dataesr/scientific-paragraphs-categorization huggingface dataset:
Polishing assemblies -To polish the final HiFi-based genomes and remove unambiguous heterozygous sites, we used the CCS reads. To perform a polishing round, we mapped all CCS reads to the scaffolded, gap-closed assemblies using pbmm2 (https://github. com/PacificBiosciences/pbmm2) with arguments: --preset CCS -N 1 and called variants using DeepVariant (Poplin et al. , 2018). We then filtered for sites with genotype 1/1 and a 'PASS' filter value, meaning that all or nearly all reads support an alternative sequence at this position and passed DeepVariant's internal filters. With this method, we do not polish any heterozygous or polymorphic regions of the genome, but only those that are incorrect and not supported by any CCS reads. We then corrected base errors using bcftools consensus v. 1. 12 127.
Inferring and annotating orthologous genes To assess gene completeness in assemblies and infer orthologs for phylogenomic, selection and gene loss analyses, we used TOGA  41  (https://github. com/hillerlab/TOGA, commit v. c4bce48). Briefly, TOGA uses pairwise genome alignment chains between a reference species (human hg38 assembly) and a query species (other mammals) to infer and annotate orthologous genes and to classify them as intact or lost. TOGA implements a novel paradigm to infer orthologous gene loci that largely relies on intronic and intergenic alignments and uses machine learning to accurately distinguish orthologous from paralogous or processed pseudogene loci. We used the human GENCODE V38 (Ensembl 104) annotation as input for TOGA, providing 39,664 transcripts of 19,456 coding genes.
Selection of non-chiropteran genome assemblies To obtain a broad genome representation of mammals for our selection screen, we included 95 other mammal and ten bat genomes, representing the main mammalian groups and bat families (Supplementary Table  5 ). We only selected assemblies for which at least 16,000 ancestral placental mammal genes have an intact reading frame, as determined by TOGA (detailed below) (Supplementary Figure  7 ). For Chiroptera, we included the 10 new and ten previously published bat assemblies. 18 of these 20 bats were assembled from long sequencing reads  28, 29, 40  while the remaining two genomes were assembled from Illumina short-read data 149,150 (Supplementary Table  3 ). For five mammalian orders (Primates, Rodentia, Cetartiodactyla, Carnivora, Chiroptera), we selected exactly 20 species.
Genome-wide Unbiased Selection Screen To identify genes under positive selection, we used aBSREL  48  , an adaptive branchsite random effects likelihood method implemented in HYPHY 151. aBSREL was run in exploratory mode to test all branches and nodes within the phylogenetic tree. For each gene, multiple test corrections over all tested branches were applied using the Benjamini-Hochberg procedure. In total, 17,130 genes were screened for selection using our ASTRAL topology as input. Alignments of genes of interest were inspected by eye to rule-out spurious signals due to misalignments. To test whether enrichment results of genes under selection (see below) are representative for mammalian orders or driven by individual species, we performed a subsampling analysis. We ran four additional selection screens using the same dataset of 17,130 genes, but subsampled the five groups having 20 species (Chiroptera, Carnivora, Cetartiodactyla, Rodentia, and Primates) by randomly selecting only ten species.
Groups with less than 20 genomes were not subsampled, thus each subsampled dataset included 115-50=65 species. Subsamples 1-3 removed species at random, whereas subsample 4 included the ten species in the five 20-species orders that were left out in subsample 1. For each subsampled set of species, codon alignments were generated and cleaned as for the full dataset, and the same input transcripts were screened for selection.
non bats, β1 is the coefficient on branch length, and X represents branch length. Both coefficients are normally distributed. To implement Bayesian sampling for these analyses, we used brms 157 , a package that enables coding models in R for implementation in the stan statistical language 158. For each model, we ran four separate Markov chain Monte Carlo chains using a Hamiltonian Monte Carlo approach. Compared to other Bayesian implementations, the Hamiltonian Monte Carlo approach saves time in sampling parameter spaces by generating efficient transitions spanning the posterior based on derivatives of the density function of the model. We estimated the R 2 of all models using the procedure outlined by 159. To compare model fits, we used WAIC (widely applicable information criterion), which weighs log pointwise predictive density against the expected effective number of parameters as defined by 160 and provides estimates of the standard error of the difference between the best fit and other models.
