bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bacterial structure and dynamics in mango (Mangifera indica) orchards after long term organic and conventional treatments under subtropical ecosystem
Authors: Kumar Govind , Suman Archana , Lal Shatrohan , Ram R. A. , Bhatt Pankaj , Pandey Ghanshyam , Chaudhary Parul , Rajan Shailendra 
Published: October 2021

AbstractThis study explores the comparative effect of conventional and organic treatments on the rhizosphere microbiome of Mangifera indica cv. Dashehari. The long-term exposures (about 20 years) were monitored under a subtropical ecosystem. Based on plant growth properties and acetylene reduction assay, 12 bacterial isolates (7 from G1-organic and 5 from G2-conventional systems) were identified as Pseudomonas and Bacillus spp. In the conventional system, dehydrogenase activity significantly decreased (0.053 µg TPF formed g−1 of soil h−1) and adversely affected the bacterial diversity composition. In comparison, organic treatments had a good impact on dehydrogenase activity (0.784 µg TPF formed g−1 of soil h−1), alkaline phosphatase (139.25 µg PNP g−1 soil h−1), and bacterial community composition. The Metagenomics approach targeted the V3 and V4 regions to see the impact in the phylum, order, family, genus, and species for both the treatments. Results showed that phylum Acidobacteria (13.6%), Firmicutes (4.84%), and Chloroflexi (2.56%) were dominating in the G2 system whereas phylum Bacteroides (14.55%), Actinobacteria (7.45%), and Proteobacteria (10.82%) were abundantly dominated in the G1 system. Metagenome sequences are at the NCBI-GenBank sequence read archive with SRX8289747 (G1) and SRX8289748 (G2) in the study PRJNA631113. Results indicated that conventional and organic conditions affect rhizosphere microbiome and their environment.
RETRACTED ARTICLE: Human induced pluripotent stem cell-derived platelets loaded with lapatinib effectively target HER2+ breast cancer metastasis to the brain
Authors: Bhan Arunoday , Ansari Khairul , Chen Mike Y. , Jandial Rahul 
Published: October 2021

AbstractPrognosis of patients with HER2+ breast-to-brain-metastasis (BBM) is dismal even after current standard-of-care treatments, including surgical resection, whole-brain radiation, and systemic chemotherapy. Radiation and systemic chemotherapies can also induce cytotoxicity, leading to significant side effects. Studies indicate that donor-derived platelets can serve as immune-compatible drug carriers that interact with and deliver drugs to cancer cells with fewer side effects, making them a promising therapeutic option with enhanced antitumor activity. Moreover, human induced pluripotent stem cells (hiPSCs) provide a potentially renewable source of clinical-grade transfusable platelets that can be drug-loaded to complement the supply of donor-derived platelets. Here, we describe methods for ex vivo generation of megakaryocytes (MKs) and functional platelets from hiPSCs (hiPSC-platelets) in a scalable fashion. We then loaded hiPSC-platelets with lapatinib and infused them into BBM tumor-bearing NOD/SCID mouse models. Such treatment significantly increased intracellular lapatinib accumulation in BBMs in vivo, potentially via tumor cell-induced activation/aggregation. Lapatinib-loaded hiPSC-platelets exhibited normal morphology and function and released lapatinib pH-dependently. Importantly, lapatinib delivery to BBM cells via hiPSC-platelets inhibited tumor growth and prolonged survival of tumor-bearing mice. Overall, use of lapatinib-loaded hiPSC-platelets effectively reduced adverse effects of free lapatinib and enhanced its therapeutic efficacy, suggesting that they represent a novel means to deliver chemotherapeutic drugs as treatment for BBM.
Assessing signals of selection and historical demography to develop conservation strategies in the Chilean emblematic Araucaria araucana
Authors: Fuentes Glenda , González Fidelina , Saavedra Javier , López-Sepúlveda Patricio , Victoriano Pedro F. , Stuessy Tod F. , Ruiz-Ponce Eduardo 
Published: October 2021

