dataesr/scientific-paragraphs-categorization huggingface dataset:
In that respect, the French nationwide health record database Système National des Données de Santé (SNDS) recently opened to researchers is a great opportunity to carry out comprehensive health studies at the country level  [5]. Around 3,000 patients are operated on for a meningioma each year in France but only a small fraction have also been treated by PT usually for aggressive meningioma. The objective of this study was to describe and evaluate the survival of patients who received PT after meningioma surgery and search for associated prognostic factors.
MATERIALS AND METHODS We performed a cross-sectional nationwide population-based descriptive observational and analytic retrospective study. Incidental meningiomas never operated were not considered in this study; only surgically treated tumours were taken into account. Data were extracted from the SNDS, the national French medico-administrative database. Patients who underwent the surgical resection of a meningioma between the first of January 2008 and the 31 December 2017 were included. Cases were selected using an algorithm combining two variables as described previously: the type of the surgical procedure identified by the Common Classification of Medical Acts (CCAM) and the primary diagnosis according to the International Classification of Diseases (ICD-10)  [6] [7] [8] [9]. Benign meningiomas were considered as corresponding to the D32 ICD-10 code, atypical to D42 and malignant to C70.
Follow-up time was calculated by the reverse Kaplan-Meier estimator method. In essence, there is no lost to follow-up patient in the SNDS; those who died are automatically registered as such in the database. All tests were 2-sided and statistical significance was defined with an alpha level of 0. 05 (p<0. 05). Analysis was performed with both the SAS Enterprise guide version 7. 15 (SAS Institute Inc. , Cary, NC, USA), the R programming language and software environment for statistical computing and graphics (R version 4. 0. 4 [2021-02-15]; R Core Team, R Foundation for Statistical Computing, Vienna, Austria) and the survival package among others. The statistical programme and workflow was written in R Markdown v2 with RStudio for dynamic and reproducible research. This study was conducted according to the RECORD guidelines for studies conducted using routinely-collected health data and, according to the SAMPL Guidelines  [11, 12].
Strengths and limitations The strengths of the SNDS reside both in high number of patients and in exhaustive data available from every hospital in France. The database representativeness is nearly perfect, since it includes the whole country's population of nearly 68 million of inhabitants constituting one of the largest AMDB in the world  [5]. Compiled from a number of institutions, its accuracy is nonetheless limited by inconstancies in data collection and recording. Moreover, important variables such as the quality of resection are not recorded in the SNDS  [13]. Despite some limitations, the SNDS is an invaluable tool to assess meningioma outcome. It offers an incomparable means to explore associations with other pathology, medication or combine surgical treatment which has and could not be assessed before.
It is generally ac-knowledged that PT is safe, effective and recommended for many types of paediatric cancers, ocular melanomas or adult chordomas. Although some promising results have been reported, they are based on small studies. PT has been used to treat meningiomas since the early 1980s, though with outdated technologies and planning tools available at the time. However, PT technology has rather improved with modulated protons by pencil-beam scanning now available in all three centres in France since 2016. Although PT may afford higher control rates, evidence is limited to single institution series without comparison group. Thanks to the recent availability of the SNDS database, we gather the largest population of meningioma treated by PT. The paucity of similar works renders difficult our findings comparison as only a few reports examining outcome after PT for meningioma have been published (Table 6).
233 € for photons  [34]. No cost-effectiveness study of protons vs. photons has been undertaken in the treatment of meningioma nor has a study compared PFS or OS of meningioma patients after PT vs. conventional RT  [35]. Considering its cost, it seems appropriate to assess whether PT improve outcome for meningioma not to mention Lesueur et al. [25]  point of view: for skull base meningiomas, data from stereotactic series and IMRT present excellent LC with minimal side effects, thus any improvement with protons might only be marginal. The SNDS appears to be a suitable tool to answer the above-mentioned queries best after integration of more patients and extended follow-up. Using this unique database, we found that 5-year PFS and OS after meningioma surgery and PT is favourable but impaired for older patients with high level of morbidities, tumour of the convexity, malignant histopathology and for those having a hydrocephalus requiring internal CSF shunting.
Acknowledgments The authors would like to thank  Marjorie Boussac ,  Julius Kemme , and EL Mehdi GABBAS from the  CNAM  for the data extraction;  Hamid Mammar M. D. , Ph. D. Oncologie Radiothérapie Protonthérapie Institut Curie Laboratoire d'Imagerie Translationnelle en Oncologie  (LITO),  U1288   Université Paris Saclay/Inserm/Institut Curie ;  Jérôme Doyen ,  Department of Radiation Oncology, Antoine Lacassagne Cancer Centre, University of Nice-Sophia, Nice, France ;  Mrs Deborah Houston  and  Elizabeth Leeson  for their manuscript review, English proofreading, grammar and spelling check.
