dataesr/scientific-paragraphs-categorization huggingface dataset:
1% for 20 of the 21 compounds considered. For sake of comparison with gold standard in feature annotation in metabolomics, collisional cross section are among the most reproducible parameters with interlaboratory variation in the range of 2%  36, 41, 53  and 5% and are usually the threshold for identification confirmation. 6, 54 Although HILIC is a powerful method to separate polar compounds, deviation of the retention time up to 10% to in-house databases are usually considered for feature annotation. 6 s a first approach, we propose that such a scoring system can be based on different ranges of bias between μ eff measurements and μ eff values in databases (Table  1 ). Such databases should be built on a reliable manner, taking into consideration multiple technical replicates, performed in multiple laboratories, and involving different instruments.
Using 10% acetic acid as the BGE, the deviation to the consensus value below 10% was easily achieved for most metabolites in complex biological matrices. By using a system suitability test based on a short panel of compounds with different migration speeds, we envision it possible to test the BGE and assess whether it is performing conformed to the database. For example, our data here exemplified μ eff measurements with a bias below 5%, thus provided an added piece of information to credential compounds and aid identifications (Table  1 ). Further, credentialing may consider electrophoretic migration for added fidelity. As the mobility of slow-migrating compounds is more dependent on the differences of physicochemical properties of the BGE, conversion to μ eff overestimates relative bias and reproducibility.
■ CONCLUSIONS This study encompassing 13 laboratories and 16 platforms spanning 11 countries and 2 continents found CE-MS a robust and reproducible technology for metabolomics. Despite major variations in experimental conditions, CE instruments and methods, CE-ESI ion sources, and even users, conversion of migration times into μ eff reduced variability from 10. 9% on RMT to 3. 1% in the μ eff scale using the same BGE composition. Tabulating μ eff under specific BGE compositions into universal database adds another compound-dependent and reliable value, thus complementing traditional MS-MS/MS databases in metabolomics (e. g. , HMDB  55  and Metlin  56  ). The use of μ eff requires only a limited number of internal standards (e. g. , two different compounds used here) while substantially enhancing compound identification in metabolomics via a targeted or untargeted approach.
■ ACKNOWLEDGMENTS The  Vidi grant scheme of The Netherlands Organization of Scientific Research  ( NWO Vidi 723. 016. 003 ) is acknowledged for the financial support of a part of this Metabo-ring study and for the financial support of M. v. M. and W. Z. N. D. acknowledges the financial support from  Horizon 2020 Marie Sklodowska-Curie CO-FUND  (Grant Agreement no:  707404 ). P. N. acknowledges support from the  National Science Foundation  (award  IOS-1832968 ), the  National Institute of Health  ( R35GM124755 ), and the  Arnold and Mabel Beckman Foundation  ( Young Investigator Grant ). A. J. C. , I. L. , and J. A. T. acknowledge the  European Commission via Horizon 2020  project  ACEnano  (Grant  H2020-NMBP-2016-720952 ). P. B. -M. acknowledges funding from the  Natural Sciences and Engineering Research Council of Canada and Genome Canada.
M. S. and A. G. gratefully acknowledge the grants of the  National Research, Development and Innovation Office  ( NN127062 ,  2018-2. 1. 17-TÉT-KR-2018-00010 ). This work was also sponsored by the  BIONANO_GINOP-2. 3. 2-15-2016-00017project. This is contribution # 173  from the  Horvath Csaba Memorial Laboratory of Bioseparation Sciences. A. L. would like to acknowledge the  CNRS  ( UMR 7140 ),  University of Strasbourg. G. A. H. D. B. , C. C. , and R. N. would like to thank the  Reǵion Centre Val de Loire  and the  Labex SynOrg  ( ANR-11-LABX-0029 ) for financial support. A ́. L. G. and C. B. acknowledge the  Ministry of Science, Innovation and Universities of Spain and FEDER funds (MICINN)  (ref. RTI2018-095166-B-I00 ), and the  Autonomous Community of Madrid (NOVELREN-CM. ref:  B2017/BMD3751 ).
, 2019)   (Shehata et al. , 2015). The characterization of the solutes by 13 C NMR spectroscopy may be carried out on extracts or on fractions obtained by chromatographic methods. It may happen that fractions of interest also contain an important amount of these high boiling point solvents. The presence of high intensity resonances from solvents is not a problem in 13 C NMR spectroscopy most of times since their resonance lines are very sharp. However, NMR data acquisition of series of samples is often achieved in automation mode and standard acquisition parameters are used for this purpose. Since 13 C 1 H spectra are recorded, the calibration of pulses is necessary on the 1 H channel for proper decoupling. Decoupling pulse miscalibration may cause decoupling artifacts around the intense solvent signals to, at a point their intensity is comparable to the one of the signals of interest  (Blechta and Schraml, 2015).
