dataesr/scientific-paragraphs-categorization huggingface dataset:
Even if temperature did not appear crucial for the intact protein mix analysis, we still made the choice to keep a relatively high temperature of 60 • C for further analysis as it is known to benefit to the elution of some difficult proteins like mAbs and to limit column backpressure. Finally, method performance was quickly investigated; consecutive dilutions of the protein standard allowed us to approximate a limit of detection at the low ng level. Linearity based on peak area was demonstrated for 5 to 500 ng mass loads of all peaks except for the Exo Klenow protein that exhibits the most intense signal and demonstrated saturation when the injected amount exceeded 100 ng. Repeatability of t Rs was better than < 0. 5 % RSD for all the detected peaks (See supplementary data 3). These performance data were obtained on previous generation instrumentations (both the chromatographic system and the mass spectrometer) and may be better when testing on state-of-the-art systems.
Fig. 5A  shows the TIC profile obtained from a 100 ng-injection of material. Proteins were found to elute from 12 to 40 min; 13 peaks appeared to represent the majority of the TIC peaks areas. These peaks have been annotated with their protein assignments in Fig. 5A. Protein identification was performed by mass matching of histones theoretical sequences and sequencing data were used for confirmation. Table  2  summarizes the most relevant mass assignments made in this experiment while Fig. 5  panels B, C, D and E represent the deconvoluted mass spectra of H2B1, H4, H3 and H2A1 histone variants. Extracted ion chromatogram (XIC) signals from these 4 peaks were used to estimate an average LC peak FWHM of 16 s, which is reassuringly comparable to results obtained with the protein standard. It is worthwhile to compare the results of this experiment with those published by Zhou et al.
Top2 MSMS cycles are typically used with a sequencing speed close to 1 Hz in order to accumulate several microscans. This instrument limitation makes it more favorable to apply extended gradients. In our experiment, MS and MSMS data were next processed with Prosight and Toppic for protein identification. Fig. 6C  shows the Venn diagram of the 89 unique identified proteins by combination of outputs from the two software. 64 proteins (about 72 %) were consistently identified by both while each of the two software applications singly identified 14 % of the remaining proteins i. e. , 12 and 13 unique proteins. Fig. 6D  shows finally the STRING protein graph composed of 89 identified nodes with protein-protein interaction links or connections among them. Red nodes show proteins with GO molecular function classified as structural constituents of the ribosome in accordance with expected identifications.
32 mm Â 4 lm), and a TCD connected to a J&W Pora-PLOT Q-HT capillary column (25 m Â 0. 53 mm Â 20 lm). As analysis time is 30 min, no data were collected during the early stages of activation and induction. An HPR 20 QIC R&D mass spectrometer (Hiden Analytical) was connected to the effluent to monitor as a function of time-on-stream the mass-to-charge ratios  16  respectively. The reaction was carried in a time on stream (ToS) from 5 min up to 20 h. The feed gas was replaced at different ToS with nitrogen to desorb the most volatile products retained on the catalyst. The reactor was then rapidly cooled to 150 °C with a dry airflow to analyze the retained hydrocarbons at 5 min, 10 min, 30 min, 1 h, 4 h, 10 h, or 20 h ToS. The recovered materials were referred to as (X-MoHZ-15) Y where X stands for wt % Mo and Y for ToS.
Acknowledgments The authors acknowledge financial support from the  European Union (ERDF)  and '' Région Nouvelle Aquitaine ". A. Beuque , and  L. Pinard  thank the  European Union 's  Horizon 2020 research and innovation program  for its funding under grant agreement No  814548. This publication only reflects the author's views, and neither Agency nor the Commission is responsible for any use that may be made of the information contained therein. L. Pinard  thanks the  Region Normandie  for funding the  BioDNH ''Chaire d'Excellence ".
