dataesr/scientific-paragraphs-categorization huggingface dataset:
Xper3 is a collaborative system that manages structured descriptive data on taxa or specimens. It is available online and linked to web services including two services for identification: a free (multiple) access key (Vignes Lebbe et al. 2015)  and single access key  (Burguiere et al. 2013 ). These web services use the TDWG Structured Descriptive Data format (SDD) (Hagedorn et al. 2005). The Xper3 platform was launched in November 2013. Three years later, 1990 users had created accounts and edited 2499 knowledge bases (KB). Unfortunately, there exists no public overview of the existing content.
• characters and states, documented by texts and images cannot be used for building another key without making copies. In order to solve the first problem, we analyse Xper3 metadata (e. g. , name of KB, owner, number of contributors, date of creation, date of last modification) and we provide an overview of the existing content. Firstly, 48% of KB are empty or inactive with extremely limited content (fewer than 3 taxa or characters), which has not been accessed for a long time. We discard these KB in our analysis and only consider the 1300 active KB. We also discard "test" KB and duplicate KB. Surprisingly, we discovered 15 medical KB for diagnosis of various diseases and 34 non-taxonomic KB (e. g. , wine, fashion, computing equipment). For taxonomic KB, we present the taxonomic and geographic distribution of the KB (angiosperms and arthropods are prevailing taxa) and we compare with the number of known species.
The second point concerns semantic data sharing. We compute the rate of terms (character, character state) duplicated in several KB in the same taxonomic groups, in order to evaluate the interest in sharing resources between Xper3 KB. Then we look for existing ontologies in the bioportal (https://bioportal. bioontology. org/ontologies). Although Xper3 may manage structured data, its data model does not use an ontology language like RDF*1 or OWL*2 (ontology languages and tools offer unique identifier and reasoning mechanisms), and each KB has its own vocabulary. We will be contacting KB owners to obtain more detailed metadata and to facilitate the automatic publishing of authorized KB on the Xper3 website. We plan also to implement an easy link between Xper3 and external ontologies to help editing new KB and to export KB data models to existing ontologies.
Data collection. We stayed approximately 14 days in six Agta camps and three BaYaka camps to collect data on both reproductive histories and social interactions. Reproductive success. To establish a measure of reproductive success we conducted reproductive histories with 39 Agta and 38 BaYaka mothers. We enquired about all currently living offspring (of all ages), producing a proxy of reproductive success as it captures both fertility and early life survival. Motes. Social networks were captured using 'motes' (wireless sensing devices) which communicate with one another and store all communications within a specified distance  37. The device we utilised was the UCMote Mini (Unicomp Ltd, Standford, USA). Each device sends a message that contained its unique ID, a time stamp and the signal strength at a programmed interval (every two minutes).
All individuals within a camp wore the motes from a period ranging from five to nine days depending on the camp. While the motes were worn throughout the night, data was only selected from between 5:00 and 20:00. This was to avoid long hours of simply recording who slept in the same shelter. If individuals arrived at a camp during the experiment they were promptly given a mote, and entry time was recorded. Similarly, if an individual left a camp at any time before the end of the experiment, the time they returned the mote was recorded. To ensure swaps did not occur individuals were regularly asked to check they were wearing the correct armband. All mote numbers were also checked when they were being handed back to ensure we always knew who had worn each mote. Any swaps were recorded during the experiment and adjusted in the final data processing.
Validation of the motes can be found in the SI. Medical survey. Among the Agta we conducted a medical survey based on sickness symptoms over the last two weeks, focusing on gastro-intestinal disease, influenza and fever, respiratory tract infections and intestinal parasites. After data collection with a qualified health care assistant the completed questionnaire was handed back to the field doctor for diagnosis. The total number of medical diagnoses for each individual was calculated, which varied between zero to two instances of sickness. To control for wealth effects, we also recorded key household belongings present in each house during interviews (further information in the SI). Ethics. This research and fieldwork was approved by UCL Ethics Committee (UCL Ethics code 3086/003) and carried out with permission from local government and tribal leaders in Palanan and the Congo.
This raw data was adjusted for time present in camp of both individuals in the dyad, to control for individuals arriving to camp during the experiment or leaving the experiment early. The social network only comprised of individuals aged 12 years or older. This threshold was applied as after the age of eleven, hunter-gatherer children conduct significantly more caring and economic activities. They also require less care and provisioning themselves  93. All network measures were standardized by camp, thus represent whether or not a centrality score was high relative to the camp average  5, 94. Given that most camps were small, almost all individuals had some level of interaction with each other. Therefore, degree centrality was computed from the ties which were greater than 1% of recorded weighted interactions.
