dataesr/scientific-paragraphs-categorization huggingface dataset:
We similarly removed burn-in from the log files of *BEAST and combined them before using loganalyzer, which is a piece of software which comes with *BEAST, to compute the ESS values. The command was: loganalyser -burnin 0 input_log output_file MP-EST. We combined maximum clade credibility gene trees or distributions of gene trees with MP-EST version 1. 2. When combining distributions of gene trees we provided the 100 sub-sampled trees for all genes as one large input to MP-EST. RAxML and FastTree ML tree estimation. RAxML version 7. 9. 4 was used to compute ML gene trees with the command: raxmlHPC-PTHREADS-SSE3 -T 2 -m GTRGAMMA -s input_sequence -n output_id -N 20 -p 1234 FastTree verson 2. 1. 7 SSE3 was used to compute ML gene trees with the command: FastTree -nt -gtr < input_sequence > output_tree.
Mb). The average number of MCMC iterations reached by BBCA within each bin was 158 million, while the 48-hour *BEAST analysis reached 204 million, and the 96-hour *BEAST analysis reached 479 million. Laurasiatheria simulated datasets. We compared BBCA, *BEAST, and CA-ML on the Laurasitheria simulated datasets, using 24-hour analyses of *BEAST on each bin of size 25, and allowing up to 96 hours for *BEAST on the 100-gene datasets. *BEAST failed to run on two of the 1500 bp datasets; consequently, all our comparisons for the 1500 bp datasets are based on the eight remaining replicates. Results for the CA-ML, BBCA, and the 48and 96-hour *BEAST analyses are shown in Figures 3, 4 and 5. The 96-hour *BEAST analysis was more accurate than the 48-hour *BEAST analysis, but even the 96-hour analysis was much less accurate than the BBCA analysis.
Figure7Average species tree estimation error on one Laurasiatheria 1000bp simulated dataset using BBCA, *BEAST and concatenation with maximum likelihood (CA-ML). BBCA is run with a 24-hour or 48-hour time limit on each 25-gene bin, and *BEAST is run with a 48-hour, 96-hour or 168-hour time limit. BBCA using either 24 hours or 48 hours per bin recovers the true species tree, but both *BEAST analyses and the CA-ML fail to recover the true species tree.
Methods The Slovenian sport services market has been monitored for more than fifteen years with the approach taken by Andreff and his colleagues (1994); therefore, high quality population data was used for this study. The survey examined operating revenues among all of 5,254 sport NGOs in Slovenia (sport clubs and associations) that provided annual income statements for each year from 2007 to 2010. The data in this study has been obtained at the request of the authors, using annual financial reports from the Agency for Public Legal Records and Services in the Republic of Slovenia, the main primary source of official public and other information on business entities in Slovenia. The operating revenues have been defined as a stream of benefits accruing to the sport NGOs from following types of revenues: Sales revenues (such as revenue from sport lessons, tickets sales, sponsorship contracts, media rights, merchandising, food and drink sales in the clubhouse, trade of players, the rental of premises, the organization of sport and non-sport events within the club's premises, tournament fees, own lotteries, etc.
The results presented here do not ostensibly agree with the data in  [21]  that the albino exhibits an early overproduction of ipsilateral RGCs. These discrepant findings can be attributed to differences in the methods of data collection and display: in our previous study  [21] , we used bromodeoxyuridine (BrdU) birthdating at embryonic ages in combination with retrograde labeling via the optic tract at postnatal ages, whereas in the present study, we utilized EdU birthdating in combination with Zic2 expression at embryonic ages to chart VT RGCs at the time when they are specified to project ipsilaterally. Moreover, in our previous study, we quantified ipsilateral RGCs born at each age as a percentage of total ipsilaterally projecting RGCs (BrdU + /dextran + ) at postnatal ages, and reported an increase in early-born ipsilateral RGCs in the albino retina.
