dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank  Deep Seq  ( Next Generation Sequencing Facility of the University of Nottingham, UK ), the  nmRC (Nanoscale and Microscale Research Centre of the University of Nottingham, UK) , the  Microscopy and Histology Facility of the University of Aberdeen (UK) , the  VIB Metabolomics Core (VIB-UGent, Belgium). This work was supported by grants from the  UK Biotechnology and Biological Sciences Research Council  Grant (Grant Nos. BB/L027739/1  and  BB/N023927/1  to D. E. S. ), the Coordinating Action in Plant Sciences Promoting sustainable collaboration in plant sciences (Grant Nos. ERACAPS13. 089_RootBarriersto D. E. S. ), the  Engineering and Physical Sciences Research Council  (Grant No. EP/R025282/1 ) and the  Future Food Beacon of Excellence at the University of Nottingham  ( Nottingham Research Fellowship  to G.
On the other hand, an opposite pattern was observed during adipogenesis in human preadipocytes with increased levels of miR-424(322)/503 throughout the whole adipogenic course (14 d) (Figure  4A ), and the same effect was observed in lipid-filled human adipocytes after an acute induction of miR-424(322)/503 for 48 h (Figure  4B ), thus indicating that the impact of the miR-424(322)/503 on the adipocyte gene transcriptional program is not exclusively restricted to the blockage of the adipogenic course. Targetscan predictions based on both seed sequence conservation  [53]  and non-conserved target sites  [54]  were used as a strategy to identify specific miRNA targets among all the messenger RNAs with significant variations (i. e. , [FC] > 1. 5 plus adj. FDR p-value < 0. 05). After integrating our original datasets with computational predictions, we focused on the overlapping genes showing an inverse differential expression pattern between Wt/miR-KO adipocytes and engineered human adipocytes with persistent/acute increased levels of miR-424(322)/503 (Figure  4C ).
RNA sequencing (RNA-seq) was performed on engineered human adipocytes with increased levels of the cluster miR-424(322)/503 A) over the course of differentiation (14 days) and B) during the last 48 h of terminal differentiation. Upper left: principal component analysis (PCA). Upper right and down: gene set enrichment analysis (GSEA) was used to uncover enriched gene signatures from the molecular signatures database (MSigDB). Red and blue circles (nodes) represent different annotations exhibiting positive or negative enrichment, respectively (FDR q-val < 0. 05). Size of nodes reflect pvalue (p-val < 0. 05 for all samples). Arrows interconnect pathways presenting common genes in the leading edge subset for each annotation. C) Venn diagram showing the overlap between potential Targetscan (TS) target genes with differential expressions between Wt/miR-KO mouse adipocytes (red circle); differentiating human adipocytes with or without induction of the miR-424(322)/503 cluster (green circle); and adipocytes with or without cluster induction for the last 48 h of differentiation (blue circle).
[76] Fat samples were then embedded in paraffin and some sections were stained with hematoxylin and eosin (H&E). The area of 100 adipocytes in 10× images of fat per mice was measured using the ImageJ software (Rasband, W. S. , National Institutes of Health, Bethesda, Maryland, USA). To calculate the average adipocyte volume, the radius of each individual adipocyte area was estimated, assuming a circular model. The estimated average radius was then used to calculate the volume (assuming a spherical model) of each adipocyte by means of the sphere volume formula: V = 4/3 r 3. Number of adipocytes was finally provided as volume of fat deposit/average volume of adipocytes. [77] dipocytes' Size: To determine the effects on adipocyte morphology, visceral and subcutaneous fat was obtained immediately after euthanasia.
Fat pads of mice from each group were fixed in formalin and embedded in paraffin, and cut in 5 micrometer sections, and stained with H&E. ImageJ was used within 10× images to analyze the area of 100 adipocytes. Cells were outlined by enhanced contrast function and the calculated area was obtained, in pixels, for each as described in Parlee and colleagues. [77] This process was applied to 5 images per slice, resulting in 1500 adipocytes analyzed per genotype and sex or 500 adipocytes per mouse. Measurements were obtained from three individual animals per group. Data are presented as the average ± SD for each group. Gaussian fit histograms showing adipocyte area distribution were calculated as described in. [78] uman Samples: This study was also intended to examine the expression of the miR-424(322)/503 locus in human adipose tissue.
