dataesr/scientific-paragraphs-categorization huggingface dataset:
We reevaluated this relationship using recently published highresolution genetic maps (Bherer et al. , 2017), meiotic double-strand breaks (DSBs) maps  (Pratto et al. , 2014)  and meiotic gene expression datasets  (Guo et al. , 2015; Lesch et al. , 2016). These new data show that the relationship between crossover rate and meiotic gene expression is even stronger than initially reported: we observed that the crossover rate is 3. 5 (males) to 5. 4 (females) times lower in highly expressed genes (top 10%) compared to weakly expressed genes (bottom 10%) (Figure  3A , Figure  3 -figure supplement 3A,B). This reduction in crossover rate is explained, at least in part, by a lower density of meiotic DSB hotspots within highly expressed genes (Figure  3 -figure supplement 3C). In agreement with Bherer et al.
B Single cells (embryos) Figure  5. Correlation between expression level and GC3 in a panel of tissues and cell types. (A) Bulk adult tissues data  (Fagerberg et al. , 2014)  and (B) early embryo single-cell data  (Guo et al. , 2015). These two subsets were obtained via very different protocols, which prevents direct crosscomparisons. Samples are sorted by increasing correlation coefficient (R 2 ) between expression levels and GC3 (NB: all correlations are negative). Samples containing somatic cells are shown in blue; male germ cells in orange (testis or single cell) and female germ cells in red (PGC: primordial germ cells). The green point corresponds to cells from the inner cell mass (ICM) of the blastocysts, i. e. pluripotent cells from an early stage of development preceding the differentiation of germ cells.
Human protein coding genes For each of the human protein coding genes in the Ensembl (RRID: SCR_002344) release 83  (Yates et al. , 2016) ; assembly GRCh38. p5), we identified a canonical transcript as defined in http:// www. ensembl. org/Help/Glossary?id=346 (PERL script available in supplementary material). Mitochondrial genes were excluded from this analysis. Sequences of the remaining 19,766 canonical transcripts together with exons coordinates, were downloaded through the BioMart query interface  (Smedley et al. , 2015) (RRID: SCR_010714).
Expression data Gene expression levels were collected from three publicly available human RNA-seq experiment datasets. The first one includes 27 differentiated adult tissues  (Fagerberg et al. , 2014; Kryuchkova-Mostacci and Robinson-Rechavi, 2015) ; EBI accession number E-MTAB-1733). We downloaded normalized expression levels, already averaged across replicates, from  (Fagerberg et al. , 2014; Kryuchkova-Mostacci and Robinson-Rechavi, 2015)  (see supplementary information). The second one is based on single-cell RNA-seq analysis, and includes 20 samples, corresponding to inner cell mass (ICM) of the blastocysts, and to primordial germ cells (PGC) and somatic cells, from male and female embryos at different development stages (4, 7 or 8, 10, 11 and 17 or 19 weeks,  (Guo et al. , 2015)  GEO accession number GSE63818).
We downloaded normalized expression levels from their dataset of pool-split PGCs (for more details see supplementary information). Female 17 weeks PGCs are entered in meiosis  (Guo et al. , 2015). This sample was therefore taken as representative of the transcriptome of meiotic cells in female. The third dataset corresponds to human male germ cells at pachytene spermatocytes (i. e. cells entering meiosis) and at round spermatids stages (post meiotic stage) (  [Lesch et al. , 2016] ; GEO accession number GSE68507, human RNA expression datasets GSM1673959, GSM1673963, GSM1673967, GSM1673971, GSM1673975 and GSM1673978). Guo and Lesch datasets include several replicates for each sample. We therefore computed the average expression levels over all replicates for each sample. The sex-averaged meiotic expression level was estimated by computing the mean of expression levels in female 17 weeks PGCs  (Guo et al.
Acknowledgement This work was supported by  French National Research Agency (ANR)  grant  DaSiRe  ( ANR-15-CE12-0010-01/DaSiRe ) and the "appel d'offre fond recherche-projets emergents" of the  ENS de Lyon. This work was performed using the computing facilities of the  CC LBBE/PRABI. FP received a doctoral scholarship from  Ecole Normale Superieure de Lyon  (http://www. ens-lyon. eu/). We thank  Gae ¨l Yvert  for initiating the discussion and  Adam Eyre-Walker  and  Vincent Daubin  for helpful suggestions on a first version of our manuscript.
