dataesr/scientific-paragraphs-categorization huggingface dataset:
Mutants Δ20 and C showed FLuc levels comparable to WT in the presence and absence of miR-122, respectively, whereas FLuc levels of ISL were strongly reduced, in line with the previously demonstrated impact of these mutations on the folding of SLII. At later time points, no replication was observed for any construct in the absence of functional miR-122 (Fig. 5d , miR mut ), again demonstrating the important contribution of miR-122 to stability and replication of HCV genome. Yet, the mutants, all incapable of miR-122 binding, showed a divergent behavior: While the ISL mutant, impairing SLII formation, remained replication deficient even in the presence of miR-122, mutations Δ20 and C restored viral replication due to their capability to efficiently support SLII folding (Fig. 5c ). These data again emphasized the contribution of translation stimulation by miR-122 to HCV replication and provided further experimental evidence suggesting that mir-122 binding suppresses unfavorable folding of SLII.
More elaborate in cell techniques will therefore be required in future studies to clarify whether miR-122 indeed prevents alternative RNA folds interfering with IRES activity. We generated several mutants of DI predicted to either favor SLII formation or alternative structures interfering with IRES function. Alterations in DI that were designed to suppress deleterious structures, and in turn stabilize SLII, indeed activated early translation in absence of miR-122. Mechanistically, we could observe a shift towards 80S formation in ribosome profiling assays for the SLII stabilizing mutants Δ20 and C, comparable to the addition of miR-122 to WT genomes. These data argue for a stabilized functional SLII, as this feature promotes eIF2 dissociation, and enables 60S recruitment  20. Accordingly, the ISL mutant, stabilizing SLII alt showed an inverse phenotype of abrogated translation and a block at the 40/48S stage.
These results corroborate a previous report of Filbin and colleagues, observing a similar behavior of a ΔSLII construct  29. The data obtained with the DI mutants therefore are the strongest support for our hypothesis of a strong impact of DI on the folding of a functional SLII element. However, studies addressing HCV IRES structure often excluded DI, since it is not part of the IRES and thereby missed the negative impact on SLII formation  30. Our data suggest that the predicted structural variation at the 5′ terminus of the HCV genome could simply be the result of the reciprocal evolutionary pressure on the active conformations of each strand (SLII vs. SLIIz′). Hence, miR-122 could assist the dual function of these complementary sequences and prevent deleterious folds. Currently it is not known whether miR-122 is already bound to the viral RNA within the virion or meets the 5′ UTR upon release of the genome into the cytoplasm of a newly infected cell.
pFK-I 341 PILuc-ubi/NS3-3′/JFH1 (PI-Luc-SG) has been used in a previous study  40. It was generated by replacing the HCV IRES of pFK-I 389 Luc-ubi/NS3-3′/JFH1 with the HCV 5′ UTR-Polio IRES cassette from pFK-I 341 PILuc/NS3-3′/JFH1 41 using SbfI and XbaI (NEB). pRL-CMV (GenBank AF025843) was used for in vitro transcription of Renilla luciferase mRNA, as spike-in template for translation assays. pUC18 vectors were used for transcription of HCV 5′ UTR truncations (1-120nt, 40-120nt) for NMR analysis. The fragments were amplified from pFK-I 389 Luc-ubi/NS3-3′/JFH1 plasmids with primers harboring SbfI and SmaI sites. pFK-I 341 PINLuc/I 389 FLuc/NS3-3′/JFH1 (Bi-Luc-SG) was generated by insertion of a fusion PCR product of the I 341 PI cassette from pFK-I 341 PILuc/NS3-3′/JFH1 and the Nano Luciferase gene from pNL1.
The bands were quantified by phosphor imaging using a Molecular Imager FX scanner (Bio-Rad). SHAPE data were analyzed with SAFA  51. The data were normalized to the mean of the top 10% reactivities. Intermediate reactivity (0. 2-0. 8) is indicated in yellow, highly reactive nucleotides (>0. 8) are colored in red. For differential analysis of miR-bound versus free RNA the normalized values were subtracted and all differences of at least 0. 3 were considered as significant. Less reactive nucleotides are depicted in green, more reactive in red. For SHAPE, dimethyl sulfate (DMS) and nicotinoyl azide (NAz) probing of the full-length HCV genome, RNA was transcribed, purified, and folded as previously described  18. Briefly, RNA was in vitro transcribed by runoff transcription with T7 RNA polymerase followed by treatment with RQ1 DNase (Promega).
