dataesr/scientific-paragraphs-categorization huggingface dataset:
Fluorescence emission was detected from 500 to 550 nm for Syto 9 and from 640 to 660 nm for Syto 61. Images were taken every micrometer throughout the whole biofilm depth. For visualization and processing of three-dimensional (3D) image, the Zen 2. 1 SP1 software (Carl Zeiss Microscopy, Oberkochen, Germany) was used. Quantitative analyses of images stacks were performed using the.
Acknowledgments: We wish to thank  Magalie Barreau  and  Olivier Maillot  for technical assistance. T. Clamens  and  T. Rosay  were recipients of a doctoral fellowship from the  French Ministry of Research (MRE). This work was supported by grants from the  Evreux Portes de Normandie , the  Conseil Général de l'Eure, European Union (FEDER) ,  Normandy Region  and the  French Association "Vaincre la Mucoviscidose ".
Results Transcriptome of low-and high permeability brain metastases. To study the BTB at the molecular level, gene expression was compared between LCM metastases of relatively low and high permeability to TRD within the same mouse brain (Fig. 1a ). TRD was used as a marker of paracellular permeability, as its uptake in experimental brain metastases correlated directly with that of paclitaxel, vinorelbine, doxorubicin, and lapatinib  4, 10, 20. The gene expression patterns of the human 231-BR tumor cells and mouse tumor microenvironment were captured using human and mouse microarrays, respectively. Of the 39,000 mouse transcripts and 47,000 human transcripts, 2748 murine and 1097 human were differentially expressed (P < 0. 05, t-test) (Supplementary Data 1 and 2). Figure  1b , c presents heatmaps of differentially expressed genes from the mouse and human microarrays, respectively.
The in vitro BBB model system offers the opportunity to interrogate specific sets of cells under multiple experimental conditions; despite years of optimization it remains an incomplete correlate of the actual BBB. In vivo, a limited course of S1P3 antagonist treatment also significantly tightened the BTB in two model systems, but was without significant effects on the already closed BBB. Permeability of methotrexate was also quantified in whole brain homogenates after S1P3 antagonist treatment, and demonstrated a trend of increased permeability. These data are encouraging as the whole brain homogenates were dominated by uninvolved brain, where the TRD experiments only quantified the metastatic lesions. Our findings provide a proof of principle that compounds targeting the astrocytic neuroinflammatory response in the brain metastatic microenvironment can modulate BTB permeability.
The 4T1-BR cell line was provided by Dr. Suyun Huang, MD Anderson Cancer Center, TX, USA. Parental lines MDA-MB-231, SUM190, and JIMT-1 were sent to ATCC® for authentication, using 17 short tandem repeat (STR) loci and the gender determining locus. Of these, only MDA-MB-231 was available in the ATCC® STR database and was a match. The SUM190 and JIMT-1 lines were not in the ATCC® STR database and could not be authenticated. Each brain seeking variant was compared to the parental line using the same technology and all the three matched their corresponding parental line, confirming the provenance of the brain seeking variants. Animal experiments. Animal experiments were conducted under a National Cancer Institute-approved Animal Use Agreement, following the Animal Care and Use Committee (ACUC) regulations.
Quality and quantities of RNA were analyzed using the RNA Pico Chips and the Agilent 2100 Bioanalyzer (Agilent Technologies). Each sample had an average of 117 ng µL -1 (10 µL total) and a RNA integrity number of 8. 5. Gene expression profiling was performed by the NCI-Frederick Genomics Core Facility using the Nugen Ovation® labeling kit in conjunction with the following GeneChip®: Human Genome U133 Plus 2. 0 array (whole human genome expression array for over 47,000 transcripts including ESTs) and Mouse Genome 430 2. 0 array (whole mouse genome expression array for over 39,000 transcripts including ESTs) (Affymetrix). A pivot table was generated for the human and the mouse GeneChip, with t-test analysis used to compare data from highly permeable vs. poorly permeable lesions. Genes with Pvalues of <0.