Mycelia of Raw reads were trimmed and aligned to the Trametes versicolor reference transcripts available at the JGI MycoCosm database (http://genome. jgi-psf. org/programs/fungi/index. jsf) using CLC Genomics Workbench v8. For mapping, the minimum length fraction was 0. 9, the minimum similarity fraction 0. 8 and the maximum number of hits for a read was set to 10. The unique and total mapped reads number for each transcript were determined, and then normalized to RPKM (Reads Per Kilobase of exon model per Million mapped reads). Intact pairs were counted as two, broken pairs as one. The complete data sets were submitted to GEO (GSE154077). The Baggerly's test included in CLC Genomic workbench was applied to the data to identify differentially regulated transcripts. In addition, Benjamini & Hochberg multiple-hypothesis testing corrections with False Discovery Rate (FDR) were used.
Comparative genomic and phylogenetic analysis A comparative genomic analysis was performed on 240 sequenced fungal genomes that belong to the clade of Agaricomycotina. This analysis has been carried out by using the Mycocosm database from the Joint Genome Institute (at the date of 16/10/2017). Fungal omega GSTs sequences have been recovered by using the peptide sequence of TvGSTO3S (Prot ID "48691 ", Type-A) and TvGSTO3C (Prot ID "60698 ", Type-B) with the Basic Local Alignment Search Tool in the JGI website (BLAST). To check the affiliation of sequences to the Omega class, the sequences were aligned with the MEGA software (version 6, CLUSTALW)  (Tamura et al. , 2013)  and the sequence identity were determined by using MatGAT software  (Campanella et al. , 2003). In comparison with the Omega class, another genomic analysis of the Xi class has been carried out with the same methodology by using the peptide sequences of TvGSTX1 (Prot ID "66368"), TvGSTX2 (Prot ID "50990" and TvGSTX3 (Prot ID "73942") as templates with the BLAST.
A phylogenetic analysis of Omega and Xi class has been performed on ten fungal genomes from various orders and that have a high number of genes coding for GSTOs. The selected sequences were aligned using the MAFFT program and a phylogenetic tree was constructed using the neighbor-joining method with the bootstrap resampling number set at 1000  (Rozewicki et al. , 2019). The phylogenetic tree was visualized using iTOL  (Letunic and Bork, 2019).
Production and purification The production in Escherichia coli (Rosetta2 DE3 pLysS strain, Novagen) and purification of the nine selected TvGSTOs (accession number in the JGI database: TvGSTO1C: 157166; TvGSTO2C: 67635; TvGSTO3C: 60698; TvGSTO1S: Tv75639; TvGSTO2S: Tv56280; TvGSTO3S: Tv48691; TvGSTO4S: Tv65402; TvGSTO5S: Tv54358 and TvGSTO6S: Tv23671) were performed as explained previously  (Deroy et al. , 2015).
2 M ammonium sulfate. Crystals of TvGSTO2C-naringenin and TvGSTO2C-oxyresveratrol complexes were prepared by the 'dry soaking method' as explained previously  (Perrot et al. , 2018; Schwartz et al. , 2018). Briefly, 0. 1 µL of ligand (100 mM in DMSO) was used to coat each well of the plate and left to complete evaporation. Then, one TvGSTO2C crystal together with 1 µL of its mother liquor was dispensed on the dried ligand. After incubation (10 hours for oxyresveratrol; 2 months for naringenin), the crystals did not show severe damage and were flash frozen after a quick soaking in their mother liquor supplemented with 20% glycerol. Preliminary X-ray diffraction experiments were carried out in-house on an Agilent SuperNova diffractometer (Oxford Diffraction) equipped with a CCD detector. Data collections were carried out at the ESRF, on beamline FIP BM30A and ID30B (Grenoble, France).
