bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increased early motivational response to food in adolescent anorexia nervosa revealed by magnetoencephalography
Authors: Romero Frausto Hugo , Roesmann Kati , Klinkenberg Isabelle A. G. , Rehbein Maimu A. , Föcker Manuel , Romer Georg , Junghoefer Markus , Wessing Ida 
Published: May 2021

AbstractBackgroundIt remains unclear to what extent reduced nutritional intake in anorexia nervosa (AN) is a consequence of a reduced motivational response to food. Although self-reports typically suggest AN patients have a reduced appetitive response, behavioral and neurophysiological measures have revealed evidence for both increased and reduced attentional biases towards food stimuli. The mechanisms influencing food perception in AN, might be clarified using time-sensitive magnetoencephalography (MEG) to differentiate the early (more automatic processing) stages from the late (more controlled) stages.MethodsMEG was recorded in 22 partially weight-restored adolescent AN patients and 29 age- and gender-matched healthy control (HC) participants during a rapid serial visual presentation paradigm using 100 high-calorie food, 100 low-calorie food, and 100 non-food pictures. Neural sources of event-related fields were estimated using the L2-Minimum-Norm method and analyzed in early (50–300 ms) and late (350–500 ms) time intervals.ResultsAN patients rated high-calorie food as less palatable and reported overall less food craving than HC participants. Nevertheless, in response to food pictures AN patients showed relative increased neural activity in the left occipito-temporal and inferior frontal regions in the early time interval. No group differences occurred in the late time interval.ConclusionsMEG results speak against an overall reduced motivational response to food in AN. Instead, relative increased early food processing in the visual cortex suggests greater motivated attention. A greater appetitive response to food might be an adaptive mechanism in a state of undernourishment. Yet, this relative increased food processing in AN was no longer present later, arguably reflecting rapid downregulation.
Recent Warming Fuels Increased Organic Carbon Export From Arctic Permafrost
Authors: Zhang Xiaowen , Bianchi Thomas S. , Hanna Andrea J. M. , Shields Michael R. , Izon Gareth , Hutchings Jack A. , Ping Chien‐Lu , Kanevskiy Mikhail , Haghipour Negar , Eglinton Timothy I. 
Published: May 2021

AbstractClimate‐driven thawing of Arctic permafrost renders its vast carbon reserves susceptible to microbial degradation, serving as a potentially potent positive feedback hidden within the climate system. While seemingly intuitive, the relationship between thermally driven permafrost losses and organic carbon (OC) export remains largely unexplored in natural settings. Filling this knowledge gap, we present down‐core bulk and compound‐specific radiocarbon records of permafrost change from a sediment core taken within the Alaskan Colville River delta spanning the last c. 2,700 years. Fingerprinted by significantly older radiocarbon ages of bulk OC and long‐chain fatty acids, these data expose a thermally driven increase in permafrost OC export and/or deepening of mobilizable permafrost layers over the last c. 160 years after the Little Ice Age. Comparison of OC content and radiocarbon data between recent and Roman warming episodes likely implies that the rate of warming, alongside the prevailing boundary conditions, may dictate the ultimate fate of the Arctic's permafrost inventory. Our findings highlight the importance of leveraging geological records as archives of Arctic permafrost mobilization dynamics with temperature change.
T-cell-based immunotherapy of acute myeloid leukemia: current concepts and future developments
Authors: Daver Naval , Alotaibi Ahmad S. , Bücklein Veit , Subklewe Marion 
Published: May 2021

