dataesr/scientific-paragraphs-categorization huggingface dataset:
Dynamic Flux Balance Analysis dFBA was implemented by computing steady-state flux balance analysis (FBA) solutions with time-dependent exchange fluxes using the COBRApy toolbox  47  and custom python scripts. The rate of isocaproate formation, as represented by the 0. 864 ppm peak in the 1 H-NMR time series, was selected as a normalization marker to align the time axes of all three runs because the 0. 864 ppm isocaproate peak is well-separated in the 1 H-NMR spectra, permitting reliable integration. A logistic curve (1) was fit to the 0. 864 ppm isocaproate peak in the 1 H time series of each run as described in " 1 H and 13 C spectra analyses. " The time axes for the three runs were normalized by aligning the times at which 5% and 95% of maximum logistic isocaproate 1 H signal was measured (Extended Data Fig.
22. ATP hydrolysis was selected for the biological objective as a common metabolic driver during log phase, stationary phase, and sporulation. Steady-state FBA solutions were calculated along a simulated 36-hour timescale with a resolution of 1 solution per hour. Metabolic flux trajectories of selected reactions were visualized using custom MATLAB scripts (Figure  3 ). Fluxes contributing to the production and consumption of cytosolic L-alanine, Lglutamate, ATP, pyruvate, and ammonia were recorded at each timepoint (Supplementary Table  6 , columns C-AK). Predicted amino nitrogen flow from L-leucine to L-alanine was estimated by the following scheme. We define two phases of ammonia metabolism: the deamination phase from 1-9 hours where there is net secretion of ammonia, and the assimilation phase from 10-21 hours where there is net uptake of ammonia.
To accurately capture the L-alanine amino group contribution from Lleucine, we considered the leucine-origin ammonia released in the deamination phase and recycled in the assimilation phase. For detailed calculations of leucine-origin amino nitrogen flow to alanine, see Supplementary Note 1 and Supplementary Table  6. Analyses of  15 N-13  C peak splitting in 13 C NMR spectral analyses of 13 C alanine NMR data measured with Bruker BioSpin (Bruker Corporation, Billerica, MA, USA) were analyzed with NUTS, 2D Pro (Acorn NMR Inc. , Livermore, CA, USA). The fid files were processed using 0. 2Hz line-broadening and were zero-filled before Fourier transformation. After the Fourier transformation, resonance peaks were quantified using curve-fitting with Lorentzian line shapes. Curve fitting was first performed globally to determine the average peak width across all fitted peaks.
Acknowledgments: We thank  Mary Delaney  for microbiology support,  Michael Judge  and  Art Edison  for helpful comments and for confirming capacity of sealed HRMAS NMR rotors to maintain anaerobic conditions. Funding:  National Institutes of Health  grant  R01AI153653  (LB)  National Institutes of Health  grant  P30DK056338  (LB)  BWH Precision Medicine Institute (LB) National Institutes of Health  grant  S10OD023406  ( LLC) National Institutes of Health  grant  R21CA243255  ( LLC) National Institutes of Health  grant  R01AG070257  ( LLC) MGH A. A. Martinos Center for Biomedical Imaging (LLC, LB ).
X-ray data collection and physical measurements Diffraction data of the title compound was collected at 150K with D8 VENTURE Bruker AXS diffractometer equipped with graphite monochromatic MoKα radiation ( λ= 0. 71073Å). Absorption corrections were performed using the multi-scan technique using the SADABS program  [15]. The total number of measured reflections was 7298 among which 2282 were independent and 1948 had the intensity I > 2(I). The structure was solved by direct methods using SHELXT program, which revealed the position of all non-hydrogen atoms, and then refined with full-matrix least-square methods based on F 2 (SHELXL)  [16]  included in the WINGX program  [17]. A final refinement on F 2 converged at R(F 2 ) = 0. 061 and wR(F 2 ) = 0. 152. The crystallographic data and the structure refinements are summarized in Table  1.
ACCEPTED MANUSCRIPT -CLEAN COPY In this theoretical study, all the calculations were performed using the GaussView program  [18]  and the Gaussian 09 software package  [19]  by using the Density functional theory (DFT) with the Becke-three-parameter hybrid exchange functional combined with the Lee-Yang-Parr correlation functional (B3LYP)  [20, 21]  levels, the 6-311++G(d,p) basis set was used for all. In order to analyze the intramolecular interactions, Hirshfeld surfaces and their associated two-dimensional fingerprint plots were performed by the Crystal Explorer version 3. 1 software  [22]  program imported on a CIF file. The topological properties were calculated by the Multiwfn program package  [23]  as well as the reduced density gradient are graphed by Multiwfn and plotted by the VMD program  [24].
