dataesr/scientific-paragraphs-categorization huggingface dataset:
0 fluorometer (Thermo Fisher Scientific, Italy). The metatranscriptome analysis was performed by FISABIO (Valencia, Spain) using the Illumina R NextSeq Mid Output platform (San Diego, CA, United States) with 2 × 100 bp short insert paired-end libraries (NextSeq Reagent Kit v2. 5). FISABIO also performed the quality assessment and the sequence joining (forward R1 and reverse R2). Quality assessment was performed with the PRINSEQ-lite program using the following parameters: min_length: 50 bp; trim_qual_right: 30 bp; trim_qual_type: mean; and trim_qual_window: 20 bp.
Whole-genome sequence analysis and annotation Metabolic pathways were predicted based on the annotated whole-genome sequences of the strains using the PathoLogic tool of the program Pathway Tools 26. 0  (Paley et al. , 2021). Information about enzyme encoding genes and the related metabolic pathways was extracted using the SmartTables function of the program. The network of metabolic pathways was visualized using Cytoscape 3. 9. 1 (https://cytoscape. org/). Horizontally acquired genomic islands (GIs) were identified using SeqWord Genomic Island Sniffer  (Bezuidt et al. , 2009). Genomic comparisons and synteny were visualized using Circos software  (Krzywinski et al. , 2009)  and Blast Dot Plot graph obtained by the RAST server  (Aziz et al. , 2008; Overbeek et al. , 2014; Brettin et al. , 2015).
Percentages of amino acid identity levels used as the input for Circos visualization and the Blast Dot Plot graph were obtained by the RAST server. Average nucleotide identity (ANI) was calculated for each genome couple compared using the ANI calculator (http://enve-omics. ce. g atech. edu/ani/index) as described previously  (Goris et al. , 2007; Rodriguez and Konstantinidis, 2014). The CRISPRfinder online program (https://crispr. i2bc. paris-saclay. fr/cgi-bin/crispr/ advRunCRISPRFinder. cgi) was used to detect CRISPRs system in all sequenced and annotated genomes of nanohaloarchaea. The NetNGlyc-1. 0 online program (https://services. healthtech. dtu. dk/ services/NetNGlyc-1. 0) was used to predict N-glycosylation sites in nanohaloarchaeal proteins using artificial neural networks that examine the sequence context of Asn-Xaa-Ser/Thr sequons  (Gupta and Brunak, 2002).
The whole-genome reference sequence of the strain Ca. Nanohalococcus occultus SVXNc [CP107255] was indexed using the buildindex function of the Rsubreads package (Bioconducter, www. bioconductor. org). The obtained Illumina RNA reads were mapped to the reference sequence by the function align of the Rsubread package. The numbers of reads aligned against each coding sequence of the reference genomes were counted by the function featureCounts of the Rsubread package and then normalized by the lengths of the coding sequences to Reads per Kilobase per Million reads (RPKM) values shown in Supplementary Table  S1. The prediction of ncRNA was confirmed by modeling the 2D structures of the ncRNA molecules using the RNAfold WebServer (http://rna. tbi. univie. ac. at/cgi-bin/ RNAWebSuite/RNAfold. cgi).
Genome methylation profiling For the prediction of genome methylation profiles, the PacBio reads were mapped against the whole-genome sequence of the strain Ca. Nanohalococcus occultus SVXNc using pbmm2 aligner of the software package SMRT Link v10. 1. 0. 119588 (https:// www. pacb. com/support/software-downloads/) followed by the prediction of methylated nucleotides and methylation motifs using ipdSummary and motifMaker tools of the SMRT Link package. The following command lines were used to run the pipelines on the server: pbmm2 index path_to_reference_FASTA_file path_to_reference _index_MMI_file. pbmm2 align -sort path_to_reference_index_MMI_file path_to_read_database_XML_file path_to_output_BAM_file. ipdSummary path_to_output_BAM_file -reference path_to_reference_FASTA_file -identify m6A, m4C -gff path_to_output_GFF_file.
Funding This study was supported by a grant from the  FUTURENZYMES  Project (Contract  101000327 ), funded by the  European Union 's  Horizon 2020 Research Program. MK was supported by  Agence Nationale de la Recherche  grant  ANR-20-CE20-0009. This work has been additionally supported by the project "Emergence of virulence and antibiotic-resistance vectors in coastal and deep sea marine environments and analysis of the mechanisms and conditions underlying their spread and evolution" funded by the  MIUR Progetti di Ricerca di Rilevante Interesse Nazionale (PRIN)  Bando 2017 -grant  201728ZA49_001  and by the project " Innovazione tecnologica per la tutela e valorizzazione degli ecosistemi marini (ITEM) " funded by  MIUR   CTN02_00059_9948371.