Data sets were indexed and integrated with XDS  (Kabsch, 2010) , and scaled and merged with XSCALE or Aimless  (Evans and Murshudov, 2013)  from the CCP4 suite  (Winn et al. , 2011). The structure of TvGSTO1C was solved by molecular replacement using MOLREP  (Vagin and Teplyakov, 2010)  with the coordinates of TvGSTO3S from Trametes versicolor (PDB code 6F43) as the search model. The structures of TvGSTO2C and TvGSTO3C were solved by molecular replacement using MOLREP with the coordinates of TvGSTO1C as the search model. In the structures of the complexes involving TvGSTO2C, electron density maps revealed unambiguously the presence of the ligands in binding pockets of the protein. Restraint files for naringenin and oxyresveratrol were generated with the GRADE server (URL http://grade. globalphasing.
org/cgi-bin/grade/server. cgi). Structures were refined with PHENIX  (Liebschner et al. , 2019)  and manually improved with COOT  (Emsley and Cowtan, 2004). Validation of all structures was performed with MolProbity  (Davis et al. , 2004)  and the PDB validation service (http://validate. wwpdb. org). Coordinates and structure factors have been deposited in the Protein Data Bank (PDB codes TvGSTO1C : 6HJS ; TvGSTO2C : 6SR8, TvGSTO2C/Naringenin : 6SRA ; TvGSTO2C/oxyresveratrol : 6SR9 and TvGSTO3C : 6SRB).
To check the reductase and the peroxidase activities of the TvGSTOs, several concentrations of 2-hydroxyethyl disulfide (HED, 50 -2000 µM) and cumene hydroperoxide (CuOOH, 100 -2500 µM) were respectively tested by following the consumption of NADPH (at 340 nm) catalyzed by glutathione reductase. At 25°C, the reaction mixture was composed of a 500 µL of 30 mM Tris-HCl pH 8. 0, 1 mM EDTA buffer containing 1 mM of reduced glutathione, 180 µM of NADPH, 0. 5 units of yeast glutathione reductase. For all the experiments above, data analysis and the calculations of the kinetic parameters have been performed by using a nonlinear regression model based on the Michaelis-Menten equation with the GraphPad Prism software. Kinetic parameters of TvGSTO1C, 2C and C3 for the deglutathionylation activity towards S-glutathionyl-phenylacetophenone (GS-PAP) have been determined by using high performance liquid chromatography.
Thermal stability assay These assays were performed as described in Deroy et al. (Deroy et al. , 2015)  in 96 well microplates (Harshell, Biorad) and the measurements were carried out using a real time PCR detection system (CFX 96 touch, Biorad). The assays were achieved as follows : 5 μL of Tris-HCl (150 mM) pH 8 buffer, 2 μL of molecules (initial concentration of 1250 µM), 5 μL of proteins at a final concentration of 20 µM, 2 μL of SYPRO orange previously diluted 80 fold and 11 μL of ultra-pure water for a total volume of 25 μL per well. The plate was centrifuged 30 seconds at 4000g. The fluorescence was measured (at excitation at 485 nm and emission at 530 nm) each minute starting from 3 minutes at 5°C with temperature increase 1°C per minute up to 95°C. The denaturation temperature (Td), which corresponds to the temperature where 50% of the highest fluorescence is measured, was determined by using the non-linear regression Boltzmann sigmoidal model with the GraphPad Prism software.
While JWST and Euclid, together with NASA's Roman Space Telescope, will provide excellent access to data in the near-infrared, their capabilities in the visible wavelength range will be very limited in terms of wavelength coverage, spatial and spectral resolution, and bandpass diversity. As a result, after the end of HST, astronomy will effectively lose access to high-spatial resolution, versatile, spectrophotometric observatory capabilities. While the visible wavelength range will be observable by JWST, Euclid, and Roman, these facilities will not cover the full wavelength range, spectral resolution and bandpasses demanded by the science landscape in the 2030s. Specifically, none of these observatories extend beyond HST's capabilities as an observatory. Up to ∼ 1μm, JWST will not have a better spatial resolution than HST, as it is only diffraction limited above roughly 1.
There is a consistent discrepancy between early and late measurements on the 4-6σ level. Data from  [9]  in which Cepheid variables are accessible to a 2. 4 m class telescope. The near-IR channel on HabEx/HWC would vastly increase the volume accessible to such measurements, allowing precision Cepheid-based measurements to dozens of galaxies that have hosted SNe Ia identified between now and when HabEx launches, thereby significantly reducing the uncertainty in the local value of the Hubble constant. The required precision photometry is not achievable from the ground. JWST will be able to achieve some of this science, but fewer accessible SN Ia will have been identified when JWST launches, and JWST is highly inefficient for cadenced observations given its slow slew and settle times. The time required for such a program is estimated based on  [6] , which used HST to identify and measure Cepheids in 20 nearby galaxies with a mean exposure time of ∼15 kiloseconds per galaxy.
