dataesr/scientific-paragraphs-categorization huggingface dataset:
After several washing steps, CD14 + cells were obtained with purity above 90%, as determined by flow cytometry. The resulting cells were suspended in complete RPMI medium supplemented with 53 ng/mL canine GM-CSF and 17 ng/mL canine IL-4 and cultured in a 12-well plate for six days at 37˚C. For these two protocols, morphological changes from monocytes (day 0) to cMoDCs (day 6) were characterized by flow cytometry analysis (size and granulometry) and microscopic light observation after cytocentrifugation and May Gru ¨newald Giemsa staining (Microm Microtech, France, F/010253). A comparison of cMoDCs obtained with these two protocols is shown in supplemental data (S1 Fig).
05% in comparison with the culture treated with PBS. This increase was far less important for NPs-MPLA 0. 1% or 0. 2% treatment. Together with the previous results on internalization and cytotoxicity, the nanoparticles created with MPLA at a 0. 025% loading ratio seem to be the most appropriate composition for use in vaccine development. This composition was loaded with EgTrp and used in the next part of the study. Finally, we evaluated the expression of activation markers on cMoDCs 24 h after challenge with the different formulations. An example of cytometry profiles obtained was shown in supplemental data S3 Fig,  and results  were analyzed in Fig 4. The percentage of CD80-positive cells was quite similar for all formulations tested (between 94. 5% and 97%) and were significantly different from the CD80 expression pattern in the PBS condition (p-value � 0.
High-throughput cDNA analysis of mCRPC clinical samples We browsed the clinical sample data from. 54 These data were obtained from a cohort of patients with PCa at a different stage of the disease. We selected 35 patients with mCRPC to study their gene expression profiles, including three untreated patients with mCRPC as the reference population, and 32 patients treated with taxane-based chemotherapy. Gene expression levels were calculated as the relative expression of an individual gene to the gene's expression level in a reference population. The study approval and patients consent were included in the original publication. 54 munoblotting, immunohistochemistry, and flow cytometry analysis Immunoblotting and immunohistochemistry and flow cytometry analysis were performed as previously described,  29 55  and primary antibodies are listed in online supplemental table 3.
Lymphocyte proliferation For T-cell proliferation assays, 5×10 5 CFSE-stained murine lymph node cells (2. 5 µM, 5 min; Sigma) were seeded in a 96-well U-bottomed plate. Cells were then stimulated for 72 hours with coated anti-CD3 antibody (1 µg/mL, 145-2 C11 clon, BD Pharmingen) and proliferation assessed by CFSE dilution in presence of 5×10  4  autologous splenocytes and a variable number of tumor cells as indicated. Cells were then stained for CD8 (561093, BD Pharmingen) and for CD4 (22 150 046sp, ImmunoTools) in staining buffer (PBS 1% FBS, 0. 01% sodium azide) for 30 min on ice, (n=3). Flow cytometry data acquisition was performed using a FACSAria (BD Biosciences) and analysis using the FlowJo software.
Figure4High-throughput analysis of metastasis transcriptome from metastatic samples of patients with mCRPC, treated or not by docetaxel-based chemotherapy. Gene expressions in patients treated with docetaxel (DTX+) or untreated for proinflammatory genes (A), for cytokines/chemokines gene expressions for Th2 or Th17 (B) or Th1 profiles (C), using microarray database (GSE35988). 54 IL, interleukin; IFN g, interferon gamma; mCRPC, metastatic and castration-resistant prostate cancer. on December 10, 2020 by guest. Protected by copyright. http://jitc. bmj. com/ J Immunother Cancer: first published as 10. 1136/jitc-2020-001535 on 8 December 2020. Downloaded from.