Registry (COVID-19 tracker) Twenty-six tertiary ACHD centres from nine European countries participated in this prospective, multicentre, cohort study. All ACHD patients who are tested positive for SARS-CoV-2 or with a strong clinical suspicion (clinical signs highly suggestive of COVID-19) presenting to or contacting one of the participating centres were included. Clinical observations were recorded and updated at regular time intervals until recovery or death and reported to the study coordinators at the University Hospital Inselspital in Bern, Switzerland. Data was initially collected weekly, later bi-weekly and monthly and were summarized in a report with all pertinent information related to demographics, clinical characteristics, and clinical outcomes of ACHD-patients with COVID-19, allowing incorporation of 'real-time' risk data into day-to-day clinical work at participating centres.
Statistical considerations SPSS software (version 26. 0, SPSS Inc. , Chicago, Illinois) and STATA 15 statistical software (Stata Corporation, College Station, TX, USA) were used for the analysis of the data. Distribution of continuous variables was assessed using skewness, kurtosis, and visual inspection of the histogram. For the comparison between surveys, results of nineteen valid matched pairs (survey 1 vs survey 2) were analysed. Data related to five surveys of the first round were excluded from the analysis because the corresponding ACHD experts did not answer to the second round of the survey. For the analysis of the COVID-19 Tracker, patients with missing data related to the date of COVID-19 diagnosis, as well as patients with missing outcome data were excluded. Continuous variables were presented as means (standard deviation [SD]) or medians (interquartile range [IQR]) and compared using paired t-test, or Wilcoxon, as appropriate, for the comparison of dependent samples (comparison of answers between the two surveys), and t-test or Mann-Whitney U test for the comparison of independent samples (stratified patient characteristics).
Comparison between surveys Overall, 43 surveys (24 from the first wave and 19 from the second one) were collected. A total of 19 valid matched pairs (survey 1 vs survey 2 for each participant) were analysed. A detailed comparison between surveys conducted in April 2020 and March 2021 is depicted in Table  S2  and Fig. 1. In both surveys, only a minority of participating ACHD physicians considered all ACHD patients to be at risk in case of COVID-19. With the ongoing pandemic, registry data replaced national or working group consensus documents as primary source for risk stratification. At the time of the second survey, 95% of all participants relied on registry data for risk counselling. The use of other sources for this purpose did not importantly differ between surveys (Table  S2 ). Fig. 1  depicts the perceived importance of general and ACHD specific risk factors for a complicated COVID-19 course.
Analysis of the COVID-19 tracker From a total of 700 patients included into the registry, 638 individuals (91%, n = 168 for the first wave and n = 470 for the subsequent waves) with valid data on date of diagnosis and outcome were included. The median (IQR) age was 34 (26-44) years and 52% were women. The diagnosis of COVID-19 was confirmed by means of laboratory testing in 576 (90%) of the patients. Thirty-six percent of the patients had a cardiac defect of mild anatomical complexity, while defects of moderate and severe complexities were found in 35% and 29% of the participants, respectively. There were 36 (6%) cases with a complicated disease course, of whom 17 died (2. 7% overall). The proportion of cases with a complicated disease course stratified by CHD and complexity, main residual heart defect-related problem and number of comorbidities is depicted in Fig.
Acknowledgements Anissa Boubrit ,  Université de Paris, Hôpital Européen Georges Pompidou, Paris, France ;  Francisco Buendía Fuentes, Adult Congenital Heart Disease Unit, Department of Cardiology, Hospital Universitari i Politècnic La Fe and CIBERCV, València, Spain ;  Julie De Backer ,  Department of Cardiology, Ghent University Hospital, Belgium ;  Michèle De Hosson ,  Department of Cardiology, Ghent University Hospital, Belgium ;  Laura Dos Subirà. Unitat Integrada de Cardiopaties Congènites de l'Adolescent i de l'Adult Vall d'Hebron-Sant Pau, Department of Cardiology, Vall d'Hebron University Hospital and CIBERCV, Barcelona, Spain ;  Rocío García-Orta ,  Adult Congenital Heart Disease Unit, Department of Cardiology. Hospital Universitario Virgen de las Nieves. Granada. Spain. 2  Instituto de Investigación Biosanitaria ibs.
