dataesr/scientific-paragraphs-categorization huggingface dataset:
g. , insulin use, HbA 1c level and obesity heavily influence one another which may also confound the results. And finally, due to the characteristics of Polish society, only patients of Caucasian ethnicity were included and our findings may have not be applicable for persons from other ethnic groups. This study has also several strengths. One of them is its case-control design with strictly matched pairs of case subjects and their comparators, with each pair taken from the very same center. The study was based on a high-quality data sources using samples with a long follow-up time (mean time from diabetes diagnosis to index time has exceeded 10 years) and extensive covariate information, including the date of the onset of diabetes, date of cancer diagnosis, treatment details, metabolic control and other common risk factors, which allowed to explore the relationship between T2DM and cancer risk.
These reads were used in combination with the 228,613 reads previously obtained (4) from shotgun 454-GS FLX sequencing for the assembly step using the integrated processing environment NG6  (5). A total of 10 scaffolds were generated, and five scaffolds could be ordered and oriented against the high-resolution NheI optical map of the chromosome  (6). Chromosomal sequences corresponding to each ribosomal operon (six), gaps (five), nucleotide ambiguities (19 regions), and pseudogenes (78 putative) were determined by Sanger sequencing of appropriate PCR products. Due to the presence of a large DNA duplication on two plasmids, accurate plasmid assembly could be performed only by a combination of numerous methods, such as comparison of 454-generated scaffolds against PacBio RS single-molecule real-time (SMRT) data (39,739 reads), PCR analyses, and Southern hybridization of pulsed-field gel electrophoresis (PFGE) of plasmid linearized by S1 nuclease  (7).
Annotation of the assembled chromosome and plasmids was performed using the integrated bacterial genome annotation platform AG-MIAL (  8 ), followed by a manual curation process. The complete genome of L. lactis subsp. lactis A12 consists of a single circular chromosome of 2,603,898 bp (average 35. 6% GϩC content) containing 2,624 coding sequences (CDSs), including 39 pseudogenes, 65 tRNA genes, and six ribosomal operons. The strain contains four plasmids: pA12-1 (5,736 bp, 33. 7% GϩC content), pA12-2 (9,105 bp, 34. 8% GϩC content), pA12-3 (42,401 bp, 33. 5% GϩC content), and pA12-4 (69,485 bp, 32. 9% GϩC content). Unexpectedly, the last two plasmids harbor a nearly identical region of 21,475 bp in size that contain genes previously found to be involved in raffinose metabolism  (4). Accession number(s).
Results Identification of layer-specific piriform genes. We hypothesized that layer-specific piriform genes could reveal a molecular code of projection neuron connectivity. We thus used laser-capture micro-dissection and RNA deep sequencing to identify genes selectively expressed in piriform layers I, II and III. Piriform layers can easily be identified morphologically, based on the differential density of neurons within each layer (Fig. 1a ). We then prepared RNA from the micro-dissected tissue and performed RNA deep sequencing to identify genes selectively expressed in neurons of a given layer. DESeq analysis and Independent Component Analysis combined with Gene Set Enrichment Analysis  30  were used to generate molecular signatures that discriminate the three layers, and to rank genes based on their relative expression levels (see Methods section).
A given field of view was divided into 15 bins, and the fraction of cells in each bin was calculated as the total number of cells in each bin, divided by the total number of cells in the field of view. The fraction of projecting neurons expressing a given gene was calculated as the number of CTB-labelled cells expressing a given gene, divided by the total number of CTB-labelled cells. The morphologies of ChR2-eYFP-expressing cells were reconstructed from high resolution confocal images (12 bit grayscale, x, y: 0. 6 mm/pixel, z step size 0. 5 mm), using the 'Simple Neurite Tracer' Image J plug-in  48. Statistical analyses were performed using GraphPad Prism 6 software.
Acknowledgements We thank  Christine Ho  for help with laser-capture micro-dissection,  Eric J. Kremer  and the Montpellier Vector Core for CAV2-Cre virus,  Shen-Ju Chou  for plasmids, and  France Maloumian  for help in preparing the figures. We thank  Walter Fischler ,  Niccolo Zampieri ,  Gilad Barnea , and members of the  Fleischmann lab  for critical comments on this manuscript. This work was supported by a  Marie Curie International Reintegration grant  ( IRG 276869 ) and the ' Amorcage de jeunes equipes' program  ( AJE201106 ) of the  Fondation pour la Recherche Medical  (to A. F. ), a 'Team structuring' grant from the  Research University Paris Sciences and Letters (PSL)  (to S. G. and A. F. ), by a postdoctoral fellowship from the  LabEx Memolife  (to A. D. ), and by the  LabEx Transimmunom  ( ANR-11-IDEX-0004-02 ) (to D.
