dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The first author would like to thank the  Département de Mathématiques de l'Université d'Angers (France)  and the  Geanpyl  project of the  Pays de Loire  for their support and hospitality during the preparation of the final version of this work. The second author would like to thank the  University of Sevilla (Spain)  for its support during a stay in April 2012, for the preparation of this paper.
Raman micro-spectroscopy More precisely, 997 polymorphonuclears, 95 monocytes and 1127 lymphocytes from 12 different blood samples have been considered in the first part of this study, and a Raman spectrum has been acquired on each of them. In the second part, 4257 spectra have been registered on lymphocytes of 49 leukemic patients suffering from hyper leukocytosis Chronic Lymphocytic Leukemia, and 2596 spectra have been recorded on lymphocytes of 27 healthy individuals. These spectra have been then studied, using around 90 cells per blood sample. Raman data were first pretreated to erase contaminant information into the spectra and then were analyzed using a multivariate statistical method which put forward the relevant information needed to distinguish in a first time lymphocytes from polymorphonuclears.
Conclusion IHMO project has demonstrated the power of Raman micro-spectroscopy coupled with supervised classification algorithm such as Support Vector Machines for cell classification and more precisely for the diagnosis of CLL. Morphological descriptors obtained from multi-Z and multispectral images provide another independent classification that still needs to be assessed. The multimodal microscopy platform can be used more generally in the field of cytohematology, however application to cytological and histological pathology would need further developments and could take profit from new methods in data classification.
Acknowledgements • The  French National Research Agency (ANR)  for funding  • Chih-Chung Chang  and  Chih-Jen Lin , LIBSVM: a library for support vector machines, 2001. Software available at http://www. csie. ntu. edu. tw/~cjlin/libsvm  • Clinical staff of the university hospital of Reims • Rodolphe Dagiral  and  Valérie Coomans  from  Réactifs RAL  for developing and providing standardizes MGG stains used for multi-spectral imaging classification  • Philippe Rideau ,  David Pointu  and  Claire Vernois  from  NIKON France  for defining and installing appropriate microscopy hardware  • Emmanuel Froigneux  from  HORIBA JOBIN YVON  for developing and providing the micro-spectroscopy Raman module.
Electronically stored patient records from the departments of paediatric cardiology of the French national network for complex congenital heart diseases (M3C) are being searched to identify the children to be included. The minimum dataset will comprise: identification of the subject (file number in the centre or department, full name, sex, date and place of birth), and characteristics of the intervention (date, underlying disease, type of procedure, technical details, such as fluoroscopy time and dose area product, (DAP), which are needed to reconstruct the doses received by each child). The cohort will be followed up through linkage with the two French paediatric cancer registries, which have recorded all cases of childhood leukaemia and solid cancers in France since 1990 and 2000, respectively.
Data available for the cohort Electronically stored patient records from the departments of paediatric cardiology of tertiary hospitals in France are being searched to identify the children to be included. The minimum dataset will comprise: identification of the patient (file number in the centre or service, full name, sex, date and place of birth and characteristics of the CCP (date of the procedure, age, weight, underlying disease, type of procedure, technical details including but not limited to fluoroscopy time and dose area product (DAP)). Follow-up of the children Health status will be followed up by assessments in the future and every five years from 2014 (Figure  1 ). The vital status of each child will be identified by crosslinkage with the national vital status registry (Répertoire National d'Identification des Personnes Physiques (RNIPP)).
Up to age 15, follow-up of cancer incidence will be performed though cross linkage with the paediatric cancer registries (Registre des Tumeurs Solides de l'Enfant (RTSE) and Registre National des Hemopathies de l'Enfant (RNHE)), which since 1990 and 2000, respectively, have recorded all cases of childhood (i. e. , under 15 years old at diagnosis) leukaemia and cancers in France. Above the age of 15 years, follow-up will be based on mortality status as France has no national cancer registry for adult cancers. Follow-up of morbidity through data from the medical insurance system (specifically, the SNII-RAM, an inter-health insurance scheme information system) may be available in the future.