Acknowledgements The authors wish to express special thanks to  Dr Javier Cotignola ,  Lics Guillermo Piazza ,  Ignacio Gonzalez-Perez  and  Gustavo Carrizo  ( IQUIBICEN-CONICET; QB-FCEN-UBA, Argentina ) for technical help; the staff at the  FCEN-Central Animal Facility  for animal husbandry,  Dr Hong  and  Roffo hospital's nurses (Roffo hospital, CABA, Argentina)  for drugs (docetaxel was kindly gifted from  Roffo hospital ) and advice;  Sophie Tartare-Deckert  and  Marcel Deckert  from  French laboratories  for helpful scientific discussions and support. The authors also want to thank the  INSERM and Molecular Mediterranean Medicine Center (C3M) -Nice-Sophia Antipolis University-Faculty of Sciences (Nice) ,  Victor Ségalen University / IDEX(Bordeaux)  and  Paris-Diderot University-Epigenetic and Cell Fate Center (Paris) , all from France.
Molecular Modeling Docking simulations were run according to the protocol described previously  [15, 16, 24]. In brief, the ligand was sketched with VIDA (OpenEye Scientific Software) version 4. 4. 0. 4  [41] , while the protonation state was assigned by QUACPAC (OpenEye Scientific Software) version 2. 0. 0. 3  [42]. Ligand energy minimization was carried out by SZYBKI (OpenEye Scientific Software) version 1. 10. 0. 3 using the MMFF94S force field  [43]. Conformational analysis was performed with OMEGA (OpenEye Scientific Software) version 3. 1. 0. 3 by storing up to 600 conformers of each molecule  [44, 45]. Finally, molecular docking was carried out with the FRED program (OpenEye Scientific Solutions) version 3. 3. 0. 3  [46, 47]. The NMR structure of the NC in a complex with a small molecule inhibitor (PDB ID: 2M3Z) was used as rigid receptor in molecular docking simulations  [35].
In patients, suboptimal therapeutic regimens (failing to induce ICD)  (Tesniere et al, 2010; Pfirschke et al, 2016) , selective alterations in cancer cells (preventing the emission of immunogenic signals during ICD), and inherited or acquired defects in immune effectors (abolishing the perception of ICD by the immune system) can contribute to therapeutic failure due to an insufficient immune recognition of malignant cells  (Kroemer et al, 2013). Importantly, ICD induction can synergize with subsequent immune checkpoint blockade targeting PD-1/PD-L1 interaction  (Pfirschke et al, 2016; Liu et al, 2019)  and hundreds of clinical trials are investigating such combination effects (www. clinicaltrials. gov). Given the rising significance of ICD, it is important to understand the rules governing its induction at the cellular and molecular levels, especially considering that their comprehension may facilitate the identification of novel, effective ICD inducers.
After fixation, cells were stained for peIF2a as described above and cytoplasmic intensity was quantified. K-N U2OS CALR-RFP cells were inoculated subcutaneously (s. c) in the flank of nu/nu mice. Tumors were injected with PBS (Ctr) (n = 5), 0. 5 mg/kg tunicamycin (TM) for 6 h (n = 3) or 0. 5 mg/kg DACT for 6 h (n = 4) or 24 h (n = 3). Tumors were cut and stained with a phospho-eIF2a (Ser51)-specific antibody followed by an Alexa Fluor-647 secondary antibody and counterstained with Hoechst 33342. Two slices per tumor were imaged for their DAPI, RFP, and Cy5 signals. Out-of-focus images were removed from the dataset leading to the analysis of the following conditions: 8 × Ctr, 5 × TM, 8 × DACT 6 h, and 6 × for DACT 24 h. PeIF2a was quantified measuring Cy5 intensity in the cytoplasm (K, L) and CALR translocation by measuring the coefficient of variation (CV) of the RFP signal in the cytoplasm (M, N).