INTRODUCTION A static type system can be an extremely powerful tool for a programmer, providing early error detection, and offering strong compile-time guarantees on the behavior of a program. However, compared to dynamic typing, static typing often comes at the expense of development speed and flexibility, as statically-typed code might be more difficult to adapt to changing requirements. Gradual typing is a recent and promising approach that tries to get the best of both worlds  [Siek and Taha 2006]. The idea behind this approach is to integrate an unknown type, usually denoted by ł?ž, which informs the compiler that additional type checks may have to be performed at run time. Therefore, the programmer can gradually add type annotations to a program and controls precisely how much checking is done statically versus dynamically.
However, this piece of code is perfectly valid in a gradual type system, the compiler will simply add dynamic checks to ensure that the value bound to x can be passed as an argument to succ or not according to the case. Moreover, it will also add checks to ensure that the value returned by f is used correctly. Nevertheless, there are some flaws in this piece of code. For example, it is possible to pass a value of any type as the second argument of f (the type system ensures that the first argument will always be a Boolean). In particular, if one applies the function f to (a Boolean and) a value of type string, then the application will always fail, independently from the value of condition, and despite the fact that the application is statically considered well-typed. This problem can be avoided by set-theoretic types, in particular by using the union type Int | Bool to type the parameter x of the function so as to ensure that every second argument of f that is neither an integer nor a Boolean will be statically rejected by the type checker.
This is obtained by the following code let f (condition : Bool) (x : (Int | Bool)) : (Int | Bool) = if condition then succ ((Int) x) else not  ((Bool)  x) The code above shows that the use of union types fixes the shortcoming we pointed out. However in order to ensure that the applications of succ and not are both well typed we also had to add two type casts 1  that check at run-time whether the argument has the required type and raise an exception otherwise. Remark. The use of explicit type-casts should not surprise the reader. Any language with union types needs an operation to dynamically check the type of values that are given union types. Such operations may have different forms and be implemented in different ways and at different degrees: they range from the simple check of constructors/tags (eg, when unions are restricted to datatypes/variant-types), to value inspection primitives such as those of Typed Racket  [Tobin-Hochstadt and Felleisen 2008]  (eg, procedure?, number?, etc.
), till the unconstrained check of the type of a value returned by an expression e, that is, match e with t 1 -> e 1 |. | t n -> e n which is used in languages like CDuce  [Benzaken et al. 2003]  where unions are full fledged. 2 This article studies the latter case and therefore a type cast (t)e is just syntactic sugar for 3  match e with t -> e | _ -> raise "Cast error". □ In this second definition of f we have ensured, thanks to union types, that every application of f has now a chance to succeed. However, this is obtained at the expenses of the programmer who has now the burden to insert in the code the type-cases/type-casts necessary to ensure safety (in the sense established by  Wright and Felleisen [1994] ). By using set-theoretic types in conjunction with gradual types, it is possible both to ensure that f will only be applied to booleans or integers and to delegate the insertion of type casts to the system.
This is shown by the following piece of code that our system will compile into the previous one. if condition then succ x else not x In this example, the variable x is of type ((Int | Bool) & ?), where ł&ž denotes an intersection. This indicates that x has both type (Int | Bool) and type ?. Intuitively, this means that the function f accepts as a second argument a value of any type (which is indicated by ?), as long as this value is also an integer or a Boolean. The effect of having added ł& ?ž in the type of the parameter is that the programmer is no longer required to add the explicit casts in the body of the function: the system will take care of it at compile time. The combination of a union type with ł& ?ž to type a parameter corresponds to a programming style in which the programmer asks the system to statically enforce that the function will be applied only to arguments in the union type and delegates to the system the dynamic checking, where/if necessary, for each case in the union; and while adding explicit casts in a five-line example such as the above is quite straightforward, in general (eg, in thousand-line modules), it is not always so, whence the interest of having a system that adds all and only the casts that are necessary to ensure type safety.
if condition then succ x else not x which shows in a clear way that the application of f to a (necessarily Boolean) argument returns an overloaded function whose result type depends on the type of its argument: the two occurrences of ł?ž in the input types of the overloaded function indicate that, in both cases (ie, whatever the type of the argument is), some dynamic cast may be needed in the body of the function and, thus, may have to be added at compile-time. We want to conclude this introduction by mentioning singleton types, that we do not consider in this work but that can be straightforwardly added to our theory without any further modification. In a language such as CDuce every value also denotes the singleton type that contains only that value. In particular CDuce features two separate types for true and false and the type Bool is then simply defined as the union true | false.
