dataesr/scientific-paragraphs-categorization huggingface dataset:
Data availability. All Landsat data are archived by the U. S. Geological Survey. The data can be acquired at no cost via EarthExplorer (https://earthexplorer. usgs. gov/) and several other on-line tools hosted by the USGS. High resolution commercial satellite imagery (e. g. , Worldview, Quickbird) is subject to a licensing agreement with Digital Globe, Inc. and inquiries should be directed to the Polar Geospatial Center (www. pgc. umn. edu/). UAV image mosaics, ArcGIS shapefile layers for penguin nests, and additional photographic data collected during this expedition may be obtained from the authors on request.
Methods This retrospective non-interventional study was approved by the national regulatory authorities (CCTIRS ref. 13. 425 / CNIL n. 2009-674) and was partly based on data collected in the national registry of β-TM patients. 15 Between December 1985 and December 2012, 134 patients had received an allogeneic HSCT for β-TM in 21 French transplantation centers. Fifteen patients died within two years post transplant. Twelve patients resumed regular transfusions after graft failure and 107 of 134 patients were alive at least two years after successful HSCT. Six were not analyzed in the long-term study (e. g. because they had returned to their home country or were lost to follow up) and 2 died of chronic GvHD early in the third year post transplant. Finally, 99 patients were studied for transplant-related long-term effects.
Definition of methods and end points Late effects data documented by physicians were collected through visits to reference or transplant centers. Collected data included medical examination results, long-term treatment, and laboratory tests (serum ferritin, creatinine and hormone levels). Measurements of height and weight were converted to standard deviation scores (SDS) using French references. 16 Delay of puberty, hypogonadism, being overweight, hypothyroidism, heart failure, and diabetes were defined using standard criteria (see Online Supplementary Methods).
Statistical analysis Continuous variables were reported as mean±Standard Deviation (SD) or as median and interquartile range (IQR) for nonnormal distribution. Wilcoxon signed rank test was used to compare sample median. As repeated measurements were made on the same statistical units (several measurements for each patient), univariate and multivariate linear mixed-effects models were used. 17 Those variables significantly associated with outcome and those that were marginally significant (P<0. 10) in univariate analysis were included into multivariate analysis. For all analysis, a twotailed test was used; P<0. 05 was considered significant. All statistical analysis was performed using IBM SPSS Statistics v. 20 (IBM SPSS Inc. , Chicago, IL, USA).
Computational solution The previous sections tells us that equation (  2 ) is a general expression allowing the non-Fickian behaviour to be accounted for in the macroscopic formulation. The kernel function is therefore the signature of the product behaviour and its history can be expressed as the form of a convolution product that account for the time evolution of the conditions undergone by the product. This formulation was embedded in the coupled heat and mass transfer code TransPore, a custom computational model currently used in our team as comprehensive physical engine to perform inverse analysis  [8, 12]. [11].
Consumption data 2. 1. 2. 1. Food consumption data The EFSA Comprehensive European Food Consumption Database (Comprehensive Database) provides a compilation of existing national information on food consumption at individual level. It was first built in 2010  (EFSA, 2011a; Huybrechts et al. , 2011; Merten et al. , 2011). Details on how the Comprehensive Database is used are published in the Guidance of EFSA  (EFSA, 2011a). The latest version of the Comprehensive Database updated in 2015 contains results from a total of 51 different dietary surveys carried out in 23 different Member States covering 94,532 individuals. Within the dietary studies, subjects are classified in different age classes as follows: Infants: < 12 months old Toddlers: ≥ 12 months to < 36 months old Other children: ≥ 36 months to < 10 years old Adolescents: ≥ 10 years to < 18 years old Adults: ≥ 18 years to < 65 years old Elderly: ≥ 65 years to < 75 years old Very elderly: ≥ 75 years old Two additional surveys provided information on specific population groups: 'Pregnant women' (≥ 15 years to ≤ 45 years old; Latvia) and 'Lactating women' (≥ 28 years to ≤ 39 years old; Greece).
