dataesr/scientific-paragraphs-categorization huggingface dataset:
7% (64/309) deletions, 9% (28/309) duplications, 1. 6% (5/309) insertions, and 1. 3% (4/309) insertion/deletions. More than 50% (156/309) of WFS1 variants are missense variants, 19% are frameshifts (60/309), and 16. 5% are nonsense changes (51/309). Inframe deletions, duplications, insertions, and indels made up 11. 6% (36/309) of the variants, and eight (2. 6%) affect putative splice or regulatory sites. Of the missense variants in the database, 57% (89/156) are predicted to be pathogenic, 32% (50/156) are likely pathogenic, five (3%) are benign/likely benign, and 7. 7% (12/156) are variants of uncertain significance. Twenty-nine of the missense variants are known to have an autosomal-dominant mode of inheritance, 28 are involved in sensorineural hearing loss, and one variant (c. 1385A>G; p.
Glu462Gly) is associated with autosomal-dominant congenital nuclear cataracts. Private variants (reported once or present in single family or small population) account for 43% (133/309) of the total unique variants in the WFS1 database. The majority of the variants reported (86%; 264/309) are located in exon 8. Most commonly reported variants are c. 1362_1377del (p. Tyr454*) reported 35 times in 18 patients, c. 1243_1245del (p.
Pro16 92Leufs*39), and c. 6901del (p. Val2301Trpfs*43). The c. (7677+ 1_7678-1)_(10387+1_10388-1)del (p. Gly2560Serfs*46) identified in intron 9, a 362-bp deletion c. 845brk6_8817del (p. Thr2819Argfs*29) was identified in exon 10 and c. 11738dup (p. Ser3914Lysfs*6) was found in exon 18. Bonnycastle et al. (2013)nts in 59 UK WS patients from 48 families (Table3) referred to the West Midlands Regional Genetic Service, Birmingham Women's Hospital and Department of Medicine, Padua University, Italy. All novel variants identified were submitted to the EURO-WABB database (https://lovd. euro-wabb. org). The significance of the missense variant c. 3392C>G (p. Ala1131Gly) was unclear, although it is predicted to be probably damaging by the PolyPhen-2 algorithm. In the patient, this variant occurs in the homozygous state together with a homozygous pathogenic frameshift-causing deletion (c.
1% formic acid for the last 6 min. Spray voltage was set at 1. 6 kV; heated capillary was adjusted to 270 • C. Survey full-scan MS spectra (m/z = 400-1,600) were acquired with a resolution of 70,000 after accumulation of 10 6 ions (maximum filling time 200 ms). The 10 most intense ions were fragmented by higher-energy collisional dissociation after accumulation of 10 5 ions (maximum filling time 50 ms). MS and MS/MS data were acquired using the software Xcalibur (Thermo Scientific). (3) Data analyses: RAW files were processed using MaxQuant, version 1. 5. 1. 2 (Cox and Mann, 2008). Spectra were searched against the Uniprot database (Mus musculus taxonomy, March 2015 version) and the frequently observed contaminants database embedded in MaxQuant. The I = L option was activated. Trypsin was chosen as the enzyme and 2 missed cleavages were allowed.
Peptide modifications allowed during the search were: carbamidomethylation (C, fixed), acetyl (Protein N-ter, variable) and oxidation (M, variable). Minimum number of unique peptides was set to 1. The matching between runs option was activated. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDEpartner repository  (Vizcaino et al. , 2016)  with the dataset identifier PXD004215. (4) Statistical analyses: The following steps were mainly performed using the Perseus toolbox (version 1. 5. 1. 6) available in the MaxQuant environment. Proteins identified in the reverse and contaminant databases, identified with less than 2 razor + unique peptides, or exhibiting less than 6 iBAQ values in one condition (3 biological replicates with 2 analytical replicates each for control and p140Cap co-IPs) were discarded from the list.
