bluuebunny/crossref_metadata_2025_split huggingface dataset:
16S rDNA based skin microbiome data of healthy individuals and leprosy patients from India
Authors: Bayal Nitin , Nagpal Sunil , Haque Mohammed Monzoorul , Patole Milind S. , Valluri Vijayalakshmi , Suryavanshi Rohini , Mande Sharmila S. , Mande Shekhar C. 
Published: October 2019

AbstractLeprosy is an infectious disease that has predilection in skin and peripheral nerves. Skin has its own microbiome, however it is not extensively studied in Indian leprosy patients. Here, by using next-generation 16S rDNA sequencing, we have attempted to assess the skin associated microbial diversity pertaining to affected and unaffected skin of Indian leprosy patients. A total of 90 skin swab samples were collected from 60 individuals (30 healthy controls, 30 patients) residing in Hyderabad and Miraj, two distinct geographical locations in India to assess the homo/heterogeneity of skin microbial signatures. While a large increase in genus Methylobacterium and Pseudomonas was seen in patients from Miraj and Hyderabad respectively, a considerable decrease in genus Staphylococcus in the leprosy patients (as compared to controls) from both geographical locations was also observed. We expect that, these datasets can not-only provide further interesting insights, but will also help to observe dynamics of microbiome in the diseased state and generate hypotheses to test for skin microbiome transplantation studies in leprosy.
Satellite-based time-series of sea-surface temperature since 1981 for climate applications
Authors: Merchant Christopher J. , Embury Owen , Bulgin Claire E. , Block Thomas , Corlett Gary K. , Fiedler Emma , Good Simon A. , Mittaz Jonathan , Rayner Nick A. , Berry David , Eastwood Steinar , Taylor Michael , Tsushima Yoko , Waterfall Alison , Wilson Ruth , Donlon Craig 
Published: October 2019

AbstractA climate data record of global sea surface temperature (SST) spanning 1981–2016 has been developed from 4 × 1012 satellite measurements of thermal infra-red radiance. The spatial area represented by pixel SST estimates is between 1 km2 and 45 km2. The mean density of good-quality observations is 13 km−2 yr−1. SST uncertainty is evaluated per datum, the median uncertainty for pixel SSTs being 0.18 K. Multi-annual observational stability relative to drifting buoy measurements is within 0.003 K yr−1 of zero with high confidence, despite maximal independence from in situ SSTs over the latter two decades of the record. Data are provided at native resolution, gridded at 0.05° latitude-longitude resolution (individual sensors), and aggregated and gap-filled on a daily 0.05° grid. Skin SSTs, depth-adjusted SSTs de-aliased with respect to the diurnal cycle, and SST anomalies are provided. Target applications of the dataset include: climate and ocean model evaluation; quantification of marine change and variability (including marine heatwaves); climate and ocean-atmosphere processes; and specific applications in ocean ecology, oceanography and geophysics.
Mithramycin A Inhibits Colorectal Cancer Growth by Targeting Cancer Stem Cells
Authors: Quarni Waise , Dutta Rinku , Green Ryan , Katiri Sandhyabanu , Patel Bhaumik , Mohapatra Shyam S. , Mohapatra Subhra 
Published: October 2019

