dataesr/scientific-paragraphs-categorization huggingface dataset:
), in particular concerning the evaluation of experimental sources of uncertainty. • Provide recommendations on the SINBAD evaluations based on the experience, needs and expectations of the nuclear data community; To participate in establishing the priority list of relevant benchmarks according to the needs of ND community, in particular among new and recent benchmarks; promote including the selected benchmarks in SINBAD; contribute sensitivity profiles. • To participate, in coordination with EGRTS WPRS, in establishing the review group and organisation of pilot exercise of SINBAD evaluations. The FNG benchmark evaluations performed within the EC Fusion for Energy (F4E) project are good candidates for the pilot exercise. WPEC SG47 will work in close coordination with the SINBAD project and Expert Group on Radiation Transport and Shielding (EGRTS) of OECD/NEA.
WPEC SG47 shall provide feedback on the existing database, promote further development and provide recommendations on the SINBAD evaluations based on the experience, needs and expectations of the nuclear data community. Cooperation with other NEA activities  [8]  such as WPEC SG45 (Validation of Nuclear Data Libraries (VaN-DaL) Project), SG46 (Efficient and Effective Use of Integral Experiments for ND Validation), JEFF  [9]  and European Comission (EC) projects such as SANDA and EU-ROfusion is likewise important in order to study and recommend the proper mathematical and physics procedures to integrate these data in the ND evaluation process and thus avoid their misuse. Several laboratories from US (LLNL, ORNL) China (FDS, CIAE), Russia (IPPE) and others expressed interest in this activity.
Present status and quality review Several of the SINBAD benchmarks are old, some dating back to the 1960s and the access to the detailed and reliable experimental information neede for the validation of the present high-quality nuclear data is difficult or not possible. Still, these benchmarks are valuable since they provide the record of experimental data on which present data and methods are often based. On the other hand, some of these experiments may not be best suited for the present nuclear data validation and improvement. A thorough revision and classification of the benchmark experiments according to the completeness, reliability and consistency of information was therefore started about 10 years ago. More than half of the SINBAD experiments were already, or are currently being revised and reclassified  [10] [11] [12] [13].
Candidates for future SINBAD evaluations SINBAD database includes now over 100 benchmarks. The progress was slow in the recent years but the activities on further expansion of the database shall continue. The objectives of the future work are twofold, on one side to continue with the more detailed and complete quality evaluations of the existing database, and on the other side to complement the database with new benchmark evaluations. At the WPEC SG47 kick-off meeting several past shielding benchmarks of interest for nuclear data validation were identified. Among the candidates for future SIN-BAD evaluations the following can be highlighted: • FNG-Cu and FNG-HCLL: evaluations done within F4E in 2018, review needed • FNS Cu, Ti, Li 2 O: requested from JAEA • OKTAVIAN benchmarks • LLNL pulsed spheres • IPPE: BTiH, U • CIAE neutron leakage spectra from Fe, SiC, graphite • REZ Fe sphere and slab benchmarks  [17]  • VENUS- • KFK 1977 iron sphere gamma measurements using 252 Cf source • NIST 2000 50-cm Fe sphere experiment using 252 Cf source • LRC, Ohio neutron leakage spectra from Ta sphere with Am-Be source • Ohio University Fe spheres with D(d,n) neutron source • Mn bath experiment.
Recent SINBAD evaluations -FNG Copper Benchmark A neutronics benchmark experiment on a pure Copper assembly  [14]  was performed end 2014 -beginning 2015 at the 14-MeV Frascati neutron generator (FNG) of ENEA Frascati with the objective to provide the experimental database required for the validation of the copper nuclear cross-section data relevant for ITER design calculations, including the related uncertainties. Evaluation of the benchmark for the SINBAD database was performed in the scope of the F4E project  [15]  and the review is ongoing to include the data in SINBAD. FNG Cu benchmark is planned to be used as a pilot evaluation in the scope of WPEC SG47. The experiment was performed in the frame of the European Fusion Program. Reaction rates, neutron flux spectra and doses were measured at several locations inside the 60x70x70 cm 3 Copper block (Fig.
Conclusions The SINBAD database currently contains compilations and evaluations for 102 fission, fusion and accelerator relevant shielding problems and continues to represent an important experimental database for validating nuclear data, codes and nuclear design. The SINBAD database is now widely used for code and data validation. Materials covered include: Air, N. O, H 2 O, Al, Be, Cu, graphite, concrete, Fe, Pb, Li, Ni, Nb, SiC, Na, SS, W, V and mixtures thereof. Over 40 organisations from 14 countries and 2 international organisations have contributed data and work in support of SINBAD. SINBAD was successfully used in the scope of Fusion for Energy (F4E), EUROfusion, CHANDA, WPEC CIELO, SG39, SG46, EFF-4 and IAEA activities and demonstrated to be suitable for validation of modern nuclear data evaluations and codes, in combination with criticality, kinetics and other benchmarks.
