Mapping the Pathways of Photo-induced Ion Migration in Organic-inorganic Hybrid Halide Perovskites

Organic-inorganic hybrid perovskites (OIHPs) exhibiting exceptional photovoltaic and optoelectronic properties are of fundamental and practical interest, owing to their tunability and low manufacturing cost. For practical applications, however, challenges such as material instability and the photocurrent hysteresis occurring in perovskite solar cells under light exposure need to be understood and addressed. While extensive investigations have suggested that ion migration is a plausible origin of these detrimental effects, detailed understanding of the ion migration pathways remains elusive. Here, we report the characterization of photo-induced ion migration in OIHPs using \textit{in situ} laser illumination inside a scanning electron microscope, coupled with secondary electron imaging, energy-dispersive X-ray spectroscopy and cathodoluminescence with varying primary electron energies. Using methylammonium lead iodide (MAPbI$_3$), formamidinium lead iodide (FAPbI$_3$) and hybrid formamidinium-methylammonium lead iodide as model systems, we observed photo-induced long-range migration of halide ions over hundreds of micrometers and elucidated the transport pathways of various ions both near the surface and inside the bulk of the OIHPs, including a surprising finding of the vertical migration of lead ions. Our study provides insights into ion migration processes in OIHPs that can aid OIHP material design and processing in future applications

Simulation Method for the Physical Deformation of a Three-Dimensional Soft Body in Augmented Reality-Based External Ventricular Drainage

Objectives Intraoperative navigation reduces the risk of major complications and increases the likelihood of optimal surgical outcomes. This paper presents an augmented reality (AR)-based simulation technique for ventriculostomy that visualizes brain deformations caused by the movements of a surgical instrument in a three-dimensional brain model. This is achieved by utilizing a position-based dynamics (PBD) physical deformation method on a preoperative brain image. Methods An infrared camera-based AR surgical environment aligns the real-world space with a virtual space and tracks the surgical instruments. For a realistic representation and reduced simulation computation load, a hybrid geometric model is employed, which combines a high-resolution mesh model and a multiresolution tetrahedron model. Collision handling is executed when a collision between the brain and surgical instrument is detected. Constraints are used to preserve the properties of the soft body and ensure stable deformation. Results The experiment was conducted once in a phantom environment and once in an actual surgical environment. The tasks of inserting the surgical instrument into the ventricle using only the navigation information presented through the smart glasses and verifying the drainage of cerebrospinal fluid were evaluated. These tasks were successfully completed, as indicated by the drainage, and the deformation simulation speed averaged 18.78 fps. Conclusions This experiment confirmed that the AR-based method for external ventricular drain surgery was beneficial to clinicians

Conformational heterogeneity of molecules physisorbed on a gold surface at room temperature

A quantitative single-molecule tip-enhanced Raman spectroscopy (TERS) study at room temperature remained a challenge due to the rapid structural dynamics of molecules exposed to air. Here, we demonstrate the hyperspectral TERS imaging of single or a few brilliant cresyl blue (BCB) molecules at room temperature, along with quantitative spectral analyses. Robust chemical imaging is enabled by the freeze-frame approach using a thin Al2O3 capping layer, which suppresses spectral diffusions and inhibits chemical reactions and contamination in air. For the molecules resolved spatially in the TERS image, a clear Raman peak variation up to 7.5 cm(-1) is observed, which cannot be found in molecular ensembles. From density functional theory-based quantitative analyses of the varied TERS peaks, we reveal the conformational heterogeneity at the single-molecule level. This work provides a facile way to investigate the single-molecule properties in interacting media, expanding the scope of single-molecule vibrational spectroscopy studies. Tip-enhanced vibrational spectroscopy at room temperature is complicated by molecular conformational dynamics, photobleaching, contaminations, and chemical reactions in air. This study demonstrates that a sub-nm protective layer of Al2O3 provides robust conditions for probing single-molecule conformations

Sclerostin inhibits Wnt signaling through tandem interaction with two LRP6 ectodomains

Low-density lipoprotein receptor-related protein 6 (LRP6) is a coreceptor of the beta -catenin-dependent Wnt signaling pathway. The LRP6 ectodomain binds Wnt proteins, as well as Wnt inhibitors such as sclerostin (SOST), which negatively regulates Wnt signaling in osteocytes. Although LRP6 ectodomain 1 (E1) is known to interact with SOST, several unresolved questions remain, such as the reason why SOST binds to LRP6 E1E2 with higher affinity than to the E1 domain alone. Here, we present the crystal structure of the LRP6 E1E2-SOST complex with two interaction sites in tandem. The unexpected additional binding site was identified between the C-terminus of SOST and the LRP6 E2 domain. This interaction was confirmed by in vitro binding and cell-based signaling assays. Its functional significance was further demonstrated in vivo using Xenopus laevis embryos. Our results provide insights into the inhibitory mechanism of SOST on Wnt signaling. The low-density lipoprotein receptor-related protein 6 (LRP6) is a co-receptor of the beta -catenin-dependent Wnt signaling pathway and interacts with the Wnt inhibitor sclerostin (SOST). Here the authors present the crystal structure of SOST in complex with the LRP6 E1E2 ectodomain construct, which reveals that the SOST C-terminus binds to the LRP6 E2 domain, and further validate this binding site with in vitro and in vivo experiments.Y

Investigation of the biomechanical effect of variable stiffness shoe on external knee adduction moment in various dynamic exercises

