| 1. |
- Andreasson, Jakob, et al.
(författare)
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Automated identification and classification of single particle serial femtosecond X-ray diffraction data
- 2014
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Ingår i: Optics Express. - 1094-4087. ; 22:3, s. 2497-2510
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Tidskriftsartikel (refereegranskat)abstract
- The first hard X-ray laser, the Linac Coherent Light Source (LCLS), produces 120 shots per second. Particles injected into the X-ray beam are hit randomly and in unknown orientations by the extremely intense X-ray pulses, where the femtosecond-duration X-ray pulses diffract from the sample before the particle structure is significantly changed even though the sample is ultimately destroyed by the deposited X-ray energy. Single particle X-ray diffraction experiments generate data at the FEL repetition rate, resulting in more than 400,000 detector readouts in an hour, the data stream during an experiment contains blank frames mixed with hits on single particles, clusters and contaminants. The diffraction signal is generally weak and it is superimposed on a low but continually fluctuating background signal, originating from photon noise in the beam line and electronic noise from the detector. Meanwhile, explosion of the sample creates fragments with a characteristic signature. Here, we describe methods based on rapid image analysis combined with ion Time-of-Flight (ToF) spectroscopy of the fragments to achieve an efficient, automated and unsupervised sorting of diffraction data. The studies described here form a basis for the development of real-time frame rejection methods, e. g. for the European XFEL, which is expected to produce 100 million pulses per hour. (C)2014 Optical Society of America
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| 2. |
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| 3. |
- Ayyer, Kartik, et al.
(författare)
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3D diffractive imaging of nanoparticle ensembles using an x-ray laser
- 2021
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Ingår i: Optica. - : Optical Society of America. - 2334-2536. ; 8:1, s. 15-23
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Tidskriftsartikel (refereegranskat)abstract
- Single particle imaging at x-ray free electron lasers (XFELs) has the potential to determine the structure and dynamics of single biomolecules at room temperature. Two major hurdles have prevented this potential from being reached, namely, the collection of sufficient high-quality diffraction patterns and robust computational purification to overcome structural heterogeneity. We report the breaking of both of these barriers using gold nanoparticle test samples, recording around 10 million diffraction patterns at the European XFEL and structurally and orientationally sorting the patterns to obtain better than 3-nm-resolution 3D reconstructions for each of four samples. With these new developments, integrating advancements in x-ray sources, fast-framing detectors, efficient sample delivery, and data analysis algorithms, we illuminate the path towards sub-nano meter biomolecular imaging. The methods developed here can also be extended to characterize ensembles that are inherently diverse to obtain their full structural landscape. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License.
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| 4. |
- Barty, A., et al.
(författare)
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Self-terminating diffraction gates femtosecond X-ray nanocrystallography measurements
- 2012
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Ingår i: Nature Photonics. - 1749-4885 .- 1749-4893. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- X-ray free-electron lasers have enabled new approaches to the structural determination of protein crystals that are too small or radiation-sensitive for conventional analysis1. For sufficiently short pulses, diffraction is collected before significant changes occur to the sample, and it has been predicted that pulses as short as 10 fs may be required to acquire atomic-resolution structural information1, 2, 3, 4. Here, we describe a mechanism unique to ultrafast, ultra-intense X-ray experiments that allows structural information to be collected from crystalline samples using high radiation doses without the requirement for the pulse to terminate before the onset of sample damage. Instead, the diffracted X-rays are gated by a rapid loss of crystalline periodicity, producing apparent pulse lengths significantly shorter than the duration of the incident pulse. The shortest apparent pulse lengths occur at the highest resolution, and our measurements indicate that current X-ray free-electron laser technology5 should enable structural determination from submicrometre protein crystals with atomic resolution.