CONCLUSION In this work, we presented a foundational study for gradually-typed languages with union and intersection types and argued that the combination of the former with the latter allows a smoother and finer-grained transition between static and dynamic typing, than what is possible with the current state of the art. As the use of the unknown type ł?ž allows the programmer to gradually add type information in selected parts of the program, so the use of unions and intersections allows the same programmer to gradually refine the type information about a given part of the program or a single expression, thus enabling a new style of gradual programming. While adding unions and intersections inside arrows brings real benefits at no cost, we have also seen that for adding intersections on arrows there is instead a price to pay: intersections of arrows allow the programmer to write overloaded functions, but when these are combined with gradual types their code needs to be specialized to insert casts that depend on the type of the argument.
In CDuce łif e then e 1 else e 2 ž is just syntactic sugar for łmatch e with true -> e 1 | false -> e 2 ž. The current public release of CDuce requires all function parameters, such as condition and x, to be explicitly typed and, thus, it does not accept the code below. The code below is executable on a experimental prototype version (available at http://www. cduce. org/ocaml/bi) based on the work by Castagna et al. [2016]  and that uses a bi-directional type system to infer the types of the parameters of functions. Proc. ACM Program. Lang. , Vol. 1, No. ICFP, Article 41. Publication date: September 2017.
In brief, we first tested a dose of teriflunomide that was consistent with previous studies reporting tumour growth delay in carcinoids upon treatment with prodrug leflunomide  [47]  but animals experienced acute toxicity. This regimen had therefore to be drastically revised to remain within the ethical boundaries and a lower dose of teriflunomide was chosen in order to be consistent with data from the FDA safety report  [40]. Overall toxicity was assessed throughout this new protocol and no animal had to be euthanised whatever the treatment in our study. At a lower dose of teriflunomide, which was not reported to induce repeated dose toxicity including drug-induced carcinogenesis (5 mg/kg/day), no significant effect was observed on tumour growth with or without PF477736. This limited pharmacodynamic effect suggests that either the amount of DNA damage generated in tumour cells did not reach a level sufficient to result in cytotoxicity due to underdosing (or a suboptimal administration schedule), or that inhibition of de novo pyrimidine synthesis was circumvented to some extent by the pyrimidine salvage pathway which contributes to resistance to chemotherapies such as antimetabolites  [48].
Analysis of 20000 events was performed on a FACSCalibur flow cytometer. DNA fluorescence was collected in logarithmic mode and cell viability was quantitated using FlowJo www. impactjournals. com/oncotarget software. The population of dead cells was calculated as the sum of events in upper (left + right) and lower right quadrants in "annexin-V-FITC" vs "7-AAD" dot plots. Each experiment was performed three times.
Immunohistochemistry analysis Five tumour-bearing mice were monitored in each group on days 2 and 3 of the protocol for pharmacodynamic assessment of the aforementioned regimens by immunohistochemistry. Tumours were harvested 24 or 48 hours after the beginning of each treatment and were fixed with formalin, all sections were counterstained with hematoxylin and eosin. Samples were also probed for Ki67 and cleaved caspase-3 levels. Quantitative analysis of Ki67 section staining was performed using ImageJ software and caspase-3 cleavage was quantitated using Aperio ImageScope software.
Convergence Analysis on a Model Problem In order to study the convergence rate and spectral properties of the DDM algorithm we consider a similar setting as for the scalar case, but in three dimensions: the whole domain Ω = R 3 is separated in two curved subdomains Ω 1 and Ω 2 by a spherical boundary of radius R 0 Ω 0 := {x ∈ R 3 , |x| > R 0 }, Ω 1 := {x ∈ R 3 , |x| < R 0 }, (38) with ∂Ω 0 = ∂Ω 1 := Σ. Again, in this homogeneous medium setting we only consider the transmission operators that lead to a sparse surface representation. Using the same strategy as in Section 2. with the Matlab function fminsearch. Analytical solutions of (39) for the half-space case are provided in  [1]  for GIBC(a) and in  [45]  for GIBC(a, b). Contrary the scalar Helmholtz case and to the half-space case  [16] , where IBC(0) leads to a convergence factor that is exactly 1 for the evanescent modes, in this model problem IBC(0) leads to ρ(A m ) < 1 in the whole spectrum, although ρ(A m ) is very close to 1 for the evanescent modes, which results in a globally slowly converging DDM.
