bluuebunny/crossref_metadata_2025_split huggingface dataset:
Complete biosynthetic pathway to the antidiabetic drug acarbose
Authors: Tsunoda Takeshi , Samadi Arash , Burade Sachin , Mahmud Taifo 
Published: June 2022

AbstractAcarbose is a bacterial-derived α-glucosidase inhibitor clinically used to treat patients with type 2 diabetes. As type 2 diabetes is on the rise worldwide, the market demand for acarbose has also increased. Despite its significant therapeutic importance, how it is made in nature is not completely understood. Here, we report the complete biosynthetic pathway to acarbose and its structural components, GDP-valienol and O-4-amino-(4,6-dideoxy-α-D-glucopyranosyl)-(1→4)-O-α-D-glucopyranosyl-(1→4)-D-glucopyranose. GDP-valienol is derived from valienol 7-phosphate, catalyzed by three cyclitol modifying enzymes, whereas O-4-amino-(4,6-dideoxy-α-D-glucopyranosyl)-(1→4)-O-α-D-glucopyranosyl-(1→4)-D-glucopyranose is produced from dTDP-4-amino-4,6-dideoxy-D-glucose and maltose by the glycosyltransferase AcbI. The final assembly process is catalyzed by a pseudoglycosyltransferase enzyme, AcbS, which is a homologue of AcbI but catalyzes the formation of a non-glycosidic C-N bond. This study clarifies all previously unknown steps in acarbose biosynthesis and establishes a complete pathway to this high value pharmaceutical.
The source of the Black Death in fourteenth-century central Eurasia
Authors: Spyrou Maria A. , Musralina Lyazzat , Gnecchi Ruscone Guido A. , Kocher Arthur , Borbone Pier-Giorgio , Khartanovich Valeri I. , Buzhilova Alexandra , Djansugurova Leyla , Bos Kirsten I. , Kühnert Denise , Haak Wolfgang , Slavin Philip , Krause Johannes 
Published: June 2022

AbstractThe origin of the medieval Black Death pandemic (ad 1346–1353) has been a topic of continuous investigation because of the pandemic’s extensive demographic impact and long-lasting consequences1,2. Until now, the most debated archaeological evidence potentially associated with the pandemic’s initiation derives from cemeteries located near Lake Issyk-Kul of modern-day Kyrgyzstan1,3–9. These sites are thought to have housed victims of a fourteenth-century epidemic as tombstone inscriptions directly dated to 1338–1339 state ‘pestilence’ as the cause of death for the buried individuals9. Here we report ancient DNA data from seven individuals exhumed from two of these cemeteries, Kara-Djigach and Burana. Our synthesis of archaeological, historical and ancient genomic data shows a clear involvement of the plague bacterium Yersinia pestis in this epidemic event. Two reconstructed ancient Y. pestis genomes represent a single strain and are identified as the most recent common ancestor of a major diversification commonly associated with the pandemic’s emergence, here dated to the first half of the fourteenth century. Comparisons with present-day diversity from Y. pestis reservoirs in the extended Tian Shan region support a local emergence of the recovered ancient strain. Through multiple lines of evidence, our data support an early fourteenth-century source of the second plague pandemic in central Eurasia.
Monthly spatial dynamics of the Bay of Biscay hake-sole-Norway lobster fishery: an ISIS-Fish database
Authors: Vigier Audric , Bertignac Michel , Mahévas Stéphanie 
Published: June 2022

AbstractWe propose a database to describe the Bay of Biscay mixed demersal European fishery over the period 2010–2020 for the ISIS-Fish simulation tool. It was built upon national and European fishing databases, scientific survey datasets, models estimates, literature, and the formulation of assumptions. It accounts explicitly for spatial and seasonal processes, and for mixed fisheries phenomenons. This database encompasses population dynamics for 3 stocks, hake, sole and Norway lobster, exploitation dynamics for numerous fleets and métiers, and the description of current fishing management, as well as fishers adaptation. A calibration procedure was designed to ensure consistency between all these diverse and heterogeneous parameters compiled and estimated in the ISIS-Fish database and to ensure the model reproduces closely historical catch patterns. This database is a starting point towards operational simulations, of use for understanding the functioning of the fishery, the assessment of management strategies, or delivering short and long-term scenarios. It can be used to reproduce historical catch patterns, with room for improvement on some inter-annual and spatial dynamics.
A dataset of diversity and distribution of rodents and shrews in China
Authors: Chen Jin-Jin , Xu Qiang , Wang Tao , Meng Fan-Fei , Li Zhi-Wei , Fang Li-Qun , Liu Wei 
Published: June 2022

