bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of Nitrate Isotopes Between the South China Sea and Western North Pacific Ocean: Insights Into Biogeochemical Signals and Water Exchange
Authors: Yang Jin‐Yu Terence , Tang Jin‐Ming , Kang Sijing , Dai Minhan , Kao Shuh‐Ji , Yan Xiuli , Xu Min Nina , Du Chuanjun 
Published: April 2022

AbstractReconstructing past changes in the oceanic nitrate inventory with sedimentary N records in the South China Sea (SCS), which is the terminal of North Pacific Intermediate Water (NPIW), has regional and global implications. However, water‐column nitrate cycling that affects N isotope preservation remains poorly understood in the SCS. We present a new data set of nitrate isotopes ( and ) to elucidate nitrate dynamics in the SCS and the adjoining western North Pacific Ocean (wNPO). Greater increases in than in are observed in the SCS euphotic zone, suggesting a combined effect of partial nitrate assimilation and nitrification. In the subsurface and thermocline waters of both regions, upward disproportional decreases in and accompanied by elevated nitrate anomalies (N*) indicate an accumulation of external N. Such changes are less significant in the SCS due to higher nitrate concentrations therein, although external N influxes are comparable in both regions. High and values in the wNPO intermediate water result from the lateral transport of NPIW with isotopically more enriched nitrate from the remote denitrification zones followed by mixing with overlying water containing isotopically depleted nitrate. As NPIW flows into the SCS, its isotopically enriched signal is further diluted by strong vertical mixing with overlying and underlying waters in the interior. Compared to its source water from the wNPO, the SCS deep water has consistent nitrate isotopic compositions but significantly lower N*, indicating increased benthic denitrification at the wNPO margins with an estimated rate of 0.26–0.41 mmol N m−2 day−1.
Parameterization of Stochastically Entraining Convection Using Machine Learning Technique
Authors: Shin Jihoon , Baik Jong‐Jin 
Published: April 2022

AbstractA stochastic mixing model with a machine learning technique is proposed for mass flux convection schemes. The model consists of the stochastic differential equations (SDEs) for the fractional entrainment rate, fractional detrainment rate, fractional dilution rate, and vertical acceleration. Unknowns in SDEs are parameterized using a deep neural network with the inputs of cloud and environment properties. The deep neural network is found to predict entrainment and detrainment rates better than previously proposed parameterizations. The new mixing model is implemented in a unified convection scheme (UNICON) and tested in a single‐column mode for two marine shallow convection cases. It is shown that the simulations with the new mixing model produce realistic mean and variance of various convective updraft properties and that the appropriate amount of stochasticity is generated. Consistently accurate simulations of updraft mass fluxes and moist conserved variables reduce model errors in the original UNICON. Additional sensitivity simulations enabling or disabling the stochasticity in mixing and initialization suggest that most of the cloud variabilities are generated from the mixing process.
Comparison of Seven Weibull Distribution Models for Predicting Relative Hydraulic Conductivity
Authors: Shan Jipeng , Yang Zhenlei , Kuang Xingxing , Li Ling , Liu Junguo 
Published: April 2022

AbstractModeling water flow in unsaturated soils requires accurate characterization of relative hydraulic conductivity (RHC) and water retention curve (WRC). The overall objective of this study is to investigate the performances of seven Weibull distribution models for predicting RHC using the Assouline et al. (1998), https://doi.org/10.1029/97WR03039 WRC. Specifically, a new RHC model was proposed via the approach of Assouline (2001), https://doi.org/10.1029/2000WR900254 with the assumptions of Burdine (1953), https://doi.org/10.2118/225-G and Kosugi (1999), https://doi.org/10.2136/sssaj1999.03615995006300020003x. The proposed model, together with the other six models, was then compared with data from 40 soils to explore their predictive performances for RHC. The results showed that the proposed model provides the best agreement with measured data and yields a 16.1% improvement in RHC prediction compared to the widely used Assouline et al. (1998), https://doi.org/10.1029/97WR03039‐Mualem (1976), https://doi.org/10.1029/WR012i003p00513 model. The proposed model can be used as RHC parameterization for water flow modeling in the unsaturated zone.
Experimental Support for a Simplified Approach to CTRW Transport Models and Exploration of Parameter Interpretation
Authors: Hansen Scott K. 
Published: April 2022

