bluuebunny/crossref_metadata_2025_split huggingface dataset:
Agricultural Adaptation to Reconcile Food Security and Water Sustainability Under Climate Change: The Case of Cereals in Iran
Authors: Karandish Fatemeh , Nouri Hamideh , Schyns Joep F. 
Published: March 2022

AbstractIn this study, we simulate the crop yield and water footprint (WF) of major food crops of Iran on irrigated and rainfed croplands for the historical and the future climate. We assess the effects of three agricultural adaptation strategies to climate change in terms of potential blue water savings. We then evaluate to what extent these savings can reduce unsustainable blue WF. We find that cereal production increases under climate change in both irrigated and rainfed croplands (by 2.6–3.1 and 1.4–2.3 million t yr−1, respectively) due to increased yields (6.6%–78.7%). Simultaneously, the unit WF (m3 t−1) tends to decrease in most scenarios. However, the annual consumptive water use increases in both irrigated and rainfed croplands (by 0.3–1.8 and 0.5–1.7 billion m3 yr−1, respectively). This is most noticeable in the arid regions, where consumptive water use increases by roughly 70% under climate change. Off‐season cultivation is the most effective adaptation strategy to alleviate additional pressure on blue water resources with blue water savings of 14–15 billion m3 yr−1. The second most effective is WF benchmarking, which results in blue water savings of 1.1–3.5 billion m3 yr−1. The early planting strategy is less effective but still leads to blue water savings of 1.7–1.9 billion m3 yr−1. In the same order of effectiveness, these three strategies can reduce blue water scarcity and unsustainable blue water use in Iran under current conditions. However, we find that these strategies do not mitigate water scarcity in all provinces per se, nor all months of the year.
Traveling Ionospheric Disturbances Observed Over South America After Lithospheric Events: 2010–2020
Authors: Bravo M. , Benavente R. , Foppiano A. , Urra B. , Ovalle E. 
Published: March 2022

AbstractHere, the ionospheric response to earthquakes, earthquakes inducing tsunamis, and volcanic eruptions are presented as a contribution to the so‐called ionospheric seismology with the eventual development of real‐time warning systems in mind. A thorough analysis of Traveling Ionospheric Disturbances (TIDs) observed after these lithospheric events in South America is presented. It is based on a decade of total electron content (TEC) anomaly maps constructed explicitly for this purpose, likely the most extensive survey ever for South America. Three disturbance types are identified: TIDs generated by shock‐acoustic waves, by gravity waves, possibly induced by tsunami waves, and by Rayleigh surface waves. TIDs are observed after earthquakes with epicenters on the Pacific Ocean east coast, except one in the middle of the ocean. TIDs‐generating earthquake thresholds are found to be Mw ≥ 7.0 and depth ≤40, and TID amplitudes and ranges are proportional to earthquake magnitude. Fault mechanism and satellite‐receiver pair geometry are also considered. TIDs after volcanic eruptions confirm that atmospheric resonances are already reported. TIDs propagation direction depends strongly on the geomagnetic field direction, propagation toward the geomagnetic equator being more efficient. It was only possible to add some kind of vertical disturbance‐propagation evidence to TEC TIDs identification in some cases using ionograms from nearby ionosondes. A denser ionosonde network with greater sounding frequency would be necessary for further study.
Impact of busulfan pharmacokinetics on outcome in adult patients receiving an allogeneic hematopoietic cell transplantation
Authors: Seydoux Claire , Battegay Raphael , Halter Joerg , Heim Dominik , Rentsch Katharina M. , Passweg Jakob R. , Medinger Michael 
Published: March 2022

