dataesr/scientific-paragraphs-categorization huggingface dataset:
In the present work, an innovative approach aiming at identifying NIAS migrating from polyester-polyurethane coatings was proposed. In theory, NIAS migrating from lacquer can represent a multitude of compounds. To encompass such a possible diversity, a global untargeted analytical strategy was developed using liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) to characterize lacquer extracts and give access to their fingerprints. Hence, specific data processing was needed to address the huge amount of data generated. In addition, to enable high throughput NIAS identification, the detected compounds were compared with a specifically developed homemade database based on their exact monoisotopic mass. This strategy allowed proposing an identification for the most intense migrating predicted and unpredicted compounds.
Instrumental acquisition An UltiMate 3000 UHPLC coupled to an Orbitrap Q-Exactive mass spectrometer fitted with a heated ESI source (HESI, ThermoFisher Scientific, San José, CA, USA) was used for data acquisition. External calibration was performed by infusing calibration mixture for negative (MSCAL6-1EA) and positive (MSCAL5-1EA) ionization mode (Supelco, Bellefonte, PA, USA). A volume of 10 μL was injected on a reversedphase Hypersil Gold analytical column (100 mm × 2. 1 mm, 1. 9 μm) (ThermoFisher Scientific) kept at 40 °C. Mobile phases were composed of 10 mM ammonium acetate in both water (A) and acetonitrile (B). The gradient began with (A/B) 80:20 (v/v), ramped linearly to 0:100 over 16 min, to be maintained for 2 min before returning in 2 min and stabilizing at initial conditions. The flow rate was set at 0.
4 mL. min -1. In the positive mode, ionization parameters were as follows: sheath gas flow, 50 arbitrary units (AU); auxiliary gas flow, 10 AU; capillary temperature, 350 °C; heater temperature, 300 °C; spray voltage, 3. 5 kV; S-lens radio frequency, 70 AU. In the negative mode (separate injections), the same parameters were used except for the spray voltage, which was set at -2. 5 kV. HRMS data were acquired in full scan mode over the mass-tocharge ratio (m/z) range 155-1200 at a resolving power of 140,000 full width half maximum (FWHM) at m/z 200. Automatic gain control (AGC Target) was set at high dynamic range (5×10 5 ) and maximum injection time (IT) at 500 ms. Additionally, a selection of 22 precursor ions was fragmented in the positive targeted-MS 2 mode using higher energy collisional dissociation (HCD) after unit mass quadrupole filtering, with parameters as follows: resolving power, 70,000; AGC Target, 1×10 5 ; maximum IT, 100 ms; isolation window 0.
Post-acquisition data analysis Extracting useful information from large full scan HRMS acquired data sets requires automatic processing, which was performed under the open source programming R environment. First, raw data (. raw) were converted to the open format. mzXML using the open access msConvert software (ProteoWizard). Second, in order to extract chromatographic features, the converted datasets were processed by the xcms Rpackage using the centWave peak detection algorithm  [32] , as previously described  [33] , with slight modifications. In these R-packages, a feature corresponds to a chromatographic peak from a given ion. Parameters were optimized for the present study for noise filtering and deconvolution to resolve coeluting ions: method, BcentWave^; ppm, 5; prefilter, c(5,10000); snthresh, 6; peakwidth, c  (1, 15) ; mzdiff, 0.
002; noise, 0. A table report in. csv file format was then created for each data file (n = 3 blanks, n = 3 Lac1, and n = 3 Lac2), where each feature was defined by a precise mass (m/z), a retention time (-t R , min), and a signal intensity (area). Then, the nine lists of features were aligned according to the Retcor function (xcms R-package), leading to a new table report in. csv file format where each feature was defined by common and precise (m/z) and t R (min) as well as an individual signal intensity (area) for each sample  [34]. Used parameters were: bw, 1; mzwid, 0. 002; minfrac, 1; minsamp, 1. Usually, the insource ionization of one compound generates several ion species such as isotopologues, adducts, or fragments. Hence, the fourth and last step consisted of a deconvolution of the data table using the CAMERA R-package  [35] , which pairs signals potentially originating from a same compound (peak shape) in a so-called peak correlation group (PCgroup) and further suggests isotope and adduct assignments according to mass differences.
