dataesr/scientific-paragraphs-categorization huggingface dataset:
PMSI database The French PMSI-MCO (Médecine, Chirurgie, Obstétrique) is an exhaustive medico-administrative hospital discharge database which covers all overnight or day hospitalisations in the public and private sectors involving short-term stays in medical, surgical or obstetric facilities. [16]  The database is used by the French health authorities to manage funding of all hospital services. Each year, almost 30 million stays by over 13 million patients are reported in this database. Information is exhaustive for all public and private hospitals in France and no sampling is performed. In the PMSI, all hospital stays are attributed to a diagnosis-related group (DRG) reflecting the reasons for hospitalisation. These are identified by the physician through International Classification of Diseases, 10th revision (ICD-10) codes,  [17]  either as principal diagnoses (PD: the condition for which the patient was hospitalised), related diagnoses (RD: any underlying condition which may have been related to the PD) or as significantly-associated diagnoses (SAD: comorbidities or complications which may affect the course or cost of hospitalisation).
Study population All hospital stays in France with at least one CCAM code for AUB surgery associated with at least one ICD-10 code for idiopathic AUB documented as a PD or RD of the medical unit where the CCAM surgery was coded were identified from the PMSI-MCO database between 1 st January 2009 and 31 st December 2015. These codes are listed in S2 Table and S3 Table, and exclude post-menopausal bleeding. Only women aged between 35 and 55 years were retained. The reason for the lower age limit of 35 years was to exclude a majority of women who wished to remain fertile, since all the procedures evaluated (with the exception of curettage) are only indicated in women who no longer wish to have children. As this is not documented in the PMSU database, the age threshold was used as a surrogate criterion.
Data collection The socio-demographic characteristics of patients were collected at inclusion (age). For each initial index hospital stay, the distribution per type of hospitalisation was analysed: overnight or day hospitalisations. For patients operated on before mid-2014, outcome and complication rates was documented at 18, 24 and 60 months. Total in-hospital medical resource consumption associated with all hospitalisations occurring within the period from the initial index hospitalisation up until any stay for failure or complication was documented. Medications prescribed or delivered during outpatient consultations was not considered, as they were not documented in the database.
Costing Per capita costs at 18 months after idiopathic AUB surgery were determined for each cohort. Costing was restricted to direct costs and determined from the perspective of the French social security system (National Health Insurance; NHI). Costs were attributed from official French national tariffs for medical acts applicable in France from 2009 to 2015, and were expressed in 2017 Euros by adjustment by the a relevant Consumer Price Index. A standard national tariff was applied to each hospitalisation based on the DRG code attributed in the PMSI database. These standard tariffs include medical and related procedures, nursing care, treatments (except specific expensive drugs and implants), food and accommodation, and investment costs for hospitalised patients. Additional costs per day of hospitalisation in an intensive care unit were added to the DRG tariffs when appropriate.
For private hospitals, where physicians are reimbursed on a fee-for-service basis, physician fees were identified from the ENCC (Echelle Nationale des Coûts à méthodologie Commune, the French observatory of real-world spending on healthcare) and added to the DRG tariffs. For public hospitals, where physicians are salaried, physician fees are included in the DRG tariff, which takes it into account all personnel costs. Expensive drugs and implants were costed using the retail price listed in the public FICHCOMP database and the official tariff for the private database. For expensive drugs and implants used in 2009, their costs were attributed on the basis of the mean FICHCOMPderived costs in public hospitals for 2009, as 2009 FICHCOMP was not available for private hospitals.
Statistical analysis Categorical data were expressed as proportions and analysed by using the χ2 test or the Fisher exact test. Univariate statistical tests for continuous data included tests of mean differences with Student's t-test. Occurrence of outcomes (treatment failure or complications) were followed over time using Kaplan-Meier survival curves and outcome rates compared between 2G procedures (as the reference) and the three other procedures using Mantel-Cox log-rank test (unadjusted univariate analysis). A P values of <. 05 was used to determine the statistical significance of all tests used. Analyses were performed by using the R statistical software (version 3. 2. 3).
