dataesr/scientific-paragraphs-categorization huggingface dataset:
Design and setting This was a retrospective analysis of treatment-na€ ıve eyes that had received intravitreal VEGF inhibitors for mCNV, defined as a new diagnosis of CNV in eyes with investigator-reported high myopia [refractive error of À6. 00 Diopters (D) or greater myopia or axial length of 26. 5 mm or greater] associated with myopic lesions of the posterior pole tracked in the prospectively designed observational database -The Fight Retinal Blindness! (FRB!) Registry  (Gillies et al. 2014). Eyes with coexisting dome-shaped maculopathy or myopic tractional maculopathy and other ocular conditions unrelated to high myopia were excluded. Participants in this analysis included patients from practices in Australia, France, New Zealand, Spain and Switzerland. Institutional review board approval was obtained, and all patients gave an informed consent.
Data sources and measurements Data were obtained from each clinical visit, including the visual acuity (VA), the CNV activity, the presence of subretinal fibrosis (SRFi) and macular atrophy (MA), treatment given, procedures and ocular adverse events Visual acuity (VA) scores were expressed as the number of letters read on a logarithm of the minimum angle of resolution VA standard ETDRS chart. The diagnosis and the activity of mCNV (active or inactive) were confirmed by the treatingphysician based on findings from clinical examination (sudden onset of visual loss or metamorphopsia or the presence of macular haemorrhage), optical coherence tomography (OCT) and dye-based fundus angiography (imaging features of subretinal or intra-retinal fluid or haemorrhages), alone or in combination, at each visit.
Discussion We used the FRB! International observational outcomes database to explore the 24-month outcomes of VEGF inhibitors for treatment-na€ ıve mCNV eyes of patients predominantly of Caucasian origin in routine clinical practice. The overall model estimated mean (95%CI) improvement in VA over 24 months was +8 (5, 11) letters in all eyes. There were 29% of treated eyes completing 2 years that gained at least three lines of vision after a median (Q1, Q3) of 4 (2, 7) injections. Our study found similar visual outcomes with a previous 1-year outcomes real-world study of predominantly Caucasian mCNV patients treated with ranibizumab  (Hamilton et al. 2020). Whether mCNV behave differently in Asian and Caucasian eyes, as neovascular age-related macular degeneration does  (Mohamed, Gadhvi & Mensah 2018; Kokame et al.
2016). Our data are representative of a wide variety of international practices and practitioners. Though there is variability in the quality of data in observational studies, the FRB! system includes quality assurance measures that preclude out of range and missing data  (Gillies et al. 2014 ). To our knowledge, this is the largest long-term comparative retrospective study on VEGF inhibitors in mCNV to date, with 203 eyes included in the analysis. Our analysis also included mostly Caucasian patients, whereas most previously published reports included mainly patients of Asian origin. Our study gives additional data on longterm treatment outcomes and function predictive factors of myopic CNV in this specific population. We also included data from baseline multimodal imaging of SRFi and MA, which have both a significant impact on the outcomes of macular CNV.
Exome sequencing DNA from the index case and his parents was subjected to whole exome sequencing (WES) using Nextera Rapid Exome Capture (Illumina)(Supplementary material). Exonic and splice site variants with a minor allele frequency of <1% in external databases (i. e. ExAC, 1000 genomes) were prioritized. In silico prediction tools such as Polyphen2 (http://genetics. bwh. harvard. edu/pph2/), CADD (https://ca dd. gs. washington. edu/) and SIFT (http://sift. jcvi. org/) were used to assess pathogenicity.
WES reanalysis The fastq files for the index case and his parents were submitted to Solve-RD  [7]  through the Genome-Phenome Analysis Platform (GPAP, https://platform. rd-connect. eu/) as part of the European Reference Network for Neuromuscular Disease (ERN-EURO-NMD, https://ern-euronmd. eu/), and processed using the RD-Connect bioinformatics pipeline  [8]. The reanalysis strategy carried out by the SNV-Indels Working Group  [7, 9]  implemented automated data filtration to specifically identify previously reported disease-causing variants (as annotated in ClinVar v. 13-01-2020) from a candidate gene list of 594 genes known to be associated with NMD  [9]. The identified variant has been submitted to ClinVar (SUB8878662; https://www. ncbi. nlm. nih. gov/clinvar).