Only recently, two new evaluations were performed in the scope of F4E and some more may come in the near future. The new Many discussions were devoted recently to the format issues rather than the content itself. Reformatting the database is likely to require considerable funding and extreme caution to avoid a possible (probable) loss of data in the process of re-formatting. In the actual situation of limited funding we suggest that the main activity be preferentially focused on the new benchmark evaluations according to the SINBAD priority list and on continuation of the quality revision and classification of existing benchmark. A new WPEC SG47 on "Use of Shielding Integral Benchmark Archive and Database for Nuclear Data Validation" started in June 2019. The Subgroup is expected to provide feedback on the expectations and needs of the nuclear data community and thus contribute and orient the further development of the database.
Based on evolution, the Hsa21 region is more conserved between species that have a more recent common ancestor with Human, such as the Hominidae subclass species. The nuclear chromosome organization is a shared trait between all the Eukaryotic species. However, the rest of the genomic features are specie-specific although up to some degree these features can be conserved i. e. the number of chromosomes, their internal organization or the ratio of the different coding and non-coding elements present on each. To analyse in detail the genome features of these species, we queried the ENSEMBL (www. ensembl. org) database using biomaRt on the 270219 using the genomes assembly's databases version 95.
Interestingly, Hsa21 is the autosomal chromosome with the least number and percentage of genes. According to the most recent database, 833 genes are identified in total with 232 protein coding genes, 380 non-coding RNA, 188 pseudogenes and 15 genes to be experimentally confirmed (TEC). Finally, this chromosome holds 8. 762. 696 variants described of all kinds. To address how conserved the orthologs are to the Hsa21 genes on the different species we extracted all the known ortholog genes that diverged by a speciation event, using ENSEMBL biomaRt R package  (Brazma et al. , 2005) , and classified them in three categories: a) High confidence homologs: genes for whose ENSEMBL has a high confidence in the homology prediction annotation. b) Remote homologs when the confidence score in the homology was 0 and the sequence similarity was above 15% of the human gene with the other specie gene.
For examples, the alteration of EPHA4-PAX3 TAD by disrupting a CTCF-associated boundary generate limb malformations  (Lupiáñez et al. , 2015) ; a deletion of 66kb upstream of LMNDB1 promoter deletes a TAD boundary and produces the interaction of three enhancers with the LMNDB1 leading to overexpression of Lamin B1 and causing a rare neurological disorder characterized by a progressive central nervous system demyelination  (Giorgio et al. , 2015). In cancer TADs seem to be crucial, as 7307 mutations occurring in hESCs CTCF loops anchors were linked to several cancers as identified from the International Cancer Genome Consortium database  (Zhang et al. , 2011 , Ji et al. , 2016). Furthermore, some proto-oncogenes are insulated inside subTADs to control their activation  (Hnisz et al. , 2016).
, 2010). Over the past twenty years, numerous publicly available mouse gene expression databases and digital gene expression atlases such as MAMEP (http://mamep. molgen. mpg. de), EMBRYS  (Yokoyama et al. , 2009)   (Magdaleno et al. , 2006 , Heintz, 2004)  (http://www. gensat. org), the Allen Brain Atlas  (Lein et al. , 2007)  (http://portal. brainmap. org/), EMAGE (http://www. emouseatlas. org/emage) and based on in situ hybridization and high-throughput gene expression data have been developed and offer invaluable tools to visualize gene expression with spatiotemporal resolution. Some of these data are available in some integrated resources such as the Gene Expression Database (GXD, http://www. informatics. jax. org/expression. shtml) and the Gene Expression Omnibus (GEO, https://www. ncbi.
nlm. nih. gov/geo/). With the recent development of single-cell RNA-Sequencing, resolution of gene expression now reaches single cells. This new technique has enabled to dig into cell population diversity and cell type identification revealing rare populations of cells and leading to transcriptome-based single cell databases and atlases (DropViz: http://dropviz. org/, (Saunders et al. , 2018 , Tasic et al. , 2016) ; Single cell expression atlas: https://www. ebi. ac. uk/gxa/sc/home; Adult mouse cortical cell taxonomy: http://casestudies. brain-map. org/celltax, (Tasic et al. , 2016) ). Using Microwell-Seq, Han and collaborators profiled over fifty mouse organs, tissues and cell lines providing a mouse cell atlas database that will also include proteomic data (such as CyTOF data) and spatial information (such as in situ data) to provide a more complete atlas with multi-omic information  (Han et al.
