dataesr/scientific-paragraphs-categorization huggingface dataset:
Unfortunately, they were mostly measured by batch experiments without any washing step, i. e. without reducing the non-specific interaction contri-Fig. 1. Differences in SPE profiles of IIPs 1/4 (a), 1/6 S1 (b), and 1/8 (c) towards some cations. P: percolation of 1 mL of 1 mM MOPS buffer at pH 7 spiked with 0. 01 Bq mL -1 of 226 Ra and 10 μg L -1 of Sr(II), Ba(II), La(III), Co(II), Nb(V), Ag(I), Tl(I), and Pb(II). W: washing steps with 0. 5 mL of UP water and 0. 5 mL of HNO 3 pH 4. E1 to E3: Elution with 0. 5 mL of HNO 3 pH 3, 0. 5 mL of HNO 3 pH 2, and 1. 5 mL of HNO 3 0. 5 M, respectively. In brackets: oxidation degrees assumed to be predominant between pH 1 and 7. bution. To better compare data from literature to our values that reflect the specific capacity as a washing step was performed rather than a global capacity (sum of specific and non-specific interactions) when no washing was carried out, the specific capacity of the calcium and strontium IIPs was estimated by subtracting the capacity of the NIP to that obtained on the IIP.
Breakthrough volume measurements The breakthrough volume of the IIPs 1/6 and 1/8 was evaluated in order to know the maximum enrichment factor that could be reached in pure solutions. Percolation volumes from 1 to 50 mL and containing 100 ng of Ba(II) (less than 1% of the maximum capacity of the tested polymer amount) were loaded onto the IIPs 1/6 S1 (30 mg) and 1/8 (60 mg). The same cartridges as for previous tests were used since up to this stage, cartridges of the IIPs 1/6 S1 and 1/8 were reused about 35 and 12 times, respectively, without observing any significant loss of performance (recoveries always above 90%). Data in Fig. 4  are presented, after normalization for 100 mg of both sorbents to compare them. As no decrease in recovery was recorded after percolation of 83 and 167 mL of solution on 100 mg of IIP 1/8 and 1/6 S1, respectively, the breakthrough volumes of the IIPs were not reached in this range of volumes studied.
2,4,6-Me 3 C 6 H 2 ) SynOrg (ANR-11-LABX-0029), Carnot Institute I2C, the graduate school for research XL-Chem (ANR-18-EURE-0020 XL CHEM), and Region Normandie. T. B. thanks the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (Grant Agreement Number 758710). F. B. thanks the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie (Grant Agreement Number 101034329 and the Region Normandie (WINNINGNormandy program) for funding.
5 Labex 5 2,4,6-Me 3 C 6 H 2 ) SynOrg (ANR-11-LABX-0029), Carnot Institute I2C, the graduate school for research XL-Chem (ANR-18-EURE-0020 XL CHEM), and Region Normandie. T. B. thanks the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (Grant Agreement Number 758710). F. B. thanks the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie (Grant Agreement Number 101034329 and the Region Normandie (WINNINGNormandy program) for funding.
ACKNOWLEDGEMENTS The authors thank  Dr Pedro Lameiras  ( ICMR ) for help with NMR Water Suppression methods and the ERETIC 2 tool. The  Agence Régionale de Santé (ARS) Grand Est as well as the Centre Hospitalier Universitaire (CHU) of Reims (France)  are also acknowledged for providing a thesis grant to  Cédric Barthel. Numerous discussions with  Professor Joseph Connolly  on the content and conformity of this article are deeply appreciated.
reinhardtii, whose complete genome has been sequenced and is available in databases  (Blaby et al. , 2014; Merchant et al. , 2007). All selected genes could not be studied for both species due to either unavailability in the data banks or to the absence of functional primers. The reference genes made it possible to determine the relative gene expression differences for the targeted genes. Because they correspond to cellular functions linked to cellular integrity, their expression remains stable. The selected reference genes were βact and ef1α for C. reinhardtii and rpL13 for N. palea.
