dataesr/scientific-paragraphs-categorization huggingface dataset:
Confocal microscopy and Raster Image Correlation Spectroscopy Confocal microscopy and Raster Image Correlation Spectroscopy (RICS) experiments were performed on a Leica SP2 microscope equipped with a 63× oil immersion objective (NA = 1. 2). eGFP fluorescence was excited with a 488 nm argon laser line and the emitted fluorescence (500-550 nm) was detected by a PMT detector. The RICS analysis was performed using the SimFCS software developed by the Laboratory for Fluorescence Dynamics (http://www. lfd. uci. edu). For each cell, a stack of 50 images (256×256 pixels with a pixel size of 50 nm) was acquired at 400 Hz (2. 5 ms between the lines) with a pixel dwell time of 4. 8 μs. Moving average subtraction was performed to remove the contribution of slow moving structures and cellular displacements  [43].
The focal volume was measured prior to experiments using a 50 nM solution of tetramethylrhodamine (TMR) with a known diffusion coefficient (D = 592 μm 2 /s at 37°C)  [46]. For each condition, measurements were performed in the cytoplasm and the nucleus of 16 different cells. For each measurement, 50 acquisitions of 5 seconds duration were realized and the autocorrelation curves were calculated. Five averages of ten autocorrelation curves were calculated and analyzed independently by the Quickfit software  [47] , using the anomalous diffusion model: GðtÞ ¼ 1 V eff hCi 1 1 þ t t D a 1 ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 þ r 0 z z 2 t t D a r ð1Þ where Veff and <C> represent the effective focal volume and the average concentration of fluorescent molecules, respectively while r 0 and zz correspond to the lateral and axial dimensions of the focal volume, respectively.
Fluorescence lifetime imaging microscopy (FLIM) Time-correlated single-photon counting FLIM was performed on the same two-photon microscope as described for FCS, using an excitation wavelength of 900 nm. Imaging was carried out with a laser scanning system using two fast galvo mirrors (Model 6210, Cambridge technology, MA), operating in the descanned fluorescence collection mode. The fluorescence was directed to a fiber coupled APD (SPCM-AQR-14-FC, Perkin Elmer, CA), which was connected to a time-correlated single photon counting (TCSPC) module (SPC830, Becker & Hickl, Germany), operating in the reversed start-stop mode. Typically, the samples were scanned continuously for about 80 s to achieve appropriate photon statistics to determine the fluorescence decays. Data were analyzed using a software (SPCImage V2.
Antennal movement analysis The monitoring apparatus recorded at each time point (90 times per second) the location of the two antenna tips of each bee on the camera sensor. First, all the recordings from all bees were recalculated in the same coordinate system (x,y), with the socket of the right antenna as the origin (coordinate 0,0) and the socket of the left antenna as the unit reference on the x-axis (coordinate 1,0). Each recording thus resulted in a series of (x,y) coordinates for each antenna at each time-step (1/90 sec). This allowed a comparison between the antennal movements of different bees. In addition, heat maps describing the number of times each antenna tip was located at each coordinate could be constructed (Fig. 3 ). In these heatmaps, the number of occurrences of each data point was normalized with regard to the total number of occurrences on the entire map, to make them comparable in the various conditions.
Statistical analysis During conditioning, the occurrence of a proboscis or sting extension (depending on conditioning assay), was recorded as 1 and nonextension as 0. The acquisition curves show the percentage of individuals showing a PER or a SER to each presentation of the CS+ or of the CS2. To analyze learning performances, a repeated-measure analysis of variance (RM-ANOVA) was used, with trial (from 1 to 6) and stimulus (CS+/CS2) as within-group factors. Monte Carlo simulations demonstrated that it is permissible to use an ANOVA on dichotomous data under controlled conditions  (Lunney 1970). For each conditioning type, the two subgroups receiving 1-hexanol (odorant A; PER n ¼ 21; SER n ¼ 33) and 1-nonanol (odorant B; PER n ¼ 23; SER n ¼ 35) as CS+ were pooled. No effect of these subgroups or interaction with other variables were found (RM-ANOVA, interaction stimuli × odors × trials, PER: F (5,210) ¼ 0.
