bluuebunny/crossref_metadata_2025_split huggingface dataset:
Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends
Authors: Schlunegger Sarah , Rodgers Keith B. , Sarmiento Jorge L. , Ilyina Tatiana , Dunne John P. , Takano Yohei , Christian James R. , Long Matthew C. , Frölicher Thomas L. , Slater Richard , Lehner Flavio 
Published: July 2020

AbstractAnthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper‐ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change.
Uncertainties in Turbulent Statistics and Fluxes of CO2 Associated With Density Effect Corrections
Authors: Gao Zhongming , Liu Heping , Arntzen Evan , Mcfarland Douglas P. , Chen Xingyuan , Huang Maoyi 
Published: July 2020

AbstractDensity effect corrections (DECs) are applied to adjust raw CO2 fluxes measured by eddy covariance (EC) systems with open‐path gas analyzers. DEC is also required for adjusting the measured CO2 concentration fluctuations to obtain the adjusted CO2 concentrations for analyzing turbulent statistics or quantifying fluxes. However, our data show that the power spectra of the DEC‐adjusted CO2 concentrations are distorted in the high‐frequency range, as compared with the corresponding spectra of temperature and water vapor density. This contradicts the similarity behavior of scalars, as suggested by Monin‐Obukhov similarity theory. It is demonstrated that such a distortion is caused by the DEC‐induced spikes in the DEC‐adjusted CO2, altering turbulent statistics of CO2 and scalar similarity between CO2 and other scalars. Our results suggest that CO2 fluxes are overestimated by applying DEC especially under high Bowen ratio conditions, potentially leading to substantial uncertainties in long‐term ecosystem carbon exchange in dry regions.
Improving Wind Forecasts in the Lower Stratosphere by Distilling an Analog Ensemble Into a Deep Neural Network
Authors: Candido Salvatore , Singh Aakanksha , Delle Monache Luca 
Published: July 2020

AbstractWe discuss improving forecasts of winds in the lower stratosphere using machine learning to postprocess the output of the European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecast System. We postprocess global three‐dimensional predictions and demonstrate distilling the analog ensemble (AnEn) method into a deep neural network, which reduces postprocessing latency to near zero maintaining increased forecast skill. This approach reduces the error with respect to ECMWF high‐resolution deterministic prediction between 2–15% for wind speed and 15–25% for direction and is on par with ECMWF ensemble (ENS) forecast skill to hour 60. Verifying with Loon data from stratospheric balloons, AnEn has 20% lower error than ENS for wind speed and 15% for wind direction, despite significantly lower real‐time computational cost to ENS. Similar performance patterns are reported for probabilistic predictions, with larger improvements of AnEn with respect to ENS. We also demonstrate that AnEn generates a calibrated probabilistic forecast.
Determination of the Configurations of Boundaries in Space
Authors: Shen Chao , Zeng Gang , Zhang Chi , Rong Zhaojin , Dunlop M. , Russell C. T. , Escoubet C. Philippe , Ren Nian 
Published: July 2020

AbstractThis research aims to determine the geometrical configurations of boundary surfaces in the space environment, based on multiple spacecraft measurements. To achieve this, the Normal Field Analysis (NFA) method is presented here. With multipoint observations, the three‐dimensional gradient of the normal of boundary layers can be obtained, and the principal curvatures and principal directions of the surfaces can be deduced. The correctness of the method is then verified. Two initial applications have been carried out. The first is to determine the geometrical features of the Earth's bow shock where it is found that, with a one‐dimensional approximation, the surface of the bow shock has a rotational conicoid shape with eccentricity about 0.82, consistent with previous studies. Second, the method is also used to analyze two magnetotail dipolarization fronts showing that the dipolarization fronts are hyperbolic paraboloids or saddle surfaces with negative Gaussian curvatures. The south‐north scale of the dipolarization fronts is about 0.835–3.98 RE, and the dawn‐dusk/azimuthal scale is about 1.58–1.92 RE, confirming previous studies. The method presented can also be applied to investigate the geometries of the magnetopause, plasmapause, and other boundaries.
Groundwater Flow to Gale Crater in an Episodically Warm Climate
Authors: Baum Mark , Wordsworth Robin 
Published: July 2020

