dataesr/scientific-paragraphs-categorization huggingface dataset:
The study was based on data from the EBMT database "Promise" and from those obtained through a questionnaire sent to all participating pediatric EBMT centers. The questionnaire contained questions about pubertal development and measurement of hormone levels at different time points of pubertal development, in particular for girls, the levels of LH, FSH, and 17bestradiol before HSCT and at the last follow-up and the inception of HRT administered for gonadal failure, and for boys, the levels of LH, FSH, and testosterone before HSCT and at the last follow-up. Hormone levels at the last follow-up were measured only in the postpubertal group. The evaluation of anti-M€ ullerian hormone and inhibin B as markers of gonadal function in girls and boys  [16]  was not recorded for the inhomogeneous determination of these markers in participating EBMT centers.
The primary endpoints of this study were to evaluate gonadal function after Bu versus Treo and to analyze the differences in the onset of SP and spontaneous menarche (SM) between patients treated with Bu versus Treo during prepubertal and postpubertal phases. Secondary endpoints were to analyze gonadotropin levels in these 2 groups of patients, number of patients on HRT, and results of sperm analysis. All patients or legal guardians gave their informed consent to the use of their data in retrospective studies. The study was approved by the Institutional Review Board of the Pediatric Disease Working Party and by the Transplant Complication Working Party.
Statistical Analysis Continuous data were summarized using median, interquartile range (IQR), minimum, and maximum values. All categorical/qualitative data were presented using absolute counts and percentage. Patient-, disease-, and transplant-related characteristics of the 2 groups (Bu and Treo) were compared by using the chi-square or Fisher exact test for categorical variables and Wilcoxon test for continuous variables. Analysis was conducted in the 2 groups according to pubertal status at the time of HSCT. For measurement of hormone serum levels at last follow-up, only postpubertal patients were considered, and comparisons were stratified by gender. Two-sided P <. 05 was considered statistically significant. Because of the limited number of patients, multivariate analysis was not conducted.
S1 ). These partitions include the premaxilla, maxilla, jugal (in lizards), nasal, frontal, parietal, squamosal (supratemporal in snakes), jaw joint of quadrate, supraoccipital + otoccipital (supraotoccipital), occipital condyle, basioccipital + basisphenoid, pterygoid, and palatine. Because of the varying number of partitions across specimens, we performed separate alignments and analyses on 4 different datasets: an extant lizard dataset (Fig. 1A ) with 109 taxa and all 13 partitions with 1,222 landmarks and sliding semilandmarks (47 fixed, 595 curve, and 580 patch points); an extant snake dataset (SI Appendix, Fig. S1G ) with 65 taxa and 12 partitions (as a result of the absence of the jugal) with 1,056 landmarks and sliding semilandmarks (44 fixed, 535 curve, and 477 patch points); an extant squamate dataset with 174 taxa and 12 partitions with the same 1,056 landmarks and sliding semilandmarks as the snake dataset; and a combined extant and extinct dataset (SI Appendix, Fig.
Results Morphospace. To visualize the distribution of skull-shape variation, a morphospace was constructed from the first 3 principal components (PCs) of shape data that account for 61. 8% of the total cranial shape variation in the combined extant and fossil dataset (Fig. 2  and SI Appendix, Fig. S2 ). PC1, which accounts for 33. 5% of shape variation, broadly separates lizards and snakes, as suggested by previous studies on skull shape of squamates  (12, 23) , underscoring their distinct cranial morphotypes. Notably, the intermediate space is occupied by a polyphyletic group of fossorial lizards that includes amphisbaenians, annielids, and dibamids. Within lizards, there is a broad separation between Iguania and noniguanian taxa ("Scleroglossa"), although partial overlap exists. The pygopodids (Delma, Lialis) occupy a unique area of the morphospace likely associated with ecomorphological adaptations related to their unique limbless body among gekkotans.
The overall distribution of shape variation, including this taxonomic separation, is similar to that of the extant-only dataset (SI Appendix, Fig. S2 ). PC2 and PC3, corresponding to 16. 6% and 10. 6% of the shape variation, respectively, are both associated with the narrowness of the skull: PC2 relates to the anteroposterior elongation of the parietal, whereas PC3 relates to that of the rostrum (SI Appendix, Figs. S2  and S3 ). Taxonomic groups at and above the family level tend to cluster morphologically (Blomberg's K combined = 0. 675, K extant = 0. 889), congruent with results from 2D skull-shape data in lizards  (23). With PC2 and PC3, the phylogenetic structure is less clear (SI Appendix, Fig. S3B ), suggesting multiple convergences in the evolution of narrow and broad skulls in Squamata.
