bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanisms of bone pain: Progress in research from bench to bedside
Authors: Zhen Gehua , Fu Yuhan , Zhang Chi , Ford Neil C. , Wu Xiaojun , Wu Qichao , Yan Dong , Chen Xueming , Cao Xu , Guan Yun 
Published: June 2022

AbstractThe field of research on pain originating from various bone diseases is expanding rapidly, with new mechanisms and targets asserting both peripheral and central sites of action. The scope of research is broadening from bone biology to neuroscience, neuroendocrinology, and immunology. In particular, the roles of primary sensory neurons and non-neuronal cells in the peripheral tissues as important targets for bone pain treatment are under extensive investigation in both pre-clinical and clinical settings. An understanding of the peripheral mechanisms underlying pain conditions associated with various bone diseases will aid in the appropriate application and development of optimal strategies for not only managing bone pain symptoms but also improving bone repairing and remodeling, which potentially cures the underlying etiology for long-term functional recovery. In this review, we focus on advances in important preclinical studies of significant bone pain conditions in the past 5 years that indicated new peripheral neuronal and non-neuronal mechanisms, novel targets for potential clinical interventions, and future directions of research.
Skyrmion pinning energetics in thin film systems
Authors: Gruber Raphael , Zázvorka Jakub , Brems Maarten A. , Rodrigues Davi R. , Dohi Takaaki , Kerber Nico , Seng Boris , Vafaee Mehran , Everschor-Sitte Karin , Virnau Peter , Kläui Mathias 
Published: June 2022

AbstractA key issue for skyrmion dynamics and devices are pinning effects present in real systems. While posing a challenge for the realization of conventional skyrmionics devices, exploiting pinning effects can enable non-conventional computing approaches if the details of the pinning in real samples are quantified and understood. We demonstrate that using thermal skyrmion dynamics, we can characterize the pinning of a sample and we ascertain the spatially resolved energy landscape. To understand the mechanism of the pinning, we probe the strong skyrmion size and shape dependence of the pinning. Magnetic microscopy imaging demonstrates that in contrast to findings in previous investigations, for large skyrmions the pinning originates at the skyrmion boundary and not at its core. The boundary pinning is strongly influenced by the very complex pinning energy landscape that goes beyond the conventional effective rigid quasi-particle description. This gives rise to complex skyrmion shape distortions and allows for dynamic switching of pinning sites and flexible tuning of the pinning.
Machine learning the metastable phase diagram of covalently bonded carbon
Authors: Srinivasan Srilok , Batra Rohit , Luo Duan , Loeffler Troy , Manna Sukriti , Chan Henry , Yang Liuxiang , Yang Wenge , Wen Jianguo , Darancet Pierre , K.R.S. Sankaranarayanan Subramanian 
Published: June 2022

AbstractConventional phase diagram generation involves experimentation to provide an initial estimate of the set of thermodynamically accessible phases and their boundaries, followed by use of phenomenological models to interpolate between the available experimental data points and extrapolate to experimentally inaccessible regions. Such an approach, combined with high throughput first-principles calculations and data-mining techniques, has led to exhaustive thermodynamic databases (e.g. compatible with the CALPHAD method), albeit focused on the reduced set of phases observed at distinct thermodynamic equilibria. In contrast, materials during their synthesis, operation, or processing, may not reach their thermodynamic equilibrium state but, instead, remain trapped in a local (metastable) free energy minimum, which may exhibit desirable properties. Here, we introduce an automated workflow that integrates first-principles physics and atomistic simulations with machine learning (ML), and high-performance computing to allow rapid exploration of the metastable phases to construct “metastable” phase diagrams for materials far-from-equilibrium. Using carbon as a prototypical system, we demonstrate automated metastable phase diagram construction to map hundreds of metastable states ranging from near equilibrium to far-from-equilibrium (400 meV/atom). We incorporate the free energy calculations into a neural-network-based learning of the equations of state that allows for efficient construction of metastable phase diagrams. We use the metastable phase diagram and identify domains of relative stability and synthesizability of metastable materials. High temperature high pressure experiments using a diamond anvil cell on graphite sample coupled with high-resolution transmission electron microscopy (HRTEM) confirm our metastable phase predictions. In particular, we identify the previously ambiguous structure of n-diamond as a cubic-analog of diaphite-like lonsdaelite phase.
Perirenal adipose afferent nerves sustain pathological high blood pressure in rats
Authors: Li Peng , Liu Boxun , Wu Xiaoguang , Lu Yan , Qiu Ming , Shen Yihui , Tian Yunfan , Liu Chi , Chen Xiru , Yang Chuanxi , Deng Mengqing , Wang Yaqing , Gu Jia , Su Zhongping , Chen Xuguan , Zhao Kun , Sheng Yanhui , Zhang Shijiang , Sun Wei , Kong Xiangqing 
Published: June 2022

