bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuroimaging studies within Cognitive Genetics Collaborative Research Organization aiming to replicate and extend works of ENIGMA
Authors: Koshiyama Daisuke , Miura Kenichiro , Nemoto Kiyotaka , Okada Naohiro , Matsumoto Junya , Fukunaga Masaki , Hashimoto Ryota 
Published: June 2020

AbstractReproducibility is one of the most important issues for generalizing the results of clinical research; however, low reproducibility in neuroimaging studies is well known. To overcome this problem, the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) consortium, an international neuroimaging consortium, established standard protocols for imaging analysis and employs either meta‐ and mega‐analyses of psychiatric disorders with large sample sizes. The Cognitive Genetics Collaborative Research Organization (COCORO) in Japan promotes neurobiological studies in psychiatry and has successfully replicated and extended works of ENIGMA especially for neuroimaging studies. For example, (a) the ENIGMA consortium showed subcortical regional volume alterations in patients with schizophrenia (n = 2,028) compared to controls (n = 2,540) across 15 cohorts using meta‐analysis. COCORO replicated the volumetric changes in patients with schizophrenia (n = 884) compared to controls (n = 1,680) using the ENIGMA imaging analysis protocol and mega‐analysis. Furthermore, a schizophrenia‐specific leftward asymmetry for the pallidum volume was demonstrated; and (b) the ENIGMA consortium identified white matter microstructural alterations in patients with schizophrenia (n = 1,963) compared to controls (n = 2,359) across 29 cohorts. Using the ENIGMA protocol, a study from COCORO showed similar results in patients with schizophrenia (n = 696) compared to controls (n = 1,506) from 12 sites using mega‐analysis. Moreover, the COCORO study found that schizophrenia, bipolar disorder (n = 211) and autism spectrum disorder (n = 126), but not major depressive disorder (n = 398), share similar white matter microstructural alterations, compared to controls. Further replication and harmonization of the ENIGMA consortium and COCORO will contribute to the generalization of their research findings.
Seasonal vegetation and management influence overland flow velocity and roughness in upland grasslands
Authors: Bond Stephanie , Kirkby Mike J. , Johnston Jean , Crowle Alistair , Holden Joseph 
Published: June 2020

AbstractThere is considerable interest in how headwater management may influence downstream flood peaks in temperate humid regions. However, there is a dearth of data on flow velocities across headwater hillslopes and limited understanding of whether surface flow velocity is influenced by seasonal changes in roughness through vegetation cycles or management. A portable hillslope flume was used to investigate overland flow velocities for four common headwater grassland habitats in northern England: Low‐density Grazing, Hay Meadow, Rank Grassland and Juncus effusus Rush pasture. Overland flow velocity was measured in replicate plots for each habitat, in response to three applied flow rates, with the experiments repeated during five different periods of the annual grassland cycle. Mean annual overland flow velocity was significantly lower for the Rank Grassland habitat (0.026 m/s) followed by Low‐density Grazing and Rushes (0.032 and 0.029 m/s), then Hay Meadows (0.041 m/s), which had the greatest mean annual velocity (examples from 12 L/min flow rate). Applying our mean overland flow velocities to a theoretical 100 m hillslope suggests overland flow is delayed by >1 hr on Rank Grassland when compared to Hay Meadows in an 18 mm storm. Thus grassland management is important for slowing overland flow and delaying peak flows across upland headwaters. Surface roughness was also strongly controlled by annual cycles of vegetation growth, decay, grazing and cutting. Winter overland flow velocities were significantly higher than in summer, varying between 0.004 m/s (Rushes, November) and 0.034 m/s (Rushes, June); and velocities significantly increased after cutting varying between 0.006 m/s (Hay meadows, July) and 0.054 m/s (Hay meadows, September). These results show that seasonal vegetation change should be incorporated into flood modelling, as cycles of surface roughness in grasslands strongly modify overland flow, potentially having a large impact on downstream flood peak and timing. Our data also showed that Darcy‐Weisbach roughness approximations greatly over‐estimated measured flow velocities.
Accelerated continental‐scale snowmelt and ecohydrological impacts in the four largest Siberian river basins in response to spring warming
Authors: Suzuki Kazuyoshi , Hiyama Tetsuya , Matsuo Koji , Ichii Kazuhito , Iijima Yoshihiro , Yamazaki Dai 
Published: June 2020