The present data could thus lead to a regain of interest for DACT, which is currently limited to some cases of pediatric sarcoma, gestational trophoblastic diseases, and metastatic testicular carcinomas, even though it has shown efficiency in preclinical studies performed in other kinds of cancers  (Takusagawa et al, 1982; Kam & Thompson, 2010; Cortes et al, 2016). Interestingly, one clinical trial currently investigating the effect of DACT in combination with ipilimumab and melphalan for the treatment of melanoma has shown promising results (NCT01323517)  (Ariyan et al, 2018). ◀ Figure  5. Immune-dependent effect of DACT on WEHI 164 tumors growth and sensitization to immunotherapy. A-K 3 × 10 5 mouse fibrosarcoma WEHI 164 cells were injected subcutaneously (s. c. ) into the flank of immunocompetent syngeneic Balb/c mice with n mice per group (n = 7 for DACT + anti-PD-1, n = 8 for DACT, and n = 9 for Ctr, anti-PD-1, anti-CD4/anti-CD8, and DACT + anti-CD4/anti-CD8).
ICD prediction The GI 50 (dose for which 50% of cell growth is inhibited) for a panel of 52,578 compounds (identified via their NSC number) tested on 60 different cell lines was retrieved from the National Cancer Institute website (https://dtp. cancer. gov/databases_tools/bulk_data. htm). From these 52,578 compounds, 49,419 were found to possess a valid PubChem CID (Compound ID number) using the PubChem identifier exchange service (https://pubchem. ncbi. nlm. nih. gov/ide xchange/idexchange. cgi). The related structure data file (sdf) for each CID was obtained from Pubchem, and the ICD prediction scores were calculated using the ICDPred R package available at https://github. com/kroemerlab/ICDpred. Mitoxantrone was used as a reference to select potential ICD inducers.
Secondary cytoplasmic ROIs were used for the quantification of quinacrine, peIF2a, XBP1s, and ATF6. After exclusion of cellular debris and dead cells from the dataset, parameters of interest were normalized, statistically evaluated, and graphically depicted with R software. Using R, images were extracted and pixel intensities scaled to be visible (in the same extent for all images of a given experiment). Scale bars represent 20 lm, except for microphotographs of tissue (Fig  3K  and M ) where it represents 10 lm.
Assessment of DCs activation markers BMDCs were collected and differentiated as described above. MCA205 were treated for 24 h and co-cultured with BMDCs (100,000 dying MCA205 cells and 100,000 BMDCs per well in round-bottom 96-well plate) for 24 h at 37°C. Subsequently, cells were incubated with Fixable Viability Dye eFluor 780 (Invitrogen) and anti-mouse CD16/CD32 (clone 93, BioLegend) to block Fc receptors for 15 min, at 4 °C, and then stained with 1:100 anti-CD11c PerCP Cy5. 5 (clone N4/8, BioLegend) or anti-CD11c eF450 (clone HM450, eBioscience) as well as with 1:400 anti-MHCII FITC (clone M5/114. 15. 2, BioLegend), and anti-CD86 APC (clone GL-1, BioLegend) for 30 min at 4 °C before fixation with 3. 7% formaldehyde. Samples were run through a BD LSRFortessa flow cytometer, and data were acquired using BD FACSDiva software (BD Biosciences) and analyzed with FlowJo software.
The mice were sacrificed when tumors reached 1. 8 cm 2 or depicted any signs of discomfort following the EU Directive 63/2010 and our Ethical Committee advice (or before, if required by the setting of the experiment). Animals that had to be sacrificed during the experiment due to an ethical endpoint other than tumor size were excluded from the analysis. Tumor growth and overall survival were analyzed with the help of the TumGrowth software package  (Enot et al, 2018) , freely available at https://github. com/ kroemerlab.
A quantitative PCR of each sample was run in duplicate to measure the amount of mRNAs coding for IFNc (with probe Mm00439619m1, Thermo Fisher Scientific) and peptidylprolyl isomerase A (Ppia) (with probe Mm02342430, Thermo Fisher Scientific) using TaqMan Fast Advanced Master Mix (Thermo Fisher Scientific). qRT-PCR data were normalized to the expression level of the housekeeping gene Ppia and then to the means of the level of corresponding mRNA in control mice.