AbstractHypertension is a pathological condition of persistent high blood pressure (BP) of which the underlying neural mechanisms remain obscure. Here, we show that the afferent nerves in perirenal adipose tissue (PRAT) contribute to maintain pathological high BP, without affecting physiological BP. Bilateral PRAT ablation or denervation leads to a long-term reduction of high BP in spontaneous hypertensive rats (SHR), but has no effect on normal BP in control rats. Further, gain- and loss-of-function and neuron transcriptomics studies show that augmented activities and remodeling of L1-L2 dorsal root ganglia neurons are responsible for hypertension in SHR. Moreover, we went on to show that calcitonin gene-related peptide (CGRP) is a key endogenous suppressor of hypertension that is sequestered by pro-hypertensive PRAT in SHRs. Taken together, we identify PRAT afferent nerves as a pro-hypertensive node that sustains high BP via suppressing CGRP, thereby providing a therapeutic target to tackle primary hypertension.
Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease
Authors: Cadby Gemma , Giles Corey , Melton Phillip E. , Huynh Kevin , Mellett Natalie A. , Duong Thy , Nguyen Anh , Cinel Michelle , Smith Alex , Olshansky Gavriel , Wang Tingting , Brozynska Marta , Inouye Mike , McCarthy Nina S. , Ariff Amir , Hung Joseph , Hui Jennie , Beilby John , Dubé Marie-Pierre , Watts Gerald F. , Shah Sonia , Wray Naomi R. , Lim Wei Ling Florence , Chatterjee Pratishtha , Martins Ian , Laws Simon M. , Porter Tenielle , Vacher Michael , Bush Ashley I. , Rowe Christopher C. , Villemagne Victor L. , Ames David , Masters Colin L. , Taddei Kevin , Arnold Matthias , Kastenmüller Gabi , Nho Kwangsik , Saykin Andrew J. , Han Xianlin , Kaddurah-Daouk Rima , Martins Ralph N. , Blangero John , Meikle Peter J. , Moses Eric K. 
Published: June 2022

AbstractWe integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10−3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.
Identifying colorectal cancer caused by biallelic MUTYH pathogenic variants using
tumor mutational signatures
Authors: Georgeson Peter , Harrison Tabitha A. , Pope Bernard J. , Zaidi Syed H. , Qu Conghui , Steinfelder Robert S. , Lin Yi , Joo Jihoon E. , Mahmood Khalid , Clendenning Mark , Walker Romy , Amitay Efrat L. , Berndt Sonja I. , Brenner Hermann , Campbell Peter T. , Cao Yin , Chan Andrew T. , Chang-Claude Jenny , Doheny Kimberly F. , Drew David A. , Figueiredo Jane C. , French Amy J. , Gallinger Steven , Giannakis Marios , Giles Graham G. , Gsur Andrea , Gunter Marc J. , Hoffmeister Michael , Hsu Li , Huang Wen-Yi , Limburg Paul , Manson JoAnn E. , Moreno Victor , Nassir Rami , Nowak Jonathan A. , Obón-Santacana Mireia , Ogino Shuji , Phipps Amanda I. , Potter John D. , Schoen Robert E. , Sun Wei , Toland Amanda E. , Trinh Quang M. , Ugai Tomotaka , Macrae Finlay A. , Rosty Christophe , Hudson Thomas J. , Jenkins Mark A. , Thibodeau Stephen N. , Winship Ingrid M. , Peters Ulrike , Buchanan Daniel D. 
Published: June 2022