Vibrational spectral analysis In order to give more information about the crystal structure, infrared spectroscopy has been used to identify the functional groups present in the crystal and to investigate their vibrational behavior in the solid state. The infrared spectrum was recorded at room temperature in the 4000-400 cm -1 range and compared to the theoretical spectrum by using the density functional theory (DFT) method associated with the B3LYP/6-311 ++ G (d,p) basis set on the optimized geometries of the title compound. The calculated and experimental infrared spectra are shown in Fig. 5. The vibrational spectra showed good correlations with the experimental data with slight difference between the experimental and the theoretical spectra. These small differences which may be due to the fact that the DFT calculations were carried in the gas phase where the crystalline packing forces were not considered.
Atomic force microscopy (AFM). The AFM images were acquired using a Bruker Dimension Icon atomic force microscope (Bruker Dimension IconTM, Billerica, MA, USA). Silicon RTESPA-300 cantilevers (Bruker, Billerica, MA, USA) having a nominal tip diameter of 8 nm were used to perform the AFM measurements. Intermittent contact mode AFM images (1024 × 1024 data points) of 1 μm × 1 μm by keeping the working set point above 70% of the free oscillation amplitude was employed. A scan rate of 0. 5 Hz was used for the acquisition of the images. The Gwyddion 2. 54 software was used to process the images and characterize the roughness of WS 2 coatings on three different substrates (SiO 2 /Si, Si, and Al 2 O 3 ). 2. 2. 4. X-Ray diffraction (XRD). The X-ray diffraction patterns of films consisting of 8 monolayers (8 ML) deposited on SiO 2 /Si, Si and Al 2 O 3 substrates were recorded with a Phillips X'pert MRD diffractometer using Cu K α radiation (spot size 1.
Acknowledgements The authors would like to acknowledge  Lars Riekehr  for the TEM images,  Tomas Edvinsson  for conducting the preliminary PL measurements, and  Yunlin Zheng  for XRD measurements. This work was supported by the  FLAG-ERA  grant for the  Layered Metal Sulfides (LaMeS)  project by the  Swedish Research Council  (VR Grant  2017-06816 ); by the  French National Research Agency  grant  ANR-17-GRF1-0001-03  and by the  Carl Tryggers Foundation  contract  CTS 19:258. A. L. acknowledges the support from the  Swedish Research Council  (Grants No. 2014-6463  and  2018-05336 ) and  Marie Sklodowska Curie Actions  (Cofund, Project  INCA 600398 ). A. F. acknowledges funding by  FLAG-ERA Graphene Basic Research 2 2017 in project LaMeS DFG  project number  400335214. S. H. and P. S. acknowledges  Carl Tryggers Stiftelse for Vetenskaplig Forskning  (grant no:  CTS 17:450 ) for the financial support.
The two Gdapatite and Gd-cyclosilicate phases were then segmented in the micrographs thresholding manually grey values, and the respective areas were measured in the binary images. These data were used to calculate the area covered by the Gd-apatite phase which is divided by the total crystalized area: %F ¼ %F Ap /(%F Ap þ%F Cy ). Powder X-Ray Diffraction (XRD) experiments of cyclosilicate compounds were performed using the CRISTAL beamline of the SOLEIL synchrotron facility (Paris, France). Each sample was introduced in a quartz capillary (0. 3 mm of diameter) spinning around its axis to reduce preferred orientation (PO) of the crystallites. All the patterns were collected in transmission using a Debye-Scherrer geometry using a monochromatic X-ray source set at λ ¼ 0. 72930 Å (beam energy 17 keV).
Data were recorded at room temperature with a 21 silicon (111) monocrystal analyser in the angular range 0 2θ 60 with a step of 0. 002. The Rietveld method was employed for the crystal structure refinement of cyclosilicate phases using the Fullprof program and the previous XRD data. For the first refinement with Ca 3 Yb 2 (Si 3 O 9 ) 2 , the monoclinic Ca 3 Y 2 (Si 3 O 9 ) 2 phase (space group C2/c)  [9]  was selected as the original structure model in which the scattering factor of Yb 3þ replaced the Y 3þ one. Then, the output structure data (lattice parameters, atomic position, occupancy factors …) were recursively used as the new starting point for next refinement of Ca 3 RE 2 (Si 3 O 9 ) 2 (Yb → Dy → Gd → Sm → Nd). For all RE-cyclosilicates, the background was fitted with a six-order polynomial function and the peak profile was modelled using a pseudo-Voigt function.