Values were normalized to the control at each time point, and the percentage of inhibition and of reversibility were calculated. For this first parameter, the curve of continuous treatment was considered, with the maximum effect (100% inhibition) obtained by the slope of avidin control curve, and the percentage of inhibition was defined as the complementary ratio between these two slopes. For calculating the latter parameter, the maximum effect was defined as the measured area between biotin and avidin controls curves. Then, a percentage of reversibility was computed by calculating the complementary ratio between the area separating the continuous and discontinuous treatment curves, normalized by the maximum effect. Retrospective in silico analysis of different classes of inhibitors Compound annotations were retrieved from the MeSH (Medical Subject Headings) database, and drugs were clustered in functional groups: protein synthesis inhibitors, DNA synthesis inhibitors, poly (ADP-ribose) polymerase (PARP) inhibitors, and antimetabolites.
Impact These findings may improve the application of dactinomycin in clinics and offer new combination strategies for the treatment of childhood sarcoma. In addition, the discovery of transcription as a characteristic of ICD may facilitate the development of immunotherapies. parametric data of different conditions to a control, using the t-test function from the stats R package or the T. TEST function of Excel. A pairwise multiple comparison test with a Benjamin-Hochberg correction was used to compare each condition to another in a dataset, using the pairwise. t. test function from the stats R package. A Kolmogorov-Smirnov test was used to compare distributions using the ks. test function from the stats R package. Pearson correlations were performed, using the ggscatter function from the ggpubr R package.
freely available at https://github. com/kroemerlab. A type II ANOVA test was used for tumor growth and a log-rank test for mice survival at 1. 8 cm². For all tests, the statistical significance levels are shown with stars or hashes: */ # P < 0. 05, **/ ## P < 0. 01, ***/ ### P < 0. 001. Statistical tests and P-values are detailed in Appendix TableS5.
Acknowledgements pSpCas9(BB)-2A-GFP (PX458) was a gift from  Feng Zhang  (Addgene plasmid #48138; http://n2t. net/addgene:48138;RRID:Addgene_48138); Topotecan (609699), 7-Hydroxystausporine (72271), becatecarin ( 101524 ), 5-fluorodeoxycytidine (515328), and RH-1 (394347) were kindly provided by the  NCI. G. K. is supported by the  Ligue contre le Cancer  (équipe labellisée);  Agence National de la Recherche (ANR)-Projets blancs ;  ANR  under the frame of E-Rare-2, the  ERA-Net for Research on Rare Diseases; Association pour la recherche sur le cancer (ARC) ;  Cancéropôle Ile-de-France ;  Chancellerie des universités de Paris  ( Legs Poix ),  Fondation pour la Recherche Médicale (FRM) ; a donation by Elior;  European Research Area Network on Cardiovascular Diseases (ERA-CVD, MINO-TAUR) ;  Gustave Roussy Odyssea , the  European Union   Horizon 2020 Project Oncobiome ;  Fondation Carrefour ;  High-end Foreign Expert Program in China  ( GDW20171100085  and  GDW20181100051 ),  Institut National du Cancer (INCa) ;  Inserm (HTE) ;  Institut Universitaire de France ;  LeDucq Foundation ; the  LabEx Immuno-Oncology ; the  RHU Torino Lumière ; the  Seerave Foundation ; the  SIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination (SOCRATE) ; and the  SIRIC Cancer Research and Personalized Medicine (CARPEM).
Data availability The GI 50 for a panel of 52,578 compounds was retrieved from the National Cancer Institute website (https://dtp. cancer. gov/database s_tools/bulk_data. htm). Valid PubChem CID was retrieved from PubChem identifier exchange service (https://pubchem. ncbi. nlm. nih. gov/idexchange/idexchange. cgi), and related structure data files (sdf) were obtained from Pubchem. ICD prediction scores were calculated using ICDPred available at https://github. com/kroemer lab/ICDpred. Expanded View for this article is available online.