Analysis of non-covalent interactions using NCIPlot software (see SI for additional details) in the transition states of the  Cl methanol elimination during the lactonization step revealed the presence of a T shaped π-stacking interaction between the aryl groups, as well as an alkene-arene π-stacking interaction during the formation of the cis lactone. These stabilizing interactions, which are not present in the TS leading to the formation of the trans lactone offer a free energy difference of 4. 5 kcal. mol -1 in favor of the formation of the cis lactone. Surprisingly, when 2i was reacted with pivaldehyde, the expected allylation product could not be detected; instead we isolated γ-lactone 11 in 57% yield (Figure  6 , H). To understand this unusual formal γ-oxidation/ lactonization cascade, we carried out a set of reactions.
Antipromastigote Activity L. amazonensis promastigotes were cultivated in Schneider's insect medium supplemented with 10% HIFCS, as indicated above, in either absence or presence of different concentrations of the substances. Culture was initiated with 1. 0 × 10 6 cells/mL and maintained at 26 • C for 72 h. Cell viability was estimated via reduction of resazurin. The 50% inhibitory concentration (IC 50 ) was determined via logarithmic regression analysis using GraphPrism 5 software.
Acknowledgements Q. L. , A. B. , D. A. V. and A. S. acknowledge the  European Research Council for funding  (grant agreement  757501 ). Q. L. D. , A. B. , C. B. , L. V. , D. A. V. and A. S. would like to thank the  CNRS  for general support. I. d. R. and C. D. are indebted to CALMIP for HPC resources (Grant  2017-[p17010 ]). A CC-BY public copyright license has been applied by the authors to the present document and will be applied to all subsequent versions up to the Author Accepted Manuscript arising from this submission, in accordance with the grant's open access conditions.
Funding  T. Mangeat  had a PhD studentship from the  Ligue Nationale Contre le Cancer. This work was supported by a grant of  Ligue Régionale contre le Cancer de la Lozère ; the  French National Research Agency  under the program  Investissements d' Avenir Grant Agreement   LabEx MAbImprove  (Grant No. ANR-10-LABX-53 ) and the  SIte de Recherche Intégrée sur le Cancer (SIRIC) Montpellier-Cancer  (Grant No. INCa-DGOS-Inserm 6045 ).
Given the growing importance of the field of chemobrionics since the term was coined in 2015 and the increase in the number of published papers, it has become necessary to catalogue all the papers published to date. Here we present the chemobrionics database, which lists all the chemical gardens synthesised according to their anion, cation and experimental protocol. The aim of this database is to encourage the study and dissemination of chemical gardens in order to find new experimental avenues in the field of chemobrionics. As this is such a fruitful field, the database is continuously updated.
Introduction Chemical gardens are self-organizing structures that biomimic plant-like structures with tubes and vesicles shapes. Johann Glauber described these structures for the first time in 1646. [1] Since then, chemical gardens have attracted the attention of scientists, who have recently called this research field chemobrionics. [2] ] [9] [10] [11]  Classical experiments on chemical gardens were performed by adding to a solution of an anion a metal salt (except the too-soluble alkali metals). The metal salt can be added in solid form, as single crystal or as a pellet of polycrystalline powder, or as a second liquid. The most common anion solution used to promote the growth of chemical gardens have been silicate, but many others have also been used. [2] 18] Therefore, taking into account the wide number of conditions to promote the growth of chemical gardens, here we present the chemobrionics database, which curates all the papers published to date about chemical gardens, to the best of our knowledge.
Results and Discussion Since the term chemobrionics was coined in 2015, the number of publications in this field has increased. From the first description of chemical gardens by Glauber  [1]  in the 17th century up to and including 2015, 95 papers have been published. Since then and up to the end of 2022, when this article is written, 104 papers have been published (Fig. 1 ). ‡ In addition, 2 papers have been already accepted and taken into account in the database (although they are not shown in figure  1 ). [21, 22] his increase in the number of publications demonstrates the scientific interest in this field, as also testified by the award of a COST project of the European Union (COST Action CA17120 Chemobrionics). Therefore, and in order to help the scientific community, the chemobrionics database has been designed.