AbstractThe rodents and shrews are important reservoirs for a large number of zoonotic pathogens. Here by performing a literature review, we determined the occurrence and distribution of rodents and shrews in China at three scales including province, city, and county levels. The peer-reviewed papers published in English and Chinese were collected, standard procedures were applied in reference books, field surveys and websites to remove duplicates, and information on recorded locations of rodents and shrews was extracted. The dataset contains 13,911 records of geo-referenced occurrences for 364 rodents and shrews distributed over 1,663 locations distinguished. As pathogens continue to emerge from rodents and shrews, this dataset could assist efforts to put preliminary bounds around a variety of spatial analyses of rodents and shrews, facilitate a better understanding of the transmission risk of the pathogens they carry, and be helpful for assessing the risk of future emergence of rodent-borne zoonoses.
Biological traits of marine benthic invertebrates in Northwest Europe
Authors: Clare David S. , Bolam Stefan G. , McIlwaine Paul S. O. , Garcia Clement , Murray Joanna M. , Eggleton Jacqueline D. 
Published: June 2022

AbstractBiological traits analysis (BTA) provides insight into causes and consequences of biodiversity change that cannot be achieved using traditional taxonomic approaches. However, acquiring information on biological traits (i.e., the behavioural, morphological, and reproductive characteristics of taxa) can be extremely time-consuming, especially for large community datasets, thus hindering the successful application of BTA. Here, we present information on ten key biological traits for over a thousand marine benthic invertebrate taxa surveyed in Northwest Europe (mainly the UK shelf). Scores of 0 to 3 are provided to indicate our confidence that taxa exhibit each possible mode of trait expression. The information was acquired over a decade through an extensive appraisal of relevant sources, including peer-reviewed papers, books, online material and, where necessary, professional judgement. These data may be inspected, used, and augmented by fellow researchers, thus assisting in the wider application of BTA in marine benthic ecology.
In toto light sheet fluorescence microscopy live imaging datasets of Ceratitis capitata embryonic development
Authors: Strobl Frederic , Schetelig Marc F. , Stelzer Ernst H. K. 
Published: June 2022

AbstractThe Mediterranean fruit fly (medfly), Ceratitis capitata, is an important model organism in biology and agricultural research with high economic relevance. However, information about its embryonic development is still sparse. We share nine long-term live imaging datasets acquired with light sheet fluorescence microscopy (484.5 h total recording time, 373 995 images, 256 Gb) with the scientific community. Six datasets show the embryonic development in toto for about 60 hours at 30 minutes intervals along four directions in three spatial dimensions, covering approximately 97% of the entire embryonic development period. Three datasets focus on germ cell formation and head involution. All imaged embryos hatched morphologically intact. Based on these data, we suggest a two-level staging system that functions as a morphogenetic framework for upcoming studies on medfly. Our data supports research on wild-type or aberrant morphogenesis, quantitative analyses, comparative approaches to insect development as well as studies related to pest control. Further, they can be used to test advanced image processing approaches or to train machine learning algorithms and/or neuronal networks.
HOPS-R01 phase II trial evaluating neoadjuvant S-1 therapy for resectable pancreatic adenocarcinoma
Authors: Nakamura Toru , Hayashi Tsuyoshi , Kimura Yasutoshi , Kawakami Hiroshi , Takahashi Kuniyuki , Ishiwatari Hirotoshi , Goto Takuma , Motoya Masayo , Yamakita Keisuke , Sakuhara Yusuke , Ono Michihiro , Tanaka Eiichi , Omi Makoto , Murakawa Katsuhiko , Iida Tomoya , Sakurai Tamaki , Haba Shin , Abiko Takehiro , Ito Yoichi M. , Maguchi Hiroyuki , Hirano Satoshi ,   Hokkaido Pancreatic Cancer Study Group (HOPS), Nakamura Toru , Hayashi Tsuyoshi , Kimura Yasutoshi , Kawakami Hiroshi , Takahashi Kuniyuki , Ishiwatari Hirotoshi , Goto Takuma , Motoya Masayo , Yamakita Keisuke , Sakuhara Yusuke , Ono Michihiro , Tanaka Eiichi , Omi Makoto , Murakawa Katsuhiko , Iida Tomoya , Sakurai Tamaki , Haba Shin , Abiko Takehiro , Ito Yoichi M. , Maguchi Hiroyuki , Hirano Satoshi , Sasajima Junpei , Kitano Yohei , Yanagawa Nobuyuki , Matsumoto Kakuya , Tanno Satoshi , Imamura Masafumi , Shitani Masahiro , Takahashi Minoru , Miyakawa Hiroyuki , Nakamura Fumitaka , Ambo Yoshiyasu , Kamachi Hirofumi , Taketomi Akinobu 
Published: June 2022

