dataesr/scientific-paragraphs-categorization huggingface dataset:
In contrast, calibration set 3 is the more constrained with the Suboscines / Oscines split bounded between 28 -34 Myrs. Unsurprisingly, this calibration led to the youngest estimates, dating the origins of passerines at 59 Myrs (56 -63 Myrs) and the Paleognathae / Neognathae at 65 Myrs (63 -69 Myrs). In all runs, our estimates of the origin of Zosterops have lower limits of CI including 2. 5 Myrs and mean estimates are also often considerably lower than this value (Table  1 ). Using the calibration set 1, the ten replicated datasets gave a mean age estimate for the origin of Zosterops around 2 million years ago (Table  1 ). S3 ). For greater clarity, the cladogram focuses on passerine birds only, but see Fig  S3  for a cladogram of the inferred phylogeny for the whole set of investigated avian species.
More broadly, our analysis is consistent with a recent origin of Zosterops, with a crown clade age of less than 5 Myrs and probably between 1 and 3. 5 Myrs (Table  1 ). Additionally, we performed a completely independent molecular dating by applying the regression method proposed in  Nabholz et al. (2016). Based on nine full Zosterops mitochondrial genomes, we calculated molecular divergence. The divergence between Z. lateralis and the other Zosterops has a median of 0. 205 subst. /site (max = 0. 220, min = 0. 186) for the third codon position. Assuming a median body mass for the genus of 10. 7 g  (Dunning, 2007) , we estimated a divergence date between 2. 3 and 6. 2 Myrs. These estimates are in line with our previous dating based on nuclear data and with molecular dating based on fossil calibration confirming the extremely rapid diversification rate of white-eyes.
Small interchromosomal differences in the distribution of nucleotide diversity values were detected for both female-and male-based estimates, suggesting that both datasets give similar results at the chromosomal level, except for the neoZ chromosome for which substantial differences were observed between the two datasets (Fig. S4 ). Even considering this source of variability, the neoZ chromosome still shows significant deviation from the mean autosomal diversity for both datasets (π females =1. 04e-3 and π males =1. 34e-3, respectively; ttests, p<2e-16 for both datasets), thus representing 57. 6% and 73. 5% of the mean autosomal diversity. This reduced level of nucleotide diversity was similarly detected for the neoZ-Z and the neoZ-4A regions of the neo-Z chromosome (C, Fig. 5 ). Based on both datasets, a lower nucleotide diversity was observed on neoZ regions as compared to the autosomal chromosomes.
1 ) for a total of 6,339 alignments of single-copy orthologs, corresponding to 6,073 autosomal genes, 66 on the remaining autosomal region of the 4A chromosome (hereafter autosome-4A), 164 on the neoZ-Z, 54 on the neoZ-4A and 17 on the neoW-4A. For the neoZ-4A and neoW-4A, we made a special effort to identify gametologs (homologous sequences between neoZ-4A and neoW-4A genes, which were previously excluded during the filtering of 1:1 orthologs). We then compared the d N /d S of neoZ-4A and neoZ-Z genes. To do that, we randomly subsampled the data to match the number of genes in neoZ-4A region (54) before concatenation and then computed d N /d S ratios. The variability in d N /d S is evaluated by bootstrapping genes and creating repeated concatenation of 54 genes for each genomic region. For all species, the d N /d S ratio reaches significantly higher values for neoZ-Z genes than for autosomal genes (Fig.
(2009)  regarding the recent and extensive diversification of Zosterops. Using two independent datasets (mitochondrial and nuclear) and methods, we confirmed the recent origin of the genus. Our analyses are consistent with a diversification of white-eyes over less than 5 Myrs and that could be as young as 1 Myr. With the exception of the African Great Lakes cichlids  (Genner et al. 2007 ), the genus Zosterops represents one of the most exceptional diversification rates among vertebrates  (Lagomarsino et al. 2016). As an example, it is more than ten times higher than the average diversification rate estimated across all bird species by  Jetz et al. (2009). Even the large and relatively recent radiation of the Furnariidae (ovenbirds and woodcreepers) has a net rate of diversification markedly lower than the white-eyes (r = 0.
