dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analysis All variables were recorded to have lower value for lower limitation and higher value for higher limitation. Since higher values for the hand-grip results originally corresponded to lower limitation, these results were inverted (i. e. computing the inverse of the hand grip result) to have a similar trend between the other limitation evaluations. Then, all limitations variables are coded from the lowest to the highest limitations. Distribution of the data and associations between each of the four categories of selfreported limitations and the gait speed and hand-grip tests were described using mean with standard deviation, median and maximal and minimal values of each variable. General linear models were created for analyzing variance and the association between selfreported limitations and the gait speed and hand-grip tests, both without and with adjustments for gender, body mass, size and age.
This study was supported by  IReSP ,  CapaciT  project (Institute for research in public health, in French-http://www. iresp. net/). The CONSTANCES Cohort is supported by the  Caisse Nationale d'Assurance Maladie des travailleurs salaries-CNAMTS , and is funded by the  Institut de Recherche en SantePublique/Institut Thematique SantePublique , and the following sponsors:  Ministère de la santeet des sports, Ministère delegueà la recherche  ( ANR-11-INBS-0002 ), Institut national de la santeet de la recherche medicale, Institut national du cancer et Caisse nationale de solidaritepour l'autonomie. None of these funding institutions were involved in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.
Genetic analysis A rythmologic genes panel (CASQ2, CALM1, DSC2, DSG2, DSP, KCNE1, KCNE2, KCNQ1, KCNH2, KCNJ2, LMNA, NKX2-5, PKP2, RYR2, SCN5A, TRDN, CACNA1C genes) using next generation sequencing techniques on MiSeq (Illumina, San Diego CA), was performed on genomic DNA extracted from leucocyte of peripheral blood using standard techniques. It studied all exons and flanking intronic region of all genes and identified two heterozygous variations on CACNA1C (NM_199460. 3) and PKP2 (NM_004572. 3) genes. In the CACNA1C gene, a missense variant c. 1220A>C in exon 9 was found, predicting an amino acid substitution of an alanine (hydrophilic amino acid) for a glutamine (hydrophobic amino acid with loss of a negative charge) at codon 407 (p. Glu407Ala). This mutation had never been reported before and was missing from the gnomAD exomes database.
Discussion We report an unusual case of homogeneous adult Timothy syndrome with de novo novel heterozygous CACNA1C variation. She presented severe cardiac phenotype with incomplete TS1 features and the known c. 2146-1G>C heterozygous inherited variation of PKP2. The fact that the rythmologic genes panel was not targeted on the known deleterious regions of CACNA1C allowed us to diagnose this disease. Next generation sequencing is useful for genetic etiology in patients with rare non-classic phenotypes but results could be difficult to analyze. The assessment of the pathogenicity of the variant on several sites (gnomAD exomes database, PolyPhen, Varsome), the neomutation and the topography of the variation in front of p. Gly406Arg are in favor of very high probability of a damaging effect of the mutation.
Over the last two decades, the number of gene/protein sequences gleaned from sequencing projects of individual genomes and environmental DNA has grown exponentially. Only a tiny fraction of these predicted proteins has been experimentally characterized, and the function of most proteins remains hypothetical or only predicted based on sequence similarity. Despite the development of postgenomic methods, such as transcriptomics, proteomics, and metabolomics, the assignment of function to protein sequences remains one of the main challenges in modern biology. As in all classes of proteins, the growing number of predicted carbohydrateactive enzymes (CAZymes) has not been accompanied by a systematic and accurate attribution of function. Taking advantage of the CAZy database, which groups CAZymes into families and subfamilies based on amino acid similarities, we recombinantly produced 564 proteins selected from subfamilies without any biochemically characterized representatives, from distant relatives of characterized enzymes and from nonclassified proteins that show little similarity with known CAZymes.
Therefore, despite the development of faster, cheaper, and miniaturized experimental methods, ascribing a function to a gene product remains the main challenge of biology in the postgenomic era  (8). Reliable functional predictions are based on experimentally determined knowledge and on a suitable estimate of the divergence beyond which precise function cannot be readily extrapolated  (9). Inspection of sequence databases show that they are heavily polluted by erroneous functional predictions owing to the lack of universal similarity thresholds that can ensure robust propagation of protein function  (8, 10, 11). This problem has become particularly acute with the emergence of bioinformatic methods that can detect extremely remote sequence similarities  (12) (13) (14). The enzymes that assemble and deconstruct glycans have been classified into sequence-based families starting in 1991  (15) (16) (17) (18) (19) (20).
