dataesr/scientific-paragraphs-categorization huggingface dataset:
EXPERIMENTAL PROCEDURES Preparation of "Native" MUC5B-Fresh whole human saliva (six different donors) was solubilized in 0. 1 M NaCl, 20 mM Tris, pH 7. 4, and native MUC5B mucins were purified by CsCl density gradient centrifugation and Sepharose CL-2B size exclusion chromatography as described previously  (19). Samples of purified native MUC5B mucins were labeled with fluorescein isothiocyanate (FITC) as described previously  (22). Expression and Purification of Recombinant Human MUC5B N-terminal Domains-MUC5B (GenBank TM accession number NM_002458) N-terminal constructs were created consisting of D1-D2-DЈ-D3 (NT5B) (residues 26 -1304) (8), D1 (residues 26 -424), D1-D2 (residues 26 -793), D2-DЈ-D3 (residues 425-1304), and D3 (residues 894 -1304) (see Fig. 3a ). Recombinant proteins were expressed with an N-terminal His 6 tag using the mammalian episomal expression vector pCEP-His in 293-EBNA  (23)  and A549 cells (human lung carcinoma cells).
After 20 h at room temperature, radioactivity was determined in aliquots of the sample and diffusate by scintillation counting. Data were analyzed with GraphPad Prism 5. 0 software, and curves were fitted to a single binding site or multiple binding sites. Inhibition of Calcium-dependent Assembly of Intact MUC5B-Diffusion measurements on MUC5B were obtained from confocal fluorescence recovery after photobleaching experiments performed as described previously  (19, 22). The concentration dependence of MUC5B self-diffusion was determined with FITC-mucin solutions (0. 05-0. 2 mg/ml) in 0. 1 M NaCl, 20 mM Tris, pH 7. 4, with and without 20 mM CaCl 2. The inhibition of MUC5B self-diffusion by polypeptide specific antisera (dilution of 1/50) was determined with FITC-mucin (0. 1 mg/ml) in 0. 1 M NaCl, 20 mM Tris, pH 7.
Analysis was performed using ASTRA version 6 software. Electron Microscopy and Image Analysis-For transmission electron microscopy (TEM) and image analysis, protein samples (ϳ10 -20 g/ml) were negatively stained in 2% (w/v) uranyl acetate. TEM data were recorded on a Tecnai BioTwin at 100 kV under low dose conditions. Images were recorded on a Gatan Orius CCD camera at 3. 5 Å/pixel. All image processing was performed using EMAN2  (26)  on data that were low pass Gaussian-filtered to 20 Å resolution, using strategies described previously  (27). Particles were selected into 72-pixel (NT5B monomer) or 144-pixel (NT5B dimer and D2-DЈ-D3 complexes) boxes using selective swarm parameters in E2Boxer. All datasets contained ϳ5000 unique particles. Following class averaging, preliminary models were generated to assess sym-metry.
The dimer-enriched sample had a clear C2 symmetry, and this was applied to all subsequent processing. Following five rounds of iterative refinement, the resolution was determined using FSC-0. 5 criteria  (26). Hydrodynamic parameters were determined with the HYDROMIC software  (28). Small Angle X-ray Scattering (SAXS)-SAXS data were collected on NT5B protein in 25 mM Tris, 200 mM NaCl, pH 7. 4, at the P12 beam line (Petra-III (Deutsches Elektronen Synchrotron (DESY), Hamburg, Germany)). Data were collected at 10 °C using a European Molecular Biology Laboratory/European Synchrotron Radiation Facility (EMBL/ESRF) new generation automated sample changer. The scattering intensities were recorded using a Pilatus 2M pixel x-ray detector (DECTRIS) with sample-to-detector distance of 3. 1 m (q-range 0.