Focusing our study on young children will also allow us to follow them in incidence data for at least 10 years, through the French paediatric cancer registries. Nevertheless, due to the medical context, this population of children is characterised by very good medical follow-up with regular medical visits. Specifically, details regarding the child's health at the time of the CCP will be reliably available from the French hospital discharge summary database (programme de médicalisation des systèmes d'information, PMSI), based upon diagnosis-related groups (DRG)  [41]. This will make it possible to take into account such confounding factors as Down Syndrome, which is known to be associated with both cancer and heart defects. The previous absence of any such cohort in France highlights the novelty of the project at the national level.
Data collection Male participants with and without CHD were examined in the morning after an overnight fast. Patients with stable CHD (cases) were examined in the clinics of the Cardiology Department, Toulouse University Hospital and underwent a coronary angiography. Control subjects were examined in the same health center. The medical examination started with standardized face-to-face interviews performed by a trained physician using standardized methods. During this interview, participants received oral and written information on the aim of the study and signed a consent form. Then a blood sample was taken from each participant. Each participant then completed standardized questionnaires, lasting for about 40 min, covering age, socioeconomic variables, educational level (number of years spent at school), smoking status, alcohol consumption, physical activity, information on cardiovascular risk factors, and past medical (personal and parental) history.
For each quantitative variable, regression analyses were performed with polynomial models to look for possible nonlinear relationships with dependent variables. Lack of multicolinearity for IF1 and HDL-C or apoA-I was assessed by examining the variance infl ation factors in the fi nal models. Interactions between IF1 and other explanatory variables were tested. The specifi c contribution to the model for each explanatory variable was estimated. In the tables, data are presented as percentages for qualitative variables and as means with standard deviations for quantitative ones. The chi-square test was used to compare the distribution of qualitative variables between cases and controls. The mean values of quantitative variables were compared by Student t -test. Shapiro-Wilks was used to test the normality of distribution of residuals and Levene test to test the homogeneity of variances.
43 g/l for HDL-C, and 1. 37 g/l for apoA-I) to test the statistical interaction between IF1 and HDL-C or apoA-I. The Hosmer-Lemeshow chi-square statistic was used to assess model fi t. The performance of the fi nal model was evaluated by analysis of the area under the receiver operating characteristic (ROC) curve (AUC). The internal validity of the prediction model was evaluated by bootstrapping ( 18 ) using 100 random samples. ROC curves were constructed, and models with and without IF1 or HDL-C, separately or in combination, were compared  ( 19 ). Analyses were two-tailed, and P < 0. 05 was considered to be signifi cant. moderate alcohol consumption (<40 g/day) in controls and, conversely, a higher percentage of both abstinent and excessive drinkers ( у 40 g/day) in cases (data not shown).
The future NFS installation will produce high intensity neutron beams from hundreds of keV up to 40 MeV. Taking advantage of this facility, data of particular interest for the nuclear community in view of the development of the fast reactor technology will be measured. The development of an experimental setup called FALSTAFF for a full characterization of actinide fission fragments has been undertaken. Fission fragment isotopic yields and associated neutron multiplicities will be measured as a function of the neutron energy. Based on time-of-flight and residual energy technique, the setup will allow the simultaneous measurement of the complementary fragments velocity and energy. The performances of TOF detectors of FALSTAFF will be presented and expected resolutions for fragment masses and neutron multiplicities, based on realistic simulations, will be shown.
Introduction The advent of the Neutrons For Science (NFS) facility at Caen (France) in 2015 will allow exploring the underexploited fast energy domain in order to provide data for fundamental physics and nuclear technology. On one hand, a lot of information is needed for the development of physics models to reach a complete and precise description of the fission process. On the other hand, the development of fast reactor technology and of reactors dedicated to the incineration of minor actinides shed light on the need of new nuclear data. These arguments have motivated the development of a new detection system called FALSTAFF (Four Arm cLover for the STudy of Actinide Fission Fragments). Based on timeof-flight (TOF) and residual energy technique, FALSTAFF will allow the simultaneous measurement of the complementary fragments nuclear charge, mass and kinetic energy.
Furthermore, scientists challenged this designation of ionized water as inappropriate and being what drinking water is naturally, but without interference. For those reasons, in 1993 the Ministry of Health, Labour and Welfare requested the Association of Alkaline Ionized Water Apparatus to provide scientific data guarantying the quality, efficiency and security of ionized water. This task was undertaken by Professor Itokawa of the Medical Department of Kyoto University who led a review committee and released a public report in 1994 confirming the safety of ionised water. This was followed in 1997 by a further report confirming its effectiveness in the treatment of gastro-intestinal illness. In 1999, at the 25th General Congress of the Japanese Association of Medical Sciences, the report was presented under the title Electrolytic Functional Water in Medical Treatment.