Software Xcalibur Qual Browser software (ThermoFisher Scientific) was used to generate an elemental formula (C, H, O, and N selected atoms) from a measured mass along with a degree of unsaturation (DoU) and a ppm deviation compared with the theoretical mass. ACD/MS Fragmenter software (Advanced Chemistry Development, ACD, Toronto, ON, Canada) was used to predict fragments from a hypothetic molecular structure draw. Suggested fragments were calculated based on established mass spectrometry fragmentation rules. The parameters selected were atmospheric pressure ionization technique, positive mode, and five fragmentation steps with the possibilities of all the common reactions (aromatic bonds cleavage, resonance reaction, rings formation, and hybrid shift). ChemSketch software (ACD) was used to estimate the Log(P) values of the diol carbon chains.
Homemade database of predicted oligomers A homemade database was developed and populated considering nine polyols (eight diols and one triol) and four polyacids (three diacids and one triacid) known to be potentially used as monomers in lacquer polyester formulations intended for food contact coatings, according to the literature  [28] [29] [30]  and guidelines  [6, 7]  (Table  1 ). All plausible monomer combinations up to dodecamers were enumerated, leading to more than 1 million combinations. Then, each combination was further enumerated in possible linear, partially, and fully cyclized forms (depending on the number of H 2 O losses), resulting in a higher number of oligomer structures. Finally, all combinations above 1000 Da were discarded, leading to 80,639 unique monomer and elemental formula combinations, involving up to 11 monomers.
Homemade database search Among the most intense lacquer-specific PCgroups and as compiled in Table  2 , 61% matched the homemade database (<2 ppm deviation) as predicted combinations, based on known monomer formulations. Among these PCgroups, 28 and 27 were specific to Lac1 and Lac2, respectively, whereas six were mutual. PCgroups corresponding to isomers were gathered into predicted combinations, so that 11 and 14 predicted combinations were specific to Lac1 and Lac2, respectively, whereas three were common. Mass deviations were all found to be consistent at <1. 5 ppm, with a slight trend to decrease with an increasing m/z ratio (ESM Fig. S4 ). As shown in Fig. 1 , predicted combinations listed in Table  2  explained most peaks visible on the base peak chromatograms. In terms of involved monomers, common predicted combinations were all and exclusively based on NPG and PA only, confirming expected similarities between both lacquers.
Chromatographic consistency Consistency of information deduced from the confrontation of measured exact masses and the database was further investigated in terms of chromatographic considerations. First, it could be observed that for oligomers constituted of the same monomers, (for example No. 1, 2, and 3, Table  2 ), the retention time was increasing according to the chain length (see ESM Fig. S6  for illustrations). Indeed, cyclic tetramers were eluted first, followed by cyclic hexamers, then cyclic octamers, attesting to the decreasing polarity of these compounds, as previously observed by Bradley and co-workers  [29]. Moreover, most of the time several peaks could be detected for a given combination because of the presence of terephthalic and isophthalic acid isomers in both lacquers as well as the possibilities of arrangements within the chain.
Chromatographic separation was rather satisfactory for cyclic tetramers because of the limited number of isomers but hardly and not achievable for cyclic hexamers and octamers, respectively, due to the increasing number of isomers. In terms of polarity and considering variations in diols composition, a consistent impact was observed. Indeed, using the molecular modelling ChemSketch software, Log(P) values were estimated for each carbon chain diol monomer, i. e. , without the alcohol functions, which were considered reacted as part of ester bounds to PA diacid monomers (e. g. , ethane instead of EG). Therefore, calculated Log(P) values were found to be 0. 98, 1. 82, 3. 05, and 3. 94 for DEG, EG, NPG, and HD Table  1  Polyol and polyacid monomers selected to populate the homemade database. SML: specific migration limit (mg.
In order to simplify the interpretation processing, only fragments detected above a relative intensity to the base peak of 5% were considered. The ACD/MS Fragmenter software was helpful to elucidate the structure of the main fragments (ESM Table  S4 ). Indeed, fragments were often matching combinations of diol and diacid monomer present in the oligomer, with rearrangements after a loss of one molecule of water for example. In addition, and logically, the more the oligomer is composed of various monomers, the more the list of observed fragments is long. Likewise, some fragment ions were specific to given monomers, such as at m/z 149 and sometimes 167 for PA, m/z 69 for NPG or m/z 83 for HD, respectively. Conversely, there was no specific fragment ion discriminating EG from DEG. Indeed, DEG is composed in some way of two EG and a rupture can occur on each side of the central oxygen, leading to EG-like fragments.