AbstractOrbiter and rover data have revealed a complex and intermittent hydrological history in Gale Crater on Mars, where habitable environments appear to have endured for at least thousands of years. The intermittency may be the result of a dominantly cold climate punctuated by geologically brief periods of warmth and active hydrology. However, the time required to establish an integrated hydrological cycle in a warming climate is difficult to ascertain and has not been thoroughly investigated. Here we model the transient evolution of groundwater flow and subsurface temperature, the slowest evolving components of the hydrological cycle, during a warm departure from cold conditions. We find that tens of thousands of years are likely required before groundwater could be a meaningful source for large lakes in Gale. With highly favorable conditions, primarily high permeability, significant flow might develop in thousands of years. This implies that surface water dominates during the beginning of a warm phase. Annual mean surface temperatures in Gale below 290 K would likely leave the nearby highlands frozen at the surface. In that case, deep aquifers beneath a highlands permafrost layer could deliver water to Gale, where low temperatures would have reduced evaporation.
Discontinuation of antidepressants after remission with antidepressant medication in major depressive disorder: a systematic review and meta-analysis
Authors: Kato Masaki , Hori Hikaru , Inoue Takeshi , Iga Junichi , Iwata Masaaki , Inagaki Takahiko , Shinohara Kiyomi , Imai Hissei , Murata Atsunobu , Mishima Kazuo , Tajika Aran 
Published: July 2020

AbstractA significant clinical issue encountered after a successful acute major depressive disorder (MDD) treatment is the relapse of depressive symptoms. Although continuing maintenance therapy with antidepressants is generally recommended, there is no established protocol on whether or not it is necessary to prescribe the antidepressant used to achieve remission. In this meta-analysis, the risk of relapse and treatment failure when either continuing with the same drug used to achieved remission or switching to a placebo was assessed in several clinically significant subgroups. The pooled odds ratio (OR) (±95% confidence intervals (CI)) was calculated using a random effects model. Across 40 studies (n = 8890), the relapse rate was significantly lower in the antidepressant group than the placebo group by about 20% (OR = 0.38, CI: 0.33–0.43, p < 0.00001; 20.9% vs 39.7%). The difference in the relapse rate between the antidepressant and placebo groups was greater for tricyclics (25.3%; OR = 0.30, CI: 0.17–0.50, p < 0.00001), SSRIs (21.8%; OR = 0.33, CI: 0.28–0.38, p < 0.00001), and other newer agents (16.0%; OR = 0.44, CI: 0.36–0.54, p < 0.00001) in that order, while the effect size of acceptability was greater for SSRIs than for other antidepressants. A flexible dose schedule (OR = 0.30, CI: 0.23–0.48, p < 0.00001) had a greater effect size than a fixed dose (OR = 0.41, CI: 0.36–0.48, p < 0.00001) in comparison to placebo. Even in studies assigned after continuous treatment for more than 6 months after remission, the continued use of antidepressants had a lower relapse rate than the use of a placebo (OR = 0.40, CI: 0.29–0.55, p < 0.00001; 20.2% vs 37.2%). The difference in relapse rate was similar from a maintenance period of 6 months (OR = 0.41, CI: 0.35–0.48, p < 0.00001; 19.6% vs 37.6%) to over 1 year (OR = 0.35, CI: 0.29–0.41, p < 0.00001; 19.9% vs 39.8%). The all-cause dropout of antidepressant and placebo groups was 43% and 58%, respectively, (OR = 0.47, CI: 0.40–0.55, p < 0.00001). The tolerability rate was ~4% for both groups. The rate of relapse (OR = 0.32, CI: 0.18–0.64, p = 0.0010, 41.0% vs 66.7%) and all-cause dropout among adolescents was higher than in adults. To prevent relapse and treatment failure, maintenance therapy, and careful attention for at least 6 months after remission is recommended. SSRIs are well-balanced agents, and flexible dose adjustments are more effective for relapse prevention.
ALDH2 contributes to melatonin-induced protection against APP/PS1 mutation-prompted cardiac anomalies through cGAS-STING-TBK1-mediated regulation of mitophagy
Authors: Wang Shuyi , Wang Lin , Qin Xing , Turdi Subat , Sun Dongdong , Culver Bruce , Reiter Russel J. , Wang Xiaoming , Zhou Hao , Ren Jun 
Published: July 2020

