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Gelation of protein condensates formed by liquid-liquid phase separation occurs in a wide range of biological contexts, from the assembly of biomaterials to the formation of fibrillar aggregates, and is therefore of interest for biomedical applications. Soluble-to-gel (sol-gel) transitions are controlled through macroscopic processes such as changes in temperature or buffer composition, resulting in bulk conversion of liquid droplets into microgels within minutes to hours. Using microscopy and mass spectrometry, we show that condensates of an engineered mini-spidroin (NT2repCT YF ) undergo a spontaneous sol-gel transition resulting in the loss of exchange of proteins between the soluble and the condensed phase. This feature enables us to specifically trap a silk-domain-tagged target protein in the spidroin microgels. Surprisingly, laser pulses trigger near-instant gelation. By loading the condensates with fluorescent dyes or drugs, we can control the wavelength at which gelation is triggered. Fluorescence microscopy reveals that laser-induced gelation significantly further increases the partitioning of the fluorescent molecules into the condensates. In summary, our findings demonstrate direct control of phase transitions in individual condensates, opening new avenues for functional and structural characterization.

This work investigates the performance of the electrospray aerosol generator at the European X-ray Free Electron Laser (EuXFEL). This generator is, together with an aerodynamic lens stack that transports the particles into the X-ray interaction vacuum chamber, the method of choice to deliver particles for single-particle coherent diffractive imaging (SPI) experiments at the EuXFEL. For these experiments to be successful, it is necessary to achieve high transmission of particles from solution into the vacuum interaction region. Particle transmission is highly dependent on efficient neutralization of the charged aerosol generated by the electrospray mechanism as well as the geometry in the vicinity of the Taylor cone. We report absolute particle transmission values for different neutralizers and geometries while keeping the conditions suitable for SPI experiments. Our findings reveal that a vacuum ultraviolet ionizer demonstrates a transmission efficiency approximately seven times greater than the soft X-ray ionizer used previously. Combined with an optimized orifice size on the counter electrode, we achieve >40% particle transmission from solution into the X-ray interaction region. These findings offer valuable insights for optimizing electrospray aerosol generator configurations and data rates for SPI experiments., (open access.)

Imaging the structure and observing the dynamics of isolated proteins using single-particle X-ray diffractive imaging (SPI) is one of the potential applications of X-ray free-electron lasers (XFELs). Currently, SPI experiments on isolated proteins are limited by three factors: low signal strength, limited data and high background from gas scattering. The last two factors are largely due to the shortcomings of the aerosol sample delivery methods in use. Here we present our modified electrospray ionization (ESI) source, which we dubbed helium-ESI (He-ESI). With it, we increased particle delivery into the interaction region by a factor of 10, for 26 nm-sized biological particles, and decreased the gas load in the interaction chamber corresponding to an 80% reduction in gas scattering when compared to the original ESI. These improvements have the potential to significantly increase the quality and quantity of SPI diffraction patterns in future experiments using He-ESI, resulting in higher-resolution structures., (© 2024. The Author(s).)

The idea of using ultrashort X-ray pulses to obtain images of single proteins frozen in time has fascinated and inspired many. It was one of the arguments for building X-ray free-electron lasers. According to theory, the extremely intense pulses provide sufficient signal to dispense with using crystals as an amplifier, and the ultrashort pulse duration permits capturing the diffraction data before the sample inevitably explodes. This was first demonstrated on biological samples a decade ago on the giant mimivirus. Since then, a large collaboration has been pushing the limit of the smallest sample that can be imaged. The ability to capture snapshots on the timescale of atomic vibrations, while keeping the sample at room temperature, may allow probing the entire conformational phase space of macromolecules. Here we show the first observation of an X-ray diffraction pattern from a single protein, that of Escherichia coli GroEL which at 14 nm in diameter is the smallest biological sample ever imaged by X-rays, and demonstrate that the concept of diffraction before destruction extends to single proteins. From the pattern, it is possible to determine the approximate orientation of the protein. Our experiment demonstrates the feasibility of ultrafast imaging of single proteins, opening the way to single-molecule time-resolved studies on the femtosecond timescale., (© 2024. The Author(s).)