Study population Between 1 st January 2009 and 31 st December 2015, 152,531 35-55 year old women hospitalised for surgery for idiopathic AUB were identified in the PMSI database, of whom 42,647 presented at least one exclusion criterion and were excluded. The cohort of patients available for analysis thus consisted of 109,884 patients. Of these, 88,165 could be followed for 18 months, 80,054 for 24 months and 33,251 for 60 months. The flow diagram for the selection of patients is illustrated in Fig  1. The mean age of the participants was 46 years, with no difference in age between surgery types (S1 Table ).
This was essentially driven by a decrease in the number of women undergoing curettage, which decreased by 37%. A concomitant doubling in the number of 2G procedures over the same period was insufficient to compensate for the fall in the number of curettages. In addition, sales of IUD in France decreased over the same period  [18] , which means that a shift to non-surgical interventions cannot account for the fall in the number of women undergoing surgery for idiopathic AUB. The principal strengths and weaknesses of the study derive from the use of the PMSI database as the data source. Among the strengths, the database is exhaustive and all cases of surgery for idiopathic AUB will have been captured, and their hospital follow-up tracked comprehensively. Moreover, the large number of cases documented allows the study outcomes to be determined with precision.
Bias due to sampling errors and to loss to follow-ups should be minimal (due to the comprehensiveness of the database) and coding errors are believed to be rare. Nonetheless, since the tariffs for 1G and 2G procedures are different, it is possible that certain 2G procedures will have been coded as 1G procedures in order to benefit from more advantageous reimbursement. A major weakness is that the reasons for the choice of specific surgical acts are not documented, and this is a particular issue in imputing causal links between surgery and complications. However, the objective of the study was not to analyse the reasons underlying the choice of surgical procedure, but to describe the surgeries actually performed for the treatment of idiopathic AUB. Moreover, the database does not include data on histological findings on the surgery material, so the diagnosis of idiopathic AUB could not be ascertained in this way.
In addition, the PMSI database is only available since 2006, and for this reason, women who had undergone surgery prior to this date may have erroneously been considered as incident cases. Finally, the PMSI database only contains information on care delivered in hospitals, and thus care provided in the community is not identified, which might underestimate the real cost and precludes obtaining an exhaustive treatment history for each patient. It is important to note that this study was restricted to women with idiopathic AUB aged 35 -55 years old. The lower age threshold was set in order to discourage inclusion of women wishing to remain fertile, as the procedures evaluated in the study (except curettage) are reserved for women who no longer wish to have children. Since the age criterion is not a perfect one, it is quite possible that certain women over 35 who still wanted to have children were included, which would have inflated the number of women undergoing curettage.
Given this age distribution, any bias related to this would be expected to be minimal. The widespread use of curettage is surprising since, according to the 2010 French guidelines,  [1]  it is only considered acceptable when preservation of fertility is required. No information is available in the PMSI database on whether the women treated desired to remain fertile or not, but given the age group included (35-55 years), it may be considered that participants would be less likely to wish to remain fertile than younger women. In the 2013 Netherlands guidelines  [11]  and the 2018 Anglo-Welsh guidelines,  [12]  curettage is no longer recommended in any context. Further research is needed to identify why curettage remains so widely used in France and to identify barriers to its replacement by more effective surgical procedures.
These are substitutions that have occurred repeatedly in convergent lineages, towards the same derived state, or towards similar derived states (e. g. towards amino acids with similar biochemical profiles). Methods vary in how they quantify the similarity between substitutions, resulting in different sets of candidate substitutions  [1] [2] [3]. Finding foreground convergent (causative) substitutions among many substitutions in genomes containing billions of sites is a challenge in modern bioinformatics. Several processes at work in genome evolution may affect the number of convergent substitutions in a given dataset. For instance, mutational biases, changes in recombination rates, biased gene conversion (bGC) or changes in population size may inflate or diminish the number of convergent substitutions.