Cells were subsequently stained with antibodies to CD3, CD4, CD8 for 30 minutes. Samples were acquired on a BD LSRFortessa using DIVA software and data were analyzed by FlowJo software (Treestar). Preparation of OT1 T cells: Spleens from transgenic OT1 transgenic mice were pressed through a 70 m filter (Miltenyi Biotech), washed with PBS, and resuspended in 1X BD Pharm lyse buffer for red blood cell lysis. In the BBN model, at week 12, 10 6 OT1 T cells in 100 L of PBS were transferred to mice intravenously. Orthotopic model: MB49 cell stocks were thawed and cultured for 2-4 days in R10 medium before implantation. For tumor implantation, mice were anaesthetized and bladders drained of urine by pressure to the lower abdomen. Bladders were pre-treated by transurethral instillation of 25 L poly-L-lysine (0.
5E ). Finally, there were no differences in total T cells, or CD4 + and CD8 + T cell subsets (Fig. 5F ). In these analyses, we included an antibody against folate receptor 4 (FR4), which is highly expressed on natural regulatory T cells  [36] , and while we detected a large number of CD4 + regulatory T cells, there were no differences between unvaccinated and vaccinated mice in either sex (Fig. 5F ). As statistical analysis supported that these data did not arise from different distributions (range of p values = 0. 43-0. 96 for all populations measured) in any immune cell populations investigated, we combined the data from unvaccinated and vaccinated animals for further analysis.
ACKNOWLEDGMENTS We gratefully acknowledge insightful discussions, technical support, and/or critical reading of the manuscript by  Dr John Taylor  and  Livia Lacerda Mariano. We thank our spouses and partners for being supportive of our work-at-home efforts during the COVID-19 pandemic. of Glasgow, and in particular,  Drs Simon Milling  and  Robert Nibbs , for the academic opportunity offered through the integrated Masters ( MSci) program  with work placement in Life Sciences, which supported the research visits of COB, EA, and HZ.
Background: The human microbiota contributes to health and well-being. Antimicrobials (AM) have an immediate effect on microbial diversity and composition in the gut, but next to nothing is known about their long-term contribution to saliva microbiota. Our objectives were to investigate the long-term impact of AM use on saliva microbiota diversity and composition in preadolescents. We compared the lifetime effects by gender and AMs. We used data from 808 randomly selected children in the Finnish Health In Teens (Fin-HIT) cohort with register-based data on AM purchases from the Social Insurance Institution of Finland. Saliva microbiota was assessed with 16S rRNA (V3-V4) sequencing. The sequences were aligned to the SILVA ribosomal RNA database and classified and counted using the mothur pipeline.
Discussion Here, we describe an association of lifetime AM use with saliva microbiota richness, diversity composition and functional capacity in Finnish adolescents. AM use was obtained reliably and objectively from the medical purchase registry held by the Social Insurance Institution of Finland (www. kela. fi), which contains information on all medical expenditures and purchases requiring prescriptions. The data covers the whole lifespan of the adolescents for each of the 808 children individually. Our key findings are (i) lifelong exposure to AMs is associated with alterations of the saliva microbiota, (ii) the long-term effect of azithromycin use was the most noticeable and (iii) re-establishment of saliva microbiota occurs rapidly after AM exposure. More diverse microbiota communities are believed to be more stable and resistant towards invasion and other disturbances  [33]  and to sustain health.
Study design and sampling We randomly selected 973 children from the prospective Finnish Health in Teens (Fin-HIT) cohort  [49]  using a function written in the PHP programming language on the SQL database study database. The function selected participants and samples randomly among the list of Fin-HIT participants who took part in the school assessment, with sample delivered to the biobank and had completed the consent form at the time of recruitment. We did not include the participants from the pilot recruitment that was done at home. This cohort consists of approximately 11,000 9-14-year-old children and 6500 of their mothers or other legal guardians that were recruited in densely populated areas across Finland. During the baseline data collection, subjects filled in an online questionnaire on lifestyle factors, provided a saliva sample and had their anthropometric measures measured in a standardised way  [50].