AbstractThe pivotal role of cancer initiating stem cells (CSCs) in tumor initiation, growth, metastasis and drug resistance has led to the postulation of a ‘total cancer therapy’ paradigm, which involves targeting both cancer cells and CSCs for effective therapy. However, the progress in identifying drugs for total cancer therapy has been limited. Herein, we show for the first time that mithramycin A (Mit-A) can successfully inhibit CSC proliferation, in addition to inhibiting bulk cancer cells in a model of colorectal cancer (CRC), the second leading cause of death among men and women in the United States. To this end, a polymeric nanofiber scaffold culture system was established to develop 3D tumor organoids (tumoroids) from CRC cell lines such as HT29, HCT116, KM12, CT26 and MC38 as well as ex vivo mouse tumors. These tumoroids possessed increased expression of CSC markers and transcription factors, expanded the number of CSCs in culture and increased CSC functional properties measured by aldehyde dehydrogenase activity. Screening of an NCI library of FDA approved drugs led to the identification of Mit-A as a potential total cancer therapy drug. In both sphere and tumoroid culture, Mit-A inhibits cancer growth by reducing the expression of cancer stemness markers. In addition, Mit-A inhibits the expression of SP1, a previously known target in CRCs. Moreover, Mit-A significantly reduces growth of tumoroids in ex vivo cultures and CRC tumor growth in vivo. Finally, a dose-dependent treatment on CRC cells indicate that Mit-A significantly induces the cell death and PARP-cleavage of both CSC and non-CSC cells. Taken together the results of these in vitro, ex vivo and in vivo studies lead to the inference that Mit-A is a promising drug candidate for total cancer therapy of CRCs.
Structural analysis of biological targets by host:guest crystal lattice engineering
Authors: Ernst Patrick , Plückthun Andreas , Mittl Peer R. E. 
Published: October 2019

AbstractTo overcome the laborious identification of crystallisation conditions for protein X-ray crystallography, we developed a method where the examined protein is immobilised as a guest molecule in a universal host lattice. We applied crystal engineering to create a generic crystalline host lattice under reproducible, predefined conditions and analysed the structures of target guest molecules of different size, namely two 15-mer peptides and green fluorescent protein (sfGFP). A fusion protein with an N-terminal endo-α-N-acetylgalactosaminidase (EngBF) domain and a C-terminal designed ankyrin repeat protein (DARPin) domain establishes the crystal lattice. The target is recruited into the host lattice, always in the same crystal form, through binding to the DARPin. The target structures can be determined rapidly from difference Fourier maps, whose quality depends on the size of the target and the orientation of the DARPin.
Identification of microRNAs and relative target genes in Moringa oleifera leaf and callus
Authors: Pirrò Stefano , Matic Ivana , Guidi Arianna , Zanella Letizia , Gismondi Angelo , Cicconi Rosella , Bernardini Roberta , Colizzi Vittorio , Canini Antonella , Mattei Maurizio , Galgani Andrea 
Published: October 2019

AbstractMicroRNAs, a class of small, non-coding RNAs, play important roles in plant growth, development and stress response by negatively regulating gene expression. Moringa oleifera Lam. plant has many medical and nutritional uses; however, little attention has been dedicated to its potential for the bio production of active compounds. In this study, 431 conserved and 392 novel microRNA families were identified and 9 novel small RNA libraries constructed from leaf, and cold stress treated callus, using high-throughput sequencing technology. Based on the M. oleifera genome, the microRNA repertoire of the seed was re-evaluated. qRT-PCR analysis confirmed the expression pattern of 11 conserved microRNAs in all groups. MicroRNA159 was found to be the most abundant conserved microRNA in leaf and callus, while microRNA393 was most abundantly expressed in the seed. The majority of predicted microRNA target genes were transcriptional factors involved in plant reproduction, growth/development and abiotic/biotic stress response. In conclusion, this is the first comprehensive analysis of microRNAs in M. oleifera leaf and callus which represents an important addition to the existing M. oleifera seed microRNA database and allows for possible exploitation of plant microRNAs induced with abiotic stress, as a tool for bio-enrichment with pharmacologically important phytochemicals.
Regulatory Crosstalk of Doxorubicin, Estradiol and TNFα Combined Treatment in Breast Cancer-derived Cell Lines
Authors: Nassiri Isar , Inga Alberto , Meškytė Erna Marija , Alessandrini Federica , Ciribilli Yari , Priami Corrado 
Published: October 2019