Mass spectrometry based proteomic analysis Control and patient-derived fibroblasts were grown to a 70% confluency and mechanically harvested. Label free shotgun proteomic analysis was performed as previously described  [10]. To interrogate protein-dysregulation pathways a Gene Ontology (GO) term analysis was performed. Proteomaps (www. proteomaps. net) was used to visualise affected cellular functions. The mass spectrometry proteomics data was submitted to the ProteomeXchange Consortium via the PRIDE (PXD023584; https://www. ebi. ac. uk/pride).
Proteomic findings To further validate the pathogenicity of the detected variant and to obtain biochemical insights into the underlying pathophysiology, a proteomic profile on patient-derived fibroblasts was carried out. Applying a data independent acquisition (DIA) approach, a total of 3558 proteins were quantified. Among these, 323 were significantly dysregulated (p-ANOVA ≤ 0. 05): 143 (4. 2%) and 180 (5. 6%) proteins showed increased and decreased abundance, respectively. An intersection of dysregulated proteins with genetic variants revealed no significant correlations. Proteomaps and a GO term analysis revealed a dysregulation of diverse signaling cascades including the NF-kappa-B pathway. We also detected an increased abundance in proteins of the RNA-processing machinery, while decreased proteins suggested impaired exosomal activity (Fig.
Radboud Institute for Molecular Life Sciences, Nijmegen, the Netherlands; Neuropaediatrics Department, Institut de Recerca Pediàtrica Hospital Sant Joan de Déu, CIBERER, Barcelona, Spain; 35 Dubowitz Neuromuscular Centre, UCL Great Ormond Street Hospital, London, UK; 36 Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK Funding The Solve-RD project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 779257. Several authors of this study are members of the European Reference Network for Neuromuscular disease, Project ID No 739543. This study was supported by the AFM (grant 21644 to AR), the framework of the NME-GPS project by the European Regional Development Fund (AR/US/AS), the support by the Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen, the Regierende Bürgermeister von Berlininkl.
Items 3 to 16 of the survey were about demographics, training, integration into the labor market, and scientific and leadership involvement. The survey link was again made available through survio. com, remaining online from July 16, 2018, to September 15, 2018. Participants were invited once via the Brazilian Society of Angiology and Vascular Surgery (SBACV) institutional email account. The population was estimated at 810 women vascular surgeons linked to the abovementioned society, according to the institution's database. Assuming a confidence level of 95% and a maximum margin of error of 4% and using the OpenEpi  13.
Statistical analysis Questionnaires with a "No" answer to item 1 requesting informed consent were excluded from analyses. SPSS for Windows version 25. 0 (IBM Corp. , Armonk, NY, USA) was used for tabulation and analysis. Results are presented as numbers and percentages. The odds ratio chi-square test was used for categorical variables and the non-parametric Pearson's chi-square test was employed for continuous quantitative variables. For all analyses, a value of p ≤ 0. 05 was established.
RESULTS From a total of 810 invitations sent out, 287 questionnaires were answered. All participants marked "Yes" in response to the informed consent question. Due to inconsistencies in the registration data collected for item 2, 6 questionnaires were excluded, resulting in a total of 281 valid responses. The data collected in the pilot study were not included in the present study. The full questionnaire is shown in Supplemental Table  1.
Masting characterizes large, intermittent and highly synchronous seeding events among individual plants and is found throughout the plant Tree of Life (ToL). Although masting can increase plant fitness, little is known about whether it results in evolutionary changes across entire clades, such as by promoting speciation or enhanced trait selection. Here, we tested if masting has macroevolutionary consequences by combining the largest existing dataset of population-level reproductive time series and time-calibrated phylogenetic tree of vascular plants. We found that the coefficient of variation (CV p ) of reproductive output for 307 species covaried with evolutionary history, and more so within clades than expected by random. Speciation rates estimated at the species level were highest at intermediate values of CV p and regional-scale synchrony (S r ) in seed production, that is, there were unimodal correlations.