Line profi les in q y were taken at the Yoneda Peak for each image. [ 44 ] Owing to a slight shading from the beam-stop, visible on the right-hand side of Figure  3  e,f, all line profi les presented are taken from the left side of the images. Quantitative analysis of GISAXS measurements has been undertaken using the distorted wave born approximation to simulate scattering from periodic features in the fi lm under investigation. Unfortunately, it did not prove possible to achieve a good fi t to the data at low q values due to the irregular shape and large size distribution of grains in the fi lms (as can be seen from the SEM images of nominally identical fi lms presented in Figure  4  ). Nevertheless, whilst a quantitative analysis has not been possible, we show below that a qualitative analysis can still provide useful information on the evolution of the fi lm during the annealing process.
As the annealing time increased from 80 to 100 and then 120 min, the average device PCE increased from 7. 8% to 10. 7% and fi nally to 12. 2%. This improved effi ciency arises due to an increase in J SC from 15. 8 to 17. 2 and fi nally to 18. 4 mA cm -2 , as well as an increase in FF from 50. 6 to 64. 0 and then 68. 8%. At annealing times longer than 120 min, PSC performance begins to reduce with all device metrics undergoing a reduction. Our high effi ciency devices exhibit minimal hysteresis in their current density against voltage behavior, as can be seen in Figure  S9  (Supporting Information). The observed trends in device performance can be understood with reference to the GISAXS, GIWAXS, and SEM data presented above. Initial increases in performance can be attributed to the combined effect of two processes.
Film Characterization : SEM images were taken using an FEI Inspect F scanning electron microscope. Here an incident beam energy of 5 kV was used in combination with a secondary electron detector. AFM measurements were performed using a Veeco Dimension 3100 in tapping mode with Budget Sensors Tap300-G tips. Gwyddion software ( http://gwyddion. net/ ) was used for image analysis. Fabrication of Solar Cells : Prepatterned glass-ITO substrates were purchased from Ossila Ltd. Substrate cleaning and deposition of the PEDOT:PSS hole transport layer and perovskite active layer were as described above, with perovskite fi lms formed having a thickness of ≈380 nm. Following the thermal annealing step, the perovskite fi lms were moved into a nitrogen glovebox where PC 70 BM (99%, Ossila Ltd) was deposited by spin-coating of a 50 mg mL -1 solution in chlorobenzene (heated for 12 h at 70 °C and fi ltered using a 0.
Acknowledgements The authors thank  Darren Watters  at  Ossila Ltd. for solution preparation,  Mejd Alsari  and  Oier Bikondoa  for assistance with the GIWAXS beamtime at  ESRF  and  Bailey Curzadd  for construction of the chamber for GIWAXS experiments. The authors also thank  Yiwei Zhang ,  Paul Staniec , and  Jon Griffi  n for assistance with the  GISAXS beamtime at Diamond. A. T. B. thanks the  EPSRC  for funding via the  E-Futures Doctoral Training Centre in Interdisciplinary Energy Research   EP/G037477/1. The authors gratefully acknowledge funding via  UK EPSRC  via research grants  EP/M025020/1  " High resolution mapping of performance and degradation mechanisms in printable photovoltaic devices " and  EP/J017361/1  " Supergen Supersolar Hub. ".
Data accessibility Data is within this article and raw data is available in Gene Expression Omnibus repositories (GEO: GSE17725; http://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc ¼GSE17725 and GEO: GSE82344; http://www. ncbi. nlm. nih. gov/geo/ query/acc. cgi?token ¼yxibwieatzavpqv&acc ¼GSE82344).
Microarray analysis We used the MaxRS method developed for the analysis of heterologous hybridization profiles  [1] , a method that has been previously applied in king penguins  [3]. All results were normalized using the quantile method after log2 transformation to make them comparable across microarrays  [4]. Gene expression of NI penguins, considered as control in the study, were compared to those of SA or AA groups. Differentially expressed genes between NI vs. SA or NI vs. AA were determined using the empirical Bayes moderated t-statistics implemented in the Bioconductor package limma  [5]. We focused on the genes involved in the redox homeostasis and gathered them into six functional clusters according to GenOntology annotation and literature search  [2, 6, 7]. All analyses were performed using the R statistical software Table  1.