AbstractAlthough neoadjuvant therapy (Nac) is recommended for high-risk resectable pancreatic cancer (R-PDAC), evidence regarding specific regimes is scarce. This report aimed to investigate the efficacy of S-1 Nac for R-PDAC. In a multicenter phase II trial, we investigated the efficacy of Nac S-1 (an oral fluoropyrimidine agent containing tegafur, gimeracil, and oteracil potassium) in R-PDAC patients. The protocol involved two cycles of preoperative S-1 chemotherapy, followed by surgery, and four cycles of postoperative S-1 chemotherapy. Two-year progression-free survival (PFS) rates were the primary endpoint. Overall survival (OS) rates and median survival time (MST) were secondary endpoints. Forty-nine patients were eligible, and 31 patients underwent resection following Nac, as per protocol (31/49; 63.3%). Per-protocol analysis included data from 31 patients, yielding the 2-year PFS rate of 58.1%, and 2-, 3-, and 5-year OS rates of 96.8%, 54.8%, and 44.0%, respectively. MST was 49.2 months. Intention-to-treat analysis involved 49 patients, yielding the 2-year PFS rate of 40.8%, and the 2-, 3-, and 5-year OS rates of 87.8%, 46.9%, and 33.9%, respectively. MST was 35.5 months. S-1 single regimen might be an option for Nac in R-PDAC; however, the high drop-out rate (36.7%) was a limitation of this study.
Urine metabolomics links dysregulation of the tryptophan-kynurenine pathway to inflammation and severity of COVID-19
Authors: Dewulf Joseph P. , Martin Manon , Marie Sandrine , Oguz Fabie , Belkhir Leila , De Greef Julien , Yombi Jean Cyr , Wittebole Xavier , Laterre Pierre-François , Jadoul Michel , Gatto Laurent , Bommer Guido T. , Morelle Johann 
Published: June 2022

AbstractSARS-CoV-2 causes major disturbances in serum metabolite levels, associated with severity of the immune response. Despite the numerous advantages of urine for biomarker discovery, the potential association between urine metabolites and disease severity has not been investigated in coronavirus disease 2019 (COVID-19). In a proof-of-concept study, we performed quantitative urine metabolomics in patients hospitalized with COVID-19 and controls using LC–MS/MS. We assessed whether metabolites alterations were associated with COVID-19, disease severity, and inflammation. The study included 56 patients hospitalized with COVID-19 (26 non-critical and 30 critical disease); 16 healthy controls; and 3 controls with proximal tubule dysfunction unrelated to SARS-CoV-2. Metabolomic profiling revealed a major urinary increase of tryptophan metabolites kynurenine (P < 0.001), 3-hydroxykynurenine (P < 0.001) and 3-hydroxyanthranilate (P < 0.001) in SARS-CoV-2 infected patients. Urine levels of kynurenines were associated with disease severity and systemic inflammation (kynurenine, r 0.43, P = 0.001; 3-hydroxykynurenine, r 0.44, P < 0.001). Increased urinary levels of neutral amino acids and imino acid proline were also common in COVID-19, suggesting specific transport defects. Urine metabolomics identified major alterations in the tryptophan-kynurenine pathway, consistent with changes in host metabolism during SARS-CoV-2 infection. The association between increased urinary levels of kynurenines, inflammation and COVID-19 severity supports further evaluation of these easily available biomarkers.
The seismic reflection Moho across the mid-Norwegian continental rifted margin
Authors: Peron-Pinvidic Gwenn 
Published: June 2022

