dataesr/scientific-paragraphs-categorization huggingface dataset:
Pneumocystis jirovecii Typing Extracted DNAs of BAL and induced sputum samples were examined for Pneumocystis genotyping based on unilocus and multilocus sequence typing (MLST) methods. Three loci, mtLSUrRNA, cytochrome b (CYB) and superoxide dismutase (SOD) genes were analyzed, as we previously described, using direct sequencing  (Vindrios et al. , 2017). Consensus sequences were aligned with reference sequences [GenBank accession numbers M58605 (mtLSUrRNA), AF074871 (CYB) and KT592355 (SOD)]  (Sinclair et al. , 1991; Walker et al. , 1998; Singh et al. , 2017)  using the BioEdit software with the Clustal R W program. MtLSUrRNA alleles were named using the nomenclature described previously by  Beard et al. (2000) , CYB and SOD alleles were named using the nomenclature described previously by  Esteves et al.
The analysis involved 33 nucleotide sequences. There were a total of 1152 positions in the final dataset. Evolutionary analyses were conducted in MEGA7. Patients and samples are identified with a letter (R for Reunionese patients, G for Guianese patients and B for Brest patients) followed by a number. patients, who were infected with cytochrome b mutant P. jirovecii organisms, were effectively subjected to atovaquone prophylaxis in a context of hematological malignancy (myeloma for one patient, and T-cell acute lymphoblastic leukemia for the other), at the time of PCP diagnosis. This observation was consistent with that we recently reported concerning the selection of cytochrome b mutants in heart transplant recipients in a context of PCP case clusters and the use of atovaquone prophylaxis  (Argy et al.
Ongoing clinical studies When the current Trial Watch was redacted the ClinicalTrials. gov database (http://www. clinicaltrials. gov/) listed no less than 103 clinical studies that matched the following criteria: (1) they involved at least one bona fide ICD-inducing chemotherapeutic agent; (2) they were implemented in the context of immunomonitoring; and (3) they were initiated after July 2017 (when the latest Trial Watch on this topic was published)  20  (Figure  1 , Tables  1  and 2 ). In this context, multiple immunological biomarkers (including several biomarkers of ICD) are being examined (Figure  1a , Tables  1  and 2 ), including: (1) T-cell immunoprofiling, including assessment of T cell activation, suppression, phenotype, and exhaustion, as well as the quantification of tumor-infiltrating or circulating T cells; (2) quantification of immunosuppressive ligands (e.
Combined with fludarabine and PD-L1 CAR-T cells NCT03330834 Melanoma I Recruiting Combined with fludarabine, IL-2, nivolumab and adoptive transfer of autologous TILs NCT03475134 Recruiting Combined with fludarabine, autologous TILs, aldesleukin, nivolumab and ipilimumab NCT03526185 Myeloid malignancies II Not yet recruiting Combined with multimodal chemotherapy cyclosporine, tacrolimus and HSC transplantation NCT03270748 Myeloma I Recruiting Combined with fludarabine and SLAMF7 CAR-T therapy NCT03710421 Recruiting Combined with fludarabine, gamma secretase inhibitor LY3039478, BCMA specific CAR-T cells NCT03502577 Recruiting Combined with fludarabine, BCMA CART and huCAR-T19, NCT03549442 Recruiting Combined with fludarabine and CAR-BCMA T cells NCT03716856 NA Recruiting Combined with fludarabine and CAR-BCMA T cells NCT03380039 Osteosarcoma II Recruiting Combined with fludarabine, fludarabine phosphate, aldesleukin and TILs NCT03449108 Ovarian cancer I Recruiting Combined with decitabine, aldesleukin, genetically engineered NY-ESO 1 specific T lymphocytes NCT03017131 Recruiting Combined with fludarabine and anti-meso CAR-T cells NCT03799913 II Withdrawn Combined with anti-CSF1 mAb PD-0360324 NCT02948101 Pancreatic cancer I Recruiting Combined with GVAX, pembrolizumab and IMC-CS4 NCT03153410 (Continued ).