A notable exception was the neoZ region for which no fast-neoZ effect was identified. Although most of the analyses are congruent, our report is based on a limited number of individuals and from only one population of Z. borbonicus. Further investigations based on a complementary and extensive dataset will probably help to fine-tune the conclusions, especially regarding the lack of any fast-Z effect or the drastic increase of TE on the neoW-4A. Lastly, given the huge difference in diversity between autosomes and sex chromosomes, we emphasize the importance of taking into account sex chromosomes for local adaptation studies, at least by scanning autosomes and sex chromosomes separately (see  Bourgeois et al. 2018  for an example). We also extracted DNA of a Zosterops pallidus female collected in February 2015 in South Africa, Free state province, Sandymount Park, 10 kms from Fauresmith (coordinates: S: -29.
GENOME ASSEMBLY The paired-end reads were filtered using  Trimmomatic (v0-33; Bolger et al. , 2014)  using the following parameters: "ILLUMINACLIP:TruSeq3-PE-2. fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:50". The mate-pair reads were cleaned using  NextClip (v1. 3. 1; Leggett et al. 2013 ) using the following parameters : "--min_length 20 --trim_ends 0 --remove_duplicates". Paired-end and mate-pair reads were assembled using SOAPdenovo (v2. 04; Luo et al 2012) with parameters "-d 1 -D 2". Several k-mers (from 27 to 37-mers) were tested and we chose the assembly maximizing the N50 scaffold length criteria. Next, we applied Gapcloser v1. 10 (a companion program of SOAPdenovo) to fill the gap in the assemblies. Given that the PacBio technology produces long reads but with quite high sequencing error rates, we used LoRDEC (v0.
pl script  (Bradnam et al. 2013 ; https://github. com/ucdavisbioinformatics/assemblathon2-analysis) to evaluate the different genome assemblies. These statistics include genome size, number of scaffolds, scaffold N50, scaffold N90 and the proportion of missing data (N%). Additionally, we used BUSCO (v3. 0. 2;  Waterhouse et al. 2017 ), a commonly used tool for evaluating the genome completeness based on the content in highly conserved orthologous genes (options: "-m genome -e 0. 001 -l aves_odb9 -sp chicken"). The mitochondrial genome was assembled using mitobim (v1. 8;  Hahn et al. 2013)  with the mitochondrial genome of Z. lateralis (accession : KC545407) used as reference (socalled "bait"). The mitochondrial genome was automatically annotated using the web server mitos2 (http://mitos2. bioinf.
GENOME-GUIDED DE NOVO TRANSCRIPTOME ASSEMBLY. RNA-seq reads were used to generate a transcript catalogue to train the gene prediction software. First, RNA-seq reads were filtered with trimmomatic (v0-33;  Bolger et al. , 2014)  using the following parameters : "ILLUMINACLIP:TruSeq3-PE. fa:2:30:10 SLIDINGWINDOW:4:5 LEADING:5 TRAILING:5 MINLEN:25". Second, the filtered RNA-seq reads were mapped onto the reference genome using HISAT2  (Kim et al. 2015). HISAT2 performed a splice alignment of RNA-Seq reads, outperforming the spliced aligner algorithm implemented in TopHat  (Kim et al. 2015). Finally, two methods were used to assemble the transcripts from the HISAT2 output bam file: i) Cufflinks  (Trapnell et al. 2010 ) using the following parameters: "-q -p 10 -m 300 -s 100" and ii) Trinity (v2.
PROTEIN-CODING GENE ANNOTATION Gene annotation was performed using the PASA pipeline combined with EVidenceModeler  (Haas et al. 2008; Haas et al. 2011 ; https://github. com/PASApipeline/PASApipeline/ wiki ). The complete annotation pipeline involved the following steps: 1. ab initio gene finding with Augustus (Stanke and Waack 2003 ; http://bioinf. unigreifswald. de/augustus/) using the parameter : "--species=chicken".
2. Protein homology detection and intron resolution using genBlastG  (She et al. 2011;  http://genome. sfu. ca/genblast/download. html). Protein sequences of several passerines were used as references, namely zebra finch (Taeniopygia guttata; assembly taeGut3. 2. 4;  Warren et al. 2010) , collared flycatcher (Ficedula albicollis; assembly FicAlb_1. 4;  Ellegren et al. 2012) , medium ground-finch (Geospiza fortis; assembly GeoFor_1. 0;  (Zhang et al. 2012 ) and hooded crow (Corvus cornix; accession number JPSR00000000. 1;  Poelstra et al. 2014 ). Genblast parameters were : "-p genblastg -c 0. 8 -r 3. 0 -gffpro -cdna -e 1e-10". 3. PASA alignment assemblies based on overlapping transcript from Trinity genomeguided de novo transcriptome assembly (see above)  (Haas et al. 2003). This step involved the so-called PASAPipeline (v2.