AbstractLoss of genetic diversity reduces the ability of species to evolve and respond to environmental change. Araucaria araucana is an emblematic conifer species from southern South America, with important ethnic value for the Mapuche people (Pehuenche); the Chilean Government has catalogued its conservation status as vulnerable. Climatic fluctuations were potentially a major impact in the genetic variation within many tree species. In this context, the restricted geographic distribution of A. araucana in Chile appears to be a consequence of the Last Glacial Maximum (LGM). During the past two centuries, strong human intervention has also affected the geographical distribution and population sizes of A. araucana. Reduction of population size may cause loss of genetic diversity, which could affect frequency of adaptive loci. The aims of this study were to know the existence of potential loci under selection and populations with genetic, demographic disequilibrium in the Chilean distribution of A. araucana. Based on 268 polymorphic AFLP loci, we have investigated potential loci under selection and genetic, demographic disequilibrium within seven Chilean populations of Araucaria araucana. Correlation of 41 outlier loci with the environmental variables of precipitation and temperature reveals signatures of selection, whereas 227 neutral loci provide estimates of demographic equilibrium and genetic population structure. Three populations are recommended as priorities for conservation.
Empirically classifying network mechanisms
Authors: Langendorf Ryan E. , Burgess Matthew G. 
Published: October 2021

AbstractNetwork data are often explained by assuming a generating mechanism and estimating related parameters. Without a way to test the relevance of assumed mechanisms, conclusions from such models may be misleading. Here we introduce a simple empirical approach to mechanistically classify arbitrary network data as originating from any of a set of candidate mechanisms or none of them. We tested our approach on simulated data from five of the most widely studied network mechanisms, and found it to be highly accurate. We then tested 1284 empirical networks spanning 17 different kinds of systems against these five widely studied mechanisms. We found that 387 (30%) of these empirical networks were classified as unlike any of the mechanisms, and only 1% or fewer of the networks classified as each of the mechanisms for which our approach was most sensitive. Based on this, we use Bayes’ theorem to show that most of the 70% of empirical networks our approach classified as a mechanism could be false positives, because of the high sensitivity required of a test to detect rarely occurring mechanisms. Thus, it is possible that very few of our empirical networks are described by any of these five widely studied mechanisms. Additionally, 93 networks (7%) were classified as plausibly being governed by each of multiple mechanisms. This raises the possibility that some systems are governed by mixtures of mechanisms. We show that mixtures are often unidentifiable because different mixtures can produce structurally equivalent networks, but that we can still accurately predict out-of-sample functional properties.
Angiogenic effects of cell therapy within a biomaterial scaffold in a rat hind limb ischemia model
Authors: Amani Saeede , Shahrooz Rasoul , Hobbenaghi Rahim , Mohammadi Rahim , Baradar Khoshfetrat Ali , Karimi Ali , Bakhtiari Zahra , Adcock Ian M. , Mortaz Esmaeil 
Published: October 2021

AbstractCritical limb ischemia (CLI) is a life- and limb-threatening condition affecting 1–10% of humans worldwide with peripheral arterial disease. Cellular therapies, such as bone marrow-derived mesenchymal stem cells (MSCs) have been used for the treatment of CLI. However, little information is available regarding the angiogenic potency of MSCs and mast cells (MC) in angiogenesis. The aim of this study was to evaluate the ability of MCs and MSCs to induce angiogenesis in a rat model of ischemic hind limb injury on a background of a tissue engineered hydrogel scaffold. Thirty rats were randomly divided into six control and experimental groups as follows: (a) Control healthy (b) Ischemic positive control with right femoral artery transection, (c) ischemia with hydrogel scaffold, (d) ischemia with hydrogel plus MSC, (e) ischemia with hydrogel plus MC and (f) ischemia with hydrogel plus MSC and MCs. 106 of each cell type, isolated from bone marrow stroma, was injected into the transected artery used to induce hind limb ischemia. The other hind limb served as a non-ischemic control. After 14 days, capillary density, vascular diameter, histomorphometry and immunohistochemistry at the transected location and in gastrocnemius muscles were evaluated. Capillary density and number of blood vessels in the region of the femoral artery transection in animals receiving MSCs and MCs was increased compared to control groups (P < 0.05). Generally the effect of MCs and MSCs was similar although the combined MC/MSC therapy resulted in a reduced, rather than enhanced, effect. In the gastrocnemius muscle, immunohistochemical and histomorphometric observation showed a great ratio of capillaries to muscle fibers in all the cell-receiving groups (P < 0.05). The data indicates that the combination of hydrogel and cell therapy generates a greater angiogenic potential at the ischemic site than cell therapy or hydrogels alone.
Biosynthesis of iron oxide magnetic nanoparticles using clinically isolated Pseudomonas aeruginosa
Authors: Khan Abid Ali , Khan Sana , Khan Suhaib , Rentschler Simone , Laufer Stefan , Deigner Hans-Peter 
Published: October 2021