Acknowledgments ADG is supported by  Research Foundation Flanders' (FWO) Excellence of Science (EOS)  grant ( 30837538 ) for the 'DECODE' consortium and the  KU Leuven  via the C1 grant ( C14/ 19/098 ) as well as the  POR award funds  ( POR/16/040 ). ST is supported by  Research Foundation Flanders' (FWO)  as a Senior Clinical Investigator and by the Stichting tegen Kanker. GK 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 ;  Chancelerie 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, MINOTAUR) ;  Gustave Roussy Odyssea , the  European Union   Horizon 2020 Project Oncobiome ;  Fondation Carrefour ;  Highend 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).
s. Recruiting Combined with cyclophosphamide, taxol and alpha lipoic acid NCT03908528 Lymphoma I Recruiting Combined with multimodal chemotherapy, RO7082859, NCT03467373 obinutuzumab, rituximab and tocilizumab II Not yet Combined with multimodal chemotherapy, nivolumab and rituximab NCT03749018 recruiting Neuroblastoma II Recruiting Combined with dinutuximab, sargramostim, ASCT and EBRT NCT03786783 Osteosarcoma II Not yet Combined with multimodal chemotherapy NCT03390946 recruiting Recruiting Combined with APX005M NCT03719430 Ovarian cancer II Not yet Combined with paclitaxel, gemcitabine, and pembrolizumab NCT03539328 recruiting III Recruiting Combined with carboplatin, niraparib and atezolizumab NCT03598270 Renal medullary carcinoma II Recruiting Combined with multimodal chemotherapy NCT03587662 Epirubicin Breast cancer II Recruiting Combined with nab-paclitaxel, cyclophosphamide and NCT03289819 pembrolizumab Recruiting Combined with multimodal chemotherapy and pembrolizumab NCT03515798 Not yet Combined with multimodal chemotherapy, trastuzumab, NCT03894007 recruiting pertuzumab, atezolizumab and trastuzumab Small cell lung cancer II Not yet Combined with SHR-1210 NCT03755115 recruiting Colorectal cancer I Recruiting Combined with fluorouracil, leucovorin and CYAD-101 NCT03692429 II Recruiting Combined with nivolumab, 5-fluorouracil and leucovorin NCT03388190 Active, not yet Combined with 5-fluorouracil, cetuximab and avelumab NCT03174405 recruiting Recruiting Combined with 5-fluorouracil, levoleuucovorin, bevacizumab and NCT03698461 atezolizumab Recruiting Combined with surgical resection, 5-fluorouracil, leucovorin and NCT03844750 pembrolizumab Not yet Combined with surgical resection, capecitabine and pembrolizumab NCT03984578 recruiting III Recruiting Combined with fluorouracil, leucovorin calcium and bevacizumab NCT02997228 Gastric, esophageal and/or I Recruiting Combined with surgical resection, fluorouracil and atezolizumab NCT03784326 gastroesophageal cancer I/II Withdrawn Combined with surgical resection, radiation, fluorouracil and NCT03307941 monalizumab II Not yet Combined with capecitabine NCT03764553 Recruiting II Recruiting Combined with multimodal chemotherapy and atezolizumab NCT03421288 Recruiting Combined with fluorouracil, leucovorin and zolbetuximab NCT03505320 Recruiting Combined with fluorouracil, leucovorin, nivolumab and trastuzumab NCT03409848 II Recruiting Combined with fluorouracil, leucovorin and pembrolizumab NCT03488667 Gastrointestinal neoplasms I/II Recruiting Combined with capecitabine and IMU-131 NCT02795988 Lymphoma I Recruiting Combined with gemcitabine, atezolizumab and rituximab NCT03321643 II/III Recruiting Combined with gemcitabine, nivolumab and rituximab NCT03366272 Pancreatic cancer III Recruiting Combined with multimodal chemotherapy and anti-PDCD1 antibody NCT03977272 Recruiting Combined with multimodal chemotherapy and anti-PDCD1 antibody NCT03983057 ASCT, Autologous hematopoietic stem cell transplantation; CAR, chimeric antigen receptor; EBRT, external beam radiation therapy; NS, not specified.
