dataesr/scientific-paragraphs-categorization huggingface dataset:
However, it does not accept different input or output formats like IUPAC, WURCS (Web3 Unique Representation of Carbohydrate Structures), which would make the tool more versatile. LiGraph. LiGraph  [35]  (http://www. glycosciences. de/tools/ LiGraph/) is an online tool based on the concept of schematic drawings of oligosaccharides to display glycan structures. This tool also renders images of glycans in different notation using a text input. The input for the carbohydrate structure consists of a list of names and connections. The glycan structure is output in the specified notation: either ASCII IUPAC sugar nomencla-fonts, and turn off the linkage annotations or change their orientation; all of which increases the usability of the software. The input structure can be further used to search the GlyTouCan  [34]  database to explore the literature details related to the input structure.
GlycoGlyph is an efficient tool for sketching or building glycans with a highly usable interface that can significantly help researchers to improve the uniformity in glycan formats in literature/manuscripts. It can also be a tool of choice for text mining for the query structure. GlycanBuilder2. GlycanBuilder2  [40]  is a Java-based glycan drawing tool which runs locally as an application on different platforms including Windows, macOS and Linux. It is freely available for downloading at http://www. rings. t. soka. ac. jp/ downloads. html. GlycanBuilder2 is a newer version of Glycan-Builder  [20]  with additional features. This version is capable of supporting various ambiguous glycans consisting of monosaccharides from plants and bacteria. The tool uses the SNFG notation to display glycan structures.
Moreover, this updated version can convert a drawn structure into WURCS sequences for further use as a query for glycan search or registration in databases like GlyTouCan. GlycanBuilder2 provides an excellent interface (Figure  6 , top) for glycan drawing. Glycan structures can be drawn manually using the mouse or by importing text input files. The interface provides a list of templates: N-Oglycans, glycosphingolipids, glycosaminoglycans(GAGs). Rows of CFG notations for monosaccharides assist with glycan structure drawing on canvas. The application also supports the glycan symbol notations for the University of Oxford (UOXF) format. The input complies with various linear sequence and text formats. They include GlycoCT , GLYcan structural Data Exchange using Connection Tables (GLYDE-II), Bacterial Carbohydrate Structures DataBase (BCSDB)  [41] , carbohydrate sequence markup language (CabosML)  [42] , CarbBank  [43] , LinearCode  [44] , LINUCS, IUPAC-condensed and Glyco-suiteDB  [45].
The output yields structures in the following formats: GlycoCT, LinearCode, GLYDE-II and LINUCS. Thus, GlycanBuilder2 is a versatile tool which can be used for glycan sketching or building and also as a glycan sequence converter from one format to another. Original GlycanBuilder. GlycanBuilder  [10, 20]  was originally part of the GlycoWorkbench platform  [49]. This interface is integrated in most tools of the Glycomics@ExPASy collection that require a drawing interface to query data. Glycan-Builder is written in Java Programming language and can be used as standalone or as an applet for embedding in web pages for glycan search. For example, GlycanBuilder is integrated in SugarbindDB  [50]  to draw glycan structures and search the database (https://sugarbind. expasy. org/builder), and in GlycoDigest or GlyS3  [10, 20]  to define the input of these tools.
Glycano. Glycano (available at http://glycano. cs. uct. ac. za) is a software tool for drawing glycans. This tool is based on JavaScript, which can be used without the requirement of any server or browser dependency. The interactive interface allows sketching via the drag-and-drop method on canvas (with or without grid). The software is provided with "UCT" and "ESN", interchangeable interfaces (Figure  7 , middle) with different symbols for monosaccharides. These names (UCT and ESN) correspond to the University of Cape Town, South Africa, where Glycano was developed, and to the "Essentials of Glycobiology Symbol Nomenclature", precursor of the SNFG symbol set  [55]. The interface provides a wide choice of monosaccha-rides and substituents represented in SNFG symbols but lacks the standard colour scheme.