h. : acoustic waves in the underground Marmousi model  [47].                          Find r in H(curl, Σ ij ) and ρ in H 1 (Σ ij ) such that ∀r ∈ H(curl, Σ ij ) and ∀ρ ∈ H 1 (Σ ij ): - Σ ij a k 2 ∇ Σ ij ρ • r dΣ ij - Σ ij r • r dΣ ij + Σ ij γ T i ( E n+1 i ) • r dΣ ij - Σ ij b k 2 curl Σ ij (γ T i ( E n+1 i )) • curl Σ ij r dΣ ij = 0, Σ ij ρρ dΣ ij + Σ ij r • ∇ Σ ij ρ dΣ ij = 0; (44) available online on the web site of the ONELAB projet  [29, 30] : http://onelab. info/ wiki/GetDDM. GetDDM is based on the open source finite element solver GetDP (http: //getdp. info) [17, 18, 28]  and the open source mesh generator Gmsh (http://gmsh. info)  [31, 32]. Various 2D and 3D test-cases are provided online (see Figure  6 ) for both acoustic and electromagnetic wave problems, as well as detailed instructions on how to build the software for parallel computer architectures.
Pre-compiled, serial versions of the software for Windows, MacOS and Linux are also available for development and testing. While GetDDM is written in C++, all the problem-specific data (geometry description, finite element formulation with appropriate transmission condition, domain decomposition algorithm) are directly written in input ASCII text files, using the code's built-in language. This general implementation allows to solve a wide variety of problems with the same software, without recompilation, and hides all the complexities of the finite element implementation from the end-user (in particular the MPI-based parallelization). Moreover, the software is designed to work both on small-and medium-scale problems (on a workstation, a laptop, a tablet or even a mobile phone) and on large-scale problems on high-performance computing clusters, without changing the input files.
Acknowledgements This work was supported in part by the  Wallonia-Brussels Federation  ( ARC grant for Concerted Research Actions   ARC WAVES 15/19-03 ), the  Belgian Science Policy  ( PAI grant   P7/02 ), the  Walloon Region  (WIST3 grants ONELAB and ALIZEES), the  French ANR  (grant MicroWave  NT09 460489  " Programme Blanc ") and the  "EADS Foundation " ( High-BRID  project, grant  089-1009-1006 ). Computational resources have been provided by  CÉCI , funded by  F. R. S. -FNRS (Fonds de la Recherche Scientifique)  under grant n  • 2. 5020. 11 ,and the Tier-1 supercomputer of the  Fédération Wallonie-Bruxelles , funded by the  Walloon Region  under grant n  • 1117545.
e. , image analysis with the HiSeq Control Software and Real-Time Analysis component, base-calling with the RTA software and demultiplexing with CASAVA (Illumina). The RNAseq data are available from NCBI GEO datasets under the accession number GSE74030. The quality scores across all bases of all reads and the N (non-attributed bases) content across all bases were determined for each condition with the FastQC software from the Babraham Institute 1. Both analyses showed good quality values (data not shown). The reads were next aligned simultaneously on reference genomes, i. e. , L. garvieae N201 (unpublished, GOLD project ID = Gp0034836 and NCBI BioProject ID = 184287) and S. aureus MW2 (RefSeq number = NC_003923. 1), using the BWA package  (Li and Durbin, 2009)  with a seed of 32 bases and a maximum of two mismatches tolerated on the seed.
Using the Samtools suite  (Li et al. , 2009)  we excluded from further analyses those reads with low alignment quality scores (MAPQ index < 20). Reads which mapped on multiple sites (between 0. 3 and 3. 2% depending on the sample) and reads which did not map on any site considering the stringency applied (between 8. 7 and 15. 5% depending on the sample) were excluded from further analysis (see Supplementary Table  1 ). Reads overlapping genes were counted with the HTSeq Count software in Union mode  (Anders et al. , 2015). Differentially expressed genes were identified using the Bioconductor R 2  packages EdgeR, DESeq and DESeq2  (Anders and Huber, 2010; Robinson et al. , 2010; Love et al. , 2014). Genes with less than 15 reads (from the three biological replicates of two compared samples) were filtered and thus removed from the analysis.