Heat maps were generated using Matrix2png version 1. 2. 1 software. Validation of the LCM/microarray. For each mouse of a new cohort, one 8 μm brain section was analyzed directly under a fluorescent microscope to identify highly vs. poorly TRD permeable metastases. The adjacent section was stained with antibodies directed to the proteins of interest: GFAP (1:10,000-cat#MAB360, Millipore), GABA A receptor α1, (1:50-cat#75-136 clone N95/35, NeuroMab), GABA A receptor γ2 (1:50-cat#224003, Synaptic System), S1P3 (1:100-cat#LS-B2155, LSBio and 1:100-cat#NBP1-00789, Novus), EphA5 (1:50-cat#GTX25398, GeneTex Inc. ), NeuN (1:50-cat#MAB377, Millipore), and CD31 (1:500cat#550274, BD Pharmingen). See Supplementary Table  1  for all antibodies' references. Briefly, slides were fixed with methanol for 5 min at -20 °C, washed with PBS then incubated in blocking buffer (PBS with 5% goat serum, DAKO) for 20 min at room temperature.
Primary antibodies were incubated overnight at 4 °C. After three washes, the secondary antibodies (1:500, Alexa Fluor® antibodies) and DAPI were incubated for 1 h at room temperature. The slides were mounted using fluorescence mounting medium (Dako). Photographs of highly permeable and poorly permeable metastatic lesions in each section were acquired with the Zeiss Axioskop, at 10× or 20×. Quantification of immunostaining was performed on the entire field with the analysis program of Zeiss Axioskop Axiovision4 © software as previously described  19. GABA A receptor α1, GABA A receptor γ2, and S1P3 antibodies stained activated astrocytes, therefore the quantification of these three markers was normalized to GFAP staining. EphA5 antibody stained astrocytes, neurons, and at a lesser extent metastatic cells.
There was no marker that could represent those three cellular components, therefore the quantification of EphA5 staining was expressed as percentage of area stained in the entire microscopic field. Image analysis and figure processing. All immunofluorescent pictures were acquired with the Zeiss Axioskop, and quantification performed on the original Zeiss format ". czi", using Zeiss Axioskop Axiovision4© software. For quantification, the surface area covered by each fluorescent marker was measured in the entire picture. The markers expressed in astrocytes (S1P3, GABA Aγ2, GABA Aα1, and EphA5) were normalized to all the activated astrocytes using GFAP. The maker expressed in neurons (EphA5) was normalized to all the neurons using NeuN. After quantification, all the ". czi" images were exported as jpeg/tif.
2 (found). The synthetic route to TY-52156 is shown in Figure  10. TY-52156 efficacy experiments. Five to seven-week-old athymic NIH nu/nu mice were anesthetized with isoflurane/O 2 and injected in the left cardiac ventricle with 231-BR cells (1. 75 × 10 5 cells in 0. 1 mL Ca 2+ Mg 2+ free PBS). At day 24 postinjection for the 231-BR model, mice were randomized (based on body weights using StudyLog software randomization feature) to vehicle or 10 mg kg -1 of TY-52156 (in 0. 5 w per v% Tragacanth Gum (MP Biomedicals, Inc. )) groups, BID by oral gavage. The treatments were administered for 4 days. On day 28 for the 231-BR model, mice received TRD followed by a perfusion as described above. It was expected that some mice would require euthanasia before the end of the treatment because of neurological or morbid symptoms (per ACUC rules): those mice were excluded from the data analysis.
At necropsy, brains were fresh frozen in OCT. Ten series of five 8 µm-slices (2 slices per slide) were sectioned every 300 µm, through the entire brain in a ventral to dorsal orientation. The first section in each series of 5 was H&E stained to localize and count the metastasis clusters, and the following slides were used to photograph TRD exudation and IF with the following markers: CD31 (1:500-cat#550274, BD Pharmingen), human cytokeratin (1:100-cat# M0821, DAKO) and Ki67 (1:100-cat# M7240, Dako). Photographs were acquired and analyzed by the Zeiss software, ZEN software. For the 231-BR model, the vehicle group contained 11 mice and the TY-52156 treated group had eight mice. TRD diffusion was quantified on a continuous rather than dichotomized basis, measuring the surface area covered by TRD.
For each mouse, one section on one slide (two tissue sections per slide) from the series with the highest number of metastases was used for TRD quantification. The image was captured at 10×, over 5-10 s interval, to avoid thawing the tissue. This same slide was used for IF staining: Ki67, cytokeratin and CD31 on one section, and S1P3, GFAP and CD31 on the other. ZEN software enabled identification of the exact coordinates of the pictures taken for TRD. After IF staining, the same coordinates were used to capture images of the same cells, enabling normalization of TRD to cytokeratin staining as a marker of metastases burden, or to CD31 as a marker of blood vessel density. For each IF marker, percent of area over the entire picture was measured. Two mice per group did not receive TRD, for PK analysis.