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| 5. |
- Bellisario, Alfredo
(författare)
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Deep learning assisted phase retrieval and computational methods in coherent diffractive imaging
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, advances in Artificial Intelligence and experimental techniques have revolutionized the field of structural biology. X-ray crystallography and Cryo-EM have provided unprecedented insights into the structures of biomolecules, while the unexpected success of AlphaFold has opened up new avenues of investigation. However, studying the dynamics of proteins at high resolution remains a significant obstacle, especially for fast dynamics. Single-particle imaging (SPI) or Flash X-ray Imaging (FXI) is an emerging technique that may enable the mapping of the conformational landscape of biological molecules at high resolution and fast time scale. This thesis discusses the potential of SPI/FXI, its challenges, recent experimental successes, and the advancements driving its development. In particular, machine learning and neural networks could play a vital role in fostering data analysis and improving SPI/FXI data processing. In Paper I, we discuss the problem of noise and detector masks in collecting FXI data. I simulated a dataset of diffraction patterns and used it to train a Convolutional Neural Network (U-Net) to restore data by denoising and filling in detector masks. As a natural continuation of this work, I trained another machine learning model in Paper II to estimate 2D protein densities from diffraction intensities. In the final chapter, corresponding to Paper III, we discuss another experimental method, time-resolved Small Angle X-ray Scattering (SAXS), and a new algorithm recently developed for SAXS data, the DENsity from Solution Scattering (DENSS) algorithm. I discuss the potential of DENSS in time-resolved SAXS and its application for structural fitting of AsLOV2, a Light-Oxygen-Voltage (LOV) protein domain from Avena sativa.
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| 6. |
- Bellisario, Alfredo, et al.
(författare)
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Deep learning phase retrieval in X-ray single-particle imaging and object support from autocorrelations
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Phase retrieval is an important optimization problem that occurs, for example, in the analysis of coherent diffraction patterns from isolated proteins. All iterative algorithms employed for phase retrieval in this context require some a priori knowledge of the object, usually in the form of a support that describes the extent of the particle. Phase retrieval is a time-consuming task that can often fail, particularly if the support is too loose or of bad quality. In this paper, we present a neural network that can produce low-resolution estimates of the phased object in a fraction of the time that it takes for a full phase retrieval and that can also successfully be used as support for further analysis. Our network is trained on simulated data from biological macromolecules and is thus tailored to the type of data seen in a typical CDI experiment. Other approaches to support finding either require very accurate data without missing regions or require the full phase-retrieval algorithm to be run for a long time. Our network could both speed up off-line analysis, and provide real-time feedback during data collection.
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| 7. |
- Bellisario, Alfredo, et al.
(författare)
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Noise reduction and mask removal neural network for X-ray single-particle imaging
- 2022
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Ingår i: Journal of applied crystallography. - : International Union of Crystallography (IUCr). - 0021-8898 .- 1600-5767. ; 55, s. 122-132
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Tidskriftsartikel (refereegranskat)abstract
- Free-electron lasers could enable X-ray imaging of single biological macro-molecules and the study of protein dynamics, paving the way for a powerful new imaging tool in structural biology, but a low signal-to-noise ratio and missing regions in the detectors, colloquially termed 'masks', affect data collection and hamper real-time evaluation of experimental data. In this article, the challenges posed by noise and masks are tackled by introducing a neural network pipeline that aims to restore diffraction intensities. For training and testing of the model, a data set of diffraction patterns was simulated from 10 900 different proteins with molecular weights within the range of 10-100 kDa and collected at a photon energy of 8 keV. The method is compared with a simple low-pass filtering algorithm based on autocorrelation constraints. The results show an improvement in the mean-squared error of roughly two orders of magnitude in the presence of masks compared with the noisy data. The algorithm was also tested at increasing mask width, leading to the conclusion that demasking can achieve good results when the mask is smaller than half of the central speckle of the pattern. The results highlight the competitiveness of this model for data processing and the feasibility of restoring diffraction intensities from unknown structures in real time using deep learning methods. Finally, an example is shown of this preprocessing making orientation recovery more reliable, especially for data sets containing very few patterns, using the expansion-maximization-compression algorithm.
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| 8. |
- Daurer, Benedikt J.