The functional diversity (specificity) of these enzymes is enormous and reflects the wide diversity of glycan structures found in nature. The database of carbohydrate-active enzymes (CAZymes), CAZy (www. cazy. org), compiles the various families of glycoside hydrolases (GHs), polysaccharide lyases (PLs), glycosyltransferases, and several other categories of enzymes that act on carbohydrates  (21). In the classification system that underlies the CAZy database, families are defined by sequences that cluster around at least one biochemically characterized member  (21). Interestingly, the sequence-based CAZyme families often group together enzymes of differing substrate specificity  (15) , showing that the acquisition of novel substrate specificity is commonplace among CAZymes. However, as observed in general protein databases, a similarity search conducted against the entries in the CAZy database essentially yields uncharacterized or unreliably named gene products and thus fails to produce reliable functional inference.
The substrates used as well as the organism of origin of the protein are indicated. "Weak" indicates limited cleavage. of family PL9 (GenBank accession no. AEI51087. 1) is not a PL, but rather a GH able to cleave the main chain of the exopolysaccharide (EPS) secreted by the ubiquitous cyanobacterium Nostoc commune. Therefore, this enzyme and its orthologs define a new GH family, GH160 (Table  3 ), which may share structural similarity with PL9 lyases. This is the first report of an enzyme able to degrade the EPS of Nostoc spp. The probability of ascribing a function to the most distant hypothetical sugar-cleaving enzymes (third set) was not expected to be very high; however, we validated GH or PL activities for approximately 18% (19 enzymes) of the 104 soluble proteins screened in this category (Table  3 ).
For example, the endoβ(1,4)-glucanase activity of a GH2_dist protein (GenBank accession no. WP_029428707. 1), revealed by the degradation of tamarin gum (xyloglucan), had not been previously observed in family GH2. Similarly, another GH2_dist protein (GenBank accession no. WP_029427454. 1) displayed a β-D-xylosidase activity not previously reported in family GH2. Interestingly, family GH2 was created in 1991 and has been the subject of numerous biochemical investigations. Therefore, our results demonstrate that polyspecificity remains underestimated even for such wellestablished GH families, with a direct impact on functional inference from sequence data only. Even more unexpected was the finding that the two distant relatives of the GH49 family (Gen-Bank accession nos. EDY96541. 1 and EDY96565.
1) can cleave a cell wall polysaccharide from the green algae Chaeotomorpha spp. and Cladophora spp. , whose backbone is composed of sulfated arabinan  (34) , a structure highly dissimilar to dextran and pullulan, previously known as the sole substrates of family GH49 enzymes. The results of NMR analysis of the reaction products of GenBank EDY96541. 1 are presented in SI Appendix, Fig. S4. The rationale for selecting the most distant hypothetical sugarcleaving enzymes category was to explore the frontiers of the CAZy families so divergent that bioinformatic methods failed to predict putative functions. Functional screening of the proteins of this category led to assignment of the function of enzymes that are the founding members of 13 new families, 2 of which were described by others during the course of our work.
In a virtuous circle, the novel families now define new frontiers to be explored. This method can now be extended to new sets of hypothetical sugar-cleaving enzymes. We have explored a portion of the large amount of sequence data rationally grouped and classified in the CAZy database. To continue exploring the diversity of sugar-cleaving enzymes, the production of several thousands of recombinant GHs and PLs is now technically possible  (35)  and is limited only by the cost of gene synthesis which, fortunately, continues to decrease. Thus, the main bottleneck for functional assignment likely is not protein production, but rather the availability of a large and diverse array of substrates. Although this was not a major problem for the screening of enzymes classified in subfamilies of the GH5 and GH43 families, the assignment of function to distantly related enzymes (GHxx_dist and PLxx_dist) and the most distant hypothetical sugar-cleaving enzymes depended directly on the diversity of substrates in the screening library.