A direct relationship between the presence of bacterial persister cells and the recalcitrant nature of chronic infections has been proposed  [16]. The c-di-GMP metabolism in P. aeruginosa is highly complex: 42 genes containing putative diguanylate cyclases (DGCs) and/or phosphodiesterase are present  [17]. It has been shown that SCVs generated in vitro as well as obtained from clinical isolates contain mutations that upregulate the activity of a specific DGC, i. e. YfiN (also called TpbB  [18] , encoded by the PA1120 gene), suggesting a key role of this enzyme. Since YfiN is the effector protein of a tripartite signaling module YifBNR  [14, 19, 20] , in this work we choose to use the name YfiN for coherence with the other two members of the operon PA1119 and PA1121, which, in the Pseudomonas genome database (http://www.
e. magnesium or manganese). To verify whether c-di-GMP could in any way hamper or negatively affect substrate binding to YfiN HAMP-GGDEF , the GTP binding experiment was also repeated in the presence of an excess of product: no influence of c-di-GMP on the binding affinity of the substrate was observed (Figure  S2  and Table  2 ). Taking these data together we can also exclude an eventual feedback inhibition mechanism involving heterodomain cross-linking. To further verify whether these results could be affected by the truncation of the N-terminal portion of the enzyme, we measured the enzymatic activity of purified YfiN HAMP-GGDEF.
Likewise, Wood and coworkers have shown that in vitro feedback inhibition for fulllength YfiN is observed only at c-di-GMP concentration higher than 200 μM  [18]. Thus, the YfiBNR signaling system appears to be an ON/OFF switch, with the output of the module (i. e. c-di-GMP production) responding only to external stress signals and not to endogenous c-di-GMP levels. It as been shown that the domain architecture of YfiN represents a widespread module to connect periplasmic stimuli to a cytosolic response or vice   [27, 28] ; WspR from P. aeruginosa  [29] ; A1U3W3 from M. aquaeolei  [32]  and XCC4471 from X. campestris  [31]. C) Structure superposition of YfiN GGDEF with the other DGC. YfiN GGDEF (black); PleD from C. crescentus  [27, 28]  (grey -PDB: 2wb4 -rmsd: 1. 23 Å); WspR from P. aeruginosa  [29]  (cyan -PDB: 3i5a -rmsd: 1.
31 Å); XCC4471 from X. campestris  [31]  (light purple -PDB: 3qyy -rmsd: 1. 64 Å) and A1U3W3 from M. aquaeolei  [32]  (dark purple -PDB: 3ign -rmsd: 1. 34 Å). The first row shows the homo-domain cross-linking (GGDEF/GGDEF), while the second shows the hetero-domain cross-linking (within the same chain) of inhibited PleD and two c-di-GMP receptors. For all structures different colors are used to illustrate domains belonging to different subunits, the side chains of the two arginines and the aspartic acid (R1; R2 and D) are shown as sticks, while the two bound c-di-GMP molecules as balls and sticks. Grey continuous lines indicate H-bonds, while green continuous lines highlight the π-cation interaction among a charged nitrogen atom of the arginine residues and the guanine delocalised πsystem. I p and I s indicate primary and secondary inhibitory sites respectively.
Starting from top left, the reported structure are: PleD (PDB: 2v0n  [28] ); WspR (PDB: 3bre  [30] ); A1U3W3 (PDB: 3ign  [32] ); PleD (PDB: 1w25  [27] ); PelD (PDB: 4dn0 )  [33]. and PP4397 (PDB: 3kyf  [34] ). B) Comparison of the I-site of YfiN and (PDB: 2v0n  [28] ). The two subunits of a hypothetical inhibited dimer of YfiN (superposed on the structure of PleD) are shown in white and pink, while the same color code of panel A is used for PleD. C-di-GMP molecules (bound to PleD) are shown as lines. YfiN lacks two of the three arginine residues binding to c-di-GMP through the stair motif interaction (D273 and N351 -bold labels). Moreover, the presence of a bulky side chain (Y379) yields a shift of helix-A, implying a reduced, sub optimal, volume of the I-site. Microcalorimetric titrations of 14 μM enzyme solution with GTP (170 μM in the syringe).