AbstractWe present a new model of ESR1 network regulation based on analysis of Doxorubicin, Estradiol, and TNFα combination treatment in MCF-7. We used Doxorubicin as a therapeutic agent, TNFα as marker and mediator of an inflammatory microenvironment and 17β-Estradiol (E2) as an agonist of Estrogen Receptors, known predisposing factor for hormone-driven breast cancer, whose pharmacological inhibition reduces the risk of breast cancer recurrence. Based on the results of transcriptomics analysis, we found 71 differentially expressed genes that are specific for the combination treatment with Doxorubicin + Estradiol + TNFα in comparison with single or double treatments. The responsiveness to the triple treatment was examined for seven genes by qPCR, of which six were validated, and then extended to four additional cell lines differing for p53 and/or ER status. The results of differential regulation enrichment analysis highlight the role of the ESR1 network that included 36 of 71 specific differentially expressed genes. We propose that the combined activation of p53 and NF-kB transcription factors significantly influences ligand-dependent, ER-driven transcriptional responses, also of the ESR1 gene itself. These results provide a model of coordinated interaction of TFs to explain the Doxorubicin, E2 and TNFα induced repression mechanisms.
Deep learning-based optical field screening for robust optical diffraction tomography
Authors: Ryu DongHun , Jo YoungJu , Yoo Jihyeong , Chang Taean , Ahn Daewoong , Kim Young Seo , Kim Geon , Min Hyun-Seok , Park YongKeun 
Published: October 2019

AbstractIn tomographic reconstruction, the image quality of the reconstructed images can be significantly degraded by defects in the measured two-dimensional (2D) raw image data. Despite the importance of screening defective 2D images for robust tomographic reconstruction, manual inspection and rule-based automation suffer from low-throughput and insufficient accuracy, respectively. Here, we present deep learning-enabled quality control for holographic data to produce robust and high-throughput optical diffraction tomography (ODT). The key idea is to distil the knowledge of an expert into a deep convolutional neural network. We built an extensive database of optical field images with clean/noisy annotations, and then trained a binary-classification network based upon the data. The trained network outperformed visual inspection by non-expert users and a widely used rule-based algorithm, with >90% test accuracy. Subsequently, we confirmed that the superior screening performance significantly improved the tomogram quality. To further confirm the trained model’s performance and generalisability, we evaluated it on unseen biological cell data obtained with a setup that was not used to generate the training dataset. Lastly, we interpreted the trained model using various visualisation techniques that provided the saliency map underlying each model inference. We envision the proposed network would a powerful lightweight module in the tomographic reconstruction pipeline.
Intranasal oxytocin selectively modulates the behavior of rhesus monkeys in an expression matching task
Authors: Taubert Jessica , Flessert Molly , Liu Ning , Ungerleider Leslie G. 
Published: October 2019

AbstractAlthough the neuropeptide oxytocin (OT) is thought to regulate prosocial behavior in mammals, there is considerable debate as to how intranasal OT influences primate behavior. The aim of this study was to determine whether intranasal OT has a general anxiolytic effect on the performance of rhesus monkeys tasked with matching face stimuli, or a more selective effect on their behavior towards aversive facial expressions. To this end, we developed an innovative delayed match-to-sample task where the exact same trials could be used to assess either a monkey’s ability to match facial expressions or facial identities. If OT has a general affect on behavior, then performance in both tasks should be altered by the administration of OT. We tested four male rhesus monkeys (Macaca mulatta) in both the expression and identity task after the intranasal administration of either OT or saline in a within-subjects design. We found that OT inhalation selectively reduced a selection bias against negatively valenced expressions. Based on the same visual input, performance in the identity task was also unaffected by OT. This dissociation provides evidence that intranasal OT affects primate behavior under very particular circumstances, rather than acting as a general anxiolytic, in a highly translatable nonhuman model, the rhesus monkey.
Antiviral interferons induced by Newcastle disease virus (NDV) drive a tumor-selective apoptosis
Authors: Ginting Teridah Ernala , Christian Salomo , Larasati Young Othiwi , Suryatenggara Jeremiah , Suriapranata Ivet Marita , Mathew George 
Published: October 2019