However, the precisions and sensitivities observed here are much worse than those reported in  [18] , because simulations do not use the PCOC model, which enforces substitutions on all transition branches. Note that diffsel, which performs well in our experiments, is also the most expensive method computationally by several orders of magnitude (table  1 ). Other methods may be preferable for large datasets unless extensive computing resources are available. The better performance of profile methods may be owing to their fitting the simulation conditions better. However, it is unclear how we could have simulated convergent evolution realistically without using mutation-selection models that use profiles of amino acid frequencies. In the end, this indicates that profile methods may perform better on empirical data as well; apart from diffsel, which always comes out first, the variability of the AUC ranks among trees, however, indicates that using several methods on a dataset is recommended.
We then ran the seven methods on two previously published datasets, where a list of convergent sites had been proposed  [20, 24, 28]. In these articles, the detection of convergent sites was performed by a version of the identical method for Cyperaceae, and by either diffsel or a dN/dS analysis for Amaranthaceae. Note that in the original diffsel article, the method was run with slightly different settings: it evaluated fitness profiles separately for the sister clades of convergent clades. In this article, diffsel was instead set up to only evaluate one profile per site for convergent clades and one profile per site for the rest of the tree. This change was done to make diffsel results more comparable with other methods and explains the differences with the original results. We compared the ranks of these previously reported convergent sites across methods.
The alignments and the ranks are available in electronic supplementary material, figures S10 and S11, along with further discussion. Overall, the methods tend to agree with each other and rank the previously reported convergent sites among their best candidates (figure  5 ). In particular, most profile methods are in strong agreement with the publications; this is especially true for TDG09. Some methods fail to find any or nearly any convergent evolution on the Amaranthaceae alignment (identical, multinomial, topological), which is consistent with our results on data simulated on the same tree (figure 3a(ii)). These methods have a more consistent behaviour on the Cyperaceae dataset. For both datasets, most of the sites that have low ranks have low ranks across methods. For instance, this is the case for sites 733 and 770 in Cyperaceae, and 143 and 439 in Amaranthaceae.
(c) Pipeline and implementation of the methods The results in this article were obtained using an all-in-one pipeline that encompasses simulations, detection and post-simulation analysis, including the generation of the plots used for figures 3 and 4. The pipeline itself was implemented in OCaml using bistro (https://github. com/pveber/bistro), a library to build statically typed reproducible workflows. Special attention was paid to reproducibility, in particular, by following the guidelines given in  [31]. Instructions to reproduce our results are given in the electronic supplementary material. The implementations of the methods used in the pipeline are as follows: -The multinomial method has been implemented de novo in Python as well as the identical and topological methods which additionally use executables from the bppsuite  [30].
They are available via the pipeline. -The TDG09 implementation we used is a slightly modified version of the one available on github (table  1 ) where multithreading has been removed to avoid multithreading-related problems. Results should be identical to the github version. In addition, a script available in the pipeline repository was written to adapt input alignments and trees to TDG09 expected formats. -For diffsel, we used an optimized version of the original implementation that is faster but implements the same model. The implementation we used is available on github (table  1 ). In addition, we use a different approach to establish MCMC convergence. The original method compares two MCMC chains using the tracecomp program from the Phylo-Bayes suite  [32]. Instead, we run only one chain, use the Raftery and Lewis's Diagnostic implemented in the R package coda (v0.
Conclusion Our simulation results reveal the performance of existing methods to detect two different types of convergent amino acid evolution on simulated data, in isolation or combined with each other. The simulations have been performed with complex models of sequence evolution, parametrized so as to generate datasets that resemble empirical data on a few test statistics. However, some key assumptions underlying those models are clearly unrealistic: first, each site is simulated independently of the others. It would be useful to incorporate epistatic constraints in our simulations as those increase the number of background convergent substitutions  [16]. Such a model has been proposed  [16, 17] , but the current implementation can only work one branch at a time, not along a tree topology.
