bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electron Signatures of Reconnection in a Global eVlasiator Simulation
Authors: Alho M. , Battarbee M. , Pfau‐Kempf Y. , Khotyaintsev Yu. V. , Nakamura R. , Cozzani G. , Ganse U. , Turc L. , Johlander A. , Horaites K. , Tarvus V. , Zhou H. , Grandin M. , Dubart M. , Papadakis K. , Suni J. , George H. , Bussov M. , Palmroth M. 
Published: June 2022

AbstractGeospace plasma simulations have progressed toward more realistic descriptions of the solar wind–magnetosphere interaction from magnetohydrodynamic to hybrid ion‐kinetic, such as the state‐of‐the‐art Vlasiator model. Despite computational advances, electron scales have been out of reach in a global setting. eVlasiator, a novel Vlasiator submodule, shows for the first time how electromagnetic fields driven by global hybrid‐ion kinetics influence electrons, resulting in kinetic signatures. We analyze simulated electron distributions associated with reconnection sites and compare them with Magnetospheric Multiscale (MMS) spacecraft observations. Comparison with MMS shows that key electron features, such as reconnection inflows, heated outflows, flat‐top distributions, and bidirectional streaming, are in remarkable agreement. Thus, we show that many reconnection‐related features can be reproduced despite strongly truncated electron physics and an ion‐scale spatial resolution. Ion‐scale dynamics and ion‐driven magnetic fields are shown to be significantly responsible for the environment that produces electron dynamics observed by spacecraft in near‐Earth plasmas.
Deriving Full‐Coverage and Fine‐Scale XCO2 Across China Based on OCO‐2 Satellite Retrievals and CarbonTracker Output
Authors: He Changpei , Ji Mingrui , Li Tao , Liu Xinyi , Tang Die , Zhang Shifu , Luo Yuzhou , Grieneisen Michael L. , Zhou Zihang , Zhan Yu 
Published: June 2022

AbstractDue to the coarse spatial resolution, the column‐averaged dry‐air mole fraction of CO2 (XCO2) data from the CarbonTracker may be inadequate to reflect the spatial heterogeneity of XCO2. We developed a machine learning model to fill the data gaps in the Orbiting Carbon Observatory 2 satellite retrievals across China during 2015–2018, with cross‐validation R2 = 0.95 and RMSE = 0.91 ppm. Based on the gap‐filled data set, the multiyear average XCO2 was the highest in East China (405.71 ± 3.72 ppm) and the lowest in Northwest China (403.99 ± 3.47 ppm). At the national level, the multiyear seasonal XCO2 varied from 402.54 ± 3.95 ppm in summer to 406.28 ± 3.19 ppm in spring. While the XCO2 kept increasing, the rate of increase declined from 3.23 to 2.10 ppm/year. The machine learning approach is feasible for downscaling and calibrating the CarbonTracker XCO2 data. The full‐coverage and fine‐scale XCO2 data set is expected to advance our understanding of the carbon cycles.
Tree Rings Reveal Unmatched 2nd Century Drought in the Colorado River Basin
Authors: Gangopadhyay Subhrendu , Woodhouse Connie A. , McCabe Gregory J. , Routson Cody C. , Meko David M. 
Published: June 2022

AbstractThe ongoing 22‐year drought in the Upper Colorado River Basin (UCRB) has been extremely severe, even in the context of the longest available tree‐ring reconstruction of annual flow at Lees Ferry, Arizona, dating back to 762 CE. While many southwestern drought assessments have been limited to the past 1,200 years, longer paleorecords of moisture variability do exist for the UCRB. Here, gridded drought‐atlas data in the UCRB domain along with naturalized streamflow data from the instrumental period (1906–2021) are used in a K‐nearest neighbor nonparametric algorithm to develop a streamflow reconstruction for the Lees Ferry gage starting in 1 CE. The reconstruction reveals a second‐century drought unmatched in severity by the current drought or by well‐documented medieval period droughts in the UCRB. Although data are sparse, analysis of individual long tree‐ring records and other paleoclimatic data also support the occurrence of an exceptional second‐century drought.
A Global Perspective on Lunar Granular Flows
Authors: Bickel V. T. , Loew S. , Aaron J. , Goedhart N. 
Published: June 2022