AbstractNewcastle disease virus (NDV) strongly induces both type I and III antiviral interferons (IFNs-α/-β and IFN-λ, respectively) in tumor cells while it induces mainly type III IFN in normal cells. Impairment of antiviral type I IFN signaling in tumor cells is thought to be the reason for effective oncolysis. However, there is lack of clarity why lentogenic strain NDV can also induce oncolysis. NDV infection caused apoptosis in normal and tumor cells as demonstrated with the caspase-3 enzyme activation and annexin-V detection. The apoptosis response was inhibited by B18R protein (a type I IFN inhibitor) in tumor cells i.e. A549 and U87MG, and not in normal cells i.e. NB1RGB and HEK293. Similarly, UV-inactivated medium from NDV infection was shown to induce apoptosis in corresponding cells and the response was inhibited in A549 and U87MG cells with the addition of B18R protein. Treatment with combination of IFNs-α/-β/-λ or IFNs-α/-β or IFN-λ in NB1RGB, HEK293, A549 and U87MG showed that caspase activity in IFNs-α/-β/-λ group was the highest, followed with IFN-α/-β group and IFN-λ group. This suggests that tumor-selectivity of NDV is mainly because of the cumulative effect of type I and III in tumor cells that lead to higher apoptotic effect.
Rapid human-driven undermining of atoll island capacity to adjust to ocean climate-related pressures
Authors: Duvat Virginie K. E. , Magnan Alexandre K. 
Published: October 2019

AbstractMost studies addressing the future of atoll islands focused on ocean-climate drivers of risk, especially sea-level rise, and disregarded the role of local human disturbances. However, the future habitability of these countries will critically depend on the response of inhabited and exploited islands to ocean-climate pressures. Here, using the Maldives as a case study and based on a database including 608 islands (representing 56.8% and 86.0% of the country’s land area and population, respectively), we assess the influence of human disturbances on island natural response capacity over the last decade. We show that over the last decade, island change was rapid and primarily controlled by anthropogenic drivers. The great majority of inhabited and exploited islands now exhibit an altered-to-annihilated capacity to respond to ocean-climate pressures, which has major implications for future research and adaptation strategies. First, future studies should consider not only climate, but also anthropogenic tipping points (in contrast to climate tipping points). Second, adaptation strategies must be implemented without delay, despite climate uncertainties, in order to contain any additional detrimental path-dependency effects. This study provides critical information for better addressing the attribution issue under climate change, and a replicable rapid assessment frame.
Diat.barcode, an open-access curated barcode library for diatoms
Authors: Rimet Frédéric , Gusev Evgenuy , Kahlert Maria , Kelly Martyn G. , Kulikovskiy Maxim , Maltsev Yevhen , Mann David G. , Pfannkuchen Martin , Trobajo Rosa , Vasselon Valentin , Zimmermann Jonas , Bouchez Agnès 
Published: October 2019

AbstractDiatoms (Bacillariophyta) are ubiquitous microalgae which produce a siliceous exoskeleton and which make a major contribution to the productivity of oceans and freshwaters. They display a huge diversity, which makes them excellent ecological indicators of aquatic ecosystems. Usually, diatoms are identified using characteristics of their exoskeleton morphology. DNA-barcoding is an alternative to this and the use of High-Throughput-Sequencing enables the rapid analysis of many environmental samples at a lower cost than analyses under microscope. However, to identify environmental sequences correctly, an expertly curated reference library is needed. Several curated libraries for protists exists; none, however are dedicated to diatoms. Diat.barcode is an open-access library dedicated to diatoms which has been maintained since 2012. Data come from two sources (1) the NCBI nucleotide database and (2) unpublished sequencing data of culture collections. Since 2017, several experts have collaborated to curate this library forrbcL, a chloroplast marker suitable for species-level identification of diatoms. For the latest version of the database (version 7), 605 of the 3482 taxonomical names originally assigned by the authors of therbcL sequences were modified after curation. The database is accessible athttps://www6.inra.fr/carrtel-collection_eng/Barcoding-database.
Impact of UV sterilization and short term storage on the in vitro release kinetics and bioactivity of biomolecules from electrospun scaffolds
Authors: Evrova Olivera , Kellenberger Damian , Scalera Chiara , Calcagni Maurizio , Giovanoli Pietro , Vogel Viola , Buschmann Johanna 
Published: October 2019