008 -0. 47 Å Ϫ1 ). The two-dimensional data were integrated and reduced as described previously  (29). Data were analyzed using the ATSAS 2. 5. 1 software (EMBL Hamburg). An average model was produced from 10 ab initio structures using the DAMAVER software  (30). Hydrodynamic parameters for the models were determined using HYDROPRO version 7. C  (31). Analytical Ultracentrifugation-The sedimentation coefficients of NT5B incubated in 5 mM CaCl 2 or 5 mM EGTA at pH 7. 4, pH 6, or pH 5 were determined from velocity experiments using the Optima XL-A ultracentrifuge (Beckman Instruments). Samples (n ϭ 3) were centrifuged in a double sector cell at 35,000 rpm, taking 200 scans at 1. 5-min intervals at 280 nm, at 20 °C. Sedimentation coefficients were determined using SedFit version 13. 0b  (32).
5 ϫ 7 nm. The structure visualized from the dimerenriched NT5B sample was approximately twice the size of the monomer with dimensions 24 ϫ 17 ϫ 9 nm. The dimer also had an extended, boomerang-like shape, but with a more pronounced central region (Fig. 5, c  and e ). To confirm that the D3-domain was located centrally within the dimer, a construct (D2-DЈ-D3) lacking the D3-domain was analyzed (Fig. 6 ), and this also had a boomerang shape. Together these data support the model that dimerization of NT5B is mediated by disulfide links between the D3-domains and these form the junction between monomers in the TEM dimer image. The HYDROMIC software (28) was utilized to calculate the hydrodynamic properties of the TEM monomer and dimer structures, and these predicted parameters showed good agreement with the values determined experimentally by sedimentation velocity analysis (AUC) (Table  1 ).
SAXS data were collected for dimer-enriched samples of NT5B at ϳ10 mg/ml concentration at the synchrotron radiation source, Petra III. The radius of gyration (R g ) for the dimer obtained from the Guinier plot was 7. 7 nm (Fig. 7 ), and the maximum particle dimension was estimated at 26. 6 nm using GNOM (35) (data not shown). Ab initio bead models were generated using the DAMMIN program  (36). Ten simulations of DAMMIN were computed to determine the common structural features and averaged to calculate the threedimensional structure using the DAMAVER software (30) (Fig. 5d ). The SAXS model generated, with dimensions 26 ϫ 11 ϫ 9 nm, closely resembled the structure observed in TEM (Fig. 5c ). The theoretical sedimentation properties of the SAXS structure were calculated using the HYDROPRO software  (31) , and the predicted values were also compared with those determined experimentally (Table  1 ).
General Reagents used for synthesis were purchased from Aldrich, Fluka and Merck; organic solvents were purchased from Merck. Melting points were recorded with a Stuart SMP10 instrument. IR spectra were recorded from 4,000 to 650 cm -1 with a Perkin-Elmer Spectrum 100 instrument by ATR (Attenuated Total Reflectance) technique on a CdSe crystal. 1 H-NMR, COSY and 13 C-NMR spectra were recorded with a Bruker 400 Ultrashield spectrometer (at 400 MHz for 1 H-NMR and at 100 MHz for 13 C-NMR) operating at room temperature, using DMSO-d 6 as the solvent and TMS as the internal standard. Abbreviations for the data quoted are: s, singlet; d, doublet; t, triplet; q, quartet; dd, doublet of doublets; ddd, doublet of doublet of doublets; m, multiplet. The electrospray ionization (ESI) mass spectra were measured on a Thermo Scientific HPLC/MSQ Plus.
Synthesis Experimental details for the synthetic procedures and analytical data and spectra of the pyridinium salts are described. The corresponding bis-pyridine (1 or 2) (2 mmol) and halide derivatives (4. 4 mmol) were refluxed in acetonitrile (20 mL) for 10 to 24 h. The mixture was cooled to room temperature. The solvent was removed by filtration, and the solid thus obtained was washed with hot acetonitrile. The compounds showed high purity, as assessed by spectroscopic and elemental analyses, and were used without further purification.