X-ray free-electron lasers (XFELs) can probe chemical and biological reactions as they unfold with unprecedented spatial and temporal resolution. A principal challenge in this pursuit involves the delivery of samples to the X-ray interaction point in such a way that produces data of the highest possible quality and with maximal efficiency. This is hampered by intrinsic constraints posed by the light source and operation within a beamline environment. For liquid samples, the solution typically involves some form of high-speed liquid jet, capable of keeping up with the rate of X-ray pulses. However, conventional jets are not ideal because of radiation-induced explosions of the jet, as well as their cylindrical geometry combined with the X-ray pointing instability of many beamlines which causes the interaction volume to differ for every pulse. This complicates data analysis and contributes to measurement errors. An alternative geometry is a liquid sheet jet which, with its constant thickness over large areas, eliminates the problems related to X-ray pointing. Since liquid sheets can be made very thin, the radiation-induced explosion is reduced, boosting their stability. These are especially attractive for experiments which benefit from small interaction volumes such as fluctuation X-ray scattering and several types of spectroscopy. Although their use has increased for soft X-ray applications in recent years, there has not yet been wide-scale adoption at XFELs. Here, gas-accelerated liquid sheet jet sample injection is demonstrated at the European XFEL SPB/SFX nano focus beamline. Its performance relative to a conventional liquid jet is evaluated and superior performance across several key factors has been found. This includes a thickness profile ranging from hundreds of nanometres to 60 nm, a fourfold increase in background stability and favorable radiation-induced explosion dynamics at high repetition rates up to 1.13 MHz. Its minute thickness also suggests that ultrafast single-particle solution scattering is a possibility., (open access.)

Free-electron lasers could enable X-ray imaging of single biological macromolecules 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., (© Alfredo Bellisario et al. 2022.)

One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand-maximize-compress ( EMC ) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered., (© Yulong Zhuang et al. 2022.)

The advent of X-ray Free Electron Lasers (XFELs) has ushered in a transformative era in the field of structural biology, materials science, and ultrafast physics. These state-of-the-art facilities generate ultra-bright, femtosecond-long X-ray pulses, allowing researchers to delve into the structure and dynamics of molecular systems with unprecedented temporal and spatial resolutions. The unique properties of XFEL pulses have opened new avenues for scientific exploration that were previously considered unattainable. One of the most notable applications of XFELs is in structural biology. Traditional X-ray crystallography, while instrumental in determining the structures of countless biomolecules, often requires large, high-quality crystals and may not capture highly transient states of proteins. XFELs, with their ability to produce diffraction patterns from nanocrystals or even single particles, have provided solutions to these challenges. XFEL has expanded the toolbox of structural biologists by enabling structural determination approaches such as Single Particle Imaging (SPI) and Serial X-ray Crystallography (SFX). Despite their remarkable capabilities, the journey of XFELs is still in its nascent stages, with ongoing advancements aimed at improving their coherence, pulse duration, and wavelength tunability., (© 2024. The Author(s), under exclusive license to Springer Nature Switzerland AG.)

Single particle imaging at atomic resolution is perhaps one of the most desired goals for ultrafast X-ray science with X-ray free-electron lasers. Such a capability would create great opportunity within the biological sciences, as high-resolution structural information of biosamples that may not crystallize is essential for many research areas therein. In this paper, we report on a comprehensive computational study of diffraction image formation during single particle imaging of a macromolecule, containing over one hundred thousand non-hydrogen atoms. For this study, we use a dedicated simulation framework, SIMEX, available at the European XFEL facility. Our results demonstrate the full feasibility of computational single-particle imaging studies for biological samples of realistic size. This finding is important as it shows that the SIMEX platform can be used for simulations to inform relevant single-particle-imaging experiments and help to establish optimal parameters for these experiments. This will enable more focused and more efficient single-particle-imaging experiments at XFEL facilities, making the best use of the resource-intensive XFEL operation. [ABSTRACT FROM AUTHOR]

