bluuebunny/crossref_metadata_2025_split huggingface dataset:
Crustal Structure of the Nankai Subduction Zone Revealed by Two Decades of Onshore‐Offshore and Ocean‐Bottom Seismic Data: Implications for the Dimensions and Slip Behavior of the Seismogenic Zone
Authors: Bassett Dan , Arnulf Adrien , Kodaira Shuichi , Nakanishi Ayako , Harding Alistair , Moore Gregory 
Published: October 2022

AbstractTwo‐decades of onshore‐offshore, ocean‐bottom seismometer, and passive‐source data are integrated to obtain high‐resolution 3‐D constraints on the architecture of the Nankai subduction zone. Our model reveals large along‐strike variability in the width of the outer‐forearc, with the crustal backstop (VP ≥ 5 km/s) extending within 50 km of Nankai Trough offshore Tokai and Kii Peninsula, but is a factor of 2 further landward (90–115 km) offshore Cape Muroto and Kyushu. The crustal backstop broadly coincides with the down‐dip extent of shallow slow‐earthquakes and the up‐dip extent of co‐seismic slip and geodetic locking, suggesting a link with the shallow frictional transition. In the inner‐forearc, high seismic‐velocities (VP > 6.6 km/s) in Kii Peninsula reflect Miocene plutons, impacting the nucleation and segmentation of large megathrust earthquakes. The complex geometry of the subducting slab drives spatial variability in the location of the down‐dip frictional transition. Variability in the width of the outer‐forearc, the dip of the subducting slab, and the depth distribution of deep slow‐slip events combine to produce large changes in the width of the seismogenic zone. This is most pronounced across Bungo channel, where the seismogenic zone narrows from 90 to 120 km in Shikoku to <60 km offshore Kyushu. Pinching of the seismogenic zone may explain the smaller area, and thus magnitude, of earthquakes offshore Kyushu and the reduction in slip‐deficit rate. Our results suggest crustal‐scale architecture is a key driver of profound along‐strike transitions in the location of frictional transition zones, and the width and slip behavior of the intervening seismogenic zone at Nankai Trough.
Heterogeneity in Microseismicity and Stress Near Rupture‐Limiting Section Boundaries Along the Late‐Interseismic Alpine Fault
Authors: Warren‐Smith E. , Townend J. , Chamberlain C. J. , Boulton C. , Michailos K. 
Published: October 2022

AbstractPaleoseismic evidence from the late‐interseismic Alpine Fault suggests key section boundaries conditionally inhibit rupture. We utilize a year of data from a two‐part seismometer network (Dense Westland Arrays Researching Fault Segmentation) to characterize ∼7,500 earthquakes (−0.7 ≤MLv≤ 4.2) and ∼800 focal mechanisms, producing high‐resolution structural images of these boundaries to study effects of material and structural heterogeneities on mode‐switching rupture behavior. Lithologically‐controlled frictional behavior and crustal strength appear to influence lateral and vertical on‐fault seismicity distributions. Ultramafic hanging‐wall serpentinite and serpentinite‐related fault core minerals along the South Westland (SW) boundary, result in a locally shallow seismogenic cuttoff (∼8 km) and abundant on‐fault seismicity. Maximum horizontal compressive stress rotations (14° anti‐clockwise and 20° clockwise near the SW and North Westland (NW) boundaries, respectively, relative to the Central Section), coupled with spatially variable fault frictional properties, are more important than geometry alone in controlling Sections' relative frictional stability. Whereas the SW and Central Sections are well‐oriented for failure, the NW Section is severely misoriented compared with favorably oriented faults of the Marlborough Fault Zone, which possibly facilitate a preferred rupture route. Geometrically, a 40° dip change at the SW boundary may be accommodated either by a single through‐going fault plane ‐ a difficult geometry across which to obtain multi‐segment earthquakes when considering rupture dynamics ‐ or by a deeper vertical fault strand truncated by a shallower listric plane. Our new observations have implications for Alpine Fault rupture scenarios and highlight the need to consider a range of spatially heterogeneous, interdependent physical factors when evaluating controls on rupture segmentation.
Impaired synaptic transmission in dorsal dentate gyrus increases impulsive alcohol seeking
Authors: Nalberczak-Skóra Maria , Beroun Anna , Skonieczna Edyta , Cały Anna , Ziółkowska Magdalena , Pagano Roberto , Taheri Pegah , Kalita Katarzyna , Salamian Ahmad , Radwanska Kasia 
Published: October 2022