Acknowledgment MH was supported by the  German Research Foundation  ( HI1423/5-1 ) and the  LOEWE-Centre for Translational Biodiversity Genomics  (TBG) funded by the  Hessen State Ministry of Higher Education, Research and the Arts  (HMWK), TB by the  German Research Foundation  ( INST 269/768-1 ), LMD by the  National Science Foundation  ( NSF-IOS 2032063  and  2031906 ,  NSF-DEB 1838273 ), TML by the  National Science Foundation  (Award  ID 2010853 ), ATI by a  Key grant  from the  National Science Foundation of Zhejiang Province  ( Z23C010003 ), BKL by the  Royal Ontario Museum Governors , the  National Science Foundation  ( DEB-0344430 ), and the  Toronto Zoological Society , AB by the  Natural Sciences and Engineering Research Council of Canada  ( RGPIN-2022-03010 ) and the  Canadian Institutes of Health Research  ( 479539 ), VG by a  PGS-D scholarship  funded by the  Natural Sciences and Engineering Research Council of Canada (NSERC)  ( 569587-2022 ), SCV by a  UKRI Future Leaders Fellowship  ( MR/T021985/1 ), an  ERC Consolidator Grant  ( 101001702 ; BATSPEAK), and a  Max Planck Research Group  awarded by the  Max Planck Society , SJP by a  Junior Chair grant  from the  Institut Universitaire de France , GM by the  Max Planck Society , AK and JP by the  Robert Koch Institute , ECT by  Irish Research Council Laureate  Award  IRCLA/2017/58  and  Science Foundation Ireland Future Frontiers   19/FFP/6790.
Data availability Genome assemblies and all sequencing data have been submitted to NCBI (accession number pending). TOGA, transposable element and miRNA annotations of newly-sequenced bats and alignments of selected genes are available for download at http://genome. senckenberg. de/download/Bat1KImmune/. Accession codes and identifiers of publicly available genomic data are listed in Supplementary Tables  3  and 5.
Output was processed to eliminate overlapping hits using RM2Bed. py, part of the RepeatMasker installation package to generate BED files for downstream analyses. miRNAs' with multiple copies and determined the authenticity of these copies based on their secondary structure that we predicted with RNAfold (v2. 4. 18) 135. (https://github. com/davidaray/bioinfo_tools/blob/master/extract_align. py, RepeatAfterMe (RAM) https://zenodo. org/record/7076442), and the TE-Aid package included in 129. Briefly, each assembly was subjected to an initial RepeatModeler analysis. Because RepeatModeler will often produce incomplete putative consensus sequences, each putative consensus was subjected to an extension using RAM. These extended consensus sequences were then curated using a custom bash script (TEcurate.
sh) that categorized each sequence into one of four categories (LINE, LTR, DNA, or Unidentified) using RepeatClassifier, which is part of the RepeatModeler package. TEcurate. sh would then use the TE-Aid package to generate genome coverage plots, self-alignment dot-plots, structure and ORF plots, and copy number estimates. For any elements clearly categorized as LINE, LTR, or DNA, the identity provided by RepeatClassifier was used to generate a unique identifier that included species of origin, the Annotation of miRNAs Annotation of miRNA genes in the newly-sequenced bats was performed similarly to reference 29. Briefly, prior to miRNA prediction, repetitive and low-complexity regions in each bat genome were masked with the Dfam database (v3. 5) (https://www. dfam. org/releases/Dfam_3. 5/) using RepeatMasker (v4.
After all putative TE consensus sequences were classified and named, all consensus sequences were collapsed with previously known mammalian TEs per a variation of the 80-80-80 rule of Wicker et al. using USEARCH 131 with parameters -id 0. 80 -minsl 0. 95 -maxsl 1. 05 -maxaccepts 32 -maxrejects 128 -userfields query+target+id+ql+tl and comparison to the mammalian TE library from 42. All novel TE consensus sequences have been submitted to the Dfam TE database 132. The resulting mammalian TE library was used to mask all assemblies with RepeatMasker. http://www. repeatmasker. org). For each masked genome, conserved miRNA genes were predicted using the Rfam database (v14) 133   and Infernal (v1. 1. 2) 134. Infernal uses not only sequence similarity but also miRNA secondary structures for homology searches.