Locus In the mitochondrial locus, 40 segregating sites in the 102 sampled individuals defined 26 different haplotypes. Overall, NADH2 was the most polymorphic locus, showing the highest number of segregating sites, haplotypes and nucleotide diversity (π = 0. 059) (Table  1 ). For most loci and populations, there were no significant deviations from neutral expectations as suggested by non-significant Tajima's D and Fu's F s estimates (Supplementary Table  1 ). Nuclear and mitochondrial sequence data have been submitted to the GenBank database (accession numbers ON918736-0N920126). A very strong pattern of population genetic structure was revealed by the mitochondrial network, with the haplotypes distributed in three clearly segregated groups and no allele sharing between them (Fig. 1a ). The group formed by the haplotypes sampled in the Western Pacific was deeply divergent (thirteen substitutions apart) from the clades sampled in the Central Pacific and Atlantic Ocean, corresponding to 1.
Phylogenetic relationships among major clusters and the historical demography The *BEAST analyses using the mitochondrial and nuclear datasets combined provided strong support for the same topology across replicate runs and suggested a basal group of Bulwer's petrels from the Western Pacific, and a well-supported sister relationship between the Central Pacific populations and those sampled in the Atlantic Ocean (Fig. 3 ). The relationships of the different populations within the Atlantic clade are not well resolved. Implementation of the IMa2 model to three main genetic groups of Bulwer's petrels, suggested by the BEAST analysis with the combined dataset, and the STRU CTU RE analysis, obtained convergence, low autocorrelation values and posterior density curves that showed clear peaks for all demographic parameters estimated (Supplementary Fig.
Discussion Our results uncovered a contrasting phylogeographic pattern between the two main ocean basins where the species occurs, including an older evolutionary split between two distinct, isolated lineages evolving in the western and central Pacific Ocean, and a third, panmitic group in the Atlantic Ocean. The remarkable genetic differentiation within the Pacific Ocean but also between ocean basins reveal that both physical and paleo-oceanographic barriers have played an important role in the evolutionary history of this highly vagile, pan-tropical species. In the present study, the pattern of population differentiation inferred from the complete dataset suggest that the Bulwer's petrel populations from the Atlantic and Pacific Ocean basins are genetically differentiated, as well as those breeding in the Western and Central Pacific groups.
The pattern is more clear with the mitochondrial locus whereas the nuclear data suggest a pattern of intermediate polyphyly between the Central Pacific and Atlantic groups. This is likely due to the nuclear lineages incomplete sorting, in line with the general expectation that nuclear loci will rarely show strong support for monophyly in recently diverged populations  11, 18, 32, 33. Despite the absence of obvious physical barriers between Japan and Hawaii, we found two deep evolutionary lineages of Bulwer's Petrels breeding in these archipelagos, which have been evolving independently for many generations, historically having exchanged very few to no migrants. This pattern of isolation despite the lack of  Bayesian assignments of co-ancestry for all sampled Bulweria bulwerii individuals based on nuclear anonymous genotypes.
Amplification of this fragment was carried out in 25 µl volume reactions containing the same final reagent concentrations as were used with the nuclear loci  30  , as well as the same thermocycler profile but with an annealing temperature of 58 °C. All loci were sequenced in both directions. Sequences were assembled into contigs, aligned and edited in SEQUENCHER v. 4. 2 (Gene Codes Corporation), which was also used to check the validity of the base calls. Seven loci displayed heterozygous length polymorphisms, and all gaps from the data sets were trimmed. The phase of nuclear alleles with multiple heterozygous SNPs were resolved using the Bayesian algorithm implemented in PHASE v. 2. 1. 1  47. Input files were prepared for PHASE using the software SeqPHASE  48. Polymorphism and population structure.
Median-joining haplotype networks, based on the largest blocks of non-recombining fragments, were estimated for all loci using NETWORK v. 4. 6. 0. 0 55 (https:// www. fluxus-engin eering. com/ share net. htm). To detect population structure without the need to define a priori the populations, we used Bayesian clustering analyses, as implemented in STRU CTU RE 2. 3  56  (https:// web. stanf ord. edu/ group/ pritc hardl ab/ struc ture. html). We ran two sets of analyses depending on how the data was formatted: the first set used allelic data for each of the nuclear locus, and the second used the dataset converted to SNPs. There were no differences in results between the two sets and we present results only for the former dataset. In the final analysis, In STRU CTU RE, colony of origin was not used as prior information, and analyses assumed an admixture model and correlated allele frequencies among populations.