The retinae were then flat-mounted on a Fisherbrand® Frosted slide (Pittsburgh, PA, USA), making 4 to 5 cuts at equidistant points along the periphery, each one in a radial direction from center to periphery, and then coverslipped with Fluoro-Gel (Electron Microscopy Sciences, Hatfield, PA, USA). The region of the retina expressing Zic2 was imaged with a Zeiss Axioplan2 microscope (Zeiss, Thornwood, NY, USA) and 20x objective with an Axiophot camera and Axiovision software (Zeiss, Thornwood, NY, USA). For quantification of Zic2 + cells in retinal whole mounts, multiple 20x images of the Zic2-expressing region were stitched together to create a final image containing the entire Zic2 zone in the VT retina using Adobe Photoshop CS6 (Adobe Systems Incorporated, San Jose, CA, USA). Zic2 + RGCs were counted in sectors of equal width (75 μm) from the periphery to the center of the retina through the Zic2expressing RGC territory, using ImageJ (National Institutes of Health, Bethesda, MD, USA) (Figure  1A ).
Stained sections of the retina were imaged using a Zeiss AxioImager M2 microscope equipped with Apo-Tome, AxioCam MRm camera, and Neurolucida software (V10. 40, MicroBrightField Systems, Williston, VT, USA). A merged stack of eight images (2 μm steps) was acquired with the ApoTome and 20x objective. All quantifications for sections processed for IHC were performed using Meta Imaging Series Metamorph 7. 0. The inner surface of the retina was divided into radial sectors of equal width (100 pixels, 1 pixel = 0. 3205 μm) from the periphery to the center (Figure  2B ). For each sector, a line was drawn from the inner surface of the retina towards the outer surface in the axis of cell migration (Figure  2B ). Cell numbers were recorded for each individual sector. The first sector was circumscribed by the peripheral-most border of Islet1/2 + cells.
Images were thresholded with the Metamorph program such that only the most strongly labeled cells were counted. Retinal area was measured using the Region Tracing Tool on the Metamorph imaging system and 1 pixel = 1. 64 μm 2. For statistical analysis at E15. 5, the second and fourth sections caudal to the section where the optic nerve is attached to the eye were chosen because the Zic2 + cells in pigmented retina are most numerous in these sections. The number of Islet1/2 + RGCs and the number of Zic2 + RGCs in these two sections were summed and then averaged across individuals. At E17. 5, the first and third sections rostral to the section where the optic nerve exits the eye were chosen for quantitation, as the orientation of the retina with respect to the optic nerve has changed from E15.
After EdU revelation, slides were washed 2 × 10 minutes in PBS at room temperature. Sections were coverslipped with Fluoro-Gel. Imaging and quantification were performed as described above. The EdU signal in retinae injected at E13 and collected at E15. 5 was thresholded such that only the cells that became post-mitotic at E13 (brightest) were counted, using the Meta Imaging Series software Metamorph 7. 0. The EdU signal in retinae injected at E14 and collected at E15. 5 did not require thresholding because the window between the age of injection and collection was too short for multiple rounds of division, minimizing the disparity in EdU signal strength amongst postmitotic RGCs. The EdU signal in retinae injected at E15 and collected at E17. 5 did not require thresholding, even though the time window between injections and collection was 2.
Acknowledgements We thank members of the  Mason laboratory  and  Professors Ray Guillery ,  Suzanne Roffler-Tarlov ,  Hynek Wichterle ,  Wes Grueber  and  Janet Sparrow  for helpful discussion. This research was supported by  NIH  grants  EY012736  and  EY015290 ,  P30EY019007  (CM, PB, AR, IR), and  T32 EY013933  (PB); The  Human Frontier Science Program (AR) ; and  The Gatsby Initiative in Brain Circuitry (CM and AR).
Instationary 13 C-MFA The dynamics of most of the measured mass isotopomer distributions for the Rol-expressing strain followed a comparable trend compared to the control strain (Supplementary files 1 and 2) in  [25]. There are clear differences observed in the final enrichment of Glc6P, Fru6P and FBP, which are lower in the Rol-expressing strain, as well as in the enrichment dynamics of trehalose (slower in X-33/ROL). Within a dataset, expected dynamics are observed: The enrichment dynamics of the intermediates of the lower part of the network (TCA cycle) and the storage carbohydrate trehalose were slower compared to glycolysis and PPP metabolites. The glycolytic intermediates reached isotopic steady states after about 10-15 minutes, which is high compared to the turnover time (data not shown) but a commonly observed delay  [25, 36, 37].
Acknowledgments This study was supported by the  Spanish Ministry of Science and Innovation  ( CICYT  project  CTQ2010-15131  and  Ph. D. fellowship for  Joel Jordà ), the  Catalan Government  (contract grant  2009-SGR-281  and  Xarxa de Referència en Biotecnologia). We thank  Reza Maleki-Seifar ,  Angela ten Pierick  and  Cor Ras  for GC and LC MS/MS concentration and mass isotopomer measurements.