WikiPathways (https://www. wikipathways. org/index. php/WikiPathways); miRNA targets from miRTarBase (http://mirtarbase. mbc. nctu. edu. tw/) and regulatory motif matches from TRANSFAC (http://genexplain. com/transfac/); tissue specificity from Human Protein Atlas (https://www. proteinatlas. org/); protein complexes from CORUM (http://mips. helmholtzmuenchen. de/corum/) and human disease phenotypes from Human Phenotype Ontology (https://hpo. jax. org/app/). 152,153   (last access on May 10, 2022) using all annotated human genes as the background. As databases, we used Gene Ontology (http://geneontology. org/), and pathways from KEGG (https://www. genome. jp/kegg/), Reactome (https://reactome. org/) and.
test whether the Cys78 deletion in ISG15 of certain bats affects the formation of stable ISG15 homodimers, we used AlphaFold2 108 through ColabFold 170 to infer the structure of the putative ISG15 homodimer of human, of the Chinese rufous horseshoe bat (Rhinolophus sinicus), and of the cyclops roundleaf bat (Doryrhina cyclops). Starting from each ISG15 sequence, ColabFold identified homologous sequences by running MMseqs2 171 against the UniRef100 database 172 and against a set of environmental sequences 173. Structural template information was obtained from the PDB70 database 174. Next, the AlphaFold-multimer-v2 model 175 was employed to infer five structural models of the dimer, with 12 rounds of recycling.
Cytokine profiling IL-10, IFN-g and tumor necrosis factor alpha (TNF-a) were analyzed in supernatants by Luminex array. Species-dedicated kits were used in order to ensure that antibodies did not cross-react. Custom Milliplex Non-Human Primate and Human Cytokine Magnetic Bead Panel (Millipore) were used according to the manufacturer's instructions. All samples were analyzed using a Bio-Plex 200 reader and the Bio-Plex Manager Software (Bio-Rad).
Bioinformatics analyses Bulk RNA-seq: Quality of the raw sequences was verified using FastQC. All samples presented a similar profile, with an average Phred quality score above 30. Reads were quantified using the quasi-mapping-based mode of Salmon  (Patro et al. , 2017). This step needed a preliminary indexing of reference transcripts, which was performed using the "salmon index" command with default setting k-mer size k=31. The references used were the Genome Reference Consortium Human Build 38 (hg38, Genbank accession G C A _ 0 0 0 0 0 1 4 0 5. 1 5 ) f o r t h e h u m a n a n a l y s i s a n d Macaca_fasicularis_5. 0 (Genbank accession GCA_000364345. 1) for the macaque analysis. Raw counts were processed using the DESeq2 package in R/Bioconductor  (Love et al. , 2014)  (Supplementary Table  3 ).
Pre-ranked gene set enrichment analysis (GSEA) was performed using GenePattern and the gene sets belonging to the Molecular Signatures Database (MSigDB) v7. 5. Single-cell RNA sequencing (scRNA-seq): PBMC transcriptomic and clinical data from healthy and HBV-infected patients (n=23) was obtained from the Gene Expression Omnibus (GEO) database accession GSE182159  (Zhang et al. , 2023). Sample integration was performed using the FindIntegrationAnchors and IntegrateData functions of Seurat (v4. 2)  (Satija et al. , 2015). Cell clustering was performed with the FindClusters function of Seurat using a resolution of 0. 5 for the analysis, which resulted in 25 clusters. Marker genes for each of the clusters were identified with the FindMarkers function of Seurat and were employed to provide labels to 14 major cell types (Supplementary Figure  2A ).
Statistical analyses Comparison of cytokine levels in the supernatant of HBVstimulated and control samples was performed using a Wilcoxon matched-pairs test. Statistical tests were performed using GraphPad Prism software v9. 4 (GraphPad Software). Differential expression analysis between groups was performed using the Wald test in DESeq2. Gene expression changes were considered significant if presenting a false discovery rate (FDR) =<0. 05 following correction for multiple testing using the Benjamini-Hochberg method.
At the individual gene level, a clear example that illustrates this situation is interferon gamma inducible protein 16 (IFI16), a DNA sensor previously shown to inhibit HBV cccDNA transcriptional activity  (Yang et al. , 2020). Indeed, HBV stimulation induced the downregulation of IFI16 in human pDCs, which is markedly different from its upregulation in macaque pDCs (Figure  2E ). Furthermore, we wanted to explore if the impairment of IFI16 could be observed in vivo at later stages of the disease. Therefore, we analyzed a recently available scRNA-seq PBMC dataset  (Zhang et al. , 2023) , obtained from healthy controls (HC, n=6) or individuals at different stages of the disease, including immune tolerant (IT, n=6), immune active (IA, n=5), acute recovery (AR, n=3) and chronic recovery (CR, n=6) (Figure  2F , Supplementary Figure  2A ).