Informed consents were waived for the other samples, as the patients were deceased. All the samples, regardless of the country of origin, were anonymized and approved by the Office of Human Subjects Research Protections (OHSRP) at the National Institutes of Health (OHSRP #13093). IF staining was performed as described previsouly  19. Briefly, tissues were fresh frozen and then embedded in OCT. H&E staining and IF with S1P3 and GFAP antibodies (sources above) were performed on 8 µm sections. Pictures were acquired with Zeiss Axioskop and ZEN software  19. Another cohort of patients' brain metastasis samples was immune-stained and analyzed by pathologists from the Medical University of Gdańsk, Poland. Generation of immortalized brain-derived cell lines. Primary human astrocytes (#1800) and brain vascular pericytes (#1200) were purchased and cultured in astrocyte medium (#1801) and pericyte medium (#1201), respectively, according to manufacturer's protocol (ScienCell research laboratories).
Cytokine profiling. Assessment of cytokines secreted by shControl and S1PR3knocked down HAL cells was performed using Proteome profiler-human cytokine array (R&D Systems, #ARY005B). Media from ~70% confluent HAL-shControl-1,2 and HAL-shS1PR3-1,2 was replaced with serum-free HA medium. 12-16 h later, the media was harvested, particulates were removed by brief centrifugation, aliquoted and frozen. Fresh aliquots were quantified, and ~500 µL was used for the assay according to the manufacturer's protocol. Using ImageJ software, the intensity of quantifiable spots was measured. The intensities were normalized using reference spots from both membranes. Fold change of cytokine expression in shS1PR3 astrocytes compared to shControl cells was calculated and graph was plotted. Cytokine inhibition. Once the in vitro BBB/BTB cultures were established as described above, culture media on astrocytes was changed to serum-free AM.
Percent cell growth was calculated using normalized fluorescence at 570 nm/585 nm and plotted. Statistical analysis. Power analysis indicated that a minimum of n = 4 was required to detect a significant small-to-medium effect size, with an acceptable power of 0. 8. For in vitro data, four to seven technical replicates of each experiment were performed. For each replicate, three measurements were recorded at each time point. When n was less than 5, individual data points were plotted in the graph. For in vivo data, power calculation indicated that 8-11 mice per group were required to obtain a statistical power of 0. 8. An exception is Fig. 7d, e , for which only five mice were used in the vehicle control (several mice had to be euthanized earlier because of morbid symptoms). All the data were analyzed using the software Graphpad Prism 7.
01 (GraphPad Software, Inc. ). Nonparametric tests were performed on datasets not normally distributed. Specific tests are mentioned in each figure legend. Briefly, for bivariable analysis, two-tailed Mann-Whitney test was chosen for unpaired data and Wilcoxon rank test was chosen for matched-paired data. For multivariable analysis, a non-parametric Levene's test was performed with SPSS software from IBM to verify the equality of variances in the samples (P > 0. 05). Subsequently, Kruskal-Wallis test followed by Dunn's multiple comparison test was performed. To analyze interaction between S1P3 overexpression and TRD diffusion, Chisquare statistical analysis was performed. We used P < 0. 05 for significance.
Acknowledgments The authors acknowledge the statistical advice of  Dr. Seth Steinberg  and  Mr. David Liewher ,  Biostatistics  and Data Management Section, CCR,  NCI, Bethesda, MD, USA. This work was supported by the  Intramural program  of the  National Cancer Institute, U. S. Department of Defense Breast Cancer Research Program , grant number:  W81 XWH-062-0033 , and a research grant from the  Inflammatory Breast Cancer Foundation. The human tissue samples from France were provided by AP-HM tumor bank  AC-2013-1786 ,  BB-0033-00097. The immunohistochemistry of human tissue samples performed in Poland was partly funded by the  Institutional  Grant  ST-23  from the  Medical University of Gdańsk. This project has been funded in whole or in part with Federal funds from the  National Cancer Institute, National Institutes of Health , under Contract No.
Data availability. The authors declare that all the data supporting the findings of this study are available within the paper and its supplementary information files. Full gels and Western blots are presented in Supplementary Fig. 12. The microarray data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus and are accessible through GSE112776 [https://www. ncbi. nlm. nih. gov/ geo/query/acc. cgi?acc=GSE112776].