AbstractBoth human and animal studies indicate that the dentate gyrus (DG) of the hippocampus is highly exploited by drug and alcohol abuse. Yet, it is poorly understood how DG dysfunction affects addiction-related behaviors. Here, we used an animal model of alcohol use disorder (AUD) in automated IntelliCages and performed local genetic manipulation to investigate how synaptic transmission in the dorsal DG (dDG) affects alcohol-related behaviors. We show that a cue light induces potentiation-like plasticity of dDG synapses in alcohol-naive mice. This process is impaired in mice trained to drink alcohol. Acamprosate (ACA), a drug that reduces alcohol relapse, rescues the impairment of dDG synaptic transmission in alcohol mice. A molecular manipulation that reduces dDG synaptic AMPAR and NMDAR levels increases impulsive alcohol seeking during cue relapse (CR) in alcohol mice but does not affect alcohol reward, motivation or craving. These findings suggest that hindered dDG synaptic transmission specifically underlies impulsive alcohol seeking induced by alcohol cues, a core symptom of AUD.
Exploring the causal effects of genetic liability to ADHD and Autism on Alzheimer’s disease
Authors: Pagoni Panagiota , Dardani Christina , Leppert Beate , Korologou-Linden Roxanna , Smith George Davey , Howe Laura D. , Anderson Emma L. , Stergiakouli Evie 
Published: October 2022

AbstractFew studies suggest possible links between attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and Alzheimer’s disease but they have been limited by small sample sizes, diagnostic and recall bias. We used two-sample Mendelian randomization (MR) to estimate the bidirectional causal association between genetic liability to ADHD and ASD on Alzheimer’s disease. In addition, we estimated the causal effects independently of educational attainment and IQ, through multivariable Mendelian randomization (MVMR). We employed genetic variants associated with ADHD (20,183 cases/35,191 controls), ASD (18,381 cases/27,969 controls), Alzheimer’s disease (71,880 cases/383,378 controls), educational attainment (n = 766,345) and IQ (n = 269,867) using the largest GWAS of European ancestry. There was limited evidence to suggest a causal effect of genetic liability to ADHD (odds ratio [OR] = 1.00, 95% CI: 0.98–1.02, P = 0.39) or ASD (OR = 0.99, 95% CI: 0.97–1.01, P = 0.70) on Alzheimer’s disease. Similar causal effect estimates were identified as direct effects, independent of educational attainment (ADHD: OR = 1.00, 95% CI: 0.99–1.01, P = 0.76; ASD: OR = 0.99, 95% CI: 0.98–1.00, P = 0.28) and IQ (ADHD: OR = 1.00, 95% CI: 0.99–1.02. P = 0.29; ASD: OR = 0.99, 95% CI: 0.98–1.01, P = 0.99). Genetic liability to Alzheimer’s disease was not found to have a causal effect on risk of ADHD or ASD (ADHD: OR = 1.12, 95% CI: 0.86–1.44, P = 0.37; ASD: OR = 1.19, 95% CI: 0.94–1.51, P = 0.14). We found limited evidence to suggest a causal effect of genetic liability to ADHD or ASD on Alzheimer’s disease; and vice versa.
Histopathological evaluation of pulp response to portland cement compared to MTA after primary canines pulpotomy (in vivo study)
Authors: Alzoubi Hasan , Bshara Nada , AL-Manadili Ahmad 
Published: October 2022

Abstract
Introduction
ECC (Early childhood caries) is very common in children. Because of the small size of primary anterior teeth, endodontic exposures occur early. Pulp tissue response after pulpotomy of primary anterior teeth by both MTA and Portland Cement is very important when pulp exposures occur in these teeth.

Aim
This study aimed to evaluate in vivo pulp tissue responses after the primary canines pulpotomy with either White Portland Cement (WPC) or White Mineral Trioxide Aggregate (WMTA), by histopathological analysis.

Materials and methods
The study included 30 primary canines in 21 healthy children aged 6–9 years old and it was classified into 2 groups according to the material. Group 1: included 15 teeth capped by White Portland Cement, and Group 2: included 15 teeth capped by white MTA. The dentine bridge formation, soft Tissue Organization, tissue fibrosis, formed dentin bridge thickness, pulp calcifications, hemorrhage in the pulp tissue, and deposition of new dentin on the inner surface of the dentin at 3 months periods were recorded.