Data were normalized using the Relative Log Expression (RLE) normalization factor for EdgeR and the DESeq normalization factor for DESeq and DESeq2. Gene expression changes with adjusted p-value of less than 0. 05 (by the FDR method from Benjamini-Hochberg) were declared differentially expressed. Differentially expressed genes highlighted by at least one of the three packages were considered for further investigation. Genes were sorted into two lists: one of genes differentially expressed in both pure culture and co-culture and one of genes differentially expressed only in pure culture or only in co-culture. These lists were separately subjected to a Blast2Go analysis  (Conesa et al. , 2005). Blast2Go analysis consisted first of a BlastX 3 on the nr database with 20 hits and a maximum E-value of 1.
Determination of Gene Expression by RT-qPCR Total RNA was retro-transcribed using a High Capacity cDNA Reverse Transcription kit (Invitrogen, Life Technologies, Carlsbad, CA, USA) following the supplier's instructions. Ct of genes of interest (see Supplementary Table  2 ) were determined by RT-qPCR as described by  Delpech et al. (2015). All primers were designed using PrimerExpress R software (Applied Biosystems R , Life Technologies). By comparison with the Ct of the tufB reference gene stable in our conditions (data not shown), expression of a gene of interest ("goi") was calculated using the formula introduced by  Pfaffl (2001). The influence of two experimental factors was studied: the presence of S. aureus (with high or low aeration, gene expression in co-culture divided by gene expression in pure culture) and aeration level (in presence or absence of S.
Effect of Enzyme-Treated Co-culture Supernatants on S. aureus Planktonic Growth Since the inhibition of S. aureus may not be related solely to hydrogen peroxide, we looked for another possible antistaphylococcal molecule produced by L. garvieae in the culture supernatants. We monitored S. aureus growth (OD 600 ) over 24 h in either non-inoculated BHI or in supernatants prepared from H 2 O 2 -free cultures (presence of catalase) with low aeration (either pure culture of S. aureus or co-culture of L. garvieae and S. aureus). In order to avoid any nutritional competition, BHI at a final concentration of 1X was added to each culture. Growth of S. aureus in supernatant from S. aureus pure culture was comparable to that in plain BHI (data not shown). During the stationary phase, the OD 600 measured in S.
Impact of Aeration on the Expression of L. garvieae Genes Potentially Involved in the Antagonism against S. aureus To complete the RNA-seq data obtained only at 9 h, we determined the expression of ten genes from the cultures previously used for RNA-seq analyses, at 6, 9, and 24 h by RT-qPCR. These genes, potentially involved in the antagonism mechanisms, were involved in O 2 consumption (noxE and lox), H 2 O 2 synthesis (pox and sodA), H 2 O 2 degradation (ahpC, ahpF, gpx, and trxB1) and resistance to other peroxides (ohrA and ohrR). The presence of S. aureus induced only slight changes in their expression (data not shown). With high aeration, ahpC and pox were over-expressed 2. 4-fold and 2. 0-fold in the presence of S. aureus at 6 h. With low aeration, S. aureus induced a 3. 1-fold over-expression of trxB1 at 9 h and a 3.
ACKNOWLEDGMENTS The authors would like to thank Adrien Nivoliez for his help in determining the quality of our RNAs in the Probionov laboratory, Magali Cordaillat-Simmons, David Tropel, Laurent Rios, Monique Zagorec, Yves Le Loir, Pierre Renault, Hélène Falentin, and Christophe Chassard for their helpful advice and Maryline Bornes and Harriet Coleman for English proofreading.
Data Collection and Preparation The complete genome, and protein coding sequences of Nematostella vectensis, Aiptasia pallida, and Acropora digitifera, were obtained from NCBI (NCBI Resource Coordinators 2013). Genome data for Hydra magnipapillata was collected through Ensembl (www. ensembl. org) (Flicek et al. 2012)  while the genomes of Stylophora pistillata, Amplexidiscus fenestrafer, and Discosoma sp. are available for download at http://corallimorpharia. reefgenomics. org (Liew et al. 2016). In order to prepare the gene models for the subsequent comparative analyses, we discarded alternative isoforms and only selected the longest gene model for each locus. Further, we removed proteins with fewer than ten amino acids or low sequence quality (>20% stop codons, >20% nonstandard amino acids).