The alternative assignment possibilities for this peak   S1  (see the Supporting Information). Automatic structure calculation was conducted using, in addition to the information from the manual calculation, automatically picked peak lists from the CHHC, PAR, PDSD, and two PAIN spectra (Table  S2 ) for iterative assignment by CYANA (Table  S2 ). This procedure yielded the structure shown in Figure  4. The quaternary structure of the fibril is defined by two interlaced protofilaments and resembles a cinnamon roll. Figure  4  b displays the NMR bundle representing the 20 lowest-energy structures. The structure is deposited in the PDB database with ID 2mvx, the chemical shifts in the BMRB with ID 25289. The cross section of the fibril can be approximated by a rectangle that is closed by intermolecular salt bridges between the Glu3 and Lys28 side chains.
We thank  A. Däpp  and  A. Hunkeler  for support,  M. Ernst  for expert advice,  Beth Lin  for help with STEM, and the  ETH-EMEZ  for TEM. This work was supported by the  Swiss National Science Foundation SNF  (grant  200020_134681 ,  200020_146757 ), the  CNRS  ( ANR-12-BS08-0013-01 ,  ANR-11-BSV8-021-01 ), the " NCCR Neural Plasticity and Repair" program  of the SNF. P. G. is supported by the  Lichtenberg program  of the VW Foundation. Supporting information for this article is available on the WWW under http://dx. doi. org/10. 1002/anie. 201408598.
This suggested that a decrease in the intracellular K + concentration affects the protein folding state as an important temperature elevation. We concluded that, even a moderate drop in extracellular salt conditions represents a major stressor for halophilic cells (Ms in preparation). The biophysical experiments suggested that cellular responses must exist to protect the halophilic proteomes against the deleterious effects of salt deprivation. Comparative genomic analysis revealed a common unique halophilic protein core of 800 proteins and indicated that a third of the genes encode for proteins with no significant matches in to the databases  (59). In H. salinarum, whole genome DNA microarray experiments showed that a moderate decrease in salt concentration modifies the expression of genes encoding for potassium and phosphate transporters as well as peptide transporters  (23).
Gene expression studies indicated that the heat shock promoter of the thermosome is also strongly salt regulated, suggesting that the low salt and the heat and salt stressors use similar, if not identical, transcriptional regulators. A novel type of chaperonin complex called Ssp45 was also identified  (24). The 450-kDa complex is a ring shaped molecular edifice comprising about 10 subunits. The complex displays Mg 2+ dependent ATPase activity that is strongly stimulated by the presence of K + ions. In vitro, it binds to proteins in low salt conditions and slows down their unfolding. The protein is rapidly accumulated the halophilic cells shortly after exposure to a lower salt concentration. Interestingly, searches in databases did not allow the identification of SsP45 homologues in nonhalophilic archaeal strains.
Such combination is associated with the functional integration of an electrochemical microelectrode and a pH-ChemFET on a single chip, leading to the realization of a pH-ChemFET based coulometric sensor-actuator system  [15]  also known as electrochemical field effect transistor (ElecFET)  [19]. In parallel with the technological development of pH-ChemFET based microdevices, modelling investigations were also conducted. Based on the site-binding theory  [20, 21] , such studies led to the development of complete behavioural models using SPICE  [22] , MATHEMATICA  [23]  or VHDL-AMS  [24]  softwares. From a general point of view, these different models focus on the study of electrolyte/insulator/semiconductor capacitive structures while taking into account the FET electrical behaviour due to well-known current-voltages equations  [24, 25].
Beyond the pH measurement, it is necessary to consider other phenomena occurring in liquid phase such as diffusion, migration, acid/basic chemical reactions, enzymatic biochemical reactions,. This was performed for EnFET microsensors  [26, 27]  as well as for pH-ChemFET-based coulometric sensor-actuator system  [28, 29]. Nevertheless, such modelling efforts have to be carried out in order to completely understand the ElecFET detection/transduction principles. In this paper, we report modelling of ElecFET microdevices in the frame of water electrolysis and hydrogen peroxide oxidation using the MATLAB™ software, studying main influential parameters (polarization voltage and time as well as integration level) while dealing with impulsional pH variations in microvolume and H 2 O 2 detection.
