dataesr/scientific-paragraphs-categorization huggingface dataset:
Alignment files were converted to the HOMER's tag density format  68  before retrieving reads for each CDS per kilobase and one million mapped reads (rpkm) using HOMER's perl script analyzeRNA. pl. This read count table was merged with a published list of estimated protein concentrations (nM) in the X. laevis egg using mass-spectrometry  13  (Supplementary Data 4). Chromatinassociated proteins regulating RNAPII-mediated transcription were filtered based on human (version 2. 0, 09/2014) and Xenbase-released gene ontology (GO) associations. The genes associated with any of the following GO terms were verified with UniProt (UniProt Consortium, 2015) whether chromatin binding is supported by functional evidence: chromatin (GO:0000785), DNA binding (GO:0003677), DNA-templated regulation of transcription (GO:0006355), sequence-specific DNA binding and TF activity (GO:0003700) and DNA replication (GO:0006260).
Genomic coordinates of accessible pCRMs are listed in Supplementary Data 3 and 10 (mPouV/Sox3 LOF experiment). Next-generation capture-C. About 500 mid-blastula embryos per condition were collected in 9-ml capped glass vials and briefly washed once with 1% MMR. The embryos were then fixed with 1% formaldehyde (Sigma, F8775) in 9 ml 1% MMR at room temperature for 40 min. The fixation reaction was terminated by briefly rinsing the embryos three times with ice-cold 1% MMR. The embryos were aliquoted into 2-ml round-bottom microcentrifuge tubes in batches of ∼250 embryos (filling the volume of ∼250 µl water). The supernatant was removed before equilibrating embryos in 250 µl ice-cold HEG buffer (50 mM HEPES pH 7. 5, 1 mM EDTA and 20% glycerol). Once the embryos settled to the bottom of the tube as much liquid as possible was discarded.
DNA concentration was measured on a fluorometer with broad range concentration reagents. The DNA yield was 2-4 µg. To capture the genomic regions of interest (viewpoints), 5′-biotinylated oligonucleotides of 120 bases (hereafter called probes) (Supplementary Data 10) were designed for each viewpoint as follows: The viewpoints were DpnII fragments of 300-3300 bp which were overlapping gene promoters or located <1 kb from them. Each probe matched the terminal sequence of the same DNA fragment strand including the DpnII restriction site GATC. The probe sequence was examined using BLAT to check whether it is unique and did not partially match any other genomic regions. Furthermore, CENSOR v4. 2. 29  86  and RepeatMasker v4. 0. 6 71 programs were run to discard any probes that contained repeats.
Acknowledgements We thank  Abdul Sesay ,  Leena Bhaw ,  Harsha Jani ,  Deborah Jackson  and  Meena Anissi  for deep sequencing;  Mike Klymkowsky ,  Manolis Gialitakis  and  John Gurdon  for supplying antibodies;  Stefan Hoppler  and  Yukio Nakamara  for discussing β-catenin ChIP protocol;  Jim Hughes  and  Damien Downes  for sharing pre-publication results of an improved next-generation capture-C method;  Ying Wang  for providing sequence conservation tracks;  Mareike Thompson ,  Rita Monteiro  and  Clara Collart  for critical reading of the manuscript; and the  Smith lab  for discussions and advice. G. E. G and J. C. S. were supported by the  Medical Research Council  (program number  U117597140 ) and are now supported by the  Francis Crick Institute , which receives its core funding from  Cancer Research UK  ( FC001-157 ), the  UK Medical Research Council  ( FC001-157 ), and the  Wellcome Trust  ( FC001-157 ).
Cell Culture The SNB-19 (RRID:CVCL_0535), provided by Dr. HL Tang  [32] , is a human astrocytoma cell line, which was maintained in Corning RPMI 1640 medium (Product number: 10-040-CV, Mediatech, Inc. , Manassas, VA, USA) supplemented with 10% fetal bovine serum (FBS) and 100 units/mL penicillin plus 100 µg/mL streptomycin. Vero76 cell is a derivative of the original Vero cells, which were originally isolated from the kidney of a normal adult African green monkey. Vero76 cells (ATCC-CRL-1587, Manassas, VA) were grown in Dulbecco's Modified Eagle Medium (DMEM) medium (Product number: 10-017-CV, Mediatech, Inc. , Manassas, VA, USA), supplemented with 10% FBS and 100 units/mL penicillin, plus 100 µg/mL streptomycin.