This database can be downloaded from zenodo repository as. csv  [19] or can be consulted live on a dedicated website (Fig. 2 ). [20] In this database, the chemical gardens have been catalogued according to the anion and cation used, and the experimental setup. Accompanying this information are the references to the papers describing these chemical gardens. Therefore, in this database, a chemical garden with the same anion and cation may appear in several entries if different experimental methods have been used to synthesize it or if it has been combined with an additional ion. For example, the combination of silicate with calcium appears a total of 8 times in the database, as it has been synthesized using three different experimental approaches (solid, gel and paste), but it has also been synthesized by combining them with CO2, with carbonate anion, with phosphate anion and with iron cation.
These calcium silicate gardens have been described in a total of 27 different papers. Thanks to this database, some interesting results can be extracted on the main chemical gardens on which chemobrionics research has focused. The main anion used has been silicate (53 entries in the database), followed by carbonate (35 entries) and phosphate (25 entries). In figure  3  can be seen all those anions which have more than 5 entries in the database. Among the cations, iron has been the most used cation, both +2 and +3 (32 entries), followed by calcium (31 entries) and copper (21 entries). Focusing on the methods used, using one solid phase (i. e. solid setup in the database) and mixing two liquid phases (i. e. liquid setup) have been by far the most used methods, appearing in 86 and 72 entries, respectively.
In other cases, anions and cations only appear in one entry, so that these routes of synthesis of chemical gardens are open to new experimental contributions. For instance, that is the case of aluminates,  [23]  chlorite  [24]  or tungstates,  [25]  for anions; and lithium,  [17, 26]  cerium  [27]  or gold,  [1, 28]  for cations. Within the database, there are chemical gardens that can be considered special, because they cannot be differentiated by anions and cations, so the same terms appear in both fields of the database, such as ice,  [29]  steel,  [3, 15]  Portland cement,  [30]  and xenon hydrates. [31]  is also interesting to note that some researchers have studied natural structures that they have described as chemical gardens, although such structures are less accessible than the experimental synthesis of chemical gardens and, therefore, there are fewer references.
Conclusion In conclusion, given the increasing number of works in the field of chemobrionics, we have found it necessary to create a database to collect and catalogue them in order to facilitate the bibliographic work of future research. In addition, this database can be used to detect research gaps on which to focus future works. This database is alive and the references cited in it are periodically updated. For this reason, the zenodo repository is used for its distribution, where future updates can be easily found. Future updates of the database can be adapted to the needs of the community by making it more specific as necessary.
This is the pre-peer reviewed version of the following article: Pimentel, Carlos, Zheng, Mingchuan, Cartwright, Julyan H. E. , & Sainz-Díaz, C. Ignacio (2023). Chemobrionics Database: Categorisation of Chemical Gardens According to the Nature of the Anion, Cation and Experimental Procedure. ChemSystemsChem, which has been published in final form at https://doi. org/10. 1002/syst. 202300002. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
ACKNOWLEDGEMENTS We would like to thank  ESRF  for the provision of the beamtime at ID31 beamline as well as  Helena Isern  and  Florian Russello  for the help with the beamline preparation. R. C gratefully acknowledge financial support from the  French National Research Agency  through the  HOLYCAT  project (grant number n•  ANR-22-CE05-0007 ) and  Dr. Bernard Fraisse  from the analysis and characterisation platform of the  Pôle Chimie Balard. L. C. , , K. K, V. M, F. M. and L. D. gratefully acknowledge financial support from the  French National Research Agency  through the  BRIDGE  project (grant number n• ANR-19-ENER-0008-01 ).
Acknowledgements This work was supported by the  China Scholarship Council (CSC , PhD grant of R. C. ), by the  French Agence Nationale de la Recherche  (project  ANR-17-CE07-0002 AbsoluCat , PhD grant of A. H. ,  PDRA  grant of P. A. ) and by the  Consejo Nacional de Ciencia y Tecnologia (CONACYT ,  PDRA  grant of M. M. -A. ). Omar Khaled  and  Ludovic Dubreucq  ( IPCM, Sorbonne Université ) are acknowledged for assistance with chiral HPLC experiments and preparation of starting materials, respectively. Gilles Clodic  ( MS3U, Sorbonne Université ) is acknowledged for the ESI analysis of catalytic samples. The GDR 3712 Chirafun is acknowledged for allowing a collaborative network between the partners of this project. Keywords:  supramolecular polymer • switchable catalyst • stereodivergency • chirality induction • benzene-1 ,3, 5tricarboxamide• dynamicity• amino alcohol• copper hydride catalysis.