2. 0; https://github. com/PASApipeline/PASApipeline/ ) used with the following parameters : "-C -r -R --ALIGNERS blat,gmap". 4. Next, EVidenceModeler (v1. 1. 1; Haas et al. 2008 ) was used to compute weighted consensus gene structure annotations based on the previous steps (1 to 3). We used the following parameters : "--segmentSize 500000 --overlapSize 200000" and an arbitrary weight file following the guidelines provided at http://evidencemodeler. github. io/. 5. Finally, we used the script "pasa_gff3_validator. pl" of PASA add UTR annotations and models for alternatively spliced isoforms. Finally, StringTie  (Pertea et al. 2015)  was also used to estimate the proportion of annotated CDS with RNA-seq information support. We defined three sets of genes depending on their reliability, namely the "high reliability" set corresponding to genes with a low TE content in coding regions (<10%, Fig.
FILTERING SCAFFOLDS ORIGINATING FROM AUTOSOMES, W AND Z CHROMOSOMES Given that we have sequenced a female genome, we likely assembled contigs from W, Z and autosomal chromosomes. To identify scaffolds originating from sex chromosomes or autosomes, we mapped seven females and five males reads from Z. borbonicus birds published in  Bourgeois et al. (2017)  onto our female genome assembly. We first mapped all raw reads against the Z. borbonicus reference genome using BWA mem v. 0. 7. 5a  (Li, 2013) , we then removed duplicates with Picard 1. 112 (http://broadinstitute. github. io/picard). We then used Mosdepth  (Pedersen & Quinlan, 2018)  to compute median per-site coverage for each scaffold, following the same strategy than in  Smeds et al. (2015). For each i scaffold, total coverage for males and females were computed as the sum of coverage of all individuals.
Second, we used DeCoSTAR, a computational method tracking gene order evolution from phylogenetic signal by inferring gene adjacencies evolutionary histories, in order to not only improve the genome assembly of Z. borbonicus, but also 26 additional extant avian assemblies including the high coverage (>100X) of  Zhang et al. 2014  and the other passerine genomes (Table  S2 ). The gene trees were obtained for phylogenies of single-copy orthologs (see above) estimated using IQ-TREE model GTR+G4 and 1000 so-called "ultra-fast bootstrap" (v1. 6. 2;  Nguyen et al. 2014). A snakemake pipeline (https://github. com/YoannAnselmetti/DeCoSTAR _pipeline) were used to apply DeCoSTAR on gene orders and phylogenies. Finally, scaffold orders given by LASTZ and DeCoSTAR were manually reconciled to determine the consensus scaffold orders along the Z.
We used uniform prior on divergence times, combined with soft calibrations  (Rannala and Yang, 2007; Yang and Rannala, 2006). The MCMC were run for at least 8,000 cycles. MCMC convergence were diagnosed by running two independents MCMC and by visually checking the evolution of the likelihood and other parameters along the Markov chain (in ". trace" files). Additionally, we applied an independent molecular dating using the method proposed by  Nabholz et al. (2016). Seven complete mitochondrial Zosterops genomes were downloaded from Genbank, including Z. erythropleuros (KT194322), Z. japonicus (KT601061), Z. lateralis (KC545407), Z. poliogastrus (KX181886), Z. senegalensis (KX181887), Z. senegalensis (KX181888). We also included the sequences of the Réunion grey white-eye and the Orange River white-eye assembled in the present study.
GENOME-WIDE ESTIMATES OF NUCLEOTIDE DIVERSITY Based on the previously generated BAM files (see 'Filtering scaffolds originating from autosomes, W and Z chromosomes' section), we then use GATK to generate the gvcf from the six parents of the three progenies described in  Bourgeois et al. 2017  (three males and three females). Joint genotyping, as well as all subsequent analyses, was then performed separately for the three males and the three females. We followed all the GATK best practices under the GATK suite, except for variant filtration which was performed using a custom script to speed up computations. This step however followed the same procedures than under GATK, assuming the following thresholds: QD>2. 0, FS<60. 0, MQ>40. 0, MQRANKSUM>-2. 0, READPOSRANKSUM>-2. 0 and RAW_MQ > 45000. For each individual, we then reconstructed two genomic sequences.
