dataesr/scientific-paragraphs-categorization huggingface dataset:
The mean expression for each gene in each cell type was computed from the single-cell expression data (if not provided). For the Zeisel dataset  109  , we used the mean expression at level 4 (39 cell types from 19 regions for the mouse nervous system). For the Saunders dataset  110  , we computed the mean expression of the different classes in each of the 9 different brain regions sampled (88 cell types in total). We filtered out any genes with non-unique names, genes not expressed in any cell types, non-protein coding genes, and, for mouse datasets, genes that had no expert curated 1:1 orthologs between mouse and human (Mouse Genome Informatics, The Jackson laboratory, version 11/22/2016, http://www. informatics. jax. org/downloads/reports/index. html#homology), resulting in 16,472 genes.
Gene expression was then scaled to a total of 1 million UMIs (unique molecular identifiers) (or transcript per million (TPM)) for each cell type/tissue. Using a previously described method  38  , a metric of gene expression specificity was calculated by dividing the expression of each gene in each cell type by the total expression of that gene in all cell types, leading to values ranging from 0 to 1 for each gene (0 meaning that the gene is not expressed in that cell type and 1 meaning that all of the expression of the gene is in that cell type). We then selected the top 10% most specific genes for each cell type/tissue for enrichment analysis. MAGMA v1. 08  37  was used to test gene-set enrichment using GWAS summary statistics, covarying for gene size, gene density, mean sample size for tested SNPs per gene, the inverse of the minor allele counts per gene and the log of these metrics.
We excluded any SNPs with INFO score <0. 6, with MAF < 1% or with estimated odds ratio > 25 or smaller than 1/25, as well as SNPs located in the MHC region (chr6:25-34 Mb). We set a window of 35 kb upstream to 10 kb downstream of the gene coordinates to compute gene-level association statistics and used the European reference panel from the phase 3 of the 1000 genomes project as the reference population  113. We then used MAGMA to test whether the 10% most specific genes (with an expression of at least 1 TPM or 1 UMI per million) for each cell type/tissue were associated with BD. The P value threshold for significance was P < 9. 1E-03, representing a 5% false discovery rate (FDR) across datasets. Further gene-set analyses were performed restricted to genes targeted by drugs, assessing individual drugs and grouping drugs with similar actions.
This approach has been described previously  41. Gene-level and gene-set analyses were performed in MAGMA v1. 08  37. Gene boundaries were defined using build 37 reference data from the NCBI, available on the MAGMA website (https://ctg. cncr. nl/software/magma), extended 35kb upstream and 10kb downstream to include regulatory regions outside of the transcribed region. Gene-level association statistics were defined as the aggregate of the mean and the lowest variantlevel P value within the gene boundary, converted to a Z-value. Gene sets were defined comprising the targets of each drug in the Drug-Gene Interaction database DGIdb v. 2  39  and in the Psychoactive Drug Screening Database Ki DB  40  , both downloaded in June 2016  41. Analyses were performed using competitive gene-set analyses in MAGMA.
Mendelian randomization Seventeen traits associated with BD in clinical or epidemiological studies were selected for Mendelian randomization (MR) to dissect their relationship with BD (Supplementary Note). Bi-directional generalized summary statistics-based MR (GSMR)  51  analyses were performed between BD and the traits of interest using GWAS summary statistics, implemented in GCTA software (v1. 93. 1f beta). The instrumental variables (IVs) were selected by a clumping procedure internal to the GSMR software with parameters: --gwasthresh 5e-8 --clump-r2 0. 01. Traits with less than 10 IVs available were excluded from the GSMR analyses to avoid conducting underpowered tests  51  , resulting in 10 traits tested (Bonferroni-corrected P value threshold < 2. 5E-03). The HEIDI-outlier test (heterogeneity in dependent instruments) was applied to test for horizontal pleiotropy (PHEIDI < 0.
01)  51. For comparison, the MR analyses were also performed using the inverse variance weighted regression method, implemented via the TwoSampleMR R package, using the IVs selected by GSMR  119, 120. To further investigate horizontal pleiotropy, the MR Egger intercept test was conducted using the TwoSampleMR package  119, 120  and MR-PRESSO software was used to perform the Global Test and Distortion Test  121.