Results
Data were analyzed statistically; the Mann–Whitney U test was performed for the assessment of histopathological criteria. Descriptive statistics were performed for the analysis of participant properties. Histopathological analysis showed complete dentin bridge formation and normal soft tissue organization for both materials. Statistical analysis showed no significant differences in dentine bridge formation (P value = 0.213), soft Tissue Organization (P value = 0.339), tissue fibrosis (P value = 0.079), formed dentin bridge thickness (P value = 0.139), pulp calcifications (P value = 0.581), hemorrhage in the pulp tissue (P value = 0.117), and deposition of new dentin (P value = 0.097), during the observation period.

Conclusions
Within the limitation of the current study WPC was similar to WMTA in terms of histological criteria so PC may serve as a good alternative to MTA in primary teeth pulpotomy.
Deubiquitylase OTUD1 confers Erlotinib sensitivity in non-small cell lung cancer through inhibition of nuclear translocation of YAP1
Authors: Liu Huafeng , Zhong Liting , Lu Yanjun , Liu Xuewen , Wei Jiawang , Ding Yuhai , Huang Huiling , Nie Qihong , Liao Xiaohong 
Published: October 2022

AbstractEvidence exists suggesting tumor-inhibiting properties of deubiquitylase OTUD1 in various malignancies. We herein investigated the anti-tumor effect and clarified the downstream mechanisms of OTUD1 in the chemoresistance of non-small cell lung cancer (NSCLC) cells. Expression of OTUD1 was examined in NSCLC (PC-9 cells) and erlotinib-resistant NSCLC (PC-9/ER) cell lines. OTUD1 was bioinformatically predicted to be weakly expressed in NSCLC tissue samples and verified in PC-9/ER cells. PC-9/ER cells were subsequently subjected to ectopic expression of OTUD1 alone or combined with SOX9 to dissect out the effect of OTUD1 on the proliferation, chemoresistance and apoptosis in vitro and in vivo. OTUD1 upregulation sensitized NSCLC cells to erlotinib both in vitro and in vivo. In the presence of OTUD1 overexpression, nuclear translocation of YAP1 was inhibited and its expression was inactivated. This effect of OTUD1 was associated with the decreased ubiquitination level of YAP1. SOX9/SPP1 inactivation was the consequence of inhibited nuclear translocation of YAP1. Overexpression of SOX9 reversed the inhibitory effect of OTUD1 on the resistance of NSCLC cells to erlotinib. In conclusion, our study reveals that OTUD1 potentially acts as a tumor suppressor and suppresses erlotinib resistance of NSCLC through the YAP1/SOX9/SPP1 axis, suggesting that OTUD1 may serve as a target for reducing chemoresistance for NSCLC.
Sevoflurane induces microRNA-18a to delay rat neurodevelopment via suppression of the RUNX1/Wnt/β-catenin axis
Authors: Jiang Yuge , Liu Yaobo , Sun Yuhui , Liu Yongzhe , Feng Long , Duan Mingda , Liu Yi , Xu Longhe 
Published: October 2022

AbstractSevoflurane anesthesia is reported to repress neurogenesis of neural stem cells (NSCs), thereby affecting the brain development, but the underlying mechanism of sevoflurane on the proliferation of NSCs remains unclear. Thus, this study aims to discern the relationship between sevoflurane and NSC proliferation. Bioinformatics tools were employed to predict the expression of microRNA-18a (miR-18a) in 9-day-old neonatal rat hippocampal tissues after sevoflurane treatment and the downstream genes of miR-18a, followed by a series of assays to explore the relationship among miR-18a, runt related transcription factor 1 (RUNX1), and β-catenin in the hippocampal tissues. NSCs were isolated from the hippocampal tissues and subjected to gain-/loss-of-function assays to investigate the interactions among miR-18a, RUNX1, and β-catenin in NSCs and their roles in NSC development. Bioinformatics analysis and experimental results confirmed high expression of miR-18a in rat hippocampal tissues and NSCs after sevoflurane treatment. Next, we found that miR-18a downregulated RUNX1 expression, while RUNX1 promoted NSC proliferation by activating the Wnt/β-catenin signaling pathway. The behavioral experiments also showed that sevoflurane caused nerve injury in rats, whilst RUNX1 overexpression protected rat neurodevelopment. Our findings uncovered that sevoflurane attenuated NSC proliferation via the miR-18a-meidated RUNX1/Wnt/β-catenin pathway, thereby impairing rat neurodevelopment.
The effect of enantioselective chiral covalent organic frameworks and cysteine sacrificial donors on photocatalytic hydrogen evolution
Authors: Weng Weijun , Guo Jia 
Published: October 2022