AbstractDry granular flows are ubiquitous, yet poorly understood mass wasting features on the Moon. Above all, their global distribution, relation to the physical environment, and drivers are poorly understood. Here, we build and deploy a convolutional neural network and map 28,101 flow features between 60°N and S by scanning through ∼150,000 Lunar Reconnaissance Orbiter images. We observe that flows are heterogeneously distributed over the Moon, where all major hotspots are located in craters and almost all hotspots are located in the nearside maria. We further observe that younger surfaces feature higher flow feature densities, while pre‐Nectarian terranes can still host flows, remaining subject to active erosion billions of years after their formation. Our observations suggest that impacts at various scales have been—and likely still are—acting as the main, global‐scale, long‐ and short‐term driver of flow occurrence, strongly influenced by the properties of the target rock material.
Reevaluating Links Between Meteorite Impacts and Early Cenozoic Global Warming
Authors: Zorzi A. , Tikoo S. M. , Beroza G. C. , Sleep N. H. 
Published: June 2022

AbstractThe Paleocene‐Eocene Thermal Maximum (PETM) and the lower Chron 29n hyperthermal event were recently proposed to have been triggered by the meteorite impacts that formed the Marquez Dome (Texas, USA; 58.3 ± 3.1 Ma) and Boltysh (Ukraine; 65.39 ± 0.14 Ma) craters, respectively. We use shock physics hydrocode simulations and radiative forcing calculations to quantify the expected global temperature increase associated with impacts of different scales via the release of CO2 and CH4 sourced from target rocks into the atmosphere. Our results suggest that the <2 km diameter impactors associated with the Marquez Dome and Boltysh craters were too small to have induced hyperthermal‐like (>1 K) temperature changes, even if target rocks were carbon‐rich; >10 km diameter impactors may produce hyperthermal events, but such large impacts are predicted to be uncommon during the Cenozoic era (2–4 objects per Gyr).
Diverse P‐T‐t Paths Reveal High‐Grade Metamorphosed Forearc Complexes in NW China
Authors: Wang Hao , Xiao Wenjiao , Windley Brian F. , Zhang Qian W. L. , Tan Zhou , Wu Chunming , Shi Mengyan 
Published: June 2022

AbstractSubduction zones provide important constraints on reconstruction of tectonic configurations and convergent geodynamics. The timing and evolution of the subduction zones at the interaction between the Paleo‐Asian and Tethyan Oceans remain ambiguous, casting significant uncertainty on the reconstructions of proto‐Asia and subduction dynamics. Here, we report new petrologic and geochronologic data of a high‐grade metamorphic complex in the Dunhuang area, NW China, together with thermodynamic modeling, geothermobarometry, and second ion mass spectrometry U‐Pb chronology to reveal the complex metamorphic structure and history of the Paleozoic subduction‐exhumation channel at the intersection of the Paleo‐Asian and Tethyan domains. The subduction zone contains a diverse collection of eclogite, high‐pressure (HP) granulites, amphibolites, and metasedimentary rocks with a broad spectrum of P‐T‐t paths, which were buried and exhumed at different depths at ∼463–411 Ma. Our first dating of the oldest (∼463 Ma) HP granulite extends the orogenic period earlier to the Middle Ordovician. The uneven change in subduction gradients from ∼18°C/km to ∼10°C/km illustrates the thermal evolution of the subduction zone from infancy to maturity. A dramatic drop of the gradient at ∼420 Ma suggests a potential short‐term switch of the subduction dynamics from “hot” to “cool,” possibly due to plate geometry reorganization in response to slab roll‐back. Our data demonstrate that the Dunhuang Complex was chaotically mixed and juxtaposed at different levels in the subduction‐exhumation channel. The southward younging and increase in depth of the HP metamorphism indicate that the Dunhuang Complex was formed by north‐dipping subduction of the Proto‐Tethyan Ocean from the Early Paleozoic.
Structured Exposure in an Unstructured Setting: Case Study of Parental Exposure Intervention to Increase Parental Mastery of Medical Care During Inpatient Hospitalization
Authors: Albright Dana K. , Kullgren Kristin A. , Andersen Melissa N. 
Published: June 2022