s Recruiting Combined with cord blood transplantation NCT03802773 Leukemia I Recruiting NCT03241940 Recruiting Combined with fludarabine phosphate and CD19/CD22 CAR-T cell therapy NCT03233854 Not yet Combined with fludarabine, CD19 CAR-T cells and PD-1 KO engineered T cells NCT03298828 recruiting Recruiting Combined with tacrolimus, allogeneic HSC transplantation, filgrastim and total marrow irradiation NCT03467386 Recruiting Combined with fludarabine and omnlmmune NCT03790072 Recruiting Combined with leukapheresis, fludarabine and huJCAR014 NCT03103971 Recruiting Combined with fludarabine and anti-CD19/CD22 CAR-T cells NCT03919526 I/II Recruiting Combined with fludarabine and KTE-X19 NCT03624036 III Recruiting Combined with multimodal chemotherapy, TBRT, G-CSF and peripheral blood transplant NCT03480360 NA Recruiting Combined with multimodal chemotherapy, thymoglobuline, cyclosporine, lymphocyte injection of NCT03035422 prophylactic donor and transfusion graft of peripheral stem cells Liver cancer I Recruiting Combined with nivolumab and IRX-2 NCT03655002 Active, not Combined with fludarabine and GAP-T cells NCT02932956 recruiting I/II Recruiting Combined with IMA970A and CV8102 NCT03203005 Recruiting Combined with fludarabine and MUC-1 CAR-T cells NCT03633773 II/III Recruiting Combined with iNKT cells and human recombinant IL-2 NCT04011033 Lung cancer I Recruiting Combined with radiation, G-CSF and PBMCs NCT02579005 Not yet recruiting.
Indication(s) Phase Status Notes Ref. Prostate cancer I Recruiting Combined with fludarabine, fludarabine phosphate and autologous anti-PSCA-CAR-T-cells NCT03873805 Sarcoma II Withdrawn Combined with pembrolizumab, GSK3377794 and fludarabine NCT03697824 Solid and I/II Recruiting Combined with CAR-T cell therapy NCT03638206 hematological malignancies Solid malignancies I Withdrawn Combined with GM-CSF and TAPA-pulsed DC vaccine NCT02705703 Recruiting Combined with RT, aspirin, nivolumab and ipilimumab NCT03728179 I/II Recruiting Combined with fludarabine and PD-1 expressing mesoCAR-T cells NCT03615313 Active, not Combined with imiquimod topical cream and TAPA-pulsed DC vaccine NCT02224599 recruiting II Recruiting Combined with pembrolizumab and DPX-survivax NCT03836352 ALLO, allogeneic;.
The CUORE detector is now operational and has been taking science data since Spring 2017. With the first ∼3 weeks of collected data, we present here the most stringent constraint on the 130 Te half-live for the neutrino-less double beta decay. Neutrinoless double-beta decay (ββ(0ν)), is a very rare process in which a nucleus with mass number A and charge Z undergoes the decay (A, Z) → (A, Z + 2) + 2e -in which no neutrino is emitted. Assuming that the process is mediated by the exchange of a light neutrino, ββ(0ν) provides the most sensitive test of the Majorana nature of neutrinos  [1]. While the corresponding two-neutrino double-beta decay (ββ(2ν) ) has been observed for several nuclides  [2] , the observation of ββ(0ν) would provide direct evidence for lepton number violation implying the existence of new physics beyond the Standard Model.