Hence, measures of miR-424-5p and miR-503-5p in abdominal subcuta-neous fat samples were retrieved from publicly available GEO datasets (http://www. ncbi. nlm. nih. gov/geo/) and ArrayExpress (https://www. ebi. ac. uk/arrayexpress/), with accession numbers GSE45159  [48]  and E-TABM-1140,  [47]  respectively. The expression profiling of these datasets was based on Illumina platforms. Series matrix files were downloaded to screen and verify miR-424(322) and miR-503 expression levels in human adipose tissue. GSE45159 collected 197 fat samples from Finnish men aged 57 ± 7 years (BMI = 26. 6 ± 3. 3 kg m -2 ), and E-TABM-1140 contained a final amount of 131 participants (only women; median age 58 y; BMI = 27. 36 ± 5. 53 kg m -2 ). The samples in these two databases were collected with needle biopsies in the population of the Kuopio town, in eastern Finland,  [79]  and by means of punch biopsies taken in volunteers of the UK Adult Twin Registry,  [80]  respectively.
" Samples of SC adipose tissue after surgery-induced weight loss were also analyzed. Around 2 years after bariatric surgery, an incisional biopsy of SC adipose tissue from the abdomen was obtained. This study is described in detail elsewhere. [51] ll subjects were of Caucasian origin, gave written informed consent after the purpose of the study was explained to them, and reported that their bodyweight had been stable for at least 3 months before entering the study. Samples and data from subjects included in this study were provided by the FATBANK platform, promoted by the CIBEROBN, and coordinated by the IDIBGI Biobank (Biobanc IDIBGI, B. 0000872), integrated in the Spanish National Biobanks Network. All samples were handled in accordance with the standard operating procedures and the approval of the Ethics, External Scientific, and FATBANK Internal Scientific Committees.
To induce increased expression of miR-424(322) and miR-503, doxycycline (Alfa Aesar, J60579) was added to the culture media at 500 ng mL For each assay, intracellular lipid accumulation was measured using Oil Red O staining. When Oil Red O staining was not available, lipid droplet area was quantified by means of the Fiji software (https://imagej. nih. gov/ij/), a platform for custom biological image analysis. [82] Image processing approaches were applied to the area taken by lipid droplets, which were quantified using a threshold plugin after sharpening pixel intensity. Values obtained were expressed as the percentage (%) of total microscopy image filled by highly refringent vacuoles of lipid within the cytoplasm of adipocytes observed under bright-field illumination. Three to eight biological replicates were collected separately for total DNA, RNA, and protein extraction after adipocyte differentiation and treatment, if any.
Gene expression measures were assessed by real time PCR. RNA-seq: Complete RNA-sequencing data that support the findings of this study have been deposited in the community-endorsed repository Gene Expression Omnibus (GEO) (http://www. ncbi. nlm. nih. gov/geo/) with the accession code number GSE185819. 2 × 75bp paired-end polyA capture RNA sequencing was performed on a NextSeq500 Illumina sequencing platform at MAR Genomics (http://sam. imim. es). Raw sequencing reads (coverage 30M reads/sample) in the fastq files were mapped with STAR version 2. 5. 3a  [83] to the Gencode release 29 based on the GRCh38. p12 reference genome (for human samples), and to the Gencode release 17 based on the GRCm38. p6 reference genome (for mouse samples), together with corresponding GTF files. Table  counts  were obtained with FeatureCounts function in the package subread, version 1.
5. 1. [84] The differential expression genes (DEG) analysis for different conditions was assessed with a variance modeling at the observational level (voom) plus an empirical Bayes moderated t-statistics model (limma) in the limma package version 3. 30. 13  [85] and the R (version 3. 3. 2) programming environment (https://www. R-project. org/), together with different Comprehensive R Archive Network and Bioconductor packages (http://cran. r-project. org/). Genes having less than 10 counts in at least 3 samples were excluded from the analysis. Raw library size differences between samples were treated with the weighted trimmed mean of M-values normalization method (TMM), implemented in the edgeR package. [86] hese normalized counts were used in order to make the unsupervised analysis, PCA, and clusters, also used to discard any potential batch effect.
html). Three collections of gene sets were evaluated: Hallmark, C2 (containing all curated gene sets), and C5, which includes the gene ontology (GO) biological process. Pathways diagrams were performed using Enrichment Map application in Cytoscape (v. 3. 7. 2). [88]  Relative miR-424 and miR-503 abundance in humans was achieved by re-analyzing two independent ncRNA-seq cohorts performed in men and women. [47, 48] miRNA counts data were downloaded and miR-424 and miR-503 counts were normalized in relation to the sum of all the miRNA counts for the corresponding individual (Counts Per Million), following previous recommendations. [89] Cross-species human/mouse miR-424(322) and miR-503 targets were identified by downloading and integrating predictions from Targetscan_V7. 2. Targets were further filtered by their expression (RPKM/TPM > 0.