5 min on a standard desktop. Firstly, we remind the foundations of the algorithm and detail how we adapted SpecGlob (the method we previously developed following the same aim, but limited to the interpretation of perfect simulated spectra) to the interpretation of imperfect experimental spectra. Then, we highlight the interest of SpecGlobX as a complementary tool downstream to three open modification search methods on a large simulated spectra dataset. Finally, we ran SpecGlobX on a proteome-wide dataset downloaded from PRIDE to demonstrate that SpecGlobX functions just as well on simulated and experimental spectra. We then carefully analyzed a limited set of interpretations. Conclusions: SpecGlobX is helpful as a decision support tool, providing keys to interpret peptides carrying complex modifications still poorly considered by current.
Background Interpreting fragmentation mass spectra and their assignment to a peptide sequence is an important and challenging issue in proteomics, especially when peptides carry one or several modifications. These modifications could explain the low rate of interpreted spectra after a standard bottom-up mass spectrometry analysis  [1, 2]. While the modifications on proteins may be the consequence of co-or post-translational events in the cell, they may also be due to sample preparation (use of chemicals during the preparation, e. g. , surfactants) or to the presence of allelic variants not described in the protein databases. Although reference databases of modifications exist and can draw up a list of more than a thousand modifications such as in Unimod  [3] , the variety of putative modifications is so large that existing databases cannot be exhaustive.
Besides, it is also difficult, if not impossible, to predict and account for all possible modifications occurring in a sample. In recent years, several open modification search (OMS) methods have been proposed to enhance the identification of mass spectra corresponding to modified peptides. These identifications are achieved through the comparison of experimental spectra to 'reference spectra' , either simulated in silico from peptide candidates-referred to as theoretical spectra-or collected in a spectral database  [4]. Whereas conventional methods (also called restricted or closed-search methods) try to identify experimental spectra in comparison to reference spectra in a narrow search mass window, OMS methods evaluate all or at least a large part of the reference spectra without any (or only a limited restriction) on their masses.
Several advantages distinguish OMS methods from their conventional methods counterparts: (1) they enable the interpretation of spectra corresponding to peptides with unanticipated modifications;  (2)  the large number of modifications they can underpin does not alter identification results confidence as it occurs when an extremely large search space is generated by the introduction of many variable modifications on simulated spectra in the reference spectra database  [5, 6]. The result of an OMS method is a list of PSMs (St, Se, ∆M) where St denotes the theoretical fragmentation spectrum of a candidate peptide, Se denotes an experimental spectrum, and ∆M is the mass difference between St and Se. This mass difference ∆M, if above the mass accuracy of the instrument, should be explained by one or several modifications carried by the peptide in the experience.
However, to our knowledge, there is currently no open-source software adapted to routine laboratory use allowing the ∆M interpretation without any a priori on the modifications, including labile ones. To fill this gap, we implemented SpecGlobX, which aligns very quickly pairs of spectra (St, Se). SpecGlobX (SpecGlob eXtended version adapted to eXperimental spectra) is a standalone software based on a dynamic programming algorithm. It derives from SpecGlob  [19] , which we first developed using perfect simulated spectra. This initial step was essential to evaluate the SpecGlob algorithm's ability to consider complex and variable modifications and to optimize its execution time. To reach a fast execution speed, we introduced-among other things-a simplification in the alignment of spectra compared to previous methods also based on dynamic programming  [20] [21] [22] : each peptide is modeled by a series of peaks corresponding to only the b-ions generated by an ideal fragmentation.
However, on their side, experimental spectra are not ideal; they lack some fragmentation peaks and are noisy. In this article, we present the main adaptations developed in SpecGlobX towards the applicability of SpecGlob on experimental spectra, considering the imperfections of these spectra. Then, we highlight the benefits that SpecGlobX delivers downstream to three OMS methods: SpecOMS  [23] , MODPlus  [14] , and MSFragger  [9]  on a simulated dataset that mimics experimental spectra. Indeed, even if the complexity of an experimental spectrum is difficult to reproduce, simulated spectra are helpful to understand the behavior of an algorithm when there is no ground truth available for large-scale interpretation of PSM lists. Finally, we challenged Spec-GlobX on a set of experimental spectra already interpreted by different OMS software, namely the HEK293 dataset  [24].