The Giardia lamblia virus (GLV) is a non-enveloped icosahedral dsRNA and endosymbiont virus that infects the zoonotic protozoan parasite Giardia duodenalis (syn. G. lamblia, G. intestinalis), which is a pathogen of mammals, including humans. Elucidating the transmission mechanism of GLV is crucial for gaining an in-depth understanding of the virulence of the virus in G. duodenalis. GLV belongs to the family Totiviridae, which infects yeast and protozoa intracellularly; however, it also transmits extracellularly, similar to the phylogenetically, distantly related toti-like viruses that infect multicellular hosts. The GLV capsid structure is extensively involved in the longstanding discussion concerning extracellular transmission in Totiviridae and toti-like viruses. Hence, this study constructed the first high-resolution comparative atomic models of two GLV strains, namely GLV-HP and GLV-CAT, which showed different intracellular localization and virulence phenotypes, using cryogenic electron microscopy single-particle analysis. The atomic models of the GLV capsids presented swapped C-terminal extensions, extra surface loops, and a lack of cap-snatching pockets, similar to those of toti-like viruses. However, their open pores and absence of the extra crown protein resemble those of other yeast and protozoan Totiviridae viruses, demonstrating the essential structures for extracellular cell-to-cell transmission. The structural comparison between GLV-HP and GLV-CAT indicates the first evidence of critical structural motifs for the transmission and virulence of GLV in G. duodenalis. Author summary: We determined the first atomic structure of a unique dsRNA virus known as the Giardia lamblia virus (GLV). The structure of GLV is important for two reasons. First, the GLV structure is the representative structure of a primitive group of viruses that infects unicellular parasites but has adapted an extracellular lifestyle. Hence, by comparing the structure of GLV with that of other dsRNA viruses, we could identify essential surface loop structures that have evolved to enable dsRNA viruses to infect their hosts extracellularly. Second, the GLV structure empowers us to formulate a strategy for engineering GLV, with a focus on its future therapeutic applications. G. duodenalis, a common zoonotic parasite, can infect both humans and domestic animals, often leading to severe diarrhea. Conventional anti-parasitic drugs are employed to treat G. duodenalis symptomatic infections; however, cases of refractories to these drugs are increasingly being reported. A new alternative approach gaining interest is virotherapy, which harnesses viruses that infect parasites to combat infections. An in-depth structural comparison between two GLV prototypes revealed significant structural mechanisms that potentially enhance the virulence of GLV for efficiently clearing Giardia parasites from infected patients. [ABSTRACT FROM AUTHOR]

This article explores the challenges and solutions in data reduction at the European XFEL facility, which produces X-ray pulses. The facility generates a large amount of data during experiments, which presents difficulties in storage and interpretation. The article outlines the data infrastructure and various techniques for data reduction, aiming to maximize scientific value while minimizing strain on the infrastructure. The facility has successfully implemented reduction methods to decrease data storage volume and has assessed the risks associated with data reduction. Data reduction is important for scientific research, benefiting users by improving decision-making and simplifying data analysis, as well as having environmental benefits. The article emphasizes the collaboration between facility experts and users to ensure effective data reduction strategies and excellent scientific results. [Extracted from the article]

The European X-ray Free Electron Laser is a research facility located close to Hamburg, offering X-ray pulses with ultra-high brilliance and femtosecond duration at megahertz repetition rates. The detection systems necessary to unlock the full scientific potential made possible by this machine poses considerable challenges both in terms of data volume and rate, as well as the interpretation of their recorded signal. To provide optimal data quality, expert and detector-specific knowledge not easily accessible to external facility users is essential, and its implementation must cope with the generated volumes. We therefore aim to perform these preparatory processing steps and offer users a dataset suitable for further analysis as the primary data product. This work describes the machinery and workflows providing this data to users in an automatic, configurable and reproducible manner, both online during the experiment, and offline for scientific analysis afterward on the way to publication. [ABSTRACT FROM AUTHOR]