Retrospective Analysis of Patients Treated with Nicardipine 2 mg/mL Oral Formulation Children who were treated with the previous nicardipine hydrochloride 2 mg/mL oral formulation in our center from 1 January 2020 to 31 December 2020 were identified using an internal compounding software program. Electronic medical files (CDP2 ® software, C. PAGE patient files) and prescriptions were consulted to collect demographic data and the prescribed doses of nicardipine. The study obtained ethics approval provided by the institutional ethics committee (CERDE-HLJ: Comité d'Ethique pour la Recherche sur Données Existantes et/ou Hors Loi Jardé) with the number E2023-02.
Acknowledgements This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon H2020 research program  (grant agreement no. 716314 ). CNRS and  Ecole Polytechnique  are thanked for funding. A. J. is grateful to  Ecole Polytechnique  for a PhD fellowship. Nicolas Casaretto  is thanked for his assistance in analyzing the crystallographic data. This work was performed using HPC resources from the  GENCI (CINES/IDRIS , Grant No. 2021-A0100806830 ).
Acknowledgments. This work was supported by the  LABEX MANUTECH-SISE  ( ANR-10-LABX-0075 ) of  Université de Lyon , within the " Plan France 2030 " operated by the  French National Research Agency (ANR) , and the program " Investissements d'Avenir"  ( ANR-11-IDEX-0007 ). Authors equally acknowledge the  GIE Manutech-USD  platform for allowing the realization of the surface ripples on the ZnTe sample.
Pathogenicity of variants was determined according to the recommendations of the American College of Medical Genetics (ACMG)  [14]. Blood-based CRIM assay was done by western blot analysis as described previously  [15]. GAA variants and their corresponding CRIM status were all compared with data present in the Pompe disease GAA variant database (http://www. pompe varia ntdat abase. nl/). A standard anonymous form was sent to all expert centers, completed by the local investigator, and sent to our center for data to be entered into the database. Management and control of the data were performed by a clinical research associate using Microsoft Access® software.
X-ray diffraction data collection was carried out on a Bruker PHOTON III DUO CPAD diffractometer equipped with an Oxford Cryosystem liquid N 2 device, using MoÀ Kα radiation (λ = 0. 71073 Å). The crystal-detector distance was 37 mm. The cell parameters were determined (APEX3 software)  [25]  from reflections taken from 1 set of 180 frames at 1 s exposure. The structures were solved using the program SHELXT-2014. [26] The Hatoms were included in calculated positions and treated as riding atoms using SHELXL default parameters. The non-H atoms were refined anisotropically, using weighted full-matrix least-squares on F2. A semi-empirical absorption correction was applied using SADABS in APEX3; transmission factors: T min/ T max = 0. 7091/0. 7456 for 5a BF4 ; T min/ T max = 0. 7264/0. 7456 for 5a BArF ; T min/ T max = 0.
Acknowledgements This research was funded by the  International Center Frontier Research in Chemistry (icFRC) , the  LabEx CSC  ( ANR-10-LABX-0026 CSC ) and  French National Research Agency  ( ANR-21-CE07-0014 ). RW thanks the  LabEx CSC, Strasbourg , for a PhD fellowship. LG thanks the  ANR  for a PhD fellowship and AP-H thanks the  French Ministry of Research  for a PhD fellowship.
The main goal was to assess the influence of photo-or electro-chemical activation on the properties of these naphthoquinone derivatives. F-PD and F-PDO were compared to their analogues PD and PDO that are lacking fluorinated substitution on the 2-methyl group of the menadione subunit. These data are also discussed with respect to those previously measured for PD-bzol. 17, 26 Cyclic (CV) and square wave (SWV) voltammograms were first recorded in the potential range from 0 to -2. 1 V vs. KCl(3 M)/Ag/AgCl reference electrode (+0. 210 V vs. NHE). For PD, PD-bzol and PDO (i. e. , PD-bzol and PDO are PD metabolites following PD's bioactivation), we previously showed that reduction of the electroactive 1,4-naphthoquinone core resulted in two successive reversible one-electron transfers (Figures  S3-S9  in the ESI) in DMSO.