Cell Cycle Analysis ADSCs were seeded at a density of 3,000 cells per cm 2. After 72 hours, cells were harvested and fixed in 70% ethanol for 2 hours on ice, washed with phosphate-buffered saline (PBS), and incubated in PBS-0. 1% Tween containing 25 mg/ml propidium iodide and 250 mg/ml RNase-A for 15 minutes. Cells were analyzed with a FACSCalibur system (BD Biosciences, Franklin Lakes, NJ, http://www. bdbiosciences. com). Cell cycle repartition was assessed with Modfit LT 4. 0 (Verity Software House, Topsham, ME, http://www. vsh. com).
For 8-oxoG measurement, fluorescence intensity was quantitated with Cell Profiler software (Broad Institute, Cambridge, MA, http://www. cellprofiler. org). respectively, by using the SureTag DNA Labeling Kit according to the manufacturer's instructions (Agilent Technologies, Santa Clara, CA, http://www. agilent. com). The labeled DNA was hybridized to a SurePrint G3 Human 4 3 180K comparative genomic hybridization (CGH) microarray with an overall median probe spacing of 13 kb (11 kb in Reference Sequence genes) and washed according to the manufacturer's instructions (Agilent Technologies). Arrays were scanned by using an Agilent G2565CA microarray scanner; images were analyzed by using Feature Extraction software, version 10. 1. 1. 1; and data analysis was performed by using Genomic Workbench 7.
kapabiosystems. com). RNA-seq experiments were performed on an Illumina HiSeq2000 using a paired-end read length of 2 3 100 bp with the Illumina TruSeq SBS sequencing kit, version 3. We performed spliced mapping with the Spliced Transcripts Alignment to a Reference (STAR) software, version 2. 3. 1f [12] , against Homo sapiens genome (Ensembl 37. 74, http://useast. ensembl. org). Then we sorted, removed duplicates from alignment files, and merged them. We used Cufflinks software, version 2. 1. 1 (University of Washington, Seattle, WA, http://cole-trapnell-lab. github. io/cufflinks/) [13]  to build new transcripts and merge the annotation file with the reference annotation file from Ensembl (http://useast. ensembl. org). With a homemade script, we computed raw reads counts on each transcripts/genes and renamed genes with Ensembl id.
Differential Expression Analysis Raw count RNA-seq data at the gene level (three replicates for each growth condition with, respectively, 1% and 21% O 2 in the medium to P1) were processed and analyzed within the R computing environment (https://www. r-project. org) [14]  by using the edgeR package  [15]  from Bioconductor (https://bioconductor. org). Raw data were normalized by using the trimmed mean of M-values normalization procedure  [16]  to account for the different sequencing depths between the samples. To deal with very lowly expressed genes in any of the experimental conditions, normalized data were submitted to filtering. We filtered out genes that were not expressed and kept genes that were expressed in at least one sample. The relationships between conditions and library reproducibility within each condition were determined by a multidimensional scaling method.
Differential gene expression was evaluated by using an overdispersed Poisson (negative binomial) model combined with a likelihood ratio test  [17]. In a manner analogous to a one-way analysis of variance test, we performed differential expression analysis of count data between the two groups: hypoxia vs. normoxia. Because the samples come from three different donors receiving both hypoxia and normoxia treatment, a paired design was used. The design was formed from an additive model that included both the donor and the group factor without the interaction term. Genes with significant evidence for differential expression were evaluated by an adjusted p value based on the Benjamini-Hochberg multiple testing correction  [18]  in conjunction with a data-based filtering procedure using the HTSFilter  [19]  package of Bioconductor.
Pathway Enrichment Analysis EntrezGene ID of differentially expressed genes were entered into the WebGestalt resource (http://bioinfo. vanderbilt. edu/webgestalt/ ). For analysis, the following parameters were entered: reference, Homo sapiens genome; method, hypergeometric; multiple test adjustment, Benjamini-Hochberg; significance level,. 05; database, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (http://www. genome. jp/kegg/pathway. html).