Modelling of Diffusion Phenomena in Watery Phase The diffusion model was adapted from a previous one developed for the EnFET-based microsensors and based on a finite element model implemented in MATLAB™ software  [26, 27]. It is associated with Fick's diffusion equation, assuming a one-dimensional model in spherical coordinates (Figure  1 ). The variable parameter is therefore the radius of the sphere r: C(r,t) t  D 1 r 2  r r 2 C(r,t) r       G ( 16 ) where C(r,t) describes the concentration of H 3 O + or OH -ion for the studied case, D is the associated diffusion coefficient and G represents the chemical species generation according to the associated electrochemical reaction. As a result, for the different studied cases, Equation  (11)  gives: H 2 O oxidation (V P > E 0+ ): [H 3 O  ](r,t) t  D H 3 O  1 r 2  r r 2 [H 3 O  ](r,t) r          G  (17) H 2 O reduction (V P < E 0-): [OH  ](r,t) t  D OH  1 r 2  r r 2 [OH  ](r,t) r          G  (18) H 2 O 2 oxidation (V P > E 1+ ): [H 3 O  ](r,t) t  D H 3 O  1 r 2  r r 2 [H 3 O  ](r,t) r          G 1 (19) In order to solve diffusion equations, the following initial and boundaries conditions were chosen: Thus, initial conditions assume spatially uniform concentrations of water-based ions and boundary conditions assume that no flux goes through the physical barrier of the sensor surface (r = 0) or far from it (r = r max = 3 cm).
Conclusions Using MATLAB™ software, we have investigated the modelling of the ElecFET microdevice in the case of water electrolysis and hydrogen peroxide oxidation, taking into account chemical and electrochemical and acid/basic reactions in water phase as well as diffusion phenomena of water-based ions. In the first case, results show that the ElecFET phenomena depend strongly on the polarization parameters on the microelectrode (voltage V P and time t P ) as well as on dimensional characteristics related to the ElecFET functional integration (distance between the microelectrode and the pH-ChemFET gate sensitive gate area d). On one hand, according to the polarization sign, oxidation and reduction reactions of water are responsible for impulsional pH variations localized at the microscale (typical dimension: 1 mm and less).
When an Ax-NiR-A647N molecule was trapped it was possible to observe its turning-over during many cycles for several seconds. Different from the Af-NiR-A655 experiment (vide supra), the oxidized and reduced levels could be easily distinguished (Figure  7 ). As in the previous study, no single kinetic behavior was observed, pointing again to heterogeneity in the NiR population. This time the better time resolved data allowed a more sophisticated analysis. The dwell times in the reduced and oxidized states were analyzed by means of a bin-free state identification procedure. This comprised first the application of an intensity-change-point-finding algorithm as a smart low-pass filter directly on time-tagged data  [34]. This was followed by applying an intensity thresholding algorithm to identify the states.
The mean and the spread of the activation energies amounted to 0. 347 eV and 0. 028 eV, respectively. It is gratifying to note that the catalytic rate is very different for high (5 mM DMPD) or low (50 μM DMPD) substrate concentrations but that the k on distribution is independent of substrate concentration (not shown). This confirms that we are dealing with an intramolecular process, i. e. , ET from T1 to TNC. 11a. The number of "on" intervals present in this trace amounts to 2767. The red line is the monoexponential fit to the normalized data with a decay constant (k on ) of 660 s -1 ; (b) Distribution of k on obtained from ~720 molecules of SLAC. The green line is the fit corresponding to a lognormal distribution with a mean value of 450 s -1. The measurements reported in Figures  11  and 12a  were made in 20 mM MOPS buffer (pH 7.