Assuming similar exposure times, but reaching to much greater volumes given the eight-fold improvement in HabEx sensitivity relative to HST (i. e. , taking advantage of the D 4 -scaling for unresolved sources), a survey of a few dozen galaxies could be accomplished in a few weeks of observations. This would increase the number of well-calibrated Cepheid distances to galaxies known to host type-Ia supernovae by a factor of several, thereby decreasing the uncertainties in the local value of the Hubble constant. Such data would also be valuable for a range of nearby galaxy science, such as resolved studies of their stellar populations. These observations would require a 4 m class telescope (or larger), with a field-ofview comparable to nearby galaxies (i. e. , ≥ 2. 5×2. 5 arcmin 2 ), and multiple filters options for imaging from the optical (≥ 0.
Lipidomics Spheroids (30-40 per sample) were washed in DPBS and snapfrozen at the time of sampling. At the time of analysis, samples were subjected to Lipidomic Mass Spectrometry as previously described. [29] 12. RNA-Seq Total RNA was isolated from 8-16 spheroids (3D culture) or one confluent well of a 6-well plate (2D culture), corresponding to 40 000-80 000 cells. RNA sequencing by poly-A capture was performed for seven donors by the National Genomics Infrastructure facility at Science for Life Laboratory, Stockholm, Sweden, using a minimum of 100 ng RNA input material. The results were integrated with available RNA-Seq data from additional preadipocytes, 2D differentiated adipocytes, MAAC, fresh adipose tissue, and explant samples. [12]  Genes with an average number of fragments per kilo base per million mapped reads >1 across all samples were analyzed using Qlucore (Lund, Sweden).
Transcription Factor Activity Analyses The activity profiles of 503 transcription factors were analyzed during adipocyte differentiation in 2D monolayer and 3D spheroid culture using the ISMARA algorithm by inferring motif activities based on a linear model with a Bayesian procedure where a Gaussian prior on motif activities was used to avoid overfitting. [32] The parameters of the prior distribution of the Gaussian likelihood model were estimated using crossvalidations in which activities were inferred on a randomly selected subset of 80% of promoters and the parameters corresponding to the optimal fit were validated using the remaining 20% of promoters. Transcription factor binding motifs were validated using human ChIP-Seq data in JASPAR. [33].
Acknowledgements The work was supported by the  European Research Council (ERC)   Synergy Grant SPHERES  (agreement No. 856404 ) under the European Union's  Horizon 2020 research and innovation program  (ercspheres. univ-tlse3. fr),the  Swedish Research Council  [grant agreement numbers:  2016-01153 ,  2016-01154 ,  2018-02488  and  2019-01837 ], the  EU/EFPIA/OICR/McGill/KTH/Diamond Innovative Medicines Initiative 2 Joint Undertaking  (EUbOPEN grant number  875510 ) and by the  Strategic Research Programmes in Diabetes (SFO Diabetes)  and  Stem Cells and Regenerative Medicine (SFO StratRegen). Furthermore , the authors were supported by grants from the  Margareta af Uggla's Founda-tion , the  Novo Nordisk Foundation  (including the  Tripartite Immunometabolism Consortium Grant   NNF15CC0018486 , the  MeRIAD consortium  grant number  0064142 , the  MSAM  Consortium  NNF15SA0018346  and  NNF20OC0061149 ),  Knut and Alice Wallenberg Foundation ,  CIMED , the  Swedish Diabetes Foundation , the  Stockholm County Council ,  Fondation pour la Recherche Médicale  ( DEQ20170336720 ),  Agence Nationale de la Recherche   ANR-17-CE14-0015Hepadialogue  and As-traZeneca France.
The authors gratefully acknowledge support from the  Bioinformatics and Expression Analysis Core Facility  and the  VirusTech Core Facility at Karolinska Institutet  for integrating RNA-Seq datasets from different sources and provision of AAV-GFP serotypes, respectively. SVF spheroid and TERT-hWA imaging were performed at the  Biomedicum Imaging Core (BIC)  facility and the  LCI facility/Nikon Center of Excellence, Karolinska Institutet. The authors also acknowledge the assistance of  Dr. Sonia Youhanna  with spheroid culture.
Importantly, Tifab mRNA expression (GEPIA2 dataset) is significantly increased in AML patients compared with healthy controls (Figure  2H ), and higher TIFAB expression is correlated with poorer overall survival (Figure  2I ) in AML patients. Collectively, these data indicate that TIFAB accelerates AML cell proliferation and corroborated its function in AML, as reported recently  (Niederkorn et al. , 2020b).