AbstractAmple clinical evidence suggests a high incidence of cardiovascular events in Alzheimer’s disease (AD), although neither precise etiology nor effective treatment is available. This study was designed to evaluate cardiac function in AD patients and APP/PS1 mutant mice, along with circulating levels of melatonin, mitochondrial aldehyde dehydrogenase (ALDH2) and autophagy. AD patients and APP/PS1 mice displayed cognitive and myocardial deficits, low levels of circulating melatonin, ALDH2 activity, and autophagy, ultrastructural, geometric (cardiac atrophy and interstitial fibrosis) and functional (reduced fractional shortening and cardiomyocyte contraction) anomalies, mitochondrial injury, cytosolic mtDNA buildup, apoptosis, and suppressed autophagy and mitophagy. APP/PS1 mutation downregulated cyclic GMP-AMP synthase (cGAS) and stimulator of interferon genes (STING) levels and TBK1 phosphorylation, while promoting Aβ accumulation. Treatment with melatonin overtly ameliorated unfavorable APP/PS1-induced changes in cardiac geometry and function, apoptosis, mitochondrial integrity, cytosolic mtDNA accumulation (using both immunocytochemistry and qPCR), mitophagy, and cGAS-STING-TBK1 signaling, although these benefits were absent in APP/PS1/ALDH2−/− mice. In vitro evidence indicated that melatonin attenuated APP/PS1-induced suppression of mitophagy and cardiomyocyte function, and the effect was negated by the nonselective melatonin receptor blocker luzindole, inhibitors or RNA interference of cGAS, STING, TBK1, and autophagy. Our data collectively established a correlation among cardiac dysfunction, low levels of melatonin, ALDH2 activity, and autophagy in AD patients, with compelling support in APP/PS1 mice, in which melatonin rescued myopathic changes by promoting cGAS-STING-TBK1 signaling and mitophagy via an ALDH2-dependent mechanism.
Establishment of bone marrow-derived M-CSF receptor-dependent self-renewing macrophages
Authors: Nasser Hesham , Adhikary Partho , Abdel-Daim Amira , Noyori Osamu , Panaampon Jutatip , Kariya Ryusho , Okada Seiji , Ma Wenjuan , Baba Masaya , Takizawa Hitoshi , Yamane Mariko , Niwa Hitoshi , Suzu Shinya 
Published: July 2020

AbstractRecent studies have revealed that tissue macrophages are derived from yolk sac precursors or fetal liver monocytes, in addition to bone marrow monocytes. The relative contribution of these cells to the tissue macrophage pool is not fully understood, but embryo-derived cells are supposed to be more important because of their capacity to self-renew. Here, we show the presence of adult bone marrow-derived macrophages that retain self-renewing capacity. The self-renewing macrophages were readily obtained by long-term culture of mouse bone marrow cells with macrophage colony-stimulating factor (M-CSF), a key cytokine for macrophage development. They were non-tumorigenic and proliferated in the presence of M-CSF in unlimited numbers. Despite several differences from non-proliferating macrophages, they retained many features of cells of the monocytic lineage, including the differentiation into dendritic cells or osteoclasts. Among the transcription factors involved in the self-renewal of embryonic stem cells, Krüppel-like factor 2 (KLF2) was strongly upregulated upon M-CSF stimulation in the self-renewing macrophages, which was accompanied by the downregulation of MafB, a transcription factor that suppresses KLF2 expression. Indeed, knockdown of KLF2 led to cell cycle arrest and diminished cell proliferation in the self-renewing macrophages. Our new cell model would be useful to unravel differences in phenotype, function, and molecular mechanism of proliferation among self-renewing macrophages with different origins.
Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide
Authors: Sivaraman Ganesh , Krishnamoorthy Anand Narayanan , Baur Matthias , Holm Christian , Stan Marius , Csányi Gábor , Benmore Chris , Vázquez-Mayagoitia Álvaro 
Published: July 2020