Thus, we should either refine the Ts65Dn model by removing the non-homologous region to Hsa21 or generate a new model with a segregating chromosome containing all the main regions homologous to Hsa21. This will also bring together the same context and organization, but the tools needed to achieve this goal are still to be either improved or described. Overall, the transposition of brain cognitive phenotype between human and animal models is still a challenge. Even though we can assess certain implicit or explicit memory functions in animal models, a standardization of methods may reduce the variability observed between datasets and increase the reproducibility of the results. The rat represents a new opportunity to investigate cognitive deficit in DS and to test preclinical drugs but we may consider other species in the future even more closely related to human.
Gating strategy For Micromonas: The trigger channel was Forward Scatter (FSC), to allow detection of pigmented cells (both Micromonas and Nannochloropsis are algae with natural chlorophyll fluorescence), dead cells, and cell detritus. No gates were applied in the data collection mode, only for post analysis. All cells (with plasmid in treratments either pulsed, or not pulsed) were visualized in a two parameter histogram of FSC vs Chlorophyll (692/40 nm bp). For means, the population of non-detrital particles (living cells) was gated into a second two parameter histogram of FALS vs GFP (520/35 nm bp), as well as GFP vs Chlorophyll. From there cells with eGFP fluorescence were analyzed as were cells with baseline eGFP fluorescence and the geometric mean of these fluorescences were compared, as were cell abundance in each population.
acknowledgements We thank  M. Salisbury  and  D. Lacono ,  C. Poirier ,  M. Hamilton ,  C. Eckmann ,  H. Igel ,  C. Yung  and  K. Hoadley  for assistance;  V. K. Nagarajan ,  M. Accerbi  and  P. J. Green  who carried out Agrobacterium studies in Heterosigma akashiwo, and  N. Kraeva ,  C. Bianchi  and  V. Yurchenko  for the help with designing the p57-V5+NeoR construct. We are also grateful to the protocols. ioteam ( L. Teytelman  and  A. Broellochs ) for their support. This collaborative effort was supported by the  Gordon and Betty Moore Foundation EMS Program of the Marine Microbiology Initiative  (grant nos. GBMF4972  and  4972. 01  to F. -Y. B. ;  GBMF4970  and  4970. 01  to M. A. and A. Z. W. ;  GBMF3788  to A. Z. W. ;  GBMF 4968  and  4968. 01  to H. C. ;  GBMF4984  to V. H. ;  GBMF4974  and  4974.
Data analysis FACS softwares noted in our methods section that were used for data analysis after collection on the FACS instrument are FloJo v. 10. 6. 1 and WinList 3D v7. 0 (Verity Software House). For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers. We strongly encourage code deposition in a community repository (e. g. GitHub). See the Nature Research guidelines for submitting code & software for further information.
Rme1 was also bound to its own promoter, suggesting a transcriptional autoregulation (Fig. 1a ). We validated the ChIP-chip data by ChIP-qPCR, detecting Rme1 binding at the upstream regions of a set of selected genes (Supplementary Fig. 2a ). In parallel, we performed global gene expression profiling of the RME1 overexpression strain grown for 2 and 4 h in doxycyclinecontaining medium as compared to the non-induced culture (Supplementary Data 6). We found 423 and 446 upregulated (fold-change ≥1. 5, P < 0. 05) and 185 and 235 downregulated (foldchange ≤ -1. 5, P < 0. 05) genes after 2 and 4 h of induction, respectively (Fig. 1b, c ). As a control, doxycycline treatment alone did not significantly alter gene expression  26  (GSE67226, https://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc=GSE67226).
5%), yielding a ~3 fold enrichment of Rme1 direct targets in Palige et al. datasets (P = 6. 72 × 10 -9 using a hypergeometric test). Rme1 controls chlamydosporulation in species other than C. albicans. The data presented above raised the question of whether Rme1 acts as a regulator of chlamydosporulation. We tested this hypothesis by growing the C. albicans wild-type (WT) strain SC5314, an rme1 knockout mutant (rme1ΔΔ, CEC4411) and an RME1 overexpression strain (P TET -RME1 in a WT background, CEC5031) in "chlamydospore-inducing conditions" (on Potato Carrot Bile (PCB) solid medium at 25 °C in darkness and microaerophilia)-with doxycycline for P TET induction-for 3 days, a condition that triggers the formation of chlamydospores by the SC5314 WT strain (Fig. 2a ). Strikingly the P TET -RME1 strain formed numerous rounded cells with a chlamydospore-like aspect in the presence of doxycycline, whereas the rme1ΔΔ strain did not produce chlamydospores (Fig.