Abstract
Carriers of germline biallelic pathogenic variants in the
MUTYH gene have a high risk of colorectal cancer. We test
5649 colorectal cancers to evaluate the discriminatory potential of a tumor mutational
signature specific to MUTYH for identifying biallelic
carriers and classifying variants of uncertain clinical significance (VUS). Using a
tumor and matched germline targeted multi-gene panel approach, our classifier identifies
all biallelic MUTYH carriers and all known non-carriers in an
independent test set of 3019 colorectal cancers (accuracy = 100% (95% confidence
interval 99.87–100%)). All monoallelic MUTYH carriers are
classified with the non-MUTYH carriers. The classifier
provides evidence for a pathogenic classification for two VUS and a benign
classification for five VUS. Somatic hotspot mutations KRAS
p.G12C and PIK3CA p.Q546K are associated with colorectal
cancers from biallelic MUTYH carriers compared with
non-carriers (p = 2 × 10−23 and
p = 6 × 10−11, respectively). Here, we
demonstrate the potential application of mutational signatures to tumor sequencing
workflows to improve the identification of biallelic MUTYH
carriers.
Machine learning for exploring small polaron configurational space
Authors: Birschitzky Viktor C. , Ellinger Florian , Diebold Ulrike , Reticcioli Michele , Franchini Cesare 
Published: June 2022

AbstractPolaron defects are ubiquitous in materials and play an important role in many processes involving carrier mobility, charge transfer and surface reactivity. Determining small polarons’ spatial distributions is essential to understand materials properties and functionalities. However, the required exploration of the configurational space is computationally demanding when using first principles methods. Here, we propose a machine-learning (ML) accelerated search that determines the ground state polaronic configuration. The ML model is trained on databases of polaron configurations generated by density functional theory (DFT) via molecular dynamics or random sampling. To establish a mapping between configurations and their stability, we designed descriptors modelling the interactions among polarons and charged point defects. We used the DFT+ML protocol to explore the polaron configurational space for two surface-systems, reduced rutile TiO2(110) and Nb-doped SrTiO3(001). The ML-aided search proposes additional polaronic configurations and can be utilized to determine optimal polaron distributions at any charge concentration.
Data-driven analysis of process, structure, and properties of additively manufactured Inconel 718 thin walls
Authors: Fang Lichao , Cheng Lin , Glerum Jennifer A. , Bennett Jennifer , Cao Jian , Wagner Gregory J. 
Published: June 2022

AbstractIn additive manufacturing of metal parts, the ability to accurately predict the extremely variable temperature field in detail, and relate it quantitatively to structure and properties, is a key step in predicting part performance and optimizing process design. In this work, a finite element simulation of the directed energy deposition (DED) process is used to predict the space- and time-dependent temperature field during the multi-layer build process for Inconel 718 walls. The thermal model results show good agreement with dynamic infrared images captured in situ during the DED builds. The relationship between predicted cooling rate, microstructural features, and mechanical properties is examined, and cooling rate alone is found to be insufficient in giving quantitative property predictions. Because machine learning offers an efficient way to identify important features from series data, we apply a 1D convolutional neural network data-driven framework to automatically extract the dominant predictive features from simulated temperature history. Very good predictions of material properties, especially ultimate tensile strength, are obtained using simulated thermal history data. To further interpret the convolutional neural network predictions, we visualize the extracted features produced on each convolutional layer and compare the convolutional neural network detected features of thermal histories for high and low ultimate tensile strength cases. A key result is the determination that thermal histories in both high and moderate temperature regimes affect material properties.
Mechanical-robust and recyclable polyimide substrates coordinated with cyclic Ti-oxo cluster for flexible organic solar cells
Authors: Zhang Guangcong , Chen Qiaomei , Xie Chengcheng , Wang Yongmei , Zhao Chaowei , Xiao Chengyi , Wei Yen , Li Weiwei 
Published: June 2022