The user can easily modify the structure with by click and drag, which allows to either cut/ copy, delete or move a portion of the structure. The drawn structure can be saved in text format, in. gly format or as an image (PNG and SVG formats). A drawback to note is that linking the monosaccharides at specific positions is only possible in the UCT mode, which means that back-and-forth between the two symbol systems is necessary to define the linkages correctly. Despite some drawbacks, this is an excellent tool due to its ease-of-use, tenable degree of freedom, and functionalities/options for sketching and building glycan structures. GlycoEditor. GlycoEditor  [19]  (available at https://jcggdb. jp/ idb/flash/GlycoEditor. jsp) is an online software for drawing glycans. Through a straightforward interface, three ways of input are possible: by JCGGDB ID, through a library of common oligosaccharides and by direct input.
A list of most common monosaccharides is presented, and the rest can be found categorised by family. The click and drag addition of new monosaccharides trigger the selection of linkage-type and configuration (Figure  7 , bottom). The tool provides an option to create repeating units. Additionally, several functionalisation options are also available. Once the structure is ready, the user can save it as an. xml file. GlycoEditor allows searching a given structure across many databases in four ways: exact structure match (with or without anomer and linkage specifics) and the same for substructure match. The central database featured is the JCGGDB, to which can be added, among others: Glaxy, GlycomeDB, GlycoEpitope, GMDB, KEGG, etc. Searching by ID is also possible. GlycoEditor is a now dated tool that allows efficiently building glycans and performing databases searches.
The simplest method for drawing involves a selection of monosaccharides and glycosidic linkages from an available list to generate a glycan structure. Alternatively, a text box option provides a way to draw uncommon types of monosaccharides. The tool also contains templates from KEGG GLYCAN and their importation using their accession number. Besides, input files in KCF can be used while the output can be saved in LINUCS, KCF or an image in PNG format (Figure  8 , bottom). The glycan structure in text format can be further used as a query for search in KEGG GLYCAN and CarbBank databases. Hence, KegDraw can be an option for the freely available tool for drawing and querying chemical structures. However, there are similar tools already available for glycan drawing with more advanced and acceptable notations.
Glycan builders Sweet II. Sweet [58]  is a web-based program for constructing 3D models of glycans from a sequence using standard nomenclature accessible at http://www. glycosciences. de/modeling/ sweet2/doc/index. php (Figure  9 , top). This tool is available as a part of the glycosciences. de website, which also provides other options for analysing glycans in three-dimensional space. This program uses a glycan sequence in a standard format and generates a 3D model in the form of a. pdb file. The glycan input can come from a library of relevant oligosaccharides, available through one of the sub-menus. Alternatively, manual input is possible in three platforms adapted for increasing complexity. The model can be further minimised using MM2  [59]  and MM3  [60]  methods. The 3D models can be viewed using molecular viewers like JMol, WebMol-applet, Chemis3D-applet, etc.
A useful feature of this tool is the real-time rendering of the carbohydrate image: each added monosaccharide and modified linkage is directly reported to the image as well as to a text (GRS) format. Option for numerous chemical modifications is also available. On the other hand, the Glycan Modeler allows in silico N-/Oglycosylation for glycan-protein complexes and generates a "most relevant" glycan structure through Glycan Fragment Database (GFDB)  [68]  search which gives proper orientations relative to the target protein. In the absence of target glycan sequence in GFDB, the structures are generated by using the valid internal coordinate information (averaged phi, psi, and omega glycosidic torsion angles) in the CHARMM force field. Input files for CHARMM can be generated for the purpose of MD simulation.
Amongst other possible outputs, 3D representations of the glycans are available as. pdb files. This tool can be helpful for researchers to generate 2D depictions of a glycan and then obtain the corresponding 3D representation, which can be useful for modelling studies of glycans and glycoconjugates. doGlycans. doGlycans  [69]  is a compilation of tools dedicated for preparing carbohydrate structures for atomistic simulations of glycoproteins, carbohydrate polymers and glycolipids using GROMACS  [70, 71]  In the form of Python scripts; the tools are used to prepare the system, which generally includes the processing of a. pdb file using the pdb2gmx tool. Subsequently, a glycosylation model can be prepared for carbohydrate polymer simulation using the prepreader. py script. Similarly, the doglycans.
py script can be used to develop models for glycoproteins and glycolipids. Together, these tools are called doGlycans toolset. Although doGlycans is highly flexible, it only uses the sugar units that are defined in GLYCAM. The topologies generated for glycosylated proteins and glycolipids are compatible with the OPLS  [72]  and AMBER  [73]  force fields. The topology for carbohydrate polymers is based on the GLYCAM force field. The user needs to provide the ceramide topology as input to generate the topologies for glycolipids. The tools contained in doGlycans create 3D models and simulation files as a starting point for more complex molecular simulation studies. [63]  interface which accepts a text input for glycans and generates 3D models. CHARMM-GUI (Glycan reader and Modeler)  [64]  interface with a 3D structure output generated using a glycan sequence as input.