For chronic exposure assessment, food consumption data were available from 44 different dietary surveys carried out in 19 different European countries. When for one particular country and age class two different dietary surveys were available, only the most recent one was used. This resulted in a total of 35 dietary surveys selected to estimate chronic dietary exposure. In Appendix A, Table  A. 1, these dietary surveys and the number of subjects available for the chronic exposure assessment are described. Overall, the food consumption data gathered by EFSA in the Comprehensive Database are the most complete and detailed data currently available in the EU. Consumption data were collected using single or repeated 24-or 48-h dietary recalls or dietary records covering from 3 to 7 days per subject.
Methodologies 2. 2. 1. Dietary exposure assessment The CONTAM Panel considered it appropriate to estimate only chronic exposure to PFOS and PFOA (see  Section 3. 4). As suggested by the EFSA Working Group on Food Consumption and Exposure (EFSA, 2011a), dietary surveys with only 1 day per subject were not considered as they are not adequate to assess repeated exposure. Similarly, subjects who participated only 1 day in the dietary studies, when the protocol prescribed more reporting days per individual, were also excluded for the chronic exposure assessment. Thus, for chronic exposure assessment, food consumption data were used from 35 different and most recent dietary surveys carried out in 19 different European countries present in the latest version of the Comprehensive Database (Appendix A, Table  A.
1). Not all countries provided consumption information for all age groups, and in some cases the same country provided more than one consumption survey. When for one particular country and age class two different dietary surveys were available, only the most recent one was used. For calculating chronic dietary exposure to PFOS and PFOA, food consumption and body weight data at the individual level were accessed in the Comprehensive Database. Occurrence data and consumption data were linked at the lowest (most detailed) FoodEx level possible. In addition, the different food commodities were grouped within each food category to better explain their contribution to the total dietary exposure to PFOS and PFOA (see  Section 3. 2. 1). The mean and the high (95th percentile) chronic dietary exposures were calculated by combining PFOS and PFOA mean occurrence values for food samples collected in different countries (pooled European occurrence data) with the average daily consumption for each food at individual level in each dietary survey and age class.
• Area 3: Data on observations in humans, including epidemiology, case reports and biomarkers of exposure and effects. In addition to the literature search outsourced by EFSA, further literature searches were performed in June 2016 and December 2016, for the above 3 areas, in order to cover peer-reviewed literature published between 2013 and November 2016. Further search strategies were designed to identify literature published after 2007, which covered additional areas, including, chemistry, analysis, synthesis, production, use, environmental fate, food occurrence and human exposure. An overview of the search terms is given in Appendix D  (Table D. 1). Web of Science  14  and PubMed 15  were identified as databases appropriate for retrieving literature for the present evaluation. The references resulting from the literature search were imported and saved using a software package (EndNote 16  ), which allows effective management of references and citations.
9 excel fileunder 'Supporting information' Section on the web page). Overall, the main contributors to the LB mean chronic dietary exposure to PFOS were the food categories 'Fish and other seafood' (contributing up to 86% in adults), followed by 'Meat and meat products' (contributing up to 52% in the elderly) and 'Eggs and egg products' (contributing up to 42% in infants). Particularly, 'Fish meat' had the highest contribution to the overall PFOS LB mean exposure among the food subgroups within 'Fish and other seafood', in all age groups (up to 79% in the elderly). For infants, toddlers and other children, also 'Fish offal' made an important contribution (up to 40%); however, this was only true for few surveys. On the other hand, 'Crustaceans' and 'Water molluscs' contributed less. Despite high PFOS concentrations measured in liver of game mammals, the exposure to PFOS from this food is negligible as the consumption of such products was reported by only a limited number of subjects (only three subjects consuming liver of game mammals reported in the Comprehensive database).
This study estimated that the UB dietary intake was 10 ng/kg bw per day for average adult consumers. A study by  Noorlander et al. (2011)  estimated dietary exposure for the Dutch population on the basis of analysis of pooled samples from a market basket survey and combining it with a food consumption survey for 6,250 people. The median long-term intake for PFOS was estimated at 0. 3 ng/kg bw per day and for PFOA 0. 2 ng/kg bw per day, with corresponding 99th percentile intakes of 0. 6 and 0. 5 ng/kg bw per day, respectively. In a Norwegian study comprising 175 men and women with a wide range of sea food consumption, individual dietary intakes were estimated based on data from food frequency questionnaires and a database of PFOS and PFOA concentrations in food purchased in Norway. Median intakes of 1.