Protein lists from those studies were curated, mapped to stable IDs (Entrez, Uniprot, MGI) for human and mouse and combined into single list containing only unique protein/gene name, IDs and publication source (PMID). Summary data for the 35 publications with associated metadata (PMID, year, method, species and number of proteins found) are presented in Supplementary Table  S2 ). Enrichment analysis of annotation in the interactome was performed in R, specifically using the Bioconductor package ClusterProfiler for Gene Ontology (GO) and KEGG enrichment analysis  (Yu et al. , 2012)  and Bioconductor ReactomePA package for pathway over-representation analysis (http://bioconductor. org/packages/release/bioc/html/ReactomePA. html). For each enrichment type (GO, KEGG, Reactome), two background sets of proteins were used: (1) the default mouse genome list from Bioconductor and (2) our list of 6688 published synaptic proteins-to reveal the consistency in enriched terms.
p-values, adjusted for multiple comparison p. adjust and q-values for false discovery rates (FDR) are provided in Supplementary Table  S3. For disease enrichment the annotation data were standardized using MetaMap  (Aronson and Lang, 2010)  and NCBO Annotator  (Whetzel et al. , 2011; Musen et al. , 2012)  to recognize terms found in the Human Disease Ontology (HDO)  (Schriml et al. , 2012)  Recognized enriched disease ontology terms were then associated with gene identifiers and stored locally. Disease term enrichment' , for the p140Cap dataset' , could then be calculated using the Topology-based Elimination Fisher method  (Alexa et al. , 2006)  found in the topGO package (http://topgo. bioinfmpi-inf. mpg. de/), together with the standardized OMIM and Ensembl variation gene-disease annotation data (14111 genedisease associations), mapped onto the full HDO tree.
A PSD network was constructed from a list of 1,443 proteins obtained from a study of the PSD in the human brain  (Bayes et al. , 2011). Protein-protein interactions were obtained by mining publicly available databases: HIPPIE  (Schaefer et al. , 2012) , BioGRID  (Chatr-Aryamontri et al. , 2015) , IntAct  (Kerrien et al. , 2012) , and performing an InterologWalk over different species using Bio::Homology::InterologWalk  (Gallone et al. , 2011). The connected PSD network consists of 1,312 proteins and 8,031 protein interactions (i. e. , 131 proteins could not be connected into the network). This PSD network was clustered making use of the spectral properties of the network; the network being expressed in terms of its eigenvectors and eigenvalues, and partitioned recursively (using a fine-tuning step) into communities based on maximizing the Modularity clustering measure  (Newman, 2006; Simpson et al.
, 2010). Where first we found the node which, when moved from one community to the other, gave the maximum change in Modularity. This node's community was then fixed and we repeat the process until all nodes had been moved. The whole process was repeated from this new state until the change in the Modularity, between the new and old state, was less than the predefined tolerance. The modularity of the full PSD network was found to be 0. 36. Robustness of the full PSD network communities was assessed by running the algorithm 500 times, randomly selecting 80% of the network node set and related interactions each time. The package clusterCons  (Simpson et al. , 2010)  was used to build a consensus matrix from which to test the robustness of the communities, and proteins found inside the communities.
Synaptic Localisation of p140CAP Complexes with Comparative Study of Reported Synaptic Datasets To further map the p140Cap interactome, we searched published neuronal proteome datasets for p140Cap and its interactors. We found that p140Cap was reported in the majority of the published PSD datasets (Supplementary Table  S2 ). In a few co-IP studies, p140Cap was detected in complexes with PSD95  (Dosemeci et al. , 2007) , mGluR5  (Farr et al. , 2004) , Chmpb2  (Chassefeyre et al. , 2018) , and Snap25  (Fossati et al. , 2015). Further, we searched for the 351 identified interactors of p140Cap across the published PSD proteomic datasets and found an exceptionally high enrichment (order of E-14 of significance in average) (Supplementary Table  S2 ). We also sought to verify whether p140Cap and associated proteins were found in presynaptic preparations as well, and we found that p140Cap was detected in the presynaptic compartment in several studies  (Gronborg et al.
, 2010; Boyken et al. , 2013; Weingarten et al. , 2014). Specifically, it was detected in complexes with Rims1, Syn1-2-3, Git1, and Wasf1 in co-IP experiments on presynaptic protein complexes (August B Smit, personal communication). However, it was not reported in other studies focusing on synaptic vesicles (SV) or SVrecycling proteins  (Morciano et al. , 2005 (Morciano et al. , , 2009;; Gorini et al. , 2010; Brinkmalm et al. , 2014; Wilhelm et al. , 2014). p140Capinteracting proteins, in turn, were found enriched in presynaptic datasets, although with a lower score than that found in postsynaptic studies (Supplementary Table  S2 ). Therefore, our proteomic data, in agreement with previous studies, place p140Cap mainly, but not exclusively, in the PSD. We then examined all the p140-interacting proteins to evaluate their distribution between pre-and postsynaptic complexes.