Measuring the effects of mothers' social network position on living offspring. We used number of living offspring as it captured both fertility and child survivorship and is, therefore, our best measure of reproductive success. Due to differences in data collection between the two fieldsites we were unable to use a more robust measure of fitness (survivorship to age 16) as we did in previous work  71  , because the BaYaka dataset does not include mortality data. Therefore, number of currently living offspring was used in both populations. In order to control for the relationship between age and reproductive success, we removed the effect of age on fertility by producing age-specific fertility residuals from non-linear models. Generalised linear models were run with the dependent variable of living offspring and predictors of age and the square of age to capture the quadratic nature of the fertility distribution.
These models contained a discrete variable of camp residence to capture any camp specific effects and all models met normality assumptions demonstrating the suitability of linear regressions (Table  S1 ). Exploration of the Agta data revealed that the relationship between network centrality and number of living offspring demonstrated a significant interaction with age. As a result, in both datasets two models were run, one containing the interaction effect between centrality and age, and one without. In all cases if the interaction was insignificant at p >0. 05 then the interaction was removed from the model and the non-interaction model is reported (non-significant models reported in the SI). Given the interaction term, age was mean centred (36 years in the Agta, and 41. 6 in the BaYaka) to ease interpretation.
Acknowledgements We thank the  Human Evolutionary Ecology  and  Hunter-Gatherer  groups at  University College London ,  Heidi Colleran ,  Sarah Myers  and  Matt Thomas  for their comments on earlier drafts,  Ed Seabright  for graphical input, our assistants in the Philippines and Congo, and most importantly, the Agta and  BaYaka. Finally , we thank  Lauren Brent  and one anonymous reviewer for their insightful and useful comments. This project was funded by  Leverhulme Trust  Grant  RP2011-R 045  (to A. B. M. and R. M. ). R. M. received funding from  European Research Council Advanced  Grant  AdG 249347.
To meet such treatment modality, in 2006, Campochiaro and colleagues delivered the gene encoding PEDF to the retina of nvAMD patients using adenoviral (Ad) delivery and reported significant improvement in 25% of patients after 12 weeks and no harmful side effects. 7, 8 However, no followup to the trial has been reported. Currently, three additional gene therapy clinical trials are ongoing (https://clinicaltrials. gov/): trial NCT01494805 is based on the use of an adeno-associated viral (AAV) vector encoding sFlt-1, a splice variant of VEGF receptor 1; trials NCT01301443 and NCT01678872 are based on the use of a lentiviral vector expressing endostatin and angiostatin (RetinoStat). Aside from the results reported by Campochiaro et al. ,  8   Ophthalmol. Vis. Sci. , abstract) in which substantial transgene expression as well as a safe and well-tolerated treatment exhibiting signs of clinical benefit were reported for RetinoStat.
No statistical difference was observed between PEDF secretion by PEDFtransfected and PEDFo-transfected human RPE cells for the first 3. 5 months. However, at 5 and 7 months after transfection, secretion by 1 Â 10 4 and 5 Â 10 3 pFAR-PEDFo-transfected human RPE cells was significantly higher than secretion by cells transfected with pFAR-PEDF, suggesting that the optimization protocol improved stability. In contrast to the genomic integration profile of retroviral systems and other transposon systems (piggyBac and Tol2), which show integration preferences for actively transcribed genes,  [51] [52] [53]  SB-based integration is random. 37, 54 Compared to computationally generated control datasets, SB100X-mediated genomic integration of the PEDF gene delivered by the pFAR4 vector into primary human RPE cells showed a close-to-random profile.
Real-Time qPCR For human RPE cells, real-time qPCRs were performed on a LightCycler 1. 2 Instrument using the LightCycler FastStart DNA Master SYBR Green I kit (Roche) according to the manufacturer's recommendations. The cDNA samples were run in duplicate using the following primers: GAPDH (GenBank: NM_002046. 3) as the internal control gene (F: 5 0 -ATC CCA TCA CCA TCT TCC AG-3 0 and R: 5 0 -ATG AGT CCT TCC ACG ATA CC-3 0 ), endogenous PEDF (GenBank: NM_002615. 4) (F: 5 0 -GCT GGC TTT GAG TGG AAC GA-3 0 and R: 5 0 -GTG TCC TGT GGA ATC TGC TG-3 0 ), and endogenous plus recombinant PEDF (F: 5 0 -CCT GCA GGA GAT GAA GCT GCA-3 0 and R: 5 0 -TCC ACC TGA GTC AGC TTG ATG-3 0 ), for the detection of the endogenous PEDF gene plus the PEDF and the optimized PEDF genes encoded in the pFAR4 miniplasmids.