AbstractRiver runoff from the four largest Siberian river basins (the Ob, Yenisei, Lena, and Kolyma) considerably contributes to freshwater flux into the Arctic Ocean from the Eurasian continent. However, the effects of variation in snow cover fraction on the ecohydrological variations in these basins are not well understood. In this study, we analysed the spatiotemporal variability of the maximum snow cover fraction (SCFmax) in the four Siberian river basins. We compared the SCFmaxfrom 2000 to 2016 with data in terms of monthly temperature and precipitation, night‐time surface temperatures, the terrestrial water storage anomaly (TWSA), the normalised difference vegetation index (NDVI), and river runoff. Our results exhibit a decreasing trend in the April SCFmaxvalues since 2000, largely in response to warming air temperatures in April. We identified snowmelt water as the dominant control on the observed increase in the runoff contribution in May across all four Siberian river basins. In addition, we detected that the interannual river runoff was predominantly controlled by interannual variations in the TWSA. The NDVI in June was strongly controlled by the timing of the snowmelt along with the surface air temperature and TWSA in June. The rate of increase in the freshwater flux from the four Siberian rivers decreased from 2000 to 2016, exhibiting large interannual variations corresponding to interannual variations in the TWSA. However, we identified a clear increase trend in the freshwater flux of ~4 km3/year when analysing the long‐term 39‐year historical record (1978–2016). Our results suggest that continued global warming will accelerate the transition towards the earlier timing of snowmelt and spring freshwater flux into the Arctic Ocean. Our findings also highlight the effects of earlier snowmelt on ecohydrological changes in the Northern Hemisphere.
Effect of Saponin from Tupistra chinensis Baker on proliferation and apoptosis of ovarian cancer cells by Wnt/β‐Catenin pathway
Authors: Ji Xiaoli , Yang Chengcheng , Xie Jia , Yin Xiaolan , Hu Quan 
Published: June 2020

AbstractThe present study aimed to investigate the molecular mechanism and the effect of Saponin from Tupistra chinensis Baker (STCB) on the proliferation and apoptosis of ovarian cancer cells. To investigate the inhibitory effect of STCB on the proliferation of ovarian cancer cells, SKOV3 cells were cultured and the methyl thiazolyl tetrazolium assay was used. Flow cytometry was also used to analyze the cell cycle distribution and apoptotic rate. Ki‐67, cyclin D1, cleaved caspase‐3, cleaved caspase‐9, β‐catenin, and c‐Myc protein expressions were detected by western blot. Ovarian cancer cells were treated with STCB and Wnt pathway activator lithium chloride (LiCl). These methods were also used to determine the proliferation, cell cycle distribution, and apoptosis of ovarian cancer cells. In STCB‐treated group, the proliferation inhibition and apoptosis rate, the proportion of G0‐G1 phase, and the expression level of cleaved caspase‐3 and 9 of ovarian cancer cells were significantly increased. Similarly, the expression of Ki‐67, cyclin D1, β‐catenin, and c‐Myc were significantly decreased (p < .05). The results also showed that in STCB‐LiCl‐treated group, while the proliferation inhibition rate of ovarian cancer cells, the proportion of G0‐G1 cells, the expression level of cleaved caspase‐3 and 9, and the apoptosis rate (p < .05) were significantly decreased, the expression level of Ki‐67, cyclin D1, β‐catenin, and c‐Myc was significantly increased. STCB induced G0‐G1 phase arrest, inhibited cell proliferation, and promoted apoptosis of ovarian cancer cells by inhibiting Wnt/β‐catenin pathway.
Rapid identification of human ovarian cancer in second harmonic generation images using radiomics feature analyses and tree‐based pipeline optimization tool
Authors: Wang Guangxing , Sun Yang , Chen Youting , Gao Qiqi , Peng Dongqing , Lin Hongxin , Zhan Zhenlin , Liu Zhiyi , Zhuo Shuangmu 
Published: June 2020