STAR+METHODS Detailed methods are provided in the online version of this paper and include the following:  analyses, the following antibodies were used when appropriate: biotinylated lineage markers (CD3, CD4, CD5, CD8, B220, and Ter119) plus streptavidin PE-CF594, Gr-1, Mac-1 and Sca1-PE or PE-Cy5, c-kit-BV421, CD34-A700, CD16/32-APC or -PECy7, BrdU-APC, Ki67-PE, and caspase3-PE. LSRII was used for all the analyses, and FACSAria was used for cell sorting. Data was analyzed using FlowJo (TreeStar). d KEY RESOURCES.
(E) Expression of immature marker CD117 in Con or leukemia cells overexpressing TIFAB. (F) Colony numbers of Con or leukemia cells overexpressing TIFAB with or without 4-hydroxytamoxifen (4-OHT, 0. 25 mM). Data are represented as means G SEM. *p < 0. 05, t test. A-F, representative results of at least three independent experiments. (G) Survival curve of sublethally irradiated mice receiving TIFAB-or empty-vector (Con)-transduced MLL-AF9 leukemia cells (n = 5 each, representative results of two independent experiments). **p < 0. 01, log rank test. (H) Expression of Tifab mRNA in AML and normal controls. Data were extracted from GEPIA2 Database, which combines TCGA (the Cancer Genome Atlas) and GTEx (Genotype-Tissue Expression) data. The normal controls are unrelated normal bone marrow tissue in the TCGA and GTEx datasets.
ACKNOWLEDGMENTS We thank  Dr. Klaus Rajewsky  ( Max Delbru ¨ck Center for Molecular Medicine, Berlin ) for the permission to use NIKDT3 flSTOP mice. We thank  Heath Vignes ,  Michael Shey  ( University of Iowa Flow Cytometry Core facility ) and  Mike Sramkoski  ( Case Western Reserve University ) for cell sorting. J. M. Z was sponsored by the  Chinese Government Scholarship  (No. 201908210304 ) and partially the  Department of Pathology startup funds  ( Case Western Reserve University and University Hospitals ). This work was supported by the  U. S. Department of Veterans Affairs  ( I01 BX004255 ) and the  National Institutes of Health/National Cancer Institute  ( R01CA237006 ), and the  Department of Pathology startup funds  ( Case Western Reserve University and University Hospitals ) to C.
*p < 0. 05, t test. (E) Expression of immature marker CD117 in Con or leukemia cells overexpressing TIFAB. (F) Colony numbers of Con or leukemia cells overexpressing TIFAB with or without 4-hydroxytamoxifen (4-OHT, 0. 25 mM). Data are represented as means G SEM. *p < 0. 05, t test. A-F, representative results of at least three independent experiments. (G) Survival curve of sublethally irradiated mice receiving TIFAB-or empty-vector (Con)-transduced MLL-AF9 leukemia cells (n = 5 each, representative results of two independent experiments). **p < 0. 01, log rank test. (H) Expression of Tifab mRNA in AML and normal controls. Data were extracted from GEPIA2 Database, which combines TCGA (the Cancer Genome Atlas) and GTEx (Genotype-Tissue Expression) data. The normal controls are unrelated normal bone marrow tissue in the TCGA and GTEx datasets.
RNA Sequencing Total RNA samples extracted from iRPE were sequenced at the iGenSeq transcriptomic platform of the Brain and Spine Institute (ICM, Paris, France). RNA quality was checked by capillary electrophoresis (Agilent 2100 Bioanalyzer system, Les Ulis, France), and RNA with integrity numbers (RIN) ranging from 7. 8 to 8. 2 was accepted for library generation. Quality of raw data was evaluated with FastQC. Libraries were prepared with Roche KAPA mRNA HyperPrep kit and sequenced with the Illumina NextSeq 500 Sequencing system using NextSeq 500 High Output Kit v2 (150 cycles), 400 million of reads, 50Gbases. STAR v2. 5. 3a was used to align reads on reference genome hg19 using standard options. Quantification of gene and isoform abundances was performed with RSEM 1. 2. 28, prior to normalization on library size with edgeR bioconductor package.
In Vivo Retinal Morphology Retinal morphology was assessed in vivo under anesthesia (ketamine 100 mg/kg, xylazine 10 mg/kg) using MICRON III image-guided optical coherence tomography (OCT, Phoenix Research Labs, Pleasanton, CA, USA). Pupils were dilated with drops of MYDRI-ATICUM (2 mg/0. 4 mL, VIDAL, Issy les Moulineaux, France). OCT scan location and direction were visualized on a bright-field retinal image, and OCT real-time images of the retinal cross sections passing through optic nerve were taken with MICRON OCT software.