Z i = (Y i -µ)/σ (1) Afterwards, the next area (A i ) was calculated as the difference between the mean of standardized biomarker response and CI (Z i ) of each exposed group and the mean of the unexposed biomarker data and CI (Z 0 ) (Equation (  2 )). A i = Z i -Z 0 (2) Lastly, in order to obtain the IBRv2 index, the absolute value of A i summed for each parameter in each experimental condition is describe in Equation  (3). IBR = Σ|A i | (3) 2. 11. Health Index (HIS) The Health Index (HIS) was developed and calibrated using biomarkers from active biomonitoring programs and subsequently applied on datasets obtained from mesocosms experiments or field studies. The aim of the present method is to develop and test an objective decision-support expert system capable of integrating biomarker results into a five-level health-status index.
The expert system is based on a set of rules derived from available data on responses to natural and contaminant-induced stress of marine animals. Integration of parameters includes the level of biological organization; biological significance; mutual inter-relationship; and qualitative trends in a stress gradient. Details of the expert system and algorithm description are in Dagnino et al. [24]. The health index was applied in the gills and digestive gland considering biomarkers over a stress gradient yield characteristic trend such as the following: bell-shaped (SOD, CAT and GPx), increasing (LPO) or decreasing (AChE and CI). The results were integrated into a five-level health status index such as A (high), B (good), C (moderate), D (poor) and E(bad), following the classification established by the European Union Water Framework Directive.
Notably, interspecific variation should be considered when comprehensively evaluating environmental risks. For example, the freshwater gastropod Biomphalaria glabrata showed much higher nerve injuries than P. corneus upon pesticide exposure  (Garate et al. , 2020) , and the freshwater amphipod Gammarus pulex accumulated more diclofenac than Hyalella azteca  (Fu et al. , 2020). Although those researches enriched information for risk assessments, it is little known how the specific species variations exactly contribute to the disparities to pollutants. Manufactured nanoparticles (NPs) are extensively used in various commercial products. Silver (Ag) NPs, in particular, display great antimicrobial and antiseptic properties, and are the most commonly used NPs in products since 2012  (The Nanodatabase, 2022).
Statistical analysis Statistical analysis was performed using the software GraphPad Prism 9. 3. 1. One-way analysis of variance (ANOVA) with AgNP concentration as the fixed factor, followed by Dunnett's tests, was applied to test its effects on the bioaccumulation and physiological parameters. Regression analysis in bioaccumulation (concentration-response calculation) was performed using a four-parameter non-linear regression equation. For comparison between AgNPs and Ag + effects, an unpaired t-test was applied. Principal Component Analysis (PCA) and correlation matrices were applied using the packages Factoshiny and Corrplot within the R statistical environment (version 4. 1. 2) to identify and visualize the pattern of endpoints among treatments.
The presented theoretical spectra also give the same overall shape and Stokes shifts seen in experimental data (Figure  1 ). Firstly, we have obtained vibrationally resolved absorption and emission spectra of the studied molecules. Calculations were performed using the VG-FC model. As shown in the literature  [32] , neglect of the excited state geometry relaxation is not only a reasonable, but sometimes crucially important (for calculation convergence) assumption. The comparison of the ground and excited state geometries (Figure  3 ) shows that although there is a noticeable change in structure between S 0 and S 1 (reduction of C 7 -C 8 -C 1Ph -C 2Ph dihedral angle leading to improved conjugation between BODIPY and C 8 -substituent), this change is consistent between the two studied dyes, so the general trends for relevant properties should be preserved.
Synchronous emission spectra were measured in the range of 250-350 nm with wavelength shifts ∆λ of 15 and 60 nm. Excitation and emission slit widths values were 5. 0 nm. Time-resolved fluorescence spectroscopy experiments were carried out by means of a PicoQuant FluoTime 300 high performance fluorescence lifetime and steady state spectrometer with a PicoQuant PLS 450 sub-nanosecond pulsed light-emitting diode as an excitation source. An instrument response function of a system was measured with a stray light signal of a dilute colloidal silica suspension (LUDOX ® ). Fluorescence decay curves were measured at the maximum of the emission peaks and fluorescence lifetimes were obtained by reconvolution of the decay curves using a PicoQuant EasyTau 2 software package. Standard quartz cuvettes with 10 mm light path were used for all experiments.