RosettaCarbohydrate. Rosetta is a software suite for macromolecular modelling as an extensive collection of computer code mostly written in C++ and Python languages. Rosetta is available to academic and commercial researchers through a license available at https://www. rosettacommons. org/software/ license-and-download. The licence is free for academic users. The tool runs best on Linux or macOS platforms only. It can be installed on a multiprocessor computing cluster to increase efficiency. RosettaCarbohydrate  [74, 75]  tool provides the methods for general modelling and docking applications for glycans and glycoconjugates. The application accepts the standard PDB, GLYCAM, and GlycoWorkbench (. gws) file formats and the available utilities (codes) helps with the general problems in sampling, scoring, and nomenclature related to glycan modelling.
It samples glycosidic bonds, ring forms, side-chain conformations, and utilises a glycan-specific term within its scoring function. The tool also consists of utilities for virtual glycosylation, protein-glyco-ligand docking, and glycan "loop" modelling. This tool is best for the researcher with basic knowledge and skills to work with a command-line interface (Linux). PolysGlycanBuilder. PolysGlycanBuilder  [76]  is a web-based tool (http://glycan-builder. cermav. cnrs. fr/) with an interactive and more usable interface (Figure  10 ). The software translates a glycan sequence or polysaccharide repeat unit into the coordi-nate set of the corresponding tertiary structure, in one or several of its low energy conformations. The construction follows an intuitive scheme which is as close as possible to the way glycoscientists draw the sequence of their structures.
The simplest method for model building involves dragging and dropping monosaccharide units to the canvas or workspace grid. The software displays rows of monosaccharides in the form of standard SNFG symbols with 3D information (furanose/pyranose shape, configuration, anomericity, and ring conformation). Glycosidic linkages can be easily defined, as the values of the dihedral angles (Φ, Ψ, Ω). They can be manually set or extracted from a database of low energy conformations of 600 disaccharide segments. The monosaccharides have been subjected to geometry optimisation using molecular mechanics approach. For a given input sequence, the corresponding 3D coordinates are generated at the PDB format. Within the process of construction, the structure is displayed via the LiteMol and eventually optimised to remove any steric clashes.
3D-SNFG VMD interface and visualisation algorithms. The recently introduced 3D-Symbol Nomenclature for Glycans (3D-SNFG)  [15]  allows the representation of carbohydrates in an unusual way: the SNFG symbols are added to a three-dimensional structure. The 3D-SNFG script must be integrated into the visual molecular dynamics (VMD)  [21, 78]  viewer software to enable the representation of glycans as large SNFG-matching3D shapes that can either replace the molecular monosaccharides or stay lodged at the geometric centre of the cycle (Figure  11 , top left). Upon the input of a glycan-containing structure (in PDB format), the integrated script in VMD automatically recognises the common monosaccharide names and generates the 3D shapes. The embedded script also enables shortcuts keys from keyboard to quickly change between large and small 3D-SNFG shapes and also label the reducing terminus.
This tool is based on Python and provides additional computing environment within the PyMOL package. The tool is provided with a template list of saccharide structures to facilitate structure building and visualisation. The interface provides three option menus to assist glycan structure building. The two first options help to specify residues to be connected from a list of available templates, and the third one allows selection of the chemical bond between the residues. The visualisation using PyMOL includes three cartoon-like representations. These display modes provided in the tool simplify the representation of glycan structures in cartoon, wire and bead representations. In cartoon and wire representations, the rings in sugars are shown as non-flat polygons connected by rods while in the bead representation mode, these cycles are represented as a sphere.