Zika Virus Molecular Clones and Infection The MR766 ZIKV strain was the first documented Zika strain that was isolated from caged monkey in the Zika forest in Uganda in 1947  [9]. Hence, it is called the historical strain. This viral strain has been passaged countless times in new-born mouse brains. The molecular clone of ZIKV-ZIKV-MR766-NIID was generated, based on the sequence of ZIKV strain MR766 Uganda 47-NIID (Genbank access # LC002520), using the infectious sub-genomic amplicon (ISA) method as described previously  [33]. The BR15 ZIKV strain (BeH819015) was isolated from a blood sample of a patient and sequenced after one passage in mosquito C6/36 cells. It was one of the earliest Zika viral sequences that was isolated from one of the Northern states of Brazil (Pará) in July 2015 from a large clade  [34, 35].
The molecular clone of BR15 was generated, based on the BeH819015 sequence (Genbank Accession number: KU365778), using the same strategy as that of the ZIKV-MR766-NIID  [30, 33]. BR15 is available to BEI resources (Manssas, VA, USA) under the catalog number NR-51129. The ZIKV Paraíba_01/2015 strain (Genbank Accession number: KX280026) was originally isolated from the northeast state of Paraíba (Brazil) in 2015 from a serum sample of a febrile female. The virus was passed twice in Vero cells, and a molecular clone (ZIKV-ICD aka 674v4) was generated as described  [36]. For viral infection, the cells were seeded in culture plates and incubated at 37 • C/5% CO 2 overnight to allow the cells to attach to the wells. The second day, ZIKV was added to the cells with the multiplicity of infection (MOI) of 1.
After washing, cells were incubated with Texas Red-conjugated goat anti-mouse IgG secondary antibody (Cat# T-862, ThermoFisher, Waltham, MA, USA) at suggested concentration in the incubation buffer for 1 h at room temperature. After washing, cells were stained with DAPI for 5 min and washed again. Cells were then mounted with mounting medium and visualized on a Leica DM4500B microscope (Leica Microsystems, Buffalo Grove, IL) with Openlab software (Improvision, Lexington, MA, USA). ZIKV-induced caspase-3 cleavage, a hallmark of cellular apoptosis, was measured, by using the same immunostaining method, as described except cells was tested at 72 h p. i. , and the primary antibody used was Cleaved Caspase-3 (Asp175) (5A1E) Rabbit mAb (Cat#9664, Cell Signaling, Danvers, MA, USA). The secondary antibody used was the FITC-conjugated goat anti-rabbit IgG secondary antibody (Cat# 31635, ThermoFisher, Waltham, MA, USA).
Statistical Analysis Unless indicated, two-tailed and paired student t-test was used for a pair-wise comparison of data, using Microsoft Excel software. Two-way ANOVA analysis was used to analyze results generated for Figure  1B  infected cells with each molecular clone are shown in (Figure  1D ). Infection with the MR766 molecular clone resulted in statistically higher percentages of infected cells, with an average of 81. 9% than the two Brazilian molecular clones, that displayed 57. 8% for BR15 and 46. 1% for ICD. Together, these data indicate that the historical African strain MR766 showed a higher rate vRNA production and better infectivity in SNB-19 cells than that of the epidemic Brazilian ZIKV molecular clones (BR15 and ICD) presumably due to, at least in part, higher level of virus binding.
Contribution of the ZIKV C-prM Region to ZIKV-Induced Growth Restriction and Apoptotic Cell Death The data shown in Figure  3D ,E were unexpected. It is believed that if the virus has high binding efficiency to the host cells, it should result in higher percentage of viral infected cells. Since ZIKV induces cytotoxicity, we reasoned that the C-prM region could contribute to ZIKV-induced cytotoxicity, which affects the outcome of the measured levels of viral infection. To test this possibility, we measured the effects of chimeric viruses on cell proliferation and viability. As shown in Figure  4A , genetic determinant(s) of cell viability was associated with of the C-prM region of the viral genome. For instance, both MR766 and M/B showed similar cell growth pattern, which was clearly distinguishable from that of BR15 and B/M.
5 mL Centrifugal Filters (Millipore) and sequenced at the CGEB-Integrated Microbiome Resource (IMR, cgeb-imr. ca), Dalhousie University on the same Miseq Illumina sequencer using Miseq reagent kit V3 (Illumina) producing 2 × 300-bp long reads. All sequences were deposited in GenBank under SRA accession number PRJNA524010.