Exposure to PFOA came primarily from fruit and vegetables. Brantsaeter et al. (2013)  estimated individual dietary intakes of PFOS and PFOA for 487 pregnant Norwegian women, and median intakes of 44. 6 and 34. 2 ng/day were reported, respectively. This corresponds to median estimated intakes of 0. 64 and 0. 49 ng/kg bw per day for PFOS and PFOA, respectively when assuming a body weight of 70 kg. The intake estimates were based on data from food frequency questionnaires and a database of PFOS and PFOA concentrations in food purchased in Norway  (Brantsaeter et al. , 2013). Klenow et al. (2013)  estimated dietary exposure to selected PFASs for four selected European states including Belgium, the Czech Republic, Italy and Norway. These countries were selected to represent Western, Southern, Eastern and Northern Europe, and were part of the EU project PERFOOD.
Two human renal brush-border membrane carriers, OAT4, which is only expressed in human kidney, and URAT1 are involved in the initial step in the reabsorption of PFOA  (Nakagawa et al. , 2009; Yang et al. , 2010; Han et al. , 2012). The polymorphism of OATs in human populations and its consequence in the toxicokinetics of drugs and contaminants they transport have been reported in a limited number of articles. Naturally occurring genetic variants of OAT4 were identified in public databases and by resequencing DNA samples from individuals comprising four distinct ethnic groups. Nine total non-synonymous variants demonstrating altered transport of endogenous substrates were identified  (Shima et al. , 2010) , but no publications focused on PFOA were identified. The studies investigating the fate of radiolabelled PFOA in rodents  (Vanden Heuvel et al.
PFOA In their previous opinion, the CONTAM Panel derived a TDI for PFOA of 1. 5 lg/kg bw from liver effects occurring in a subchronic study with male rats EFSA (2008). Data on developmental and reproductive toxicity studies using exposure to low doses of PFOA were limited. In fact, the most sensitive endpoint identified for developmental and reproductive toxicity originated from a study by  Abbott et al. (2007). In this study, a reduction in neonatal survival was observed at 0. 6 mg/kg bw per day which resulted in a NOAEL of 0. 3 mg/kg bw per day. In addition, from a two-generation reproduction study on PFOA, in which Sprague-Dawley rats were given 1, 3, 10 or 30 mg/kg bw per day PFOA, by oral gavage, NOAELs for reproductive function (30 mg/kg bw per day), sexual maturation (10 mg/kg bw per day) and for body weight as well as increased liver weight (< 1 mg/kg bw per day) in both parental and F1 male animals could be derived  (Butenhoff et al.
, 2011; Tucker et al. , 2015). Since none of the studies provides a direct link to potential adverse outcomes, the CONTAM Panel could not consider these data as a reference point of departure for reasons specified in the sections below. In a study with CD-1 mice exposed to PFOA at 0, 0. 01, 0. 1, 0. 3, 1 or 5 mg/kg bw per day, by gavage, from GD 1 to 17, no difference in live pup numbers was observed, while postnatal mortality was not assessed  (Hines et al. , 2009). However, as briefly mentioned above a transient body weight gain of the pups at the mid-age observation group  (21-33 weeks)  was observed for 0. 01-0. 3 mg/kg, which was accompanied by a transient increase in serum levels of leptin and insulin in the 0. 01 and 0. 1 mg/kg groups. At 18 months of age, abdominal fat weight and relative amounts of white fat were decreased in the 1 mg/kg bw per day and 5 mg/kg bw per day exposure groups, the 3 mg/kg bw per day group was not assessed.
Van Esterik et al. (  2016 ) investigated whether early exposure to low doses of PFOA could program C57BL/6JxFVB hybrid mice for metabolic impairment later in life. No general developmental and reproductive toxicity effects became apparent. Whenever possible, authors subjected dose-response data obtained to BMD modelling (BMD) approach  (Slob, 2002)  with the PROAST software versions 38. 0 and 38. 1 (www. rivm. nl/proast). In males, a dose-dependent decrease in body weight was observed from PND 4 until 21 weeks, when the diet was changed from normal diet to high fat diet. In females, this effect persisted even after feeding of a high fat diet for 2 weeks, with a BMDL 5 of 849 lg/kg bw per day. Male organ metrics were only affected for absolute and relative liver weight, which increased, and tibial length, which decreased.