AbstractOvarian cancer is currently one of the most common cancers of the female reproductive organs, and its mortality rate is the highest among all types of gynecologic cancers. Rapid and accurate classification of ovarian cancer plays an important role in the determination of treatment plans and prognoses. Nevertheless, the most commonly used classification method is based on histopathological specimen examination, which is time‐consuming and labor‐intensive. Thus, in this study, we utilize radiomics feature extraction methods and the automated machine learning tree‐based pipeline optimization tool (TOPT) for analysis of 3D, second harmonic generation images of benign, malignant and normal human ovarian tissues, to develop a high‐efficiency computer‐aided diagnostic model. Area under the receiver operating characteristic curve values of 0.98, 0.96 and 0.94 were obtained, respectively, for the classification of the three tissue types. Furthermore, this approach can be readily applied to other related tissues and diseases, and has great potential for improving the efficiency of medical diagnostic processes.
Preparation recombination human‐like collagen/fibroin scaffold and promoting the cell compatibility with osteoblasts
Authors: Hu Kun , Hu Miaomiao , Xiao YongHao , Cui Yuzhu , Yan Jia , Yang Guijuan , Zhang Fan , Lin Guangqin , Yi Hanping , Han Lu , Li LuHai , Wei Yen , Cui Fuzhai 
Published: June 2020

AbstractOn this basis, a novel recombinant human‐like collagen (RHLC)/silk fibroin scaffold material with high porosity and controllable aperture was prepared. The compatibility of osteoblasts (OB) with the blends was tested in vitro. The morphology, adhesion and growth of scaffold cells were observed by scanning electron microscope and laser confocal microscope. Extensive measurements, including 3‐[4, 5‐dimethylthiazole‐2‐acyl]‐2, 5‐diphenyl tetrabrominate assays, intracellular total protein content, and alkaline phosphatase activity assays were performed after 7 days of culture. Survival and protein content increased in RHLC/fibroin stents. LSCM and SEM results confirmed that the cells grew better in the mixed scaffolds than in the pure silk scaffolds, and showed that the cells were easy to adhere and diffuse in the RHLC/silk scaffolds. RHLC/silk fibroin scaffolds are promising biomaterials for bone tissue engineering.
Poly‐L‐lactide scaffolds with super pores obtained by freeze‐extraction method
Authors: Budnicka Monika , Kołbuk Dorota , Ruśkowski Paweł , Gadomska‐Gajadhur Agnieszka 
Published: June 2020

AbstractA nonplanar polylactide scaffold to be used in tissue engineering was obtained by freeze‐extraction method. Properties of the scaffold were modified by adding Eudragit® E100. The impact of the modification on morphology, porosity and pore size, mass absorbability, mechanical properties was determined. Scanning electron microscopy (SEM), hydrostatic weighing test, static compression test was used to this end. The chemical composition of the scaffold was defined based on infrared spectroscopy (FTIR) and energy‐dispersive X‐ray spectroscopy (EDX). Biocompatibility was confirmed by quantitative tests and microscopic observation. The obtained results show that the obtained scaffolds may be applied as a carrier of hydrophilic cellular growth factors for more efficient tissue regeneration.
Population Pharmacokinetic Model of Dexmedetomidine in a Heterogeneous Group of Patients
Authors: Ber Justyna , Wiczling Paweł , Hołysz Marcin , Klupczyńska Agnieszka , Bartkowska‐Śniatkowska Alicja , Bieda Krzysztof , Smuszkiewicz Piotr , Nowicka Małgorzata , Żurański Łukasz , Sobczyński Paweł , Matysiak Jan , Grześkowiak Edmund , Bienert Agnieszka 
Published: June 2020

AbstractDexmedetomidine is a hepatically eliminated drug with sedative, anxiolytic, sympatholytic, and analgesic properties that has been increasingly used for various indications in the form of a short or continuous intravenous infusion. This study aimed to propose a population pharmacokinetic (PK) model of dexmedetomidine in a heterogeneous group of intensive care unit patients, incorporating 29 covariates potentially linked with dexmedetomidine PK. Data were collected from 70 patients aged between 0.25 and 88 years and treated with dexmedetomidine infusion for various durations at 1 of 4 medical centers. Statistical analysis was performed using a nonlinear mixed‐effect model. Categorical and continuous covariates including demographic data, hemodynamic parameters, biochemical markers, and 11 single‐nucleotide polymorphisms were tested. A 2‐compartment model was used to describe dexmedetomidine PK. An allometric/isometric scaling was used to account for body weight difference in PK parameters, and the Hill equation was used to describe the maturation of clearance. Typical values of the central and peripheral volume of distribution and the systemic and distribution clearance for a theoretical adult patient were central volume of distribution = 22.50 L, peripheral volume of distribution  = 86.1 L, systemic clearance =  34.7 L/h, and distribution clearance = 40.8 L/h. The CYP1A2 genetic polymorphism and noradrenaline administration were identified as significant covariates for clearance. A population PK model of dexmedetomidine was successfully developed. The proposed model is well calibrated to the observed data. The identified covariates account for <5% of interindividual variability and consequently are of low clinical significance for the purpose of dose adjustment.
Relative importance of top‐down vs. bottom‐up control of lake phytoplankton vertical distributions varies among fluorescence‐based spectral groups
Authors: Lofton Mary E. , Leach Taylor H. , Beisner Beatrix E. , Carey Cayelan C. 
Published: June 2020