Shape Disparity and Evolutionary Rates. We fit variable-rates evolutionary models to the data to assess evolutionary mode by using PC scores encompassing 95% of the shape variation. A λ model of trait evolution was supported, albeit weakly, for the extant squamate dataset (SI Appendix, Table  S3 ). However, Ornstein-Uhlenbeck (OU) models were favored for the lizard and snake datasets when analyzed separately, suggesting that each group exhibits different optimum trait values for skull shape. Model fitting supports the λ model for every partition, with the exception of the δ model for the squamosal (supratemporal) and jaw joint (SI Appendix, Table  S3 ). Estimated disparity and evolutionary rates also display a mosaic pattern across partitions. The early history of squamates is characterized by elevated rates of shape evolution in the premaxilla, nasal, jugal, frontal, parietal, and palatine (Fig.
The ancestral squamate skull (SI Appendix, Fig. S7  A and C), based on extant-only and combined datasets, features subrectangular frontals and parietals, most closely resembling the scincid Sphenomorphus solomonis and the lacertid Lacerta with regard to Procrustes distance. The estimated ancestral snake skull (SI Appendix, Fig. S7B ) exhibits a broad nasal articulated posteriorly with the frontal, a relatively deep maxilla, subrectangular frontal and parietal, triangular supratemporal, and a relatively flat mandibular articular surface of the quadrate that is positioned immediately lateral to the otoccipital-basioccipital boundary (i. e. , not far posterior from the occiput). Among sampled taxa, it is closest to the terrestrial lamprophiid Aparallactus modestus in shape. Ecology and Developmental Covariates.
To explicitly test how ecological and developmental factors have driven skull-shape evolution in squamates, we examined the link between disparity and evolutionary rates to key ecological and developmental variables, including habitat, diet, locomotion, and reproductive mode (Materials and Methods and SI Appendix, Table  S5 ). For these analyses, we analyzed the extant-only dataset because of the need for data on ecology and reproductive modes. Reproductive mode is not a clear predictor of cranial shape or mean evolutionary rates (SI Appendix, Fig. S8A ), although weak effect is seen on the occiput in lizards (R 2 < 0. 04; P ≈ 0. 05). In both lizards and snakes, an aquatic lifestyle is associated with higher rates of evolution (Fig. 5B  and SI Appendix, Fig. S8 ). Fossorial and herbivorous lizards also generally exhibit elevated rates of skull evolution (Fig.
These analyses supported the most complex model tested, which considers each characterized partition as a module. As previously described (28), we further inspected the estimated correlation (ρ) values within each partition and each pair of partitions (SI Appendix, Table  S7 ). For the extant dataset with 12 partitions, these criteria pointed to an "occiput" module consisting of supraotoccipital, occipital condyle, and basioccipital + basisphenoid partitions, a "palate" module comprising the pterygoid and palatine, and all other partitions each forming separate modules, for a total of 10 modules in lizards and 9 modules in snakes. Remarkably, results from extant lizard and snake datasets supported the same pattern of cranial integration despite fundamental differences in their cranial architecture as demonstrated by the morphospace analyses.
In snakes, the jaw joint on the quadrate yielded stronger correlations with the supraotoccipital and occipital condyle (ρ between = 0. 59 and 0. 67, respectively) than in lizards, but these partitions were not coalesced into a single module because of their extremely high within-partition correlations  (ρ jaw joint = 0. 99, ρ occipital condyle = 0. 97). Phylogenetically naïve EMMLi and CR analysis  (27)  and analyses of landmark-only and subsampled landmark + sliding semilandmark datasets produced largely congruent results that support these cranial modules (Materials and Methods and SI Appendix, Tables  S7  and S8  and Fig. S9 ). For the combined dataset with 5 regions, EMMLi and CR analysis supported the partitioning of the premaxilla, maxilla, frontal, parietal, and supraotoccipital as separate anatomical modules (SI Appendix, Tables  S7  and S8 ).