Crystallographic analysis relies on the scattering of quanta from arrays of atoms that populate a repeating lattice. While large crystals built of lattices that appear ideal are sought after by crystallographers, imperfections are the norm for molecular crystals. Additionally, advanced X-ray and electron diffraction techniques, used for crystallography, have opened the possibility of interrogating micro- and nanoscale crystals, with edges only millions or even thousands of molecules long. These crystals exist in a size regime that approximates the lower bounds for traditional models of crystal nonuniformity and imperfection. Accordingly, data generated by diffraction from both X-rays and electrons show increased complexity and are more challenging to conventionally model. New approaches in serial crystallography and spatially resolved electron diffraction mapping are changing this paradigm by better accounting for variability within and between crystals. The intersection of these methods presents an opportunity for a more comprehensive understanding of the structure and properties of nanocrystalline materials. [ABSTRACT FROM AUTHOR]

The JUNGFRAU detector is a well-established hybrid pixel detector developed at the Paul Scherrer Institut (PSI) designed for free-electron laser (FEL) applications. JUNGFRAU features a charge-integrating dynamic gain switching architecture, with three different gain stages and 75 µ m pixel pitch. It is widely used at the European X-ray Free-Electron Laser (EuXFEL), a facility which produces high brilliance X-ray pulses at MHz repetition rate in the form of bursts repeating at 10 Hz. In nominal configuration, the detector utilizes only a single memory cell and supports data acquisition up to 2 kHz. This constrains the operation of the detector to a 10 Hz frame rate when combined with the pulsed train structure of the EuXFEL. When configured in so-called burst mode, the JUNGFRAU detector can acquire a series of images into sixteen memory cells at a maximum rate of around 150 kHz. This acquisition scheme is better suited for the time structure of the X-rays as well as the pump laser pulses at the EuXFEL. To ensure confidence in the use of the burst mode at EuXFEL, a wide range of measurements have been performed to characterize the detector, especially to validate the detector alibration procedures. In particular, by analyzing the detector response to varying photon intensity (so called 'intensity scan'), special attention was given to the characterization of the transitions between gain stages. The detector was operated in both dynamic gain switching and fixed gain modes. Results of these measurements indicate difficulties in the characterization of the detector dynamic gain switching response while operated in burst mode, while no major issues have been found with fixed gain operation. Based on this outcome, fixed gain operation mode with all the memory cells was used during two experiments at EuXFEL, namely in serial femtosecond protein crystallography and Kossel lines measurements. The positive outcome of these two experiments validates the good results previously obtained, and opens the possibility for a wider usage of the detector in burst operation mode, although compromises are needed on the dynamic range. [ABSTRACT FROM AUTHOR]

The noise caused by sample heterogeneity (including sample solvent) has been identified as one of the determinant factors for a successful X-ray single-particle imaging experiment. It influences both the radiation damage process that occurs during illumination as well as the scattering patterns captured by the detector. Here, we investigate the impact of water layer thickness and radiation damage on orientation recovery from diffraction patterns of the nitrogenase iron protein. Orientation recovery is a critical step for single-particle imaging. It enables to sort a set of diffraction patterns scattered by identical particles placed at unknown orientations and assemble them into a 3D reciprocal space volume. The recovery quality is characterized by a "disconcurrence" metric. Our results show that while a water layer mitigates protein damage, the noise generated by the scattering from it can introduce challenges for orientation recovery and is anticipated to cause problems in the phase retrieval process to extract the desired protein structure. Compared to these disadvantageous effects due to the thick water layer, the effects of radiation damage on the orientation recovery are relatively small. Therefore, minimizing the amount of residual sample solvent should be considered a crucial step in improving the fidelity and resolution of X-ray single-particle imaging experiments. [ABSTRACT FROM AUTHOR]