This is in line with previous reports describing how an increase in IFI16 expression following peg-IFN treatment was associated with hepatitis B e antigen (HBeAg) seroconversion in CHB patients  (Lu et al. , 2021). Considering that IFI16 levels increase following HBV clearance but do not seem to completely return to basal levels, it would be interesting to explore its potential epigenetic alteration. Indeed, this has been observed for components of the IFN-g pathway in response to HBV infection  (Lim et al. , 2018). In summary, our dataset serves as a valuable resource to gain a deeper understanding of immune responses taking place during HBV infection. This and similar studies could prove useful for the identification of potential targets against HBV. FR1503100944-I). The study was conducted in accordance with the local legislation and institutional requirements.
Patient population This was a retrospective review of a prospective ASD database collected from five centers. All patients were enrolled into an institutional review board-approved protocol by the respective sites. Data from all consecutive patients who underwent ASD surgery with a minimum follow-up of 2 years were obtained. Inclusion criteria were: age > 18 years and presence of a spinal deformity defined by one of the following parameters: Cobb angle ≥ 20°, pelvic tilt (PT) ≥ 25°, sagittal vertical axis (SVA) ≥ 5 cm or thoracic kyphosis (TK) ≥ 60°. For the present study, only patients with a preoperative CM > 20 mm were included for analysis.
Outcomes of interest Radiographic data were collected before surgery and at 6 months and 2 years postoperatively (coronal balance, Cobb angle, global tilt-GT and PI). All measurements were conducted on whole spine, frontal and lateral x-rays using the KEOPS Balance Analyzer 3D software (S. M. A. I. O. ). Leg length discrepancy (LLD) was evaluated for all patients, but as the observed LLD was not clinically significant in any of the considered cohorts, this parameter was not included in further analysis. Functional outcomes were evaluated with the Scoliosis Research Society-22r (SRS-22r), the Oswestry Disability Index (ODI) and the Short Form Health Survey (SF-36), which were obtained at baseline and at each followup. In addition, the occurrence of mechanical complications was recorded. The "Adherence" and "Non-adherence" groups were compared for baseline characteristics (age, gender, BMI, ASA score, radiographic characteristics and functional outcomes).
Statistical analysis Qualitative variables were analyzed in terms of frequencies and percentages for each parameter. Quantitative variables were expressed as means and standard deviations (SD). For the analysis on adherence vs non-adherence to the O-CM classification and the analysis on clinical outcomes in patients with CM at 2 years > or < 20 mm, baseline comparability was tested and T tests and Chi 2 tests were performed to compare the two groups for continuous and dichotomous variables, respectively. In case of baseline differences, a propensity score was calculated and used to perform a matchpaired analysis (caliper = 0. 2 SD) to adjust for possible confounders. The propensity score was calculated considering all obtained baseline data (demographic, radiographic and functional outcomes parameter), with a caliper of 0.
Mechanical complications Among the included patients, 105 were O-CM type 1 and 153 O-CM type 2. The summary of the baseline characteristics of the patients is shown in Table  1. Considering the baseline differences between the two groups, a propensity score was calculated considering all obtained baseline data (demographic, radiographic and functional outcomes parameter) and was then used to perform a match-paired analysis. The observed mechanical complications were distributed as follows: 46% were rod breakage and pseudarthrosisrelated complications; 22% were screws breaks and implant loosening; 32% were proximal junctional segment complications, such as kyphosis (PJK), failure (PJF) and adjacent segment degeneration. At 2 years, the unadjusted analysis showed fewer mechanical complications in the "adherence group" compared to the "non-adherence group" (31.
Characteristics of the study population Among the 191 patients followed in the two laboratories between 2012 and 2017, only 132 were included in this study due to missing data for some patients. The population was aged between 24 and 87 years; the mean age of the cohort was 54. 9 years (SD ± 12. 8 years). The majority of women were postmenopausal 76. 5% (101/132) and multiparous 84. 6% (77/91) with a maximum of 12 pregnancies. Moreover, age at first sexual intercourse varied between 10 and 22 years (median = 16 years). Only 35. 6% (36/101) had never been to school. Histological analyses showed that 6. 82% (9/132) of the patients had ADC, 12. 12% (16/132) had CIN3 and SCC was found in 81. 06% (107/132) of included patients (Table  1 ). The mean age of patients with CIN3 was 46. 7 years (SD ± 10.
