dataesr/scientific-paragraphs-categorization huggingface dataset:
Signature scores were computed using the Seurat function "AddModuleScore" using default parameters. ATAC-seq. Chromatin profiling was performed by ATAC-seq as described in Buenrostro et al. 37. In brief, 50,000 cells per sample were washed in cold PBS and lysed. Transposition reaction was performed at 37 °C for 30 min and DNA was purified with MinElute PCR purification kit (Qiagen). Transposed DNA was amplified for 5 cycles and additional PCR cycles were evaluated by real-time PCR. Libraries were sequenced on Novaseq 6000 using 1xSp-Flow Cell (Illumina). A total of 130-210 × 10 6 paired reads were generated per sample. ATAC-seq data analysis. (1) Alignment, peak calling, and visualization: ATAC-Seq sequencing reads were aligned to the mouse reference genome mm10 using BWAMEM (bwa-0. 7. 15, opt -k 19 -T 30 -M).
Only properly paired uniquely mapped reads were kept for further analysis (samtools -f 0 × 2 -q 30). Peaks were called using MACS2 v2. 1. 2 with default parameters and a 5% FDR threshold. ATAC-seq signal tracks were generated using bamCoverage (deeptools-v2. 5. 3, -binSize 10 -normalizeUsing BPM), and visualized in Integrative Genomics Viewer (IGV) software. (2) Comparison between conditions: Two strategies of peak calling were performed: (1) to detect individual peaks in each separate condition, peaks were called on merged replicates versus genome background; (2) to detect modulated peaks between conditions, peaks were called on merged replicates using 1 condition as treatment and another as control; further analysis on modulated peaks were filtered either by (1) only real peaks identified above by the peak caller, (2) fold-enrichment ≥ =2, or (3) uniquely identified in treatment condition during individual peak calling.
(3) Signature enrichment analysis: ATAC peaks were annotated using HOMER::annotatePeaks to nearest TSS gene. Signature enrichment analysis was applied on selected signatures using hypergeometric test alternative greater and BH adjusted p-value < 0. 01. Transcription factor motif enrichment was used to identify transcriptional programs associated with the epigenetic changes. Statistical analysis. Data are given as mean ± s. e. m. Prism software (Graphpad Software, Inc. ) was used to perform statistical analysis. Two-tailed Mann-Whitney test was used to compare groups statistically. Long-rank (Mantel-Cox) test was performed for statistical analysis of survival study. A p value lower than 0. 05 (*p < 0. 05) was considered as threshold for statistical significance among control groups and experimental groups.
Acknowledgements We thank  Virginie Dangles-Marie ,  Celine Daviaud ,  Isabelle Grandjean ,  Mikael Garcial , and  Cedric Pauchard , the mouse facility technicians and flow cytometry core at  Institut Curie. We acknowledge  Dr. Ana Lalanne  for the help with tetramer staining. We thank  Nathalie Amzallag  for technical assistance. This work was supported by the  ANR-14-CE16-009  ( Programme ANR Innovation biomedical   DS0404 ,  2014 ),  Institut National de la Santé et de la Recherche Médicale ,  Labex DCBIOL  ( ANR-10-IDEX-0001-02 PSL  and  ANR-11-LABX0043 ),  SIRIC INCa-DGOS-Inserm_12554. L. L. N. was supported by  ANR-14-CE16-009  ( Programme ANR Innovation biomedical   DS0404 , 2014). P. C. was supported by a fellowship from the  International Ph. D. program  of  Institut Curie. P. G. was supported by a Ph.
In k and m, the data are donor matched from n = 9 and n = 4 donors. Exact p-values are indicated and determined with two-(g) or onetailed (m) unpaired Mann-Whitney test, the Kolmogorov-Smirnov test (j), a twotailed paired Wilcoxon test (k), and a two-tailed unpaired t test (n). Source data are provided as a Source Data file.