Objective: Parental stress can have an impact on health outcomes of chronically ill children ( Cousino & Hazen, 2013 ). Pediatric psychologists are well suited to address these issues with understanding of empirically supported treatments, impact of mental health on medical care behaviors, and parent–child interactions ( Ernst et al., 2015 ). Use of empirically supported treatments, such as graduated exposure therapy (ET), within an uncontrolled environment such as an inpatient setting can be challenging. This case study illustrates adaptation of ET in an inpatient setting to address parental mastery of medical care. Method: ET was implemented with a mother of an infant with a newly placed tracheostomy to reduce her severe anxiety that was preventing her from interacting with her infant or engaging in medical care necessary for hospital discharge. Results: Through 31 exposure sessions, the patient’s mother met all four treatment targets: daily tracheostomy care, stoma desensitization, tracheostomy tube changes, and suctioning. Self-reported distress data were presented for each exposure. Conclusions: Use of ET with a clear treatment plan and coordinated multidisciplinary inpatient team efforts can successfully reduce severe parental anxiety that is impeding medical care, hindering parent–child interaction, and interfering with parental ability to care for a child with complex medical needs. This article discusses multiple factors that are unique to the inpatient setting and the target behaviors for consideration. Implications for Impact Statement This case highlights the use of empirically supported treatments to target complex parent behaviors in a pediatric inpatient setting. Reducing barriers to discharge, such as inability to demonstrate adequate medical care, promotes better patient and family outcomes.
Meta-analysis of mucosal microbiota reveals universal microbial signatures and dysbiosis in gastric carcinogenesis
Authors: Liu Changan , Ng Siu-Kin , Ding Yanqiang , Lin Yufeng , Liu Weixin , Wong Sunny Hei , Sung Joseph Jao-Yiu , Yu Jun 
Published: June 2022

AbstractThe consistency of the associations between gastric mucosal microbiome and gastric cancer across studies remained unexamined. We aimed to identify universal microbial signatures in gastric carcinogenesis through a meta-analysis of gastric microbiome from multiple studies. Compositional and ecological profiles of gastric microbes across stages of gastric carcinogenesis were significantly altered. Meta-analysis revealed that opportunistic pathobionts Fusobacterium, Parvimonas, Veillonella, Prevotella and Peptostreptococcus were enriched in GC, while commensals Bifidobacterium, Bacillus and Blautia were depleted in comparison to SG. The co-occurring correlation strengths of GC-enriched bacteria were increased along disease progression while those of GC-depleted bacteria were decreased. Eight bacterial taxa, including Veillonella, Dialister, Granulicatella, Herbaspirillum, Comamonas, Chryseobacterium, Shewanella and Helicobacter, were newly identified by this study as universal biomarkers for robustly discriminating GC from SG, with an area under the curve (AUC) of 0.85. Moreover, H. pylori-positive samples exhibited reduced microbial diversity, altered microbiota community and weaker interactions among gastric microbes. Our meta-analysis demonstrated comprehensive and generalizable gastric mucosa microbial features associated with histological stages of gastric carcinogenesis, including GC associated bacteria, diagnostic biomarkers, bacterial network alteration and H. pylori influence.
Big data, machine learning, and population health: predicting cognitive outcomes in childhood
Authors: Bowe Andrea K. , Lightbody Gordon , Staines Anthony , Murray Deirdre M. 
Published: June 2022

Abstract
The application of machine learning (ML) to address population health challenges has received much less attention than its application in the clinical setting. One such challenge is addressing disparities in early childhood cognitive development—a complex public health issue rooted in the social determinants of health, exacerbated by inequity, characterised by intergenerational transmission, and which will continue unabated without novel approaches to address it. Early life, the period of optimal neuroplasticity, presents a window of opportunity for early intervention to improve cognitive development. Unfortunately for many, this window will be missed, and intervention may never occur or occur only when overt signs of cognitive delay manifest. In this review, we explore the potential value of ML and big data analysis in the early identification of children at risk for poor cognitive outcome, an area where there is an apparent dearth of research. We compare and contrast traditional statistical methods with ML approaches, provide examples of how ML has been used to date in the field of neurodevelopmental disorders, and present a discussion of the opportunities and risks associated with its use at a population level. The review concludes by highlighting potential directions for future research in this area.

Impact

To date, the application of machine learning to address population health challenges in paediatrics lags behind other clinical applications. This review provides an overview of the public health challenge we face in addressing disparities in childhood cognitive development and focuses on the cornerstone of early intervention.

Recent advances in our ability to collect large volumes of data, and in analytic capabilities, provide a potential opportunity to improve current practices in this field.