In the process of the development of structural biology, both the size and the complexity of the determined macromolecular structures have grown significantly. As a result, the range of application areas for the results of structural studies of biological macromolecules has expanded. Significant progress in the development of structural biology methods has been largely achieved through the use of synchrotron radiation. Modern sources of synchrotron radiation allow to conduct high-performance structural studies with high temporal and spatial resolution. Thus, modern techniques make it possible to obtain not only static structures, but also to study dynamic processes, which play a key role in understanding biological mechanisms. One of the key directions in the development of structural research is the drug design based on the structures of biomolecules. Synchrotron radiation offers insights into the three-dimensional time-resolved structure of individual viral proteins and their complexes at atomic resolution. The rapid and accurate determination of protein structures is crucial for understanding viral pathogenicity and designing targeted therapeutics. Through the application of experimental techniques, including X-ray crystallography and small-angle X-ray scattering (SAXS), it is possible to elucidate the structural details of SARS-CoV-2 virion containing 4 structural, 16 nonstructural proteins (nsp), and several accessory proteins. The most studied potential targets for vaccines and drugs are the structural spike (S) protein, which is responsible for entering the host cell, as well as nonstructural proteins essential for replication and transcription, such as main protease (Mpro), papain-like protease (PLpro), and RNA-dependent RNA polymerase (RdRp). This article provides a brief overview of structural analysis techniques, with focus on synchrotron radiation-based methods applied to the analysis of SARS-CoV-2 proteins. [ABSTRACT FROM AUTHOR]

Understanding the interaction of intense, femtosecond X-ray pulses with heavy atoms is crucial for gaining insights into the structure and dynamics of matter. One key aspect of nonlinear light–matter interaction was, so far, not studied systematically at free-electron lasers—its dependence on the photon energy. Here, we use resonant ion spectroscopy to map out the transient electronic structures occurring during the complex charge-up pathways of xenon. Massively hollow atoms featuring up to six simultaneous core holes determine the spectra at specific photon energies and charge states. We also illustrate how different X-ray pulse parameters, which are usually intertwined, can be partially disentangled. The extraction of resonance spectra is facilitated by the possibility of working with a constant number of photons per X-ray pulse at all photon energies and the fact that the ion yields become independent of the peak fluence beyond a saturation point. Our study lays the groundwork for spectroscopic investigations of transient atomic species in exotic, multiple-core-hole states that have not been explored previously. Intense light pulses can create nonlinear ionization processes in atoms and molecules. Here the authors study the photoionization of xenon atoms using intense free-electron laser pulses that can create extremely high charge states and produce hollow atoms, featuring up to six simultaneous core-holes. [ABSTRACT FROM AUTHOR]

The phase transition between water and ice is ubiquitous and one of the most important phenomena in nature. Here, we performed time-resolved x-ray scattering experiments capturing the melting and recrystallization dynamics of ice. The ultrafast heating of ice I is induced by an IR laser pulse and probed with an intense x-ray pulse which provided us with direct structural information on different length scales. From the wide-angle x-ray scattering (WAXS) patterns, the molten fraction, as well as the corresponding temperature at each delay, were determined. The small-angle x-ray scattering (SAXS) patterns, together with the information extracted from the WAXS analysis, provided the time-dependent change of the size and the number of liquid domains. The results show partial melting (~13%) and superheating of ice occurring at around 20 ns. After 100 ns, the average size of the liquid domains grows from about 2.5 nm to 4.5 nm by the coalescence of approximately six adjacent domains. Subsequently, we capture the recrystallization of the liquid domains, which occurs on microsecond timescales due to the cooling by heat dissipation and results to a decrease of the average liquid domain size. The phase transition between water and ice is a ubiquitous phenomenon in nature. Here, the authors conduct a time-resolved x-ray scattering experiment using X-ray Free Electron Lasers to elucidate a comprehensive picture of the melting and recrystallization dynamics of crystalline ice, based on direct structural information. [ABSTRACT FROM AUTHOR]