AbstractAcute myeloid leukemia (AML) is a heterogeneous disease linked to a broad spectrum of molecular alterations, and as such, long-term disease control requires multiple therapeutic approaches. Driven largely by an improved understanding and targeting of these molecular aberrations, AML treatment has rapidly evolved over the last 3–5 years. The stellar successes of immunotherapies that harness the power of T cells to treat solid tumors and an improved understanding of the immune systems of patients with hematologic malignancies have led to major efforts to develop immunotherapies for the treatment of patients with AML. Several immunotherapies that harness T cells against AML are in various stages of preclinical and clinical development. These include bispecific and dual antigen receptor-targeting antibodies (targeted to CD33, CD123, CLL-1, and others), chimeric antigen receptor (CAR) T-cell therapies, and T-cell immune checkpoint inhibitors (including those targeting PD-1, PD-L1, CTLA-4, and newer targets such as TIM3 and STING). The current and future directions of these T-cell-based immunotherapies in the treatment landscape of AML are discussed in this review.
Single-cell profiling of tumor heterogeneity and the microenvironment in advanced non-small cell lung cancer
Authors: Wu Fengying , Fan Jue , He Yayi , Xiong Anwen , Yu Jia , Li Yixin , Zhang Yan , Zhao Wencheng , Zhou Fei , Li Wei , Zhang Jie , Zhang Xiaosheng , Qiao Meng , Gao Guanghui , Chen Shanhao , Chen Xiaoxia , Li Xuefei , Hou Likun , Wu Chunyan , Su Chunxia , Ren Shengxiang , Odenthal Margarete , Buettner Reinhard , Fang Nan , Zhou Caicun 
Published: May 2021

AbstractLung cancer is a highly heterogeneous disease. Cancer cells and cells within the tumor microenvironment together determine disease progression, as well as response to or escape from treatment. To map the cell type-specific transcriptome landscape of cancer cells and their tumor microenvironment in advanced non-small cell lung cancer (NSCLC), we analyze 42 tissue biopsy samples from stage III/IV NSCLC patients by single cell RNA sequencing and present the large scale, single cell resolution profiles of advanced NSCLCs. In addition to cell types described in previous single cell studies of early stage lung cancer, we are able to identify rare cell types in tumors such as follicular dendritic cells and T helper 17 cells. Tumors from different patients display large heterogeneity in cellular composition, chromosomal structure, developmental trajectory, intercellular signaling network and phenotype dominance. Our study also reveals a correlation of tumor heterogeneity with tumor associated neutrophils, which might help to shed light on their function in NSCLC.
Selection of a picomolar antibody that targets CXCR2-mediated neutrophil activation and alleviates EAE symptoms
Authors: Shi Xiaojie , Wan Yue , Wang Nan , Xiang Jiangchao , Wang Tao , Yang Xiaofeng , Wang Ju , Dong Xuxue , Dong Liang , Yan Lei , Li Yu , Liu Lili , Hou Shinchen , Zhong Zhenwei , Wilson Ian A. , Yang Bei , Yang Guang , Lerner Richard A. 
Published: May 2021

AbstractReceptors and their ligands are important therapeutic targets for about one third of marketed drugs. Here, we describe an epitope-guided approach for selection of antibodies that modulate cellular signaling of targeted receptors. We chose CXC chemokine receptor 2 (CXCR2) in the G-protein coupled receptor superfamily as receptor and a CXCR2 N-terminal peptide for antibody selection. We obtain a highly selective, tight-binding antibody from a 1011-member antibody library using combinatorial enrichment. Structural and Hydrogen-Deuterium-Exchange mass spectrometry analyses demonstrate antibody interaction with an N-terminal region of CXCR2 that is part of the IL-8 epitope. The antibody strongly inhibits IL-8-induced and CXCR2-mediated neutrophil chemotaxis in vitro and alleviates hCXCR2-dependent experimental autoimmune encephalomyelitis symptoms in mice. As inappropriate neutrophil migration accompanies many diseases including inflammatory bowel disease, glomerulonephritis, allergic asthma, chronic obstructive pulmonary disease, and cancer, this antibody has potential for development as a therapeutic agent, akin to anti-TNF antibodies. However, an important difference here is that the antibody targets the chemokine receptor and competes with natural ligand, rather than targeting the ligand itself.
Cosmogenic in situ 14C-10Be reveals abrupt Late Holocene soil loss in the Andean Altiplano
Authors: Hippe Kristina , Jansen John D. , Skov Daniel Søndergaard , Lupker Maarten , Ivy-Ochs Susan , Kober Florian , Zeilinger Gerold , Capriles José Mariano , Christl Marcus , Maden Colin , Vockenhuber Christof , Egholm David Lundbek 
Published: May 2021

