Microsecond time-resolved X-ray scattering by utilizing MHz repetition rate at second-generation XFELs.

Detecting microsecond structural perturbations in biomolecules has wide relevance in biology, chemistry and medicine. Here we show how MHz repetition rates at X-ray free-electron lasers can be used to produce microsecond time-series of protein scattering with exceptionally low noise levels of 0.001%. We demonstrate the approach by examining Jɑ helix unfolding of a light-oxygen-voltage photosensory domain. This time-resolved acquisition strategy is easy to implement and widely applicable for direct observation of structural dynamics of many biochemical processes.

Lyotropic liquid crystal phases of monoolein in protic ionic liquids.

Monoolein-based liquid crystal phases are established media that are researched for various biological applications, including drug delivery. While water is the most common solvent for self-assembly, some ionic liquids (ILs) can support lipidic self-assembly. However, currently, there is limited knowledge of IL-lipid phase behavior in ILs. In this study, the lyotropic liquid crystal phase behavior of monoolein was investigated in six protic ILs known to support amphiphile self-assembly, namely ethylammonium nitrate, ethanolammonium nitrate, ethylammonium formate, ethanolammonium formate, ethylammonium acetate, and ethanolammonium acetate. These ILs were selected to identify specific ion effects on monoolein self-assembly, specifically increasing the alkyl chain length of the cation or anion, the presence of a hydroxyl group in the cation, and varying the anion. The lyotropic liquid crystal phases with 20-80 wt. % of monoolein were characterized over a temperature range from 25 to 65 °C using synchrotron small angle x-ray scattering and cross-polarized optical microscopy. These results were used to construct partial phase diagrams of monoolein in each of the six protic ILs, with inverse hexagonal, bicontinuous cubic, and lamellar phases observed. Protic ILs containing the ethylammonium cation led to monoolein forming lamellar and bicontinuous cubic phases, while those containing the ethanolammonium cation formed inverse hexagonal and bicontinuous cubic phases. Protic ILs containing formate and acetate anions favored bicontinuous cubic phases across a broader range of protic IL concentrations than those containing the nitrate anion.

Observations of phase changes in monoolein during high viscous injection.

Serial crystallography of membrane proteins often employs high-viscosity injectors (HVIs) to deliver micrometre-sized crystals to the X-ray beam. Typically, the carrier medium is a lipidic cubic phase (LCP) media, which can also be used to nucleate and grow the crystals. However, despite the fact that the LCP is widely used with HVIs, the potential impact of the injection process on the LCP structure has not been reported and hence is not yet well understood. The self-assembled structure of the LCP can be affected by pressure, dehydration and temperature changes, all of which occur during continuous flow injection. These changes to the LCP structure may in turn impact the results of X-ray diffraction measurements from membrane protein crystals. To investigate the influence of HVIs on the structure of the LCP we conducted a study of the phase changes in monoolein/water and monoolein/buffer mixtures during continuous flow injection, at both atmospheric pressure and under vacuum. The reservoir pressure in the HVI was tracked to determine if there is any correlation with the phase behaviour of the LCP. The results indicated that, even though the reservoir pressure underwent (at times) significant variation, this did not appear to correlate with observed phase changes in the sample stream or correspond to shifts in the LCP lattice parameter. During vacuum injection, there was a three-way coexistence of the gyroid cubic phase, diamond cubic phase and lamellar phase. During injection at atmospheric pressure, the coexistence of a cubic phase and lamellar phase in the monoolein/water mixtures was also observed. The degree to which the lamellar phase is formed was found to be strongly dependent on the co-flowing gas conditions used to stabilize the LCP stream. A combination of laboratory-based optical polarization microscopy and simulation studies was used to investigate these observations.

Methadone use in a male with the FMRI premutation and FXTAS.

The fragile X-associated tremor ataxia syndrome (FXTAS) is caused by the premutation in FMR1 gene. Recent reports of environmental toxins appear to worsen the progression of FXTAS. Here we present a case of male adult with FXTAS and a long history of methadone use. The patient shows a faster progression in both symptoms of disease and MRI changes compared to what is typically seen in FXTAS. There has been no research regarding the role of narcotics in onset, progression, and severity of FXTAS symptoms. However, research has shown that narcotics can have a negative impact on several neurodegenerative diseases, and we hypothesize that in this particular case, methadone may have contributed to a faster progression of FXTAS as well as exacerbating white matter disease through RNA toxicity seen in premutation carriers.

The pypadf package: computing the pair angle distribution function from fluctuation scattering data.

The pair angle distribution function (PADF) is a three- and four-atom correlation function that characterizes the local angular structure of disordered materials, particles or nanocrystalline materials. The PADF can be measured using X-ray or electron fluctuation diffraction data, which can be collected by scanning or flowing a structurally disordered sample through a focused beam. It is a natural generalization of established pair distribution methods, which do not provide angular information. The software package pypadf provides tools to calculate the PADF from fluctuation diffraction data. The package includes tools for calculating the intensity correlation function, which is a necessary step in the PADF calculation and also the basis for other fluctuation scattering analysis techniques.

Crystal structure via fluctuation scattering.