Materials and Methods Bioinformatics: Selection of Targets. The daily updates of the CAZy database rely on the careful analysis of newly released protein sequences from GenBank by comparing them with previously analyzed/stored sequences  (21, 36). To obtain accurate annotation, our procedures make use of sequence libraries of varying levels of granularity: subfamilies, families, and remote relatives. In this work, targets were drawn from three categories: "uncharacterized subfamilies," "distant members within families," and "hypothetical sugar-cleaving enzymes. " Details of the selection process are provided in SI Appendix, Materials and Methods. Screening Experiments. For this study, E. coli codon optimization, gene synthesis, and cloning of the 539 targets was outsourced to NZYTech. High-throughput expression and purification assays were conducted following the protocol described by  Saez and Vincentelli (27).
ACKNOWLEDGMENTS. This work was supported by the  French National Research Agency  (Grant  ANR-14-CE06-0017 ) and the  French Infrastructure for Integrated Structural Biology (FRISBI)  (Grant  ANR-10-INSB-05-01 ). W. H. has received support from the  Glyco@Alps Cross-Disciplinary Program  (Grant  ANR-15-IDEX-02 ),  Labex ARCANE , and  Grenoble Graduate School in Chemistry, Biology, and Health  (Grant  ANR-17-EURE-0003 ). B. H. , N. T. , and R. V. have received support from  FRISBI  (Grant  ANR-10-INSB-05-01 ).
Trial registration number NCT02783898 (ClinicalTrials. gov). Findings: Two hundred forty-three participants were recruited over an 18-month period. A symptomatic rhythm was detected at 90 days in 69 (n = 124; 55. 6%; 95% CI 46. 9-64. 4%) participants in the intervention group versus 11 (n = 116; 9. 5%; 95% CI 4. 2-14. 8) in the control group (RR 5. 9, 95% CI 3. 3-10. 5; p b 0. 0001). Mean time to symptomatic rhythm detection in the intervention group was 9. 5 days (SD 16. 1, range 0-83) versus 42. 9 days (SD 16. 0, range 12-66; p b 0. 0001) in the control group. The commonest symptomatic rhythms detected were sinus rhythm, sinus tachycardia and ectopic beats. A symptomatic cardiac arrhythmia was detected at 90 days in 11 (n = 124; 8. 9%; 95% CI 3. 9-13. 9%) participants in the intervention group versus 1 (n = 116; 0.
net) email address of the coordinating Edinburgh research team. This email included a Portable Document Format (pdf) file attachment of the ECG tracing along with the participant's AliveCor app login (which was their study number; no identifiable participant data left the local site). The AliveCor app rhythm analysis algorithm automatically reported any ECG recorded as Normal, Atrial Fibrillation or Unclassified. The duty Consultant Emergency Physician at the coordinating Edinburgh centre along with a trial team Emergency Physician reviewed the ECG. The central study team contacted the local study team to arrange follow-up if required. In cases of disagreement, the central cardiology team were contacted for further opinion. If specialist follow-up of the ECG tracing was not required, the local study team wrote to the participant informing them and asked them to arrange follow-up with their general practitioner (GP) who was also contacted with the report.
They returned this diary to the local study team along with the participant satisfaction and compliance questionnaire, and smartphone-based event recorder at the end of the 90 days in a pre-paid stamped, addressed envelope. Participants failing to do this were reminded by phone. Participant study information identified by study number alone, was collected on a paper Case Report Form and then entered into a specially designed password protected online accessed secure database (REDCAP; http://www. project-redcap. org), the server of which was held within the University of Edinburgh. The primary outcome was assessed by each local study team.
Baseline data were therefore collected on 125 participants in the intervention group and 117 in the control group. Participants ranged from 17 to 74 years of age with a mean age of 39. 5 (SD 13. 7). Table  3  details examination findings, initial ECG and management. One participant in each group was lost to follow-up leaving 124 participants available for analysis in the study group and 116 in the control group. A symptomatic rhythm was detected at 90 days in 69 (n = 124; 55. 6%; 95% CI 46. 9-64. 4%) participants in the intervention group versus 11 (n = 116; 9. 5%; 95% CI 4. 2-14. 8) in the control group (RR 5. 9, 95% CI 3. 3-10. 5; p b 0. 0001). A symptomatic cardiac arrhythmia was detected at 90 days in 11 (n = 124; 8. 9%; 95% CI 3. 9-13. 9%) participants in the intervention group versus 1 (n = 116; 0.