Source data are provided as a Source Data file. spleen and the BM of treated mice showed, respectively, that Phago + MDMs exhibited decreased membrane expression of the scavenger receptor CD163 (compared with Phago -MDMs, Fig. 4b ) and highly expressed iNOS (Fig. 4c ). These results confirmed that in vivo, phagocytosis of leukemia cells promoted the activation of MDMs toward a proinflammatory phenotype. In contrast to MDMs sorted from tumor-free NSG mice infused with Co. TD-Mos or p21TD-Mos (Fig. 4d ), Phago -MDMs sorted from mCherry + MOLT4 cell-engrafted NSG mice injected with p21TD-Mos exhibited a significant increase in iNOS expression on d 35 (Fig. 4e ), suggesting that Phago + MDMs can support the proinflammatory reprogramming of surrounding TAMs in the TME. To test this hypothesis, FACS-sorted Phago -and Phago + MDMs from Co.
The control MOLT4 cell line (CrCo. MOLT4) was obtained by transduction with the empty eSpCas9-LentiCRISPRv2 vector. The shRNA targeting the 3' untranslated region of p21 (sh3'UTRp21 CGCTCTACATCTTCTGCCTTA) cloned into the pLKO. 1 lentiviral vector was predesigned and validated by Sigma MISSION (#TRCN0000287021). The SIRPA 2 promoter sequence (EP026655) identified by the Eukaryotic Promoter Database (EPD) to be expressed in human primary Mos and macrophages was fused to a luciferase (Luc) reporter gene and cloned into the pRRL-EF1-PGK-GFP lentivirus after the insertion of three stop codons at the 3' end of the E2F1 promoter. The initiator motif of the SIRPA 2 promoter is present at -530 bp before the transcription start site (TSS) of the SIRPα gene. Control (AIP, RRL-EF1-PGK-GFP, eSpCas9-LentiCRISPRv2 and LKO.
1 × 10 6 each) were cultured in MM supplemented with 10% HI FBS for 96 h. The mean pixel densities of analyzed cytokines were determined with Gene tools from Syngene software version 4. 02. 03 (Syngene). For quantification of human IFNγ secretion into the cell supernatants of Phago + MDMs and Phago -MDMs by Quantikine ELISA (RD, #DIF50C) (according to the manufacturer's instructions), the degradation of internalized cells was assessed at 96 h and after extensive washing, fresh medium was added to the MDMs for up to 7 d for quantification. For WB analysis, Phago + MDMs and Phago -MDMs were cultured for 7 d. For the study of bystander activation of macrophages, 2 h after FACS sorting, Phago - MDMs (0. 1 × 10 6 in 1 ml of MM supplemented with 10% HI FBS) were allowed to adhere to the bottom chambers of 24-well plates; Phago - MDMs or Phago + MDMs (0.
Gene expression Determination of p21 and SIRPα mRNA levels by RT-qPCR was performed as we previously described  17, 53  using predesigned TaqMan gene expression probes for SIRPα (Hs00757426 S1), p21 (Hs00355782 m1) and GAPDH (Hs02758991 g1). The RT-qPCR data were analyzed with qPCR CFX Maestro Version 4. 0. 2325. 0418. (Biorad). Gene expression analysis of Phago -MDMs and Phago + MDMs was performed with an Agilent® SurePrint G3 Human GE 8x60K Microarray (Agilent Technologies, AMADID 28004) using Microarray images Extraction software version (10. 7. 3. 1) (Agilent Technologies) and Microarray raw intensities limma package for R v2. 13. 0 software (Agilent Technologies), with two technical replicates for each sample. Data were generated with each analyzed donor by determining the mean of two technical replicates of the Log2-fold change (FC) in the gene intensity ratio of Phago + MDMs/ Phago -MDMs to produce a comprehensive analysis of modulated genes known for their ability to regulate anti-inflammatory or proinflammatory macrophage activation (Supplementary Data 1).
