Development and internal validation of machine learning-based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke.

Aims: We developed new machine learning (ML) models and externally validated existing statistical models [ischaemic stroke predictive risk score (iScore) and totalled health risks in vascular events (THRIVE) scores] for predicting the composite of recurrent stroke or all-cause mortality at 90 days and at 3 years after hospitalization for first acute ischaemic stroke (AIS). Methods and results: In adults hospitalized with AIS from January 2005 to November 2016, with follow-up until November 2019, we developed three ML models [random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBOOST)] and externally validated the iScore and THRIVE scores for predicting the composite outcomes after AIS hospitalization, using data from 721 patients and 90 potential predictor variables. At 90 days and 3 years, 11 and 34% of patients, respectively, reached the composite outcome. For the 90-day prediction, the area under the receiver operating characteristic curve (AUC) was 0.779 for RF, 0.771 for SVM, 0.772 for XGBOOST, 0.720 for iScore, and 0.664 for THRIVE. For 3-year prediction, the AUC was 0.743 for RF, 0.777 for SVM, 0.773 for XGBOOST, 0.710 for iScore, and 0.675 for THRIVE. Conclusion: The study provided three ML-based predictive models that achieved good discrimination and clinical usefulness in outcome prediction after AIS and broadened the application of the iScore and THRIVE scoring system for long-term outcome prediction. Our findings warrant comparative analyses of ML and existing statistical method-based risk prediction tools for outcome prediction after AIS in new data sets.

Dynamic adaptive X-ray optics. Part II. High-speed piezoelectric bimorph deformable Kirkpatrick-Baez mirrors for rapid variation of the 2D size and shape of X-ray beams.

The tangential curvature of actively bent X-ray mirrors at synchrotron radiation and X-ray free-electron laser (XFEL) facilities is typically only changed every few hours or even days. This operation can take tens of minutes for active optics with multiple bending actuators and often requires expert guidance using in situ monitoring devices. Hence, the dynamic performance of active X-ray optics for synchrotron beamlines has historically not been exploited. This is in stark contrast to many other scientific fields. However, many areas of synchrotron radiation and XFEL science, including macromolecular crystallography, could greatly benefit from the ability to change the size and shape of the X-ray beam rapidly and continuously. The advantages of this innovative approach are twofold: a large reduction in the dead time required to change the size of the X-ray beam for different-sized samples and the possibility of making multiple changes to the beam during the measurement of a single sample. In the preceding paper [Part I; Alcock, Nistea, Signorato & Sawhney (2019), J. Synchrotron Rad. 26, 36-44], which accompanies this article, high-speed visible-light Fizeau interferometry was used to identify the factors which influence the dynamic bending behaviour of piezoelectric bimorph deformable X-ray mirrors. Building upon this ex situ metrology study, provided here is the first synchrotron radiation beamline implementation of high-speed adaptive X-ray optics using two bimorphs operating as a Kirkpatrick-Baez pair. With optimized substrates, novel opto-mechanical holders and a next-generation high-voltage power supply, the size of an X-ray beam was rapidly and repeatedly switched in <10 s. Of equal importance, it is also shown that compensation of piezoelectric creep ensures that the X-ray beam size remains stable for more than 1 h after making a major change. The era of high-speed adaptive X-ray optics for synchrotron radiation and XFEL beamlines has begun.

Molecularly resolved protein electromechanical properties.

Previous work has shown that protein molecules can be trapped between the conductive surfaces presented by a metal-coated AFM probe and an underlying planar substrate where their molecule-specific conductance characteristics can be assayed. Herein, we demonstrate that transport across such a derived metal-protein-electrode junction falls within three, pressure-dependent, regimes and, further, that pressure-dependent conductance can be utilized in analyzing temporal variations of protein fold. Specifically, the electronic and mechanical properties of the metalloprotein azurin have been characterized under conditions of anisotropic vertical compression through the use of a conducting atomic force microscope (CP-AFM). By utilizing the ability of azurin to chemically self-assemble on the gold surface presented either by the apex of a suitably coated AFM probe or a planar metallic surface, molecular-level transport characteristics are assayable. Under conditions of low force, typically less than 2 nN, the weak physical and electronic coupling between the protein and the conducting contacts impedes tunneling and leads to charge buildup followed by dielectric breakdown. At slightly increased force, 3-5 nN, the copper protein exhibits temporal electron occupation with observable negative differential resistance, while the redox-inactive zinc mutant does not. At imposed loads greater than 5 nN, appreciable electron tunneling can be detected even at low bias for both the redox-active and -inactive species. Dynamic current-voltage characteristics have been recorded and are well-described by a modified Simmons tunneling model. Subsequent analyses enable the electron tunneling barrier height and barrier length to be determined under conditions of quantified vertical stress. The variance observed describes, in essence, the protein's mechanical properties within the confines of the tunnel junction.