Identification of Small Nucleotide Polymorphisms We added read groups in STAR alignment files, merged them, and removed multimapped reads. The mapping quality was set to 40 for all uniquely mapped reads. We used the GATK software package, version 3. 0 (Broad Institute)  [20, 21]  to perform all the variant calling by following the best practices recommendations for variant calling in RNA-seq data. We used the GATK tools for split spliced reads and performed the indel (insertion and deletion) realignment with the indel Mills and 1KG databanks. We recalibrated base quality with dbSNP software, version 138 (National Center for Biotechnology Information, Bethesda, MD, http:// www. ncbi. nlm. nih. gov) [22]  and previous indel databanks. Then, we used HaplotypeCaller (Broad Institute) to detect small nucleotide polymorphisms (SNPs) and indels.
Detection efficiency evaluation using experimental setup and comparison with MCNPX results To evaluate 222 Rn detection efficiency it is necessary to remove the 218 Po and 214 Po alpha peak tail from 222 Rn peak. The counting from tails of 218 Po and 214 Po are estimated using Colegram software as shown in Fig. 5  (blue line). Once the counting rate for radon peak is evaluated, the detection efficiency is calculated using the radon reference activity concentration and the detection volume. This experimental determination of the detection efficiency is repeated eighteen times; the arithmetic mean is found to be    0. 320 with a standard deviation of 0. 002. On the other hand, the detection efficiency evaluated using MCNPX software is 0. 3212 (3). This last uncertainty is mainly due to the volume measurement uncertainty since the statistical uncertainty and air density variation are negligible.
Acknowledgments This work has been supported by the  European Metrology Research Programme  (EMRP), JRP-Contract  IND57   MetroNORM  (www. emrponline. eu). The EMRP is jointly funded by the EMRP participating countries within EURAMET and the  European Union. The authors acknowledge the financial support for this work from the  Laboratoire National de Métrologie et d'Essais (LNE).
Growth of the free-living mycelium Tulasnella calospora (Boud. ) Juel AL13/4D was isolated from mycorrhizal roots of Anacamptis laxiflora (Lam. ) R. M. Bateman, Pridgeon and M. W. Chase in northern Italy  (Girlanda et al. , 2011)  and deposited in the mycological collection of the University of Turin (accession number MUT4182). Free-living mycelium was maintained on solid 2% malt extract agar at 25°C. To evaluate growth on different N sources, eight hyphal plugs (6 mm diameter) of 20-d-old T. calospora mycelia were transferred into flasks containing 50 ml of modified synthetic Pachlewski P5 liquid medium adjusted to pH 5. 5  (Kemppainen & Pardo, 2011)  with L-glutamine, monosodium glutamate, ammonium tartrate, sodium nitrate or ammonium sulphate, each added as 0. 49 g of N. Inoculated flasks were maintained at 25°C under constant shaking (120 rpm).
Gene identification and phylogenetic analysis Fungal genes coding for proteins possibly involved in N uptake and transfer were identified in the T. calospora genome database on the Joint Genome Institute (JGI) fungal genome portal MycoCosm (http://genome. jgi. doe. gov/Tulca1/Tulca1. home. htm). Plant transcripts coding for proteins potentially involved in N uptake and transfer were selected from the RNA-Seq database obtained in this study, as described in RNA-Seq experiments. Multiple protein alignments were performed with MUSCLE  (Edgar, 2004). Phylogenetic trees were constructed with the maximum likelihood method using MEGA v. 7. 0  (Kumar et al. , 2016) ; bootstrap analyses were conducted on the basis of 1000 resamplings of the sequence alignment. Full-length TcAMT1 and TcAMT2 isolation TcAMT1 (1467 bp) and TcAMT2 (1611 bp) full-length cDNA isolation was carried out through PCR amplification of T.
RNA-Seq experiment Two different RNA-Seq experiments were carried out to investigate expression of T. calospora and S. vomeracea genes, and the experimental set-up is illustrated in Fig. S1. In the first experiment (RNA-Seq-A), T. calospora transcripts were investigated in free-living mycelium and in mycorrhizal S. vomeracea protocorms grown on solid oat medium (0. 3% milled oats and 1% agar). Preparation of libraries and 2 9 100 bp Illumina HiSeq2000 (Illumina Inc. , San Diego, CA, USA) mRNA sequencing (RNA-Seq) was performed at the IGA Technology Services facilities (Udine, Italy). The complete series has been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE63869. For the second experiment (RNA-Seq-B), T. calospora free-living mycelium was grown on modified MelinÀNorkrans medium with two different N sources, ammonium and glutamine, each added as 0.