The two lists showed a high degree of overlap, which was expected since the majority of synaptic proteins are found in both compartments. Figure  2A  shows the distribution of the p140-interacting proteins between PSD (5023 proteins from 25 postsynaptic studies and presynaptic compartment (1215 proteins from 9 presynaptic studies). 334 of the 352 p140Cap interactors overlap with these datasets. Of these proteins, none were described as specifically presynaptic, whereas the majority was described as specifically postsynaptic (247) or found in both compartments (87). This further supports a predominantly postsynaptic localization of the p140Cap complexes. The presence of p140Cap in the PSD has been previously shown in rat synaptic fractionation, where it is enriched in the PSD fraction together with PSD95  (Mclean Colin et al.
Functional Enrichment Analyses of the p140CAP-Containing Protein Complexes To obtain a functional perspective of the p140Cap interactome, we tested its enrichment against KEGG, GO ontology and Reactome databases (Supplementary Table  S3 ). We ran analysis against two reference (background) lists: (1) the default mouse genome list provided by Bioconductor and (2) a combined list of 6688 proteins from published synapse proteomics studies, to reveal more specific p140Cap associated terms compared to the whole synaptosome. Both reference lists demonstrated a very high level of consistency in top enriched terms. However, using the synaptic as background gives more conservative (i. e. , lower) significance values for enriched terms. The full lists for enrichment results are presented in Supplementary Table  3.
81E-15), "actin cytoskeleton organization" (P = 4. 37E-11), "regulation of synaptic plasticity" (P = 1. 96E-09) and "regulation of protein complex assembly" (P = 3. 63E-06) (Supplementary Table  S3 ). Analysis of enrichment against the Reactome pathway database revealed the overrepresentation for "Transmission across Chemical Synapses" (P = 7. 05E-15), "Unblocking of NMDA receptor, glutamate binding and activation" (P = 4. 90E-10), "Cell-cell junction organization" (P = 1. 44E-08), "Ras activation upon Ca influx through NMDA receptor" (P = 2. 49E-08), "L1CAM interactions" (P = 1. 00E-07) (Supplementary Table  S3 ). To classify proteins into functionally related modules, we checked for the correlation between the experimentally measured protein abundances and Reactome pathway terms for the top 174 interacting proteins with the highest significance.
The p140CAP Interactome within the Structure of the PSD Given the enrichment in PSD (Figure  2A ), we examined previously described PSD protein network models to assess whether the p140Cap-interacting proteins form structural composites within the PSD or are rather randomly distributed throughout the network. We built a protein-protein interaction (PPI) network based on a human PSD protein dataset combined with the interaction data from several public databases (see  Materials and Methods and Mclean Colin et al. , 2016  for details). Spectral cluster analysis was performed on the network as described in  Mclean Colin et al. (2016). Within the PSD network of 1,312 proteins, we identified 60 structural clusters based on the network topography. Essentially each cluster contains proteins that are more densely connected to other proteins within the cluster than to proteins elsewhere in the network (Figure  4 ).
Disease Enrichment of p140Cap Related Proteins Synaptic dysfunction has emerged as a common theme in neurological and psychiatric disorders, and recent large-scale genetic studies in ASD and schizophrenia  (De Rubeis et al. , 2014 ;   Fromer et al. , 2014)  have further strengthened this hypothesis. The pathophysiological mechanisms might include abnormal expression of discrete synaptic proteins or the inability to organize into functional macromolecular complexes  (Bayes et al. , 2011). We investigated the disease enrichment of the genes encoding p140Cap interacting molecules (351 genes), using genedisease annotation data collected from OMIM (http://omim. org/) and Ensembl variation  (Chen et al. , 2010)  databases mapped onto the HDO tree using the topOnto package (https:// github. com/statbio/topOnto).
These analyses yielded a core background list of 14,111 gene-disease associations mapped onto 1,491 HDO terms. We also considered lists of risk genes and loci emerged from recent studies, including ASD  (Sanders et al. , 2015) , epilepsy (EuroEPINOMIC-RES Consortium, 2014), Bipolar Disorder  (Kataoka et al. , 2016)  and Schizophrenia  (Fromer et al. , 2014; Schizophrenia Working Group of the Psychiatric Genomics, 2014). The 826 gene-disease associations resulting from these analyses were then merged with the annotation set from the databases, yielding a total of 14,357 genedisease associations mapped onto 1,491 HDO terms. Using the Topology-based Elimination Fisher method  (Alexa et al. , 2006) , we found that the p140Cap dataset is significantly enriched for genes associated with schizophrenia (P = 2.