In addition of visualization of static structures, the tool also allows analysis of trajectories of MD simulations. The tool can be used for conformational search using a Monte Carlo approach  [86]. The conformational search is done by perturbing a torsional angle, followed by an energy minimization using the MMFF94 force field. Azahar is freely accessible from http:// www. pymolwiki. org/index. php/Azahar. UnityMol/SweetUnityMol. Sweet UnityMol  [32]  is a molecular structure viewer (Figure  11 , middle) developed from the game engine Unity3D. The software is available for free download (https://sourceforge. net/projects/unitymol/files/ UnityMol_1. 0. 37/) from the SourceForge project website. It can be installed in Mac, Windows and Linux platforms. The program reads files in PDB, mmCIF, Mol2, GRO, XYZ, and SDF formats, OpenDX potential maps and XTC trajectory files.
Funding This research was performed within the framework of the  PhD4GlycoDrug Innovative Training Network and  was funded from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement No  765581. The work was supported by the  Cross-Disciplinary Program Glyco@Alps, within the framework "Investissement d'Avenir" program  [ ANR-15IDEX-02 ].
Binding to mannose specific lectins The binding of the liposomes to ConA and BC2LA was evaluated as a function of their oligomannose structures. The Flu-Lip equipped with Tri-Man (1), Man-tri (4), PMan4 (6) and PMan5  (7)  showed better and similar apparent binding to ConA than with Man (3) (Figure  3A ). The binding profile was similar with BC2LA excepted that the binding of Man-tri-spa (5b) was lower than Man-tri (4b) (Figure  3B ). There was a weak binding of Glc (2b) due to a small affinity of ConA for α-D-glucosyl residues. In contrast, Glc (2b) did not interact with BC2LA. Thus, those oligomannose structures conserved their binding capacity to lectins after their linkage to the diether lipid and insertion in the lipid bilayer of liposomes. The results were in agreement with data reported in literature indicating that compared to MeαMan, the relative affinity to ConA of a tri-antenna mannopyranoside, PMan5 (7a), PMan4 (6a) and Man-tri (4a) was 16-, 20.
Acknowledgements We warmly thank  Dr. L. Landemarre  from  GLYcoDiag (Orléans, France ). We thank D. Gosset 1 , the P@CYFIC platform at  CBM  and  C. Baillou  3 for their technical assistance in flow cytometry. The authors acknowledge  Drs. D. Lesur  ( UMR 7378 ) and  S. Pilard  ( Plateforme Analytique, UPJV, France ) for MS and HPLC. This work was supported by grants from  "Région Centre Val de Loire " (APR IR 2015  VACARME  project),  European Community  (Univax:www. UniVax- FP7. eu). Haifei Gao received 2 years fellowship from "Région Centre Val de Loire " (APR IR 2015  VACARME  project). We certify that there is no conflict of interest, no competing interest and no disclosure.
Retro-Transcription (RT) and Quantitative PCR The SuperscriptTM II Transcriptase Reverse Kit is used for RT (Invitrogen, Carlsbad, CA, USA) GB. Reverse transcription was performed using 1 µg of total RNA. The RT-PCR reactions were performed, for selected genes (Table  1 ), according to the manufacturer's instructions using 2× MESA GREEN qPCR MasterMix Plus for SYBR 258 Assay (Eurogentech, Liège, Belgique) 96-well qPCR plate (Sarstedt, Nümbrecht, Germany), optical seal (Dutcher, Brumath, France), and the Mx3005PTM sequence detection system (Agilent technologies, Santa Clara, CA, USA). In each reaction, 10 ng of reverse transcripted RNA (based on initial RNA concentration) was used. All primers were used at 400 nM in a 20 µL reaction. Quantitative analysis was made based on the cycle threshold (Ct) value for each well and calculated using the MxPro software (Agilent technologies, Santa Clara, CA, USA).
05%). The reaction was amplified with Streptavidine-peroxydase (Interchim, Montluçon, France). Cytokines concentration was finally highlighted with the addition of OPD (10 mg/mL, Sigma-Aldrich, St Louis, MO, USA). After color development, the plates were read in a Multiskan spectrophotometer at 492 nm powered by Ascent™ Software v2. 06 (Multiskan RC Thermo Labsystems, Thermo Fisher Scientific, Waltham, MA, USA). The purified and biotinylated antibodies used were the following: Mouse anti-human IL2, rat anti-human IL6, rat anti-human TGFβ1, and mouse anti-IFN-γ (all from BD PharmingenTM, San Jose, CA, USA). Results were expressed in pg/mL as the mean of triplicates wells after subtracting background values.