Acknowledgements We gratefully acknowledge  D. M. Ojcius  for helpful scientific discussions,  NH Theraguix  for supporting our projects against cancer, and  M. Morabito  and  L. Bencheikh  for their technical support. This work benefited from the facilities and expertise of the Imaging and  Cytometry Platform  ( S. Salome-Desnoulez  and  T. Manoliu ),  Genomic and Bioinformatic Platforms  ( N. Droin  and  G. Meurice ) and  UMS   3655 CNRS / US 23   INSERM (Gustave Roussy Cancer Campus Villejuif, France). This work was supported by funds from the  Agence Nationale de la Recherche  ( ANR-10-IBHU-0001 ,  ANR-10-LABX33 ,  ANR-11-IDEX-003-01  and  ANR  Flash  COVID-19 "MacCOV "), the  Fondation ARC pour la recherche le cancer  (www. fondation-arc. org),the  Fondation de France , the  Fondation Gustave Roussy , the  Institut National du Cancer  ( INCa 9414  and  INCa   16087 ), the  SIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination (SOCRATE) , the  Care network  (directed by  X.
Data availability Source data are provided with this paper. The microarray gene expression data of the modulated genes in phagocytic macrophages with respect to nonphagocytic macrophages are provided in Fig. 1j , Supplementary Data 1 and Source Data file. The microarray gene expression large dataset is available in ArrayExpress repository under the access code E-MTAB-12280. The SIRPA 2 promoter sequence (EP026655) is available in the Eukaryotic Promoter Database (EPD) (https://epd. epfl. ch//index. php). The remaining data generated in this study are provided in the Article, Supplementary Information or Source Data file. Source data are provided with this paper.
Photopatterning and protein functionalization of EM grids Following PLL-g-PEG incubation, excess PBS was removed from the well containing the grid, with enough remaining to keep the sample hydrated. 15 µL of UV sensitive photo initiator (PLPP, Alvéole, Paris, France) was added to the well and the sample was placed on the stage of a Leica DMi8 epifluorescence microscope equipped with a Fluotar 20x/0. 40 N. A. objective and the Alvéole Primo photopatterning system (Alvéole, Paris, France). Digital masks for ECM patterns were made using the open-source software program Inkscape  54  , which were loaded onto the Leonardo plugin (Alvéole Laboratory) on μManager software  55. The pixel/µm ratio generated by Primo calibration was used to define the geometries of ECM patterns. For each grid, a single mask consisting of a 10 × 10 array of hollow square micropatterns (50 × 50 µm or 66.
2, ATCC CRL-2936). IF was conducted according to standard protocols with a dilution of 1 µg/ml. Both WB and IF were done using an antibody against alpha catenin (mouse monoclonal antibody against alpha catenin 15D9, AM00014PU-N, OriGene Technologies Inc. ; kindly provided by Nelson's group). Preparation of micropatterned grids, cell plating, and titration for cryo-ET Micropatterned grids were rinsed once in sterile 1x PBS and screened for integrity and quality of patterns on an inverted light microscope (Eclipse TE 2000-U, Nikon) equipped with manual controlled shutter, filter wheels, and a 14 bit cooled CCD camera (Orca II) controlled by MetaMorph software (Universal Imaging), using a Plan Fluor ELWD 40/ 0. 60 Ph2 or a Plan Fluor 10/0. 30 Ph1 objective lens (Nikon). Alternatively, micropatterned grids were imaged using a Spinning Disk (CSUX M1-L, Solamere) attached to a standard fluorescence widefield inverted microscope (Axio Observer 7, Zeiss).
1 M Pipes, 1 mM EGTA and 1 mM MgSo4). The initial 5 min were at room temperature, while the remaining 25 min were carried out over ice. After 30 min of incubation, the fixative solution was removed, and grids were gently rinsed three times in cold complete PHEM buffer (60 mM Pipes, 25 mM HEPES, 2 mM MgSo 4 , 10 mM EGTA, pH 6. 9)  59, 60. The light microscopy information, collected on the inverted microscope set up described above was used to improve the precision of selecting regions of interest for cryo-tomography data collection. For observation, each grid was flipped (cells face down) and placed in a MatTek dish in presence of PHEM. Areas of interest were identified, their positions recorded and phase contrast, fluorescence images were collected. Upon completion of this survey, grids were plunge frozen.