AbstractBusulfan (Bu) is widely used in conditioning regimens before allogeneic hematopoietic cell transplantation, with variable metabolism due to interindividual differences of pharmacokinetics (PK). The purpose of this study was to correlate pharmacokinetics and clinical outcomes. Lower-AUC, in range-AUC and higher-AUC were defined as ±25% of the targeted Bu-AUC. In 2019, we changed Bu dosing from 4×/day (Bu-4) to 1×/day (Bu-1) for ease of application. AUC-target range was reached in 46% of patients; 40% were in low-AUC and 14% in high-AUC. Among all toxicities, viral and fungal infections were significantly more frequent in high-AUC compared with low-AUC (20% vs. 8%; p = 0.01 and 37% vs. 17%; p = 0.03). Bu-1 showed lower PK values (66% vs. 36% of Bu-4 in low-AUC; p < 0.01) and higher incidence of mucositis (p = 0.02). Long-term outcomes at 2 years showed a higher non-relapse mortality (NRM) (p < 0.01) and higher relative risk of death in the high-AUC group compared to the other groups. Cumulative incidence of relapse and acute/chronic GvHD were not significantly different. The optimal cut-off in Bu-AUC associated with low NRM was 969 µmol/l*min (ROC AUC 0.67, sensitivity 0.86 and specificity 0.47) for Bu-4. In conclusion, low-AUC BU-PK seems of benefit regarding NRM and survival.
RETRACTED ARTICLE: Circular RNA circStag1 promotes bone regeneration by interacting with HuR
Authors: Chen Gaoyang , Long Canling , Wang Shang , Wang Zhenmin , Chen Xin , Tang Wanze , He Xiaoqin , Bao Zhiteng , Tan Baoyu , Zhao Jin , Xie Yongheng , Li Zhizhong , Yang Dazhi , Xiao Guozhi , Peng Songlin 
Published: March 2022

AbstractPostmenopausal osteoporosis is a common bone metabolic disorder characterized by deterioration of the bone microarchitecture, leading to an increased risk of fractures. Recently, circular RNAs (circRNAs) have been demonstrated to play pivotal roles in regulating bone metabolism. However, the underlying functions of circRNAs in bone metabolism in postmenopausal osteoporosis remain obscure. Here, we report that circStag1 is a critical osteoporosis-related circRNA that shows significantly downregulated expression in osteoporotic bone marrow mesenchymal stem cells (BMSCs) and clinical bone tissue samples from patients with osteoporosis. Overexpression of circStag1 significantly promoted the osteogenic capability of BMSCs. Mechanistically, we found that circStag1 interacts with human antigen R (HuR), an RNA-binding protein, and promotes the translocation of HuR into the cytoplasm. A high cytoplasmic level of HuR led to the activation of the Wnt signaling pathway by stabilizing and enhancing low-density lipoprotein receptor-related protein 5/6 (Lrp5/6) and β-catenin expression, thereby stimulating the osteogenic differentiation of BMSCs. Furthermore, overexpression of circStag1 in vivo by circStag1-loaded adeno-associated virus (circStag1-AAV) promoted new bone formation, thereby preventing bone loss in ovariectomized rats. Collectively, we show that circStag1 plays a pivotal role in promoting the regeneration of bone tissue via HuR/Wnt signaling, which may provide new strategies to prevent bone metabolic disorders such as postmenopausal osteoporosis.
AMTB, a TRPM8 antagonist, suppresses growth and metastasis of osteosarcoma through repressing the TGFβ signaling pathway
Authors: Liu Yujie , Leng Ao , Li Lin , Yang Bo , Shen Shihui , Chen Hui , Zhu Enhao , Xu Qiyue , Ma Xiaoyu , Shi Peilin , Liu Yun , Liu Tielong , Li Lei , Li Kun , Zhang Dan , Xiao Jianru 
Published: March 2022

AbstractSince its first identification in prostate cancers and prostate tissues, transient receptor potential melastatin-subfamily member 8 (TRPM8) is subsequently found to be overexpressed in a wide range of cancers and is shown to be implicated in tumorigenesis and tumor progression. Here, we used N-(3-aminopropyl)-2-[(3-methylphenyl) methoxy] -N-(2-thienylmethyl) benzamide hydrochloride (AMTB), a specific TRPM8 antagonist, to explore its antitumoral effect on osteosarcoma. We find that AMTB suppresses osteosarcoma cell proliferation, metastasis and induces cellular apoptosis. Xenograft model in nude mice experiments also define that AMTB can increase the sensitivity of tumor cells to cisplatin, the cytotoxic chemotherapeutic regimens in treating osteosarcoma. Molecularly, AMTB specifically antagonizes TRPM8 which is upregulated in osteosarcoma and its expression level in osteosarcoma tissues is negatively related to patients’ prognosis. Finally, RNA sequencing analysis was performed to explore the mechanism underlying the antitumoral effect of AMTB on osteosarcoma cells and the results prove that AMTB suppresses the Transforming Growth Factor β (TGFβ) signaling pathway. Our study provides evidence that TRPM8 could be a potential therapeutic target and AMTB can suppress growth and metastasis of osteosarcoma cells through repressing the TGFβ signaling pathway and increase the sensitivity of tumor cells to cisplatin.
Usp8 promotes tumor cell migration through activating the JNK pathway
Authors: Zhao Yunhe , Peng Dezhen , Liu Yanyun , Zhang Qian , Liu Bin , Deng Yanran , Ding Wenhao , Zhou Zizhang , Liu Qingxin 
Published: March 2022

