dataesr/scientific-paragraphs-categorization huggingface dataset:
2002)  and a customized Python script (Supplemental File S4). For ortholog comparisons, typical enhancer and SE target genes were annotated based on gene proximity using Nebula. All gene names were converted to Ensembl ids and compared based on homology annotations from Ensembl (Genes 82)  (Cunningham et al. 2015). Analysis of the ATAC-seq library was performed as previously described  (Buenrostro et al. 2013). Overrepresented motifs in ATACseq peaks within SEs were identified using the RSAT peak-motifs tool  (Thomas-Chollier et al. 2012a,b). For more details, see Supplemental Material.
Data access Zebrafish H3K27ac ChIP-seq data generated in this study have been submitted to the NCBI Gene Expression Omnibus (GEO; http://www. ncbi. nlm. nih. gov/geo/)  (Edgar et al. 2002)  under accession number GSE75734. Council (FLAME-337440), ATIP-Avenir and La Fondation Bettencourt Schueller and Fondation pour la Recherche Medicale (FRM DBI201312285578). Y. A. P. -R. was partially funded by a scholarship from Secretaría de Ciencia, Tecnología e Innovación -Seciti, México.
Acknowledgments We thank  Igor Ulitsky ,  Matthew Guenther , and  Violaine Saint-André  for helpful comments on this manuscript. We also thank all members of the  Shkumatava lab  for help with zebrafish dissections and for useful discussions. High-throughput sequencing was performed by the  ICGex NGS platform of Institut Curie  supported by the grants  ANR-10-EQPX-03  ( Equipex ) and  ANR-10-INBS-09-08  ( France Génomique Consortium)  from the  ANR  (" Investissements d'Avenir" program ) and by the  Canceropole Île-de-France. This work was supported by grants from the European Research Figure 6. Functional analysis of vertebrate SEs. (A) Genomic context and conservation of the zebrafish (left) and mouse (right) irf2bpl and Irf2bpl loci. Horizontal bars represent SEs (red). Raw H3K27ac ChIP-seq, ATAC-seq, and  Nanog ChIP -seq profiles are shown in tag counts (y-axis).
Work scope Given the uncertaintya roundq uick estimating, the authors decided to addresst he research hypothesis that different methods are (or not) consistentw ith each other,a tl east to as atisfactory degree. For this purpose, the current work assesses five functional unit methods that are approved andw ell known amonge stimators, as well as Lange's thermodynamic cost correlations. We escalated all selected methods to ac ommon currency,l ocation, and basis year. T hree biorefinery processes, employingc hemical, biochemical, and thermo-biochemical technologies, are used as validation models. We first compared the resultsw ith reference literature estimations and then with reportedc apital costs from commercial biorefineries. For the latter,c ost information was retrieved from al arge databasew e have been compiling with cost and process information for commercial biorefineries that are already in operation worldwide or are announced to come online in the near future.
Selectedcost basis Variations of the correlations'c onstantsh ave been proposed in the literature,  [8, 26]  but since recorrelationd etailsa re unknown, we used the original equationsa sp roposed by their authors and escalated them accordingt ot heir instructions. First, we set 2011a st he common cost basis year and calculated the ISBL in millions of dollarsf or ag reenfield plant built overnight in the US (Gulf Coast). We compared the six proposed methods with the reported literature estimations. T hen, we calculated the DCC in millions of US dollars for all processes to compare the resultso btained by the methods with announced commercial plant costs retrieved from our database. We report details on the escalation methodology and calculations for updating the aforementioned methods in the SupportingI nformation.
Probabilistic comparison with commercial capital costs However, as the reference costs are only estimations,t heir accuracyh as to be verified. We have been compiling ad atabase with historical costs and process parameters from existing or announced biorefineries worldwide. The information is collected mainly from press releases and announcements published by the companies. T odate, the database has gatheredinformation for 320 commercialb iorefineries employing all kinds of technologiest op roduce biofuelsa nd/orb iochemicals. We retrievedc apital cost data for dry corn to ethanol, soybean oil to biodiesel, and thermochemical ethanol production plants; these are illustrated as scatterplots in Figures  4 5 6 (marked as circles). It is assumed that the announcedc ommercial capital cost refers to the total DCC of the plant, that is, ISBL + OSBL, if no furtheri nformation is provided.