AbstractMagnetotactic bacteria are microscale complex natural systems that synthesize magnetic nanoparticles through biologically controlled mineralization. Nanoparticles produced by this process are biocompatible due to the presence of surrounding membranes. The mechanism controlling synthesis is cost-effective and is executed by complex genomes (operons). The results are monodispersed magnetic nanoparticles displaying advantages over polydispersed ones synthesized by physical and chemical methods. In this work, we isolated Pseudomonas aeruginosa from clinical samples and demonstrated its ability to biosynthesize magnetic nanoparticles. P. aeruginosa was thrived in a carbon-minimal medium supplemented with iron at low pH. The cells aligned parallel to a magnetic field, confirming their magnetic properties. The magnetic nanoparticles were extracted, purified, and characterized using electron microscopy, magnetometry, dynamic light scattering, and X-ray diffraction. This work represents the first isolation of a magnetotactic bacterium from clinical samples. The aerobic nature of these bacteria allows them to be easily cultured under laboratory conditions, unlike their well-known microaerophilic counterparts. The biosynthesized magnetic nanoparticles can be used in many applications, including magnetic resonance imaging, diagnostics, and therapeutics (i.e., magnetic hyperthermia).
Long-term stability predictions of therapeutic monoclonal antibodies in solution using Arrhenius-based kinetics
Authors: Kuzman Drago , Bunc Marko , Ravnik Miha , Reiter Fritz , Žagar Lan , Bončina Matjaž 
Published: October 2021

AbstractLong-term stability of monoclonal antibodies to be used as biologics is a key aspect in their development. Therefore, its possible early prediction from accelerated stability studies is of major interest, despite currently being regarded as not sufficiently robust. In this work, using a combination of accelerated stability studies (up to 6 months) and first order degradation kinetic model, we are able to predict the long-term stability (up to 3 years) of multiple monoclonal antibody formulations. More specifically, we can robustly predict the long-term stability behaviour of a protein at the intended storage condition (5 °C), based on up to six months of data obtained for multiple quality attributes from different temperatures, usually from intended (5 °C), accelerated (25 °C) and stress conditions (40 °C). We have performed stability studies and evaluated the stability data of several mAbs including IgG1, IgG2, and fusion proteins, and validated our model by overlaying the 95% prediction interval and experimental stability data from up to 36 months. We demonstrated improved robustness, speed and accuracy of kinetic long-term stability prediction as compared to classical linear extrapolation used today, which justifies long-term stability prediction and shelf-life extrapolation for some biologics such as monoclonal antibodies. This work aims to contribute towards further development and refinement of the regulatory landscape that could steer toward allowing extrapolation for biologics during the developmental phase, clinical phase, and also in marketing authorisation applications, as already established today for small molecules.
Genome sequencing of turmeric provides evolutionary insights into its medicinal properties
Authors: Chakraborty Abhisek , Mahajan Shruti , Jaiswal Shubham K. , Sharma Vineet K. 
Published: October 2021