To deepen the understanding of the fluorescence properties of F-PDO, experiments were performed in an i PrOH/DCE (v/v) mixture ([F-PDO] = 0. 25 mM) under irradiation at 350 nm (Rayonet photochemical reactor 224 W). Whether in the presence or the absence of -met, a UV-irradiation for 2 h 15 resulted in the formation of a new absorption band centered at  435 nm and 415 nm in the absence and presence of -met, respectively. Regardless of the presence of -met, no spectral alteration of F-PDO could be observed in the absence of UV-irradiation (Figure  8 ) confirming that photoreduction to semi-naphthoquinone or dihydronaphthoquinone is the process at the origin of these spectral alterations in agreement with literature data (vide supra). In addition, comparison of the absorption spectra of F-PDO in the absence and presence of -met highlighted substantial spectral differences (Figure  S23  in the ESI).
Acknowledgments This work was supported by the  Université de Strasbourg  and the  CNRS. The authors wish to thank the  Laboratoire d'Excellence (LabEx) ParaFrap consortium  for funding [ ANR-11-LABX-0024 ], and creating a proper framework for this scientific research. This observation of metabolite fluorescence, discovered by serendipity, has also benefited from the received financial support from the  CNRS  through the  MITI interdisciplinary programs "Vie & lumière". Dr Valérie Mazan  ( LIMA UMR7042 ) is gratefully acknowledged for the quantum yield measurements.
In principle, this can be easily done by acquiring quantitative data for each isotope. However, such an approach would require the use of an internal lithium reference inside the studied sample. This strategy is generally followed in liquid-state NMR. However, for solid materials, it appeared worthwhile to develop a method, without an internal reference, to quantify  7  Li and  6  Li using high resolution solid-state NMR techniques. It is the objective of this work. The method we have developed was tested on several samples with unknown 7 Li/ 6 Li isotope ratios. These samples consist of lithiated silicon-based electrodes in which isotopic enrichment was performed using an electrochemical method. The main  6  Li enrichment setups that were used in the present work are illustrated in Fig. 1.
The signal-to-noise ratio is improved by averaging 500 single spectra to produce each coadded spectrum. A number of previous works have demonstrated that coadded LILBID spectra of one compositional type are applicable to in situ mass spectra from CDA (e. g. ,  Klenner et al. , 2019; Klenner, Postberg, Hillier, Khawaja, Cable, et al. , 2020; Klenner, Postberg, Hillier, Khawaja, Reviol, et al. , 2020). The threshold for peak retention in the mass spectra was set at 0. 005%. Recorded mass spectra are archived in a comprehensive spectral LILBID database and aid planning for future space missions to icy moons  (Klenner et al. , 2022).
Data Sets and Selection Criteria In this work, benzoic acid, and two of its isomeric derivatives, 2,3-DHBA and 2,5-DHBA, have been investigated with LILBID-TOF mass spectrometry. Each compound was injected into LILBID as an aqueous solution of concentration 0. 025 M, significantly below the solubility limits of these species, at a flow rate of 0. 23 mL min -1. Three different simulated impact velocity regimes were studied in this work-henceforth called low, intermediate, and high-because different impact speeds of ice grains can produce fundamentally different spectral appearances even when the grains have the same composition  (Klenner et al. , 2019). The low velocity simulation corresponds to an impact velocity ∼4-6 km/s and is achieved by operating the laser at 92. 0% intensity with a mass spectrometer delay time of 69 µs.
Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise "glycocodes" that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs.
These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e. g. , ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics.
In combination with sophisticated molecular calculations at the density functional theory (DFT) level, the resulting spectra can be used to obtain detailed structural models of the investigated ions. Perspectives. The accumulation of experimental data has revealed that closely related isomers have distinct IR f ingerprints. Such unique IR f ingerprints of well-characterized standards could be organized in a database and used to identif y structural features such as the sulfation pattern and perhaps the entire sequence of unknown GAG oligosaccharides in the f uture. However, already at the level of oligosaccharides, the chemical space of GAGs is too large to be fully covered by synthetic molecules. Theoretical spectra computed f rom DFT structures may be required to bridge this gap and annotate structures that are not accessible via synthesis.