This review explores the potential role of machine learning and big data analysis in the early identification of children at risk for poor cognitive outcomes.
Post-transplant cyclophosphamide and sirolimus based graft-versus-host disease prophylaxis after allogeneic stem cell transplantation for acute myeloid leukemia
Authors: Lazzari Lorenzo , Balaguer-Roselló Aitana , Montoro Juan , Greco Raffaella , Hernani Rafael , Lupo-Stanghellini Maria Teresa , Villalba Marta , Giglio Fabio , Facal Ana , Lorentino Francesca , Guerreiro Manuel , Bruno Alessandro , Pérez Ariadna , Xue Elisabetta , Clerici Daniela , Piemontese Simona , Piñana José Luis , Sanz Miguel Ángel , Solano Carlos , de la Rubia Javier , Ciceri Fabio , Peccatori Jacopo , Sanz Jaime 
Published: June 2022

AbstractPost-transplant cyclophosphamide (PTCy) has emerged as a promising graft-versus-host disease (GvHD) prophylaxis in allogeneic hematopoietic stem cell transplantation (allo-HSCT). However, no studies have reported the efficacy of a GvHD prophylaxis based on PTCy with sirolimus (Sir-PTCy) in patients with acute myeloid leukemia (AML). In this retrospective study, we analyze the use of sirolimus in combination with PTCy, with or without mycophenolate mofetil (MMF), on 242 consecutive adult patients with AML undergoing a myeloablative first allo-HSCT from different donor types, in three European centers between January 2017 and December 2020. Seventy-seven (32%) patients received allo-HSCT from HLA-matched sibling donor, 101 (42%) from HLA-matched and mismatched unrelated donor, and 64 (26%) from haploidentical donor. Except for neutrophil and platelet engraftment, which was slower in the haploidentical cohort, no significant differences were observed in major transplant outcomes according to donor type in univariate and multivariate analysis. GvHD prophylaxis with Sir-PTCy, with or without MMF, is safe and effective in patients with AML undergoing myeloablative allo-HSCT, resulting in low rates of transplant-related mortality, relapse/progression, and acute and chronic GvHD in all donor settings.
Splicing analyses for variants in MMR genes: best practice recommendations from the European Mismatch Repair Working Group
Authors: Morak Monika , Pineda Marta , Martins Alexandra , Gaildrat Pascaline , Tubeuf Hélène , Drouet Aurélie , Gómez Carolina , Dámaso Estela , Schaefer Kerstin , Steinke-Lange Verena , Koehler Udo , Laner Andreas , Hauchard Julie , Chauris Karine , Holinski-Feder Elke , Capellá Gabriel 
Published: June 2022

AbstractOver 20% of the DNA mismatch repair (MMR) germline variants in suspected Lynch syndrome patients are classified as variants of uncertain significance (VUS). Well-established functional assays are pivotal for assessing the biological impact of these variants and provide relevant evidence for clinical classification. In our collaborative European Mismatch Repair Working Group (EMMR-WG) we compared three different experimental approaches for evaluating the effect of seven variants on mRNA splicing in MMR genes: (i) RT-PCR of full-length transcripts (FLT), (ii) RT-PCR of targeted transcript sections (TTS), both from patient biological samples and (iii) minigene splicing assays. An overall good concordance was observed between splicing patterns in TTS, FLT and minigene analyses for all variants. The FLT analysis depicted a higher number of different isoforms and mitigated PCR-bias towards shorter isoforms. TTS analyses may miss aberrant isoforms and minigene assays may under/overestimate the severity of certain splicing defects. The interpretation of the experimental findings must be cautious to adequately discriminate abnormal events from physiological complex alternative splicing patterns. A consensus strategy for investigating the impact of MMR variants on splicing was defined. First, RNA should be obtained from patient’s cell cultures (such as fresh lymphocyte cultures) incubated with/without a nonsense-mediated decay inhibitor. Second, FLT RT-PCR analysis is recommended to oversee all generated isoforms. Third, TTS analysis and minigene assays are useful independent approaches for verifying and clarifying FLT results. The use of several methodologies is likely to increase the strength of the experimental evidence which contributes to improve variant interpretation.
Precocious puberty in a case of Simpson–Golabi–Behmel syndrome with a de novo 240-kb deletion including GPC3
Authors: Watanabe Keisuke , Noguchi Atsuko , Takahashi Ikuko , Yamada Mamiko , Suzuki Hisato , Takenouchi Toshiki , Kosaki Kenjiro , Takahashi Tsutomu 
Published: June 2022