Acknowledgements We are grateful to  Rahel Klein  and  Ulrike Herian  for excellent technical assistance. We thank  Jérome Boisbouvier  and  Bernhard Brutscher  ( IBS, Grenoble, France ) for aiding in interpretation of NMR data. The study was funded by a grant from the  Baden-Württemberg Stiftung  to V. L. ( BWST_NCRNA_024 ). This work used the  High Field NMR, Biophysical  and  Cell-Free  facilities at the  Grenoble Instruct-ERIC Center (ISBG ;  UMS 3518 CNRS-CEA-UJF-EMBL ) with support from  FRISBI  ( ANR-10-INSB-05-02 ) and  GRAL  ( ANR-10-LABX-49-01 ) within the  Grenoble Partnership for Structural Biology  (PSB). C. M. benefited from an  ANRS  fellowship. A. R. was supported by the  Deutsche Forschungsgemeinschaft  ( SFB 1129 TP13 ).
Acknowledgements This work was supported by a grant from  Agence Nationale de la Recherche  ( ANR-11-JS07-011-01 ) and the  Institut National du Cancer  ( PLBIO 2014-152 ). A PhD fellowship (to T. P. A. T. ) was supported by  VIED  grant  911. We would like to thank  Dr. Annie Ladoux  for kindly providing us HEK93 lysates and  Dr. Stéphane Azoulay  for helpful discussions. We would also like to acknowledge the " GIS Chimiothèque Nationale"  for the constitution of the  French National Chemical Library  and the  Essential Chemical Library  screened in this work.
Acknowledgments The authors would like to greatly acknowledge all the persons and informants who participated in this study namely the following students from INATAA institute:  Alaeddine OKKI ,  Abdelkarim BENSID ,  Ibrahim GHENNAM ,  Oualid ADEL ,  Fahem MOUS-SAOUI ,  Selma BOUDJADA ,  Meryem KEHAL ,  Ahlam BENDJEDOU ,  Djahira CHENINA ,  Rahma GATER.
Data collection The French network of cancer registries has been previously described  [21]. A cancer registry specifically collecting data about primary tumors of the CNS is based in Gironde, a department located in southwestern France. With an area of 9975 km 2 , it's the largest French department. The population was estimated in 2012 to be 1,483,712 inhabitants (including 257,155 children and 92,327 adolescents). The sex ratio M/F was 0. 92 and about 78% of the population lives in urban area (with a ratio urban/rural = 3. 56). All neurosurgical activity was based in Bordeaux where the registry is located and no adjacent department had a neurosurgical institution. Expertise in pathology was mainly located in the University Teaching Hospital, which was the regional center of reference for public and private laboratories.
Twenty-nine CT and 30 MRI machines are now available in the Gironde area, installed in the 1980s in the largest health centers. Patients from Gironde with suspected CNS tumors are unlikely to be referred outside the area, as the regional neurosciences center is based in Bordeaux. From May 1999, all patients who lived in the department of Gironde in whom any new primary tumor of the CNS was diagnosed, whether symptomatic or asymptomatic, benign or malignant were prospectively registered. Spinal tumors were included. We excluded pituitary tumors, tumors associated with AIDS, recurrence of tumors, and metastatic tumors. No case was obtained from autopsy or from a death certificate only. Collection of the data is exhaustive because of the collaboration of a work group comprising practitioners (neurosurgeons, neuropathologists, medical oncologists, radiotherapists, neurologists, etc) involved in the diagnosis and therapeutic management of patients.
To identify eligible cases and minimize the number of cases that may have been missed, multiple overlapping sources were used: (1) clinical reports obtained through registration forms filled in by practitioners, (2) extractions from the French National Hospital Database (PMSI) for relevant discharge data, (3) neuropatholology reports, (4) requests to the French Health Insurance Organization (Affections de Longue Durée) for free health treatment for CNS tumors, (5) death certificates, and (6) other cancer registries (The French National Registry of Childhood Solid Tumours and the Gironde Registry of Hematopoietic Malignancies). Medical data were individually reviewed to ensure that the diagnoses were eligible, to check for the diagnosis date (from April 1999), and to fill in exclusion criteria.