AbstractTumor metastasis is the most cause of high mortality for cancer patients. Identification of novel factors that modulate tumor cell migration is of great significance for therapeutic strategies. Here, we find that the ubiquitin-specific protease 8 (Usp8) promotes tumor cell migration through activating the c-Jun N-terminal kinase (JNK) pathway. Genetic epistasis analyses uncover Usp8 acts upstream of Tak1 to control the JNK pathway. Consistently, biochemical results reveal that Usp8 binds Tak1 to remove ubiquitin modification from Tak1, leading to its stabilization. In addition, human USP8 also triggers tumor cell migration and activates the JNK pathway. Finally, we show that knockdown of USP8 in human breast cancer cells suppresses cell migration. Taken together, our findings demonstrate that a conserved Usp8-Tak1-JNK axis promotes tumor cell migration, and providing USP8 as a potential therapeutic target for cancer treatment.
Fixational drift is driven by diffusive dynamics in central neural circuitry
Authors: Ben-Shushan Nadav , Shaham Nimrod , Joshua Mati , Burak Yoram 
Published: March 2022

AbstractDuring fixation and between saccades, our eyes undergo diffusive random motion called fixational drift. The role of fixational drift in visual coding and inference has been debated in the past few decades, but the mechanisms that underlie this motion remained unknown. In particular, it has been unclear whether fixational drift arises from peripheral sources, or from central sources within the brain. Here we show that fixational drift is correlated with neural activity, and identify its origin in central neural circuitry within the oculomotor system, upstream to the ocular motoneurons (OMNs). We analyzed a large data set of OMN recordings in the rhesus monkey, alongside precise measurements of eye position, and found that most of the variance of fixational eye drifts must arise upstream of the OMNs. The diffusive statistics of the motion points to the oculomotor integrator, a memory circuit responsible for holding the eyes still between saccades, as a likely source of the motion. Theoretical modeling, constrained by the parameters of the primate oculomotor system, supports this hypothesis by accounting for the amplitude as well as the statistics of the motion. Thus, we propose that fixational ocular drift provides a direct observation of diffusive dynamics in a neural circuit responsible for storage of continuous parameter memory in persistent neural activity. The identification of a mechanistic origin for fixational drift is likely to advance the understanding of its role in visual processing and inference.
Protein-based SARS-CoV-2 spike vaccine booster increases cross-neutralization against SARS-CoV-2 variants of concern in non-human primates
Authors: Pavot Vincent , Berry Catherine , Kishko Michael , Anosova Natalie G. , Huang Dean , Tibbitts Tim , Raillard Alice , Gautheron Sylviane , Gutzeit Cindy , Koutsoukos Marguerite , Chicz Roman M. , Lecouturier Valerie 
Published: March 2022

AbstractThe emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that partly evade neutralizing antibodies raises concerns of reduced vaccine effectiveness and increased infection. We previously demonstrated that the SARS-CoV-2 spike protein vaccine adjuvanted with AS03 (CoV2 preS dTM-AS03) elicits robust neutralizing antibody responses in naïve subjects. Here we show that, in macaques primed with mRNA or protein-based subunit vaccine candidates, one booster dose of CoV2 preS dTM-AS03 (monovalent D614 or B.1.351, or bivalent D614 + B.1.351 formulations), significantly boosts the pre-existing neutralizing antibodies against the parental strain from 177- to 370-fold. Importantly, the booster dose elicits high and persistent cross-neutralizing antibodies covering five former or current SARS-CoV-2 variants of concern (Alpha, Beta, Gamma, Delta and Omicron) and, unexpectedly, SARS-CoV-1. Interestingly, we show that the booster specifically increases the functional antibody responses as compared to the receptor binding domain (RBD)-specific responses. Our findings show that these vaccine candidates, when used as a booster, have the potential to offer cross-protection against a broad spectrum of variants. This has important implications for vaccine control of SARS-CoV-2 variants of concern and informs on the benefit of a booster with the vaccine candidates currently under evaluation in clinical trials.
A natural timeless polymorphism allowing circadian clock synchronization in “white nights”
Authors: Lamaze Angelique , Chen Chenghao , Leleux Solene , Xu Min , George Rebekah , Stanewsky Ralf 
Published: March 2022