Petley's result was also quite accurate:i tc ould not be attributedt ot he inherent assumptionso ft he correlation, but to the large process database from which it was derived. A ll Bridgwater's correlations deviated significantly from the reported DCC for attributing high scores to the process conversion. For the bioethanol process, this is rather small, once again due to high amounts of solvent, and according to Bridgwater,t his makest he process more complex and more expensive. Lange's [Eq. (  15 )] correlation for the ISBL provided av ery good appraisal because the costs of distillation and purification were quite high, and thus, the amount of energy transfer was strongly correlated to the cost. As expected, Lange's [Eq. (  14 )] correlation for the DCC was not as accurate because no highly endo-/exothermicr eactions were involvedi nt he process and the plant scale was rather small, involvingb oth continuous (distillation columns) and batch units (fermenters).
The DCC and capacity of the corn-to-ethanol plants are (not strongly) correlated, but do not follow strong economies of scale. For the biodiesel process, the majority of methods fell within the 90 %C. I. :t he reported deviations can be explained by the impact of temperature on the total capital cost. The cost waso verestimated because of the weight given to the maximum process temperature. The methodsw ered eveloped during the 1970s and, since then, there has been technical progress to reduce the cost of the pieces of equipment versus their operating temperature. It is evident from the results in Figure  5t  hat biodiesel plants fall within the category of conventional chemical plants and follow strong economies of scale. The smallest deviations were reported for thermochemical ethanol. The main reason is that this process is quite similar to the classic coal gasification process, whichi sp robably part of the costing methods' database.
Acknowledgements The  European Commission  is gratefully acknowledged forfunding the  Renewable Systems Engineering project  ( RENESENG-FP7 Marie Curie project ). We would also like to thank  Intelligen,I nc. (DemetriP etrides)  for upscaling the SuperPro flowsheets and  Jean-Paul Lange  for his valuable comments and recommendations. Keywords: biomass • early-stage estimates • investments • process development • sustainable chemistry.
Material and Methods All patients are randomized 1:1 in to 2 groups (SCS+PNS vs SCS). Group 1 (SCS+PNS) receives "hybrid stimulation" with PNS implantation one month after the inclusion visit. In the second group, patients continue to be treated with SCS alone for 4 months post-inclusion before having access to PNS. The main objective of this study is to demonstrate the added value of subcutaneous PNS by comparing the ability of hybrid stimulation (SCS+PNS) versus SCS alone to improve analgesic efficacy, functional outcome on quality of life and coverage of the residual low back pain component at three months. This variation in the pain surface area covered is evaluated by mapping, using the Neuro-Mapping Tools software (N3MT).
Acknowledgements. This work was supported by  Inserm ,  The Ministère de l'Education Nationale de la Recherche et de la Technologie , the  University of Rennes 1 , the  Région Bretagne , the  INCa (Institut national du cancer) , and the 'Ligue contre le cancer, comités du grand Ouest'. Research in the Vandenabeele group is supported by  Belgian grants (Interuniversity Attraction Poles ,  IAP 7/32 ), Flemish grants (Research Foundation Flanders:  FWO G. 0875. 11 ,  FWO G. 0973. 11 ,  FWO G. 0A45. 12N ,  FWO G. 0172. 12 ,  FWO G. 0787. 13N ,  FWO G. 0607. 13N ,  FWO KAN 31528711 ,  FWO KAN 1504813N ,  FWO G0E04. 16N ),Methusalem grant ( BOF16/MET_V/007 ), Ghent University grants (MRP, GROUP-ID consortium,  BOFGOA2014000702 ), grant from the  Foundation against Cancer  ( F94 ), and grants from  VIB.
Acknowledgements This work was funded by the  Agence Nationale de la Recherche  under ComplexDynamics (MB) and NMRSignal (MRJ) and by  Finovi. SM acknowledges the  EMBO longterm fellowship  ( ALTF 468-2014 ) and  EC  ( EMBOCO-FUND2012 ,  GA-2012-600394 ) through  Marie Curie Action. This work used platforms of the  Grenoble Instruct Centre (ISBG ; U MS 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). TheE Mf acility is supported by the  Rhône-Alpes Region , the  Fondation pour la Recherche Medicale (FRM)  and  FEDER  funds.