Membranes were incubated overnight at 4 °C with a 3% BSA (Fisher BioReagents, BP9703-100)-TBST solution containing the primary antibody. Thereafter, membranes were incubated for 1 h with secondary HRPconjugated antibodies at room temperature (Jackson Immunoresearch, 115-035-003 and 111-035-003). Signal was detected with a western blot HRP substrate (Millipore, WBLUF0500). The antibodies used in this study include anti-SNCG (Sigma Aldrich, HPA014404), Anti-TNFAIP8 (Sigma Aldrich, HPA057089), anti-UNG (GeneTex, GTX113860), anti-CHRDL1 (GeneTex, GTX49225), anti-CEBP-(Santacruz, sc-166258) anti-AdipoQ (Life Technologies, PA1-24411), anti-PPAR (Santacruz, sc-7273),anti-FABP4 (R&D Systems, MAB3150) and anti-Actin (Sigma Aldrich, A5441).
Peak assignment was performed with the ALEX software  [106]  and applied a mass accuracy of less than 3 ppm. Quantification was achieved by multiplication of the spiked-in IS amount with the analyte-to-IS intensity ratio. The following www. advancedscience. com lipid species were applied as internal standards: Cer 18:1;O2/14:0, Cer 18:1;O2/17:0, DG 14:0/14:0/0:0, DG 20:0/20:0/0:0, HexCer 18:1;O2/12:0, HexCer 18:1;O2/17:0, LPC 13:0/0:0, LPC 19:0/0:0, PC 14:0/14:0, PC 22:0/22:0, PE 14:0/14:0, PE 20:0/20:0, PI 17:0/17:0, SM 18:1;O2/12:0, TG 17:0/17:0/17:0, and TG 19:0/19:0/19:0. Lipid species were annotated according to the recently published proposal for shorthand notation. [107] xtracted data were processed by self-programmed Macros as described in. [106] Lipidomic data have been made publicly available in Figshare (10.
3 obese participants), were enrolled. An independent sample of 19 morbidly obese patients (6 men) following bariatric surgery was analyzed before and after 1 year of surgery-induced weight loss. The study protocol was approved by the Ethics Committee and the Committee for Clinical investigation (CEIC) of the "Hospital Universitari Dr. Josep Trueta de Girona. " Enzyme-linked immunosorbent assays were used to measure -Synuclein in human plasma (R&D, DY5745-05) and in serum from miR-KO and Wt mice under NC (LifeSpan Biosciences, Inc. , LS-F12685-1). Intra and inter-assay coefficients of variation were between 5 and 10%. Other biochemical assessments were performed as routine laboratory measures. Statistical Analysis: Where indicated, data are expressed as mean ± standard deviation (S. D. ) or standard error of means (S.
E. M. ). Statistical analysis was performed using SPSS (IBM Analytics) or GraphPad Prism, version 8. 0 (GraphPad Software), with a P-value of less than 0. 05 considered significant. Statistical significance was determined by the Fisher's ex-act t-test in comparisons between two groups. Differences between paired samples were compared by paired Student's t-test. One-way ANOVA followed by Tukey's honestly significant difference post-hoc test was used to compare multiple groups (3 and above) and determine which specific groups differed from each other. Statistical significance was assessed in time-course experiments by adjusted ANOVA after applying Šidák's corrections to repeated measures. Spearman's test was employed in correlation analyses. Sample sizes (n) are mentioned in each figure legend.
Acknowledgements The authors are indebted to the participants of the FATBANK platform, promoted by the  CIBEROBN  and the  IDIBGI Biobank (Biobanc IDIBGI ,  B. 0000872 ), and integrated in the  Spanish National Biobanks Network , for their collaboration and coordination. The authors thank the  IMIM Microarray Analysis Service (Hospital del Mar Medical Research Institute; Barcelona, Spain ) for technical assistance. This study has been funded by  Instituto de Salud Carlos III (ISCIII)  through the projects  CP17/00063 ,  CP19/00109 , and  PI18/00550  (Cofounded by  European Regional Development Fund (ERDF)  "a way to build Europe," by the  European Social Fund (ESF) , " investing in your future "), by the grant  RTI2018-095611-A-I00  funded by  MCIN/AEI/10. 13039/501100011033and  the  European Union , and by the  Marató de TV3 Foundation  (Project # 201623-30-31 ).