AbstractDaily temporal organisation offers a fitness advantage and is determined by an interplay between environmental rhythms and circadian clocks. While light:dark cycles robustly synchronise circadian clocks, it is not clear how animals experiencing only weak environmental cues deal with this problem. Like humans, Drosophila originate in sub-Saharan Africa and spread North up to the polar circle, experiencing long summer days or even constant light (LL). LL disrupts clock function, due to constant activation of CRYPTOCHROME, which induces degradation of the clock protein TIMELESS (TIM), but temperature cycles are able to overcome these deleterious effects of LL. We show here that for this to occur a recently evolved natural timeless allele (ls-tim) is required, encoding the less light-sensitive L-TIM in addition to S-TIM, the only form encoded by the ancient s-tim allele. We show that only ls-tim flies can synchronise their behaviour to semi-natural conditions typical for Northern European summers, suggesting that this functional gain is driving the Northward ls-tim spread.
Ferroelectric photosensor network: an advanced hardware solution to real-time machine vision
Authors: Cui Boyuan , Fan Zhen , Li Wenjie , Chen Yihong , Dong Shuai , Tan Zhengwei , Cheng Shengliang , Tian Bobo , Tao Ruiqiang , Tian Guo , Chen Deyang , Hou Zhipeng , Qin Minghui , Zeng Min , Lu Xubing , Zhou Guofu , Gao Xingsen , Liu Jun-Ming 
Published: March 2022

AbstractNowadays the development of machine vision is oriented toward real-time applications such as autonomous driving. This demands a hardware solution with low latency, high energy efficiency, and good reliability. Here, we demonstrate a robust and self-powered in-sensor computing paradigm with a ferroelectric photosensor network (FE-PS-NET). The FE-PS-NET, constituted by ferroelectric photosensors (FE-PSs) with tunable photoresponsivities, is capable of simultaneously capturing and processing images. In each FE-PS, self-powered photovoltaic responses, modulated by remanent polarization of an epitaxial ferroelectric Pb(Zr0.2Ti0.8)O3 layer, show not only multiple nonvolatile levels but also sign reversibility, enabling the representation of a signed weight in a single device and hence reducing the hardware overhead for network construction. With multiple FE-PSs wired together, the FE-PS-NET acts on its own as an artificial neural network. In situ multiply-accumulate operation between an input image and a stored photoresponsivity matrix is demonstrated in the FE-PS-NET. Moreover, the FE-PS-NET is faultlessly competent for real-time image processing functionalities, including binary classification between ‘X’ and ‘T’ patterns with 100% accuracy and edge detection for an arrow sign with an F-Measure of 1 (under 365 nm ultraviolet light). This study highlights the great potential of ferroelectric photovoltaics as the hardware basis of real-time machine vision.
Large interannual variability in supraglacial lakes around East Antarctica
Authors: Arthur Jennifer F. , Stokes Chris R. , Jamieson Stewart S. R. , Rachel Carr J. , Leeson Amber A. , Verjans Vincent 
Published: March 2022

AbstractAntarctic supraglacial lakes (SGLs) have been linked to ice shelf collapse and the subsequent acceleration of inland ice flow, but observations of SGLs remain relatively scarce and their interannual variability is largely unknown. This makes it difficult to assess whether some ice shelves are close to thresholds of stability under climate warming. Here, we present the first observations of SGLs across the entire East Antarctic Ice Sheet over multiple melt seasons (2014–2020). Interannual variability in SGL volume is >200% on some ice shelves, but patterns are highly asynchronous. More extensive, deeper SGLs correlate with higher summer (December-January-February) air temperatures, but comparisons with modelled melt and runoff are complex. However, we find that modelled January melt and the ratio of November firn air content to summer melt are important predictors of SGL volume on some potentially vulnerable ice shelves, suggesting large increases in SGLs should be expected under future atmospheric warming.
Deep learning corrosion detection with confidence
Authors: Nash Will , Zheng Liang , Birbilis Nick 
Published: March 2022