Quantum Chemical Calculations Procedure The conformational search for COOH-Ph-BODIPY and NHS-Ph-BODIPY was performed in a metadynamic approximation. The calculations were carried out by means of the xtb program  [51]  with the CREST add-on  [52]. The more accurate GFN2-xTB method was chosen along with the iMTD-GC algorithm. The conformational screening revealed four conformers for COOH-Ph-BODIPY and four conformers for NHS-Ph-BODIPY. The lowest energy conformers were chosen for further DFT and TDDFT study. Each conformer was optimized at the CAM-B3LYP/6-31G(d,p) level, which provides a balanced description of both ground and excited states  [53]. For each resulting structure, ten excitation vertical absorption spectra were computed. For the first three excitations, gradients as well as vertical gradient Franck-Condon (VG-FC) vibronic spectra within the TD formalism as implemented in the FCclasses 3.
0 program  [54]  were also obtained. Vibronic spectra calculations used ground state vibrational frequencies, vertical excitation energies computed at ground state geometries and excited state gradients computed at the same geometries. All empirical parameters pertaining to the VG-FC algorithm, such as number of points for the fast Fourier transform (FFT), were directly estimated by the FCclasses program. All vibronic spectra are broadened with Gaussian functions with the constant width of 322 cm -1. This value was chosen because it gives the best agreement between experimental and theoretical spectra of fully unsubstituted BODIPY. All calculations, unless otherwise mentioned, were performed within the CPCM model with DMSO parameters using the ORCA 5. 0 program suite  [55] [56] [57]. Quantities of interest, such as ground and excited state dipole moments as well as transition density matrix elements, were computed using the latest version of the Multiwfn program  [58].
Molecular Docking Procedure The molecular docking of the proteins-BODIPY conjugates was performed in two stages. At the first stage, a blind docking was carried out by means of the Autodock 4. 2 program  [61]. The crystal structures of the proteins under study were taken from the Protein Data Bank: BSA  [62]  and PotN  [63]. The structure of NHS-Ph-BODIPY was obtained by virtue of geometry optimization (Section 3. 8). The calculations were performed for a 126 Å × 126 Å × 126 Å grid with BSA in its center with a step of 0. 7 Å and a 90 Å × 126 Å × 126 Å grid with PotN in its center with a step of 0. 4 Å. Each docking experiment included 50 runs with a maximum of 25 million energy evaluations using the Lamarckian genetic algorithm  [64]. Conformations of the protein-BODIPY conjugates with minimum energies were assumed as the most stable ones.
At the second stage, a covalent docking was carried out by means of the CovDock program  [65]. On the basis of the blind docking results, a covalent binding of NHS-Ph-BODIPY and lysine residues (imine condensation pre-defined reaction) at the most energetically favorable binding site of the proteins was calculated. Conformations of the protein-BODIPY conjugates with minimum energies were again assumed as the most stable ones. A visualization of the molecular docking results were made by means of the UCSF Chimera program  [66].
1b ) but also to adjust this resolution on fly, to refine it according to the experimental map in the environment of a given atom and to deposit it. While such information is hardly available nowadays from cryo-EM databases such as EMDB  (22)  or EMPIAR (  23 ), this will be trivial using the suggested approach. Even when the decomposition (3) is illustrated by examples in cryo-EM and MX, it may be applied to oscillating spherically symmetric functions in other fields of science, in particular to calculate electrostatic potential in small-and macromolecular charge density studies  (24, 25). 2. Maximal error, up to the distance value 𝑟𝑟 𝑚𝑚𝑚𝑚𝑚𝑚 , in the images of a carbon atom at the resolution of 2 Å calculated for different 𝐵𝐵 values using the 𝛺𝛺-decomposition (3). The coefficients of the decomposition were calculated using the image of an immobile carbon atom with 𝐵𝐵 = 0 up to the distance value 𝑟𝑟 𝑚𝑚𝑚𝑚𝑚𝑚 = 10.
Acknowledgments: We thank  L. Urzhumtseva  for her help with computing and  A. Ben Shem  and  B. Klaholz  for stimulating discussions of the results and the manuscript. AU thanks the  French Infrastructure for   Integrated Structural Biology (FRISBI)   ANR-10-INSB-05-01  and Instruct, which is part of the  European Strategy Forum on Research Infrastructures (ESFRI)  and is supported by national member subscriptions.