The fragment ion at m/z 193 was intense and systematically detected in presence of PA with DEG and/or EG (ESM Table  S4 ). Furthermore, even without a specific ion, the complete set of detected ions was sufficient to be confident concerning the identification. As a conclusion regarding predicted oligomers, a total of 28 monomer combinations could be elucidated, the collection of clues (known constituting monomers, precise m/z matching database, retention time consistency, fragmentation pattern) was considered strong enough to reach the second level of identification as proposed by Sumner et al. in a context of biomarkers identification in untargeted (metabolomics) studies  [36]. A higher level of confidence will require genuine analytical standards that are still not, commercially or not, available.
Deduction of unexpected monomers Among the most intense lacquer-specific PCgroups, 36% did not match the database. Assuming that the presence of an unexpected starting monomer would lead to oligomer series, exact mass differences corresponding to the substitution of a known monomer by an unknown one were examined to reconstitute such series. This way, 15 combinations (C, H, O) involving 18 PCgroups were connected in several networks after retention time consistency verified as described above. Taking into account permuted monomers, C x H y O z elemental formula was assigned (<2 ppm deviation) (Table  3 ). Considering results from predicted oligomers and observed intensities, cyclic structures appeared more plausible than linear ones. The lengths of the cyclic oligomers were estimated from the number of oxygen atoms.
Indeed, cyclic tetramer, hexamer, and octamers can be composed of at least 8, 12, and 16 oxygen atoms, originating from the 4, 6, and 8 ester functions. Moreover, a number of PA monomers was hypothesized from the DoU. Indeed, the oligomer cycle along with the ester functions contribute to DoU of 5, 7, and 9 for cyclic tetramers, hexamers, and octamers, respectively, whereas a PA monomer bears an additional DoU of 4. Combining all this information, three distinct series were related to three tentative unexpected monomer formulas, including one diol (C 12 H 24 O 2 ) in Lac1,     3 ). Regarding Lac2, suggestions of structures were attempted. The sebacic acid (SA), not initially included in the homemade database and even less considered as a known starting monomer since not subjected to restriction, was found as the only diacid matching the elemental formula in the AP (2004) 1 guideline  [6].
Within the considered t R range, blank contributions remained quite low, at 9. 1% and 3. 2% of the total feature intensity in Lac1 and Lac2, respectively, attesting to proper sample preparation and appropriate concentration to enhance lacquer-specific signals. Predicted oligomers, defined as compounds matching the database of expectable combinations of known monomers, accounted for the most important part, 79% and 70% of total feature intensities in Lac1 and Lac2, respectively. This substantial proportion gives evidence that most NIAS accessible with the proposed sample preparation and data acquisition, including LC and ionization techniques, are predicted cyclic oligomers. Three unexpected monomers and nitrogenous compounds were hypothesized, leading to tentatively elucidated cyclic oligomers representing up to 20% of the total feature intensity in Lac2, mainly due to the presence of an intended but unknown monomer (SA).
Conclusions and perspectives The proposed methodology allowed seeking, within complex LC-HRMS datasets, predicted oligomers as well as deducing unpredicted NIAS migrating from polyester-polyurethane coatings. Relying on open-source software, the data processing was automated, facilitating the manual review along with a homemade database dedicated to predicted combinations of known monomers. In the two lacquer samples investigated, predicted cyclic oligomers accounted for two-thirds to threequarters of the cumulated signal intensities. The remaining signals were attributed to elucidated structures based on unexpected monomers explaining consistent signal series, as well as procedural blank contribution and minor nonreviewed compounds. In terms of identification confidence, all suggestions were supported by chromatographic and fragmentation consistency.
The analytical strategy (LC-ESI-HRMS) proposed was well suited to investigate cyclic oligomers. For future fication purposes, the database will be updated in light of the outcomes of the present work, including in particular the three unexpected monomers, caprolactam oligomers, as well as combinations of monomers resulting from reaction with solvents or additives (IPDI, caprolactam). If cyclic oligomers appear as major migrating NIAS from polyesterpolyurethane coating, only quantification will allow to balance with linear oligomers or other NIAS, pending complementary analyses covering more volatile fractions by GC couplings, or to balance with migrating fraction above 1000 Da. Beyond identification, which was the purpose of the present study, future work should address the quantification of such migrating substances in food simulant as well as in foodstuffs in an exposure assessment perspective.