The action of relaxation on frequency-domain profiles of BURP pulses were recalculated using exact solutions of the Bloch equations and the results were visually identical to those derived from the approximate treatment  (Canet et al. , 1994). The simulation computer source code was written in C language; it relied on the libxml2 library for the reading of the input data file (this may be an overkill for such a task, admittedly) and on the libsimu1 library for the calculation of rotation matrices by means of Eqn. (4), as programmed for the design of SLURP pulses. The libsimu1 archive file also contains a proof of Eqn. (4). The computer code for saturation simulations is available from GitHub; its installation was tested with Cygwin under Windows 10 but should be easily carried out on any other platform that provides a C compiler and UNIX-like tools.
2 g L -1 of deuterated fucose from a limited amount of glycerol in a simple batchfermentation. The fully deuterated fucose was characterized by mass spectrometry, proton and deuterium NMR, confirming full deuteration of the final product. It should be noted that the final yield of both the hydrogenated and the perdeuterated monosaccharides in this study was strongly dependent on the amount of glycerol used during the fermentation process. Due to the cost of the deuterated carbon source, this amount was limited to 45 g in both the H-and the D-study. Under optimal hydrogenated conditions where the quantity of carbon source is not limited, the highest titer of fucose obtained was 20 g L -1 (data not shown). Perdeuteration using engineered E. coli is therefore a convenient and effective method for a high-quantity production of fully deuterated simple and more complex sugars for use in neutron scattering experiments as well as in pharmacokinetic studies.
Structural analysis of deuterated fucose Positive and negative-ion ESI mass spectrometry data were recorded on the Bruker amaZon speed ion-trap mass spectrometer. A sample of deuterated fucose was solubilized in D2O to a final concentration of 50 μM. The proton and deuterium NMR spectra were recorded with a Bruker Avance™ III NMR spectrometer operating at a frequency of 400. 13 MHz for 1 H and 61. 42 MHz for 2 H. For the 1 H NMR experiments, samples of hydrogenated and deuterated fucose were solubilized in D2O with 1. 82 g L -1 sodium succinate as a standard. Residual signal of the solvent was used as the internal standard: HOD at 4. 8 ppm at 298 K. The 1 H spectra were recorded at 298 K, with a 4006 Hz spectral width, 32 768 data points, 4. 096 s acquisition times, 10 s relaxation delays and 16 scans.
The 2 H NMR spectrum was measured on a sample of 7 mg of deuterated fucose dissolved in H2O at pH 6. 7. The 2 H spectrum was acquired at 298 K, without broadband 2 H-decoupling, using a 90° pulse, 10 015 Hz sweep width, 3030 number of data points, 1 s acquisition time and 1024 number of scans.
Acknowledgements We thank the  ILL  for the provision of studentship funding to LG, and for the award of neutron beamtime. We also thank the  ILL  for access to the  Deuteration Laboratory platform in ILL's Life Sciences Group  (https://www. ill. eu/lsg). We would like to thank the  CERMAV Common Chromatography Service  ( SC3 ) platform, especially  Laurine Buon  for help with the fucose purification, and the  Chimie Nanobio Joint Technology Platform of the Institute of Molecular Chemistry of Grenoble (PCN-ICMG)  for mass spectrometry and NMR measurements. VTF wishes to acknowledge the  UK Engineering and Physical Sciences Research Council (EPSRC)  for grants  GR/R99393/01  and  EP/C015452/1  that funded the creation of the  Deuteration Laboratory within ILL's Life Sciences Group. AI wishes to acknowledge the support of  French ANR  through  Glyco@Alps  ( ANR-15-IDEX-02 ) and  Labex ARCANE / CBH-EUR - GS  ( ANR-17-EURE-0003 ).