Cryo-FIB Lamella preparation Grids were clipped using special Autogrids containing a milling slot (ThermoFisher). The milling slot allowed the access of the gallium beam at shallow angles appropriate for the cryo-lamellae preparation. Autogrids were transferred to the Aquilos 2 (ThermoFisher) dual beam cryo-FIB instrument. Cryogenic lamellae sites were chosen based on the cell-cell contact area observed by the scanning electron microscope (SEM) beam of the Aquilos 2 and correlated with the imaging obtained from the DM6 cryo-Light microscope (Leica Microsystems). Fluorescence images were aligned with the SEM tile set file using MAPS 3. 14 software (ThermoFisher). A total of 15 cryo-lamellae were prepared using the semi-automated software AutoTEM 2. 2. 0 (ThermoFisher) for rough milling and the manual interface (XT User v20.
Tomographic reconstruction, volume processing, and segmentation Tomographic reconstructions were calculated automatically during data collection as implemented in the pyCoAn package (github. com/pyCoAn/distro), an extended python version of the CoAn package. Briefly, immediately after acquisition, tilt series were automatically aligned and then reconstructed using the Simultaneous Iterative reconstruction technique. Alignment and reconstruction statistics were used to determine quality scores that are provided in real time during data collection. All interpretable reconstructions were enhanced using a Wiener-like filter accounting for the contrast transfer function at the respective defocus and an estimate of the spectral signal-to-noise ratio  62. Segmentation of the features in the reconstructions was achieved using manual tracing of membranes with Amira 63 combined with fully automated and semiautomatic  64, 65  segmentation approaches as implemented in pyCoAn.
Acknowledgements This work was supported  National Institutes of Health  grants  R01 GM119948  (N. V. , D. H. , and B. L. P. ),  NSF   CMMI-183476  (B. L. P. ) and seeding funding from  UCSB CNSI. KL was supported by  NSF   GRFP  and  UCSB  fellowship funding. LPD acknowledges useful conversations with  Dr. Leeya Engel  ( Stanford University ). G. G. and D. H. thank the  Nelson lab  for their generous gift of the pEGFP-C1-ACAT plasmid and  Dr. Kathleen A Siemers  for helping with the plasmid, characterization work, and for providing the anti-alpha catenin antibody used in the immunofluorescence experiments. The authors acknowledge the use of the  Nanostructures Cleanroom Facility and Microfluidics Lab  within the  California NanoSystems Institute , supported by the  University of California, Santa Barbara  and the  University of California, Office of the President.
The authors acknowledge the use of the Titan Krios,  Tecnai Spirit   T12  and auxiliary equipment at the cryo-EM unit of the  Sanford Burnham Prebys Medical Discovery Institute , which was created in part with the support of  US National Institutes of Health  Grant  S10-OD012372  (D. H. ) and Pew Charitable Trust 864K625 innovation award funds (D. H. ). The authors acknowledge access to the  Titan Krios, Glacios , and Aquilos-2 instruments at the  NanoImaging Core of the Institut Pasteur. The NanoImaging Core at Institut Pasteur  was created with the help of a grant from the  French Government 's  Investissements d'Avenir program  ( EQUIPEX CACSICE -Centre d'analyse de systèmes complexes dans les environnements complexes ,  ANR-11-EQPX-0008 ).
Part icipant s Thirty-five healthy adults (12 males, 23 females; ages 18-45, 24. 4±6. 2 years) were recruited as volunteers, and compensated for their time at a rate of 10 EUR/hour. Only data from N=19 participants were available for some of the analyses, due to incomplete questionnaire inputs. Recruitment was done via local adverts, with no particular specification of musical background. Participants declared to have no difficulties in hearing , and gave informed consent to participate.