All duplicate cases were thoroughly searched and excluded. To ensure completeness, a periodic review of archives and pathology records was performed in the relevant departments and laboratories. Diagnosis was based on clinical and radiological data with or without histological confirmation. Whenever a surgical specimen was available for neuropathological analysis, the slides were systematically reviewed by a pathologist not involved in the initial diagnosis. When biopsy or surgical resection of the tumor was not possible, a monthly assessment was made by experienced neuroradiologists, neurosurgeons and radiotherapists to ascertain the diagnosis. The following parameters were systematically recorded: date of birth, sex, postal code of usual residence, date of diagnosis, topography, and tumor histological subtype and grade.
Incidence rates were standardized on the 2000 US Standard Population  [31] , the Segi World Standard Population  [32]  and the Scandinavian "European" Standard Population  [33]  using the direct method of analysis to allow comparisons with other cancer registries. The annual age-standardized incidence rates (per 100,000) were calculated globally and separately for male and female. For trends, a piecewise log linear model with constant variance and uncorrelated errors was run, using Joinpoint software (version 3. 4. 2) available on the Surveillance, Epidemiology and End Results (SEER)*Stat pages on the US National Cancer Institute website (https:// surveillance. cancer. gov/joinpoint). The method implemented in the software allows choosing the number and the locations of joinpoints and testing whether an apparent change in trend is statistically significant.
The test of significance uses a MonteCarlo permutation method. We considered two jointpoints because the number of data points was 13. The date of onset was aggregated into calendar years. We characterized trends in age and sex-standardized incidence rates using the French National census 2000-2012 by estimating APCs with 95% CIs. P < 0. 05 was considered statistically significant. All tests were two-sided. Here we present data collected from January 2000 to December 2012.
While previous analyses have hypothesized that selection makes functional and genetic modularity converge  22, 44, 45, 82, 83  , other studies indicate that different morphological structures can perform equivalent functions and, therefore, there can be considerable flexibility in the neutral divergence  84, 85  or among-trait connectivity, independent of their function  19, 48. Whatever the case, our results indicate that the modular landscape of the human face can be affected by both, genetic ancestry and the morphospace under study (asymmetric versus symmetric). Furthermore, these results are of importance to future Genome Wide Association Studies based on CANDELA (and other) datasets, since they provide a first identification of integration and modularity at the phenotypic scale, that can be used to submit more refined traits to the association analyses, as a preferred approach instead of heuristic searches based on analyzing non-supervised, raw characters.
The same sample was used on a recent contribution  34, 37, 86  and conforms the main database of the CANDELA consortium  34, 37, 66, 67, 86, 87. All methods and procedures used here were performed in accordance with relevant guidelines and regulations (see below). Validation dataset are available to download from https://laofunam. com/data. Facial shape was captured following scientific photographic protocols described in detail in references  34  and  86. Upon these images, two observers (MQS and LC) placed a set of 34 standard facial landmarks using Photomodeler (http://www. photomodeler. com/ Eos Systems Inc, Vancouver, Canada). As described elsewhere  34, 86  , this platform corrects for any lens distortion automatically, and we have followed the standard recommendations for quality and accuracy provided by the software.
A scale factor was assessed using the nasion-gnathion distance measured directly on the individuals using a standard anthropometric caliper. On each individual, blood samples were collected and DNA extraction was performed following standard laboratory procedures. Genomic data involving 730,525 marker SNPs was obtained from these samples (see further details in ref. 37  ). The SNPs were pruned to remove Linkage Disequilibrium, and after removing correlated SNPs, 90,000 SNPs were left for analysis. Ancestry estimation was performed with this SNP data. Genome-wide average heterozygosity was estimated from this data using PLiNK  88, 89  , which provides a measure of excess heterozygosity compared to the overall sample. It is calculated as 1-excess homozygosity, while excess homozygosity is estimated using the inbreeding coefficient as the average excess of homozygous alleles across all SNPs for an individual as compared to the overall sample.
To enable among-subsample comparisons, individuals were allotted to American, European, or Admixed groups if their population-specific ancestry markers were above 80% in the first two cases, and below that percentages in the third group (admixed). Preliminary statistical analyses: error measurement and acquisition of the symmetric and asymmetric components of variation. Since on a previous paper  86  we have demonstrated that measurement error in size and shape was significantly lower than variation in FA, and thus negligible, the rest of the analyses were based on a single digitization of landmarks. For the multilevel analysis of morphological integration and modularity, we first decomposed the total shape variation into its symmetric and asymmetric components by conducting a Procrustes ANOVA on the total dataset.