At each position of the genome, the position (reference or alternate if any) was added to the sequence if the coverage at the position was between 3 and 50. In any other case, a "N" character was added in order to keep the sequence length the same. We then computed the Tajima's π estimator of nucleotides diversity and the GC content over non-overlapping 10 kb windows. To be highly conservative in the analysis of the neoW chromosome, all windows associated to W scaffolds and found covered in the male (ZZ) dataset were excluded from the analysis of the female (ZW) dataset, even if this non-zero coverage was observed at a single base over the genomic window. Such a non-zero coverage is expected caused by read mismapping, particularly in TE regions.
Acknowledgements BMM was supported by the  Azrieli Foundation, Israel Science Foundation  (ISF grant:  2248/19 ),  ERC SweetBrain 851765 ,  TEVA , The  Aufzien Family Center for the Prevention and Treatment of Parkinson's Disease at Tel Aviv University, Zimin, Israel Ministry of Science and Technology  (Grant No. 3-17351 ), and TCCP. UA was supported by the  Israel Science Foundation  ( ISF  grant  953/16 ),  TEVA , The  Aufzien Family Center for the Prevention and Treatment of Parkinson's Disease at Tel Aviv University , the  German Research Foundation (DFG)  (NA:  207/10-1 ) and the  Taube/Koret Global Collaboration in Neurodegenerative Diseases. RS was supported by the  Israel Science Foundation  ( ISF  grant  2417/20 ), within the  Israel Precision Medicine Partership program. The work of YN, AE, and KI was supported by  European Research Council   Consolidator Grant OCLD  (project no.
Empirical research on human mortality and extreme longevity suggests that the risk of death among the oldest-old ceases to increase and levels off at age 110. The universality of this finding remains in dispute because of two main reasons: i) high uncertainty around statistical estimates generated from scarce data, and ii) the lack of country-specific comparisons. In this article, we estimate age patterns of mortality above age 105 using data from the International Database on Longevity, an exceptionally large and recently updated database comprising more than 13,000 validated records of long-lived individuals from eight populations. We show that, in all of them, similar mortality trajectories arise, suggesting that the risk of dying levels off after age 105. As more high-quality data become available, there is more evidence in support of a levelling-off of the risk of dying as a regularity of longevous populations.
Introduction Several regularities are associated with human mortality. It is broadly accepted, for instance, that the risk of death starts growing exponentially with age at early adulthood  [1]. However, at the frontier of human longevity, we are challenged by the limits of demographic knowledge. The trajectory of the risk of dying at extreme old ages is one of the demographic patterns that is most often questioned in evolutionary theories of aging  [2] [3] [4] [5] [6]  mathematical models  [7] [8] [9]  and empirical studies  [10] [11] [12] [13] [14]. The identification of regularities in mortality patterns among the oldest-old has profound implications for societies and health sciences  [15] , and it can radically reshape evolutionary thinking  [16]. In this article, we examine an unprecedentedly large and reliable dataset of the longest-lived individuals to evaluate whether a universal pattern of human longevity emerges at extreme old ages, thereby, providing new insights into and a better understanding of the biological mechanisms of human aging.
Skepticism about the finding still prevails, however; mainly based on the statistical model chosen to evaluate the trajectory of the risk of dying  [18] [19] [20]. As people live longer, and more individuals reach exceptionally advanced ages, larger datasets on the oldest-old become available. Key among them is the International Database on Longevity (IDL), which is the result of an unprecedented collaboration between statistical offices from different countries, demographers, gerontologists and experts on longevity  [21]. The database, which was first launched in 2010, provided detailed information on 672 exhaustively validated cases of supercentenarians (individuals aged 110 or older) from a number of countries  [22]. In 2020, the IDL was updated and it now provides additional high-quality data on individuals who survived to age 105, increasing the sample size to more than 13,000 records  [23].
In this article, we examine data from eight populations included in the IDL that report validated records of all individuals aged 105 and above: France, Germany, Belgium, the United States, Denmark, Quebec, Austria and Norway. Apart from Quebec, all of them are nationally representative. For the United States, we start the analysis at age 110 because available data before that age is not country-representative  [23]. We use a fully non-parametric framework to estimate the age trajectories of the risk of dying (see Materials and Methods for details). Although comparisons are more meaningful among countries with larger populations, the estimation of the risk of dying (i. e. mortality hazard) is still possible in the eight populations studied. Differences in population sizes are reflected in the size of the confidence intervals of the estimated hazards.