AbstractWith the rapid development of flexible optoelectronic devices, recyclability is highly desirable for alleviating resource waste and environmental pollution, but remains challenging. Here, a fully closed-loop recyclable crosslinked polyimide (RCPI) was fabricated via carboxyl ligand exchange between the CPI with pendent carboxyl groups and the cyclic Ti-oxo cluster (CTOC) with labile carboxyl ligands, which could be reconverted into reprocessable CPI and CTOC solution by pivalic acid. The RCPI-based embedded AgNWs@RCPI electrode shows comparable high conductivity, transparency and low roughness with ITO (indium tin oxide)/glass electrode, and meanwhile outstanding mechanical robustness. The related flexible organic solar cells (FOSCs) provided a high efficiency of 14.78% and maintained ~97% of the initial efficiency after 5000 bending cycles at a small bending radius of 1 mm. Moreover, the recyclability of the RCPI still retains after being manufactured into the FOSCs. This work provides a promising strategy for recyclable flexible optoelectronic devices.
Directed evolution and selection of biostable l-DNA aptamers with a mirror-image DNA polymerase
Authors: Chen Ji , Chen Mengyin , Zhu Ting F. 
Published: June 2022

AbstractMirror-image aptamers made from chirally inverted nucleic acids are nuclease-resistant and exceptionally biostable, opening up opportunities for unique applications. However, the directed evolution and selection of mirror-image aptamers directly from large randomized l-DNA libraries has,﻿ to our knowledge, not been demonstrated previously. Here, we developed a ‘mirror-image selection’ scheme for the directed evolution and selection of biostable l-DNA aptamers with a mirror-image DNA polymerase. We performed iterative rounds of enrichment and mirror-image polymerase chain reaction (PCR) amplification of l-DNA sequences that bind native human thrombin, in conjunction with denaturing gradient gel electrophoresis (DGGE) to isolate individual aptamers and l-DNA sequencing-by-synthesis to determine their sequences. Based on the selected l-DNA aptamers, we designed biostable thrombin sensors and inhibitors, which remained functional in physiologically relevant nuclease-rich environments, even in the presence of human serum that rapidly degraded d-DNA aptamers. Mirror-image selection of biostable l-DNA aptamers directly from large randomized l-DNA libraries greatly expands the range of biomolecules that can be targeted, broadening their applications as biostable sensors, therapeutics and basic research tools.
Improving preeclampsia risk prediction by modeling pregnancy trajectories from routinely collected electronic medical record data
Authors: Li Shilong , Wang Zichen , Vieira Luciana A. , Zheutlin Amanda B. , Ru Boshu , Schadt Emilio , Wang Pei , Copperman Alan B. , Stone Joanne L. , Gross Susan J. , Kao Yu-Han , Lau Yan Kwan , Dolan Siobhan M. , Schadt Eric E. , Li Li 
Published: June 2022

AbstractPreeclampsia is a heterogeneous and complex disease associated with rising morbidity and mortality in pregnant women and newborns in the US. Early recognition of patients at risk is a pressing clinical need to reduce the risk of adverse outcomes. We assessed whether information routinely collected in electronic medical records (EMR) could enhance the prediction of preeclampsia risk beyond what is achieved in standard of care assessments. We developed a digital phenotyping algorithm to curate 108,557 pregnancies from EMRs across the Mount Sinai Health System, accurately reconstructing pregnancy journeys and normalizing these journeys across different hospital EMR systems. We then applied machine learning approaches to a training dataset (N = 60,879) to construct predictive models of preeclampsia across three major pregnancy time periods (ante-, intra-, and postpartum). The resulting models predicted preeclampsia with high accuracy across the different pregnancy periods, with areas under the receiver operating characteristic curves (AUC) of 0.92, 0.82, and 0.89 at 37 gestational weeks, intrapartum and postpartum, respectively. We observed comparable performance in two independent patient cohorts. While our machine learning approach identified known risk factors of preeclampsia (such as blood pressure, weight, and maternal age), it also identified other potential risk factors, such as complete blood count related characteristics for the antepartum period. Our model not only has utility for earlier identification of patients at risk for preeclampsia, but given the prediction accuracy exceeds what is currently achieved in clinical practice, our model provides a path for promoting personalized precision therapeutic strategies for patients at risk.
Macrophage-derived exosomal aminopeptidase N aggravates sepsis-induced acute lung injury by regulating necroptosis of lung epithelial cell
Authors: Gong Ting , Zhang Xuedi , Peng Zhiyong , Ye Yinfeng , Liu Ruimeng , Yang Yinggui , Chen Zhugui , Zhang Zhihao , Hu Hongfei , Yin Shuang , Xu Yi , Tang Jing , Liu Youtan 
Published: June 2022