The figure was created using KolourPaint for Ubuntu linux, Release 20. 12. 3 (freely available and downloadable at https:// apps. kde. org/ kolou rpaint/). The histograms of Fig. 3d  and e are obtained in a control experiment where the setup was equipped with co-rotating temperature sensors (thermocouples) measuring near-surface and near-bottom water temperature time series at mid-radius, at an azimuthal position angle ("longitude") of ca. 90 • from the barrier. Panels (d) and (e) show the measured temperature distributions before and after the opening, respectively. Clearly, the surface (orange) and bottom (green) temperature distributions of the "closed" case largely overlap with each other, whereas in the "open" configuration the surface and bottom histograms shifted toward higher and lower temperatures, respectively, indicating stronger vertical stratification.
Simulations in a GCM Our numerical investigations were conducted with a general circulation model or global climate model (GCM) of intermediate complexity, the so-called Planet Simulator (PlaSim), developed at the University of Hamburg  22, 23  , the technical basics of which are briefly described in the "Methods" section and further details are given in the Supplementary Material. The model incorporates atmospheric and-when coupled with a large-scale geostrophic (LSG) ocean module  24  -full-depth ocean dynamics. Instead of implementing the realistic paleogeographic shorelines and the (mostly unknown) paleobathymetry of the Eocene epoch, the "closed" configuration was modeled simply by a full-depth meridional barrier ("dam") in the Drake Passage connecting the tip of South America and the Antarctic peninsula, while otherwise keeping the present-day continental arrangement unchanged, as sketched in Fig.
5. In the zonal direction the barrier spanned two grid cells (i. e. a domain of 11. 2 • ) on PlaSim's grid with a resolution of T21. Each simulation covered a 1000-year time frame, of which the last, already quasi-stationary 200-year interval was evaluated in terms of annually averaged surface temperature fields both in the "closed" and "open" configurations (no barrier, modern topography). The model runs were conducted using an estimate  25  for the Late Eocene-Early Oligocene CO 2 level, 750 ppm. As an adjustable setting, the so-called ice module of PlaSim could be switched on or off. When active, the module computes the extent and thickness of sea ice dynamically as the temperature field changes. When turned off, however, even when the water temperature decreases below freezing point in a given grid cell, the formation of ice shelves is inhibited and, hence, so are the resulting effects on the system (most notably, the ice-albedo feedback).
Acknowledgements We are thankful for the reviewers and the editor for their insightful comments and suggestions and for the fruitful discussions with  K. Speer ,  T Haszpra ,  I. M. Jánosi ,  T. Tél. The essential help of A. Kohári during the revisions is also highly appreciated. This paper was supported by the  National Research, Development and Innovation Office (NKFIH)  under Grants  FK125024  (M. V. ), FK135115 (M. V. , J. P. , T. B, M. H. ), PD124272 (M. H. ),  FK124256  (M. H. ) and K125171 (M. V. , M. H. ). C. R. and U. H. were supported by the  DFG Spontaneous Imbalance project  ( HA 2932/8-1  and  HA 2932/8-2 ) that is part of the  DFG research unit "Multiscale Dynamics of Gravity Waves"  ( FOR 1898 ). I. D. B. was supported from  BMBF-Programm   01PL17029  " Qualitätspakt Lehre ", in the project " Exzellenz von Studium und Lehre-Individueller Studieneinstieg, innovative Studienmodelle ,  Forschendes Lernen.
" Additional support is received from the  K-125015  and  GINOP 2. 3. 2-15-2016-00033grants  of the  National Research, Development and Innovation Office (NKFIH, Hungary). Partial funding of the computational infrastructure and database servers are received from the grant  KEP-7/2018  of the  Hungarian Academy of Sciences. M. H. was supported by the  János Bolyai Research Scholarship of the Hungarian Academy of Sciences. This is MTA-MTM-ELTE Paleo contribution No. 354.
New longread sequencing technologies, namely the Pacific Biosciences (PacBio) and Oxford Nanopore technologies, can sequence the entire 16S rRNA gene, but high error rates have limited their attractiveness. For now, microbiome analysis pipelines take advantage of PacBio circular consensus sequencing (CCS) technology to sequence and error-correct full-length bacterial 16S rRNA genes  [14, 15]. However, comparative analyses have revealed that the PacBio data showed a weaker relationship with the reference whole-metagenome shotgun datasets than profiles generated by short-read sequencing platforms  [16]. In addition, the high costs impel most researchers to limit their use of long-read sequencing, and the insufficient sequencing depth that does not allow access to subdominant and rare microorganisms remains a potential issue.