Among fcc-structured alloys, only fcc-Ir 0. 42 Rh 0. 58 has been investigated up to 57 GPa at room temperature  [5]. In the current study, we report synthesis of fcc-Ir 0. 50 Pt 0. 50 , fcc-Rh 0. 66 Pt 0. Investigation of fcc-Ir 0. 50 Pt 0. 50 , fcc-Rh 0. 66 Pt 0. 33 and fcc-Rh 0. 50 Pd 0. 50 binary alloys under hydrostatic compression up to 50 GPa in diamond anvil cells allow us to obtain bulk moduli for fcc-structured binary alloys. Equations of state, thermal expansion and pressure compressibility for known refractory high-entropy alloys can be validated with experimental data obtained for fcc-structured refractory binaries. [13]  He flow, 460 ] was performed on a Q-1000 TG device. Powders (ca. 0. 1 g) were heated in Pt crucibles closed with a lead. Heating (5 K/min) was performed in helium flow (150 mL/min).
50Pt0. 50, fcc-Rh0. 66Pt0. 33 and fcc-Rh0. 50Pd0. 50 binary alloys were collected at the ID15B beamline up to 40 GPa (ESRF, λ = 0. 411235 Å, MAR 555 flat panel detector, beam size 10(v) × 10(h) μm 2 ). The samples were loaded in diamond anvil cells equipped with conically supported Boehler Almax anvils 250 μm culet sizes. He was used as a pressure transmitting medium. Ruby was applied as a pressure calibrant. The diffraction data were integrated using DIOPTAS  [17]. The unit cell parameters, the background and the line-profile parameters were refined simultaneously using JANA2006 software  [18]. The P-V data were fitted using EoS-Fit 5. 2 software  [19]. The X-ray diffraction study of [Ir(NH3)5Cl][PtBr6] single crystal at 150 K was performed on an automated Bruker APEX-II CCD diffractometer (MoKα radiation, graphite monochromator, twodimensional CCD detector, Bruker Corporation, Karlsruhe, Germany).
One hundred and fifty nine structural parameters with 48 restrains were refined and 4159 reflexes were used. The corresponding divergence factors were Rall = 9. 07% and wRref = 15. 41%; for 3150 reflections with I ≥ 2σ(I), Rgt = 6. 28%, wRgt = 14. 33% and the S factor against F2 was 1. 066. X-ray crystallographic data were deposited with an Inorganic Crystal Structure Database (ICSD) under No. 1971298. Phase composition and cell parameters of metallic alloys were obtained by in house powder X-ray diffraction (PXRD) using an ARL X'TRA diffractometer (CuKα-radiation, Ni-filter, position sensitive detectors, Bragg-Brentano reflection geometry, 2Θ = 5-100 • , ∆2Θ = 0. 03 • , 10 s/step, room temperature, Thermo Electron Corporation, Waltham, MA, USA). Polycrystalline samples were slightly ground with hexane using an agate mortar, and the resulting suspensions were deposited on the polished side of a quartz sample holder, a smooth thin layer formed after drying.
So, fcc-Ir 0. 509(5) Pt 0. 491  (5)  correspond to fcc-Ir 0. 50 Pt 0. 50 (sample A); fcc-Rh 0. 657(4) Pt 0. 343(4) correspond to fcc-Rh 0. 66 Pt 0. 33 (sample B); and fcc-Rh 0. 497(5) Pd 0. 502(5) correspond to fcc-Rh 0. 50 Pd 0. 50 (sample C). Room temperature compressibility curves for fcc-Ir 0. 50 Pt 0. 50 , fcc-Rh 0. 66 Pt 0. 33 and fcc-Rh 0. 50 Pd 0. 50 binary alloys were collected at the ID15B beamline up to 40 GPa (ESRF, λ = 0. 411235 Å, MAR 555 flat panel detector, beam size 10(v) × 10(h) µm 2 ). The samples were loaded in diamond anvil cells equipped with conically supported Boehler Almax anvils 250 µm culet sizes. He was used as a pressure transmitting medium. Ruby was applied as a pressure calibrant. The diffraction data were integrated using DIOPTAS  [17]. The unit cell parameters, the background and the line-profile parameters were refined simultaneously using JANA2006 software  [18].
The P-V data were fitted using EoS-Fit 5. 2 software  [19]. The X-ray diffraction study of [Ir(NH 3 ) 5 Cl][PtBr 6 ] single crystal at 150 K was performed on an automated Bruker APEX-II CCD diffractometer (MoKα radiation, graphite monochromator, two-dimensional CCD detector, Bruker Corporation, Karlsruhe, Germany). One hundred and fifty nine structural parameters with 48 restrains were refined and 4159 reflexes were used. The corresponding divergence factors were R all = 9. 07% and wR ref = 15. 41%; for 3150 reflections with I ≥ 2σ(I), R gt = 6. 28%, wR gt = 14. 33% and the S factor against F 2 was 1. 066. X-ray crystallographic data were deposited with an Inorganic Crystal Structure Database (ICSD) under No. 1971298. ] and also previously structurally characterized by X-ray diffraction as single crystals (Table  2 ).