4) and at 20 °C with DMPD and ascorbate concentrations of 5 mM and 10 mM, respectively. The data reported in panel (b) represent measurements that were performed at concentrations of DMPD varying from 0. 02 to 5 mM. Reprinted with permission from  [43]. Copyright 2014 The American Chemical Society. The off-times were analysed in a similar fashion. According to Scheme 3, k off is the sum of two rates: ET from TNC to T1 and a substrate concentration dependent second order rate constant (k s ). At low substrate concentrations (≤50 μM, for example) k off approaches the rate of back ET from TNC to T1. It should be kept in mind that the mechanism presented in Scheme 3 is possibly a simplification. The ET steps might be part of a more complex mechanism and may include other intermediates not shown in this scheme.
The Agence Nationale pour la Recherche (ANR-11-BS07-0014), the Direction Generale de l'Armement (DGA), the Region PACA, the Centre National de la Recherche Scientifique (CNRS) and the Aix-Marseille Universiteare gratefully acknowledged for financial support. We also thank Dr N. Vanthuyne and M. Jean (ee measurements), and Dr M. Giorgi (X-ray diffraction analysis).
Measurement of body composition and adipose tissue distribution The determination of body fat and lean body mass was performed by dual-energy X-ray absorptiometry (DEXA) using a Hologic QDR-2000 densitometer and the enhanced array whole-body software V5. 73A (Hologic, Bedford, MA). Regional adipose tissue distribution was measured by computed tomography (CT) as previously described  ( 14, 17 )  using a GE Light Speed 1. 1 CT scanner (General Electric Medical Systems, Milwaukee, WI). Briefl y, the cross-sectional scan was performed at the L4-L5 vertebrae level in supine position with arms over the head. The exact scanning position was determined using a scout image. Adipose tissue areas of interest including visceral and subcutaneous adipose tissue areas, the latter included superfi cial and deep subcutaneous adipose tissues, were highlighted and computed with attenuation ranging from Ϫ 190 to Ϫ 30 Hounsfi eld units with ImageJ 1.
Dietary CoQ10 consumption and smoking status Using a food frequency questionnaire, we found that women included in our study consumed an average of 4. 6 mg of CoQ10 per day with a range from 2. 0 to 8. 0 mg/day. BMI of the volunteers did not infl uence their daily consumption of CoQ10 from diet (supplementary Fig. 1A ). We also found that vegetal sources (oils, nuts, vegetables, and fruits) were the main sources of CoQ10 in this French Canadian population (supplementary Fig. 1C ). In this study, CoQ10 consumption did not infl uence the total levels and redox state of this molecule in the omental (supplementary Fig. 2A-C ) or the subcutaneous (supplementary Fig. 2 B-D ) adipose tissue compartment. Only four volunteers were smokers and were distributed among BMI subgroups. We did not observe any specifi c pattern of CoQ10 content or redox state in adipose tissues of these individuals (data not shown).
Regional variation of CoQ10 in obesity We were able to quantitatively assess the levels of CoQ10 ox and CoQ10 red in 24 omental and 22 subcutaneous samples. We excluded data from fi ve omental (overweight, n = 3; obese, n = 2) and seven subcutaneous (lean, n = 2; overweight, n = 4; obese, n = 1) samples because of complete oxidation of the CoQ10 red isoform during the extraction process. We considered the CoQ10 ox levels as the CoQ10 tot pool for these samples. However, only women with available data of CoQ10 ox , CoQ10 red , and CoQ10 tot within the same depot were included in this set of analysis. We fi rst analyzed the regional variation of CoQ10 content in lean, overweight, or obese patients. We did not observe a difference in CoQ10 tot content between the omental and subcutaneous adipose tissue of women within the same BMI category ( Fig.