Acknowledgments We are indebted to  P. Pirim ,  L. Josselin , and  G. Havard  ( Brain Vision Systems, Paris ) for their help in software development and to  S. Famie  ´for initial tests with the motion capture system. This work was supported by the  Agence Nationale de la Recherche (ANR) ,  Paris, France  (Project  BEE-CHANNELS ,  ANR-13-BSV7-0010 ). H. C. and P. J. thank the  French Ministere de la Recherche et de l'Enseignement Supe  ´rieur for PhD funding. We thank the  Evolbee Team  for fruitful discussions and  A. French  and two anonymous referees for helpful comments on the manuscript.
FBA-Independent Screening of Medium Components Up to date, no deep investigation for development of fermentation media for lycopene production from Y. lipolytica has been realized. In order to establish a reference medium for evaluation of the FBA efficiency, we first selected a set of 23 factors in the light of preliminary experiments and literature review for the designing of FBA-independent cultivation medium. Bioprocess improvement experiments were carried out using the engineered strain Po1f-1312E-1269IB. In a first step, we screened a set of chemicals without considering the flux balance analysis (FBA). The matrix of the Plackett-Burman design used in regard of this achievement is reported in Table  1. According to the Plackett-Burman principle, data transformation is required if the ratio max/min is greater than 10.
Modeling Platform Flux balance analysis (FBA) is the paramount method for estimating flux distributions and assumes that organisms utilize substrates adequately to maximize a fixed objective of model (biomass or a particular reaction of production). The FBA method can be used to reproduce environmental conditions necessary for achieving the maximization of the objective function of the model and is an integrated element of the COBRA 2. 0 Toolbox in Matlab. The FBA was carried out using Matlab R2011a (Mathworks, Natick, MA, USA) and the COBRA 2. 0 toolbox. We used an in silico Y. lipolytica terpenoids biosynthesis genome-scale metabolic model (GSM) yli v1. 7 updated from our previous publication  [29]. The updated GSM yli v1. 7 was composed of 718 genes, 1293 reactions, and 986 metabolites.
Plackett-Burman Design and Shake Flasks Cultivation To identify the vital factors that affect biomass and lycopene production in the engineered strain and make breakthrough improvements, a saturated screening design based on the Plackett-Burman structures incorporated into Design expert software (version 8) was adopted. The total number of trials to be implemented according to Plackett-Burman was (n+1) runs, wherein n represents the number of modules to be screened. Each component was assigned two levels of concentrations (high concentration and low concentration). Firstly, a set of 23 factors selected in light of the preliminary experiments and literature review (data not shown), were combined in 24 trials for the designing of FBA-independent cultivation media. Following this, the FBA-driven predicted factors (n = 23) were used for conducting a Plackett-Burman design of 24 runs.
The extraction step was repeated until all visible pigments in the residual cell pellet and supernatant were extracted. The obtained colored supernatants were pooled together and used for lycopene quantification via high-performance liquid chromatography (HPLC) analysis. All operations occurred on ice under dim light to prevent photodegradation, isomerizations, and structural changes of the carotenoids. The lycopene concentration of each extract was quantified by HPLC analysis which was performed on a Shimadzu LC-20A HPLC instrument equipped with a LC solution software program, LC-20AD pump, and a detector with a UV-Vis lamp. Specifically, it was carried out by injecting 10 μL of the crude carotenoid extract into a Zorbax SB-Aq C18-reverse-phase column (4. 6 mm × 250 mm, 5 μm; Agilent Technologies, Palo Alto, CA, USA).
Acknowledgements. We thank  Samantha Tirmarche  and  Laure Sapey-Triomphe  for their help in the acquisition of confocal images. We also thank the imaging facility of the  Centre Technologique des Microstructures. We are grateful to  Scott Pitnick ,  John Belote  and  Renate Renkawitz-Pohl  for providing fly stocks used in this work.
Data The CRISPR spacer counts were obtained from the September 2013 version of the CRISPRdb  (Grissa et al. , 2007)  and included spacers from all partitions in the genome in question (that is, both chromosomeand plasmid-encoded spacers). The spacer number ranged from 0 to 736. The updated version of the ATGC database clusters ~60% of proteins and 62% of genomes from RefSeq (as of June 2013) into 269 groups of closely related genomes of bacteria and archaea  (Novichkov et al. , 2009; Puigbo et al. , 2014). Clusters of Orthologous Groups (COGs) shared between genomes in each ATGC were identified  (Tatusov et al. , 1997; Kristensen et al. , 2010) , leaving singletons defined as those genes that were not shared with any of the closely related genomes included in the given ATGC. These singletons are most likely to have arisen via recent HGT that has occurred after these closely related organisms have diverged.