The speed of translocation needs to be reduced to the record of suf f icient  electrical signals for accuracy improvement, and a reference database for recognition tunnelling sequencing of GAGs is needed too. 2. 4. 5. NMR Analytical Methods. NMR methods are attractive for GAG analysis as they are nondestructive and do not require derivatization. Over the years, the arsenal of NMR methods developed for the structural determination of biomolecules has been applied to GAGs. The most common multidimensional methods involve homonuclear spectroscopy ( 1 H-1 H correlation spectroscopy, (COSY), total correlation spectroscopy (TOCSY), nuclear Overhauser effect spectroscopy (NOESY), rotating frame Overhauser effect spectroscopy (ROESY), heteronuclear spectroscopy ( 1 H-  13  C heteronuclear single quantum coherence (HSQC), and heteronuclear multiple bond coherence (HMBC)).
However, these parameters show batch-to-batch differences not only in products of different sources but also in different processes, from the same animal source and even in the same process. Therefore, the composition of a given batch does not bear quality information if it is not compared with large analytical result databases, representing the structural variability of heparin. Statistical methods, such as principal component analysis (PCA), have been used to compare test samples against mono-and bidimensional spectral libraries of heparin of different animal and organ origins. PCA extracts from a high number of variables, which are highly correlated and challenging for interpretation of a small number of orthogonal variables, which are more useful for sample profiling. PCA proved effective in clustering GAGs according to their origin or manufacturing and differentiating different crude heparins; a very complex mixture of GAGs considered the starting material of the active pharmaceutical ingredient (API) heparin production.
Novel chemometric techniques, such as spectral filtering, have been applied to HSQC spectral databases to search for unknown features in heparin, whether due to contaminants or manufacturing failures. 78 ecently, the FDA alerted industries regarding the potential risk of heparin contamination with nonporcine ruminant material contaminants, suggesting the application of physicochemical methods to ensure the safety of drugs and protect public health. The application of multivariate classification approaches to heparin 1 H NMR spectra was a rapid and reliable tool for detecting contaminants. Partial least squares discriminant analysis (PLS-DA) provided the best discrimination of contaminated batches, enabling the detection of samples contaminated by heparin from other animal species at 5%. 79  Perspectives.
NMR integrated with statistical analysis is a valid quality tool for heparin in the entire production process and should be concurrently used with complementary techniques like SAX-HPLC and disaccharide analysis, but setting acceptance criteria requires the knowledge of the design space of normal processes of dif ferent animal source and characteristics of the main anomalies. It will require building large sample databases, supervised by regulatory authorities, and designing analytical procedures with evaluation ranges for results as simple as possible. Moreover, whereas the destination to routine pharmaceutical work usually limits NMR methods to medium f ield spectrometers (500-600 MHz), the larger availability of high f ield NMR instruments coupled with high sensitivity probes allows for increasing the sensitivity of these techniques that can also be applied on biological f ield, where a limited amount of sample is usually available.
As an ultimate level of approximation, coarse-grained (CG) methods allow the study of the structure and dynamics of very large (up to several million atoms) and heterogeneous systems by reducing the complexity of their molecular representation while retaining their fundamental physicochemical characteristics. CG and supra-CG descriptions can be back-mapped to all-atom representation, thus back-tracing important molecular features. The investigations of GAGs primarily exploit such approaches, even if physical issues of these polysaccharides can often limit their application. 2. 5. 3. 1. Quantum Mechanical Simulations. The quantum mechanical (QM) description is widely adopted to investigate GAG systems' hydrogen bonding and coordination interactions and calculate spectroscopic properties needed to complement or interpret experimental data (see the section on IRMPD above).