Acknowledgements We are grateful to the volunteers of the CANDELA sampling for their enthusiastic support for this research. We thank  Alvaro Alvarado ,  Mónica Ballesteros Romero ,  Ricardo Cebrecos ,  Miguel Ángel Contreras Sieck ,  Joyce De la Piedra ,  María Teresa Del Solar ,  William Flores ,  Martha Granados Riveros ,  Ilich Jafet Moreno ,  Jodie Lampert ,  Paola León-Mimila ,  Francisco Quispealaya ,  Diana Rogel Diaz ,  Ruth Rojas ,  Norman Russell ,  Vanessa Sarabia ,  Rosilene Paim ,  Ricardo Gunski ,  Sergeant João Felisberto Menezes Cavalheiro  and  Major Eugenio Correa de Souza Junior  for assistance with volunteer recruitment, sample processing and data entry. The following institutions kindly provided facilities for the assessment of volunteers:  Escuela Nacional de Antropología e Historia  and  Universidad Nacional Autónoma de México (México) ;  Pontificia Universidad Católica del Perú ,  Universidad de Lima  and.
Case or ad hoc studies do not consider individual variability and cannot analyze health issues as a whole. Data then need to be recorded for quite a long time and on a daily basis, helping to address this lack of knowledge. This has to be done in a natural way, in a professional environment with caregivers and medical staff  [5]. As until now, follow-up studies on senior citizens realized by using costly to set up and follow cohorts  [6] [7] [8]. Data are occasionally stored, even if the follow-up is long and based on auto-questionnaires or planned interviews with health professionals. This approach does not allow describing in detail the daily life of this population and storing health evolutions in the long run. On the contrary, nursing homes (NH) offer this possibility of tracking and recording them daily as health professionals feed these information for their proper use and, this time, without any memory bias  [9].
These new data, as well as their uses suggest innovative approaches to improve health knowledge. Korian (Paris, France) as the first private NH European group has these kinds of data. This enterprise holds 290 NH and approximatively 4% (290/7394  [10] ) of the French NH network, distributed all over the country, mostly in urban areas (see Multimedia  Appendix 1). A professional data warehouse (DWH) set up in 2010 hosts half the company French residents' population data. Their health follow-ups are recorded daily from 126 NH. For every new resident admitted in one of the NH, a personal electronic resident medical file (PERMF) is set up. Data is collected at various times: at admission (admission date, medical history, marital status, birthdate, tastes and habits), on a daily basis (new pathologies, chronic disease evolution, date of death, drugs prescriptions), or just after specific medical or health care professional visits.
Items include diagnosis, outcomes, as well as socio-demographic information. Elsewhere and a little earlier, at the beginning of the 2000 years, syndromic surveillance (SS)  [11] [12] [13] [14] [15] [16] [17] [18] [19]  showed that professional data could also be used for health and alert surveillance  [20] [21] [22] [23] [24] [25] [26]. Here professional data use for SS was only done using point-data analysis (going to the emergency, 911, web queries)  [19, [25] [26]  and not during a long term follow-up of the same people, and even more, not dedicated to senior citizens. As we have just seen, data gathered by different NH professionals offer the opportunity of following the residents' situations on the flow and on a daily basis, and through this process, of building syndromic surveillance data.
Data Collection All data are transmitted from 126 NH in real time to a national server using the group intranet. Records collected from the PERMF server are anonymized (see Multimedia appendix 2) when sent to the BBV server, keeping track of every resident even when moving from one NH to another. After this first step, health and socio-demographic data are extracted, transformed and loaded (ETL) to build the BBV data (see Multimedia appendix 3 for details). Following this second step, all residents have 2 types of data: 1-gender, age and GIR (Iso Resource Group), a French autonomy level rating indexed to government benefits  [27] [28] [29] [30] [31] [32]  at the NH entry; 2-daily care information fed on the flow by the caregivers and the medical staff, whenever deemed useful that is, their syndromic information and finally hospitalizations and/or death.