Acknowledgements We thank the participants who donated their time, life experiences and DNA to this research and the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the  PGC. The PGC has received major funding from the  US National Institute of Mental Health Bioinformatics : N. M. , A. J. F. , J. R. I. C. ,  S. Børte ,  M. J. Gandal ,  M. Kim , B. M. S. , L. G. S. , B. S. W. , H-H. W. , N. A-R. , S. E. B. , B. M. B. , V. E-P. , S. H. , P. A. H. , Y. K. ,  M. Koromina ,  M. Kubo ,  M. Leber ,  P. H. L. ,  C. Liao , L. M. O. L. , T. R. , P. R. , P. D. S. , M. S. A. ,  C. Terao , T. E. T. , S. X. , H. Y. , P. P. Z. ,  S. Bengesser ,  G. Breen , P. F. , E. S. G. , Q. S. L. , G. A. R. , H. S. , T. W. , E. A. S. Clinical: O. K. D. , M.
In addition, we performed systematic immunolabeling detection of the cuticular proteins identified by mass spectrometry in dissected stylets. We thereby establish the first proteome of stylets of an insect and determine the minimal repertoire of the cuticular proteins composing the acrostyle. Most importantly, we propose a short list of plant virus receptor candidates, among which RR-1 proteins are remarkably predominant. The data are available via ProteomeXchange (PXD016517).
Database Searching and Protein Identification The Sequest HT searching algorithm was run by Proteome Discoverer 1. 4 (Thermo Fisher Scientific) to match the acquired MS/MS spectra to a protein database, with the following settings: trypsin digest with two maximum missed cleavages, 6 and 144 amino acids as minimum and maximum peptide length, respectively, a tolerance of 10 ppm/0. 02 Da for precursors and fragment ions, respectively. Cysteine carbamidomethylation was set as a fixed modification; C-terminal protein amidation and methionine and tryptophan oxidation were set as variable modifications. Searches were performed against combined proteome databases (Table  S1 ) including: (i) the pea aphid proteome (http://aphidbase. com, version 2. 0 containing 33,291 proteincoding sequences); (ii) an eubacterial reference proteome setup for putative symbionts and aphid microbiome-related sequences (116,983 sequences); (iii) a set of sequences of entomopathogenic fungi (28,431 sequences); (iv) a set of viral sequences including aphid viruses and aphid-vectored broad-bean viruses were also selected (6,614 sequences); (v) a mixed plant proteome assembled from available Fabacae proteomes (66,777 sequences); and (vi) a set of common contaminants (116 sequences).
A homemade A. pisum CP database comprising 150 annotated CPs was constructed using the Cuticular Protein Family Prediction Tool CutProtFam-Pred (http://aias. biol. uoa. gr/ CutProtFam-Pred/home. php) to accurately detect and classify putative CPs present in the pea aphid proteome v2. 0, thanks to known consensus and semiconsensus sequences (Table  S2 ). 29 dentification of CPs in cuticular structures was carried out with this homemade database.
Data Presentation To identify the proteins that are present in pea aphid cuticular anatomical structures, pools of antennae, wings, legs, and stylet bundles were collected in triplicate on A. pisum adults. Proteins consistently identified in all three biological replicates with at least a same peptide in each replicate, regardless of being "Unique" (peptide present in only one protein) or "Shared" (peptide present in multiple different proteins), were considered as confidently identified and constituted whole proteomes of the cuticular structures. In these first data sets, proteins sharing a same identified peptide were grouped under a single protein identifier (accession number corresponding to the protein with the highest score and highest percentage of coverage of the protein. These parameters can differ from one sample to another, and a same "shared" peptide may be assigned to different protein identifiers by the algorithm).
Comparative analyses of whole proteomes were carried out using these data sets. Minimal lists of CPs were then retrieved from whole proteomes using homemade CP database (Table  S2 ). Minimal lists represent the smallest number of CPs that can explain all identified MS peptides and will be used to design peptides for antibodies production and immunolabeling of dissected stylets. 1] [32] [33]  Several proteins can be identified with a same tryptic fragment ("shared" peptide). In this case, we cannot tell how many of these proteins are actually incorporated into the cuticle of the anatomical structures. To be fully exhaustive in our quest for virus receptor candidates, lists of CPs potentially present in cuticular structures were extended to all proteins containing these "shared" peptides.