Rosellinia necatrix megabirnavirus 1-W779 (RnMBV1) is a non-enveloped icosahedral double-stranded (ds)RNA virus that infects the ascomycete fungus Rosellinia necatrix, a causative agent that induces a lethal plant disease white root rot. Herein, we have first resolved the atomic structure of the RnMBV1 capsid at 3.2 Å resolution using cryo-electron microscopy (cryo-EM) single-particle analysis. Compared with other non-enveloped icosahedral dsRNA viruses, the RnMBV1 capsid protein structure exhibits an extra-long C-terminal arm and a surface protrusion domain. In addition, the previously unrecognized crown proteins are identified in a symmetry-expanded cryo-EM model and are present over the 3-fold axes. These exclusive structural features of the RnMBV1 capsid could have been acquired for playing essential roles in transmission and/or particle assembly of the megabirnaviruses. Our findings, therefore, will reinforce the understanding of how the structural and molecular machineries of the megabirnaviruses influence the virulence of the disease-related ascomycete fungus. Author summary: A fungal plant soil-borne pathogen, Rosellinia necatrix, which can cause devastating disease white root rot in many highly valued fruit trees, is difficult to be controlled with conventional approaches such as fungicide applications. Rosellinia necatrix megabirnavirus 1-W779 (RnMBV1) is a dsRNA virus isolated from the R. necatrix field strain, W779, and this virus can be a viro-control candidate to confer hypovirulence in its host R. necatrix. To make use of RnMBV1 in the white root rot disease control, more molecular and structural investigations will offer us more insights. Here, we have performed cryo-electron microscopy (cryo-EM) single-particle analysis, to obtain the first atomic models of RnMBV1 particles. Based on the atomic structures, we found unique both surface and interior features. In addition, we found a previously unidentified protein on the viral surface. These aforementioned structural features might play important roles in the viral life cycles, and will enable us to apply this fungal virus as a viro-control approach. [ABSTRACT FROM AUTHOR]

Atmospheric aerosols exert a significant but highly uncertain effect on the global climate, and roughly half of these particles originate as small clusters formed by collisions between atmospheric trace vapors. These particles typically consist of acids, bases, and water, stabilized by salt bridge formation and a network of strong hydrogen bonds. We review spectroscopic studies of this process, focusing on the clusters likely to be involved in the first steps of particle formation and the intermolecular interactions governing their stability. These studies typically focus on determining structure and stability and have shown that acid-base chemistry in the cluster may violate chemical intuition derived from solution-phase behavior and that hydration of these clusters is likely to be complex to describe. We also suggest fruitful areas for extension of these studies and alternative spectroscopic techniques that have not yet been applied to this problem. [ABSTRACT FROM AUTHOR]

The size, polydispersity, and electron density profile of synaptic vesicles (SVs) can be studied by small-angle X-ray scattering (SAXS), i.e. by X-ray diffraction from purified SV suspensions in solution. Here we show that size and shape transformations, as they appear in the functional context of these important synaptic organelles, can also be monitored by SAXS. In particular, we have investigated the active uptake of neurotransmitters, and find a mean vesicle radius increase of about 12% after the uptake of glutamate, which indicates an unusually large extensibility of the vesicle surface, likely to be accompanied by conformational changes of membrane proteins and rearrangements of the bilayer. Changes in the electron density profile (EDP) give first indications for such a rearrangement. Details of the protein structure are screened, however, by SVs polydispersity. To overcome the limitations of large ensemble averages and heterogeneous structures, we therefore propose serial X-ray diffraction by single free electron laser pulses. Using simulated data for realistic parameters, we show that this is in principle feasible, and that even spatial distances between vesicle proteins could be assessed by this approach. [ABSTRACT FROM AUTHOR]

Helium droplets represent a cold inert matrix, free of walls with outstanding properties to grow complexes and clusters at conditions that are perfect to simulate cold and dense regions of the interstellar medium. At sub‐Kelvin temperatures, barrierless reactions triggered by radicals or ions have been observed and studied by optical spectroscopy and mass spectrometry. The present review summarizes developments of experimental techniques and methods and recent results they enabled. [ABSTRACT FROM AUTHOR]