There are different potential ways of incorporating the technology into patient care, which may depend on the configuration of local healthcare systems. In this study the devices and instructions were given to patients in the ED by a researcher, but this could also be undertaken at a follow-up appointment with a specialist nurse or family practitioner, where there is less time pressure than in emergency care. In this study, the ECGs were transmitted for central analysis; however, an alternative approach may be for the patient to show, on their phone, any recorded ECGs at a follow-up appointment. This would remove the need for the transfer of sensitive patient data and mean that a clinical system to respond to emailed ECGs would not be required. The AliveCor app rhythm analysis algorithm automatically reports any ECG recorded as normal, atrial fibrillation or unclassified with excellent sensitivity and specificity.
This study suggests that the AliveCor technology performs effectively and safely. The randomised, prospective design with systematic data collection is a key strength of the study. Whilst there was a potential variation in standard care between sites, this element of pragmatic design ensures our findings are generalisable across all types of standard care in the UK National Health Service without compromising validity. Potential limitations of our study include a large proportion of recruitment occurring in office hours largely by research staff in research active hospitals and the use of a central ECG reading service not available in routine practice. Only one type of device was studied and many similar devices are entering the market. We think that the results of this study will be generalisable across many forms of patient-activated, symptom-based home ECG recording devices.
Role of the Funding Source The study was funded by Chest, Heart and Stroke Scotland (Action Research Grant R15/A164; £23,056) and British Heart Foundation (BHF Project Grant no. PG/17/63/33198; £21,347) which included funding for purchasing the devices. MR was supported by an NHS Research Scotland Career Researcher Clinician award. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit.
To determine the relative size of the diastema, the vertical distance from the most ventral edge of hypural 1 to the most dorsal edge of the last hypural (see blue line in Fig. 1 ) was measured perpendicular to the body axis. The diastema between hypural 2 and 3 was measured along the same connecting line (see red line in Fig. 1 ). In some significant cases, the width of the CMCs in posterior view has been compared to the width of the hypurals (for orientation see Fig. 1B ). Measurements were taken from photographs using ImageJ v. 1. 50i software. Measurements for SL were taken with a digital calliper; sizes up to 120 mm are given with one digit after the decimal point and above this size rounded to the next millimetre. Photographs were taken either using a Leica M165C stereomicroscope with a Leica DFC425 camera and the Leica Application Suite (v.
4. 3. 0) software or using an Axiocam microscope camera attached to a ZEISS Discovery V20 stereomicroscope and processed with the Zeiss ZEN software. Anatomical nomenclature follows  Fujita (1989 Fujita ( , 1990) )  and the taxonomy follows  Eschmeyer et al. (2018). Results are given in systematic order, principally following  Nelson et al. (2016). For the phylogenetic relationships of major clupeocephalan clades we follow  Straube et al. (2018)  and  Betancur-R et al. (2017).
ACKNOWLEDGEMENTS We are grateful to all the colleagues supporting our studies by giving us access to specimens, sending loans and/or helping to facilitate field work for specimen sampling:  Hsuan-Ching Ho  ( National Museum of Marine Biology & Aquarium, Pingtung, Taiwan ),  Marc McGrouther  ( Australian Museum, Sydney, Australia ),  Matthias Bernreuther  ( Thünen Institut, Hamburg, Germany ),  Lourdes Fernández Peralta  ( Spanish Institute of Oceanography, Malaga, Spain ),  Alastair Graham  ( Australian National Research Collection, Hobart, Australia ),  Carsten Kühn  ( Institut für Fischerei, Born, Germany ),  Philippe Lalèyè  ( Université Abomey-Calavi, Benin ),  A. D. Tiomoko  ( Pendjari National Park, Benin ),  Peter Warth  ( Jena, Germany ),  Christian Lückstädt  ( ADDCON GmbH, Conn, Germany ),  Frederick Schedel und Ulrich Schliewen  ( Bavarian State Collection of Zoology, Munich, Germany ),  Alexander Dressel  ( Sharkcity, Germany ),  Jörg Bohlen  ( Academy of Science, Libenchov, Czech Republic ),  Gento Shinohara  ( National Museum of Nature and Science, Tokyo, Japan ),  Sandra Raredon  and  Jeff Williams  ( National Museum of Natural History, Washington, USA ),  Cindy Klepadlo (Scripps Institution of Oceanography, San Diego, USA) ,  Karsten Hartel  and  Andrew Williston  ( Museum of Comparative Zoology, Cambridge, USA ) and  Frank Schäfer  ( Aquarium Glaser, Rodgau, Germany ).