AbstractSoil sustainability is reflected in a long-term balance between soil production and erosion for a given climate and geology. Here we evaluate soil sustainability in the Andean Altiplano where accelerated erosion has been linked to wetter climate from 4.5 ka and the rise of Neolithic agropastoralism in the millennium that followed. We measure in situ cosmogenic14C directly on cultivated hilltops to quantify late Holocene soil loss, which we compare with background soil production rates determined from cosmogenic26Al and10Be. Our Monte Carlo-based inversion method identifies two scenarios to account for our data: an increase in erosion rate by 1–2 orders of magnitude between ~2.6 and 1.1 ka, or a discrete event stripping ~1–2 m of soil between ~1.9 and 1.1 ka. Coupled environmental and cultural factors in the Late Holocene signaled the onset of the pervasive human imprint in the Andean Altiplano seen today.
Oocyte-derived microvilli control female fertility by optimizing ovarian follicle selection in mice
Authors: Zhang Yan , Wang Ye , Feng Xie’an , Zhang Shuo , Xu Xueqiang , Li Lingyu , Niu Shudong , Bo Yingnan , Wang Chao , Li Zhen , Xia Guoliang , Zhang Hua 
Published: May 2021

AbstractCrosstalk between oocytes and surrounding somatic cells is crucial for mammalian oogenesis, but the structural mechanisms on oocytes to control female reproduction remain unknown. Here we combine endogenous-fluorescent tracing mouse models with a high-resolution live-cell imaging system to characterize oocyte-derived mushroom-like microvilli (Oo-Mvi), which mediate germ-somatic communication in mice. We perform 3D live-cell imaging to show that Oo-Mvi exhibit cellular characteristics that fit an exocrine function for signaling communication. We find that deletion of the microvilli-forming gene Radixin in oocytes leads to the loss of Oo-Mvi in ovaries, and causes a series of abnormalities in ovarian development, resulting in shortened reproductive lifespan in females. Mechanistically, we find that Oo-Mvi enrich oocyte-secreted factors and control their release, resulting in optimal selection of ovarian follicles. Taken together, our data show that the Oo-Mvi system controls the female reproductive lifespan by governing the fate of follicles.
Segregated oceanic crust trapped at the bottom mantle transition zone revealed from ambient noise interferometry
Authors: Feng Jikun , Yao Huajian , Wang Yi , Poli Piero , Mao Zhu 
Published: May 2021

AbstractThe recycling of oceanic crust, with distinct isotopic and chemical signature from the pyrolite mantle, plays a critical role in the chemical evolution of the Earth with insights into mantle circulation. However, the role of the mantle transition zone during this recycling remains ambiguous. We here combine the unique resolution reflected body waves (P410P and P660P) retrieved from ambient noise interferometry with mineral physics modeling, to shed new light on transition zone physics. Our joint analysis reveals a generally sharp 660-km discontinuity and the existence of a localized accumulation of oceanic crust at the bottom mantle transition zone just ahead of the stagnant Pacific slab. The basalt accumulation is plausibly derived from the segregation of oceanic crust and depleted mantle of the adjacent stagnant slab. Our findings provide direct evidence of segregated oceanic crust trapped within the mantle transition zone and new insights into imperfect whole mantle circulation.
The CINSARC signature predicts the clinical outcome in patients with Luminal B breast cancer
Authors: Goncalves Anthony , Finetti Pascal , Birnbaum Daniel , Bertucci François 
Published: May 2021

AbstractCINSARC, a multigene expression signature originally developed in sarcomas, was shown to have prognostic impact in various cancers. We tested the prognostic value for disease-free survival (DFS) of CINSARC in a series of 6035 early-stage invasive primary breast cancers. CINSARC had independent prognostic value in the Luminal B subtype and not in the other subtypes. In Luminal B patients receiving adjuvant endocrine therapy but no chemotherapy, CINSARC identified patients with different 5-year DFS (90% [95%CI 86–95] in low-risk vs. 79% [95%CI 75–84] in high-risk, p = 1.04E−02). Luminal B CINSARC high-risk tumors were predicted to be less sensitive to endocrine therapy and CDK4/6 inhibitors, but more vulnerable to homologous recombination targeting and immunotherapy. We concluded that CINSARC adds prognostic information to that of clinicopathological features in Luminal B breast cancers, which might improve patients’ stratification and better orient adjuvant treatment. Moreover, it identifies potential therapeutic avenues in this aggressive molecular subtype.
Selection of nitrogen responsive root architectural traits in spinach using machine learning and genetic correlations
Authors: Awika Henry O. , Mishra Amit K. , Gill Haramrit , DiPiazza James , Avila Carlos A. , Joshi Vijay 
Published: May 2021