The initial two months were dedicated to the system optimization and setting of the optimal working points. In April 2017 the optimization phase was not yet complete but CUORE was eventually ready for a preliminary science run. The data presented here are from a three week-long dataset collected in May 2017 and corresponding to an exposure of 38. 1 kg•yr of TeO 2 or 10. 6 kg•yr of 130 TeO 2. Main goal of this preliminary physics run was to provide preliminary information on the parameters that most strongly affect the ββ(0ν) sensitivity: the energy resolution and the Background Index (BI) in the ββ(0ν) Region Of Interest (ROI). Physics data were preceded and followed by calibration periods during which 12 Kevlar strings populated with low-intensity 232 Th sources were temporarily deployed (from room temperature across the cryogenic volume) inside the detector region in order to guarantee an approximately uniform γ-ray illumination of the detectors  [9].
Main goal of the closing calibration is to verify the stability of the detector response over the dataset. A total of 984 of 988 detectors are functioning. Each CUORE detector is equipped with  a neutron-transmutation-doped (NTD) thermistor  [10] , and a silicon heater  [11, 12]. During data collection, the voltage across each thermistor is amplified and filtered  [13]  and continuously digitized with a sampling rate of 1 kHz. A software derivative trigger with channel-dependent thresholds ranging from 20 to a few hundred keV is applied to identify thermal pulses. The efficiency of the trigger is evaluated as the fraction of tagged heater pulses that produce an event trigger. The rise and fall times of thermal pulses are on the order of 100 ms and 400 ms, respectively. A 5-s window, consisting of 1 s before and 4 s after each trigger, is separately analyzed for each triggered pulse.
In particular, the model is the same used for CUORE-0  [16]  and is composed of a posited ββ(0ν) decay peak, a peak for 60 Co coincident γ rays (1173 and 1332 keV), and a flat background. Each peak in the ROI is modeled using the calibration line shape discussed above, with the line width scaled by the resolution scaling parameter extrapolated to the peak energy. All detectors are constrained to have the same ββ(0ν) decay rate Γ 0ν , which we allow to vary freely in the fit; the position of the ββ(0ν) decay peak is fixed to the reconstructed energy of Q ββ for each bolometer-dataset. The 60 Co peak mean and rate, as well as the flat background rate are free parameters in the fit. Fig. 4  shows the spectrum of candidate events in the ββ(0ν) ROI after unblinding, together with the result of the UEML fit.
When using the phase-space factors from  [29]  and nuclear matrix elements from a broad range of recent calculation models  [30, 31, 32, 33, 34]  with the nucleon axial coupling constant g A 1. 27 we get m ββ < (210-590) meV at 90% C. L. , depending on the nuclear matrix element estimates employed. In summary, we find no evidence for ββ(0ν) decay of 130 Te and place the most stringent limit to date on the half-life for this decay. We anticipate additional optimization campaigns during 2017 to improve the detector performance by optimizing our experimental operating conditions and analysis tools. Note added in proof: a new science run was carried out during August 2017. The corresponding dataset as well as the one described in this paper were completely re-processed with a slightly improved analysis procedure.
the detector. We thank  Danielle Speller  for contributions to detector calibration, data analysis, and discussion of the manuscript. We thank  Giorgio Frossati  for his crucial support in the commissioning of the dilution unit. This work was supported by the  Istituto Nazionale di Fisica Nucleare (INFN) ; the  National Science Foundation  under Grant Nos. NSF-PHY-0605119 ,  NSF-PHY-0500337 ,  NSF-PHY-0855314 ,  NSF-PHY-0902171 ,  NSF-PHY-0969852 ,  NSF-PHY-1307204 , and  NSF-PHY-1404205 ; the  Alfred P. Sloan Foundation ; and  Yale University. This material is also based upon work supported by the  US Department of Energy (DOE) Office of Science  under Contract Nos. DE-AC02-05CH11231  and  DE-AC52-07NA27344 ; and by the  DOE Office of Science, Office of Nuclear Physics  under Contract Nos.