The adopted databases were PubMed, Scopus, and Web of Science: key words included the "vascular parameter/technique" and ultrasound and precision/reproducibility/repeatability/accuracy/validation (see online supplemental Data S1). Within this phase other pertinent papers that the authors were aware of or references within the found literature were also considered. The contributions were critically revised by a core group of facilitators (EB, RMB, AG, KR), who harmonized the whole manuscript and solved the conflicts by consensus. The final manuscript was then approved by the whole subgroup. As a final step the paper was internally reviewed by three VascAgeNet members (Figure  4 ).
17%). Clinical impact. Common carotid IMT is known to linearly increase with age in both sexes, corresponding to the development of either atherosclerosis at the intimal level or medial hypertrophy. 7 levated IMT is considered as an early marker of atherosclerosis. Reference values for common carotid IMT are available and were determined in 24. 871 individuals (53% men; age range 15-101 years) using both RF and B-mode based processing techniques. 7 ncreased IMT is associated with cardiovascular events,  66  but has no added value for risk stratification on top of classical risk factors. 67, 68 However, monitoring IMT changes can be useful as a surrogate endpoint in cardiovascular drug trials. 66 rengths and Weaknesses-The approach is consolidated since 1) semi-automatic systems are available on the market; 2) literature data about the reliability of the measurement in terms of accuracy and precision are widely available; 3) reference values have been provided by the scientific community.
68-0. 96 for intraobserver and inter-observer variability, respectively. 88 linical impact. APs appear with ageing and cardiovascular risk factors: whereas their prevalence in the general population is around 20%, 69. 1% men and 54. 2% women >75 years old showed carotid AP. 89  The detection of a carotid plaque of 50% or greater, or as a focal region with an IMT measurement ≥1. 5 mm improves risk prediction  5  and its use is recommended in current ESC prevention guidelines to identify individuals at very high risk. 90 rengths and Weaknesses-Different US-based approaches are available, ranging from the simple plaque detection to more complex and sophisticated plaque description. For the latter, reference values based on large datasets are lacking as well as large studies regarding precision.
Diameter Vascular Characteristic-Arterial diameter can be defined both as lumen-intima interfaces distance (internal diameter) or media-adventitia interfaces distance (external diameter). Technological Approach-Diameter can be measured, similarly to IMT, on longitudinal scans with a linear US probe derived by standard B-mode, UHF B-mode, and RF data at different arterial sites (eg, carotid, radial, aorta, femoral arteries). With the introduction of automatic and semi-automatic methods, diameter assessment has become more reliable and instantaneous values, useful for distension assessment, can be obtained (Figure  7 ). For example, algorithms for contour tracking have been developed and a mean final result can take into account both different spatial and temporal contributions. Also for diameter estimation, adoption of robust algorithms for processing B-mode US image sequences has shown a good agreement and comparable reproducibility with RF-based measurement.
Non-linear negative relationships between age and carotid and femoral DC in both men and women were shown and age-and sex-specific reference values are available; these data were obtained from 22. 708 individuals (age range 15-99 years, 54% men) for the carotid and from 5069 individuals (49. 5% men, age range: 15-87 years) for the femoral artery, with both RF and B-mode based semi-automatic systems. 8, 35 arotid stiffness predicts CV events on top of classical CV risk factors. 120 Its changes over time have been used in clinical trials on cardiovascular drugs to monitor their effects. 121 rengths and Weaknesses-Different approaches for local assessment elasticity by ultrasound can be implemented. Direct analysis based on contour tracking techniques applied to longitudinal scans is consolidated thanks to the availability of literature about the reliability of the measurement.
For this reason, in addition to elastography, plaque kinematics, that is, plaque motion during the cardiac cycle, has also been investigated using ultrasound imaging ( 128 ). In particular, for carotid plaque, kinematic indices, including amplitude of tissue displacements, as well as intra-plaque movement, have been shown to be different in symptomatic and asymptomatic cases. 129, 130 ccuracy. ] [133]  Precision. Elastography parameters inter-frame repeatability is reported by CV (lower or equal to 16%  134  ) or intraclass correlation coefficient between two operators (0. 66-0. 84). 135, 136 linical impact. Data about the clinical impact of this technique, which is oriented toward plaque instability detection for stroke prevention, are scarce. Strengths and Weaknesses-There is still a lack of consensus and standardizations both in terms of settings and final optimal parameters, and further evidence Box 4.