Humanized SCID Mice Model All procedures were approved by the local Ethical Committee of the IPL performed with required permission of the regional governing ethical board (approval number CEEA 152010). Anesthetized SCID mice were subcutaneously xenotransplanted with an IVIS LUMINA XR reader (Caliper Life Sciences, Hopkinton, MA, USA). Mice were divided in four groups which received: Mothing, light only, PS2 only, PS2, and Light (PDT). For PS2 only and PDT condition 100 µL of a solution at 1 mg/mL of PS2 was injected intraperitoneally. Images were then analyzed under the Living Image 4. 1 software (Caliper Life Sciences, Hopkinton, MA, USA) and results were obtained after spectral unmixing according to the manufacturer's instructions. Measurements of tumor bioluminescence were acquired at different times: Day 1, 3, 5, 7, 9, 12 to monitor tumor growth, after i.
Statistical Analysis Data were analyzed using the statistical package GraphPad for windows 3. 0. 1. All quoted p-values are two-sided, with p ≤ 0. 05 (*), p ≤ 0. 001 (**), p ≤ 0. 0001 (***), and p ≤ 0. 00001 (****) being considered statistically significant for the first and highly significant for the others.
1c  and Supplementary Data 1. 4 and 1. 8). Deletions and duplications at both loci showed a mirror effect at the global connectivity level. 16p11. 2 deletions and duplications also showed mirror effects at the network level (p = 0. 006, two-sided). This was not the case for 22q11. 2 (Supplementary Notes). A sensitivity analysis showed that results are unaffected by differences in age distribution between deletions and control groups as well as the number of remaining frames available after scrubbing (see Supplementary Notes). Effects of CNVs on FC are twice as large as those of SZ and ASD. We performed three independent CWAS, comparing FC between patients with ASD, SZ, ADHD, and their respective controls. Idiopathic SZ showed overall underconnectivity affecting 835 connections, in line with previous reports  26, 31  (Fig.
ARTICLE For ADHD, none of the individual connections survived FDR correction (Supplementary Notes and Supplementary Data 1. 7 and 1. 8). Sensitivity analyses excluding females from the SZ and ADHD cohorts showed identical results (Supplementary Notes). Among idiopathic conditions, the effect size of connectivity alteration was the highest in SZ (largest beta value = -0. 56 std of the control group), followed by autism (largest beta value = -0. 46), and ADHD (largest beta value = +0. 26). Effect sizes observed for both deletions were approximately two-fold larger (beta values = +1. 34 and -1. 64 for 16p11. 2 and 22q11. 2 respectively) than those observed in idiopathic SZ, ASD, and ADHD (Fig. 2c ). The largest effect size among the 16 connections surviving FDR for the 22q11. 2 duplication was Cohen's d = 1.
Eight and six out of the top 10 regions altered by 22q11. 2 and 16p11. 2 respectively were driving similarities with psychiatric conditions (Supplementary Data 1. 8). Despite lower power, we investigated similarities with duplication FC-signatures. The number of significant regional similarities was smaller. Out of the 28 regions showing a similarity between idiopathic conditions and duplications, 17 regions also showed similarities with deletions (See Supplementary Notes). Individuals with ADHD did not show higher similarities with the regional FC-signatures of any CNVs except for 2 regional FCsignatures of the 16p11. 2 duplication (Supplementary Data 2. 5 and 2. 6). Similarity with CNV-FC signatures is associated to symptom severity. We investigated whether regional FC similarities with deletions described above are associated with symptom severity among individuals in idiopathic psychiatric cohorts.
The limited phenotypic data in the SZ group did not allow to investigate the relationship between deletion FC-signatures and cognitive traits in this sample. Lack of similarity observed for ADHD is line with the small association between 16p11. 2 CNVs and ADHD but is discordant with the association reported for 22q11. 2  5. ADHD has a smaller effect size than SZ and ASD, which may have limited our analysis  56. Several confounding factors may have influenced some of the results. Those include sex bias, which is present across all three psychiatric cohorts, age differences in the 16p11. 2 deletion group, diagnosis of ASD and ADHD in 22q11. 2 deletion carriers, and medication status in the idiopathic ASD and SZ groups. However, carefully conducted sensitivity analyses, investigating all of these confounders did not change any of the results.