The difference between the work we showcase in this paper and our previous work  [3]  is basically in the application part, the used RQA parameters and the mode of evaluating the discrimination. In Zaylaa et al. [2, 3]  we have validated URPs on the logistic map and a single healthy and a single distressed fetuses. This paper demonstrates the application of URPs to a larger database composed of 50 FHRs (25 H-FHRs and 25 IUGR-FHRs). It also investigates the performance of additional RQA parameters including the unbiased recurrence rate (RR) and unbiased En measurements in the discrimination between healthy and distressed FHRs. This study aims also to provide the discriminative power using Cohen's kappa coefficient scores. The entropy parameter is introduced and computed from RPs to compare its performance in detecting IUGR.
This interaction modifies the transmitted frequency of the pulse. The frequency content of the backscattered signal carries the heart signature when recorded from a volume containing the fetus heart. Doppler signals are processed numerically and FHR datasets are estimated, however, the estimation is beyond the scope of this work and result from the methods discussed in  [15, 16]. Our database includes 50 FHR strips collected by MCDUS from 50 pregnant women. The women were in their third trimester and the average fetal age of the entire database was 29 ± 1 week. Recordings were obtained at Bretonneau Hospital (CHRU) in Tours, France. The consent of each patient was obtained and the study was approved by the ethical committee of the Clinical Investigation Center for Innovative Technology of Tours (CIC-IT 806 CHRU of Tours).
Relative error and standard deviation: To evaluate the performance of diagnosis or discrimination of the fetus medical state while taking the full advantage of the nonlinearity of FHR time series, both the absolute Relative Separation/Error (RE) and the Standard Deviation (SD) were calculated as in  [34]. The absolute RE is given as: ( ) ( ) ( ) % ( ) 100 H FHR D FHR i i i H FHR i RQA RQA RE RQA RQA - - -   -   = ×     (7) where i={1,. , 5} and RQA's are DET, CDET, PRSPs, RR and En. A null absolute RE, i. e. 0% relative difference between the healthy and IUGRfetuses datasets, signifies that the two sets are not classified. In contrary, a 100% absolute RE signifies that the two sets are ideally classified. SD that measures the amount of RQA i dispersion from its average value is given as follows: ( ) 2 ( ) ( ) 1 1 ( ) - - = = ± - ∑ N H FHR D FHR i i i i SD RQA RQA RQA N (8) where N is the total number of FHRs used.
Therefore, RR and DET parameters are both less effective than CDET. The non-negligible values of the SD (En) and SD (PRSPs) (see Table  3 ) reveal that these two indicators are sensitive to the fluctuations of data, thus they might be useful in the extraction of other types of complexities. However, the RQA parameters revealing the highest RS values and the lowest SD values are the utmost parameters to discrimination healthy from distressed FHR cases. The latter information was fulfilled by the use of the CDET quantification parameter. Of all the SD (RQA) values, SD (PRSP) was the highest and SD (DET) the lowest, thereby, DET data are less dispersed. Moreover, while comparing PRSP to DET we noticed that the sensitivity was 60% higher for DET than for PRSP, however the specificity was 60% lower for PRSPs than for DET.
However, the accuracy and the precision were similar 50%. Of all RQA, CDET followed by RR were the utmost parameters to discriminate healthy from Intrauterine Growth Restricted fetuses. In addition, CDET served as the ultimate generic marker for fetal distress caused by IUGR. Although RR quantitative parameter values were in general small (Figure  6  (d)), a higher RR parameter characterized H-FHRs compared to RR of D-FHRs. Moreover, H-FHRs were more irregular than D-FHRs (Figure  6  (e)). The former result still emphasizes the fact that healthy biomedical signals, i. e. H-FHRs, are highly complex in nature  [36]. Unlike the previous work  [3] , this paper enriches FHR analysis by detecting IUGR fetuses from the used FHR dataset, it showcases also a sample of URPs and RPs of one (healthy, IUGR)-FHR couple out of the 50 studied FHRs.