(författare)
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Algorithms for Coherent Diffractive Imaging with X-ray Lasers
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Coherent diffractive imaging (CDI) has become a very popular technique over the past two decades. CDI is a "lensless" imaging method which replaces the objective lens of a conventional microscope by a computational image reconstruction procedure. Its increase in popularity came together with the development of X-ray free-electron lasers (XFELs) which produce extremely bright and coherent X-rays. By facilitating these unique properties, CDI enables structure determination of non-crystalline samples at nanometre resolution and has many applications in structural biology, material science and X-ray optics among others. This work focuses on two specific CDI techniques, flash X-ray diffractive imaging (FXI) on biological samples and X-ray ptychography.While the first FXI demonstrations using soft X-rays have been quite promising, they also revealed remaining technical challenges. FXI becomes even more demanding when approaching shorter wavelengths to allow subnanometre resolution imaging. We described one of the first FXI experiments using hard X-rays and characterized the most critical components of such an experiment, namely the properties of X-ray focus, sample delivery and detectors. Based on our findings, we discussed experimental and computational strategies for FXI to overcome its current difficulties and reach its full potential. We deposited the data in the Coherent X-ray Database (CXIDB) and made our data analysis code available in a public repository. We developed algorithms targeted towards the needs of FXI experiments and implemented a software package which enables the analysis of diffraction data in real time.X-ray ptychography has developed into a very useful tool for quantitative imaging of complex materials and has found applications in many areas. However, it involves a computational reconstruction step which can be slow. Therefore, we developed a fast GPU-based ptychographic solver and combined it with a framework for real-time data processing which already starts the ptychographic reconstruction process while data is still being collected. This provides immediate feedback to the user and allows high-throughput ptychographic imaging.Finally, we have used ptychographic imaging as a method to study the wavefront of a focused XFEL beam under typical FXI conditions. We are convinced that this work on developing strategies and algorithms for FXI and ptychography is a valuable contribution to the development of coherent diffractive imaging.
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| 9. |
- Daurer, Benedikt J., et al.
(författare)
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Experimental strategies for imaging bioparticles with femtosecond hard X-ray pulses
- 2017
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Ingår i: IUCrJ. - : INT UNION CRYSTALLOGRAPHY. - 2052-2525. ; 4, s. 251-262
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Tidskriftsartikel (refereegranskat)abstract
- This study explores the capabilities of the Coherent X-ray Imaging Instrument at the Linac Coherent Light Source to image small biological samples. The weak signal from small samples puts a significant demand on the experiment. Aerosolized Omono River virus particles of similar to 40 nm in diameter were injected into the submicrometre X-ray focus at a reduced pressure. Diffraction patterns were recorded on two area detectors. The statistical nature of the measurements from many individual particles provided information about the intensity profile of the X-ray beam, phase variations in the wavefront and the size distribution of the injected particles. The results point to a wider than expected size distribution (from similar to 35 to similar to 300 nm in diameter). This is likely to be owing to nonvolatile contaminants from larger droplets during aerosolization and droplet evaporation. The results suggest that the concentration of nonvolatile contaminants and the ratio between the volumes of the initial droplet and the sample particles is critical in such studies. The maximum beam intensity in the focus was found to be 1.9 * 10(12) photons per mu m(2) per pulse. The full-width of the focus at half-maximum was estimated to be 500 nm (assuming 20% beamline transmission), and this width is larger than expected. Under these conditions, the diffraction signal from a sample-sized particle remained above the average background to a resolution of 4.25 nm. The results suggest that reducing the size of the initial droplets during aerosolization is necessary to bring small particles into the scope of detailed structural studies with X-ray lasers.
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| 10. |
- Daurer, Benedikt J., et al.
(författare)
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Ptychographic wavefront characterization for single-particle imaging at x-ray lasers
- 2021
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Ingår i: Optica. - : Optical Society of America. - 2334-2536. ; 8:4, s. 551-562
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Tidskriftsartikel (refereegranskat)abstract
- A well-characterized wavefront is important for many x-ray free-electron laser (XFEL) experiments, especially for single-particle imaging (SPI), where individual biomolecules randomly sample a nanometer region of highly focused femtosecond pulses. We demonstrate high-resolution multiple-plane wavefront imaging of an ensemble of XFEL pulses, focused by Kirkpatrick–Baez mirrors, based on mixed-state ptychography, an approach letting us infer and reduce experimental sources of instability. From the recovered wavefront profiles, we show that while local photon fluence correction is crucial and possible for SPI, a small diversity of phase tilts likely has no impact. Our detailed characterization will aid interpretation of data from past and future SPI experiments and provides a basis for further improvements to experimental design and reconstruction algorithms.
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