Acknowledgements We thank  Kira Makarova  and  Christine Pourcel  for helpful discussions and suggestions, and the eBio IFB platform for bioinformatics support to CRISPRdb. UG is supported by the  National Evolutionary Synthesis Center (NESCent). DMK, YIW and EVK are supported by intramural funds of the  US Department of Health and Human Services  (to the  National Library of Medicine). OP is supported by the  European Research Council  (grant no. 281357 ).
In 45/114, information concerning the parents was obtained through registers in their place of birth, but remained unknown for 53 transmitting parents. Survival was determined with the Kaplan-Meier estimator. Causes of death were presumed to be related to the disease, but we cannot exclude that a limited number of other pathologies were responsible. Missing ages when aid walking or wheelchair use where needed were estimated by multiple imputations using the Markov Chain Monte Carlo method. Imputed data were determined as a function of the gene involved and, for the polyQ-SCAs, the length of the CAG repeat, and analyzed using Cox models. The null hypothesis was rejected for P < 0. 05. Statistical analysis was performed with SAS software (version 9. 3; SAS Institute, Cary, NC). Data are expressed as the mean AE SD [minimum-maximum].
Acknowledgments Many thanks to the patients and families for their help. We are very grateful to  Merle Ruberg  for her critical reading of the manuscript. We acknowledge the clinicians of the SPA-TAX network involved in this study:  M. Tchikviladz  e,  M. Anheim ,  P. Ribai ,  I. Leber A. Benomar ,  S. Medjbeur ,  E. Ollagnon ,  V. Meininger ,  A. Vighetto ,  J. Pouget ,  C. Tranchant ,  H. Aliouche ,  D. Brassat ,  A. Destee ,  A. Toutain ,  C. Goizet ,  A. Lannuzel ,  D. Hannequin ,  A. Lagueny ,  P. Damier ,  C. Delpirou ,  D. Broglin ,  G. Ponsot ,  J. C. Pages ,  A. Autret ,  C. Vial ,  P. Labauge ,  P. Clavelou ,  P. Amati-Bonneau ,  E. Kaphan ,  R. Bellance ,  J. M. Leger ,  C. Desnuelle ,  P. Coutinho ,  J. Melki ,  Y. Boukhriche ,  V. Paquis ,  F. Tison ,  A. Barois ,  R. Ghnassia ,  J.
Sequence analysis and annotation Gene modeling was performed with both the Critica  [31]  and Glimmer  [32]  modeling packages. The results were combined and a basic local alignment search tool for proteins (BLASTP) versus GenBank's nonredundant database (NR) was conducted. The alignment of the N terminus of each gene model versus the best NR match was used to pick a preferred gene model. If no BLAST match was returned, the Critica model was retained. Gene models that overlapped by greater than 10% of their length were flagged, giving preference to genes with a BLAST match. In addition to BLASTP versus NR, the revised gene/protein set was searched against the KEGG GENES  [33] [34] [35] , InterPro  [36]  (incorporating Pfam  [37] , TIGRFams  [38] , SMART  [39] , PROSITE  [40] , PRINTS  [41]  and ProDom  [42] ) and Clusters of Orthologous Groups of proteins (COGs)  [43]  databases.
From these results, functional categorizations were developed using the KEGG and COGs hierarchies. Initial criteria for automated functional assignment required a minimum 50% residue identity over 80% of the length of the match for BLASTP alignments, plus concurring evidence from the above profile methods (e. g. pfam). Putative assignments were made for identities down to 30%, over 80% of the length. To determine whether C. phytofermentans produced cellulosomes, a position-specific amino acids matrix, based on the sequence of the cellulosome domains from the Clostridium species, C. cellulolyticum, C. thermocellum and C. acetobutylicum, was constructed and searched against a local database of predicted C. phytofermentans proteins using PSI-BLAST. In addition, we searched C. phytofermentans proteins using Pfam models of cohesins and dockerins.
Detection of carbohydrate-active enzymes in bacterial proteomes The search for carbohydrate-active modules (glycoside hydrolases, glycosyltransferases, polysaccharide lyases and carbohydrate esterases) and their associated carbohydrate-binding modules (CBMs) in C. phytofermentans was performed exactly as for the daily updates of the Carbohydrate-Active enZYme (CAZy) database (http://www. cazy. org/). Briefly, the sequences of the proteins in CAZy were cut into their constitutive modules (catalytic modules, CBMs and other noncatalytic modules or domains of unknown function). The resulting fragments were assembled and formatted as a sequence library for BLAST  [47]  searches. Accordingly, each protein model from C. phytofermentans (and other bacterial proteomes) was searched via BLAST against the library of approximately 100,000 individual modules using a database size parameter identical to that of the NCBI nonredundant database.