4 N. A. (images were captured with a Hamamatsu ORCA II-ER cooled CCD camera, using Openlab software version 3. 5. 1, Improvision Inc. ) or with an Olympus IX 83 microscope equipped with either a 100× oil-immersed objective or a 40× objective (images were captured with a Hamamatsu ORCA Flash cooled CCD camera, using Cell sens software). Colonies growing on PCB plates were observed with a Leica DM RXA microscope (Leica Microsystems) equipped with an oil-immersed 40× objective, and images captured as above. Images were then processed with Adobe Photoshop CS6. Candida transformation. C. albicans and C. buenavistaensis transformations were performed using the lithium-acetate transformation protocol developed by Walther and Wendland  53. In short, cells were diluted to OD 600 = 0. 2 in 50 mL YPD and grown at 30 °C until OD 600 = 0.
The RME1 deletion mutant was generated in the BWP17 background by knocking out both alleles by cassette replacement. In brief, the HIS1 and ARG4 disruption cassettes were generated by PCR using pSN52-CdHIS1 and pSN69-CdARG4  55  as templates, respectively, and specific primers containing ca. 100 bp homolog to the RME1 gene (RME1-KO-F and RME1-KO-R; all primer sequences are listed in Supplementary Data 2). Proper gene replacements were verified by PCR with RME1-KO-DETECT-F, RME1-KO-DETECT-R, RME1-500-F and RME1-500-R, CdHIS1-DETECT-F, CdHIS1-DETECT-R, CdARG4-DETECT-F and CdARG4-DETECT-R. The resulting ura-auxotrophic clones were transformed either with CIp10 58 to generate prototrophic deletion mutants or with pNIMX  59  to generate strains expressing the C. albicans-adapted reverse Tet-dependent transactivator (cartTA).
The resulting plasmids were StuIdigested prior to transforming C. albicans expressing the cartTA transactivator. Clones were verified by PCR with primers CIp_UL and CIp_UR  59. C. buenavistaensis RME1 sequence has been deposited in GenBank under accession number MK070497. Murine candidemia model. Female BALB/c mice at 6-8 weeks of age were used for disseminated candidemia following intravenous administration. Animals were separated according to their strain and housed in top-filtered cages with sterile water and food provided ad libitum. Throughout the study, mice were kept on 12 h light/dark cycles, with lights on from 07:00 h to 19:00 h, at 20 °C with ambient humidity. Mice were infected intravenously with 1 × 10 6 CFU of WT or rme1ΔΔ C. albicans strains (CEC1, CEC4788, CEC4783, CEC4785 and CEC4805) in a 0.
albicans whole-genome tiled DNA microarrays from Assembly 20 (GEO platform accession GPL13696, https://www. ncbi. nlm. nih. gov/ geo/query/acc. cgi?acc=GPL13696) overnight at 65 °C. Slides were washed in Agilent wash buffers 1 (at room temperature for 1 min) and 2 (at 37 °C for 1 min) then removed slowly from the washing dish to minimize droplets on the slide. Scanning of the arrays was performed using an Axon Autoloader 4200AL scanner and analyzed with the GenePix software version 7. 0 (Molecular Devices). Data normalization (Quantile) and peak finding were conducted using CisGenome  24. In order to visualize the ChIP-on-chip results we used the Integrated Genomics Viewer (IGV) software  61. The complete Rme1 binding datasets are available in Supplementary Data 3-5. Whole-genome transcript profiling analyses.
The GenePix files (. gpr) were imported into the Arraypipe 2. 0 software for spot filtering, background substraction (limma normexp BG correction) and Lowess global normalization of signal intensities  62. Replicate arrays (n = 3) were combined and fold-change and P-values (Welch's t-test within group) were calculated. The complete expression profiling datasets are available in Supplementary Data 6 and 8. As a control, we also assessed the effect of doxycycline on gene transcription  26. Validation of transcriptomics and ChIP-on-chip analyses. Total RNA from strains expressing P TET -RME1 (see Supplementary Data 1) or from CEC2018 WT and rme1ΔΔ strains was isolated as described before, and used to perform a reverse transcription (RT) reaction (2 μg of total RNA) using the SuperScript III enzyme (Invitrogen ® ) in a final reaction volume of 20 μL.