AbstractThe relative importance of top‐down vs. bottom‐up control of phytoplankton biomass in aquatic ecosystems has been long debated and studied. However, few studies have considered the relative importance of top‐down vs. bottom‐up control on phytoplankton vertical distributions and characteristics of deep chlorophyll maxima (DCMs), and fewer still have investigated the importance of these drivers for multiple phytoplankton groups. We examined depth profiles of four phytoplankton spectral groups and a suite of top‐down (zooplankton) and bottom‐up (nutrients, temperature, and light) drivers from 51 north temperate lakes varying on gradients of size, trophic state, light availability, and thermal stratification. We used regression trees to identify the most important drivers of different vertical distribution metrics for each phytoplankton spectral group. The relative importance of top‐down vs. bottom‐up control varied across spectral groups and was related to the characteristics of the dominant taxa within each spectral group, as assessed by microscope counts. Zooplankton biomass was the most important driver of brown algae vertical distributions, likely because this group contained highly edible taxa (primarily chrysophytes), while thermal stratification predicted vertical distributions of buoyancy‐regulating cyanobacteria. Our work highlights the importance of examining phytoplankton community composition to improve understanding of DCM characteristics and top‐down vs. bottom‐up control of phytoplankton in aquatic systems.
Infection of filamentous phytoplankton by fungal parasites enhances herbivory in pelagic food webs
Authors: Frenken Thijs , Wolinska Justyna , Tao Yile , Rohrlack Thomas , Agha Ramsy 
Published: June 2020

AbstractChytrid fungal parasites are ubiquitous in aquatic ecosystems and infect a wide array of aquatic organisms, including all phytoplankton groups. In addition to their role as parasites, chytrids serve as food to zooplankton, thereby establishing an alternative trophic link between primary and secondary production in pelagic food webs, the so‐called mycoloop. We hypothesized that, in addition to the mycoloop, chytrid infection facilitates grazing of filamentous phytoplankton by rendering it more edible to zooplankton consumers through infection‐induced fragmentation. We undertook grazing assays to compare the ability of the key zooplankter Daphnia to graze on a filamentous cyanobacterium in the presence or absence of chytrid infection. A near doubling in mean clearance rates was consistently recorded when Daphnia were fed with infected cultures of the cyanobacterium as compared to uninfected ones. Infected filaments were shorter than noninfected ones, indicating that infection‐induced fragmentation undermines resistance of filamentous phytoplankton to grazing. We propose an extended conceptualization of the mycoloop that includes both direct effects (i.e., transfer via grazing of chytrid zoospores) and indirect effects (i.e., trophic upgrading and facilitated grazing on phytoplankton via fragmentation) of chytrid infection on trophic transfer at the base of pelagic food webs.
Observation of Novel Robust Edge States in Dissipative Non‐Hermitian Quantum Walks
Authors: Wang Bo , Chen Tian , Zhang Xiangdong 
Published: June 2020

AbstractRecently, the study of non‐Hermitian physics has attracted considerable attention. The modified bulk‐boundary correspondence has been proposed to understand topological edge states in non‐Hermitian static systems. Here, a new experimental observation of edge states in non‐Hermitian time‐driven systems (quantum walks) is reported. Topologically edge states protected by Hermitian conjugation of particle–hole symmetry (PHS†) are found in the unbroken parity–time (PT)‐symmetric phase. When the system changes from the unbroken to the broken PT‐symmetric phase, the topological phase transition occurs accompanied by the change of the number of edge states. The robust properties of these edge states against static perturbations and disorder are also demonstrated experimentally. The finding of robust edge states in non‐Hermitian systems inspires to explore a robust transport channel in ubiquitously complex systems with strong dissipation.
Hydrogen‐Bonding UCST‐Thermosensitive Nanogels by Direct Photo‐RAFT Polymerization‐Induced Self‐Assembly in Aqueous Dispersion
Authors: Tran Thi Nga , Piogé Sandie , Fontaine Laurent , Pascual Sagrario 
Published: June 2020