Reactions were performed with diluted cDNA corresponding to 2 ng of initially used total RNA and a primer concentration of 0. 25 mM. Thermal cycler conditions were as follows: initial denaturation at 95 C for 10 min followed by 50 cycles with denaturation at 95 C for 10 s, annealing at 60 C for 8 s, and elongation at 72 C for 15 s. Melting curve analysis confirmed the application specificity of each primer pair. Data were processed by the LightCycler software 3. 5. 3 and evaluated using the comparative CT (2 -DDCT ) method, which describes relative gene expression. 59 r bovine IPE cells, real-time qPCRs were performed on a LightCycler 480 II instrument (Roche) using PerfeCta SYBR Green FastMix (Quanta Biosciences) according to manufacturer's recommendations. The cDNA samples were run in duplicate in three independent experiments using the following primers: GAPDH (GenBank: NM_001034034.
2) as the internal control gene (F: 5 0 -ATC ATC CCT GCT TCT ACT GG-3 0 and R: 5 0 -CTC AGT GTA GCC TAG AAT GC-3 0 ), endogenous PEDF (GenBank: AF017058. 1) (F: 5 0 -TTC CCT CTG GAC TAT CAC CT-3 0 and R: 5 0 -AAT CTG CCA TCC CTC TAG TG-3 0 ), and recombinant PEDF (F: 5 0 -CCT GCA GGA GAT GAA GCT GCA-3 0 and R: 5 0 -TCC ACC TGA GTC AGC TTG ATG-3 0 ), for the detection of the PEDF transgene encoded in the pFAR-PEDF and pFAR-PEDFo miniplasmids. Reactions were performed with diluted cDNA corresponding to 1. 2 ng of initially used total RNA, and primer concentrations of 3. 5 mM for GAPDH and recombinant PEDF, and 1. 75 mM for endogenous PEDF. Thermal cycler conditions were as follows: initial denaturation at 95 C for 10 min followed by 45 cycles with denaturation at 95 C for 5 s, annealing at 60 C for 10 s, and elongation at 72 C for 10 s.
Melting curve analysis confirmed the application specificity of each primer pair; standard curves demonstrated high efficiency and good reproducibility of each experiment. Data were processed by the LightCycler 480 software 1. 5. 1. 62 and evaluated using the standard curve-based absolute quantification method. The values were analyzed for statistical significance using a non-parametric Kruskal-Wallis test (GraphPad Prism, GraphPad).
ACKNOWLEDGMENTS This work was supported by the  European Union 's  Seventh Framework Programme  for research, technological development and demonstration, grant agreement no. 305134. C. Miskey  and Z. Ivics were supported by the  Center for Cell and Gene Therapy of the LOEWE (Landes-Offensive zur Entwicklung Wissenschaftlich-ökonomischer Exzellenz) program in Hessen, Germany. L. D. H. was supported by the  European Research Council  (advanced grant  ERC-2014-ADG 669207 ) and the  Medical Research Council  ( MR/ L007215/1 ). The authors thank  Anna Dobias ,  Antje Schiefer  ( Department of Ophthalmology, University Hospital RWTH Aachen ),  Gregg Sealy  ( Laboratory of Ophthalmology, University of Geneva ) for excellent technical support, the  Aachen Cornea Bank  ( Department of Ophthalmology, University Hospital RWTH Aachen ) for providing the human donor eyes, and  Perry B.
This work was supported by French government "Programme d'Investissements d' Avenir" under [Grant number ANR-11-INBS-0008] funding the Infectious Disease Models and Innovative Therapies (IDMIT, Fontenay-aux-Roses, France) infrastructure; and two Ph. D. grants from Société Française de Rhumatologie and INSERM. The authors warmly thank the IDMIT infrastructure staff for excellent technical assistance. The IDMIT infrastructure and its FlowCyTech facility are supported by the French government "Programme d'Investissements d' Avenir" (PIA), under grants ANR-11-INBS-0008 and ANR-10-EQPX-02-01, respectively.