AbstractWe empirically test our earlier theoretical arguments about simplification of continuous‐time random walk (CTRW) solute transport models, namely that without loss of generality the velocity‐like term, vψ, may be set to mean groundwater velocity, the dispersion‐like term, Dψ, defined by a classical, velocity‐independent dispersivity, and the so‐called time constant, τ, to unity. We also argue that for small‐scale heterogeneous advection (HA) and mobile‐immobile mass transfer (MIMT) CTRW transition time distributions, ψ(t), are unaffected by mean flow velocity. To experimentally test these claims, we re‐analyze two bench‐scale transport experiments—one for HA, one for MIMT—each performed at multiple flow rates in otherwise identical conditions, and show it is possible to simultaneously explain all breakthrough curves in each, subject to the above constraints. We compare our calibrations with earlier efforts for the same data sets. In the HA calibration we identify a ψ(t) of the same functional form as previous authors, and which yielded breakthrough predictions essentially identical to theirs, but with greatly differing parameters. This illustrates how values of individual CTRW parameters may not map one‐to‐one onto underlying physics. We recommend reporting complete model descriptions, discuss how the simplified approach assists in this and other theoretical considerations.
Improved Understanding of How Catchment Properties Control Hydrological Partitioning Through Machine Learning
Authors: Cheng Shujie , Cheng Lei , Qin Shujing , Zhang Lu , Liu Pan , Liu Liu , Xu Zhicheng , Wang Qilin 
Published: April 2022

AbstractLong‐term hydrological partitioning of catchments can be well described by the Budyko framework with a parameter (e.g., Fu's equations with parameter ω). The Budyko framework considers aridity index as the dominant control on hydrological partitioning, while the parameter represents integrated influences of catchment properties. Our understanding regarding the controls of catchment properties on the parameter is still limited. In this study, two machine learning methods, that is, boosted regression tree (BRT) and CUBIST, were used to model ω. Interpretable machine learning methods were adopted for better physical understanding including feature importance, accumulated local effects (ALE), and local interpretable model‐agnostic explanations. Among the 15 properties of 443 Australian catchments, analysis of feature importance showed that root zone storage capacity (SR), vapor pressure, vegetation coverage (M), precipitation depth, climate seasonality and asynchrony index (SAI), and water use efficiency (WUE) were the six primary control factors on ω. ALE showed that ω varied nonlinearly with all factors, and varied non‐monotonically with M, SAI, and WUE. LIME showed that the importance of the six dominant factors on ω varied between regions. CUBIST was further used to build regionally varying relationships between ω and the primary factors. Continental scale ω and evapotranspiration were further mapped across Australia based on the most robust BRT‐trained parameterization scheme with a resolution of 0.05°. Instead of using the machine learning method as a black box, we employed interpretability approaches to identify the controls. Our findings not only improved the capability of the Budyko method for hydrological partitioning across Australia, but also demonstrated that the controls of catchment properties on hydrological partitioning vary in different regions.
Glaciers of the Olympic Mountains, Washington—The Past and Future 100 Years
Authors: Fountain Andrew G. , Gray Christina , Glenn Bryce , Menounos Brian , Pflug Justin , Riedel Jon L. 
Published: April 2022

AbstractIn 2015, the Olympic Mountains contained 255 glaciers and perennial snowfields totaling 25.34 ± 0.27 km2, half of the area in 1900, and about 0.75 ± 0.19 km3 of ice. Since 1980, glaciers shrank at a rate of −0.59 km2 yr−1 during which time 35 glaciers and 16 perennial snowfields disappeared. Area changes of Blue Glacier, the largest glacier in the study region, was a good proxy for glacier change of the entire region. Modeled glacier mass balance, based on monthly air temperature and precipitation, correlates with glacier area change. The mass balance is highly sensitive to changes in air temperature rather than precipitation, typical of maritime glaciers. In addition to increasing summer melt, warmer winter temperatures changed the phase of precipitation from snow to rain, reducing snow accumulation. Changes in glacier mass balance are highly correlated with the Pacific North American index, a proxy for atmospheric circulation patterns and controls air temperatures along the Pacific Coast of North America. Regime shifts of sea surface temperatures in the North Pacific, reflected in the Pacific Decadal Oscillation (PDO), trigger shifts in the trend of glacier mass balance. Negative (“cool”) phases of the PDO are associated with glacier stability or slight mass gain whereas positive (“warm”) phases are associated with mass loss and glacier retreat. Over the past century the overall retreat is due to warming air temperatures, +0.7°C in winter and +0.3°C in summer. The glaciers in the Olympic Mountains are expected to largely disappear by 2070.
Grem1 accelerates nucleus pulposus cell apoptosis and intervertebral disc degeneration by inhibiting TGF-β-mediated Smad2/3 phosphorylation
Authors: Chen Shunlun , Lei Linchuan , Li Zemin , Chen Fan , Huang Yuming , Jiang Guowei , Guo Xingyu , Zhao Zhuoyang , Liu Hui , Wang Hua , Liu Caijun , Zheng Zhaomin , Wang Jianru 
Published: April 2022