All models that gave an expectation value lower than 0. 1 were automatically kept and manually analyzed. Manual analysis involved examination of the alignment of the model with the various members of each family (whether of catalytic or non-catalytic modules), with a search of the conserved signatures and motifs characteristic of each family. The presence of the catalytic machinery was verified for borderline cases whenever known in the family. The models that showed the usual features that would lead to their inclusion in the CAZy database were kept for annotation and classified in the appropriate class and family.
Investigation of evolutionary origins of glycoside hydrolases The taxonomic distribution of the BLASTP best hits (e-value< = 0. 01) of the glycoside hydrolases in GenBank's nonredundant database (as of January 2011) excluding C. phytofermentans sequences was compared to that of BLASTP best hits of all the ORFs within the C. phytofermentans genome. A Pearson's Chi-squared test was used to determine the significance of the differences between the two taxonomic distributions.
Microarray design A C. phytofermentans Affymetrix microarray was custom-designed for the measurement of the expression level of all open reading frames, estimation of the 5' and 3' untranslated regions of mRNA, operon determination, and discrimination between alternative gene models (differing primarily in the selection of the start codon). Putative protein coding sequences were identified using both GeneMark and Glimmer, and the union of these two predictions was used to design the array. Each coding sequence (CDS) was represented by eleven 24-mer probes. Standard Affymetrix array design protocols were followed to ensure each probe was unique to minimize cross hybridization. If two CDS differed only in their N-terminal region, the smaller of the two proteins was used for transcript analysis, but the extended region was also represented by probes to define the actual N-terminus.
Microarray processing cDNA synthesis, array hybridization and imaging were performed at the Genomic Core Facility at the University of Massachusetts Medical Center. Ten μg total RNA from each sample was used as template to synthesize labeled cDNAs using Affymetrix GeneChip DNA Labeling Reagent Kits. The labeled cDNA samples were hybridized on the arrays according to Affymetrix guidelines. The hybridized arrays were scanned with a GeneChip Scanner 3000. The resulting raw spot image data files were processed into pivot, quality report, and normalized probe intensity files using Microarray Suite version 5. 0 (MAS 5. 0)  [50]. In addition, expression values were calculated using the Custom Array Analysis Software (CAAS) package (http://www. sourceforge. net/projects/caas-microarray/) that implements the Robust Multichip Average method  [51].
The individual microarray files and the normalized gene summary values for the complete data set will be deposited in the Gene Expression Omnibus (GEO) database at NCBI  [52]. The quality of the microarray datasets were analyzed using probe-level modeling procedures provided by the affyPLM package in BioConductor  [52]. No image artifacts due to array manufacturing or processing were observed. Microarray backgrounds were within the typical 20-100 average background values for Affymetrix GeneChip. In summary, all quality control checks indicated that the RNA purification, cDNA synthesis, labeling and hybridization procedures adapted for use in C. phytofermentans resulted in high quality data. All microarray data reported in the text and figures represent the average of expression values derived from two independent RNA preparations from duplicate cultures.
Genes encoding carbohydrate-active enzymes C. phytofermentans is capable of breaking down the recalcitrant, insoluble components of plant cell walls including cellulose, hemicellulose, pectin and starch  [12]  as well as switchgrass, corn  To gain insight into the origin of the GHs of C. phytofermentans, we identified the closest relatives of the GHs of C. phytofermentans in the GenBank database using BLASTP and compared their distribution to that of the closest relatives of all of the protein-coding genes within the C. phytofermentans genome. The latter analysis was performed to calibrate how much similarity to other bacteria would be expected on average. In total, approximately 40% of the GHs of C. phytofermentans were most similar to GHs present in species outside the class Clostridia (Fig  4 ), whereas only 20% of all the genes in the C.