Through the compilation of well-designed and curated data sets, Artificial Intelligence would have the potential to substitute human intervention, providing consistent data interpretation and, ultimately, rapid glycoanalytics. Toward this goal, the role of glycobioinformatics in the setup and curation of glycomics/glycoanalytics data sets is a notable example of Unicarb-DB. In terms of 3D structure determination, the limitations glycoscience currently suffers from are similar to the difficulties inherent to the structural determination of intrinsically disordered proteins (IDPs) or regions (IDRs), for which AlphaFold2 is not greatly useful. As it stands, the contribution of glycan builders, such as glycam. org, CHARMM-GUI, GAG-Builder, and databases of equilibrated MD structures in combination with adequate conformational sampling, can address most queries.
Nevertheless, limitations of the empirical additive force field formalism remain problematic in some cases and work toward developing machine learning force fields for glycans is one of the highly anticipated upcoming innovations in the field. 106, 107 in the development of tools to load and extract information f rom glycan data sets. 108 The use of Machine Learning methods to predict and understand GAGs structure to f unctions relationships f rom existing data sets and under-development databases is one of the promising upcoming f ields of GAGs research soon.
In addition, methods should be developed to study the ability of various GAGs to assemble multimeric protein complexes and follow the motions of GAGs and GAG-binding proteins throughout the extracellular matrix and the glycocalyx to reach and bind to their partners (e. g. , cellsurface receptors). 8 ), and DP 9 (1). More than 80% of the GAGs involved in the complexes are heparin and hyaluronic acid oligosaccharides, which does not reflect the diversity of GAGs. The GAG-DB database (https://gagdb. glycopedia. eu/) provides the architecture and navigation tools to query the Protein Data Bank, UniProtKB, and GlyTouCan (the universal glycan repository) identifiers. Special attention was devoted to describing the bound glycan ligands using simple graphical representation and numerical format for cross-referencing other databases in glycoscience and functional data.
127 Experimentally, this limitation is mainly due to the lack of available well-characterized longer oligosaccharides and full-length GAGs and the subsequent limitation of 3D structures of GAG-proteins complexes (currently more than 120 PDB entries, including less than 40 nonredundant nonenzymatic complexes). 110 Computational methods to tackle long polysaccharide chains are deficient because running MD simulations for many sequences remains challenging, especially at a high-throughput level. As a result, biological phenomena induced by long GAG chains, such as protein homo-oligomerization, the formation of multimeric biomolecule complexes and cooperative effects, are underexplored. 128 espite all these difficulties, the accumulation of MD results, combined with docking studies, suggests that the patterns of recognition of GAGs by proteins follow a continuum.
Consequently, GAG interactomes should be contextualized by integrating proteoglycan interactions, transcriptomics, and/or proteomics data to generate cell-, tissue-, or disease-specific interactomes. Additional GAG interactomes can be built based on a molecular function, a biological pathway, or a cellular location. It should aid in deciphering the mechanisms associated with GAG interactions in various physio-pathological contexts. However, the integration of these data is focused on GAGbinding proteins. The development of high-throughput assays measuring the number of individual GAGs in biological samples would allow the collection of GAGomic data sets, which could then be integrated into GAG networks to refine their specificity. 136 The setup of high-trough-put binding assays based on surface plasmon resonance imaging using commercially available instruments will be helpful in calculating the kinetic and affinity parameters of an increasing number of GAG interactions.
The integration in these networks of the chemical features (e. g. , sulfation) and size of GAGs and of the amino acid sequences and domains of GAG-binding proteins would be very valuable to explore the relationships, if any, between these features and the biological or structural roles of GAG-binding proteins. GAG interaction data are freely available in public databases such as MatrixDB (http://matrixdb. univ-lyon1. fr/) and GAGDB (https://gagdb. glycopedia. eu/), which have recently been reviewed. 109 The development of standards in data sharing (e. g. , the FAIR principle) and storage repositories and databases have markedly changed access to large data sets and their retrieval and (re)use. "Big data" have become a precious resource, and its exploration will benefit from recent advances in artificial Intelligence (AI).