In Finland, AM agents for systemic use are available by prescription and sold solely in registered pharmacies. All drug purchases based on prescriptions are registered in the Drug Prescription Register held by the Social Insurance Institution of Finland (KELA, www. kela. fi). Information on drug purchases during the entire lifespan was linked to the Fin-HIT study database. We extracted information on all systemic antibiotics based on anatomictherapeutic chemical (ATC) codes (WHO Collaborating Centre for Drug Statistics Methodology; https://www. whocc. no/atc_ddd_index). Information on antibiotics administered in hospitals was not collected. In this study, we use data on AM purchases from the date of birth to the date of saliva sampling as a proxy of AM use. Among all the AMs, amoxicillin (ATC-code, J01CA04), azithromycin (J01FA10), amoxicillin-clavulanate (enzyme inhibitor) (J01CR02) and phenoxymethylpenicillin (J01CE02) were the four most commonly prescribed AMs in this study population.
Bioinformatics analysis Sequencing quality filtering was carried out and sequences were processed using the MiSeq SOP in the mothur pipeline (Version v. 1. 35. 1)  [55] , as previously described  [53]. We used the SILVA 16S rRNA database (Version V119) and taxonomy for the alignment and classification of the sequences  [56]. To ensure highquality data for the analysis, sequence reads containing ambiguous bases, homopolymers > 8 bp, more than one mismatch in the primer sequence, less than 10 base pair assembly overlap or sequences under the default per base quality score in mothur were removed. Assembled reads > 460 bp in length and singletons were excluded from the analysis. This reduced the number of assembled reads, ensuring high-quality data  [11]. The high-quality assembled reads were aligned to the SILVA 16S rRNA database, clustered into operational taxonomic units (OTUs) at a cut-off value > 98% and assigned taxonomy to OTUs using the SILVA bacteria taxonomy.
Statistical analysis All statistical analyses were conducted in R (Version 3. 4. 2) using the stats4 (Version 3. 4. 2), vegan (version 2. 5-4) and phyloseq (version 1. 25. 2) packages. We also identified potential confounding with age and gender using t test and between child languages (Finnish, Swedish and other); sequence depth groups (medium and high) with ANOVA. Differences in the microbial alphadiversity between the four groups (AM naïve (n = 48), used AMs 1-month (n = 15), 2-months (n = 13) and 3months (n = 13) prior to saliva sampling) were evaluated using ANCOVA (adjusted for depth). Based on this result, we excluded recent (3-months) AM users from the main analysis. We also excluded participants with low sequence depth (n = 112) and missing background information (n = 7). For all further analysis, the study group consists of 808 children.
Similarly, the corresponding cut-offs for amoxicillin use were (< 1; 2-5; > 6), for azithromycin (0; 1-3; > 4), for phenoxymethylpenicillin (< 0; 1; > 2) and for amoxicillin-clavulanate (0; 1-2; > 3). Beta-diversity was analysed with the permutational multivariate analysis of variance test (PERMANOVA) using the adonis function in the vegan package with 999 permutations. The analysis adjusted for age, gender, language and other AMs. PERM ANOVA was run for all AMs combined and for the four most common AMs separately, as defined previously. Pairwise PERMANOVA was used for multiple comparisons between prescription groups (low-medium, low-high and medium-high) and p values were adjusted with the Benjamini-Hochberg method. The association of bacteria abundance at the operational taxonomic level (OTUs) was tested using General Linear models (GLM) with a Negative Binomial distribution, implemented in the DESeq2 package  [57]  with AM use as a continuous variable and the resulted log 2 fold change is per increment unit AM.