49 g of N. To investigate fungal and plant gene expression in symbiosis, RNA was also extracted in a parallel experiment from symbiotic and asymbiotic S. vomeracea protocorms obtained as described in the 'Symbiotic and asymbiotic germination of Serapias vomeracea seeds' section. Illumina HiSEq2500 sequencing (2 9 150 bp) was performed at the JGI (Walnut Creek, USA). The complete series of fungal and plant transcripts was submitted to GEO (GSE86968 and GSE87120, respectively). For both RNA-Seq experiments, three separate libraries were prepared from three biological replicates for each condition. Filtered fastq files of plant-only samples were used as input for de novo assembly of S. vomeracea RNA contigs (Fig. S1 ). Reads were assembled into consensus sequences using TRINITY (ver. Phytologist (2017) 213: 365-379  www.
newphytologist. com 2. 1. 1) (Grabherr et al. , 2011). Contigs were annotated following BLASTX searches against the Arabidopsis thaliana (TAIR) and the Phalaenopsis equestris  (Cai et al. , 2015)  proteome. Reads were aligned either to the T. calospora reference transcripts (http://genome. jgi-psf. org) or to the S. vomeracea de novo assembly using CLC Genomics Workbench (Qiagen Bioinformatics; http://www. qiagenbioinformatics. com/products/ clc-genomics-workbench/). For mapping, the minimum length fraction was 0. 9, the minimum similarity fraction was 0. 8 and the maximum number of hits for a read was set to 10. The unique and total mapped read numbers for each transcript were determined, and then normalized to reads per kilobase of exon model per million mapped reads (RPKM). The Baggerly test  (Baggerly et al.
Primers for RT-qPCR (Table  S1 ) were designed using PRIMER3PLUS (http://www. bioin formatics. nl/cgi-bin/primer3plus/primer3plus. cgi/) and tested for their specificity with PRIMER BLAST (http://www. ncbi. nlm. nih. gov/tools/primer-blast/). Reactions were carried out in a StepOnePlus TM RT-qPCR System (Applied Biosystems, Thermo Fisher Scientific Inc. , Waltham, MA, USA), following the SYBR Green method (Power SYBR ® Green PCR Master Mix; Applied Biosystems) as described by  Perrone et al. (2012). Thermal cycling conditions were as follows: initial denaturation phase at 95°C for 10 min, followed by 40 cycles at 95°C for 15 s and 60°C for 1 min. Expression of target transcripts was quantified after normalization to the geometric mean of the endogenous control genes, the elongation factor (EF) genes TcEF-1a and SvEF-1a.
Statistical analyses Significant differences among treatments (T. calospora biomass and RT-qPCR experiments) were tested by a one-way analyses of variance (ANOVA), and Tukey's honest significant difference (HSD) test was used for mean separation when ANOVA results were significant (P < 0. 05). Significant differences in pairwise comparisons were assessed by Student's t-test. The SPSS statistical software package (v. 23. 0; SPSS Inc. , Cary, NC, USA) was used to run statistical analyses.
Searches in the protein sequence databases indicated for TcAMT1 and TcAMT2 a high similarity to AMTs proteins identified in other mycorrhizal basidiomycetes, such as Hebeloma cilindrosporum (76% and 69% identity with TcAMT1 and TcAMT2, respectively) or Laccaria bicolor (74% and 65% identity with TcMT1 and TcAMT2, respectively). Phylogenetic comparison with functionally characterized transporters from other fungi  (P erez-Tienda et al. , 2011)  showed that TcAMT1 clustered with high-affinity transporters, whereas TcAMT2 clustered with low-affinity transporters (Fig. 2 ). Heterologous expression of T. calospora ammonium transporters TcAMT1 and TcAMT2 in a yeast mep mutant To verify that TcAMT1 and TcAMT2 encode functional ammonium transporters, the corresponding cDNAs were constitutively expressed in the yeast triple mep mutant 31019b  (Marini et al.
calospora genes potentially involved in N uptake and metabolism, both in the free-living mycelium and in symbiosis. RNA-Seq expression data were derived from two separate experiments (illustrated in Fig. S1 ): RNA-Seq-A was run to identify genes differentially expressed by T. calospora in free-living mycelium and inside symbiotic protocorms, both obtained on oat meal, whereas RNA-Seq-B was run to investigate fungal gene expression patterns in free-living mycelia grown on two defined N sources, glutamine and ammonium. Gene expression in symbiosis was also measured in this second RNA-Seq experiment in order to gain some insights into N regulation in the protocorm environment. In the free-living mycelium grown on glutamine as the sole N source, expression of both TcAMT genes was reduced as compared with ammonium, but down-regulation was significant (FC < 0.