The Y-axis shows transcripts per TPM. The X-axis shows time of sampling as weeks after sowing. Whiskers represent distance from the lowest to the largest data point. (A) Leaf number at flowering of plants grown under LDs. Twelve plants were analyzed per genotype. The data were compared with one-way ANOVA using Tukey's honest significant difference as a post-hoc test. Different letters indicate significant differences (P # 0. 05). Whiskers represent the distance of 1. 5 times the interquartile range. The qem2 mutant was later flowering and initiated more rosette and cauline leaves than the quintuple mutant (Figures  2A  and 2B ), indicating a delay in the floral transition and impaired floral meristem identity. The region of chromosome 5 to which qem2 mapped contained no previously described flowering-time genes (Figure  2C ; Table  1 ).
At 5 weeks after germination, no AP1 expression was detected in any of the genotypes, indicating that the plant meristems were still vegetative. AP1 mRNA was detected at 6 weeks in Col-0 and chr4-2. In qem2 mutants, AP1 mRNA appeared more than 1 week later than in the quintuple mutant, which is consistent with observation that more cauline leaves formed in qem2 (Figure  4 ). We then performed RNA-seq along a developmental time course to identify the genome-wide effects of CHR4 on gene expression during the floral transition. We examined the transcriptomes of shoot apices of Col-0, the quintuple mutant, chr4-2, and qem2 plants grown for 3, 4, 5, or 6 weeks under SDs and compared the chr4-2 and qem2 transcriptomes to those of Col-0 and the quintuple mutant, respectively (Supplemental Data Set 2).
To identify protein interactors, we immunoprecipitated CHR4-VENUS protein from inflorescence tissue and 5-week-old SD apical-enriched tissue using anti-GFP antibodies and used p35S-YFP transgenic plants as a negative control. Proteins that specifically co-immunoprecipitated with CHR4-VENUS were identified by protein mass spectrometry (MS; see Methods). In total, 136 and 342 proteins were significantly (false discovery rate, FDR 5 0. 01) enriched in inflorescences and 5-week-old SD apex enriched tissue, respectively. The CHR4-interacting proteins in inflorescences included the floral homeotic MADSdomain transcription factors AP1, SEP3, PI, and AP3 (Table  2 ; Supplemental Data Set 3). The reciprocal experiment of immunoprecipitating AP1 was performed with gAP1:GFP plants and CHR4 was detected among the coimmunoprecipitated proteins (Supplemental Data Set 3 and Supplemental Figure  7 ).
Homozygous mutant plants were selected by PCR using specific primers (Supplemental Data Set 5). Seeds were immersed in 0. 1% melt universal agarose (Bio-Budget Technologies) for 3 d at 4°C in darkness for stratification. Plants were grown in soil under controlled conditions of LDs (16-h light/8-h dark) and SDs (8-h light/16-h dark) at 21°C or 27°C. The light intensity was 150 mmol$m 22 $s 21 under all conditions. The growth-chamber is equipped with fluorescent tube bulbs (F17T8/TL841 ALTO-T8; Philips) to supply wavelengths from 430 to 650 nm, and supplemented with LEDs to provide light in the far-red spectrum. As a proxy for flowering time, the number of rosette and cauline leaves on the main shoot was counted as well as the number of days to bolting and first flower opening.
One leaf sample of each selected plant was harvested and pooled. Leaf material from the quintuple plants was also harvested as a control. Genomic DNA was extracted from both pools and sent for Illumina sequencing with a depth of ;80-fold coverage. Reads were aligned to The Arabidopsis Information Resource (TAIR10) reference genome (ftp://ftp. arabidopsis. org/home/tair) using the software tool SHORE  (Schneeberger et al. , 2009). The program SHOREmap  (Schneeberger et al. , 2009; Sun and Schneeberger, 2015)  was used to identify polymorphisms, and those present in ;100% of reads in the identified mutant but absent from the progenitor were identified as candidates for the causal mutation.