Methods This is a first-in-human, prospective, multicenter, open-label, single-arm study designed to characterize the efficacy and safety of the MINIject glaucoma drainage implant and its delivery system. The STAR-I study was conducted in accordance with the tenets of the Declaration of Helsinki, the protocol was reviewed and approved by all appropriate ethics boards (Maxivision Super Speciality Eye Hospital, Hyderabad, India; Clinica de Ojos Orillac-Calvo, Panama City, Panama) and all participants provided written informed consent to participate before enrolment. Participants were recruited from sites in Panama and India between June and October 2017. The trial is listed on clinicaltrials. gov with identifier NCT03193736. Eligible participants were at least 18 years of age and were diagnosed with open-angle glaucoma (primary or secondary), with open anterior chamber angles (Shaffer grades 3 or 4), and with IOP between 21 and 35 mmHg inclusive using 1 or more topical hypotensive medications.
No eye experienced an adverse event that was judged to be related to the device itself, and during the first 6 months after surgery, no eye required a secondary surgical procedure for surgical complications or device failure. In contrast, the rates of secondary surgical interventions reported with the iStent Inject and CyPass devices were 10. 9% and 17%, respectively, albeit through 12 months of follow-up. 24, 30 he Trabectome study reported an 8. 9% subsequent trabeculectomy rate after the procedure at undisclosed periods up to 30 months. 29 No clinically relevant changes in central or peripheral corneal endothelial cell counts were seen at 6 months, although long-term monitoring is necessary considering the CyPass COMPASS XT data  32  and is ongoing. This first-in-human MIGS study was designed to provide a preliminary characterization of the safety and efficacy of the MINIject glaucoma drainage device system in eyes with medically uncontrolled POAG.
Acknowledgments. The study investigators thank the independent members of the Safety Monitoring Committee:  A. G. Jünemann, MD  ( Rostock University, Rostock, Germany ),  R. D. Fechtner, MD  ( SUNY Upstate Medical University, Syracuse, NY ),  R. A. Eiferman, MD  ( University of Louisville, Louisville, KY ), and  L. H. Silver, PhD  ( Silver Pharma Consulting, Inc, El Paso, TX ). The authors also thank  Marc Buyse, ScD  ( IDDI, Louvain-la-Neuve, Belgium ), for statistical consultation and  Tony Realini, MD, MPH , and  Katherin Awad, BSc ,  MBA , for editorial assistance.
Detection of prophages Putative prophages were detected using VirSorter v. 1. 0. 3  (27)  with the RefSeqABVir database in all the complete genomes. The least confident predictions, i. e. , categories 3 and 6, which may be prophage remnants or erroneous assignments, were excluded from the analyses. We found 26 987 putative prophages, with a size ranging from 5 to 250 kb, and an average around 42 kb, which is consistent with our previous analyses  (28).
CRISPRs and cas clusters detection CRISPR arrays and cas genes clusters were detected with CRISPR-CasFinder v. 4. 2. 19 (29) (including Mac-SyFinder v. 1. 0. 2  (30)  and CasFinder v. 2. 0. 2  (30) ). The program is available at https://crisprcas. i2bc. paris-saclay. fr/ CrisprCasFinder/Index. Only CRISPR arrays with 3 spacers or more were used in our analyses. All results are reported in Supplementary Table  S1  and S2.
Subtypes could not be assigned with this method to CRISPRs outside CRISPR-Cas loci neither to CRISPRs in loci containing more than one subtype of cas clusters. To assign a type to the CRISPRs outside CRISPR-Cas loci, we searched for similarities between their repeats and those of CRISPRs that could be typed with the method described above. We used the information on the CRISPR subtypes, taken from the CRISPR-Cas loci with a single Cas subtype, to build a databank of 4979 unique repeats (direct and reverse complement sequences) that we could confidently assign to specific Cas subtypes. This was then used to type the other repeats (those in the remaining CRISPRs). For this, we quantified the sequence similarity between every pair of CRISPR repeats using a global alignment with no gap end penalty and equal gap creation and extension penalties (-3) using the module pairwise2 from Biopython (function align.