Speciation may also be slower in species with high S r , which promotes gene flow and therefore limits reproductive isolation. Although the potential selection effects can act in opposite ways, overall there are more mechanisms for promoting faster trait evolution with higher values of both CV p and S r through pollinators, seed dispersers and pollen competition (figure  1 ). Our aim was to explore whether masting behaviours have wider implications for species and phenotypic diversification beyond their selective advantages for individual fitness  [11]. We exploited a new database of 5057 population-level reproductive time series from 682 species-the largest synthesis of reproductive time-series data to date  [25]. We first explored the utility of this database for evolutionary inference by comparing biases in the macroevolutionary characteristics of its species with the wider plant ToL.
Methods (a) Reproductive time series Seed and fruit data were obtained from MASTREE+  [25]. MASTREE+ comprises species-specific time series of annual reproductive effort for perennial plants and includes measures of flower, pollen, fruit and seed production from wild-grown populations (agricultural crops and experimentally manipulated plots were excluded). Data were extracted from the published and grey literature and unpublished datasets. A single time series is considered the set of annual observations described by a unique combination of species, sample location, reproductive variable (e. g. flower, fruit, seed) and measurement unit (e. g. fruit m -2 ). We subset MASTREE+ to include only time series with observations of fruit, cone or seed production. We restricted our analyses to time series with at least five consecutive years of observations to analyse a larger sample size while maintaining a time series length comparable to previous work  [1, 4, 5, 28]  and similar in CV p to longer time series (electronic supplementary material, figure  S1 ).
(b) Phylogenetic data and macroevolutionary estimates We analysed two complementary measures of speciation in the plant ToL. We focus on speciation, rather than diversification, because our predictions of potential masting effects on macroevolution involve changes in speciation, not extinction rates. First, we used existing estimates of speciation rates generated for 73 934 vascular plants with Bayesian analysis of macroevolutionary mixtures (BAMM)  [26]. BAMM models heterogeneity in speciation and extinction through time and across lineages and can account for non-random incomplete taxon sampling  [29]. It has been extensively validated for estimating speciation rates  [30, 31]. The BAMM speciation rate estimates we obtained here were generated using the most comprehensive time-calibrated phylogenetic tree of seed plants presently available, i.
e. GBOTB in Smith & Brown  [32]. Second, we estimated speciation rates with the diversification rate metric (DR)  [33]  using the GBOTB phylogeny. DR considers only branch lengths and splitting events and does not accommodate incomplete taxon sampling  [33] , so we focus on BAMM-derived rates in the main text. We used the GBOTB phylogeny for all subsequent analyses that required a phylogenetic tree. We also tested if masting was associated with the rate of evolutionary change in an important reproductive trait, seed size, which should be under selection from both seed dispersers and predators  [34, 35]. We collated existing estimates of the rate of seed size evolution across the plant ToL generated for 13 579 angiosperms  [27]. Briefly, seed mass data were obtained from the Royal Botanic Gardens Kew Seed Information Database (http://data.
(d) Biases in masting data MASTREE+ has positive biases to long-lived, woody species from temperate latitudinal regions, so we also tested if it had macroevolutionary biases or was generally representative of the plant ToL. We did so by comparing the speciation rates (both BAMM and DR) and rate of seed mass evolution, of our 307 study species to all other seed plants in the GBOTB phylogeny (n = 79 574). BAMM speciation rate and seed mass evolution were compared between groups using structured rate permutations on phylogenies (STRAPP) via the traitDependentBAMM function in the 'BAMMtools' package  [42]  in R. STRAPP calculates the association between macroevolutionary rates and a binary variable of occurrence in the reproductive time-series data using a Mann-Whitney U-test. The observed U-statistic is then compared to a distribution of null values to estimate statistical significance.