Crystallography is a quintessential method for determining the atomic structure of crystals. The most common implementation of crystallography uses single crystals that must be of sufficient size, typically tens of micrometres or larger, depending on the complexity of the crystal structure. The emergence of serial data-collection methods in crystallography, particularly for time-resolved experiments, opens up opportunities to develop new routes to structure determination for nanocrystals and ensembles of crystals. Fluctuation X-ray scattering is a correlation-based approach for single-particle imaging from ensembles of identical particles, but has yet to be applied to crystal structure determination. Here, an iterative algorithm is presented that recovers crystal structure-factor intensities from fluctuation X-ray scattering correlations. The capabilities of this algorithm are demonstrated by recovering the structure of three small-molecule crystals and a protein crystal from simulated fluctuation X-ray scattering correlations. This method could facilitate the recovery of structure-factor intensities from crystals in serial crystallography experiments and relax sample requirements for crystallography experiments.

The breast cancer conundrum.

For decades, rates of breast cancer have been going up faster in rich countries than in poor ones. Scientists are beginning to understand more about its causes but unanswered questions remain. Patrick Adams reports.

3D-printed sheet jet for stable megahertz liquid sample delivery at X-ray free-electron lasers.

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.

Ending polio, one type at a time.

Countries have endorsed a plan for the polio endgame, one that hinges on making inactivated polio vaccine more affordable for low- and middle-income countries.

Turkey's transformation.

Just three years after adopting tough anti-smoking measures, Turkey's tobacco consumption is down 15% and quitting is cool.

Stability, flow alignment and a phase transition of the lipidic cubic phase during continuous flow injection.

Continuous flow injection is a key technology for serial crystallography measurements of protein crystals suspended in the lipidic cubic phase (LCP). To date, there has been little discussion in the literature regarding the impact of the injection process itself on the structure of the lipidic phase. This is despite the fact that the phase of the injection matrix is critical for the flow properties of the stream and potentially for sample stability. Here we report small-angle X-ray scattering measurements of a monoolein:water mixture during continuous delivery using a high viscosity injector. We observe both an alignment and modification of the LCP as a direct result of the injection process. The orientation of the cubic lattice with respect to the beam was estimated based on the anisotropy of the diffraction pattern and does not correspond to a single low order zone axis. The solvent fraction was also observed to impact the stability of the cubic phase during injection. In addition, depending on the distance traveled by the lipid after exiting the needle, the phase is observed to transition from a pure diamond phase (Pn3m) to a mixture containing both gyriod (Ia3d) and lamellar (Lα) phases. Finite element modelling of the observed phase behaviour during injection indicates that the pressure exerted on the lipid stream during extrusion accounts for the variations in the phase composition of the monoolein:water mixture.

Preferred orientation and its effects on intensity-correlation measurements.

Intensity-correlation measurements allow access to nanostructural information on a range of ordered and disordered materials beyond traditional pair-correlation methods. In real space, this information can be expressed in terms of a pair-angle distribution function (PADF) which encodes three- and four-body distances and angles. To date, correlation-based techniques have not been applied to the analysis of microstructural effects, such as preferred orientation, which are typically investigated by texture analysis. Preferred orientation is regarded as a potential source of error in intensity-correlation experiments and complicates interpretation of the results. Here, the theory of preferred orientation in intensity-correlation techniques is developed, connecting it to the established theory of texture analysis. The preferred-orientation effect is found to scale with the number of crystalline domains in the beam, surpassing the nanostructural signal when the number of domains becomes large. Experimental demonstrations are presented of the orientation-dominant and nanostructure-dominant cases using PADF analysis. The results show that even minor deviations from uniform orientation produce the strongest angular correlation signals when the number of crystalline domains in the beam is large.

Left Atrial Volume as a Biomarker of Atrial Fibrillation at Routine Chest CT: Deep Learning Approach.

PURPOSE: To test the performance of a deep learning (DL) model in predicting atrial fibrillation (AF) at routine nongated chest CT. MATERIALS AND METHODS: A retrospective derivation cohort (mean age, 64 years; 51% female) consisting of 500 consecutive patients who underwent routine chest CT served as the training set for a DL model that was used to measure left atrial volume. The model was then used to measure atrial size for a separate 500-patient validation cohort (mean age, 61 years; 46% female), in which the AF status was determined by performing a chart review. The performance of automated atrial size as a predictor of AF was evaluated by using a receiver operating characteristic analysis. RESULTS: There was good agreement between manual and model-generated segmentation maps by all measures of overlap and surface distance (mean Dice = 0.87, intersection over union = 0.77, Hausdorff distance = 4.36 mm, average symmetric surface distance = 0.96 mm), and agreement was slightly but significantly greater than that between human observers (mean Dice = 0.85 [automated] vs 0.84 [manual]; P = .004). Atrial volume was a good predictor of AF in the validation cohort (area under the receiver operating characteristic curve = 0.768) and was an independent predictor of AF, with an age-adjusted relative risk of 2.9. CONCLUSION: Left atrial volume is an independent predictor of the AF status as measured at routine nongated chest CT. Deep learning is a suitable tool for automated measurement.© RSNA, 2019See also the commentary by de Roos and Tao in this issue.