Despite the fact that responses in the mammary gland occurred at low doses, the CONTAM Panel decided not to use the data on mammary gland development for the risk assessment. The observations for the developmental score at 0. 01 mg/kg bw per day in the mammary gland are generally speaking, indicative for a delayed pubertal transition of the mammary gland. Delayed developmental transition, as such, cannot be considered as an adverse health outcome. Furthermore, the developmental score summarises results of several individual parameters and none of the individual ones were as sensitive as the sum parameter (0. 1 mg/kg bw per day and above). In addition, pubertal development was not generally affected, because no influence of PFOA exposure on vaginal opening could be detected. At present, it is not clear whether this biological effect occurring at a low dose has to be regarded as adverse.
In addition, the ratios of DOPAC and HVA to dopamine were decreased, indicating a reduced dopamine metabolism in the anterior hypothalamic area. These data suggest that the inhibition of prolactin secretion by PFOS in adult male rats is mediated by the periventricular hypophysial dopaminergic neurons, GABA-ergic cells from the supraoptic and paraventricular nuclei, as well as by oestradiol. Exposure to 6 mg PFOS/kg bw per day decreased the expression of DRD1 mRNA in the amygdala and upregulated the expression DRD2 in frontal cortex and hippocampus  (Salgado et al. , 2016).
Image analyses and graph construction We first removed the background from each image with ImageJ software (subtract background function with a rolling ball radius of 18 pixels). All images were then analyzed with Imaris software (versions 7. 7 and 8. 3. 1, BitPlane, Oxford Instruments) software for 3D/4D visualization and analysis. Cells were individually tracked over the entire acquisition period. At each time point, the two nuclear spots were detected on the 3D image with the spot module of Imaris, and manually adjusted if necessary, and their fluorescence intensity was measured. Each spot was individually tracked over time with the ImarisTrack option, and manually corrected if necessary (supplementary Fig. 4 ). Data were then analyzed with a dedicated algorithm that determines RT values, calculates RD value, corrects photobleaching and constructs intensity graph.
Finally, we computed the parameters of a sigmoid function that fits the data. For a more convenient visualization of graph representations for the seven cell lines, times were adjusted by adding 70 minutes and 10 minutes to the coordinates of the Mid-late 2 cell line and the Late 1 cell line, respectively, because cells of these two cell lines have been cultured 130 minutes (Mid-late 2 cell line) and 70 minutes (Late 1 cell line) before the start of acquisition, while the other cell lines have been cultured 60 min before the start of acquisition. Box plots and violin plots were constructed with Python tools. Figure Legends.
Acknowledgments was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which this version posted December 3, 2018. ; https://doi. org/10. 1101/485987 doi: bioRxiv preprint The authors thank the members of the laboratory of M-N. P. for useful insights and discussions. We acknowledge the ImagoSeine core facility of the Institut Jacques Monod, member of IBiSA and France-BioImaging (ANR-10-INBS-04) infrastructures, in particular Xavier Baudin for help with photonic microscopy and Vincent Contremoulins for advice on image analysis with Imaris software. We thank Dr. David.
Each SCX fraction was on-line transferred to a Reverse Phase (RP) column (PepMap100 C18, 3 μm, 100 Å, 75 μm i. d. , 15 cm) and peptides were eluted with a linear gradient of buffer B (95% acetonitrile, 4. 9% H2O, 0. 1% formic acid) ranging from 0 to 50% within 60 min (flow: 300 nl/min). Eluted peptides were analysed by nano ESI ion trap mass spectrometer (HCT ultra, Bruker) set to isolate and fragment the top 6 most abundant peptides per cycle with a 30 sec dynamic exclusion time. Electrospray voltage was set to 2000 V and analysis mass ranges were 250-1500 m/z for MS and 100-3000 m/z for MS/MS. Data analysis was performed as described for GeLC-MS/MS. Considering the remaining high amounts of human globins in the samples, leading to wide chromatographic peaks, the dynamic exclusion time was extended to 150 sec.