Sequence Analyses The resulting sequence data was processed using the standard pipeline of the DADA2 package, version 1. 6. 0 (Callahan et al. , 2016)  2 in R 3. 3. 3 (R Core Team, 2017). We removed both the forward and reverse primers by cutting off the first 21 bases of all reads. After inspection of quality control profiles, the last 20 bases of all forward reads and the last 50 bases of all reverse reads were trimmed. The filtering parameters were: 2 https://github. com/benjjneb/dada2 maxN = 0, maxEE = c(2. 5), truncQ = 2. Sample sequences were then dereplicated, paired reads were merged and chimeric sequences identified and removed using the DADA2 package. DADA2 replaces the traditional "OTU-picking" step in amplicon sequencing workflows by inferring exact amplicon sequences variants (ASVs) from sequencing data.
Data Analyses A total of 18,647 bacterial 16S rRNA gene sequences composed of 297 different ASVs were retained after removing eukaryotic sequences (chloroplast 16S rRNA from algal cells), poor quality reads and singletons. One sample from diseased CCA did not contain any sequences and was thus removed from the dataset. We found that the most appropriate way to conduct the analyses was to normalize our raw data to relative abundances  (Weiss et al. , 2017). The ASVs table containing reference sequences, taxonomy and proportional abundance in the different samples is available as Supplementary Table  1. A non-metric multidimensional scaling ordination (nMDS) based on Bray-Curtis similarity was conducted to visualize similarities in community composition between samples. The nMDS was computed with the R package phyloseq  (McMurdie and Holmes, 2013).
Permutational multivariate analysis of variance (PERMANOVA, function adonis in the vegan package in R  (Oksanen et al. , 2013) , and pairwise comparisons between group levels with corrections for multiple testing, function pairwise. perm. manova in the RVAideMemoire package  (Hervé, 2017)  were used to evaluate statistically significant differences of nMDS grouping. To estimate alpha-diversity, the Shannon Index was calculated for each sample with the command plot_richness in the package phyloseq  (McMurdie and Holmes, 2013). β-diversity was calculated between samples based on Bray-Curtis dissimilarity. It was used to compare the dispersion in bacterial community composition associated with each type of tissue. Comparison of alpha and beta-diversity values between groups was performed using a Kruskal-Wallis test and Wilcoxon pairwise tests in R.
The selected morphotypes were picked for two successive subculturing steps onto marine agar. Each isolate was then grown in marine broth  (MB 2216, Difco)  for 48 h at 22 • C while being agitated (100 rpm). Each culture was cryopreserved in 5% dimethylsulfoxide or 35% glycerol, put into a -80 • C freezer and added to the Banyuls Bacterial Culture Collection -BBCC 4. The purified strains were genotyped by partial 16S rRNA gene sequencing. Genomic DNA was extracted from a volume of 2 ml of each liquid culture. DNA extraction, PCR, and sequencing were done as previously described  (Fagervold et al. , 2013)  using the BIO2MAR platform facilities 5. Partial 16S rRNA gene sequences were trimmed, double checked manually, and dereplicated using the package Staden-GAP4  (Staden et al. , 2003). For bacterial strain identification, each FASTA file was uploaded in Ez Biocloud  (Kim et al.
, 2012)  and compared with the cultured bacterial strain database using BLAST. Sequences from the cultured strains were also compared to ASV representative sequences by BLAST. Cultured strains sequences were deposited in GenBank under accession number: MK224651-MK224715. Bacterial abundance (CFU mL -1 ) was determined on the basis of 1 mL measured aliquots of each sample used to prepare serial dilutions. Mean CFU counts were calculated for each health status (healthy, healthy-looking, diseased) by combining counts from all plates of each CCA replicate for a given status (n = 12 plate counts per health status).
Cultured Bacterial Strains The number of bacterial colonies growing on plates (CFUs) was significantly higher in healthy and diseased CCA samples than in sea water, but there was no significant difference in abundance between healthy-looking and diseased tissues (Bonferroni-Dunn test, p < 0. 01). In total, 64 bacterial strains were isolated (Supplementary Table  2 ). After grouping strictly identical sequences, we identified 13 different isolates from healthy-looking samples exclusively, 10 from diseased samples exclusively and five that were shared  among samples (Table  2 ). Over 70% of the cultured bacteria belonged to Alphaproteobacteria (Order Rhodobacterales, family Rhodobacteraceae) regardless of the type of tissue (Figure  6 ). Members of the Rhodobacteraceae (Alphaproteobacteria) dominated both the culturable bacterial communities and the amplicon data providing indication that they are key representatives of the CCA microbiome.