The qPCR reactions contained the following components: 1 μL of cDNA from the RT reaction, 0. 5 μL of each primer (forward and reverse of a given gene, Supplementary Data 2) at 10 pmol/μL, 7. 5 μL of 2× Takyon Rox SYBR MasterMix dTTP blue (Eurogentec ® ) and 5. 5 μL H 2 O. The reactions were performed in a MicroAmp Optical 96-Well Reaction Plate (Applied Biosystems ® ) using an Eppendorf Realplex Mastercycler real-time PCR instrument (Eppendorf ® ) with 1 cycle at 50 °C for 2 min, 1 cycle at 95 °C for 10 min and 50 cycles at 95 °C for 15 s and 58 °C for 1 min. The results obtained were analysed in the realplex software version 2. 2 (Eppendorf ® ), where the threshold cycle (C T ) values were determined. The TEF3 and ACT1 genes were used as calibrator and as a gene control respectively [using the primers TEF3-F and TEF3-R, or ACT1-F and ACT1-R, respectively (Supplementary Data 2)].
Assays were performed in triplicate using three biological replicates for the RT-qPCR experiments and three times independently with two biological replicates for the ChIP-qPCR experiments. Data were expressed as the mean ± SD. Differences for a given gene/ChIP target were analysed by the two-tailed unpaired Student's t-test, the n-fold relative gene-expression values to the corresponding n-fold values of ACT1 control, or for the ChIP-qPCR the n-fold enrichment values of the target gene (ORF19. 654, CSP1, CSP2, PGA55, FEN1 and ORF19. 7250) to those of the corresponding ACT1 control, a P value < 0. 05 was considered as statistically significant. Plasmid constructions for the CSP1-and P PGA55 -GFP fusions. The CSP1-GFP fusion was generated as follows: first, the CSP1 gene was PCR amplified and cloned into pDONR207, and then transferred into the destination vector CIp10-P ACT1 -GTW-GFP  60  as described above, yielding CIp10-P ACT1 -CSP1-GFP.
Building of the C. albicans CEC2018 and C. dubliniensis rme1ΔΔ mutants. The RME1 coding region was disrupted in the C. albicans clinical isolate CEC2018 and in C. dubliniensis using the SAT1 flipping method developed by Reuß et al. 64. In order to generate the cassette to knockout CaRME1, a 543 bp fragment in the RME1 upstream region was amplified by PCR with primers RME1-KO-flip-F-Prom and RME1-KO-flip-R-Prom (Supplementary Data 2); the PCR product was then digested with KpnI and XhoI and cloned into the same sites of pSFS1  64  to generate pSFS1-P RME1. Independently, a 515 bp fragment belonging to the RME1 downstream region was amplified by PCR using the primers RME1-KO-flip-F-Ter and RME1-KO-flip-R-Ter, then digested with NotI and SacI and cloned into the same sites of pSFS1-P RME1 to generate the disruption plasmid pSFS1-P RME1 -T RME1 , that was linearized with KpnI and SacI prior to transforming the CEC2018 strain.
Transformants were selected on YPD plates supplemented with 200 µg/mL of nourseothricin (clonNAT, Werner BioAgents ® ) after 2 days at 30 °C. The disruption of a single allele of RME1 was confirmed by PCR using the primers RME1-FLIP-VERIFY-KO-F, SAP2-VERIFY-R, PSFS1-VERIFY-F and RME1-FLIP-VER-IFY-KO-R (Supplementary Data 2). Two independent transformants were grown overnight in YCB-BSA medium [(2. 34% (w/v) yeast carbon base and 0. 4% BSA)] at 30 °C to induce the loss of the SAT1 cassette via intramolecular recombination at the FRT sites by the site-specific recombinase FLP and to regenerate the sensitivity to nourseothricin. This event was verified by PCR using the primers RME1-FLIP-VERIFY-KO-F and RME1-FLIP-VERIFY-KO-R, yielding a 2 kbp fragment confirming the excision of the SAT1-FLP cassette.
The sgRNA cassettes were PCR amplified and co-transformed with the corresponding repair template fragment and a sequence encoding the CAS9 expression cassette. Primers ColoORF_NDT80/F with ColoORF_NDT80/R and ColoORF_NRG1/F with ColoORF_NRG1/R were used to confirm homozygous mutants. Chlamydospore formation screening in C. albicans clinical isolates. C. albicans clinical isolates (Supplementary Data 7), the WT reference strain SC5314 and the RME1 overexpression strain CEC4297 were grown for 24 h in 3 mL of PCB liquid medium at 25 °C in 24 deep well plates in the dark and under microaerophilic conditions. Cells were centrifuged and washed twice with water and photographed at the microscope. Chlamydospore formation scores were based on the amount of chlamydospores found by field; score 0 was given to strains unable to form chlamydospores under the tested conditions.