AbstractCovalent organic frameworks (COFs) have constituted an emerging class of organic photocatalysts showing enormous potential for visible photocatalytic H2evolution from water. However, suffering from sluggish reaction kinetics, COFs often cooperate with precious metal co-catalysts for essential proton-reducing capability. Here, we synthesize a chiral β-ketoenamine-linked COF coordinated with 10.51 wt% of atomically dispersed Cu(II) as an electron transfer mediator. The enantioselective combination of the chiral COF-Cu(II) skeleton with L-/D-cysteine sacrificial donors remarkably strengthens the hole extraction kinetics, and in turn, the photoinduced electrons accumulate and rapidly transfer via the coordinated Cu ions. Also, the parallelly stacking sequence of chiral COFs provides the energetically favorable arrangement for the H-adsorbed sites. Thus, without precious metal, the visible photocatalytic H2evolution rate reaches as high as 14.72 mmol h−1 g−1for the enantiomeric mixtures. This study opens up a strategy for optimizing the reaction kinetics and promises the exciting potential of chiral COFs for photocatalysis.
Modeling of ultrafast X-ray induced magnetization dynamics in magnetic multilayer systems
Authors: Kapcia K. J. , Tkachenko V. , Capotondi F. , Lichtenstein A. , Molodtsov S. , Müller L. , Philippi-Kobs A. , Piekarz P. , Ziaja B. 
Published: October 2022

AbstractIn this work, we report on modeling results obtained with our recently developed simulation tool enabling nanoscopic description of electronic processes in X-ray irradiated ferromagnetic materials. With this tool, we have studied the response of Co/Pt multilayer system irradiated by an ultrafast extreme ultraviolet pulse at the M-edge of Co (photon energy ~60 eV). It was previously investigated experimentally at the FERMI free-electron-laser facility, using the magnetic small-angle X-ray scattering technique. Our simulations show that the magnetic scattering signal from cobalt decreases on femtosecond timescales due to electronic excitation, relaxation, and transport processes both in the cobalt and in the platinum layers, following the trend observed in the experimental data. The confirmation of the predominant role of electronic processes for X-ray induced demagnetization in the regime below the structural damage threshold is a step toward quantitative control and manipulation of X-ray induced magnetic processes on femtosecond timescales.
Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning
Authors: Anker Andy S. , Kjær Emil T. S. , Juelsholt Mikkel , Christiansen Troels Lindahl , Skjærvø Susanne Linn , Jørgensen Mads Ry Vogel , Kantor Innokenty , Sørensen Daniel Risskov , Billinge Simon J. L. , Selvan Raghavendra , Jensen Kirsten M. Ø. 
Published: October 2022

AbstractCharacterization of material structure with X-ray or neutron scattering using e.g. Pair Distribution Function (PDF) analysis most often rely on refining a structure model against an experimental dataset. However, identifying a suitable model is often a bottleneck. Recently, automated approaches have made it possible to test thousands of models for each dataset, but these methods are computationally expensive and analysing the output, i.e. extracting structural information from the resulting fits in a meaningful way, is challenging. Our Machine Learning based Motif Extractor (ML-MotEx) trains an ML algorithm on thousands of fits, and uses SHAP (SHapley Additive exPlanation) values to identify which model features are important for the fit quality. We use the method for 4 different chemical systems, including disordered nanomaterials and clusters. ML-MotEx opens for a type of modelling where each feature in a model is assigned an importance value for the fit quality based on explainable ML.
Clinically relevant small-molecule promotes nerve repair and visual function recovery
Authors: Au Ngan Pan Bennett , Kumar Gajendra , Asthana Pallavi , Gao Fuying , Kawaguchi Riki , Chang Raymond Chuen Chung , So Kwok Fai , Hu Yang , Geschwind Daniel H. , Coppola Giovanni , Ma Chi Him Eddie 
Published: October 2022