Vibrionales and Flavobacteriales were associated with healthy-looking samples only, whilst Rhodospirillales were found in diseased CCA only (Figure  6 ). The cultured and amplicon datasets shared 12 sequences (>99% similarity) that represented 4% of the total number of ASV, which in turn represented 18% of all the amplicon sequences (Figure  7A  and Table  2 ). Four of those ASVs were within the 12th most abundant ASVs (>300 reads in total). We could, however, not match health group specific cultured strains with group specific amplicon sequences (Figure  7B ). ASVs that had a culturable representative were not significantly more represented in one of the CCA health group compared to the others. Some sequences that were obtained in culture from diseased samples only (e. g. , Culture 19 in Figure  7B ) were retrieved by amplicon sequencing in similar proportions from both healthy and diseased samples.
Among the bacterial strain isolates, 17 did not have a match in the ASVs obtained through amplicon sequences. The same type of discrepancies between culture-dependent and -independent approaches have been previously documented in plants where isolated strains were not found in the amplicon dataset  (Dissanayake et al. , 2018)  or in corals with no overlap between the cultured strains and the uncultured sequences  (Rohwer et al. , 2001). In the culture-dependent approach, the use of a solid media may enhance the growth of certain bacteria such as those with fast growing ability  (Dissanayake et al. , 2018)  even if they are not abundant in the tissues. This would result in a high number of isolates but no detection in next generation sequencing. However, in our study, the three most abundant cultured morphotypes had a match in the amplicon dataset.
Results Forty MSM responded to the advertisements on Facebook (n = 9), Growlr (n = 21), Scruff (n = 8) and through an unknown source (n = 2). After receiving the study information, one person declined to participate, four did not respond and 10 responded after theoretical saturation had been achieved and data collection had finished. In total, 25 MSM (Table  1 ) participated in an interview which lasted 43 min on average (range 26-57). Participants were most commonly 30-39 years (n = 10), white British (n = 19), had achieved a first or higher University degree (n = 22) and were full-time employed (n = 13). Two identified as trans male. Twelve participants were recruited from Growlr, 3 from Scruff, 9 from Facebook and, 1 from an unknown source. The views of MSM did not substantially differ according to geographical location or recruitment source.
Interventions and the  NIHR HPRU in Blood Borne and Sexually Transmitted Infections  at  UCL  in partnership with  Public Health England  and in collaboration with the  London School of Hygiene & Tropical Medicine. The study is supported by the  Health Protection Research Unit (NIHR HPRU ) in Evaluation of Interventions at the  University of Bristol , in partnership with  Public Health England. The views expressed are those of the authors and not necessarily those of the  National Health Service , the  NIHR , the  Department of Health and Social Care or Public Health England. JK is partly funded by the  National Institute for Health Research  ( NIHR) Collaboration for Leadership in Applied Health Research and Care West (CLAHRC West ) at  University Hospitals Bristol NHS Foundation Trust and NIHR HPRU in Evaluation of Interventions at University of Bristol  in partnership with  Public Health England.
Methods and materials Numerical simulations were made using MATLAB. Executable model definitions are provided from http://github. com/sysbio-curie/ProteinTranslationModels. Rough parameter estimation was made using numbers from  [31]  and http://book. bionumbers. org, using data for a simple eukaryotic cell, such as yeast. Typical mRNA half-life was assumed in 20-30 minutes, which is reflected in the value k d = 8•10 -4 sec -1. The number of mRNA molecules for a particular protein was estimated on average in 1000, which leads in k t =10 3 k d. Typical protein half-lie was assumed in 30 mins-1 hour which gives k s = 4•10 -4 sec -1. We assumed the stable number of ribosomes in a cell in 2•10 5 -5•10 5 which constrains the value High S and the protein/mRNA ratio in 10 2 by order of magnitude.
Contents This is a citation summary for Metabotropic glutamate receptors in the Guide to Pharmacology database (GtoPdb). It exists purely as an adjunct to the database to facilitate the recognition of citations to and from the database by citation analyzers. Readers will almost certainly want to visit the relevant sections of the database which are given here under database links. GtoPdb is an expert-driven guide to pharmacological targets and the substances that act on them. GtoPdb is a reference work which is most usefully represented as an on-line database. As in any publication this work should be appropriately cited, and the papers it cites should also be recognized. This document provides a citation for the relevant parts of the database, and also provides a reference list for the research cited by those parts.