3  and SI Appendix, Fig. S5 ), reflecting the unusual morphologies of several extinct clades relative to extant squamates (Fig. 2 ). The phylogenetic relationship of some extinct taxa to other major squamate clades remains unclear, including Slavoia and mosasaurs  (37) (38) (39) (40) (41). Although the placement of these fossils could affect the results of comparative analyses, the extent of this impact on macroevolutionary reconstructions would likely be restricted to their immediate lineages. For instance, rapid rates of evolution tend to be limited to the branches leading to extinct taxa (Fig. 3A ), whereas estimated rates remain similar for other branches compared with the extant-only dataset (SI Appendix, Fig. S5A ). Furthermore, we find congruence between results based on extant-only and combined extant and fossil datasets.
As such, alternative placements of the fossil taxa sampled in this study are not expected to substantially alter the overall results and conclusions of this study, as supported by our analyses of cranial integration and evolutionary rates using alternative phylogenetic placements of Estesia, Polyglyphanodon, and the mosasaur Plotosaurus based on Conrad  (39) , which yielded nearly identical results to the original topology (SI Appendix, Table  S7  and Fig. S5 N-S ). Given the dearth of complete, fully articulated, and minimally deformed skull material of early squamates, 3D reconstructions of estimated ancestral skull shape can provide additional insights into the morphological and ecological origins of lizards and snakes. The ancestral skull reconstruction for crown-group squamates resembles the scincid Sphenomorphus and the gymnophthalmid Colobosaura based on the extant-only dataset, and the lacertid Lacerta based on the combined dataset.
S11 ). Second, the fit between our full landmark + sliding semilandmark dataset to a landmark-only dataset is fairly poor across regions (SI Appendix, Table  S10 ), suggesting that the use of few to several landmarks in each partition is insufficient for characterizing shape variation at this taxonomic scale. Moreover, integration analysis on landmark-only data results in greater correlations between adjacent regions, likely caused by landmarks being largely limited to boundaries between partitions (SI Appendix, Fig. S9 ). Meanwhile, subsampling our full dataset down to 10% of landmarks and sliding semilandmarks within each partition still recovers results that are congruent with our full shape data (SI Appendix, Fig. S9 ). Therefore, we advocate the collection and analysis of high-dimensional GM approach for phenotypic studies, especially when investigating shape variation and covariation across anatomical regions.
Methods Morphometric Data. The taxonomic sampling represents our aim to capture the morphological, ecological, and phylogenetic breadth of Squamata, while considering available computed tomographic (CT) data to facilitate data collection (SI Appendix, Table  S2 ). Our goal was to sample 1 to 3 genera for each extant subfamily, with consideration for including species that exhibit disparate morphological and ecological characteristics (SI Appendix, SI Text). We collected 3D landmark and semilandmark data from high-resolution digital reconstructions of skulls (SI Appendix, SI Text). All mesh files were constructed from CT imaging data or surface scan data (SI Appendix, Table  S2 ). The meshes underwent a systematic protocol in the program GeoMagic Wrap (3D Systems), including virtual filling of small holes, centering, and smoothing to facilitate the placement of surface sliding semilandmarks.
The meshes are freely available for download on Phenome10k (phenome10k. org) and MorphoSource (morphosource. org). We then used Landmark Editor (64) to virtually place and export landmarks and curve semilandmarks on the right side of the skull to delineate the outlines of a priori partitions (SI Appendix, Table  S1 ), including the premaxilla, nasal, maxilla, jugal, frontal, parietal, squamosal (supratemporal), jaw joint of the quadrate, supraotoccipital, occipital condyle, basioccipital + basisphenoid, pterygoid, and palatine (SI Appendix, Fig. S1A ). Coordinate data were not collected from taxa in which cranial osteoderms are inseparable from the skull bones. By using the Morpho R package v2. 5. 1  (65) , template mesh and coordinate data were used to conduct a semiautomated procedure to place surface semilandmarks within these partitions (SI Appendix, Fig.