We performed 10 replicate runs for each K value, which varied between 1 (single population) and 6. Each replicate was run for 1 million iterations, with a burn-in of 100,000 iterations. The value of K that best fitted the data was estimated using the method of  31  implemented in STRU CTU RE Harvester  57. Since this method tends to recover the highest hierarchical level of population structure  31  , we re-ran STRU CTU RE to test for further structuring, using the same run parameters as above. Phylogenetic relationships among groups. We used the *BEAST algorithm based on the multi-species coalescent  58  as implemented in the software BEAST 1. 7  59  to estimate a species tree for the sampled taxa, using the mitochondrial and nuclear loci. The recovered topologies of the tree were the same across replicates.
As most species trees methods, *BEAST requires a priori assignment of alleles to taxa. We used the well-supported and geographically structured mtDNA network for prior assignment. The input was prepared with BEAUti v1. 7 (http:// evomi cs. org/ resou rces/ softw are/ molec ular-evolu tion-softw are/ beauti/). We ran *BEAST multiple times to test different priors and settings, and to assess convergence and mixing. The results shown are based on final runs which ran for 10 9 generations (convergence was compromised by low signal of some genes, and required very long runs), sampling every 10,000 generations, with a burn-in of 10 6 generations. We chose the most appropriate model of sequence evolution for each locus (see above), used a strict molecular clock, which could not be rejected for this dataset, and a Yule process for the species tree prior, and other priors were changed according to operator weight suggestions from previous runs.
We monitored convergence of the sampling process using TRACER 1. 5  60  , ensuring that the ESS values were above 200 and parameter posterior distributions were unimodal. Trees were summarized in TreeAnnotator v. 1. 7  61  and visualized in FigTree 1. 3. 1 (http:// tree. bio. ed. ac. uk/ softw are/ figtr ee/). We assessed nodal support using posterior probability estimates. We used a substitution rate for the NADH2 locus of 0. 028 × 10 -646 , and the nuclear rate was allowed to be estimated relative to the mtDNA rate. Coalescence estimates of historical demography. We inferred the demographic history of Bulwer's Petrel with IMa2 62 using the full data set of twelve anonymous nuclear and NADH2 loci. IMa2 implements a coalescent-based method that uses Markov Chain Monte Carlo sampling of gene genealogies to estimate population parameters scaled by the mutation rate per locus per generation (μ), such as contemporary and ancestral effective population sizes (θ, where θ = 4N e μ, and N e is the effective population size) migration rates (m = M/μ, where M is the effective migration rate per generation) and divergence times (t = Tμ, where T is the divergence time in years before present) among populations.
Acknowledgements The four samples from  Raso Islet ,  Cabo Verde , were sent to us by the late  Luís Monteiro ,  Universidade dos Açores. We thank  Vânia Ferreira  and  Mauro Silva  for lab assistance and data collection, and  J. M. Soares  and the  Clube Naval from Santa Maria Island, Azores , for transportation to Vila islet. This research was funded by  Fundação para a Ciência e a Tecnologia (FCT, Portugal)  through projects  OCEANTREE-PTDC/BIA-EVL/28565/2017 ,  UIDB/BIA/00329/2020  granted to cE3c;  UIDP/50017/2020 ,  UIDB/50017/2020  and  LA/P/0094/2020 , granted to CESAM;  UIDB/04292/2020  and  UIDP/04292/2020 , granted to MARE; project  LA/P/0069/2020  granted to the  Associate Laboratory ARNET  and  PTDC/BIABDE/67286/2006  (also funded by  FEDER  through the  Programme COMPETE-Ref :  FCOMP-01-0124-FEDER-007061 ) granted to JB.
Objective: Studies have demonstrated that exercise bene ts executive function. However, it is still unclear which exercise mode is optimal for protecting executive function among young adults and the evidence of the cerebral blood ow (CBF) mechanism of exercise on cognition. Thus, this study aimed to compare the intervention effect and the CBF mechanism of high-intensity interval training (HIIT) and moderateintensity continuous training (MICT) on executive function. Study design: This was a double-blinded randomised controlled trial study conducted from October 2020 to January 2021 (ClinicalTrials. gov identi er: NCT04830059). Ninety-three healthy young adults were randomized into the HIIT (N=33), MICT (N=32), and control groups (N=28). Participants in exercise groups were guided to perform 40 minutes of HIIT and MICT three times a week for 12 weeks, and the control group received health education for the same period.