Again, our results locate it in the p140Cap synaptic network. There is robust evidence supporting the hypothesis that synaptic dysfunction is a shared mechanism underlying a broad range of brain disorders, and our data further corroborate it. For example, alterations in glutamatergic transmission can result in a broad spectrum of psychiatric conditions. In our dataset, we detected AMPA and NMDA receptor subunits associated with schizophrenia (i. e. , GRIA1 and GRIN2A) and with a spectrum of DD/ID, ASD and seizures, often in co-morbidity (GRIA3, GRIN1, GRIN2A, and GRIN2B). Glutamatergic transmission is intertwined with synaptic calcium dynamics  (Higley and Sabatini, 2012) , and large-scale genetic studies have shown that disruption of voltage-gated calcium channels is a pathological mechanism across psychiatric disorders (Cross-Disorder Group of the Psychiatric Genomics, 2013).
Notably, this pathway holds potential for rapid therapeutic intervention  (Lencz and Malhotra, 2015). Seven VGCC subunits were found in the p140Cap interactome and four of them are associated to disease. CACNA1A haploinsufficiency can cause episodic ataxia type 2 (MIM 108500), familial hemiplegic migraine type 1 (MIM 141500) and spinocerebellar ataxia 6 (MIM 183086). More recently, CACNA1A mutations have been described in individuals diagnosed with ID, epilepsy, ADHD and/or ASD  (Damaj et al. , 2015). CACNA2D1 and CACNA2D2 are both associated with epilepsy and ID  (Edvardson et al. , 2013; Pippucci et al. , 2013; Vergult et al. , 2015) , while CACN2D3 has been recently implicated in ASD  (De Rubeis et al. , 2014). Interestingly, none of the reproducible GWAS-associated loci in schizophrenia CACNA1C, CACNA1H, and CACNB2 (Schizophrenia Working Group of the Psychiatric Genomics, 2014) was detected in our dataset.
In mice lacking PSD-95, NMDA-dependent LTP and LTD frequency is shifted to enhanced LTP, consistent with severely impaired spatial learning  (Migaud et al. , 1998). Mice mutant for Shank proteins exhibit a large spectrum of defects in LTP and LTD  (Yoo et al. , 2014). Identifying the molecular complexes controlling forms of plasticity that underlie memory consolidation and retrieval has direct implications for ID and associated co-morbidities, including ASD and ADHD. It is also important for psychiatric disorders with a cognitive impairment component and/or with a premorbid cognitive deficit, as documented in schizophrenia  (Reichenberg et al. , 2010). As mentioned above, SRCIN1 has not been genetically associated with psychiatric disorders. A de novo missense variant resulting in a p. Glu912Asp change predicted to be probably damaging by the bioinformatic predictor Polyphen-2 and not detected in the 60,706 unrelated controls of the Exome Aggregation Database (ExAC) was found in a schizophrenia cohort  (Fromer et al.
PCR product sequencing and sequence analyses were carried out as described by  Jacques et al. (2016). The genomes of the first three strains isolated were sequenced using Illumina Mi-Seq technology (Plateforme G enomique de Nantes, IRT-UN, France). Phylogenetic analyses were performed on the dataset of concatenated sequences obtained in this work and available from previous analyses for a collection of strains representing the X. fastidiosa diversity as previously described  (Jacques et al. , 2016). Briefly, sequence alignment was performed with the MUSCLE algorithm using the default parameters in GENEIOUS v. 8. 0. 5 (www. geneious. com), and a maximum likelihood (ML) tree was constructed with 1000 replicates for bootstrap values using MEGA v. 6. 0 (www. me gasoftware. net).
sandyi ST76 was identified in three coffee plants in Ile de France. Xylella fastidiosa subsp. pauca ST53 was detected in four samples of coffee plants intercepted in the Ile de France and Pays de la Loire regions. The strains from the remaining infected plants could not be assigned to sequence types because several housekeeping genes could not be amplified and/or the sequences could not be obtained. In some cases, partial data suggest a possible infection by X. fastidiosa subsp. sandyi ST72 or ST76 (data not shown).
S2 ). Interestingly, such ambiguous positions were usually discriminant between several alleles described in the pubmlst database. Because of these chromatogram overlaps at strategic positions, no allele could be assigned. These undetermined STs may result from the simultaneous presence of distinct X. fastidiosa strains in the same plants. The allele numbers indicate the concomitant presence in these samples of X. fastidiosa ST6, ST7, ST22, ST41 or ST76 and/or recombinants of these STs. Indeed, all four undetermined STs are suspected to possess alleles that can be found in these five STs (Table  S1 ). As indicated above, one plant of P. myrtifolia was infected by ST76 in a geographical  area where X. fastidiosa subsp. multiplex ST6/ST7 were preponderant. The presence of other STs was not observed but cannot be formally excluded.