AbstractHere, we report a Japanese patient with Simpson–Golabi–Behmel syndrome involving a de novo 240-kb deletion including a part of GPC3. The patient showed pre- and postnatal macrosomia associated with coarse face, macrocephaly, supernumerary nipples, and cryptorchidism and characteristically presented with precocious puberty, mostly evaluated as advanced pubertal age of 15 years at the chronological age of 11.5 years.
Learning emergent partial differential equations in a learned emergent space
Authors: Kemeth Felix P. , Bertalan Tom , Thiem Thomas , Dietrich Felix , Moon Sung Joon , Laing Carlo R. , Kevrekidis Ioannis G. 
Published: June 2022

AbstractWe propose an approach to learn effective evolution equations for large systems of interacting agents. This is demonstrated on two examples, a well-studied system of coupled normal form oscillators and a biologically motivated example of coupled Hodgkin-Huxley-like neurons. For such types of systems there is no obvious space coordinate in which to learn effective evolution laws in the form of partial differential equations. In our approach, we accomplish this by learning embedding coordinates from the time series data of the system using manifold learning as a first step. In these emergent coordinates, we then show how one can learn effective partial differential equations, using neural networks, that do not only reproduce the dynamics of the oscillator ensemble, but also capture the collective bifurcations when system parameters vary. The proposed approach thus integrates the automatic, data-driven extraction of emergent space coordinates parametrizing the agent dynamics, with machine-learning assisted identification of an emergent PDE description of the dynamics in this parametrization.
Effectiveness of BBIBP-CorV vaccine against severe outcomes of COVID-19 in Abu Dhabi, United Arab Emirates
Authors: Al Kaabi Nawal , Oulhaj Abderrahim , Ganesan Subhashini , Al Hosani Farida Ismail , Najim Omer , Ibrahim Halah , Acuna Juan , Alsuwaidi Ahmed R. , Kamour Ashraf M. , Alzaabi Ashraf , Al Shehhi Badreyya Ahmed , Al Safar Habiba , Hussein Salah Eldin , Abdalla Jehad Saleh , Al Mansoori Dalal Saeed Naser , Al Hammadi Ahmed Abdul Kareem , Amari Mohammed A. , Al Romaithi Ahmed Khamis , Weber Stefan , Elavalli Santosh , Eltantawy Islam , Alghaithi Noura Khamis , Al Azazi Jumana Nafiz , Holt Stephen Geoffrey , Mostafa Mohamed , Halwani Rabih , Khalak Hanif , Elamin Wael , Beiram Rami , Zaher Walid 
Published: June 2022

AbstractThe effectiveness of the inactivated BBIBP-CorV vaccine against severe COVID-19 outcomes (hospitalization, critical care admission and death due to COVID-19) and its long-term effectiveness have not been well characterized among the general population. We conducted a retrospective cohort study using electronic health records of 3,147,869 adults, of which 1,099,886 vaccinated individuals were matched, in a 1:1 ratio to 1,099,886 unvaccinated persons. A Cox-proportional hazard model with time varying coefficients was used to assess the vaccine effectiveness adjusting for age, sex, comorbidity, ethnicity, and the calendar month of entry into the study. Our analysis showed that the effectiveness was 79.6% (95% CI, 77.7 to 81.3) against hospitalization, 86% (95% CI, 82.2 to 89.0) against critical care admission, and 84.1% (95% CI, 70.8 to 91.3) against death due to COVID-19. The effectiveness against these severe outcomes declined over time indicating the need for booster doses to increase protection against severe COVID-19 outcomes.
Teaming up main group metals with metallic iron to boost hydrogenation catalysis
Authors: Färber Christian , Stegner Philipp , Zenneck Ulrich , Knüpfer Christian , Bendt Georg , Schulz Stephan , Harder Sjoerd 
Published: June 2022

AbstractHydrogenation of unsaturated bonds is a key step in both the fine and petrochemical industries. Homogeneous and heterogeneous catalysts are historically based on noble group 9 and 10 metals. Increasing awareness of sustainability drives the replacement of costly, and often harmful, precious metals by abundant 3d-metals or even main group metals. Although not as efficient as noble transition metals, metallic barium was recently found to be a versatile hydrogenation catalyst. Here we show that addition of finely divided Fe0, which itself is a poor hydrogenation catalyst, boosts activities of Ba0 by several orders of magnitude, enabling rapid hydrogenation of alkynes, imines, challenging multi-substituted alkenes and non-activated arenes. Metallic Fe0 also boosts the activity of soluble early main group metal hydride catalysts, or precursors thereto. This synergy originates from cooperativity between a homogeneous, highly reactive, polar main group metal hydride complex and a heterogeneous Fe0 surface that is responsible for substrate activation.