X-ray di ractometry Crystalline phases of the feed material and products were characterized by X-ray diffraction (XRD). These analyses were performed on a Bruker D8 Advance instrument, equipped with a LynxEye XE-TTM detector using a copper X-ray anode (λ Kα1 =15,418 Å), a 40 kV voltage, and a 40 mA intensity. Diffractograms were collected over an angular range of 5 • to 70 • , with a step size of 0. 02 • over a total acquisition time of 2. 5 h. Crystal phase identification was performed using Bruker-AXS DIFFRACplus Eva v4 software and the ICDD 2015 PDF database. In addition, to obtain a quantitative measurement of the crystalline phases and the total amount of amorphous phases, modeling by the Rietveld method was performed using the DIFFRACplus Topas v5 software (Bruker-AXS). The necessary calibration used the external standard method with zincite, which requires prior knowledge of the elemental composition of the samples analyzed.
Results and analysis Expected phase formation at thermodynamic equilibrium As indicated in the introduction, the nature of the carbonation reaction products depends on the composition of the initial phases contained in the feedstock as well as on the operating conditions. Equilibrium calculations were thus performed in order to take into account the complex initial composition of the slag (Table  1 ) and provide an indication of the expected nature of the stable solid phases. The calculations were performed with the PHREEQC geochemical software and the Thermoddem 2017 database  (Blanc et al. , 2012; Blanc, 2017) , implementing the B-dot model for the calculation of activity coefficients in the aqueous phase. A detailed presentation of the model is available in a previous article  (Julcour et al.
Acknowledgments The authors would like to recognize the invaluable contributions of the following persons:  Bruno Boyer ,  Jean-Louis Labat ,  Alec Maunoury ,  Quentin Ribière , and  Lahcen Farhi  from  ST LGC  for the design, commissioning and operation of the carbonation reactor system;  Christine Rey-Rouch ,  Gwenaëlle Guittier  and  Marie-Line de Solan  from  SAP LGC  for the characterization of the products;  Birsen Budan  from  LMDC  for the XRD/Rietveld analysis;  Armel Descamps-Mandine  and  Claudie Josse  from  Raimond Castaing Centre (Université Paul Sabatier -Toulouse III ) for the SEM/TEM observations and  Alexandre Freulon  from  CIRIMAT laboratory  for his assistance with the making of polished sections.
Phylogenetic repartition of dat and ddc The alternative β-alanine biosynthetic route builds on the DAP pathway, which is supported by dat and ddc. These genes are linked together on the chromosome with dat always upstream, which makes them easy to identify in databases  (67, 68). Comparative analyses conducted on our MicroScope platform (https://www. genoscope. cns. fr/agc/microscope/ home/index. php) showed that clusters of genes orthologous to dat-ddc are present in the chromosome of more than 500 organisms (as of March 2022) belonging in phyla as different as Actinobacteria, Cyanobacteria, Firmicutes, Proteobacteria (α-, β-, γ-, and δ-), Spirochaeta, and Euryarchaeota (halobacteria class). These organisms may also form β-alanine using the alternative route. As an example, S. meliloti 1021 has the colocalized Sma2400 (rhba) and Sma2402 (rhbb) genes that are 54 and 37% identical with dat and ddc of ADP1, respectively.
u. , temperature 500 C, gas 1 40 a. u. , gas 2 60 a. u. , computer-aided designmedium. MS/MS experiments were performed in the triple quadripole mode using multiple reaction monitoring scan type. For each compound, the optimization of following MS parameters (declustering potential, collision energy, and cell exit potential) was performed in order to establish the best intensity transitions (Table  S3 ). Data were processed using Analyst 1. 6. 2 (ABSciex).
The reactions were carried out in activity buffer in the presence of 10 mM DAP, 5 mM 2-oxoglutarate, 200 μM PLP, and 200 μM NAD +. The reactions were initiated by the addition of 35 μg of the enzyme; NAD + reduction was measured continuously at 340 nm. Ddc amine oxidase activity was characterized in a coupled assay with BetB in the presence of NAD + by monitoring the formation of NADH. Assays were conducted in 100 μl of activity buffer containing 1 mM NAD + , 200 μM PLP, 2. Kinetic parameters were determined from duplicate experiments by nonlinear analysis of initial rates using SigmaPlot 9. 0 (Systat Software, Inc).
Variant calling High-throughput sequencing data were analyzed using the PALOMA bioinformatic pipeline implemented in the Micro-Scope platform  (76). First, reads were mapped onto the ADP1 strain reference genome using the SSAHA2 package (version 2. 5. 1) (77). Only unique matches having an alignment score equal to at least half of their length were retained as seeds for full Smith-Waterman realignment  (78)  with a region extended on both sides by five nucleotides of the reference genome. Then, all computed alignments were screened for discrepancies between read and reference sequences, and a score based on coverage, allele frequency, quality of bases, and strand bias was computed for each detected event to assess its relevance. Finally the mutation (SNPs and small indels) with a score superior to 0.