AbstractIntervertebral disc degeneration (IVDD) is a main cause of low back pain, and inflammatory factors play key roles in its pathogenesis. Gremlin-1 (Grem1) was reported to induce an inflammatory response in other fields. This study aimed to investigate the mechanisms of Grem1 in the degenerative process of intervertebral discs. Dysregulated genes were determined by analyzing microarray profiles. The expression of Grem1 in 17 human disc samples (male:female = 9:8) and rat models (n = 5 each group) was measured by western blotting (WB), real-time quantitative PCR (RT-qPCR), and immunohistochemistry (IHC). The regulatory effects of Grem1 on apoptosis were examined using siRNAs, flow cytometry, immunofluorescence (IF), and WB. The therapeutic effect was evaluated by locally injecting specific Grem1 siRNA into IVDD rats. The expression of Grem1 was significantly increased in human degenerative intervertebral discs; furthermore, the expression of Grem1 positively correlated with the level of intervertebral disc degeneration. Grem1 was significantly overexpressed in tumor necrosis factor (TNF)-α-induced degenerative NP cells. Apoptosis in degenerative NP cells transfected with siRNA targeting Grem1 was significantly lower than that in the control group. Specific Grem1 siRNA markedly repressed the development of IVDD in surgery-induced IVDD rats. These results indicated that the expression of Grem1 was positively correlated with the severity of intervertebral disc degeneration, and Grem1 siRNA could inhibit Grem1-induced apoptosis and extracellular matrix alterations by mediating the TGF-β/Smad signaling pathway. This study may provide a therapeutic strategy for alleviating inflammation-induced apoptosis associated with intervertebral disc degeneration.
Lanthanide doped lead-free double perovskites as the promising next generation ultra-broadband light sources
Authors: Zhang Li , Yuan Mingjian 
Published: April 2022

AbstractEfficient ultra-broadband emitter is realized by using lanthanide ion doping coupled with “DPs-in-glass composite” (DiG) structure. The synergy of self-trapped exciton together with the energy transition induce this ultra-broadband emission emerge.
Body mass index associated with monoclonal gammopathy of undetermined significance (MGUS) progression in Olmsted County, Minnesota
Authors: Kleinstern Geffen , Larson Dirk R. , Allmer Cristine , Norman Aaron D. , Muntifering Grace , Sinnwell Jason , Visram Alissa , Rajkumar Vincent , Dispenzieri Angela , Kyle Robert A. , Slager Susan L. , Kumar Shaji , Vachon Celine M. 
Published: April 2022

AbstractMonoclonal gammopathy of undetermined significance (MGUS) is a premalignant clonal disorder that progresses to multiple myeloma (MM), or other plasma-cell or lymphoid disorders at a rate of 1%/year. We evaluate the contribution of body mass index (BMI) to MGUS progression beyond established clinical factors in a population-based study. We identified 594 MGUS through a population-based screening study in Olmsted County, Minnesota, between 1995 and 2003. Follow-up time was calculated from the date of MGUS to last follow-up, death, or progression to MM/another plasma-cell/lymphoid disorder. BMI (kg/m2 < 25/≥25) was measured close to screening date. We used Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association of BMI ≥ 25 versus BMI < 25 with MGUS progression and also evaluated the corresponding c-statistic and 95% CI to describe discrimination of the model for MGUS progression. Median follow-up was 10.5 years (range:0–25), while 465 patients died and 57 progressed and developed MM (N = 39), AL amyloidosis (N = 8), lymphoma (N = 5), or Waldenstrom-macroglobulinemia (N = 5). In univariate analyses, BMI ≥ 25 (HR = 2.14,CI:1.05–4.36, P = 0.04), non-IgG (HR = 2.84, CI:1.68–4.80, P = 0.0001), high monoclonal (M) protein (HR = 2.57, CI:1.50–4.42, P = 0.001), and abnormal free light chain ratio (FLCr) (HR = 3.39, CI:1.98–5.82, P < 0.0001) were associated with increased risk of MGUS progression, and were independently associated in a multivariable model (c-statistic = 0.75, CI:0.68–0.82). The BMI association was stronger among females (HR = 3.55, CI:1.06–11.9, P = 0.04) vs. males (HR = 1.39, CI:0.57–3.36, P = 0.47), although the interaction between BMI and sex was not significant (P = 0.15). In conclusion, high BMI is a prognostic factor for MGUS progression, independent of isotype, M protein, and FLCr. This association may be stronger among females.
Flubendazole induces mitochondrial dysfunction and DRP1-mediated mitophagy by targeting EVA1A in breast cancer
Authors: Zhen Yongqi , Yuan Zhaoxin , Zhang Jiahui , Chen Yao , Fu Yuning , Liu Yi , Fu Leilei , Zhang Lan , Zhou Xian-Li 
Published: April 2022