(e) Hypothesis testing We tested if species-level masting behaviours, defined by CV p and S r , were evolutionarily conserved using Pagel's λ  [43]  and the K statistic  [44]. λ estimates how trait similarity correlates with phylogenetic similarity, indicating the degree to which trait values reflect shared evolutionary history. The K statistic, by contrast, compares trait variation within clades to variation among clades, so can detect phylogenetic clustering or overdispersion  [43, 44]. With each masting metric as a response variable, we estimated Pagel's λ using phylogenetic generalized least squares (PGLS) with the gls function in the 'nlme' package and a correlation structure generated for the pruned GBOTB phylogeny using the corPagel function in the R package 'ape'. We constrained λ to between 0 and 1.
For the species with standard errors for the masting metrics (i. e. across replicate time series), we also quantified λ incorporating the errors into the PGLS by weighting observations with the inverse variances  [45]. We tested the statistical significance of λ values using the anova function in the 'nlme' package to compare each PGLS to an equivalent null model fitted without the correlation structure. We estimated the K statistic for each species using the phylogeny pruned from GBOTB and the phylosig function in the 'phytools' package in R. We tested the statistical significance of each K statistic with phylosig, which compares the estimated K value to a null distribution generated by randomly shuffling tips in the phylogeny 1000 times. These phylogenetic signal calculations were repeated with and without sampling error.
The macroevolutionary differences between clusters of species in the reproductive time-series data were compared using several examined and concealed state-dependent speciation and extinction (SecSSE) models for BAMM speciation rates, PGLS for DR speciation rates, and STRAPP for the BAMM-estimated speciation rate and the rate of seed mass evolution. We used the 'SecSSE' R package  [48]  to fit an examined-trait-dependent (ETD) model where speciation rates vary among different reproductive clusters. To assess if the ETD model was supported by our data, we compared it to a null model with constant speciation rates for all species (CR) and a concealed-trait-dependent (CTD) model where speciation rates varied independently of the pre-defined reproductive clusters. For the CTD model, we instead let speciation rates vary among five different but unknown clusters, termed 'concealed states', as recommended by  [49].
Extinction rates and transition rates between states were fixed across all states for all three models. Starting values were generated using a simple birthdeath model with the bd_ML function in the 'DDD' R package  [50] , and we reran the models with values doubled and halved to avoid only finding local maxima. We identified the best model by comparing AIC weights (AIC w )  [51]. The PGLS model was fitted as described for metric correlations, with the GBOTB phylogeny and DR speciation values as the response and the cluster each species belonged to as an explanatory factor. The STRAPP analysis tested the correlation between BAMM speciation rate or seed mass evolution and the cluster each species belonged to using the Kruskal-Wallis method and 1000 permutations. We also examined the differences in spatial synchrony and absolute latitude between masting clusters with PGLS.
Synchrony was negatively skewed so was exponentially transformed beforehand. When fitting the PGLS we co-estimated Pagel's λ in the same way as described above and the p-values were not corrected for multiple tests. To test the robustness of the results to our filtering decisions, we repeated all the analyses with different data subsets. We repeated the analyses with reproductive time series of at least 3, 4 and 6 years of consecutive observations to test the effect of the 5-year filtering decision. Similarly, we tested the effect of unit type by separately analysing datasets of only mass-based, counts-based, per-area or per-individual units. All of the code for performing the analyses can be found on Zenodo  [52].
For example, stabilizing selection on seed size may arise if both larger seeds are more apparent to predators, particularly in forests that dominate in our dataset  [54] , and smaller seeds experience more interspecific competition post-dispersal  [55]. Alternatively, the same type of selection may occur in opposing ways within species  [12, 18]. For example in Quercus ilex, pre-dispersal predation by weevils should select for large acorns  [56] , whereas post-dispersal predation by mammals selects for smaller seeds  [34]. Likewise, there may be opposing effects in different species, because of their diversity of predators, pollination methods and seed dispersal mechanisms  [57, 58]. A combination of different types of selection in different species, such as stronger selection from pollinators in animal pollinated species, but a weaker selection from seed predators in animal-dispersed species, may obscure association between rates of trait evolution and masting metrics.