AbstractAdult mammalian injured axons regenerate over short-distance in the peripheral nervous system (PNS) while the axons in the central nervous system (CNS) are unable to regrow after injury. Here, we demonstrated that Lycium barbarum polysaccharides (LBP), purified from Wolfberry, accelerated long-distance axon regeneration after severe peripheral nerve injury (PNI) and optic nerve crush (ONC). LBP not only promoted intrinsic growth capacity of injured neurons and function recovery after severe PNI, but also induced robust retinal ganglion cell (RGC) survival and axon regeneration after ONC. By using LBP gene expression profile signatures to query a Connectivity map database, we identified a Food and Drug Administration (FDA)-approved small-molecule glycopyrrolate, which promoted PNS axon regeneration, RGC survival and sustained CNS axon regeneration, increased neural firing in the superior colliculus, and enhanced visual target re-innervations by regenerating RGC axons leading to a partial restoration of visual function after ONC. Our study provides insights into repurposing of FDA-approved small molecule for nerve repair and function recovery.
Leveraging network structure in nonlinear control
Authors: Rozum Jordan , Albert Réka 
Published: October 2022

AbstractOver the last twenty years, dynamic modeling of biomolecular networks has exploded in popularity. Many of the classical tools for understanding dynamical systems are unwieldy in the highly nonlinear, poorly constrained, high-dimensional systems that often arise from these modeling efforts. Understanding complex biological systems is greatly facilitated by purpose-built methods that leverage common features of such models, such as local monotonicity, interaction graph sparsity, and sigmoidal kinetics. Here, we review methods for controlling the systems of ordinary differential equations used to model biomolecular networks. We focus on methods that make use of the structure of the network of interactions to help inform, which variables to target for control, and highlight the computational and experimental advantages of such approaches. We also discuss the importance of nonperturbative methods in biomedical and experimental molecular biology applications, where finely tuned interventions can be difficult to implement. It is well known that feedback loops, and positive feedback loops in particular, play a major determining role in the dynamics of biomolecular networks. In many of the methods we cover here, control over system trajectories is realized by overriding the behavior of key feedback loops.
Niche deconvolution of the glioblastoma proteome reveals a distinct infiltrative phenotype within the proneural transcriptomic subgroup
Authors: Lam K. H. Brian , Diamandis Phedias 
Published: October 2022

AbstractGlioblastoma is often subdivided into three transcriptional subtypes (classical, proneural, mesenchymal) based on bulk RNA signatures that correlate with distinct genetic and clinical features. Potential cellular-level differences of these subgroups, such as the relative proportions of glioblastoma’s hallmark histopathologic features (e.g. brain infiltration, microvascular proliferation), may provide insight into their distinct phenotypes but are, however, not well understood. Here we leverage machine learning and reference proteomic profiles derived from micro-dissected samples of these major histomorphologic glioblastoma features to deconvolute and estimate niche proportions in an independent proteogenomically-characterized cohort. This approach revealed a strong association of the proneural transcriptional subtype with a diffusely infiltrating phenotype. Similarly, enrichment of a microvascular proliferation proteomic signature was seen within the mesenchymal subtype. This study is the first to link differences in the cellular pathology signatures and transcriptional profiles of glioblastoma, providing potential new insights into the genetic drivers and poor treatment response of specific subsets of glioblastomas.
Machine learning-based risk factor analysis of adverse birth outcomes in very low birth weight infants
Authors: Cho Hannah , Lee Eun Hee , Lee Kwang-Sig , Heo Ju Sun 
Published: October 2022

AbstractThis study aimed to analyze major predictors of adverse birth outcomes in very low birth weight (VLBW) infants including particulate matter concentration (PM10), using machine learning and the national prospective cohort. Data consisted of 10,423 VLBW infants from the Korean Neonatal Network database during January 2013–December 2017. Five adverse birth outcomes were considered as the dependent variables, i.e., gestational age less than 28 weeks, gestational age less than 26 weeks, birth weight less than 1000 g, birth weight less than 750 g and small-for-gestational age. Thirty-three predictors were included and the artificial neural network, the decision tree, the logistic regression, the Naïve Bayes, the random forest and the support vector machine were used for predicting the dependent variables. Among the six prediction models, the random forest had the best performance (accuracy 0.79, area under the receiver-operating-characteristic curve 0.72). According to the random forest variable importance, major predictors of adverse birth outcomes were maternal age (0.2131), birth-month (0.0767), PM10 month (0.0656), sex (0.0428), number of fetuses (0.0424), primipara (0.0395), maternal education (0.0352), pregnancy-induced hypertension (0.0347), chorioamnionitis (0.0336) and antenatal steroid (0.0318). In conclusion, adverse birth outcomes had strong associations with PM10 month as well as maternal and fetal factors.