Homology modeling of full-length YfiN To gain insights into the mechanism of allosteric regulation of YfiN and how modifications affecting the periplasmic domain are transmitted into the cytoplasm, homology modeling of the full-length dimeric protein was attempted. Figure  5  shows the predicted domain organization of YfiN along with the most significant structural templates found, according to two different fold prediction servers (i. e. , Phyre2  [25]  and HHPRED  [26] ), and the dimeric model of YfiN. The N-terminal region of YfiN has been previously predicted to fold as a PAS domain, and consequently modeled  [20]  using as structural template the Sensor Kinase CitA binding domain (PDB Code: 1p0z  [40] ). However, the recent finding that the N-terminal domain of the HAMP-GGDEF-EAL protein LapD from P.
fluorescens adopts a novel fold, consisting of a V-shaped, domain-swapped dimer (PDB Code: 3pjv  [24] ) that shows only weak structural similarity to the PAS fold (RMSD ~2. 5 Å), prompted us to investigate further this issue by resubmitting the N-terminal region of YfiN to HHPRED and another fold prediction method, Phyre2  [25]. Consistent with our premise, residues 35-161 of YfiN are predicted to fold as a swapped LapD-like domain with a score and significance (HHPRED: E-value = 5. 1 e-04, score = 53. 05, confidence = 98. 2%; Phyre2: confidence = 97. 2%) higher compared to the Sensor kinase CitA (HHPRED: E-value = 1. 3, score = 33. 59, confidence = 91. 2%). Each arm of this fold consists of two α-helices and two β-strands contributed by one of the two protomers, complemented by two β-strands flanked by helical segments from the other  [24].
As in LapD, the N-and C-terminal helices of the LapD-like domains presumably connect directly to the transmembrane helices (TM2) and the HAMP domains. To model the later domain (residues 182-246) we used as structural template the HAMP domain of the aerotaxis transducer AER2 (PDB Code: 4I3M  [39] ), while transmembrane helices and neighboring positively charged loop regions (residues 11-34; 162-184) were modeled based on Sensor protein QSEC (PDB Code: 2KSE  [41] ), for all alignments see Figure  S3. Finally, the model was connected to the crystal structure of the C-terminal GGDEF domain by modeling the linker region (residues 247-253) on the basis of the template diguanylate cyclase response regulator WspR (PDB Code: 3I5C  [29] ). Following the results of the homology modeling it is likely that the allosteric switch of YfiN resembles that suggested for the LapD receptor  [24].
Therefore, we can speculate that the periplasmic domain of YfiN may not only play a regulatory role, but would also be essential to maintain the enzyme in a dimeric state, allowing the HAMP domains to form a stable four-helices bundle, thus keeping the two GGDEF domains in close proximity. The linker region between the C-terminal GGDEF domain and the stalk helix of the HAMP domain, that we suggest to be crucial in the allosteric regulation, is also highly conserved (residues 249-260: AxHDxLTgLxNR) (Figure  7C ). The importance of this region is confirmed by the deletion mutant ∆255-257, which is inactive and is dominant over the activating substitution G173D  [20]. We have modeled this loop on the basis of the inhibited structure of WspR (PDB Code: 3I5C  [29] ) but, based on the location of the GTP binding site, this conformation would be incompatible with a catalytic encountering of the two GGDEF domains.
e. with the two active sites facing each other). Therefore a severe rearrangement of the linker region (unlocking) must be assumed in order for catalysis to occur. doi: 10. 1371/journal. pone. 0081324. g007 protein concentration of 2 mg/mL in 250 mM NaCl, 10 mM Tris-HCl pH 8. 0, 10% glycerol. Radial absorbance scans were obtained at 280 nm at a spacing of 0. 003 cm with three averages in a continuous scan mode. Sedimentation coefficients were calculated using the software Sedfit  [44]  and were reduced to water and 20 °C (s 20,w ) using standard procedures. Sednterp software (http://sednterp. unh. edu/) was used to calculate the buffer density and viscosity. The sedimentation coefficient (S) of YfiN HAMP-GGDEF was 2. 3 for 98% of the protein, consistent with a molecular mass of 21 kDa, pointing to a monomeric state of YfiN HAMP-GGDEF in solution.