AbstractCorrosion costs an estimated 3–4% of GDP for most nations each year, leading to significant loss of assets. Research regarding automatic corrosion detection is ongoing, with recent progress leveraging advances in deep learning. Studies are hindered however, by the lack of a publicly available dataset. Thus, corrosion detection models use locally produced datasets suitable for the immediate conditions, but are unable to produce generalized models for corrosion detection. The corrosion detection model algorithms will output a considerable number of false positives and false negatives when challenged in the field. In this paper, we present a deep learning corrosion detector that performs pixel-level segmentation of corrosion. Moreover, three Bayesian variants are presented that provide uncertainty estimates depicting the confidence levels at each pixel, to better inform decision makers. Experiments were performed on a freshly collected dataset consisting of 225 images, discussed and validated herein.
Caltech Conte Center, a multimodal data resource for exploring social cognition and decision-making
Authors: Kliemann Dorit , Adolphs Ralph , Armstrong Tim , Galdi Paola , Kahn David A. , Rusch Tessa , Enkavi A. Zeynep , Liang Deuhua , Lograsso Steven , Zhu Wenying , Yu Rona , Nair Remya , Paul Lynn K. , Tyszka J. Michael 
Published: March 2022

AbstractThis data release of 117 healthy community-dwelling adults provides multimodal high-quality neuroimaging and behavioral data for the investigation of brain-behavior relationships. We provide structural MRI, resting-state functional MRI, movie functional MRI, together with questionnaire-based and task-based psychological variables; many of the participants have multiple datasets from retesting over the course of several years. Our dataset is distinguished by utilizing open-source data formats and processing tools (BIDS, FreeSurfer, fMRIPrep, MRIQC), providing data that is thoroughly quality checked, preprocessed to various extents and available in multiple anatomical spaces. A customizable denoising pipeline is provided as open-source code that includes tools for the generation of functional connectivity matrices and initialization of individual difference analyses. Behavioral data include a comprehensive set of psychological assessments on gold-standard instruments encompassing cognitive function, mood and personality, together with exploratory factor analyses. The dataset provides an in-depth, multimodal resource for investigating associations between individual differences, brain structure and function, with a focus on the domains of social cognition and decision-making.
The Mexican magnetic resonance imaging dataset of patients with cocaine use disorder: SUDMEX CONN
Authors: Angeles-Valdez Diego , Rasgado-Toledo Jalil , Issa-Garcia Victor , Balducci Thania , Villicaña Viviana , Valencia Alely , Gonzalez-Olvera Jorge Julio , Reyes-Zamorano Ernesto , Garza-Villarreal Eduardo A. 
Published: March 2022

AbstractCocaine use disorder (CUD) is a substance use disorder (SUD) characterized by compulsion to seek, use and abuse of cocaine, with severe health and economic consequences for the patients, their families and society. Due to the lack of successful treatments and high relapse rate, more research is needed to understand this and other SUD. Here, we present the SUDMEX CONN dataset, a Mexican open dataset of 74 CUD patients (9 female) and matched 64 healthy controls (6 female) that includes demographic, cognitive, clinical, and magnetic resonance imaging (MRI) data. MRI data includes: 1) structural (T1-weighted), 2) multishell high-angular resolution diffusion-weighted (DWI-HARDI) and 3) functional (resting state fMRI) sequences. The repository contains unprocessed MRI data available in brain imaging data structure (BIDS) format with corresponding metadata available at the OpenNeuro data sharing platform. Researchers can pursue brain variability between these groups or use a single group for a larger population sample.
Emergence and structure of decentralised trade networks around dark web marketplaces
Authors: Nadini Matthieu , Bracci Alberto , ElBahrawy Abeer , Gradwell Philip , Teytelboym Alexander , Baronchelli Andrea 
Published: March 2022

AbstractDark web marketplaces (DWMs) are online platforms that facilitate illicit trade among millions of users generating billions of dollars in annual revenue. Recently, two interview-based studies have suggested that DWMs may also promote the emergence of direct user-to-user (U2U) trading relationships. Here, we carefully investigate and quantify the scale of U2U trading around DWMs by analysing 31 million Bitcoin transactions among users of 40 DWMs between June 2011 and Jan 2021. We find that half of the DWM users trade through U2U pairs generating a total trading volume greater than DWMs themselves. We then show that hundreds of thousands of DWM users form stable trading pairs that are persistent over time. Users in such stable pairs turn out to be the ones with the largest trading volume on DWMs. Then, we show that new U2U pairs often form while both users are active on the same DWM, suggesting the marketplace may serve as a catalyst for new direct trading relationships. Finally, we reveal that stable U2U pairs tend to survive DWM closures and that they were not affected by COVID-19, indicating that their trading activity is resilient to external shocks. Our work unveils sophisticated patterns of trade emerging in the dark web and highlights the importance of investigating user behaviour beyond the immediate buyer-seller network on a single marketplace.