S1 C  and D ). The template was a hemispheric mesh with simplified geometric representations of partitions defined by corresponding landmarks and curve semilandmarks, as well as regularly distributed surface semilandmarks within these partitions. When they had been mapped onto the meshes of actual specimens, the coordinate data comprising landmarks and curve and surface sliding semilandmarks were mirrored along the median plane to temporarily create a bilateral dataset (SI Appendix, SI Text). Curve and surface sliding semilandmarks on the right side were then slid to minimize bending energy  (66, 67) , and the resulting bilateral landmark + sliding semilandmark data were then subjected to generalized Procrustes alignment  (68, 69). The mirrored left landmarks and sliding semilandmarks were then removed from further analyses.
Snake and extant datasets excluded the jugal partition and surface semilandmarks on the pterygoid and palatine because of the absence of the jugal bone in snakes and the prominent teeth on the latter 2 bones that impeded the placement of surface semilandmarks on these bones. For this study, the supratemporal bone in snakes was considered to be homologous to the squamosal bone in nonsnake squamates, at least functionally (but see ref. 70 ). In the combined extant and fossil datasets, 5 of the 13 partitions (premaxilla, maxilla, frontal, parietal, and supraotoccipital) that are exposed and preserved across all fossil specimens were included. Although effort was made to use predominantly type I landmarks to define partitions that are strictly homologous, this was not possible for such a broad taxonomic sampling.
For this reason, some partitions were delineated by using type II and III landmarks sensu Bookstein (71) as functionally homologous regions. Phylogenetic Tree. To conduct comparative phylogenetic methods, we constructed a time-calibrated phylogenetic tree by using a published timecalibrated molecular phylogeny of extant squamates (72) and incorporating extinct taxa based on previous systematic work  (39) (40) (41) 73)  and fossil occurrence data from the Paleobiology Database (paleobiodb. org). We grafted extinct taxa onto the extant tree by applying the equal-branching method (74) based on the mean of first occurrence age range. Although the phylogenetic placement of Mosasauria within squamates remains ambiguous  (37) (38) (39) 61) , Plotosaurus was placed within the molecular phylogeny as a sister taxon to Serpentes ("Pythonomorpha hypothesis") and Polyglyphanodon as sister to iguanians in accordance with the phylogeny based on combined molecular and morphological data  (40).
Although uncertainty in topology and branch lengths may alter the results of comparative analyses, we find that large-scale patterns are robust to alternative phylogenetic positions of extinct taxa, which generally have greater uncertainty in terms of position and thus may be expected to have the greatest potential to impact the outcome of analyses (SI Appendix, SI Text). Furthermore, congruent results between extant-only and combined datasets, as well as alternative placements of fossil taxa (SI Appendix, Table  S7  and Fig. S5 ), suggest that the results and conclusions are robust to the inclusion, removal, and alternative phylogenetic positions of fossil specimens. Ecological and Life History Data. Existing literature was used to collect ecological and developmental data for extant taxa (SI Appendix, Table  S5 ).
We collected data on locomotion (ground dweller, swimmer, climber, climber/ glider, digger, litter dweller, and combinations of these categories), habitat (terrestrial, fossorial, semifossorial, aquatic, semiaquatic, arboreal, semiarboreal, saxicolous, leaf litter, and combinations of these categories), diet (carnivorous, herbivorous, invertivorous, omnivorous), and reproductive mode (oviparous, viviparous). Because of the small number of ovoviviparous taxa, they were considered to be viviparous for regression analysis of reproductive mode. The definitions for these categories are provided in the SI Appendix. Although assigning categorical variables to a continuous trait is difficult, we used established categories known for species sampled in this study. Foraging and stomach content data for several taxa are unknown (SI Appendix, Table  S5 ), and these taxa were excluded from MANOVA and rates analysis on diet preference.
Data Analysis. Analyses were largely conducted in R v3. 4. 1  (75). First, a disparity-through-time plot was created for the individual partitions by using the dtt function in the GEIGER R package v2. 0. 6  (76, 77). Second, we used BayesTraitsV3 (78) to estimate evolutionary rates for the overall skull and its partitions based on PCs accounting for >95% of total shape variation (SI Appendix, Table  S3 ). All available evolutionary models were tested, including BM, OU, δ, κ, and λ models. Bayes Factor was used to determine the best-supported evolutionary model. Estimated rates based on the preferred model were used to generate a rate-through-time plot for each partition. Total disparity (Procrustes variance) and mean evolutionary rates under the BM model were calculated within each model and for each landmark and sliding semilandmark by using the morphol.