AbstractTo effectively translate bioactive scaffolds into a preclinical setting, proper sterilization techniques and storage conditions need to be carefully considered, as the chosen sterilization technique and storage condition might affect the structural and mechanical properties of the scaffolds, as well as the bioactivity and release kinetics of the incorporated biomolecules. Since rarely tested or quantified, we show here in a proof-of-concept study how these parameters are affected by UV sterilization and one week storage at different temperatures using bioactive electrospun DegraPol scaffolds that were specifically designed for application in the field of tendon rupture repair. Even though UV sterilization and the different storage conditions did not impact the morphology or the physicochemical properties of the bioactive scaffolds, UV sterilization caused significant attenuation of the growth factor release kinetics, here platelet derived growth factor (PDGF-BB) release (by approx. 85%) and slight decrease in ascorbic acid release (by approx. 20%). In contrast, 4 °C and −20 °C storage did not have a major effect on the release kinetics of PDGF-BB, while storage at room temperature caused increase in PDGF-BB released. All storage conditions had little effect on ascorbic acid release. Equally important, neither UV sterilization nor storage affected the bioactivity of the released PDGF-BB, suggesting stability of the bioactive scaffolds for at least one week and showing potential for bioactive DegraPol scaffolds to be translated into an off-the-shelf available product. These parameters are expected to be scaffold and protein-dependent.
The geographical and seasonal mosaic in a plant-herbivore interaction: patterns of defences and herbivory by a specialist and a non-specialist
Authors: Verçosa Diomar , Cogni Rodrigo , Alves Marcos Nopper , Trigo José Roberto 
Published: October 2019

AbstractIn order to evaluate the geographic mosaic theory of coevolution, it is crucial to investigate geographical variation on the outcome of ecological interactions and the functional traits which dictate these outcomes. Plant populations are attacked by specialist and non-specialist herbivores and may have different types of chemical and biotic defences. We investigated geographical and seasonal variation in the interaction between the plantCrotalaria pallidaand its two major herbivores (the specialistUtetheisa ornatrixand the non-specialistEtiella zinckenella). We first showed that attack by the two herbivores and a chemical and a biotic defence vary greatly in time and space. Second, we performed a common garden experiment that revealed genetic variation among populations in herbivore resistance and a chemical defence, but no genetic variation in a biotic defence. Third, we sampled 20 populations on a much larger geographical scale and showed great variation in attack rates by the two herbivores and a chemical defence. Finally, we showed that herbivory is not correlated with a chemical defence in the 20 field populations. Our study shows that to understand the evolution of ecological interactions it is crucial to investigate how the outcome of the interaction and the important species traits vary geographically and seasonally.
Pleione: A tool for statistical and multi-objective calibration of Rule-based models
Authors: Santibáñez Rodrigo , Garrido Daniel , Martin Alberto J. M. 
Published: October 2019

AbstractMathematical models based on Ordinary Differential Equations (ODEs) are frequently used to describe and simulate biological systems. Nevertheless, such models are often difficult to understand. Unlike ODE models, Rule-Based Models (RBMs) utilise formal language to describe reactions as a cumulative number of statements that are easier to understand and correct. They are also gaining popularity because of their conciseness and simulation flexibility. However, RBMs generally lack tools to perform further analysis that requires simulation. This situation arises because exact and approximate simulations are computationally intensive. Translating RBMs into ODEs is commonly used to reduce simulation time, but this technique may be prohibitive due to combinatorial explosion. Here, we present the software called Pleione to calibrate RBMs. Parameter calibration is essential given the incomplete experimental determination of reaction rates and the goal of using models to reproduce experimental data. The software distributes stochastic simulations and calculations and incorporates equivalence tests to determine the fitness of RBMs compared with data. The primary features of Pleione were thoroughly tested on a model of gene regulation in Escherichia coli. Pleione yielded satisfactory results regarding calculation time and error reduction for multiple simulators, models, parameter search strategies, and computing infrastructures.