Dear Editors, We would like to bring Orphanet Journal of Rare Diseases readers'attention to a specific high-risk pregnancy management. We report the case of a 30year-old, gravida 1, para 0, with achondroplasia who became spontaneously pregnant. Clinical examination highlighted a pathological anatomy of the pelvis. Pelvic computed tomography showed marked shortening of the obstetric conjugate diameter (5. 4 cm) (Fig. 1 ). In view of the patient's disease, early sonographic assessment of the fetus was performed. An unusually long cervical length was observed: 61. 7 mm at 16 weeks of gestation (Fig. 2 ). This measurement is way above the 95th centile (49. 3 mm)  [1]. There are few data on the obstetric management of women with skeletal disorders such as achondroplasia or osteogenesis imperfect  [2].
ACKNOWLEDGEMENTS We thank the anonymous referee for useful comments. We also thank  Gerhard Wurm  and  Markus Kuepper  for enlightening discussions about photophoresis experiments. This research was supported by the  Programme National de Physique Stellaire  and the  Programme National de Planétologie of CNRS/INSU, France. The authors are grateful to the  LABEX Lyon Institute of Origins  ( ANR-10-LABX-0066 ) of the  Université de Lyon  for its financial support within the program " Investissements d'Avenir"  ( ANR-11-IDEX-0007 ) of the French government operated by the  National Research Agency (ANR). All the computations were performed at the  Common Computing Facility (CCF)  of the LABEX LIO. Figs. 4 and 5 were made with SPLASH (Price 2007).
Sampling and Data Collection Procedure Selale was selected for this study because of its tradition of and potential for dairy production, its milk market coverage and its dairy supply to the Addis Ababa market. The Selale dairy cooperative union (SDCU) is the major formal milk buyer in the area. From the list of 22 dairy cooperatives that are active members of SDCU, we randomly selected four primary dairy cooperatives. The four kebeles (the smallest administrative unit) where these sample dairy cooperatives are located were taken as sample kebele for the study. By employing stratified sampling techniques, 300 farm households were selected from the four kebeles, proportionately to their population size. We administered a structured questionnaire with both closed and open-ended questions regarding the socio-economic and demographic background of the dairy farm households.
Acknowledgements We gratefully acknowledge the financial support for this study from the  Netherlands Organization for International Cooperation in Higher Education (Nuffic)  and the  International Foundation for Science (IFS). We thank individuals and organisations who generously provided the necessary information for this study. We are also grateful to the annonymous reviewers for input that helped us to revise the paper. As per the requirement of the journal we are willing to provide all the data and formulas used in the paper upon request.
Patients and Methods ethical approval was obtained for this study by the local ethics committee. patients were retrospectively identified from a radiological electronic database. patients aged 16 years or over with tibial shaft fractures, also classified as type 42 fractures by the Ao foundation,  7  treated at the study centre between July 2007 and June 2013 were included in the study. All patients from the catchment area who were treated in the study centre, but resided outside these areas, were excluded from analysis. conversely, all patients receiving their initial management outside our catchment area but who resided within it were included. This resulted in 393 fractures being available for study, of which 264 were managed with a reamed locked intramedullary nail. in addition to the immediate post-operative films, standard radiographic follow-up assessment included anteroposterior (Ap) and lateral radiographs at six weeks, three and six months.
Vegetation Activity Change Data A vegetation change indicator was developed to characterize long-term trends in activity over the study period (Figure  2 ). The indicator was obtained using a temporal decomposition method applied to a time series of MODIS 16-day maximum value composite NDVI images (MOD13Q1) with a spatial resolution of 250 m between January 2001 and December 2010. The method, described in  [25]  consists of three steps: 1) NDVI time series decomposition using BFAST based on LOESS  [26] ; 2) analysis of the BFAST trend component using linear regression; and 3) identification of significant positive or negative trend slopes using a Student's t-test. This method has already been applied to the Fort Riley and KPBS study areas  [27].