In all cases, they will be based on profile methods anchored in a mechanistic modelling of sequence evolution. As a first direction, we need to complement models of sequence evolution so that, in addition to profile changes, we can also accurately detect changes in selection efficacy and distinguish those adaptive processes from confounding factors such as bGC and ILS. Further anchoring the model in population genetics theory may allow the interpreting of detected sites in terms of the fitness advantage they provide. As a second direction, we need to improve the computational efficiency of model-based inference. This should be a major concern here, because datasets are getting larger every year; algorithmic or mathematical developments will probably be necessary to fit such complex models onto large datasets.
None of those features have been tested but are crucial for application to real data, in particular, for application to genome-wide datasets. Future analyses will have to investigate these aspects. Data accessibility. Our pipeline's code is available at https://gitlab. in2p3. fr/pveber/reviewphiltrans. It contains everything required to reproduce our results. Detailed reproduction instructions are given in electronic supplementary material, §9. All intermediate data used to produce our results (approx. 20 Go) are available from the Dryad Digital Repository: https://doi. org/10. 5061/dryad. 57hr00q/1 [35].
Acknowledgements. We would like to thank  G. Didier  for providing a modified version of msd that can work on individual sites and  T. Latrille  for providing the profiles and fruitful discussions. This work was performed using the computing facilities of the  CC LBBE/PRABI. We would like to thank the  French Institute of Bioinformatics-IFB CNRS UMS 3601 -(funded as part of  Investissement d'avenir program  managed by  Agence Nationale pour la Recherche , contract  ANR-11-INBS-0013 ) for providing life science data and tools, storage and computing resources on the IFB national service infrastructure in bioinformatics.
Acknowledgments AMD is an  FNRS Postdoctoral Researcher  under the project  CR28075116. He acknowledges support from the  EOS -contract  O013018F. JLJ is grateful for support from the  European Research Council  under the  Advanced Grant NuQFT. The authors thank the staff and members of the  School of Mathematics and Statistics at the University of Melbourne  for their kind hospitality during a simultaneous visit in 2018. The authors thank  Yacine Ikhlef ,  Philippe Ruelle  and  David Ridout  for helpful discussions, and  Gilles Parez  for proofreading the manuscript.
Model framework for colorectal cancer and cardiovascular risk assessment attributable to the consumption of red meat The model was developed for males and females more than three years old. The age classes were  3-24, 25-44, 45-64, 65-84  and ≥ 85 years old. These age classes were defined in accordance with the age classes of the incidence data. The flowchart of the risk assessment model is presented in Fig. 1. From red meat consumption in France, epidemiological studies, and French data on incidence of the outcome, the baseline probability of the outcome without red meat consumption was estimated. From this, the distribution of red meat intake in France, and the proportion of red meat consumers, the probability of the outcome with and without red meat consumption was calculated. Then the probability of the outcome specifically due to the consumption of red meat was estimated.
Red meat consumption in France Red meat consumption in metropolitan France was evaluated between 2005 and 2007 for males and females from 3 to 79 years old by the dietary survey INCA 2 (ANSES, 2014). A more recent dietary survey (INCA 3) was available (ANSES, 2017), but, unfortunately, the raw data were not accessible. Nevertheless, French food habits did not change over time regarding meat consumption. Indeed, for adults, for example, we observe only a slight decrease of the mean (49. 7 g/d versus 47. 3 g/d)  (ANSES 2014 and 2017). From the original data (ANSES, 2014), we exclusively selected the individuals who responded to the 7-day survey, which corresponds to 96% of the survey participants. Information about red meat consumption for individuals less than 3 years old and over 79 years old was not available.