AbstractThe Moho – defined as the boundary that separates the Earth’s crust from the underlying upper mantle at depths of about 5 to 7 km beneath the oceans and 30 to 40 km below continents – has been difficult to pin down with observations. Different methods have yield a variety of results, suggesting that this simple definition may be misleading. Here, we present high-resolution and deep penetrating seismic reflection data that image the whole margin basement of the mid-Norwegian rift system, including the lower basement, Moho and upper mantle, from the proximal to the outer margin domains. We propose a determination of the seismic reflection Moho in this modern rifted margin context and describe its structural heterogeneity along the margin. Finally, the seismic facies, reflectivity, geometries and structural details of the seismic reflection Moho are described and discussed in terms of tectonic deformation pattern.
Intelligent wearable allows out-of-the-lab tracking of developing motor abilities in infants
Authors: Airaksinen Manu , Gallen Anastasia , Kivi Anna , Vijayakrishnan Pavithra , Häyrinen Taru , Ilén Elina , Räsänen Okko , Haataja Leena M. , Vanhatalo Sampsa 
Published: June 2022

Abstract
Background
Early neurodevelopmental care needs better, effective and objective solutions for assessing infants’ motor abilities. Novel wearable technology opens possibilities for characterizing spontaneous movement behavior. This work seeks to construct and validate a generalizable, scalable, and effective method to measure infants’ spontaneous motor abilities across all motor milestones from lying supine to fluent walking.

Methods
A multi-sensor infant wearable was constructed, and 59 infants (age 5–19 months) were recorded during their spontaneous play. A novel gross motor description scheme was used for human visual classification of postures and movements at a second-level time resolution. A deep learning -based classifier was then trained to mimic human annotations, and aggregated recording-level outputs were used to provide posture- and movement-specific developmental trajectories, which enabled more holistic assessments of motor maturity.

Results
Recordings were technically successful in all infants, and the algorithmic analysis showed human-equivalent-level accuracy in quantifying the observed postures and movements. The aggregated recordings were used to train an algorithm for predicting a novel neurodevelopmental measure, Baba Infant Motor Score (BIMS). This index estimates maturity of infants’ motor abilities, and it correlates very strongly (Pearson’s r = 0.89, p < 1e-20) to the chronological age of the infant.

Conclusions
The results show that out-of-hospital assessment of infants’ motor ability is possible using a multi-sensor wearable. The algorithmic analysis provides metrics of motility that are transparent, objective, intuitively interpretable, and they link strongly to infants’ age. Such a solution could be automated and scaled to a global extent, holding promise for functional benchmarking in individualized patient care or early intervention trials.
Adversarial learning‐based multi‐timescale network resource management in multi‐mode green IoT network for smart building
Authors: Shi Cheng , Liu Pengju , Chen Yapeng , Zhou Zhenyu , Yang Junzhong , Zhao Chenkai , Chen Bei , Yang Sen , Mumtaz Shahid 
Published: June 2022

AbstractMulti‐mode green internet of things (IoT) network that integrates multiple communication media can well meet data transmission and processing demands of low‐carbon smart building. However, network resource management optimisation including joint optimisation of gateway and channel selection still faces technical challenges such as differentiated quality of service (QoS) demand guarantee, coupling between optimisation problems with different timescales, and adversary caused by multi‐device competition. To address these challenges, an adversarial learning‐based multi‐timescale network resource management algorithm for multi‐mode green IoT is proposed. Specifically, the minimisation problem of weighted difference between energy consumption and throughput under the long‐term queuing delay constraints is formulated to achieve differentiated QoS guarantee. Large‐timescale gateway selection is decoupled from small‐timescale channel selection by establishing matching preferences based on empirical performance, and optimised by using bilateral matching with quota. Finally, an exponential‐weight algorithm for exploration and exploitation (EXP3)‐based small‐timescale channel selection algorithm is proposed to achieve adversary awareness. Simulation results demonstrate that compared with asynchronous greedy matching algorithm and auction‐based many‐to‐many matching algorithm, the proposed algorithm performs superior in terms of energy consumption and throughput.
Self‐supervised monocular depth estimation via asymmetric convolution block
Authors: Hu Lingling , Zhang Hao , Wang Zhuping , Huang Chao , Zhang Changzhu 
Published: June 2022