Study population The EPIC study includes 521,330 participants (approximately 370,000 women and 150,000 men) aged 25-70 years at enrolment from 1992-2000. The cohort and data collection procedures have been described previously  [14, 15]. Briefly, study participants were recruited predominantly from the general population if they were residing in a particular town/province in 23 centers in 10 European countries (Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom). Exceptions to this were the French cohort which includes female members of a health insurance program; the Spanish and Italian participants who were recruited among blood donors, members of health insurance programs, employees of several enterprises such as civil servants as well as the general population; in Utrecht and Florence, women attending population-based mammographic screening programs were recruited; in Oxford, half of the cohort included ''health conscious'' participants who did not eat meat from England, Wales, Scotland and Northern Ireland; the cohorts of France, Norway, Utrecht and Naples included only women  [14].
Ascertainment of ovarian cancer cases Incident cancer cases were identified through population-based cancer registries (Denmark, Italy, the Netherlands, Norway, Spain, Sweden and United Kingdom) or by active follow-up (France, Germany and Greece) using health insurance records, cancer and pathology registries and through directly contacting the study participants and their next of kin. Mortality data were obtained from the cancer registry or mortality registries at the regional or national level. From the 325,007 participants included in the current analysis, 1293 first incident ovarian cancer cases were identified; from these, 77 and 25 cases were censored because they were non-epithelial or were missing information on tumor behavior, respectively, leaving 1191 EOCs for the current analysis.
32-0. 43 in Germany, 0. 21-0. 37 in Greece); these estimates refer to women only except for the German study  [24]  that included men and women. To convert the quantities of food consumed into estimates of daily total energy and fat intakes (total fat, fat subtypes and fat sources), the EPIC Nutrient Database  [27]  was used. Omega-6 (n-6) and n-3 were not available in the current study. As an indicator of n-3 intake, we evaluated consumption of fatty fish (4 g fat/100 g) which includes canned fish, anchovies, salmon, sardines, tuna and fish liver (fish liver available in Norway only). Participants from Potsdam, Germany were excluded from analyses of fatty fish because this information was unavailable. Data on supplement use were not available for these analyses.
To calculate a P-value for the test of linear trend, participants were assigned the median value of each fat intake category and this variable was modeled as a continuous term. We also performed stratified analyses by age at enrolment (<50 years, 50), median BMI (<24 kg/m 2 , 24), parity (nulliparous, parous) and OC use (never, ever). A P-value for interaction was calculated using a likelihood ratio test to compare a multivariate model with multiplicative interactions terms and the main effects to a model with only the main effects. Sensitivity analyses were carried out after excluding cases that occurred during the first two years of follow-up. To test for heterogeneity between countries, data analyses were conducted separately within each country and were pooled using a random effects model  [31].
All statistical tests were two-sided and a P < 0. 05 was considered statistically significant. Cox proportional hazards analyses and meta-analyses were performed using the 'survival'  [33]  and 'rmeta' packages  [34] , respectively, in R version 3. 0. 2 [35]. Cox proportional hazards competing risks analysis was performed using SAS version 9. 3 (SAS Institute Inc. , Cary, NC, USA).
Discussion We evaluated consumption of total fat, fat subtypes and fat sources in relation to EOC risk in the EPIC study that includes data from 10 European countries. Previous studies have focused on intake of total fat, saturated and/or animal fat in relation to risk of hormone related cancers such as breast, endometrial and ovarian cancer because it has been hypothesized that high levels of fat intake may stimulate extraovarian estrogen production  [8] ; however, data to support this hypothesis is inconsistent  [10] [11] [12]. In the current study, total fat intake was not associated with risk of invasive EOC overall; this result is consistent with the b Among parous women, FTP or full term pregnancies are defined as live births/still births. c Among oral contraceptive (OC) users only. d Among parous women.