At the same time, every Sunday, all residents' daily care information is aggregated to count the weekly number of syndromes per NH. By extracting all residents of the PERMRF data base from its inception, from November 1 st , 2010 till mid-February 2017 and adding every new resident entering one of the NH network every week, a one-week moving cohort of residents followed during their entire NH life course was built opening the way for our SSS. Even if most residents of this cohort were followed during their entire NH life course, syndromic data could be left truncated, for people entered before the information system (IS) inception or right truncated, for people entered lately. At IS core, the data transmissions' table containing key information about the residents' care fed on a daily basis.
Syndromic Data Analysis Data Flow Build Up and Stabilization As explained above, we computed weekly counts of ILI and AGE cases, as well as hospitalizations and deaths, as with Sentinelles, avoiding week and weekend days' heterogeneity  [78]. Then, with the ggplot function of the ggplot2 R® package  [79]  used with local regression curves fitted to the NH data (figure  2 )  [80] , we were able to track yearly tendencies as well as inconsistent data not reflecting the seasonal wintry spikes. Assessing.
Building the ARI-ILI and AGE TS The ARI-ILI and AGE TS were built by aggregating all NH weekly syndromes counts. The choice of a statistical method to analyze these then rested on definitions of statistical alerts, adapting the BBV SSS data to fit French public health infrastructure and available SS data sources  [81] , here data of the ARI-ILI and AGE Sentinelles network  [22]. Whereas the Sentinelles network used the Serfling method  [71] [72]  relying on disease incidence levels of preceding years, we used the CDC steady favorite, the CUSUM methods not drawing on data from preceding years but just from preceding weeks and one recent method, the Bayes method allowing fine tuning  [73]. For further details, see again Multimedia appendix 4.
Stability The idea here was to check the syndromic data transmission flow stability in quantity (the syndromes counts) and quality (several different recurring syndromes) during the complete period and for all 126 NH, computing the weekly syndromes frequencies for every NH. The syndromic data flow stability was traced by designing 3 chronic diseases and one often chronic ailment indexes  [83]  built as follows: whenever a resident had diabetes or a cardio-vascular problem or depression or fell, the resident's transmission date and syndromic event type were set apart. Then a similar event during a 200 days period after this resident's syndromic event was searched for, defining 4 syndromic ratios for the 6 years from year 2011 up to February 27, 2017. For further details see Multimedia appendix 5.
Quality -Precision To compute the percentage of miss-coded ARI-ILI and AGE syndromes, all ARI-ILI and AGE syndromic data were extracted during 3 weeks, one in mid-August 2016, the thirty-third week (third column) when there was neither flu, nor AGE epidemic, and two in January 2017, the third and first weeks, at the ILI and AGE epidemics weeks' peaks, according to the Sentinelles network (second column). Then, each ILI and AGE syndromic data transmission was examined, rating it as correct, adding to TP, or incorrect, adding to FP (see table  2 ).
Stability As detailed in Syndromic Data Analysis subsection-Stability sub-subsection, the data transmission stability was evaluated by studying the weekly syndromes frequencies for every NH from November 1 st 2010 as well as the ratio of weeks with syndromic data transmissions: -The weekly 26 syndromes frequencies averaged over the number of NH (126) ranged from 21. 45 to 180. 57 (mean=88. 5 standard deviation=22. 8). -The ratio of weeks of data transmissions per NH was built by computing the number of data transmissions weeks versus the data transmissions weeks span and ranged from 89% to 100% (mean= 100%, standard deviation=1%). Only one NH had a ratio of less than 95%. Finally, the syndromic data flow over time studied with 3 chronic illnesses and falls syndromes distributions showed great stability (see Multimedia appendix 5 for further details).
Principal Findings We built and assessed a national ecological NH PH SS dedicated to senior citizens. By using a national network of 126 NH and extracting all socio-demographic as well as daily medical data from EHR, a cohort of 41 061 residents was built. Through textual analysis of clinical narratives (CN), we implemented ARI_ILI and AGE syndromes. We also engineered related TS by computing weekly headcounts. Alarms with EARS_C3 and Bayes algorithms on these, over a 6 year-period, allowed us to forecast the 2016-17 influenza outbreak by more than 2 weeks as can be seen in figure  4 : our statistical alarms were triggered in December whereas the influenza epidemic according to SPF started only in January. With just four tables, this IS of a new kind showed that it is possible to follow almost every resident every day, where he or she is, during his or her entire NH life, hopefully selecting most of his or her ARI-ILI and AGE health events, from NH entry until death or exit.