For instance, we modelled the presentation of the seven chords with one long event lasting for 7 TRs irrespective of condition (P or I), to emphasise that our event of interest lies in the imagine epoch. We used the SPM hemodynamic response function (as part of the glm module of Nilearn), with dispersion and derivative, and modelled the drift using the discrete cosine transform outputs of fMRIPrep. Nuisance regressors were loaded from fMRIPrep's outputs using load_confounds (https://github. com/SIMEXP/load_confounds). These included the following time series: motion parameters with derivatives and squared derivatives, drift modelled by discrete cosine transform, white matter and CSF signal, as well as the time series of noisy components estimated by ICA AROMA  (Pruim et al. , 2015). A single GLM was estimated by modeling all four runs together, and we used the obtained regressors of interest to compute contrasts estimating differences due to harmonic function (Tonic vs.
4 Decoding models We trained decoding models  (Varoquaux & Poldrack, 2019)  to dissociate brain activity according to sets of experimentally defined labels, thereby using neural signals to distinguish (predict) the associated experimental conditions and stimulus categories. Below, we describe decoding models defined with all subjects' data in voxels from separate ROIs. In the Supplementary Methods, we also present subject-wise analyses performed on the wholebrain, akin to a searchlight, using spatial regularisation and clustering to reduce the number of features. The inputs (training data) for decoding models were obtained from the subject-wise, run-wise beta maps for each stimulus presentation, by selecting voxels in each ROI separately, after applying a 5 mm FWHM spatial smoothing. As the ROIs comprised relatively large areas, i.
Whenever models were defined using either P or I (a and b labels above), we also tested a cross-modal setup, in which the model trained on P data was tested for its performance on I, and vice-versa. In addition, as HarmonicFn was of primary interest, we also investigated to what extent decoding mistakes originated there, using contingency matrices that display HarmonicFn as ground-truth, and Key as predictor (cf Figure  6 ). For each setting, chance level was estimated using the "dummy" classifier as implemented in the "Decoder" method, which estimates chance level according to the distribution of labels in each class of the training sets (corresponding to the "stratified" strategy in sklearn: https://scikitlearn. org/stable/modules/generated/sklearn. dummy. DummyClassifier. html). Estimated chance levels were 48.
5 Representational Similarity Analysis We use RSA to check which representational geometries arise when brain data map onto chord-and phrase-level harmonic representations (harmonic function and key respectively). Rather than compare brains and models at the level of activity patterns (as with decoding), with RSA we compare representations at the level of representational dissimilarity matrices (RDMs;  Kriegeskorte & Kievit, 2013). RSA is performed in two steps: participant-level estimation of empirical (in our case: fMRI-based neural) RDMs; and group-level estimation of model fit, with theoretical RDMs. Theoretical RDMs are based on stimulus categories and experimental conditions, reflecting our hypotheses. Namely, theoretical RDMs allow a useful characterisation of the representational geometry corresponding to the tonic or dominant targets chosen here to reflect predictive scenarios accruing during a musical cadence.
The higher-bounds of the noise ceiling were above a cosine similarity of 0. 2 for all ROIs. The highest higher-bound was 0. 3, for right STG; and the lowest lower-bound was 0. 02, for left SMA. We used one-sample t-tests to compare each model performance to 0, and test whether models are below the lower-bound estimate of the noise ceiling, with Bonferroni correction for multiple comparisons. In all ROIs, none of the models was significantly below the lower bound of the noise ceiling. Model comparisons were performed using post-hoc pairwise tests, corrected using the False Discovery Rate (FDR, p < 0. 01, 6 model-pair comparisons). All RSA model estimations (with statistical tests implemented by model inference functions, detailed in the Supplementary methods), comparisons and visualisations were done using pyRSA (https://github.