Even with our large dataset, we lacked sufficient replicate time series to calculate S r at smaller spatial scales. Future studies could overcome these challenges by testing if spatial synchrony promotes genotypic differentiation between populations within species where the economies of scales from predator satiation are greatest. A further explanation for finding few statistically significant effects in our study is that our methods are sensitive to sample size. STRAPP, for example, may require many hundreds more species to detect statistically significant correlations between traits and speciation rates  [70]. BiSSE, which is similar to QuaSSE and SecSSE, requires at least 300 species for reliable results  [71]. Related, these associations may occur only for some masting behaviours. Our clustering of species into different reproductive strategies therefore returns to an important question of how masting is itself defined.
By finding that masting is an emergent property associated with different reproductive behaviours (CV p , S r ) that evolve independently from each other, our results are consistent with general theory predicting that diverse, species-specific selective pressures will create a diversity of masting behaviours  [18]. The evolution of masting has long been of interest to researchers  [72] , and efforts to compile large reproductive time-series datasets have enabled important insights, such as the phylogenetic association between masting and nutrient imbalance  [4]. Nevertheless, relatively little is known about the wider macroevolutionary consequences of masting. Here, we provide the first steps to address this gap, demonstrating the value of newly available reproductive timeseries datasets to investigate the macroevolution of masting  [25].
Future work should consider whether the macroevolutionary consequences of masting extend to the evolution of floral morphology and other reproductive traits, as well as non-reproductive aspects of the niche, such as geographical distribution or climate niche. Given the variety of reproductive behaviours and varied combinations of these behaviours that encompass masting, future attempts to understand the evolution of plant reproductive patterns must therefore focus on understanding their complexities and examining how these interact to affect evolutionary change. Data accessibility. The scripts for running the analyses can be found in a public repository: https://doi. org/10. 5281/zenodo. 5093128. A separate publication describing the MASTREE+ dataset is in preparation and the dataset can be accessed via an online data explorer: https:// mastreeplus.
shinyapps. io/mastreeplus/. The GBOTB phylogeny is available as an electronic supplementary material from Smith & Brown  [32]  (https://doi. org/10. 1002/ajb2. 1019). The BAMM objects are from Igea & Tanentzap  [26]  (https://github. com/javierigea/ LDGplants_rates) and Igea et al. [27]  (https://github. com/javierigea/seed_size). royalsocietypublishing. org/journal/rstb Phil. Trans. R. Soc. B 376: 20200372.
Considerations on the model Modelling studies are difficult exercises where one walk on a thin line between complexity/realism and simplification that is required for conceptualization, i. e. building some theoretical understanding. We have tried to do this successfully but we want to underline here a few simplifications made in this study (and already made in classical models of predator-prey interactionse. g. Wilmers et al. , 2007a, b). It is noteworthy that the code of the model is available (https://github. com/aissamorin/climate-preyvulnerability-and-predators) so that one can parametrize it for a specific system and add the complexity that would be considered critical. First, in our model, juvenile prey contribute as much energy as adult prey. Second, the predator population is not age-structured.
Acknowledgments We thank  C. Wilmers  for providing the code of the published model that serves as the basis of ours. In addition, this work benefited from the computing cluster platform of the  Centre d'Ecologie Fonctionnelle et Evolutive and from Biosphere , the  IFB  cloud for life sciences. We thank  Bruno Spataro  and  Stéphane Delmotte  from the LBBE computing services for their help in using computing facilities. Finally, we thank two anonymous reviewers for their fruitful comments on a previous draft of this manuscript. Sensitivity analyses of the long-term response of predators to 20% change in parameters when the habitat-driven hunting success decreases with rainfall.
Funding This work was partly funded by the  Agence Nationale de la Recherche  (project Landthirst  ANR-16-CE02-0001-01  and  FUTURE-PRED ANR-18-CE02-0005-01 ) and was further supported by a grant from the  "Ministère français de lʼEnseignement supérieur, de la Recherche et de lʼInnovation"  through the  "Ecole Doctorale E2M2" of "Université Claude Bernard Lyon 1 ".