Cloning and molecular characterization cDNA sequences for thrs were predicted from genomic DNA sequences originating from the European eel genome assembly (WGS Project: AZBK01), available in NCBI resources  (Henkel et al. , 2012). Briefly, blastn requests were performed from Japanese eel cDNA thr sequences on the European eel WGS database to identify genomic contigs, including thr genes. European eel thr cDNA sequences were then deduced from contigs using GENSCAN (http://genes. mit. edu/GENSCAN. html) software  (Burge et al. , 1997). The predicted transcript sequences for each thr gene were confirmed by sequencing cDNAs from European eel RNA amplification. Cloning was achieved using TOPO TA cloning kit (Invitrogen) with pCR™II-TOPO® vector, according to the manufacturer's instructions. Primers sequences were as follows: thrαA (F) 5'-GGGTCGCTGAGGAGACCT-3', thrαA (R) 5'-GGTGCTCAGACGTCCTGGT-3', thrαB (F) 5'-GCCCAACGACCCTAACCTAT-3', thrαB (R) 5'-GGATAGTAAATCAGGCCCTTAATC-3', thrβA (F) 5'-GACTCCGAGGCCCTAATTCT-3', thrβA (R) 5'-GACTCCGAGGCCCTAATTCT-3', thrβB (F) 5'-GAAGACTGAGCCCTGAGGTG-3', thrβB (R) 5'-TCACATGTACCCGCATTTGT-3'.
Phylogenetic analysis A phylogenetic tree was constructed using the Neighbor-Joining method  (Saitou and Nei, 1987)  with amino acid thr vertebrate sequences. The evolutionary distances were computed using the JTT matrix-based method  (Jones et al. , 1992)  and are in the units of the number of amino acid substitutions per site. All positions containing gaps and missing data were eliminated. For the analysis, 1000 bootstrap replicates were carried out. Phylogenetic analysis was conducted in MEGA6  (Tamura et al. , 2013). The GenBank accession numbers of the sequences used can be found in the Supplementary material.
The ef1, 18s, 40s genes were chosen as housekeeping genes since qBase+ software revealed that these mRNA levels were stable throughout analyzed samples (M < 0. 4); M gives the gene stability and M < 0. 5 is typical for stably expressed reference genes  (Hellemans et al. , 2007). Using primer 3 software v 0. 4. 0 (http://frodo. wi. mit. edu/primer3/) primers were designed i) for thrαA, thrαB, thrβA and thrβB based on cloned cDNA sequences, ii) for ef1α and 40s based on sequences available in Genbank nucleotide database, and iii) for dio1, dio3 and 18s based on sequences available in the European eel transcriptome EeelBase 2. 0 database (http://compgen. bio. unipd. it/eeelbase/), as indicated in Table  1. To design the primers of dio2 a European eel predicted cDNA sequence was used and the size of the amplicon obtained by amplification was checked (http://www.
Statistical analyses All data were analyzed using SAS statistical software (version 9. 1; SAS Institute Inc. , Cary, North Carolina). Residuals were tested for normality using the Shapiro-Wilk test and homogeneity of variances was tested using a plot of residuals versus fit values (PROC GLOT, SAS Institute 2003). Data were log 10 or arcsine square-root-transformed when data deviated from normality and/or homoscedasticity  (Zar, 1996). Together, this allowed us to decipher changes in temperature at real-time and standardized developmental intervals. To examine the effect of temperature on gene expression throughout early development (real time), we used two statistical approaches. In the first approach, we analyzed the data using a series of mixed-model repeated measures ANOVAs (PROC MIXED; SAS Institute 2003).
In the second approach, we examined variation in gene expression, throughout development at each temperature, by fitting either linear, quadratic or cubic equations to the data (PROC REG; SAS Institute 2003). This allowed us to create predictive models to explore the shape of variation throughout development for each temperature. Linear, quadratic and cubic equations were chosen apriori to fit the data based on the available literature (e. g. McDonald, 2009; Sørensen et al. , 2016). Final equation selection (linear, quadratic or cubic) was based on an F-statistic: d. f. j × (R² j -R² i ) / (1 -R² j ), where: R² i = the R² for the i-th order, R² j = the R² for the next higher order, d. f. j = the degrees of freedom for the higher-order equation with j degrees of freedom in the numerator and d.
THRβ (named aaTHRβA and aaTHRβB) were cloned in European eel larvae. The full CDS (coding DNA sequence) of the four THRs was sequenced. The nucleotide sequences of aaTHRαA (GenBank accession number KY082904) and aaTHRαB (accession number KY082905) are 1375bp and 1334 bp long, with an open reading frame (ORF) that codes for a protein of 416 and 435 amino acids respectively, while the nucleotide sequences of aaTHRβA (GenBank accession number KY082906) and THRβB (GenBank accession number KY082907) are 1288bp and 1299bp long,.