Fungal isolation from microalgal biomass To isolate fungal strains, P. lima PL4V biomass was inoculated on several liquid and solid culture media  (ME, DC, MEA and DCA media). Fungal growth at 27 C was visually evaluated every day. When fungal colonies were observed, each colony was further collected and inoculated on DCA medium for storage and morphological identification based on macroscopic and microscopic features. The MMS1589 strain was further identified based on molecular biology information (ITS and β-tubulin sequencing) according to previously published protocol  (Rédou et al. , 2015). The ITS and β-tubulin sequences for the strain MMS1589 were deposited in GenBank under accession numbers MN134000. 1 and MN164633. 1, respectively.
Mass detection was set between m/z 100 and 1000 with fast switching between positive and negative ionization mode (PI and NI), the resolution of the mass spectrometer is 9200 (at m/ z 500). In the sequences, samples and extracts of axenic nutrient medium were injected randomly using a dedicated Excel macro  (Bertrand et al. , 2013) , while MeOH blanks and QC samples were injected every 15 samples. The QC sample was prepared by mixing 30 μl of all samples together. Using the same LC-HRMS method, an OA standard (Diagnostic Chemicals Limited, Charlottetown, CA USA) was injected at 10 ng/ml and was detected in positive ionization at retention time (t R ) 14. 6 min as 827. 463 [M + Na] + (main ion). The DTX-1 was detected at t R 17. 1 min as m/z = 841. 473 [M + Na] +. All data were deposited in Zenodo (http:// doi.
Data analysis LC-HRMS data were exported as CDF files using LC Solution (Shimadzu) to allow automatic peak picking using MZmine 2 as described thereafter  (Pluskal et al. , 2010). Briefly, mass detection was performed using a centroid algorithm with a noise level of 15,000 arbitrary abundance units (AU), derived from visual inspection of data. Chromatogram building used a minimum time span of 0. 03 min, group intensity threshold of 100,000 AU, again a minimal of intensity of 15,000 AU and m/z tolerance of 30 ppm  (Myers et al. , 2017). Peak deconvolution was performed using the baseline cut-off algorithm with median m/z centre calculation, and a peak duration range between 0. 05 and 10 min. Chromatograms were deisotoped with m/z tolerance of 1 mDa, retention time tolerance of 0. 1 min and maximum charge of 3.
Conidia were round in shape. Globose cleistothecia were also visible, and sci and ascospores were present next to them. Phylogenetic analyses were performed based on the genes encoding for the fungal small subunit ribosomal RNA (SSU rRNA), internal transcribed spacer 1 (ITS) and β-tubulin of MMS1589 (all sequences were deposited in GenBank: MN134000. 1 and MN164633. 1). The MMS1589 ITS partial gene had 99% of identity with the A. pseudoglaucus strain FJAT-31014 SSU rRNA (partial sequence) and the MMS1589 β-tubulin partial gene had 99% of identity with the A. pseudoglaucus benA gene for β-1 and β-2 tubulin (partial sequence). Finally, this strain was identified as A. pseudoglaucus, formerly known as Eurotium repens  (Chaigne, Bertrand, et al. , 2017; Chen, Hubka, et al. , 2017). A specific microscale marine-like environment was designed for co-culture The study of chemical interactions between P.
pseudoglaucus being more present in the extracts. Additionally, the POChEMon approach provided a global comparison between all coculture experiments using the residual information (statistical residue not represented in the mixing model) (Figure  3B ). The size of the co-culture samples (Figure  3B ) when represented was directly related to unrepresented variance in the mixing model  (Jansen et al. , 2015). The size of this residual information (unrepresented variance in the mixing model) was directly related to the amount of information within the dataset related to metabolic alteration during co-culture for each co-culture sample. Here, this provided a strategy of unsupervised comparison between the two co-culture conditions (with or without antibiotics). Clearly, in the non-treated condition, the size of residual information of the co-culture sample (statistical residue not represented in the mixing model) was larger than in treated condition (Figure  3B ), which means more chemical alteration due to co-culture in absence of antibiotics.