AbstractThe efficient acquisition and transport of nutrients by plants largely depend on the root architecture. Due to the absence of complex microbial network interactions and soil heterogeneity in a restricted soilless medium, the architecture of roots is a function of genetics defined by the soilless matrix and exogenously supplied nutrients such as nitrogen (N). The knowledge of root trait combinations that offer the optimal nitrogen use efficiency (NUE) is far from being conclusive. The objective of this study was to define the root trait(s) that best predicts and correlates with vegetative biomass under differed N treatments. We used eight image-derived root architectural traits of 202 diverse spinach lines grown in two N concentrations (high N, HN, and low N, LN) in randomized complete blocks design. Supervised random forest (RF) machine learning augmented by ranger hyperparameter grid search was used to predict the variable importance of the root traits. We also determined the broad-sense heritability (H) and genetic (rg) and phenotypic (rp) correlations between root traits and the vegetative biomass (shoot weight, SWt). Each root trait was assigned a predicted importance rank based on the trait’s contribution to the cumulative reduction in the mean square error (MSE) in the RF tree regression models for SWt. The root traits were further prioritized for potential selection based on the rg and SWt correlated response (CR). The predicted importance of the eight root traits showed that the number of root tips (Tips) and root length (RLength) under HN and crossings (Xsings) and root average diameter (RAvdiam) under LN were the most relevant. SWt had a highly antagonistic rg (− 0.83) to RAvdiam, but a high predicted indirect selection efficiency (− 112.8%) with RAvdiam under LN; RAvdiam showed no significant rg or rp to SWt under HN. In limited N availability, we suggest that selecting against larger RAvdiam as a secondary trait might improve biomass and, hence, NUE with no apparent yield penalty under HN.
Development of an efficient Tef-1α RNA hairpin structure to efficient management of Lasiodiplodia theobromae and Neofusicoccum parvum
Authors: Nili Omid , Azizi Abdolbaset , Abdollahzadeh Jafar 
Published: May 2021

AbstractLasiodiplodia theobromae and Neofusicoccum parvum are serious worldwide-distributed plant pathogenic fungi with a wide host range in tropical and temperate climates. They cause fruit rot, canker, and dieback of twigs in various woody plants. Protection of pruning wounds using fungicides is the prevalent strategy for the management of the diseases caused by these fungi. Chemical control of plant diseases is not environmentally safe and the residues of fungicides are a threat to nature. Furthermore, genetic resources of resistance to plant diseases in woody plants are limited. The aim of this study was to investigate the efficiency of RNA silencing using an efficient hairpin structure based on Tef-1α gene for the management of L. theobromae and N. parvum. Hairpin structure of Tef-1α was cloned in pFGC5941 binary vector and the recombinant construct was named pFGC-TEF-d. Transient expression of pFGC-TEF-d using Agrobacterium LBA4404 in grapevine (Bidaneh Sefid cv.) and strawberry cultivars (Camarosa and Ventana) led to a reduction in disease progress of L. theobromae. The disease reduction in grapevine was estimated by 55% and in strawberries cultivars Camarosa and Ventana by 58% and 93%, respectively. Further analysis of transient expression of pFGC-TEF-d in strawberry (Camarosa) shown disease reduction using Neofusicoccum parvum. Here we introduce RNAi silencing using pFGC-TEF-d construct as an efficient strategy to the management of L. theobromae and N. parvum for the first time.
Dilations and degeneracy in network controllability
Authors: Chung Liam , Ruths Derek , Ruths Justin 
Published: May 2021