8 (±27. 7) paroxysmal manifestations (52% motor events) at baseline that dropped to 2. 8 (±2. 9, 76% motor events) during the treatment phase ( p=0. 028). After withdrawal, paroxysmal manifestations recurred with a mean of 24. 2 (±21. 9, 52% motor events; p=0. 043). Furthermore, brain energy metabolism normalised with triheptanoin, that is, increased Pi/PCr ratio during brain activation compared to the recovery phase ( p=0. 021), and deteriorated when triheptanoin was withdrawn. Conclusions Treatment with triheptanoin resulted in a 90% clinical improvement in non-epileptic paroxysmal manifestations and a normalised brain bioenergetics profile in patients with GLUT1-DS. Trial registration number NCT02014883.
SUBJECTS AND METHODS Participants were enrolled in an interventional clinical protocol (NCT02014883) at the Pitié-Salpêtrière Hospital promoted by INSERM and approved by the local ethical committee. All participants and/or their legal guardians signed a written informed consent before participating in the study. Four children and four adults were enrolled with GLUT1-DS as defined by low cerebrospinal fluid to blood glucose ratio and a SLC2A1 missense mutation predicted to be pathogenic by prediction software programs. Patients had a chronic history of non-epileptic paroxysmal motor disorders, especially paroxysmal exercise-induced dyskinesia, nonkinesigenic dyskinesia, limb weakness, headache, drowsiness and dysphoria. Three patients also presented a mild cognitive deficit. All patients were on a normal diet prior to their enrolment as either they objected to or did not tolerate ketogenic diets.
Furthermore, visual stimulation results in a large increase in glucose uptake and cerebral blood flow. 8 Data were collected for 4 min at rest, 8 min during visual activation, 8 min after stimulation and analysed as described. 7 9 he ratio of inorganic phosphate over phosphocreatine (Pi/PCr) was calculated to determine the brain response to cortical activation as it is directly related to the ADP levels which regulate mitochondrial oxidative metabolism. 10 aired t tests were used for plasma analyses before and after treatment. For clinical parameters, Friedman tests were used to test the global hypothesis that all study phases were equal. If significant, Wilcoxon signed-rank tests were applied for pairwise phase comparisons with an α of 0. 05. For the Pi/PCr ratio, repeated measures analysis of variance (ANOVA) were used to test the global hypothesis that all time points (rest, activation and recovery) were equal.
Acknowledgements  Ultragenyx Pharmaceutical Inc  provided the investigational drug triheptanoin and funded the study. The research leading to these results has received funding from the  programme 'Investissements d'avenir'   ANR-10-IAIHU-06. The authors are grateful to  Dr Isabelle An ,  Pr Jean-Christophe Corvol  and  Constance Flamand-Roze  for their expertise on some of the material revised for this study,  Dr Cécile Hubsch  for referral of a patient and  Maxime Janin  for excellent technical assistance. Contributors FM was involved in the study concept and design, obtaining funding, study supervision and coordination, analysis and interpretation of data, statistical analysis and drafting/revising the manuscript. EH and DG were involved in the study coordination, acquisition of data, analysis and interpretation of data and drafting/ revising the manuscript.
2014). Establishing a good reference framework would be critical for the conservation of this peculiar placental group, which includes a number of endangered species. According to the last IUCN Red list Assessment (IUCN Red List of Threatened Species 2015), 6 of the 31 living species (19%) were considered threatened, while the conservation status of 5 species could not be assessed due to lack of data. One particularly striking example is the iconic Brazilian three-banded armadillo for which no molecular data currently exist and for which only scarce biological information can be found in the literature  (Superina et al. 2014; Feij o et al. 2015). More generally, 9 species among the 31 currently recognized xenarthrans still have not been investigated via molecular means are thus not represented in GenBank.
A valuable alternative to partitioned models is provided by the Bayesian site-heterogeneous CAT-GTR (general time reversible) mixture model  (Lartillot and Philippe 2004) , in which the optimal number of site-specific substitution pattern categories is directly estimated from the data. The application of this model for analyzing mammalian mitogenomic data is only starting, but it has already been rather promising  (Hassanin et al. 2012; Botero-Castro et al. 2013; Fabre et al. 2013 ). In the case of our xenarthran data set, ML and Bayesian implementations of the optimal partitioned model and Bayesian inference under the CAT-GTR mixture model gave exactly the same, fully resolved topology apart from one unsupported node within the genus Dasypus (fig. 1 ). The xenarthran mitogenomic tree shows a fair amount of branch length heterogeneity among groups, with fast evolving clades including anteaters and Dasypodinae, and slow evolving clades such as sloths and hairy armadillos (fig.