AbstractHydrogen‐bonding upper critical solution temperature (UCST) thermosensitive nanogels based on poly(N‐acryloyl glycinamide) (PNAGA) are synthesized by photo‐reversible addition‐fragmentation chain transfer mediated polymerization‐induced self‐assembly (photo‐RAFT PISA) in aqueous dispersion using N,N′‐methylenebis(acrylamide) as crosslinker and poly(oligo(ethylene glycol) methyl ether acrylate) as both stabilizer and macromolecular chain transfer agent (macro‐CTA). Highly stable, spherical nanogels with narrow polydispersity are efficiently produced up to complete monomer conversion within 1 h under UV irradiation at low temperature (3 °C). The thermosensitive behavior of PNAGA‐based nanogels, as assessed by dynamic light scattering and UV–vis spectrophotometry, exhibits reversible heating‐induced swelling and cooling‐induced shrinking corresponding to the expected UCST behavior. The hydrodynamic diameter, swelling ratio, and phase transition temperature of nanogels can be tuned by modifying the initial molar ratio of monomer‐to‐macro‐CTA and the amount of crosslinker in the photo‐RAFT PISA of NAGA.
MADVent: A low‐cost ventilator for patients with COVID‐19
Authors: Vasan Aditya , Weekes Reiley , Connacher William , Sieker Jeremy , Stambaugh Mark , Suresh Preetham , Lee Daniel E. , Mazzei William , Schlaepfer Eric , Vallejos Theodore , Petersen Johan , Merritt Sidney , Petersen Lonnie , Friend James ,   Acute Ventilation Rapid Response Taskforce (AVERT)
Published: June 2020

AbstractThe COVID‐19 pandemic has produced critical shortages of ventilators worldwide. There is an unmet need for rapidly deployable, emergency‐use ventilators with sufficient functionality to manage COVID‐19 patients with severe acute respiratory distress syndrome. Here, we show the development and validation of a simple, portable and low‐cost ventilator that may be rapidly manufactured with minimal susceptibility to supply chain disruptions. This single‐mode continuous, mandatory, closed‐loop, pressure‐controlled, time‐terminated emergency ventilator offers robust safety and functionality absent in existing solutions to the ventilator shortage. Validated using certified test lungs over a wide range of compliances, pressures, volumes and resistances to meet U.S. Food and Drug Administration standards of safety and efficacy, an Emergency Use Authorization is in review for this system. This emergency ventilator could eliminate controversial ventilator rationing or splitting to serve multiple patients. All design and validation information is provided to facilitate ventilator production even in resource‐limited settings.
Improving the slice interaction of 2.5D CNN for automatic pancreas segmentation
Authors: Zheng Hao , Qian Lijun , Qin Yulei , Gu Yun , Yang Jie 
Published: June 2020

PurposeVolumetric pancreas segmentation can be used in the diagnosis of pancreatic diseases, the research about diabetes and surgical planning. Since manual delineation is time‐consuming and laborious, we develop a deep learning‐based framework for automatic pancreas segmentation in three dimensional (3D) medical images.MethodsA two‐stage framework is designed for automatic pancreas delineation. In the localization stage, a Square Root Dice loss is developed to handle the trade‐off between sensitivity and specificity. In refinement stage, a novel 2.5D slice interaction network with slice correlation module is proposed to capture the non‐local cross‐slice information at multiple feature levels. Also a self‐supervised learning‐based pre‐training method, slice shuffle, is designed to encourage the inter‐slice communication. To further improve the accuracy and robustness, ensemble learning and a recurrent refinement process are adopted in the segmentation flow.ResultsThe segmentation technique is validated in a public dataset (NIH Pancreas‐CT) with 82 abdominal contrast‐enhanced 3D CT scans. Fourfold cross‐validation is performed to assess the capability and robustness of our method. The dice similarity coefficient, sensitivity, and specificity of our results are 86.21 ± 4.37%, 87.49 ± 6.38% and 85.11 ± 6.49% respectively, which is the state‐of‐the‐art performance in this dataset.ConclusionsWe proposed an automatic pancreas segmentation framework and validate in an open dataset. It is found that 2.5D network benefits from multi‐level slice interaction and suitable self‐supervised learning method for pre‐training can boost the performance of neural network. This technique could provide new image findings for the routine diagnosis of pancreatic disease.