10.1186/1757-1146-6-39Journal of Foot and Ankle Research61

Deep RNA Sequencing Reveals Novel Cardiac Transcriptomic Signatures for Physiological and Pathological Hypertrophy

Although both physiological hypertrophy (PHH) and pathological hypertrophy (PAH) of the heart have similar morphological appearances, only PAH leads to fatal heart failure. In the present study, we used RNA sequencing (RNA-Seq) to determine the transcriptomic signatures for both PHH and PAH. Approximately 13–20 million reads were obtained for both models, among which PAH showed more differentially expressed genes (DEGs) (2,041) than PHH (245). The expression of 417 genes was barely detectable in the normal heart but was suddenly activated in PAH. Among them, Foxm1 and Plk1 are of particular interest, since Ingenuity Pathway Analysis (IPA) using DEGs and upstream motif analysis showed that they are essential hub proteins that regulate the expression of downstream proteins associated with PAH. Meanwhile, 52 genes related to collagen, chemokines, and actin showed opposite expression patterns between PHH and PAH. MAZ-binding motifs were enriched in the upstream region of the participating genes. Alternative splicing (AS) of exon variants was also examined using RNA-Seq data for PAH and PHH. We found 317 and 196 exon inclusions and exon exclusions, respectively, for PAH, and 242 and 172 exon inclusions and exclusions, respectively for PHH. The AS pattern was mostly related to gains or losses of domains, changes in activity, and localization of the encoded proteins. The splicing variants of 8 genes (i.e., Fhl1, Rcan1, Ndrg2, Synpo, Ttll1, Cxxc5, Egfl7, and Tmpo) were experimentally confirmed. Multilateral pathway analysis showed that the patterns of quantitative (DEG) and qualitative (AS) changes differ depending on the type of pathway in PAH and PHH. One of the most significant changes in PHH is the severe downregulation of autoimmune pathways accompanied by significant AS. These findings revealed the unique transcriptomic signatures of PAH and PHH and also provided a more comprehensive understanding at both the quantitative and qualitative levels

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC00100

Deep Learning Segmentation in 2D X-ray Images and Non-Rigid Registration in Multi-Modality Images of Coronary Arteries

X-ray angiography is commonly used in the diagnosis and treatment of coronary artery disease with the advantage of visualization of the inside of blood vessels in real-time. However, it has several disadvantages that occur in the acquisition process, which causes inconvenience and difficulty. Here, we propose a novel segmentation and nonrigid registration method to provide useful real-time assistive images and information. A convolutional neural network is used for the segmentation of coronary arteries in 2D X-ray angiography acquired from various angles in real-time. To compensate for errors that occur during the 2D X-ray angiography acquisition process, 3D CT angiography is used to analyze the topological structure. A novel energy function-based 3D deformation and optimization is utilized to implement real-time registration. We evaluated the proposed method for 50 series from 38 patients by comparing the ground truth. The proposed segmentation method showed that Precision, Recall, and F1 score were 0.7563, 0.6922, and 0.7176 for all vessels, 0.8542, 0.6003, and 0.7035 for markers, and 0.8897, 0.6389, and 0.7386 for bifurcation points, respectively. In the nonrigid registration method, the average distance of 0.8705, 1.06, and 1. 5706 mm for all vessels, markers, and bifurcation points was achieved. The overall process execution time was 0.179 s

Temporal and Causal Dynamics between the Economy and Presidents

This dissertation project investigates how economic conditions influence presidential support in the United States. In particular, I focus on uncovering the temporal and causal dynamics to better understand the topic. Of the three papers of this dissertation, the first paper develops a Bayesian machine learning method and uses it to examine the temporal dynamics between macro-level income growth and presidential approval. I develop an estimation algorithm to fit multivariate time series models via the Bayesian adaptive lasso, a machine learning-based estimator that penalizes unimportant lagged variables and mitigates the problem of overfitting. This new methodological tool allows analysts to employ large-scale time series and a multitude of lagged terms. Consequently, it aids in discovering lagged policy effects or inertia of dynamic relationships, which have so far been difficult to theorize or test. The application of the method to quarterly data for presidential approval ratings uncovers substantial lagged effects and positive long-run effects of income growth. The second paper conducts a causal mediation analysis to explore two causal mechanisms that shape the effect of local unemployment on presidential voting: retrospective voting and issue-ownership voting. In an individual-level mediation analysis of the 2008, 2012, and 2016 presidential elections, this paper presents evidence that both mechanisms were at work in these most recent elections. The incumbent party, Democrat or Republican, is punished when local unemployment is rising, through its influence on retrospective evaluations of the national economy. Once this mediation effect representing retrospective voting is accounted for, local unemployment bolsters support for Democratic presidential candidates and drives down support for Republican candidates, implying that the two parties\u27 distinct reputations for the unemployment issue engender issue-ownership voting. Finally, the third paper formulates two partisan mechanisms that might moderate the relationship between macroeconomic conditions and presidential approval: retrospective and prospective partisan mechanisms. I test this new theoretical framework against quarterly data for multiple economic indicators and presidential approval from 1964 to 2015. The effect of unemployment squares with the prospective partisan mechanism: in response to deteriorating job conditions, citizens reward Democratic presidents and punish Republican presidents with an expectation that Democratic presidents will deal better with the unemployment issue. The effects of inflation, economic growth, and income growth are best explained by the retrospective partisan mechanism: only Republican presidents are punished for deteriorating conditions in terms of these three economic indicators, suggesting that these economic issues are salient for the Republican party and citizens hold Republicans more accountable for performance on these issues