Background: Cell-based models are becoming increasingly popular for applications in developmental biology. However, the impact of numerical choices on the accuracy and efficiency of the simulation of these models is rarely meticulously tested. Without concrete studies to differentiate between solid model conclusions and numerical artifacts, modelers are at risk of being misled by their experiments' results. Most cell-based modeling frameworks offer a feature-rich environment, providing a wide range of biological components, but are less suitable for numerical studies. There is thus a need for software specifically targeted at this use case. Results: We present CBMOS, a Python framework for the simulation of the center-based or cell-centered model. Contrary to other implementations, CBMOS' focus is on facilitating numerical study of center-based models by providing access to multiple ordinary differential equation solvers and force functions through a flexible, user-friendly interface and by enabling rapid testing through graphics processing unit (GPU) acceleration. We show-case its potential by illustrating two common workflows: (1) comparison of the numerical properties of two solvers within a Jupyter notebook and (2) measuring average wall times of both solvers on a high performance computing cluster. More specifically, we confirm that although for moderate accuracy levels the backward Euler method allows for larger time step sizes than the commonly used forward Euler method, its additional computational cost due to being an implicit method prohibits its use for practical test cases. Conclusions: CBMOS is a flexible, easy-to-use Python implementation of the center-based model, exposing both basic model assumptions and numerical components to the user. It is available on GitHub and PyPI under an MIT license. CBMOS allows for fast prototyping on a central processing unit for small systems through the use of NumPy. Using CuPy on a GPU, cell populations of up to 10,000 cells can be simulated within a few seconds. As such, it will substantially lower the time investment for any modeler to check the crucial assumption that model conclusions are independent of numerical issues. [ABSTRACT FROM AUTHOR]

MS SPIDOC is a novel sample delivery system designed for single (isolated) particle imaging at X-ray Free-Electron Lasers that is adaptable towards most large-scale facility beamlines. Biological samples can range from small proteins to MDa particles. Following nano-electrospray ionization, ionic samples can be m/z-filtered and structurally separated before being oriented at the interaction zone. Here, we present the simulation package developed alongside this prototype. The first part describes how the front-to-end ion trajectory simulations have been conducted. Highlighted is a quadrant lens; a simple but efficient device that steers the ion beam within the vicinity of the strong DC orientation field in the interaction zone to ensure spatial overlap with the X-rays. The second part focuses on protein orientation and discusses its potential with respect to diffractive imaging methods. Last, coherent diffractive imaging of prototypical T = 1 and T = 3 norovirus capsids is shown. We use realistic experimental parameters from the SPB/SFX instrument at the European XFEL to demonstrate that low-resolution diffractive imaging data (q < 0.3 nm -1 ) can be collected with only a few X-ray pulses. Such low-resolution data are sufficient to distinguish between both symmetries of the capsids, allowing to probe low abundant species in a beam if MS SPIDOC is used as sample delivery., (© 2023. The Author(s).)

Like an article narrative is deemed by an editor and referees to be worthy of being a version of record on acceptance as a publication, so must the underpinning data also be scrutinized before passing it as a version of record. Indeed without the underpinning data, a study and its conclusions cannot be reproduced at any stage of evaluation, pre- or post-publication. Likewise, an independent study without its own underpinning data also cannot be reproduced let alone be considered a replicate of the first study. The PDB is a modern marvel of achievement providing an organized open access to depositor and user of the data held there opening numerous applications. Methods for modeling protein structures and for determination of structures are still improving their precision, and artifacts of the method exist. So their accuracy is realized if they are reproduced by other methods. It is on such foundations that reproducible data mining is based. Data rates are expanding considerably be they at synchrotrons, the X-ray free electron lasers (XFELs), electron cryomicroscopes (cryoEM), or at the neutron facilities. The work of a person as a referee or user with a narrative and its underpinning data may well be complemented in future by artificial intelligence with machine learning, the former for specific refereeing and the latter for the more general validation, both ideally before publication. Examples are described involving rhenium theranostics, the anti-cancer platins and the SARS-CoV-2 main protease., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)