AbstractCurcuma longa, or turmeric, is traditionally known for its immense medicinal properties and has diverse therapeutic applications. However, the absence of a reference genome sequence is a limiting factor in understanding the genomic basis of the origin of its medicinal properties. In this study, we present the draft genome sequence of C. longa, belonging to Zingiberaceae plant family, constructed using 10x Genomics linked reads and Oxford Nanopore long reads. For comprehensive gene set prediction and for insights into its gene expression, transcriptome sequencing of leaf tissue was also performed. The draft genome assembly had a size of 1.02 Gbp with ~70% repetitive sequences, and contained 50,401 coding gene sequences. The phylogenetic position of C. longa was resolved through a comprehensive genome-wide analysis including 16 other plant species. Using 5,388 orthogroups, the comparative evolutionary analysis performed across 17 species including C. longa revealed evolution in genes associated with secondary metabolism, plant phytohormones signaling, and various biotic and abiotic stress tolerance responses. These mechanisms are crucial for perennial and rhizomatous plants such as C. longa for defense and environmental stress tolerance via production of secondary metabolites, which are associated with the wide range of medicinal properties in C. longa.
The loss of DHX15 impairs endothelial energy metabolism, lymphatic drainage and tumor metastasis in mice
Authors: Ribera Jordi , Portolés Irene , Córdoba-Jover Bernat , Rodríguez-Vita Juan , Casals Gregori , González-de la Presa Bernardino , Graupera Mariona , Solsona-Vilarrasa Estel , Garcia-Ruiz Carmen , Fernández-Checa José C. , Soria Guadalupe , Tudela Raúl , Esteve-Codina Anna , Espadas Guadalupe , Sabidó Eduard , Jiménez Wladimiro , Sessa William C. , Morales-Ruiz Manuel 
Published: October 2021

AbstractDHX15 is a downstream substrate for Akt1, which is involved in key cellular processes affecting vascular biology. Here, we explored the vascular regulatory function of DHX15. Homozygous DHX15 gene deficiency was lethal in mouse and zebrafish embryos. DHX15—/— zebrafish also showed downregulation of VEGF-C and reduced formation of lymphatic structures during development. DHX15+/− mice depicted lower vascular density and impaired lymphatic function postnatally. RNAseq and proteome analysis of DHX15 silenced endothelial cells revealed differential expression of genes involved in the metabolism of ATP biosynthesis. The validation of these results demonstrated a lower activity of the Complex I in the mitochondrial membrane of endothelial cells, resulting in lower intracellular ATP production and lower oxygen consumption. After injection of syngeneic LLC1 tumor cells, DHX15+/− mice showed partially inhibited primary tumor growth and reduced lung metastasis. Our results revealed an important role of DHX15 in vascular physiology and pave a new way to explore its potential use as a therapeutical target for metastasis treatment.
Few‐shot learning with relation propagation and constraint
Authors: Gong Huiyun , Wang Shuo , Zhao Xiaowei , Yan Yifan , Ma Yuqing , Liu Wei , Liu Xianglong 
Published: October 2021

AbstractPrevious deep learning methods usually required large‐scale annotated data, which is computationally exhaustive and unrealistic in certain scenarios. Therefore, few‐shot learning, where only a few annotated training images are available for training, has attracted increasing attention these days, showing huge potential in practical applications, such as portable equipment or security inspection, and so on. However, current few‐shot learning methods usually neglect the valuable semantic correlations between samples, thereby failing in extracting discriminating relations to achieve accurate predictive results. In this work, extending on a recent state‐of‐the‐art few‐shot learning method, transductive relation‐propagation network (TRPN), which considers the correlations between training samples, a constrained relation‐propagation network is proposed to further regularise the distilled correlations and thus achieve favourable few‐shot classification performance. The proposed framework contains three main components, namely preprocess module, relational propagation module, and relation constraint module. First, sample features are extracted and a relation graph node is constructed by treating the relation of each support–query pair as a graph node in the preprocess module. After that, in the relation propagation module (RPM), the valuable information of support–query pairs is modelled and propagated to directly generate the relational representations for further prediction. Then, a relation constraint module is introduced to regularise the relational representations and make it consistent with the ground‐truth relations as much as possible. With the guidance of the effective RPM and relation constraint module, the relational representations of the support–query pairs are distinguishable and thus can achieve accurate predictive results. Comprehensive experiments conducted on widely used benchmarks validate the effectiveness of our method compared to state‐of‐the‐art few‐shot classification approaches.
Direction of arrival estimation based on modified fast off‐grid L1‐SVD
Authors: Xu Xiangjun , Shen Mingwei , Wu Xiaohuan , Wu Di , Zhu Daiyin 
Published: October 2021