AbstractWe propose an active learning scheme for automatically sampling a minimum number of uncorrelated configurations for fitting the Gaussian Approximation Potential (GAP). Our active learning scheme consists of an unsupervised machine learning (ML) scheme coupled with a Bayesian optimization technique that evaluates the GAP model. We apply this scheme to a Hafnium dioxide (HfO2) dataset generated from a “melt-quench” ab initio molecular dynamics (AIMD) protocol. Our results show that the active learning scheme, with no prior knowledge of the dataset, is able to extract a configuration that reaches the required energy fit tolerance. Further, molecular dynamics (MD) simulations performed using this active learned GAP model on 6144 atom systems of amorphous and liquid state elucidate the structural properties of HfO2 with near ab initio precision and quench rates (i.e., 1.0 K/ps) not accessible via AIMD. The melt and amorphous X-ray structural factors generated from our simulation are in good agreement with experiment. In addition, the calculated diffusion constants are in good agreement with previous ab initio studies.
Specific targeting of IL-1β activity to CD8+ T cells allows for safe use as a vaccine adjuvant
Authors: Van Den Eeckhout Bram , Van Hoecke Lien , Burg Elianne , Van Lint Sandra , Peelman Frank , Kley Niko , Uzé Gilles , Saelens Xavier , Tavernier Jan , Gerlo Sarah 
Published: July 2020

AbstractAnnual administration and reformulation of influenza vaccines is required for protection against seasonal infections. However, the induction of strong and long-lasting T cells is critical to reach broad and potentially lifelong antiviral immunity. The NLRP3 inflammasome and its product interleukin-1β (IL-1β) are pivotal mediators of cellular immune responses to influenza, yet, overactivation of these systems leads to side effects, which hamper clinical applications. Here, we present a bypass around these toxicities by targeting the activity of IL-1β to CD8+ T cells. Using this approach, we demonstrate safe inclusion of IL-1β as an adjuvant in vaccination strategies, leading to full protection of mice against a high influenza virus challenge dose by raising potent T cell responses. In conclusion, this paper proposes a class of IL-1β-based vaccine adjuvants and also provides further insight in the mechanics of cellular immune responses driven by IL-1β.
MAGPEL: an autoMated pipeline for inferring vAriant-driven Gene PanEls from the full-length biomedical literature
Authors: Saberian Nafiseh , Shafi Adib , Peyvandipour Azam , Draghici Sorin 
Published: July 2020

AbstractIn spite of the efforts in developing and maintaining accurate variant databases, a large number of disease-associated variants are still hidden in the biomedical literature. Curation of the biomedical literature in an effort to extract this information is a challenging task due to: (i) the complexity of natural language processing, (ii) inconsistent use of standard recommendations for variant description, and (iii) the lack of clarity and consistency in describing the variant-genotype-phenotype associations in the biomedical literature. In this article, we employ text mining and word cloud analysis techniques to address these challenges. The proposed framework extracts the variant-gene-disease associations from the full-length biomedical literature and designs an evidence-based variant-driven gene panel for a given condition. We validate the identified genes by showing their diagnostic abilities to predict the patients’ clinical outcome on several independent validation cohorts. As representative examples, we present our results for acute myeloid leukemia (AML), breast cancer and prostate cancer. We compare these panels with other variant-driven gene panels obtained from Clinvar, Mastermind and others from literature, as well as with a panel identified with a classical differentially expressed genes (DEGs) approach. The results show that the panels obtained by the proposed framework yield better results than the other gene panels currently available in the literature.
Characterization of a novel STAT 2 knock-out hamster model of Crimean-Congo hemorrhagic fever virus pathogenesis
Authors: Ranadheera Charlene , Valcourt Emelissa J. , Warner Bryce M. , Poliquin Guillaume , Rosenke Kyle , Frost Kathy , Tierney Kevin , Saturday Greg , Miao Jinxin , Westover Jonna B. , Gowen Brian B. , Booth Stephanie , Feldmann Heinz , Wang Zhongde , Safronetz David 
Published: July 2020