AbstractSepsis-induced acute lung injury (ALI) is a serious sepsis complication and the prevailing cause of death. Circulating plasma exosomes might exert a key role in regulating intercellular communication between immunological and structural cells, as well as contributing to sepsis-related organ damage. However, the molecular mechanisms by which exosome-mediated intercellular signaling exacerbate ALI in septic infection remains undefined. Therefore, we investigated the effect of macrophage-derived exosomal APN/CD13 on the induction of epithelial cell necrosis. Exosomal APN/CD13 levels in the plasma of septic mice and patients with septic ALI were found to be higher. Furthermore, increased plasma exosomal APN/CD13 levels were associated with the severity of ALI and fatality in sepsis patients. We found remarkably high expression of APN/CD13 in exosomes secreted by LPS-stimulated macrophages. Moreover, c-Myc directly induced APN/CD13 expression and was packed into exosomes. Finally, exosomal APN/CD13 from macrophages regulated necroptosis of lung epithelial cells by binding to the cell surface receptor TLR4 to induce ROS generation, mitochondrial dysfunction and NF-κB activation. These results demonstrate that macrophage-secreted exosomal APN/CD13 can trigger epithelial cell necroptosis in an APN/CD13-dependent manner, which provides insight into the mechanism of epithelial cell functional disorder in sepsis-induced ALI.
Comprehensive identification of SWI/SNF complex subunits underpins deep eukaryotic ancestry and reveals new plant components
Authors: Hernández-García Jorge , Diego-Martin Borja , Kuo Peggy Hsuanyu , Jami-Alahmadi Yasaman , Vashisht Ajay A. , Wohlschlegel James , Jacobsen Steven E. , Blázquez Miguel A. , Gallego-Bartolomé Javier 
Published: June 2022

AbstractOver millions of years, eukaryotes evolved from unicellular to multicellular organisms with increasingly complex genomes and sophisticated gene expression networks. Consequently, chromatin regulators evolved to support this increased complexity. The ATP-dependent chromatin remodelers of the SWI/SNF family are multiprotein complexes that modulate nucleosome positioning and appear under different configurations, which perform distinct functions. While the composition, architecture, and activity of these subclasses are well understood in a limited number of fungal and animal model organisms, the lack of comprehensive information in other eukaryotic organisms precludes the identification of a reliable evolutionary model of SWI/SNF complexes. Here, we performed a systematic analysis using 36 species from animal, fungal, and plant lineages to assess the conservation of known SWI/SNF subunits across eukaryotes. We identified evolutionary relationships that allowed us to propose the composition of a hypothetical ancestral SWI/SNF complex in the last eukaryotic common ancestor. This last common ancestor appears to have undergone several rounds of lineage-specific subunit gains and losses, shaping the current conformation of the known subclasses in animals and fungi. In addition, our results unravel a plant SWI/SNF complex, reminiscent of the animal BAF subclass, which incorporates a set of plant-specific subunits of still unknown function.
Proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort
Authors: Yang Jing , Jia Zhilong , Song Xinyu , Shi Jinlong , Wang Xiaoreng , Zhao Xiaojing , He Kunlun 
Published: June 2022

AbstractAscending to high-altitude by non-high-altitude natives is a well-suited model for studying acclimatization to extreme environments. Acute mountain sickness (AMS) is frequently experienced by visitors. The diagnosis of AMS mainly depends on a self-questionnaire, revealing the need for reliable biomarkers for AMS. Here, we profiled 22 AMS symptom phenotypes, 65 clinical indexes, and plasma proteomic profiles of AMS via a combination of proximity extension assay and multiple reaction monitoring of a longitudinal cohort of 53 individuals. We quantified 1069 proteins and validated 102 proteins. Via differential analysis, machine learning, and functional association analyses. We found and validated that RET played an important role in the pathogenesis of AMS. With high-accuracies (AUCs > 0.9) of XGBoost-based models, we prioritized ADAM15, PHGDH, and TRAF2 as protective, predictive, and diagnostic biomarkers, respectively. Our findings shed light on the precision medicine for AMS and the understanding of acclimatization to high-altitude environments.