RNA Extraction and RNA-Seq Analysis Total RNA was extracted from 15 shoot apices after removing all visible leaves under a binocular for each of the three independent biological replicates using an RNeasy Plant Mini Kit (Qiagen) and treated with DNase (Ambion) to remove residual genomic DNA. Library for sequencing was prepared using a TruSeq Library Preparation Kit (Illumina) according to the manufacturer's protocol. Sequencing was performed using the HiSeq 3000 platform (Illumina) in 150-bp single reads. For each sample, ;15,000,000 reads were generated. The software tool FastQC was used to assess quality control parameters (https://www. bioinformatics. babraham. ac. uk/projects/ fastqc/). To estimate expression levels, the RNA-seq reads were mapped to the Arabidopsis TAIR10  (Lamesch et al.
, 2012)  reference genome using the software TopHat2 under default settings  (Kim et al. , 2013) , except that only a single alignment was permitted per read and the coverage-based junction search was disabled (settings: 2g 1 -no-coverage-search). The program Samtools was used to sort and index BAM alignment files and to calculate BAM file statistics  (Li et al. , 2009). The software HTSeq was used to tabulate the number of reads mapping to each genomic feature, with counts tabulated only for genes that completely overlapped a given feature  (Anders et al. , 2015). We used the Wald test implemented in the program DESeq2 (https://bioconductor. org/packages/release/bioc/html/DESeq2. html) to detect DEGs for pair-wised comparison. To visualize the expression levels of candidate genes, the expression level for each gene was calculated as transcripts per million (TPM).
, 2009)  with default parameters. Clonal reads were removed using a customized Python (https://www. python. org/) script. Reproducibility between biological replicates was assessed using the Spearman correlation for the genome-wide read distribution at each pair of replicates using the software deepTools  (Ramírez et al. , 2014). The "multiBamSummary" function was used with default parameters except for "bin size," which was set to 1 kb and the "plotCorrelation" function of deepTools2 in Galaxy (http://deeptools. ie-freiburg. mpg. de/; Supplemental Figure  9 ). H3K27me3-and H3K4me3-modified regions were identified with the tool DANPOS2  (Chen et al. , 2013). The "Dpeak" function in DANPOS2 was used with default parameters, except for the parameter 2l (read extension length), which was set to 300 bp, the mean size of the DNA in the samples after sonification.
Data Analysis Raw data were processed using MaxQuant software (v1. 5. 7. 4, http://www. maxquant. org/; Cox and Mann, 2008)  with label-free quantification (LFQ) and Intensity Based Absolute Quantification enabled  (Tyanova et al. , 2016). MS/MS spectra were searched by the Andromeda search engine against a combined database containing Arabidopsis sequences (TAIR10_pep_ 20101214; ftp://ftp. arabidopsis. org/home/tair/Proteins/_TAIR10_protein_ lists/) and sequences of 248 common contaminant proteins and decoy sequences. Trypsin specificity was required and a maximum of two missed cleavages allowed. Minimal peptide length was set to seven amino acids. Carbamidomethylation of Cys residues was set as "fixed" and oxidation of Met and protein N-terminal acetylation as "variable" modifications. Peptide-spectrum matches and proteins were retained if they were below an FDR of 1%.
Statistical analysis of the MaxLFQ values was performed using the program Perseus (v1. 5. 8. 5, http://www. maxquant. org/). Quantified proteins were filtered for reverse hits and hits "identified by site," and MaxLFQ values were log 2 -transformed. After grouping the samples by condition, only proteins that had two valid values in one of the conditions were retained for subsequent analysis. Two-sample t tests were performed with a permutation-based FDR of 5%. Alternatively, quantified proteins were grouped by condition and only hits that had three valid values in one of the conditions were retained. Missing values were imputed from a normal distribution (0. 3 width, 2. 0 downshift, separately for each column). Volcano plots were generated in Perseus using an FDR of 1% and an S0 5 1. The Perseus output was exported and further processed using Microsoft Excel.