To fill these gaps, 135 additional MODIS Burned Area Product (MCD45) images were used to complement the HSR time series. Produced by the MODIS Fire Team at the University of Maryland (http://modis-fire. umd. edu/pages/BurnedArea. php), the Burned Area Product provided monthly images of burned pixels at a 500 m spatial resolution. Though the spatial resolution is coarse, preventing detection of small and fragmented burns, the MCD45 images were a practical and inexpensive source of data to ensure a continuous and reliable source of fire information within the time series. Next, monthly burned area maps were created for each year and used to calculate annual burned area maps. To ensure compatibility with the vegetation change indicator, monthly burned area maps were overlaid with a grid of the same spatial resolution.
GLM Validation Procedure Each GLM model generates a probability map for vegetation degradation. Model performance is then validated using two different reference datasets. The first is the vegetation degradation class resulting from the previously mentioned MODIS NDVI trend analysis. The second is a new HSR vegetation degradation class from a change analysis performed using two Landsat 5 TM images acquired near the beginning (08/05/2001) and end (08/30/ 2010) of the study period. This method was recommended by  [34] , has been proven well adapted for grassland ecosystems  [35]  [36], and has been previously used to validate vegetation change activity for the Fort Riley and KPBS study areas  [27]. The HSR dataset consists of a raster with the same spatial resolution as the vegetation activity change map (250 m) in which each grid cell corresponds to one of two classes (degraded or non-degraded) based on the interpretation of NDVI change derived from the Landsat 5 TM images.
While these data do exist, they are embedded within complex US Army database management systems and are difficult to extract for use in natural resource studies. Until such a time when training data are routinely available for land managers, the new simplified strata presented here may be used as a spatial guide to modify training schedules and prevent further declines in vegetation condition where degradation has been predicted and measured. Land managers suffering from similar data deficiencies in land usage, such as off-road vehicle use in public recreation areas, may also find utility in defining custom strata for their sites.
Acknowledgements This work was supported by the  French Agence Nationale de la Recherche  through the  Moduland  project ( ANR-11-BSH1-005 ). Funding to support international research collaboration was provided by  Ecole d'Ingénieurs de Purpan  and the  Geographic Information Systems Spatial Analysis Laboratory (GISSAL)  at  Kansas State University. Additional travel funding was provided by the  National Polytechnic Institute (INP) of Toulouse  to support researcher exchange.
All new compounds displayed satisfactory analytical and spectroscopic data correlating with their structure, and with the data reported in the literature for comparable molecules (see Experimental Section). Molecules 2016, 21, 634 3 of 15 Figure  1 ), where a benzochromene motif was fused to the pyrimidinone motif present in alkaloids Ia-IV. As a result, eighteen new BCPOs were synthesized and evaluated for their antioxidant activity, ChE inhibition, and their in vitro toxicity in liver HepG2. From these studies, we have identified compound 3Bb as a promising derivative potentially useful in further AD drug discovery steps.
Elemental analysis were performed on Flash EA 1112 Thermo Finnigan, (Thermo scientific, Waltham, MA, USA). The microwave assisted reactions were carried out in synthesis microwave (Anton Paar 300, Peseux, Switzerland) with a maximum power of 300 W. Data obtained for the new compounds correlate well with values for controls drugs, where CNS availability is known and also reported using the PAMPA assay  [26, 27]. Our data show high resemblance with previously reported results as well as with a general knowledge about the CNS availability for these drugs.
The net AUC corresponding to the sample was calculated as follows: Net AUC " AUC antioxidant ´AUC blank Using MS Excel software, regression equations were extrapolated by plotting the net AUC against the antioxidant concentration. The ORAC values were then obtained by dividing the slope of the latter curve between the slope of the Trolox curve obtained in the same assay. Final ORAC values were expressed as Trolox equivalents. Data are expressed as mean ˘SD.