AbstractBreast cancer is still one of the most common malignancies worldwide and remains a major clinical challenge. We previously reported that the anthelmintic drug flubendazole induced autophagy and apoptosis via upregulation of eva-1 homolog A (EVA1A) in triple-negative breast cancer (TNBC) and was repurposed as a novel anti-tumor agent. However, the detailed underlying mechanisms remain unclear and need further investigation. Here, we found that flubendazole impairs the permeability of the mitochondrial outer membrane and mitochondrial function in breast cancer. Meanwhile, flubendazole increased dynamin-related protein (DRP1) expression, leading to the accumulation of PTEN induced putative kinase 1 (PINK1) and subsequent mitochondrial translocation of Parkin, thereby promoting excessive mitophagy. The resultant excessive mitophagy contributed to mitochondrial damage and dysfunction induced by flubendazole, thus inhibiting breast cancer cells proliferation and migration. Moreover, we demonstrated that excessive DRP1-mediated mitophagy played a critical role in response to the anti-tumor effects of EVA1A in breast cancer. Taken together, our results provide new insights into the molecular mechanisms in relation to the anti-tumor activities of flubendazole, and may be conducive to its rational use in potential clinical applications.
NOX activation in reactive astrocytes regulates astrocytic LCN2 expression and neurodegeneration
Authors: Liu Ruijia , Wang Jun , Chen Yang , Collier Jenelle M. , Capuk Okan , Jin Shijie , Sun Ming , Mondal Sujan K. , Whiteside Theresa L. , Stolz Donna B. , Yang Yongjie , Begum Gulnaz 
Published: April 2022

AbstractReactive astrocytes (RA) secrete lipocalin-2 (LCN2) glycoprotein that regulates diverse cellular processes including cell death/survival, inflammation, iron delivery and cell differentiation. Elevated levels of LCN2 are considered as a biomarker of brain injury, however, the underlying regulatory mechanisms of its expression and release are not well understood. In this study, we investigated the role of astrocytic Na+/H+ exchanger 1 (NHE1) in regulating reactive astrocyte LCN2 secretion and neurodegeneration after stroke. Astrocyte specific deletion of Nhe1 in Gfap-CreER+/−;Nhe1f/f mice reduced astrogliosis and astrocytic LCN2 and GFAP expression, which was associated with reduced loss of NeuN+ and GRP78+ neurons in stroke brains. In vitro ischemia in astrocyte cultures triggered a significant increase of secreted LCN2 in astrocytic exosomes, which caused neuronal cell death and neurodegeneration. Inhibition of NHE1 activity during in vitro ischemia with its potent inhibitor HOE642 significantly reduced astrocytic LCN2+ exosome secretion. In elucidating the cellular mechanisms, we found that stroke triggered activation of NADPH oxidase (NOX)-NF-κB signaling and ROS-mediated LCN2 expression. Inhibition of astrocytic NHE1 activity attenuated NOX signaling and LCN2-mediated neuronal apoptosis and neurite degeneration. Our findings demonstrate for the first time that RA use NOX signaling to stimulate LCN2 expression and secretion. Blocking astrocytic NHE1 activity is beneficial to reduce LCN2-mediated neurotoxicity after stroke.
ESR1 mutant breast cancers show elevated basal cytokeratins and immune activation
Authors: Li Zheqi , McGinn Olivia , Wu Yang , Bahreini Amir , Priedigkeit Nolan M. , Ding Kai , Onkar Sayali , Lampenfeld Caleb , Sartorius Carol A. , Miller Lori , Rosenzweig Margaret , Cohen Ofir , Wagle Nikhil , Richer Jennifer K. , Muller William J. , Buluwela Laki , Ali Simak , Bruno Tullia C. , Vignali Dario A. A. , Fang Yusi , Zhu Li , Tseng George C. , Gertz Jason , Atkinson Jennifer M. , Lee Adrian V. , Oesterreich Steffi 
Published: April 2022