The corresponding protein list obtained with the previous parameters but with the extended dynamic exclusion time of 150 sec was named Without Exclusion (WE). Moreover, we improved the dynamic exclusion process by adding precursor ion exclusion (PIE) mass lists of the most abundant proteins including human globins and albumin in order to favour the identification of low abundance proteins  [20]   [21]. As the MS controlling software (Esquire Control v6. 1) allowed the exclusion of 39 masses at once, we first defined exclusion mass lists for each salt fraction (  5.
Gene ontology analysis A gene ontology analysis of nuclear extracts was performed using PANTHER (version 13. 1 Released 2018-02-03)  [22]. To this end, PlasmoDB gene names were converted into UniProt accession numbers using Retrieve/ID mapping tool in UniProt. Both CE and NE were analysed using the functional classification pie chart" for Protein Classes (molecular function) and Organelle (subcellular localisation) GO terms using P. falciparum organisms. PANTHER overrepresentation test (released 2017 1205) was also used to highlight the functional biological processes statistically overrepresented in NE compared to the complete P. falciparum gene data base (Fischer test, p value < 0. 01, FDR < 5%).
Analysis of all identified proteins obtained with the two approaches A total of 368 proteins were identified by 2D-LC-MS/MS performed on several nuclear extract replicates that were compared to the proteins identified (294) with the GeLC-MS/MS. Different sets of proteins were analysed thoroughly in particular proteins governing the translational machinery and compared to the data obtained from PlasmoDB and Plasmobase. Both 40S and 60S structural ribosomal proteins are known to be present in the nucleus  [14]  where the biogenesis of the 80S ribosomes takes place. We found 73 ribosomal proteins (29 and 44 proteins composing the 40S and 60S ribosomal sub-units, respectively). This number is in good agreement with the proteins found in higher eukaryotes  [26]. The number of ribosomal proteins defined in silico in Plasmobase (78) and PlasmoDB (81) is greater than the Regarding proteins involved in translation (initiation, elongation and termination), we found protein expression evidence (S7 Fig) for 31 including one release factor among the 5 expected in silico.
However, only few specific transcription proteins (STP) were detected, that is in good agreement with our article dealing with the in silico survey of transcription associated proteins (TAP)  [23]  known to be at limiting concentration in the nucleus. Finally, proteins with unknown function (UProt) were evaluated for new annotation (S8 Fig) with the help of the just released Plasmobase website  [16]. Plasmobase provides significant information concerning domain architecture and co-occurrence helping annotation and proposition for protein function within 11 Plasmodium species. Some proteins can be found in all Plasmodium or be present in one species such as PF3D7_1468100 detected in P. falciparum only. The domain architectures can also be compared to proteins throughout evolution listed in UniProt Database.
It is possible within the list of proteins from biologically well documented organisms (such as mammals, Danio rerio, several plants, fungi, mold or yeast) and sharing the same domain architectures to consider a function and propose an annotation for the corresponding P. falciparum protein (S8 Fig). This was done for UProt for which some putative protein annotations were proposed. Table  1  propose an example of annotation of nine UProt. Within the proteins listed, two proteins identified with a high score in Plasmobase were recently updated confirming PlasmoDB annotation and highlighting the efficacy of Plasmobase, whereas seven were not annotated in PlasmoDB. Plasmobase identified functional domains allowing putative annotations. Indeed, these functional domain architectures were explored in the Uni-Prot Database a curated collection of manually evaluated and functionally annotated proteins eliciting experimental evidence at the level of proteins in well documented eukaryote species and associated to publications.
Using the Plasmobase website based on domain architectures and domain co-occurrence found in Plasmodium we could find in other eukaryotic species proteins with similar architectures listed in UniProt database which biological functions were investigated to propose an annotation (Table  1  and S8 Fig). We considered, within the unknown proteins found in NE the one sharing similar domain architectures described in UniProt eliciting mRNA and protein evidence with an assigned validated and published biological function. Thus, it was possible to propose a putative annotation for several Plasmodium including members of translation factor and DNA and RNA proteins associated to gene regulation. The probable low abundance of specific transcription factors that have to be switched on and off rapidly to govern gene expression all along the Plasmodium complex live cycle from marked to weak parasite multiplication might be responsible for the challenging identification of these proteins.