Nevertheless, monoclinic angle β was close to 90 •. [Ir(NH 3 ) 5 Cl][PtBr 6 ] had the same crystal structure as [Rh(NH 3 ) 5 Cl][PtBr 6 ] with a monoclinic angle much closer to 90 •. Due to the monoclinic angle, all selected single crystals were twinned by 180 • rotation around the c axis and might be indexed as orthorhombic. Diffraction reflections were much blurrier at higher angles. Nevertheless, its crystal structure was not orthorhombic and did not show higher symmetry. Tests for higher possible symmetry did not give positive results. The corresponding dataset for [Ir(NH 3 ) 5 Cl][PtBr 6 ] was collected and integrated in the orthorhombic crystal system and later refined as a two component twin with 0. 528/0. 472 twin fractions. The real value of the monoclinic angle was approximately 90.
According to Table  3 , structural parameters (atomic volume and bulk moduli) for all alloys can be estimated quite well using simple models typical for ideal solid solutions. Such a finding can be used for a prediction of the compressibility of new alloys to be able to construct a complete thermodynamic database for refractory fcc-alloys. Palladium shows relatively high compressibility in the comparison with the other platinum group metals. As a result, the fcc-Rh0. 50Pd0. 50 alloy had the highest compressibility among other alloys. At the same time its compressibility had the better accordance with the ideal solution model (Equation (  2 )). A similar good satisfaction between experimentally obtained data and predicted according to Equation (2) were found for the fcc-Ir0. 42Rh0. 58 alloy.
Such a finding can be used for a prediction of the compressibility of new alloys to be able to construct a complete thermodynamic database for refractory fcc-alloys. Palladium shows relatively high compressibility in the comparison with the other platinum group metals. As a result, the fcc-Rh 0. 50 Pd 0. 50 alloy had the highest compressibility among other alloys. At the same time its compressibility had the better accordance with the ideal solution model (Equation (2)). A similar good satisfaction between experimentally obtained data and predicted according to Equation (2) were found for the fcc-Ir 0. 42 Rh 0. 58 alloy. Both investigated platinum alloys fcc-Ir 0. 50 Pt 0. 50 and fcc-Pt 0. 33 Rh 0. 67 show large deviations from predicted values. A larger value for fcc-Ir 0. 50 Pt 0. 50 can be explained by relatively low experimental pressure.
laser sources, spectral resolution). Subtle differences in the Raman setup can degrade the reproducibility of the Raman spectroscopic signals, which makes it almost impossible to quantitatively compare measurements from different setups, and this is highly detrimental to crosssetup data analysis. The setup-dependence is very likely to have a larger influence in biological applications in which the spectral contributions of interest can be very subtle in the acquired Raman signal and thus are more easily masked. If Raman spectroscopy is expected to be utilized in, e. g. , clinical scenarios, it is likely that one or more 'primary' setups hold a large database of Raman spectral characteristics of, e. g. , some disease states. Other Raman setups in different laboratories act as 'replicate' setups and send data to the 'primary' setup for testing against this 'primary' model/database.
If the Raman setups are significantly different, these statistical models are likely to fail to correctly predict the newly measured samples on the 'replicate' setups. Building up individual statistical models for each setup could be a solution to this problem, but this is not likely to be acceptable in real-world scenarios, as the models would also be setupdependent and this would further hamper the generalization of Raman spectroscopy. A more feasible and attractive approach is to remove the setup-induced spectral variations from the spectral 'database'. This is the task of pre-processing in general. 1] [22]  Spectrometer calibration corrects for the influence of a setup on the Raman signals by retrieving the correct values from the measurements of known standard materials. In many cases, an interpolation is needed to deal with the different nominal spectral resolutions of different setups.
e. , pixel size), and optical configurations ranging from highly confocal to fibreoptic probes (and hence different numerical apertures). We note that, of course, there can be spectral differences due to resonance excitation, and therefore, for the present study, we have chosen Raman setups and samples absent of resonance Raman contributions. In the end, data from 35 setups of 15 institutes were returned to a single laboratory for unified data processing and assessments. The comparability of the setups was evaluated from the perspectives of the peak positions, peak intensities, peak widths, and noise levels. We report these differences and provide recommendations for future cross-laboratory studies. Ultimately, the translation of Raman spectroscopy as a bioanalytical protocol to clinical applications will require regulatory certification, as per, for example, the European Medicine Agency "Guideline on bioanalytical method validation", which details requirements of accuracy and precision.