We then assumed that the consumption distribution of people in the age classes 65-84 and ≥ 85 years was the same as for people from 65 to 79 years old. The consumption of red meat took into account the consumption of unprocessed beef, pork, lamb and veal. More information about the individuals included in the study and the mean quantity of red meat consumed is available in Tables  1  and 2. From these consumption data, two variables were calculated: the mean consumption for each age class and gender and the probability density of consumption for red meat eaters. To estimate this latter, the function fitdist of the package fitdistrplus in the R software package (version 3. 4. 0) was used. Based upon the Akaike Information Criterion (AIC), the Gamma distribution provided the best fit, among the Weibull, Normal, Lognormal and Gamma distributions.
, 1991). BLAST analysis of the sequence through the National Center for Biotechnology Information (NCBI) server (http://blast. ncbi. nlm. nih. gov) revealed a similarity of 100% with the 16S rDNA sequence of C. burnetii (GenBank accession NR_104916. 1), with an overlap identity of 861/861 bp. This result was confirmed with a C. burnetiispecific real-time PCR conducted by the French National Reference Centre for Q fever (Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France)  (Eldin et al. , 2017). Additionally, positive Q fever serology was also observed, with phase I IgG ! 1:2048, phase II IgG ! 1:2048, phase I IgM of 1:512 and phase II IgM of 1:64. The serological profile with strongly positive phase I IgG serology was also in favor of persistent focalized infection  (Eldin et al.
A B Fig 3% and was comparable between the libraries (Additional file 1: Figure  S1 ). The correlation between the libraries that was calculated using the log 2 of the normalized counts of expressed miRNAs was R = 0. 96, indicating a strong correlation between the Holstein and Montbéliarde libraries (Additional file 1: Figure  S2 ). A total of 754 miRNAs were identified using miRDeep2 software, 738 of which were known and 16 were predicted miRNAs. The latter may be considered to be potentially novel miRNAs. These results are in accordance with data previously obtained using NGS technology in bovine MG that reported 487 known bovine miRNAs, 167 of which were miRNAs that were already known in other species  [14]. However, the number of predicted novel miRNAs was higher in the study by Le Guillou et al.
[14]  than in our study (679 vs 16, respectively). In the present study, we used the latest miRBase version, which includes a large number of known miRNAs, and this could explain the lower number of predicted miRNAs. The 25 most abundant miRNAs in the MG represented 90. 6% of the total reads. Among them, four (miR-143, miR-30a-5p, miR-148a, and miR-10b) represented more than 50% of the total reads (Fig. 2 ). A comparison of the MG miRNomes of Holstein and Montbéliarde cows using the DESeq2 package allowed the identification of 22 miRNAs that were differentially expressed (P adj ≤ 0. 05; Table  2 ) between the breeds. Among them, 11 were up-and 11 were down-regulated in Holstein cows compared to Montbéliarde cows, and 17 were found to correspond to more than 20 reads on average. Six (miR-16a, miR-186, miR-25, miR-100, mir-30e-5p and miR-146b) corresponded to more than 5, 000 reads on average.
Role of the 6 most differentially expressed miRNAs The hierarchical classification of DEMs using Permut-Matrix software allowed the classification of cows according to their breed and the clustering of miRNAs according to their level of expression (Fig. 4 ). Three groups were identified. The first group corresponded to miR-186 and miR-30e-5p, both of which showed a high expression level. The second group comprised miR-25, miR-16a, miR-100, and miR-146b, which showed an intermediate expression level. The third group comprised DEMs with low expression. Only the first and second groups (containing 6 miRNAs: miR-100, miR-146b, miR-186, miR-30e-5p, miR-25, and miR-16a) were considered for further investigation and discussion. RT-qPCR analyses were performed for miR-25, miR-146b, miR-100, and miR-186, and miR-25, miR-146b, and miR-186 showed the same expression pattern as that obtained using RNA-Seq (Additional file 1: Table  S1 ).