covalent bond allows the oxidized ligand to detach from the protein, emptying the binding cavity for rebinding to a fresh ligand molecule. We demonstrate super-resolution single-molecule localization imaging of various subcellular structures genetically encoded with UnaG, which enables facile labeling and simultaneous multicolor imaging of live cells. UnaG has the promise of becoming a default protein for high-performance super-resolution imaging. Photoconvertible proteins occupy two color channels thereby limiting multicolour localisation microscopy applications. Here the authors present UnaG, a new green-to-dark photoswitching fluorescent protein for super-resolution imaging, whose activation is based on a noncovalent binding with bilirubin
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How to transition to reduced-meat diets that benefit people and the planet
Initiation Grant of IIT Kanpur, India (project number 2018386); Wellcome Trust, Our Planet Our Health (Livestock, Environment and People - LEAP), award number 205212/Z/16/Z. L.E.R.; research program NE/N018125/1 LTS-M ASSIST -Achieving Sustainable Agricultural Systems, funded by NERC and BBSRC
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