disparity and compare. multi. evol. rates functions in the geomorph R package v. 3. 0. 5  (79, 80) , respectively. We simulated shape evolution under BM model by using the sim. char function in GEIGER R package. Ancestral shapes were calculated by using the anc. recon function in the Rphylopars R package v0. 2. 9 (81) on extant-only and combined datasets. The geomorph R package was used to assess allometry, phylogenetic signal, evolutionary allometry, and phylogenetically corrected correlations with ecological and reproductive variables in partition-specific and whole skull-shape data by using the functions procD. allometry, physignal, and procD. pgls (SI Appendix, Tables S6, S9, and S11). Because of the proportionately low contribution of (evolutionary) allometric signal, we did not correct for allometry in the datasets for other analyses.
To identify cranial modules from partitions, we employed EMMLi  (26) , a maximum-likelihood approach, and CR analysis  (27) , which is implemented in geomorph. By using the results output by EMMLi, we further assessed the pattern of integration by comparing estimated within-module correlations (ρ within ) with the estimated between-module correlation (ρ between ) for each pair of partitions (SI Appendix, SI Text). We applied a subsampling approach to ascertain the robustness of these results by running 100 repetitions of EMMLi with 10% of the total landmark dataset while keeping a minimum of three landmarks + sliding semilandmarks per partition, which consistently returned the same pattern of cranial modules, as did analyses limited to landmarks only (SI Appendix, Fig. S9 ). Results from EMMLi and CR analyses with and without phylogenetic correction yielded largely congruent results (SI Appendix, Tables  S7  and S8 ).
ACKNOWLEDGMENTS. We thank  Kristin Mahlow  and  Erin Westeen  for data collection assistance;  Eve Noirault  for reconstruction assistance;  Henry Ferguson-Gow  and  Léo Botton-Divet  for methodological assistance; and 2 anonymous reviewers for their constructive comments. European Research Council  (Grant  STG-2014-637171  to A. G. ),  National Science Foundation  ( EF-0334961  to J. A. M. ),  Deutsche Forschungsgemeinschaft  ( Mu 1760/7-1  to J. M. ),  European Council  ( Synthesis of Systematic Resources [SYNTHESYS] Grant   DE-TAF-6532  to A. W. ), and  Paleontological Society  ( Newell Grant  to A. W. ) funded this study and the data collection.
Acknowledgments We thank  Y. Bellaiche ,  O. Hamant ,  A. de Saint Germain ,  J. Traas  and members of the  FTA group  for helpful discussion and comments on the manuscript. The greenhouse staff of the IJPB is acknowledged for excellent plant care and we thank  M. Goussot  for technical assistance. This paper is dedicated to the memory of the late Olivier Grandjean who was a great help with confocal microscopy.
This work was supported by the  Agence National de la Recherche grants MorphoLeaf  (project reference  ANR-10-BLAN-1614 ) and  LeafNet  (project reference  ANR-12-PDOC-0003 ). MC was partly supported by the  Fundacion Alfonso Martin Escudero. The IJPB benefits from the support of the  Labex Saclay Plant Sciences-SPS  ( ANR-10-LABX-0040-SPS ). The funders had no by the  CUP-SHAPED COTYLEDON2 (CUC2 ) boundary gene.
These studies included 1807 children. After PCV implementation (PCV7 then PCV13), we investigated otopathogen carriage in 4405 children with AOM from 2001 to 2014  [35]. In both studies, the following data were collected: sex, age, history of AOM, antibiotic treatment during the previous 3 months, daycare attendance modality, vaccination status, and clinical symptoms (temperature > 38. 5 °C, otalgia and/or conjunctivitis). Finally, 1779 children came from unpublished studies with the same design.
Statistical analysis Double data entry involved use of the software 4D v12. 5. Statistical analysis involved use of Stata SE 13. 1 (Stata Corp. , College Station, TX, USA). Pearson chi-square test or Fisher exact test was used to compare groups (two-tailed tests). Potential risk factors were identified by univariate analysis (p < 0. 25) and introduced in multivariate logistic regression models. Only significant risk factors (p < 0. 05) remained in the final model. For statistical analysis, we merged strong and moderate biofilm-producing bacteria to compare 2 groups: "moderate or strong biofilm-producer" versus "low biofilm-producer" for both NT-Hi and S. pneumoniae. P < 0. 05 was considered statistically significant.