Additional evidence of sympatry came from the isolation of the two X. fastidiosa strains ST6 and ST7 from one plant (Cistus monspeliensis) collected in 2016 (data not shown). In the same vicinity in 2015, the simultaneous presence of distinct X. fastidiosa strains in the same plants had been observed. Taken together, these data clearly indicate that several distinct populations are currently living in sympatry in France. At least one gene fragment could not be properly amplified and/or sequenced in 117 samples, resulting in incomplete typings. The partial results obtained for these samples indicated contamination by ST6, ST7 or recombinants between one of these two STs and ST76. In addition, some samples that had incomplete typings had been classed as undetermined (C t values from 35 to 40) when identifying them as X.
Acknowledgements N. D. was funded by regional funds provided by Objectif V eg etal. The work carried out at  INRA  has received funding from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement  635646 ,  POnTE (Pest Organisms Threatening Europe). The present work reflects only the authors' view and the  EU  funding agency is not responsible for any use that may be made of the information it contains. The authors greatly acknowledge SRAL, FREDON, DSF, DDSCPP for sampling in Corsica and PACA;  Dimitri Molusson ,  Sandrine Paillard ,  Christ ele Dousset ,  Antoine Sainte-Luce ,  Virginie Juteau ,  David Agud-Miguel ,  Christelle Franc  ßois, Car ene Rivoal and  Corinne Audusseau ,  LSV-ANSES at Angers , for sample analyses, bacterial isolations and identifications;  Pauline de Jerphanion  for quantitative data on hosts;  Yannick Blanchard  and  Fabrice Touzain ,  ANSES at Ploufragan , for participating in library construction and handling strains for genome sequencing;  J erôme Gouzy  and  S ebastien Carr  ere,  CATI-BBRIC , for genome sequence assembly and annotation.
To unequivocally confirm that 3Ce is a 1 S 0 complex we subjected it to X-ray absorption spectroscopy techniques. The X-ray photoemission spectroscopy (XPS) of 3Ce is weak because the cerium is a small component of the 151-atom structure, but it exhibits a spectrum characteristic of cerium(IV) in the energy range 870-930 eV (Supplementary Fig. 8 ). The X-ray absorption near-edge spectroscopy (XANES) of 3Ce reveals two absorptions characteristic of cerium(IV)  53  , (Fig. 3d ), and when all characterization data are taken together the self-consistent picture that emerges is that 3Ce is a closed-shell singlet cerium(IV). Solid-state structures. The solid-state structures of 3Ce, 3U and 3Th were determined by single crystal X-ray diffraction and were found to be essentially isostructural. Complex 3Ce is illustrated in Fig.
Methods General. Experiments were carried out under a dry, oxygen-free dinitrogen atmosphere using Schlenk-line and glove-box techniques. All solvents and reagents were rigorously dried and deoxygenated before use. Compounds were variously characterized by elemental analyses, electrochemistry, NMR, Fourier transform infrared spectroscopy (FTIR), EPR, XANES and UV/Vis/NIR electronic absorption spectroscopies, single crystal X-ray diffraction studies (Supplementary Data 1-11), Evans methods and SQUID magnetometry, and DFT, NBO, QTAIM, CASSCF and RASSCF computational methods. Synthesis of [Ce(BIPM TMS ) 2 ][K(18C6)(THF) 2 ] (2Ce). THF (15 ml) was added to a precooled ( À 78 °C) mixture of 1Ce (1. 41 g, 1. 17 mmol) and [K(CH 2 Ph)] (0. 15 g, 1. 17 mmol). The resulting orange suspension was allowed to slowly warm to room temperature with stirring over 16 h to afford an orange solution.
Acknowledgements We are grateful to the  Royal Society , the  UK Engineering and Physical Sciences Research Council , the  Marie Curie IIF Scheme , the  European Research Council , The  University of Nottingham ,  The University of Manchester , the  UK National Nuclear Laboratory  and  COST Action   CM1006  for generous support and funding, the  National Service for Computational Chemistry Software  for access to the  Columbus HPC facility  and the  UK EPSRC National EPR Facility. We thank  Dr Emily Smith  ( University of Nottingham ) for recording the XPS spectrum of 3Ce.