Acknowledgments The coordination of EPIC is financially supported by the  European Commission (DG-SANCO)  and the  International Agency for Research on Cancer. The national cohorts are supported by  Danish Cancer Society (Denmark) ;  Ligue Genevoise Contre le Cancer ,  Institut Gustave Roussy, Mutuelle Generale de l'Education Nationale, Institut National de la Santeet de la Recherche Medicale (INSERM) (France) ;  Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany) ; the  Hellenic Health Foundation (Greece) ;  Associazione Italiana per la Ricerca sul Cancro-AIRC (Italy) ;  Dutch Ministry of Public Health, Welfare and Sports (VWS) ,  Netherlands Cancer Registry (NKR) ,  LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland) ,  World Cancer Research Fund (WCRF) ,  Statistics Netherlands  (The Netherlands);  ERC-2009-AdG 232997  and  Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway) ;  Health Research Fund (FIS) ,  Regional Governments of Andalucı ´a, Asturias ,  Basque Country ,  Murcia  (No.
PBCV-1 has a 331-kb linear double-stranded DNA (dsDNA) genome with covalently closed hairpin ends and contains 416 predicted protein-encoding sequences (CDSs) as well as 11 tRNA encoding genes  [6]. A proteomic study revealed that the purified virion is associated with 148 unique virus-encoded proteins (about 35% of the virus coding capacity) and 1 host protein  [6]. Approximately 40% of the 416 PBCV-1 gene products resemble proteins in the public databases. PBCV-1 initiates infection by attaching rapidly to the cell wall of its host  [7] , at a unique virus vertex  [8, 9]. Attachment to its host receptor is a major factor in limiting the host range. This event is immediately followed by host cell wall degradation by one or more virus-packaged enzymes at the point of contact. After wall degradation, the viral internal membrane presumably fuses with the host membrane, causing host membrane depolarization  [10] , potassium ion efflux  [11] , and an increase in the cytoplasmic pH  [12].
variabilis cells infected by PBCV-1 was conducted. cDNAs from poly(A+)containing RNAs isolated from cells at six time points covering the first hour of infection (i. e. , before virus DNA synthesis begins) were sequenced using an Illumina sequencer. A total of 105 million 50bp reads were generated and mapped to both the host and virus genomes  [6, 20] ; these data were used to measure the abundance of mRNAs. Here we address three significant issues regarding viral transcription. i) What are the sequential events of viral gene activation? ii) Do viral genes use host-like poly adenylation signals? iii) Are viral mRNAs spliced? Analysis of the C. variabilis transcripts using the same datasets is presented in a companion paper  [21].
Genome-wide PBCV-1 Transcriptome Map The number and proportion of poly(A+)-containing mRNA reads were mapped to the PBCV-1 genome for each dataset corresponding to time points at 0, 7, 14, 20, 40, and 60 min p. i. (hereafter referred to as T0, T7, T14, T20, T40 and T60, respectively) (Fig. 1 ). No viral transcripts were detected in the T0 dataset indicating that viral mRNAs are not packaged in PBCV-1 virions. However, virus mRNAs were detected as early as T7, which indicates a rapid reprogramming of the host transcription and processing machinery to produce viral mRNAs. During the first hour of PBCV-1 infection, there was a rapid increase in the proportion of viral mRNAs. At T60, 41% of the reads mapped to the virus genome, which is in the same range as some other NCLDVs -e. g. , 25-55% for vaccinia virus, see  [22].
These transcript levels are comparable to host genes known to be highly expressed in cellular organisms; e. g. , cytoplasmic ribosomal protein genes typically have normalized MRPN values between 600 and 2500 in the same dataset (Table  S1 ). Subsequently, the number of detectable PBCV-1 mRNAs increased dramatically (Fig. 1  and 2 ). At 60 min p. i. , transcripts from virtually all of the PBCV-1 genes were detected, albeit with different intensities (Fig. S1A ). For example, the mRNA level for the a312L gene (similar to the Ostreococcus virus unknown protein OsV5_171r) reached a normalized MRPN value of 165,053 (Table  S1 ). This level of transcript accumulation is 37 times more than the most highly expressed host gene, rbcS, which encodes the ribulose-bisphosphate carboxylase small chain (MRPN = 4,400 at T60).
Twelve other PBCV-1 genes, encoding thymidylate synthase and 11 unknown proteins, also had transcript levels higher than the rbcS gene in the T60 dataset. Thus the transcriptome map revealed important features of viral transcription activity during the first hour of infection: i) the sequential initiation of the virus gene transcription implies an orchestrated regulation of gene expression. ii) The RNA-seq data indicates that the levels of transcript accumulation for some virus genes are globally much higher than host genes (Fig. S1B ). iii) 99% of the virus genome sequence was covered by RNA reads at T60 (Fig. 2 ), indicating that untranscribed viral regions are very short. This finding agrees with earlier genomic studies revealing that PBCV-1 contains many overlapping open reading frames (ORFs)  [23].