RNA isolation, RNA-Seq library preparation and illumina sequencing Total RNA was isolated using TRI Reagent (Sigma) and the Directzol RNA Mini-Prep Kit (Zymo) according to manufacturer's protocol. One μg of total RNA was used per sample for library construction according to the Illumina TruSeq mRNA Library Preparation Kit protocol. Libraries were quantified using Qubit fluorescence spectrophotometry and pooled at equimolar ratios for sequencing in one lane on an HiSeq2500 platform (2 × 101bp format). Reads were demultiplexed, converted to FASTQ format using the bcl2fastq script and assessed for quality control  (Andrews, 2010). Raw read files are deposited in the NCBI Sequence Read Archive (SRA) under accession number SRP130864. 2. 5. RNA-seq read processing, genome mapping and filtering Analysis of differentially expressed genes (DEGs) was performed as a two-step process.
Firstly, Tophat v 2. 0. 14 was used to perform read mapping against S. mansoni genome version v 5. 2 with default settings and the genome annotation downloaded from WormBase ParaSite  (Howe et al. , 2016 (Howe et al. , , 2017)). Secondly, transcript assembly was performed using Cufflinks v 2. 2. 1 to produce a normalised count matrix (genes. count. tables) consisting of 16,234 assembled transcripts, of which 9949 could be mapped to 10,820 unique Smp identifiers (with some transcripts mapping to multiple Smps). Sample replicate quality was assessed by clustering of pairwise Euclidean distances and visualised in a heatmap with treatment (i. e. control or 5-AzaC) as the variable of interest. The biological replicates were, thereafter, combined and differential expression analysis performed using the DESeq2 package  (Anders and Huber, 2010)  at an FDR of 0.
05 (using Benjamini-Hochberg adjustment). Here, 4115 differentially expressed transcripts mapping to 4036 unique Smp gene identifiers were identified at a log2 fold change > ± 1. Due to splice variants, 21 of these 4036 Smps were found in both down and up regulated lists of transcripts, giving a total of 4057 differently expressed Smps. Finally, 5102 transcripts were identified by DESeq2 as having non-significant differential expression. All analysis steps were performed with default settings.
Functional enrichment analyses To investigate functional differences between the 5-AzaC and control samples, the g:GHOSt function (moderate filtering) within the g:Profiler webtool was used for the gene ontology (GO) enrichment of DEGs  (Reimand et al. , 2016). For the identification of pathways associated with each set of genes, S. mansoni pathway data were downloaded from BioCyc  (Caspi et al. , 2016)  and, thereafter, visualised using the Neo4j graphical database  (Webber, 2012). The BioCyc data consist of a series of flat files, from which data on genes, proteins, reactions, pathways and compounds were extracted. These were then stored as nodes in a Neo4j graph, with the relationships between them represented as edges. The edges included 1074 enzyme reactions (linking reaction and protein nodes) with the proteins encoded by genes and the pathway hierarchy.
To illustrate an overview of the genome locations and differential expression levels of the 4057 Smps (4115 transcripts) in the filtered (log2 fold change > ± 1) RNA-Seq dataset, a Circos plot  (Krzywinski et al. , 2009)  was generated using the S. mansoni genome v 5. 2. Further characterisation of DEGs was performed by extracting KEGG BRITE  (Kanehisa, 2016)  functional hierarchical information for each mapped Smp ID (genome v5. 2). Over-representation analysis was carried out on differentially expressed Smps identified by DESeq2. Significantly over-represented pathways (p < 0. 05) were identified and plotted using clusterProfiler  (Yu et al. , 2012)  in R. Finally, a heatmap was used to visualise transcripts that were significantly differentially expressed (adjusted p-value < 0. 05) as a response to 5-AzaC.
Significantly differentially expressed repeats The differential expression of repeats was performed using RepEnrich  (Criscione et al. , 2014). This software handles the technical difficulties that arise when mapping reads to repetitive locations in the genome (reads deriving from repeats rarely map to unique genome locations). Following the recommended protocol, we first mapped the reads uniquely to the genome using bowtie (with the -m 1 option), before calling the RepEnrich. py script with an existing annotation of repeats in bedfile format  (Lepesant et al. , 2012)  to obtain the counts for each repeat subfamily in each of the samples. Subsequently, the three control and three 5-AzaC treated samples were assembled into a 2814 × 6 matrix, where the rows correspond to the 2814 repeat subfamilies and the columns correspond to the 6 samples (3 control vs.