Search strategy and selection criteria For this systematic review and meta-analysis, we developed a study protocol (appendix p 1) based on the PRISMA guidelines (appendix p 4). We searched four databases (MEDLINE, Embase, Web of Knowledge, and Africa-Wide Information) to identify all studies published before Jan 1, 2014, which reported on stage at diagnosis of primary invasive breast cancer in women in sub-Saharan Africa. The UN classification  20  was used to define sub-Saharan African countries and to group them according to region (ie, southern, eastern, western, and middle Africa). We did an initial keyword search and subsequent searches based on Medical Subject Headings (MeSH) with various combinations of search terms "breast cancer*", "breast neoplasm*", "breast carcinoma*", "breast sarcoma*", "breast tumor*", "breast tumour*", or "breast malignanc*", AND "stage", "presentation", "grade", "clinical features", or "clinical findings", AND "Africa" (appendix p 7).
Quality assessment and data extraction In the second step, all full-text articles retrieved were reviewed to confirm eligibility and, if eligible, data were extracted. EJ-A assessed all articles for eligibility and extracted the data, using an adapted version of a pre-tested data entry electronic form. 21 All articles were independently reviewed by one of the other two reviewers (Id-S-S or VM). Data were extracted from each eligible paper on the numbers of patients who presented in stages I, II, III, and IV at diagnosis, or at early (I/II) and late (III/IV) stages if only this combined information was provided; country; study design; study population and type of clinical setting (eg, primary, secondary, or tertiary clinical facility; population-based cancer registry; public, private, or mixed patients); year of diagnosis; race; average age at time of diagnosis (mean or median; if only age categories were reported the mean age was estimated from the mid-point and the reported numbers in each category); and methods and classification used to ascertain stage.
Time at diagnosis in the original papers was either the time at clinical or pathological diagnosis. If a study provided numbers for each specific American Joint Committee Cancer Tumour Node Metastases (TNM) category (eg, T2, N0, M0; appendix p 14), we used these to derive numbers in each one of the four stages. Whenever available, we extracted data on menopausal status, tumour characteristics (eg, histology, size, grade, receptor status), and time from first symptoms to diagnosis. Disagreements between extractors were discussed and a consensus reached. Most papers with missing information were from studies done several decades ago, hence no attempt was made to contact their authors because it was unlikely that the required information could still be retrieved. If there were several papers for the same study period, setting, and author, the paper with the most information on tumour stage was selected for inclusion.
Data analysis The primary outcome was percentage (p 34 ) of breast cancer diagnosed at late stages (stages III/IV), defined as p 34 =n 34 /n, where n 34 is the number of women who presented at stages III or IV and n is the number of women with known stage information. The suite of metan and metaprop commands from Stata (version 13) were used to graphically display populationspecific late-stage percentages and to estimate pooled percentages using random effect models. The metaprop command was specifically designed to model binary data, thereby allowing for proportions near boundaries (ie, in this instance near 100% late-stage cancer). Between-population heterogeneity was assessed using I 2 statistic and the p value for heterogeneity (Cochrane's Q statistic). To examine potential sources of heterogeneity, population-specific estimates were stratified by relevant clinicoepidemiological variables, and meta-regression analyses were done to identify independent correlates of percentage of late-stage disease.
Study-level determinants of late-stage disease are expressed as absolute differences (AD) in the percentage of patients with late-stage disease (p 34 ). Analyses were first done in all study populations (black and non-black African) and then in black African populations only. The latter analyses excluded non-black African populations, which were from South Africa, because of their known privileged access to health care. The potential for small study bias was assessed using funnel plots and the Egger test. 22  compare late-stage breast cancer in sub-Saharan Africa with corresponding figures for white women and black women in the USA, relevant data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database, which includes information on all cases of invasive primary breast cancer in women from nine US population-based cancer registries  23  for two time periods: 1973-2002 and 1998-2011.
Discussion To our knowledge, this is the first systematic review of stage at diagnosis of breast cancer in sub-Saharan Africa. We compiled data from 83 studies consisting of 24 213 patients with staged cancers. The findings highlight two main issues. First, our findings show the paucity of data on one of the most important clinical prognostic markers of breast cancer in this region. Specifically, no published data from middle Africa were identified, and data from southern Africa were restricted to one country (South Africa), with only two studies done after 2000 (one in black Africans and another in non-black Africans). Furthermore, no study presented data from population-based cancer registries. Second, the findings show that most patients in sub-Saharan Africa (77% across all black study populations) were diagnosed at stages III/IV.