AbstractNetwork controllability asserts a perspective that the structure—the location of edges that connect nodes—of the network contains important information about fundamental characteristics of our ability to change the behavior that evolves on these networks. It can be used, for example, to determine the parts of the system that when influenced by outside controlling signals, can ultimately steer the behavior of the entire network. One of the challenges in utilizing the ideas from network controllability on real systems is that there is typically more than one potential solution (often many) suggested by the topology of the graph that perform equally well. Picking a single candidate from this degenerate solution set over others should be properly motivated, however, to-date our understanding of how these different options are related has been limited. In this work, we operationalize the existing notion of a dilation into a framework that provides clarity on the source of this control degeneracy and further elucidates many of the existing results surrounding degeneracy in the literature.
Antiferromagnetic skyrmion crystals in the Rashba Hund’s insulator on triangular lattice
Authors: Mukherjee Arnob , Kathyat Deepak S. , Kumar Sanjeev 
Published: May 2021

AbstractMotivated by the importance of antiferromagnetic skyrmions as building blocks of next-generation data storage and processing devices, we report theoretical and computational analysis of a model for a spin-orbit coupled correlated Hund’s insulator magnet on a triangular lattice. We find that two distinct antiferromagnetic skyrmion crystal (AF-SkX) states can be stabilized at low temperatures in the presence of external magnetic field. The results are obtained via Monte Carlo simulations on an effective magnetic model derived from the microscopic electronic Hamiltonian consisting of Rashba spin-orbit coupling, as well as strong Hund’s coupling of electrons to classical spins at half-filling. The two AF-SkX phases are understood to originate from a classical spin liquid state that exists at low but finite temperatures. These AF-SkX states can be easily distinguished from each other in experiments as they are characterized by peaks at distinct momenta in the spin structure factor which is directly measured in neutron scattering experiments. We also discuss examples of materials where the model as well as the two AF-SkX states can be realized.
Inverse renormalization group based on image super-resolution using deep convolutional networks
Authors: Shiina Kenta , Mori Hiroyuki , Tomita Yusuke , Lee Hwee Kuan , Okabe Yutaka 
Published: May 2021

AbstractThe inverse renormalization group is studied based on the image super-resolution using the deep convolutional neural networks. We consider the improved correlation configuration instead of spin configuration for the spin models, such as the two-dimensional Ising and three-state Potts models. We propose a block-cluster transformation as an alternative to the block-spin transformation in dealing with the improved estimators. In the framework of the dual Monte Carlo algorithm, the block-cluster transformation is regarded as a transformation in the graph degrees of freedom, whereas the block-spin transformation is that in the spin degrees of freedom. We demonstrate that the renormalized improved correlation configuration successfully reproduces the original configuration at all the temperatures by the super-resolution scheme. Using the rule of enlargement, we repeatedly make inverse renormalization procedure to generate larger correlation configurations. To connect thermodynamics, an approximate temperature rescaling is discussed. The enlarged systems generated using the super-resolution satisfy the finite-size scaling.
Deep convolution stack for waveform in underwater acoustic target recognition
Authors: Tian Shengzhao , Chen Duanbing , Wang Hang , Liu Jingfa 
Published: May 2021

AbstractIn underwater acoustic target recognition, deep learning methods have been proved to be effective on recognizing original signal waveform. Previous methods often utilize large convolutional kernels to extract features at the beginning of neural networks. It leads to a lack of depth and structural imbalance of networks. The power of nonlinear transformation brought by deep network has not been fully utilized. Deep convolution stack is a kind of network frame with flexible and balanced structure and it has not been explored well in underwater acoustic target recognition, even though such frame has been proven to be effective in other deep learning fields. In this paper, a multiscale residual unit (MSRU) is proposed to construct deep convolution stack network. Based on MSRU, a multiscale residual deep neural network (MSRDN) is presented to classify underwater acoustic target. Dataset acquired in a real-world scenario is used to verify the proposed unit and model. By adding MSRU into Generative Adversarial Networks, the validity of MSRU is proved. Finally, MSRDN achieves the best recognition accuracy of 83.15%, improved by 6.99% from the structure related networks which take the original signal waveform as input and 4.48% from the networks which take the time-frequency representation as input.