Gene Ratio Fig. 2. 5-AzaC affects transcripts involved in metabolic processes. A) Venn diagrams of differentially expressed enzymes participating in metabolic pathways were produced using data from BioCyc  (Caspi et al. , 2016)  and the Neo4j graph database. Smps found more abundantly expressed in 5-AzaC treated females are marked with a '+'. B) Scatter plot demonstrating significantly over-represented (p < 0. 05) KEGG functional hierarchies by differentially abundant KEGG orthologs (KOs) between 5-AzaC-treated and control females for each dataset. Circle size represents KO counts within that pathway while red colouration represents lower p values and, therefore, higher significance. Gene ratio on the xaxis represents the proportion of genes represented in the pathway to the total number of DEGs.
) regulated transcription and translation, represents another contributing factor associated with the egg-laying defect observed in 5-AzaC-treated schistosomes. In addition to 5-AzaC's recognised role in modulating the transcription of protein coding genes (e. g. (Hollenbach et al. , 2010) , this study), this epi-drug has also been shown to affect the expression of endogenous retroviruses (ERVs) and repetitive elements (REs) in ovarian cell line (TykNu and Hey) or MDS primary cell (CD34 + progenitors) cultures  (Chiappinelli et al. , 2015; Tobiasson et al. , 2017). Therefore, dysregulated RE expression in 5-AzaC-treated schistosomes could also be responsible for the egg laying phenotype observed here as well as in previous studies  (Geyer et al. , 2011). Examination of the transcriptome dataset revealed the differential expression of 2088 REs between control and drug treated female samples (Fig.
5  and Supplementary Fig. 7 ). Amongst these, only 9 REs (represented as solid green circles) were significantly enriched in the 5-AzaC-treated female samples compared to 37 REs (represented as solid red circles) significantly enriched in the control samples (Fig. 5A ). As a large proportion of the S. mansoni genome is occupied by repeats  (Berriman et al. , 2009; Lepesant et al. , 2012) , we identified the significantly enriched RE categories by comparing their occurrence in our transcriptome dataset to their occurrence in the genome. By doing so, only two types of RE in 5-AzaC-treated female schistosomes were identified as having statistically significant changes in transcription: long terminal repeats (LTR) are under-expressed (p = 0. 003) and DNA transposons are over-expressed (p = 0. 011) (Fig.
Acknowledgements We acknowledge all members of the  Hoffmann laboratory  for assisting in the maintenance of the schistosome lifecycle. Some B. glabrata snails used in this study were provided by the  NIAID Schistosomiasis Resource Center of the Biomedical Research Institute (Rockville, MD, USA)  through  NIH-NIAID  Contract  HHSN272201000005I  for distribution through  BEI Resources. This work was supported by the  UK BBSRC  ( BB/K005448/1 ) awarded to KFH and MTS as well as an IBERS PhD studentship awarded to SEM.
We analyzed data for 31 HLA-A2 D+Rrecipients; for 11, the donor did not express HLA-A2. The number of anti-CMV T cells restricted by HLA-A2 was lower for recipients who received non-HLA-A2-expressing than HLA-A2-expressing kidneys (P =. 002; Table  2 ). Therefore, the presentation of CMV peptides to CD8 + T cells by HLA-A2-expressing recipient APCs did not take place or was not efficient to drive the development F I G U R E 2 The effect of donor CMV infection on anti-CMV response required that donor and recipient share at least one human leukocyte antigen (HLA)-I identity. Data for 66 recipients sharing at least one HLA-A or HLA-B identity with donors ("no full HLA-I-mismatched recipients") and 18 recipients with full HLA-I mismatch with their donors. Data are expressed as number of spots per million CD3 + cells and per milliliter whole blood.
" More accurate analysis of the kinds of donor cells activate circulating CMV-specific CD8 + T cells would be of interest. Indeed, donor-presenting cells could be kidney cells, such as endothelial cells, fibroblasts and tubular cells, or donor passenger leucocytes. As detailed in a recent extensive review, non-haematopoietic cells are considered to support memory CD8 + T cell inflation, dependent on HLA-I. 4  This assumption relies on experimental data collected in mice infected by MCMV, which induced a large and sustained expansion of virus-specific CD8 + T cells in the blood. Indeed, infected non-haematopoietic cells in lymph nodes restimulate the central memory CD8 + T cells, which supply the blood-borne effectormemory CD8 + T cell pool. 23 Unlike the presence of life-long donor non-haematopoietic cells in SLOs, we can hypothesize that donor non-professional APCs promoting CD8 + T cell inflation in kidney transplant recipients are present in the kidney.