Our analyses represent three major contributions. First, the uncertainty around the estimates of the risk of dying is substantially reduced, by virtue of the large amount of high-quality data included in the analysis. Second, the exceptionally large dataset enables us to assess, for the first time, country-specific trajectories in the risk of dying above age 105. Third, our estimates are purely data driven; no model structure is imposed on the age patterns of mortality. These are three compelling features of our study that were neither achieved in previous studies of supercentenarians  [12, 14] , nor applied to datasets where the scarcity of data was overcome by aggregating populations  [10, 11]. According to the hypothesis that there is a mortality plateau at extreme ages  [10, 17] , a leveling-off in the risk of dying is expected to arise as a regularity in all the populations analyzed.
The lack of observations hinders the assessment of the age pattern of mortality past this age  [25]. Finally, we performed two sensitivity analysis to test the robustness of our results. First, we reduced the age interval from six to three months (see S1 Fig in  S1 File ). The trajectories of the risk of dying are very much alike in both cases. This indicates that our results do not depend on the size of the age interval. Second, we calculated the risk of dying for the total population (i. e. adding up data for males and females, see S2 Fig in  S1 File ). The trajectory of the risk of dying for the total population is almost identical to the one depicted by females, which account for most of the observed cases. This analysis entails that the results shown in.
Mortality data Exact dates of birth and death of all individuals who attained age 105 were obtained from the International Database on Longevity (IDL), which collects information from twelve European countries, Canada (Quebec only), Japan and the United States (see ref. [25]  for detailed description of the database). The IDL is an open access database and it can be retrieved from https://www. supercentenarians. org/. The data used in this study were retrieved on December 1 st , 2020. When the date of death is not available, the IDL provides information on the last date an individual was confirmed to be alive. In the case of the United States, the exact dates are unknown: for each individual, only the years of birth and death together with the age (in days) are given. Several sample frames are observed in the IDL, depending on the country  [10, 22, 23].
Estimation of confidence intervals Because of the small number of observations at the highest ages, standard methods that rely on the central limit theorem to compute confidence intervals are not valid. Hence, we assessed uncertainty surrounding our estimates by computing 95% empirical confidence intervals from data simulation. First, assuming the risk of death is constant within each age interval, for each population we transformed the estimated death rates into probabilities δ q x = 1-exp[-∑ i2I,i�x δ� δ M i ]. Then, we simulated n individuals who die according to the corresponding δ q x. The values of n match the number of records in the IDL for each country or region. We replicated this exercise 10,000 times, obtaining, for each population, 10,000 sets of death probabilities over age. Finally, we back transformed these sets of probabilities into death rates, and calculated the corresponding confidence intervals.
Data analysis. Quantitative variables. The data set initially originally included n = 173 subjects and d = 4 × 10 × 7 = 280 variables. The variables resulted from the design of the study where 4 different sets of 10 different odors each were rated with respect to 7 properties including edibility, intensity, irritation, temperature, familiarity, hedonics and painfulness. For each subject, the data set contained an additional variable that carried the olfactory diagnosis of normosmia or hyposmia. Missing odor ratings were imputed for subjects who had performed at least two thirds of the required evaluations, using k-nearest neighbors (kNN) with k = 3 within the respective olfactory set, calculated with the R-library "DMwR". (https:// cran. r-proje ct. org/ packa ge= DMwR  35  ). In addition, it was examined whether the subjects assigned to the four separate odor sets showed equal distributions of age, sex and odor diagnoses, using Kruskal-Wallis 36 and χ 237 tests, respectively.
These calculations were done using our R package "ABCanalysis" (https:// cran. r-proje ct. org/ packa ge= ABCan alysis) 41. Supervised analysis of odor property ratings for information allowing to separate olfactory diagnostic groups. Four different sets of 10 odors each, which were evaluated with respect to seven characteristics by four different sets of participants, provided a 146 × 280 sparse block diagonal matrix (odor properties) with ratings for olfactory characteristics, specifically 4 sets of 10 odors each and 7 queries per odor = 280 columns, one for each odor and property (Supplementary Fig. S1 ). To this added the class information regarding the two olfactory diagnoses. To assess whether the property ratings of odors provided information relevant for the separation of normosmic and hyposmic subjects, a supervised machine-learning algorithm in form of random forests  44, 45  was trained to map the odor properties for the 146 subjects) onto the two olfactory diagnoses.