AbstractEstrogen receptor alpha (ER/ESR1) is frequently mutated in endocrine resistant ER-positive (ER+) breast cancer and linked to ligand-independent growth and metastasis. Despite the distinct clinical features of ESR1 mutations, their role in intrinsic subtype switching remains largely unknown. Here we find that ESR1 mutant cells and clinical samples show a significant enrichment of basal subtype markers, and six basal cytokeratins (BCKs) are the most enriched genes. Induction of BCKs is independent of ER binding and instead associated with chromatin reprogramming centered around a progesterone receptor-orchestrated insulated neighborhood. BCK-high ER+ primary breast tumors exhibit a number of enriched immune pathways, shared with ESR1 mutant tumors. S100A8 and S100A9 are among the most induced immune mediators and involve in tumor-stroma paracrine crosstalk inferred by single-cell RNA-seq from metastatic tumors. Collectively, these observations demonstrate that ESR1 mutant tumors gain basal features associated with increased immune activation, encouraging additional studies of immune therapeutic vulnerabilities.
Heterogeneity of neuroendocrine transcriptional states in metastatic small cell lung cancers and patient-derived models
Authors: Lissa Delphine , Takahashi Nobuyuki , Desai Parth , Manukyan Irena , Schultz Christopher W. , Rajapakse Vinodh , Velez Moises J. , Mulford Deborah , Roper Nitin , Nichols Samantha , Vilimas Rasa , Sciuto Linda , Chen Yuanbin , Guha Udayan , Rajan Arun , Atkinson Devon , El Meskini Rajaa , Weaver Ohler Zoe , Thomas Anish 
Published: April 2022

AbstractMolecular subtypes of small cell lung cancer (SCLC) defined by the expression of key transcription regulators have recently been proposed in cell lines and limited number of primary tumors. The clinical and biological implications of neuroendocrine (NE) subtypes in metastatic SCLC, and the extent to which they vary within and between patient tumors and in patient-derived models is not known. We integrate histology, transcriptome, exome, and treatment outcomes of SCLC from a range of metastatic sites, revealing complex intra- and intertumoral heterogeneity of NE differentiation. Transcriptomic analysis confirms previously described subtypes based on ASCL1, NEUROD1, POU2F3, YAP1, and ATOH1 expression, and reveal a clinical subtype with hybrid NE and non-NE phenotypes, marked by chemotherapy-resistance and exceedingly poor outcomes. NE tumors are more likely to have RB1, NOTCH, and chromatin modifier gene mutations, upregulation of DNA damage response genes, and are more likely to respond to replication stress targeted therapies. In contrast, patients preferentially benefited from immunotherapy if their tumors were non-NE. Transcriptional phenotypes strongly skew towards the NE state in patient-derived model systems, an observation that was confirmed in paired patient-matched tumors and xenografts. We provide a framework that unifies transcriptomic and genomic dimensions of metastatic SCLC. The marked differences in transcriptional diversity between patient tumors and model systems are likely to have implications in development of novel therapeutic agents.
CO2 signaling mediates neurovascular coupling in the cerebral cortex
Authors: Hosford Patrick S. , Wells Jack A. , Nizari Shereen , Christie Isabel N. , Theparambil Shefeeq M. , Castro Pablo A. , Hadjihambi Anna , Barros L. Felipe , Ruminot Iván , Lythgoe Mark F. , Gourine Alexander V. 
Published: April 2022

AbstractNeurovascular coupling is a fundamental brain mechanism that regulates local cerebral blood flow (CBF) in response to changes in neuronal activity. Functional imaging techniques are commonly used to record these changes in CBF as a proxy of neuronal activity to study the human brain. However, the mechanisms of neurovascular coupling remain incompletely understood. Here we show in experimental animal models (laboratory rats and mice) that the neuronal activity-dependent increases in local CBF in the somatosensory cortex are prevented by saturation of the CO2-sensitive vasodilatory brain mechanism with surplus of exogenous CO2 or disruption of brain CO2/HCO3− transport by genetic knockdown of electrogenic sodium-bicarbonate cotransporter 1 (NBCe1) expression in astrocytes. A systematic review of the literature data shows that CO2 and increased neuronal activity recruit the same vasodilatory signaling pathways. These results and analysis suggest that CO2 mediates signaling between neurons and the cerebral vasculature to regulate brain blood flow in accord with changes in the neuronal activity.