AbstractCrimean-Congo hemorrhagic fever virus (CCHFV) is a tick-borne pathogen causing a febrile illness in humans, which can progress to hemorrhagic manifestations, multi-organ failure, and death. Current mouse models of CCHFV infection reliably succumb to virus challenge but vary in their ability to reflect signs of disease similar to humans. In this study, we established a signal transducer and activator of transcription 2 (STAT2) knockout hamster model to expand the repertoire of animal models of CCHFV pathogenesis that can be used for therapeutic development. These hamsters demonstrated a systemic and lethal disease in response to infection. Hallmarks of human disease were observed including petechial rash, blood coagulation dysfunction, and various biochemistry and blood cell count abnormalities. Furthermore, we also demonstrated the utility of this model for anti-CCHFV therapeutic evaluation. The STAT2 knock-out hamster model of CCHFV infection may provide some further insights into clinical disease, viral pathogenesis, and pave the way for testing of potential drug and vaccine candidates.
Prospective evaluation and classification of endoscopic findings for ureteral calculi
Authors: Hamamoto Shuzo , Okada Shinsuke , Inoue Takaaki , Sugino Teruaki , Unno Rei , Taguchi Kazumi , Ando Ryosuke , Okada Atsushi , Miura Hiroyasu , Matsuda Tadashi , Yasui Takahiro 
Published: July 2020

AbstractDifficulty in performing ureteroscopic lithotripsy (URSL) depends on endoscopic findings surrounding calculi. In this multicentre prospective cohort study of 185 patients with a single ureteral stone who underwent ureteroscopic lithotripsy registered in the SMART study between January 2014 and February 2017, we established a classification of endoscopic findings and analysed risk factors for ureteral changes. We evaluated endoscopic findings (oedema, polyps, ureteral mucosa-stone adherence, and distal ureteric tightness) based on the SMART classification. Operative time and ureteral injuries were significantly correlated with endoscopic finding grades. Multivariate analyses revealed that mucosa-stone adherence (MSA) was strongly affected by hydronephrosis grade (odds ratio, 12.4; p = 0.022) and the interval before surgery (odds ratio, 1.10; p = 0.012). The cutoff value for MSA was 98 days, with a predictive accuracy of 0.78. Risk factors for distal ureteric tightness were age (odds ratio, 0.96; p = 0.004) and early intervention (odds ratio, 0.90; p = 0.023). The cutoff value was 34 days, with a predictive accuracy of 0.72. In conclusion, appropriate intervention around 34 days (limited to 98 days) after symptom onset is necessary for treating ureteral calculi. Even if intervention passed 98 days post-symptom onset, staged URSL, alternative procedures, and detailed informed consent should be planned in advance, assuming strong MSA.
Effects of prey trophic mode on the gross-growth efficiency of marine copepods: the case of mixoplankton
Authors: Traboni Claudia , Calbet Albert , Saiz Enric 
Published: July 2020

AbstractCopepod reproductive success largely depends on food quality, which also reflects the prey trophic mode. As such, modelling simulations postulate a trophic enhancement to higher trophic levels when mixotrophy is accounted in planktonic trophodynamics. Here, we tested whether photo-phagotrophic protists (mixoplankton) could enhance copepod gross-growth efficiency by nutrient upgrading mechanisms compared to obligate autotrophs and heterotrophs. To validate the hypothesis, we compared physiological rates of the copepod Paracartia grani under the three functional nutrition types. Ingestion and egg production rates varied depending on prey size and species, regardless of the diet. The gross-growth efficiency was variable and not significantly different across nutritional treatments, ranging from 3 to 25% in the mixoplanktonic diet compared to autotrophic (11–36%) and heterotrophic (8–38%) nutrition. Egg hatching and egestion rates were generally unaffected by diet. Overall, P. grani physiological rates did not differ under the tested nutrition types due to the large species-specific variation within trophic mode. However, when we focused on a single species, Karlodinium veneficum, tested as prey under contrasting trophic modes, the actively feeding dinoflagellate boosted the egestion rate and decreased the copepod gross-growth efficiency compared to the autotrophic ones, suggesting possible involvement of toxins in modulating trophodynamics other than stoichiometric constraints.