Acknowledgements This study was part of the project  Eel Hatchery Technology for a Sustainable Aquaculture (EEL-HATCH ) supported financially by  InnovationFund Denmark , Grant no. 11-2013-3. Politis SN, received travel grants from the  COST Office (Food and Agriculture COST Action   FA1205 : Assessing and improving the quality of aquatic animal gametes to enhance aquatic resources. The need to harmonize and standardize evolving methodologies, and improve transfer from academia to industry; AQUAGAMETE). Butts, IAE was partially supported by the  Alabama Agricultural Experiment Station  and the  Hatch program  of the  National Institute of Food and Agriculture, U. S. Department of Agriculture. Miest JJ, was funded by the  FINEAQUA-project (Program for the futureeconomy, Schleswig-Holstein -European regional development fund (ERDF)).
1 F: CTGAAGCCTGGTATGGTGGT R: CATGGTGCATTTCCACAGAC Ribosomal 18S RNA 18s EeelBase 2. 0 eeel2_s7245 F: AGAGCAGGGGAACTGACTGA R: ACCTGGCTGTATTTGCCATC Ribosomal 40S GenBank RNA 40s TSA GBXM01005349. 1 F: TGACCGATGATGAGGTTGAG R: GTTTGTTGTCCAGACCGTTG.
FUNDING J-LF  acknowledges support from  BBSRC/EPSRC  (grant number  BB/M017702/1 ) and from the  ANR  (grant number  ANR-15-CE1-0008 ). MK is supported by  DGA  ( French Ministry of Defense ) and  Ecole Polytechnique. OB is supported by  Genopole Allocation Recherche 2017  and  CRI Paris Short-term Fellows. We thank  Dr. Melchior du Lac  for his technical help.
Microscopy and image acquisition SiR-Hoechst labeled DNA imaging. DNA images were acquired using a DMI8 inverted automated microscope (Leica Microsystems) featuring a confocal spinning disk unit (CSU-X1-M1N, Yokogawa). Integrated laser engine (ILE 400, Andor) with a selected wavelength of 647 nm (140 mW) was used for excitation. Samples were imaged with an oil immersion objective (Leica HCX-PL-APO 100x/1. 4 NA). Fluorescence emission of the SiR-Hoechst was filtered by a single-band bandpass filter (FF01-650/13-25, Semrock, Inc. ). Image series of 150 frames (5 fps) were acquired using Metamorph software (Molecular Devices), and detected using sCMOS cameras (ORCA-Flash4. 0 V2) and (1 × 1 binning), with sample pixel size of 65 nm. All series were recorded at 37 • C and in a humid chamber by controlling the temperature and CO 2 control flow using H201--couple with temperature and CO 2 units.
H2B-GFP imaging. Series of 150 frames were acquired with an exposure time of 200 ms using a Nipkow-disk confocal system (Revolution, Andor) featuring a confocal spinning disk unit (CSU22, Yokogawa). A diode-pumped solidstate laser with a single laser line was used for excitation of GFP at 488 nm (25 mW; Coherent). Samples were imaged with an oil immersion objective (100×, Plan Apo 1. 42, Nikon) followed by 2× magnification and fluorescence was filtered with an emission filter (ET525/30-25, Semrock, Inc. ). The fluorescent emission was detected on a cooled electron multiplying charge-coupled device camera (iXon Ultra 888), with sample pixel size of 88 nm. The system was controlled using the Revolution IQ software (Andor).
Details of all the tested algorithms can be found in Supplementary Note 1. We evaluated the performance of the different methods by determining the angular error (AE) and the endpoint error (EE) in simulated datasets. The simulation of data samples was carried out by randomly placing emitters with a defined density in a given volume with varying SNR as described in (Supplementary Note 1 and Supplementary Figure  S1 ). A series of two images was simulated where emitters undergo Brownian diffusion and therefore are displaced from one image to another. We simulated a density ranging from 0. 02 to 2. 5 emitters per pixel representing the spatial variation of chromatin compactness within hetero-and euchromatin (26) (Supplementary Figure  S1a-c ). Further, we varied the particles' diffusion coefficient as well as the number of coherently moving domains which could potentially reflect chromatin motion at different length scales (Supplementary Figure  S1f  and g ).
The AE is a relative measure and penalizes discrepancies in the direction of ground-truth and estimated flow. The evaluation of errors in the magnitude is given by the absolute EE  (36). EE = V -V. All calculations were carried out using MATLAB (MAT-LAB Release 2017a, The MathWorks, Inc. , Natick, MA, USA) on a 64-bit Intel Xeon CPUE5-2609 1. 90 GHz workstation with 64 GB RAM and running Microsoft Windows 10 Professional.