Composition of Microbial Communities The four most common protist orders in our dataset were Cristamonadida (40. 3%), Cthulumonads (14. 8%), Trichonymphida (13. 4%), and Spirotrichonymphida (12. 7%). Members from all of these taxa carry bacterial symbionts  (Dolan, 2001; Noda et al. , 2003; Ohkuma et al. , 2007; Ikeda-Ohtsubo and Brune, 2009; Desai et al. , 2010; James et al. , 2013)  (Figure  3A ). The most common bacterial phyla were Bacteroidetes (40. 6%), Spirochaetes (21. 9%), Proteobacteria (12. 4%), and Elusimicrobia (9. 1%). Except for the Proteobacteria, all of these bacterial phyla contain symbionts of lower termite-associated protists (e. g. , Treponema and Endomicrobium)  (Noda et al. , 2005 (Noda et al. , , 2006;; Strassert et al. , 2010; He et al. , 2013)  (Figure  3B ). The prevalence of protist-associated bacteria among the persistent microbiota could help explain the correlation of protist and bacterial alpha-diversity shown in Figure  2.
This analysis included the Reticulitermes indicator taxa from Table  S2 , for which we wanted to find the close relatives. Furthermore, the analysis included, as potential origin of our indicator taxa, all bacteria for which we found at Blue numbers, bootstrap probability; red numbers, approximate unbiased probability  (Suzuki and Shimodaira, 2006). The weighted UniFrac metric was used. Clustering was performed using the UPGMA algorithm. least 100 sequences in all other termites, as well as all sequences in the DictDB database  (Mikaelyan et al. , 2015b)  (clades relevant for the indicator species are drawn in Figure  S4 , the full tree as Newick file can be found in File S2). This allowed us to detect several indicator OTUs that are most closely related to bacteria from the environment and non-dictyopteran hosts, suggesting acquisition of these bacteria on the Reticulitermes lineage.
9 and P < 0. 001 that comprise at least 1,000 sequences and have no known close bacterial relatives in wood-dwellers. #seqs, number of sequences in the corresponding indicator OTU; DictDb ID refers to the label set in the DictDb_v3 database. See Figure  S4  and File S2 for phylogenetic position of the indicator OTUs. microbiomes might suffer from the above-mentioned effects. Therefore, more studies that focus on the resident termite microbiome are required to formulate and test evolutionary and ecological hypotheses. In this study, we took a first step toward focusing on the resident microbiome by controlling environment, diet, and the influx of microbes into the intestinal tract under laboratory conditions. In order to control for the varying contributions of transient microbes to the gut community due to different diet sources, we developed a setup to study diverse termite species under common conditions in the laboratory by keeping all termites on Pinus wood for at least several weeks before the start of the experiment.
Analysis Data analysis was performed using MOTHUR version 1. 33. 3  (Schloss et al. , 2009) , following the MiSeq SOP (available at https://www. mothur. org/wiki/MiSeq_SOP, see also  Kozich et al. , 2013). Main data processing steps were quality filtering of raw sequence reads, denoising, removal of chimeric sequences, taxonomic classification, and OTU clustering at 97% sequence similarity. Our detailed MOTHUR script can be found in File S6. For taxonomic classification of the bacterial 16S OTUs a representative sequence of each OTU was aligned to DictDb_v3  (Mikaelyan et al. , 2015b). The DictDB database is the SILVA  (Quast et al. , 2013)  database extended by the most comprehensive collection of termite associated bacteria and allowed us to span a large set of termites and other Dictyoptera with our analysis.
18S protist OTUs were aligned and classified using all parabasalid sequences from the SILVA SSU Ref Nr 123 database that was extended by our custom made alignment and taxonomy reference (Files S7, S8). In order to avoid coverage bias, bacterial and protist datasets were rarefied resulting in 32,824 and 22,285 sequences per sample, respectively. Statistical tests and data visualization were performed in R version 3. 1. 2 (R Core  Team, 2014). Phylogenetic trees necessary to apply UniFrac as well as the trees including OTU representative sequences were generated with FastTree version 2. 1. 7 (Price et al. , 2010). The resulting trees were visualized with Dendroscope 3. 3. 4 (Huson and Scornavacca, 2012). Assuming that microbes that are ecologically relevant for the host should not be rare, we used the weighted Unifrac metric  (Lozupone and Knight, 2005)  for our analysis.