Descriptive analysis of the demographic information The descriptive analysis of the study population is indicated in Table  1. Sixty-seven subjects were included in the data analysis (HIIT = 26, MICT = 21, CON = 20), and all participants were analyzed according to the initial grouping. There were no signi cant differences among groups in the demographic information, including age, height, Body Mass Index (BMI), years of education, and birthplace. No signi cant difference was found in baseline maximum oxygen uptake (VO 2max ) between groups. Overall, 49. 8% of the study population was male. Three groups of participants were 25. 23 ± 2. 18 years old on average, with a mean BMI of 21. 91 ± 2. 92 kg/m 2. The mean VO 2max of all the participants was 43. 71 ± 6. 98 mL/(kg•min). There was no signi cant difference in the effect of acute MICT and HIIT on RPE and PACES, indicating no difference in subjective fatigue and enjoyment between two exercise groups (Table  S1 ).
Study design and population We conducted the double-blind, randomized controlled trial (RCT) study from October 2020 to January 2021 using randomization, assignment concealment, and blinding methods (ClinicalTrials. gov identi er: NCT04830059. Data: 02/04/2021). Ninety-three participants met the inclusion criteria and were randomized into HIIT (n = 32), MICT (n = 33), and control groups (n = 28). Demographic information was collected, including age, gender, height, weight, family income, education level, and birthplace (rural or urban). Each participants had a unique identi cation number. They were randomly divided into different groups using a random number generator. The randomization process was carried out by a research staff who was not participated in the assessment and analysis of the data.
Group allocation was con dential to ensure the successful implementation of randomization. The participants' identi cation number and grouping information were hidden in an opaque envelope, which was opened by themself after the baseline assessment. Moreover, participants in the three groups came to the tness center on different days of the week, so they didn't know the existence of other groups. Participants and evaluators were blinded to the group allocation of intervention assignments throughout the study. Detailed information on the randomization, assignment concealment and blinding methods is described in the previous article  38. The sample size was calculated by the software of G-Power (Version 3. 1. 9. 7). We assumed that the effect size of the exercise intervention was medium (the effect size was set as 0.
Secondly, our sample was small considering the methodological limitations, such as the downfalls of CBF assessment with transcranial Doppler ultrasonography due to the thickness of the temporal bone, which even resulted in some participants where no signal could be acquired at all. However, all the CBF indexes were assessed by the same researcher and measured in a similar way during the whole process of the research. Additionally, we checked and con rmed data quality during preprocessing to ensure the measurement validity of CBF. Thirdly, the intermediary effect of CBF were not found, which may be due to the small sample size. We were able to identify a signi cant association between CBF and executive function. Thus, well-designed randomized controlled trials with larger sample sizes are needed to assess the effects of exercises on executive function and the mediation mechanism of CBF.
RNA Extraction and RNA-Sequencing Total RNA was extracted from the hiPSC-BAP 3D at D0 and D10 of differentiation using TRIzolTM Reagent (Sigma-Aldrich, Saint-Quentin-Fallavier, France). The quality of the RNAs was verified with RNA 6000 nanochips on the agilent 2100 bioanalyser. Purified RNA (200 ng) was used for the library preparation. Briefly, RNA libraries were prepared using the TruSeq Stranded mRNA Library Preparation Kit (Illumina, San Diego, CA, USA) following the manufacturer's instructions. The libraries were sequenced on the NextSeq system (Illumina) using a paired-end 2x75 bp protocol. Three biological replicates per condition were sequenced. The GEO accession number for the sequencing data was GSE223241.
Bioinformatic Analysis For RNA sequencing, the demultiplexing of the sequence data was performed using bcl2fastq Conversion Software (Illumina; bcl2fastq v2. 19. 1). The trimming of adapter sequences was performed using cutadapt software (version 1. 7. 1). Reads quality control was assessed using FastQC (v0. 11. 5). Subsequently, sequence reads from FASTQ files were aligned to the human genome GRCh38, downloaded from Ensembl 108. Alignment was performed using STAR aligner (version 2. 5. 2b). Over 19 millions of 75 base pairs PE-reads reads were generated per sample. The normalized counts of the different genes and isoforms were performed using RSEM (v1. 2. 31) using a GTF from Ensembl 108. Finally differential expression was performed using R version 3. 6. 3 and DESeq2 package v1. 24. 0. An adjusted p-value < 0.