The signal was not as obvious for PBCV-1 because of the smaller number of sequences analyzed, decreasing the signal to noise ratio. Further investigation of the same datasets using sequence logos confirmed the existence of a nucleotide bias in both the virus and host genes between 217 and 210 nucleotides from the CSs, as well as immediately after the CSs (Fig. S4 ). To identify possible sequence motifs functioning as a poly(A) signal, pentanucleotide repeats were counted within the 50 nucleotides upstream from the CSs. The 2 most frequent pentanucleotide repeats for C. variabilis and PBCV-1, as well as their distribution across the gene 39 ends are reported in Fig. 4C-D. TGTAA motifs were highly clustered around position 217 in both biological entities. Overall 72% of the examined PBCV-1 gene 39 extremities (26/36) had a TGTAA motif between positions 224 and 216; in C.
Transcriptome Analysis Initial alignment, statistics, and clustering analyses have already been described in  [38]. For the PBCV-1 targeted analysis described herein, several additional procedures were performed. RNA-seq read mapping was performed in two steps. First, a list of exon junctions for both the host and PBCV-1 using the genome annotations was compiled. This list served to help in the mapping of reads that span over two consecutive exons in the second step of the analysis. De novo identification of exon junctions was also performed using the TopHat program  [39]  to complete the list with possible exon junctions that were missed by gene prediction programs. All RNA-seq datasets were pooled and analyzed together in a single TopHat run. TopHat was set up so that it only considered read alignments with at most 2 mismatches with the target reference sequence and a maximum intron size of 2000 bp.
Because TopHat only reports potential exon junctions that result from the removal of introns that end by ''GT-AG'', ''GC-AG'' and ''AT-AC'' (i. e. , spliceosome-processed introns), reads that failed to align with TopHat were further aligned using the Blat program  [40]  to identify putative exon junctions resulting from spliceosome-independent excisions. In this case, the candidate junctions were identified when two segments from the same read were mapped at two distinct loci separated by less than 2000 bp on the same genomic sequence. For both the TopHat and Blat methods we only considered candidate junctions validated by at least 5 read species to limit false positives. A read species is defined as a group of identical reads irrespective of the strand (i. e. , forward and reverse reads belong to the same read species); thus validating read species refer to reads that overlap with the same genomic feature (i.
e. , in this case an exon junction) with an offset of one or more nucleotides. In a second step, reads from each individual RNA-seq dataset were simultaneously mapped to both the reference genomes and the collection of candidate exon junctions. For subsequent expression analyses, we only considered reads that generated a unique alignment in the reference genomes with at most 2 mismatches. The PBCV-1 genome has inverted repeats at its termini  [41]  containing ORFs A002bL, A002cR, A002L, A003R and A005R that have strictly identical sequences to ORFs A690fR, A690eR, A691R, A689L and A682L, respectively. To measure the number of reads for these genes we realigned each individual RNA-seq dataset allowing at most two alignments in the reference genomes. The number of reads for each of these genes was divided by two to account for the ambiguity of mapping.
Read Count Normalization To correct for gene length, we computed the Median Reads Per Nucleotide (MRPN) that is the median of read coverage values for each nucleotide position in the ORF. The rationale behind this choice is that the median is less affected by extreme and abnormal values than the mean utilized for example in the calculation of Reads Per Kilobase per Million reads (RPKM)  [42]. Thus, in addition to being less affected by local sequencing bias, this measure is particularly relevant for PBCV-1 genes where the transcription of genes frequently begins or terminates in neighboring genes, which can artificially and locally inflate read counts per gene. To further correct for sequencing depth, MRPN values for both PBCV-1 and C. variabilis ORFs were normalized by a scaling factor equal to the ratio of the sum of reads mapped to the host and virus genomes in the dataset (i.
8% agarose gel in 1X TAE buffer. Resolved DNA fragments were excised from the agarose gel and extracted using the QIAEX II Gel Extraction kit (Qiagen). Sequencing was carried out by Eurofins MWG Operon and Davis Sequencing services (Davis, CA). The relative quantity of RNA populations was estimated using Quantity One software (Bio-Rad, Hercules, CA). The volume of each band was estimated (intensity area) and the relative quantity was calculated as intensity expressed as percentage of the total intensity of all the bands in a lane.