Reliable precipitation data in the Himalayas are essential for the study of the water resources, the evolution of glaciers, and the present and future climate. Although several types of precipitation datasets are available for the Himalayan region, all of them have limitations, which hamper the quantification of the precipitation fluxes at high elevations. This study compares different types of precipitation datasets issued from (i) in situ data, (ii) satellite-based data [TRMM, Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS)], and (iii) a reanalysis product [High Asia Refined analysis (HAR)] for a small headwater catchment at high elevations (Upper Dudh Koshi, Nepal) and assesses the impact of the precipitation uncertainty on the result of the modeling of the glacio-hydrological system.
During the analyzed period from 2010 to 2015, large differences between the precipitation datasets occur regarding annual amounts (ranging from 410 to 1190 mm yr 21 ) as well as in seasonal and diurnal cycles. The simulations with the glacio-hydrological model Distributed Hydrological Soil Vegetation Model-Glaciers Dynamics Model (DHSVM-GDM) show that the choice of a given precipitation dataset greatly impacts the simulated snow cover dynamics and glacier mass balances as well as the annual, seasonal, and diurnal streamflows. Due to the uncertainty in the precipitation, the simulated contribution of the ice melt to the annual outflow also remains uncertain and simulated fractions range from 29% to 76% for the 2012-13 glaciological year.
2013; Cannon et al. 2017). Nevertheless, several types of precipitation datasets are available for the HKH region. First, some in situ measurements exist and are often used as reference data, however, the meteorological stations measuring precipitation are scarce with relatively short time series and very few observations at elevations above 5000 m MSL. Moreover instruments for in situ measurements are known for underestimating the solid precipitation  (Wolff et al. 2015). Thus, a reliable relationship between precipitation and elevation is difficult to realize. In the Dudh Koshi basin  Salerno et al. (2015)  established an exponentially decreasing precipitation gradient, while  Eeckman et al. (2017)  proposed linear gradients with elevation thresholds. As a result, large uncertainties concerning the spatial distribution of the precipitation exist.
Furthermore, gridded precipitation products are available such as TRMM based on satellite measurements  (Bookhagen and Burbank 2006) , APHRODITE based on a spatial interpolation of a rain gauge network  (Yatagai et al. 2012) , and reanalysis datasets like ERA-40  (Uppala et al. 2005) , ERA-Interim  (Dee et al. 2011) , MERRA  (Rienecker et al. 2011) , and NCEP-NCAR  (Kalnay et al. 1996). The gridded datasets provide a full spatial coverage, but are only available at coarse spatial (. 0. 258) and temporal (mostly daily) resolutions. Moreover, satellite products such as TRMM are also known for showing significant biases for solid precipitation  (Ménégoz et al. 2013; Maussion et al. 2014 ). Nevertheless, these datasets are commonly used at different spatial and time scales in the HKH region in climatological, glaciological, and hydrological studies, which all depend strongly on precipitation data.
Several studies have compared the different precipitation datasets over the HKH region  (Andermann et al. 2011; Palazzi et al. 2013; Ceglar et al. 2017 ) and showed high discrepancies in the annual amounts as well as in the seasonal variability. In contrast, the precipitation uncertainty at very high elevation and at subdaily time scales has not been addressed in these studies. Yet, the estimation of precipitation at small spatial and temporal scale is important for the understanding of glaciological or hydrological processes in these areas. For instance, in glaciological modeling the amount of precipitation and its spatial distribution on glaciers determine the accumulation and plays an important role in the glacier mass balance estimation  (Immerzeel et al. 2012; Jarosch et al. 2012). This study evaluates the precipitation uncertainty in a small high elevated catchment (above 4000 m MSL) located in the Dudh Koshi catchment in Nepal.
Five in situ and gridded precipitation datasets available for the period 2010-15 at high spatial resolution (,0. 258) and temporal resolution (from hourly to daily) were used for comparison. Among them two precipitation datasets derived from two different types of rain gauges: classical tipping buckets and Geonor gauges, which are designed for measuring solid precipitation. Due to the scarcity of in situ data in the Nepalese Himalaya, precipitation data measured with tipping buckets are often used in hydrological and glaciological studies in high elevated catchments  (Immerzeel et al. 2014; Ragettli et al. 2015; Salerno et al. 2015; Shea et al. 2015; Soncini et al. 2016 ). This study evaluates the uncertainty of in situ measurements in a catchment that receives a significant share of its annual precipitation as snow.