■ EXPERIMENTAL AND METHODS Raman Spectroscopy. Details of the experimental design are given in the Supporting Information, and the spectral data are available via an open data repository (https://doi. org/10. 5281/zenodo. 4152953). Briefly, we received data from 35 setups for the analysis in this contribution. The information of Raman setups is summarized in Table  S2 , which includes the manufacturer, the source wavelength, and the nominal spectral resolution (i. e. , pixel size). Raman spectra of the NeAr glow lamp and different substances were measured, including agar, gelatine, paracetamol, polystyrene, and cyclohexane. The number of replicate spectra obtained using each setup from the different substances is given in Table  1. The spectral data from setup ID25 were excluded from the analysis, due to recording errors in the wavenumber axis (see Figure  S1 ).
■ RESULTS AND DISCUSSION We present here the results of assessment of the abovementioned metrics calculated for different setups and substances. As our major focus in this study is the cross-setup comparability, we will mainly compare the results of different setups with each other but not specifically consider their reference values given in the literature. ] [34]  The SNR results using a single-spectrum and 10 replicate spectra are given in Figure  1  and Figure  S9 , respectively. The color shades represent setups with different source wavelengths. The meta-information of the datasets is provided in the legend, including the identification number (ID) of the setup, the type of the data, and the excitation wavelength for each measurement. The two data types, represented as 'raw' and 'ical', differed in whether an intensity calibration was done by the setup itself or not, respectively.
Any short-term setup instabilities should be understood and well controlled for the development of clinical applications. • Second, we recommend that the manufacturers provide access to the real raw data, before any processing steps are applied, so that it is more feasible to unravel data that are closer to the 'physical truth'. We would like to encourage both researchers and manufacturers to work together on standard operating procedures for verifying instrument calibration and performance. • Third, we encourage researchers and scientists to make their data openly available and actively contribute to establishing larger databases. This has been done in other data-rich communities (e. g. , ref  38  ) and would be a vast invaluable resource to build statistical models that are tolerant to unwanted spectral differences, like the spectral variations between seemingly identical analytical setups.
09. 2019 in Brussels. The ideas and suggestions listed in the conclusion of this manuscript include a collective contribution from this parallel discussion. L. A. B. C. and M. P. M. M. acknowledge the  Portuguese Foundation for Science and Technology  (Project  UIDB/00070/2020 ). S. K. and P. G. acknowledge the funding from  National Research Fund of Luxembourg (FNR)  via the project  PLASENS  ( C15/ MS/10459961 ). The scholarship from the  China scholarship council  ( CSC ) for S. G is highly acknowledged. This project was supported by the  BOKU Core Facilities Multiscale Imaging. Funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -441958208.
High temperature was generated by means of Nd: YAG laser source (λ = 1064 nm) focused on the P black crystal (≈30 μm beam spot size diameter), which acted both as reactant and laser absorber, thus avoiding any other source of contamination. No evidence for the formation of Au 69 or Re 70 hydrides was observed. X-ray diffraction data acquisition and analysis. XRD experiments were carried out at the ESRF-ID27 beamline using a monochromatic synchrotron radiation beam (λ = 0. 3738 Å) focused to ~5 μm to select different areas of the heterogeneous sample. The diffracted radiation was revealed by a MAR CCD165 detector, located approximately at 187 mm from the sample. The setup was calibrated against a CeO 2 powder standard and Dioptas software was used to integrate the 2D area images to 1D patterns.
The crystal structure was subsequently solved by direct methods and then refined on F 2 by full-matrix least-squares procedures using the SHELXL package (Supplementary Note 1). In addition, at the same pressure and at two other pressure points (4. 1 and 4. 5 GPa), panoramic oscillation images (ϕ = ±5 ∘ , acquisition time 30 s) of oligocrystalline conglomerate were recorded and used to perform Le Bail fits with JANA 2006 software after azimuthal integration (Supplementary Figs. 2 3 4 ). Spectroscopic data acquisition and analysis. The Raman spectra were acquired at LENS with 1. 5 cm -1 spectral resolution using the 647. 1 nm emission wavelengths of a Kr ion laser. The details of the Raman setup are described elsewhere  71. Raman spectra were acquired performing a 14 × 14 mapping over a 10 μm spaced grid using a single 300 groove/mm grating, which allowed to cover the 200-3300 cm -1 frequency region with 4 cm -1 spectral resolution.