AbstractThis paper proposes a modified fast off‐grid L1‐SVD (M‐FOGL1SVD) method for direction of arrival (DOA) estimation. Unlike FOGL1SVD, after obtaining the positions of the nonzero rows of the signal sources, the off‐grid overcomplete basis matrix is used to update the signal sources, thus improving the estimation accuracy of it. In addition, to reduce the approximate error of the first‐order off‐grid model, a second‐order off‐grid model is introduced through a further Taylor expansion of the steering vector. Finally, the formula for solving the off‐grid gap under the novel model is derived. Extensive simulation results indicate that the proposed algorithm has better performance than FOGL1SVD in terms of DOA estimation precision.
Marking function of Stokes number on airfoils’ aerodynamic penalties in a gas–solid flow
Authors: Jin Junjun , Lu Zhiliang , Guo Tongqing , Zhou Di , Li Qiaozhong 
Published: October 2021

AbstractThis paper aims to employ the Stokes number to mark aerodynamic penalties of airfoils caused by particles, which is crucial to implement their scaling experiments in a gas‐solid flow. Each Stokes number is associated with a series of approximate aerodynamic penalties which are obtained at the same Reynolds number with different chord lengths. In the process, two phenomena which go against the mark are discussed and their mechanisms are revealed. The results show they occur at smaller and larger ranges of Stokes number, respectively. The effect of gravity is the leading cause and a larger chord length or diameter particle can strength its effect. The application scope of the mark, meanwhile, is ascertained. A chord length smaller than 1.5 m is advised at Re = 1.00 × 106 and those at other Reynolds numbers are also presented. As Stokes number decreases from 3, the aerodynamic penalty increases exponentially first at the advised chord length and reaches up to their peak values at the Stokes number of 0.050. In addition, the change of the aerodynamic penalty with Stokes number is dominated by the momentum exchange in the direction of gravity in the region between the particle injection plane and the airfoil.
MIRACL Co‐Simulation platform for control and operation of distributed wind in microgrid
Authors: Bhattarai Bishnu , Marinovici Laurentiu , Sarker Partha S. , Orrell Alice 
Published: October 2021

AbstractThis paper presents a co‐simulation platform (CSP) developed as a part of the “Microgrids, Infrastructure Resilience and Advanced Controls Launchpad (MIRACL)” project, hereafter called MIRACL‐CSP, to allow simulation‐based testing, demonstration, and evaluations of distributed wind under various grid operating conditions. MIRACL‐CSP provides modular interactions among the power distribution system, distributed wind, and utility decision‐making framework. A hierarchical engine for large‐scale infrastructure co‐simulations (HELICS) is used as the core engine of MIRACL‐CSP to establish time and information coordination among the MIRACL‐CSP modules. In this study, MIRACL‐CSP performance is demonstrated using the IEEE 123‐node test distribution grid modelled in GridLAB‐D and the utility decision support application modelled in Python. The functionality of MIRACL‐CSP is demonstrated through various grid operational scenarios in a microgrid and networked microgrid environment. A co‐simulation study is described that demonstrated MIRACL‐CSP capabilities for the microgrid operational scenario in the IEEE 123‐node test system. MIRACL‐CSP is a generic platform that facilitates distributed wind research for different test systems, applications, and valuation of distributed wind.