Crystallization -data collection and refinement Crystallization condition for YfiN HAMP-GGDEF were screened using a crystallization robot (Phoenix, Art Robbins), by mixing 300 nL of 3. 7 mg/mL protein solution in 0. 1 M NaCl, 10 mM Tris pH 8 and 2 % glycerol with equal volumes of screen solution. No positive hit was observed during the first three month. After seven month one single hexagonal crystal was observed in the droplet corresponding to solution n. 17 of Crystal-Screen2 (Hampton) containing 0. 1 M Sodium Citrate dehydrate pH 5. 6 and 35% v/v tert-butanol. The crystal was flash frozen in liquid nitrogen, without any cryoprotectant, and diffracted to 2. 77 Å resolution (ESRF, ID 14. 1). Data were processed with XDS  [45]. The crystal belonged to the P6 5 22 space group with the following unit cell constants: a=b=70.
87 Å; c=107. 62 Å. The Matthews coefficient for YfiN HAMP-GGDEF was 1. 38 Å 3 Da -1 with a solvent fraction of 0. 11, pointing to the assumption that only the GGDEF domain (YfiN GGDEF ) was present in the crystal lattice (Matthews coefficient for YfiN GGDEF was 1. 93 Å 3 Da -1 with a solvent fraction of 0. 36). Phases were obtained by molecular replacement using the GGDEF domain of PleD (PDB ID: 2wb4) as template with Molrep  [46]. Cycles of model building and refinement were routinely carried out with Coot  [47]  and Refmac5. 6  [48] , model geometry was assessed by ProCheck  [49]  and MolProbity  [50]. Final statistics for data collection and model building are reported in Table  1. Coordinates have been deposited in the Protein Data Bank (PDB: 4iob).
Homology modeling and in silico analysis The YfiN protein sequence from Pseudomonas aeruginosa was retrieved from the Uniprot database (http:// www. uniprot. org; accession number: Q9I4L5). UniRef50 was used to find sequences closely related to YfiN from the Uniprot database. 123 orthologous sequences displaying a minimum percentage of sequence identity of 50% were obtained. Each sequence was then submitted to PSI-Blast (www. ncbi. nlm. nih. gov/blast; number of iterations, 3; E-Value cutoff, 0. 0001  [52] ), to retrieve orthologous sequences from the NR_PROT_DB database. Sequence fragments, redundancy (>95%) and too distant sequences (<35%) were then removed from the dataset. At the end of this procedure, 53 sequences were retrieved (Figure  S4 ). The conservation of residues and motifs within the YfiN sequences was assessed through a multiple sequence alignment, using the ClustalW tool  [53]  at EBI (http://www.
ebi. ac. uk/clustalw). Secondary structure predictions were performed using several tools available, including DSC  [54]  and PHD  [55] , accessed through NPSA at PBIL (http://npsa-pbil. ibcp. fr/), and Psi-Pred (http://bioinf. cs. ucl. ac. uk/psipred  [56] ). A consensus of the predicted secondary structures was then derived for further analysis. A fold prediction-based approach was utilized to gain some structural insights into the domain organization of YfiN and related proteins. Although three-dimensional modeling performed using such techniques is seldom accurate at the atomic level, the recognition of a correct fold, which takes advantage of the knowledge available in structural databases, is often successful. The programs Phyre2  [25]  and HHPRED  [26]  were used to detect domain organization and to find a suitable template fold for YfiN.
All the programs options were kept at default. A three-dimensional model of YfiN (residues 11-253) was constructed using the MODELLER-8 package  [57] , using as structural templates the following crystal structures: the Nterminal domain of the HAMP/GGDEF/EAL protein LapD from P. fluorescens (residues 35-161; PDB Code: 3pjv  [24] ); the HAMP domain of Aerotaxis transducer AER2 (residues 182-246; PDB Code: 4i3m  [39] ); Sensor protein QSEC (residues 11-34; 162-184; PDB Code: 2kse  [41] ); diguanylate cyclase response regulator WspR (residues 247-253; PDB Code: 3i5c  [29] ). A full YfiN dimeric model was built starting from the crystal structure of the cyclase domain (GGDEF -present work) and performing a backward multi-step homology modeling approach, in which each new predicted domain has been linked to the previously obtained model by following the orientation of its structural template.