Evaluation of SpecGlobX with a simulated spectra dataset Firstly, we challenged SpecGlobX on a simulated spectra dataset Dsim generated from 50,000 tryptic unique peptides randomly selected from the human proteome-downloaded from Ensembl99, release GrCh38  [27] -and whose lengths span from 12 to 25 amino acids. We transformed those peptides into doubly charged simulated spectra with the following modifications: we introduced a deamidation on each asparagine (N+ 0. 984016 Da) and a sodium adduct on each aspartic acid (D+ 21. 981943 Da); next, we randomly removed 20% of the peaks to simulate missing peaks. Two-thirds of the removed peaks were b-ion peaks and one-third were y-ion peaks, as we observed that missing peaks are mainly b-ion peaks in experimental fragmentation spectra acquired in an HCD cell (a common instrument configuration of high-resolution mass spectrometers used in proteomics).
Then, we simulated noise by adding up to 60 peaks of randomly selected masses. Lastly, we simulated a neutral loss of 17. 03 Da on the peptide mass of each spectrum. We provided the complete list of 'correct PSMs' as input to SpecGlobX i. e. , each simulated spectrum was associated with the peptide it derived from. Depending on the peptide's composition, simulated spectra in Dsim contain a range of one to Table  1  Performance of SpecGlobX measured on the simulated dataset Dsim. At first, we provided the full list of 'correct PSMs' as input to SpecGlobX: each simulated spectrum is associated with the peptide sequence it derives from (row 1). Then, we executed SpecGlobX on the PSMs returned by three different OMS methods (rows 2 to 4). Several percentages of correct identifications are summarized with and without (W/o) SpecGlobX.
Complementarity between SpecGlobX and existing OMS methods Secondly, we evaluated whether SpecGlobX improves the results provided by three existing OMS software: MODPlus  [14] , MSFragger  [9] , and SpecOMS  [23]. To this end, we first challenged each of these tools with Dsim spectra (see Additional file 1 for detailed parameters) and we examined each software's ability to interpret the mass modifications in the correctly identified PSMs. On one hand, MODPlus explains ∆M observed between Se and St by combining modifications stored in a predefined list (consisting of all or only a selection of modifications referenced in Unimod, or a list provided by the user). We have previously shown that this strategy is particularly efficient if the objective is to identify the maximum number of peptides carrying common or known in-advance modifications.
Similarly, the percentage of correct modifications relative to the number of expected modifications (based on the number of N and D in Dsim) is multiplied by two or three depending on the OMS software used. The limitation of SpecGlobX, therefore, is that even when the PSM is correct, only half of the modifications (53%) are perfectly identified and localized. This is not a surprise since some modifications cannot be corroborated without any a priori due to missing peaks. In addition, if two modifications are present on two adjacent amino acids, SpecGlobX is not able to distinguish them. Consequently, although a manual curation by an expert is still needed to remove ambiguities in the proposed alignments, SpecGlobX is helpful as a decision-support tool. SpecGlobX provides keys to interpret peptides carrying complex modifications, while this issue is still poorly considered by current open modification search software.
Alignments highlighted on the HEK293 dataset As a final evaluation, we ran SpecGlobX as a post-processing tool of SpecOMS on 24 spectra datasets generated from HEK293 cells  [24]  downloaded from PRIDE (PXD001468). This collection of spectra datasets has been used several times to evaluate open modification search methods. We converted the raw spectra files into the MGF format with msConvert release 3. 0  [28]  and obtained a list of PSMs using SpecOMS (configuration described in Additional file 1). Next, we divided the PSMs into three groups according to ∆M (∆M < 0, ∆M = 0, ∆M > 0) and filtered the PSMs to comply with an FDR < 1% computed separately for each group using a target-decoy approach. Overall, 429,703 spectra were validated, among which 149,794 had a positive ∆M and 16,545 a negative ∆M.