AbstractWithout the dependence of depth ground truth, self‐supervised learning is a promising alternative to train monocular depth estimation. It builds its own supervision signal with the help of other tools, such as view synthesis and pose networks. However, more training parameters and time consumption may be involved. This paper proposes a monocular depth prediction framework that can jointly learn the depth value and pose transformation between images in an end‐to‐end manner. The depth network creatively employs an asymmetric convolution block instead of every square kernel layer to strengthen the learning ability of extracting image features when training. During inference time, the asymmetric kernels are fused and converted to the original network to predict more accurate image depth, thus bringing no extra computations anymore. The network is trained and tested on the KITTI monocular dataset. The evaluated results demonstrate that the depth model outperforms some State of the Arts (SOTA) approaches and can reduce the inference time of depth prediction. Additionally, the proposed model performs great adaptability on the Make3D dataset.
Active contour model of breast cancer DCE‐MRI segmentation with an extreme learning machine and a fuzzy C‐means cluster
Authors: Feng Bao , Zhou Haoyang , Feng Jin , Chen Yehang , Liu Yu , Yu Tianyou , Liu Zhuangsheng , Long Wansheng 
Published: June 2022

AbstractDue to the low contrast, blurred boundary and intensity inhomogeneity of the images, accurate segmentation of breast cancer lesions with dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) still has great challenges. This paper proposed an improved active contour model (ACM) for segmenting breast cancer lesions in DCE‐MRI images. First, based on the extreme learning machine (ELM) method, a robust function is proposed that combines image intensities and time‐domain features to enhance the difference between the lesions and other tissues. Second, an edge‐stop function (ESF) is introduced by combining the image intensity, time‐domain feature, and Hessian shape index to detect the irregular and blurred boundaries. At the boundary of breast cancer lesions, the energy function of ACM is minimized and the evolution of the contour curve completes, so the accurate lesion region of breast cancer can be segmented. The mean Dice similar coefficient (DICE), Jaccard similarity (JC) and Hausdorff distance (HD) of the segmentation of the proposed model in 50 samples are 85.88±6.62%, 75.72±9.68% and 11.62±4.72 mm, respectively. The results segmented by the proposed ACM are more similar to the manual segmentation than the compared models.
Toward fully compressible numerical simulations of stellar magneto-convection with the RAMSES code
Authors: Canivete Cuissa J. R. , Teyssier R. 
Published: June 2022

Context. Numerical simulations of magneto-convection have greatly expanded our understanding of stellar interiors and stellar magnetism. Recently, fully compressible hydrodynamical simulations of full-star models have demonstrated the feasibility of studying the excitation and propagation of pressure and internal gravity waves in stellar interiors, which would allow for a direct comparison with asteroseismological measurements. However, the impact of magnetic fields on such waves has not been taken into account yet in three-dimensional simulations.
Aims. We conduct a proof of concept for the realization of three-dimensional, fully compressible, magneto-hydrodynamical numerical simulations of stellar interiors with the RAMSES code.
Methods. We adapted the RAMSES code to deal with highly subsonic turbulence, typical of stellar convection, by implementing a well-balanced scheme in the numerical solver. We then ran and analyzed three-dimensional hydrodynamical and magneto-hydrodynamical simulations with different resolutions of a plane-parallel convective envelope on a Cartesian grid.
Results. Both hydrodynamical and magneto-hydrodynamical simulations develop a quasi-steady, turbulent convection layer from random density perturbations introduced over the initial profiles. The convective flows are characterized by small-amplitude fluctuations around the hydrodynamical equilibrium of the stellar interior, which is preserved over the whole simulation time. Using our compressible well-balanced scheme, we were able to model flows with Mach numbers as low as ℳ ∼ 10−3, but even lower Mach number flows are possible in principle. In the magneto-hydrodynamical runs, we observe an exponential growth of magnetic energy consistent with the action of a small-scale dynamo. The weak seed magnetic fields are amplified to mean strengths of 37% relative to the kinetic equipartition value in the highest resolution simulation. Since we chose a compressible approach, we see imprints of pressure and internal gravity waves propagating in the stable regions above and beneath the convection zone. In the magneto-hydrodynamical case, we measured a deficit in acoustic and internal gravity wave power with respect to the purely hydrodynamical counterpart of 16% and 13%, respectively.
Conclusions. The well-balanced scheme implemented in RAMSES allowed us to accurately simulate the small-amplitude, turbulent fluctuations of stellar (magneto-)convection. The qualitative properties of the convective flows, magnetic fields, and excited waves are in agreement with previous studies in the literature. The power spectra, profiles, and probability density functions of the main quantities converge with resolution. Therefore, we consider the proof of concept to be successful. The deficit of acoustic power in the magneto-hydrodynamical simulation shows that magnetic fields must be included in the study of pressure waves in stellar interiors. We conclude by discussing future developments.