The sample stage was kept close to horizontal during the measurements by using a supermirror to alter the incoming beam angle to 0. 617°and 1. 4°for the two incident angles. The footprint was kept at 35 × 35 mm and centered beneath the cone: smaller than the 50 mm diameter circle under the rheometer cone. GISANS measurements were also taken on the same instrument by altering the beam collimation, with a footprint of 7 × 45 mm. The data were reduced in the usual way using the COSMOS program within LAMP. 37 The background was subtracted using adjacent pixels on the 2D detector away from any off-specular scattering. The data were fitted using LAMP and Rascal (A. Hughes, ISIS). The GISANS images were reduced using an IDL procedure provided by Erik Watkins (Los Alamos National Laboratory, USA), which was also used to convert the detector images to Q-space when considering changes in off-specular scattering.
■ RESULTS AND DISCUSSION Neutron Data (Low Concentration Surfactant). NR measurements were taken for 2. 5 mM AOT solution on alumina from D 2 O under static conditions. A large fringe was observed in the data compared to the bare Al 2 O 3 -D 2 O interface (Figure  2 ), corresponding to an adsorbed layer of AOT at the interface. The data are fitted to a model consisting of a symmetric head-tail-tail-head bilayer, with fittable parameters for the projected area per molecule (APM) and water molecules per head. These parameters then provide the scattering length density (SLD) profile, using known volumes for the head and tail portions of the molecule and conserving the head:tail ratio. The variation in SLD essentially provides the changes in composition away from the interface and is given by the sum of the neutron scattering lengths from all atoms within a unit cell divided by the volume of that unit cell.
5 targets. The morphology and chemical composition of targets, films and mid-IR structures were measured using a scanning electron microscope (SEM) with an energy-dispersive X-ray analyzer (EDS, JSM 6400-OXFORD Link INCA). Roughness of thin films was studied by atomic force microscopy (AFM, Ntegra Prima, NT-MDT). Tapping mode imaging was used on 2 μm × 2 μm area. Linear refractive indices of glasses, thin films and each layer of mid-IR guiding structure were obtained from the analysis of variable angle spectroscopic ellipsometry (VASE) data measured using two ellipsometers in UV-vis-NIR (300-2300 nm) and in NIR-MIR (1•7-30 μm) (J. A. Woollam Co. , Inc. , Lincoln, NE, U. S. A. ). Simulations to determine the design of optical waveguide working in mid-IR (at 7•7 μm) were performed based on refractive index contrast determined by VASE  [17, 19, 20].
The thicknesses (h) of both chalcogenide layers and the width (w) of the waveguide were established using a commercial software (FIMMWAVE, Photon Design) in order to obtain single-mode propagation at 7•7 μm and to maximize evanescent power factor ƞ in the superstrate  [21, 22]. A 5 μm-thick Ge 28. 1 Sb 6. 3 Se 65. 6 confinement layer was found to be sufficient to avoid radiation losses through the substrate. Thickness of Ge 12. 5 Sb 25 Se 62. 5 guiding layer between 1•5 and 2 μm allows obtaining single-mode propagation at a wavelength of 7•7 μm for Downloaded by [IFREMER-Centre De Brest] at 05:03 23 October 2017 deficit can be noted, 3•7 and 2•2 at. % in the case of selenium. The difference between composition of the target and the thin films can be explained to a certain extent by a sputtering yield of each component of the complex Ge-Sb-Se targets.
, Tokyo, Japan), calibrated with five dilutions (1. 00, 2. 50, 5. 00, 7. 50, 10. 00 µg/dm 3 ) of the Multi-Element Aqueous CRM Environmental Calibration Standard A (VHG Labs. , Manchester, NH, USA) with an original silver concentration of 10. 00 ± 0. 05 µg/dm 3. Qualitative and quantitative analysis of the concentration of Ag was performed using the software MassHunter Workstation Software (Agilent Technologies, Yokogawa Analytical Systems Inc. , Tokyo, Japan) for ICP-MS Version A. 01. 02 G7201A Build 291. 22 Patch 5.
Acknowledgments:  Technology Transfer Centre of Nicolaus Copernicus University in Torun  is acknowledged for covering the costs of publishing in open access. biointegration studies;  Wiesław Kozak  analyzed the biointegration studies data and provided necessary equipment and materials for immunological experiments; Beata Sadowska performed the microbiological experiments; Magdalena Szubka performed XPS analysis;  Ewa Talik  provided XPS analysis;  Piotr Piszczek ,  Aleksandra Radtke ,  Tomasz Jędrzejewski ,  Beata Sadowska , and  Fabrizio Fiori , analyzed the data;  Piotr Piszczek  wrote the paper.