Probe design Sequences of three OTUs of interest (identified in a previous study  [23] ) were targeted using probes. Thirty-mer probes (Table  1 ) were designed using KASpOD software  [24]. Adaptor sequences were added to the ends of the probes to enable their amplification by PCR, resulting in ' ATCGCACCAGCGTGT-N X -CACTGCGGCTCCTCA' sequences, with N X representing OTU-specific capture probes. Biotinylated RNA capture probes were then synthesized as described by Ribière et al. [25]. In brief, adaptors containing the T7 promoter were added to 16S rRNA gene-specific capture probes via ligationmediated PCR, and the final biotinylated RNA probes were obtained after in vitro transcription and purification.
Impact Statement Achieving microbial species-level identification improves the ecological and/or clinical relevance of the results compared to identification at higher taxonomic levels. Exploring polyphenol-degrading bacteria, we revealed an important hidden microbial diversity behind 16S operational taxonomic unit sequences from the human gut microbiota rare biosphere using gene capture by hybridization. Obtaining such precision could not be resolved by current methods, including shotgun metagenomics and profiling by third-generation sequencing. CAGA AGAC GGCA TACGAG-3′). To increase the enrichment efficiency, a second round of hybridization capture was performed using the first-round capture products. The enriched DNA was then sequenced using Illumina MiSeq 2×250 bp runs. Reads were deposited in the European Nucleotide Archive under study accession number PRJEB43604.
Bioinformatic and phylogenetic analyses Reads were scanned for library adaptors and quality-filtered using the PRINSEQ-lite PERL script  [26]  prior to analysis. 16S rRNA gene reconstruction and OTU clustering from the five samples were performed using EMIRGE 0. 60  [11]. Taxonomic classification of the sequences was then performed with RDP Classifier  [27]  using the Silva  [28]  database 119 release with the confidence cut-off set at 0. 5. The pipeline is available on GitHub (https:// github. com/ SoMarre/ CaptOTU). Phylogenetic analysis was conducted using a phylogeny analysis pipeline  [29]. The candidate 16S rRNA gene sequences were first submitted in fasta format; sequences were aligned with muscle  [30] , and the aligned sequences were curated with Gblocks  [31] ; the phylogenetic tree was reconstructed with PhyML by using the maximum-likelihood method  [32] ; and the reconstructed phylogenetic tree was visualized and rendered by FigTree v1.
4. 3  [33]. A similarity search was conducted using the blast algorithm  [34]  with default parameters in the GenBank database. We used the identity thresholds defined by Yarza et al. [7]  to evaluate novel taxa (i. e. 97 % for species, 94. 5 % for genus, 86. 5 % for family, 82. 0 % for order) confirmed by phylogenetic tree reconstruction. Text mining of annotated genomes was used to search for enzyme names associated with polyphenol metabolic pathways  [35].
Full-length 16S rRNA gene recovery from short metabarcoding sequences Three OTUs (146, 393 and 1761) derived from the 16S rDNA V3-V5 region were identified in a previous in vitro study  [23]  involving four microbial faecal communities that were incubated with a mixture of purified apple polyphenols and polysaccharides (Data S1, available in the online version of this Fig. 1. Experimental scheme to reconstruct full-length 16S rRNA genes from selected short metabarcoding OTU sequences. The principle of the method involves several steps: specific probes are first designed to target OTUs of interest. In the present study, we selected three OTUs that were previously obtained by a metabarcoding approach targeting the V3-V5 region of the 16S rRNA gene  [23]. Biotinylated probes are then hybridized to a sequencing library (Illumina library in this study) constructed from the explored metagenomic sample.
6 % (30-fold increase) for OTU 1761, 0. 14% to 0. 82 % (5. 9-fold increase) for OTU 393 and 0. 015 to 0. 083 % (5. 5-fold increase) for OTU 146. At such low relative abundances, these OTUs could be considered subdominant or rare microbial members of the community. We checked by similarity searches in the GenBank database that, as previously described, OTUs 146 and 393 were identified as members of the family Lachnospiraceae and OTU 1761 was only assigned at the order level as Clostridiales. Using our KASpOD algorithm, we identified the 20 most specific probes (seven, six and seven probes targeting OTUs 146, 393 and 1761, respectively), allowing specific and efficient gene capture from the previously obtained 16S rDNA V3-V5 sequences (Table  1 ). We selected probes dispersed over the V3-V5 sequences with limited crosshybridizations to improve enrichment efficiency and specificity.