Functional Classification Gene Ontology (GO) terms were assigned to AphidBase 2. 0 (http://bipaa. genouest. org/is/aphidbase/acyrthosiphon_ pisum/downloads/) via Blast2GO software version 5. 1. 12 using the InterProScan with the Hidden Markov Models (HMMs) present in the PFAM protein family database. 34 The number of proteins identified in each cuticular structure was compared to all corresponding functionally GO annotated terms in the entire pea aphid (A. pisum). GO term enrichment was determined via Fisher's Exact test at an FDR, p-value ≤0. 05; the reduced enrichment was determined at an FDR, p-value ≤0. 01.
All RT-qPCRs were performed in duplicates on a LightCycler 480 instrument (Roche, Basel, Switzerland) using 1:4 dituted cDNAs and a LightCycler 480 SYBR green I master mix (Roche, Penzberg, Germany) according to the manufacturer's recommendations with gene-specific primers (Table  S3 ). Two internal reference genes encoding actin and elongation factor 1α (EF1α) from A. pisum were used for normalization. Amplification efficiencies were analyzed with LinRegPCR free software (v. 2014. 5). Relative expressions were calculated using the threshold cycle (2 -ΔΔCT ) method. 35.
Phylogenetic trees were reconstructed using the maximum likelihood method implemented in the PhyML program (v3. 1/ 3. 0 aLRT). The WAG matrix, which works as empirical aminoacid substitution model to simulate the biological sequence evolution with flexibility, was selected assuming an estimated proportion of invariant sites (of 0. 009) and four gamma-distributed rate categories to account for rate heterogeneity across sites. The gamma shape parameter was estimated directly from the data (gamma = 3. 517). Reliability for internal branch was assessed using the aLRT test (SH-Like). Graphical representation and edition of the phylogenetic trees and alignments were performed with TREEDYN (v. [44]  ■ RESULTS.
Stylet-Specific Proteins Forty stylet-specific proteins have been identified in our MS data sets (Figure  2A , Table  S8 ), most of which were not previously annotated. Although not possible to ascertain, at least 13 of these stylet-specific proteins (32. 5%) likely came from the saliva remaining in the salivary canal after dissection of stylet bundles. 6] [47] [48] [49]  Two cuticle-related proteins were only present in the stylets data sets, one trehalase (ACYPI007462) reported to play a role in several processes, including chitin biosynthesis in other insects, and one RR-2 protein (ACYPI006670). 50 Whereas the saliva-related proteins and trehalase were identified with unique peptides not detected in the three other cuticular structures, the RR-2 protein was solely identified from two shared peptides (GSYSLLEADGSTR and TVEYTADDYNGFNAVVK), also identified in antennae, legs, and wings.
Localization of CPAP3 Proteins in the Stylets Three CPAP3 have been identified in the stylet data sets. With the set of antibodies produced and used against these proteins, the labeling was generally weak and visible as dots at the tip of maxillary stylets (Figure  5C , Table  4 ). ACYPI007860 was only barely revealed in the acrostyle after Chitinase treatment with a single antibody, anti-3-02, targeting a peptide that was not detected by MS. No labeling could be visualized when using anti-3-01 antibody targeting one unique MS-identified peptide of this protein. Its location within aphid stylets could therefore not be definitely stated. ACYPI006031 and ACYPI007911 were detected in the acrostyle, each with two distinct antibodies. Two peptides of ACYPI006031, respectively targeted by anti-3-06 and anti-3-07 were found embedded within the cuticle.
■ CONCLUSIONS We provide through this study the first comparative proteomics analysis of four aphid cuticular anatomical structures, namely antennae, legs, wings, and stylets. Our data gives preliminary evidence that a great number of CP proteins are common to antennae, legs, and wings, while a few CP proteins seem specific to each appendage. The stylet, which was of main interest to better understand the vector/virus interaction was found to be distinct in composition compared to the other three studied appendages. We determined the repertoire of CPs of aphid stylets and precisely mapped their accessibility in maxillae at the surface of the acrostyle. Further characterization for this short list of proteins showed that they are highly conserved in aphid species and thus all represent good candidate receptors of plant viruses.
* sı Supporting Information The Supporting Information is available free of charge at https://pubs. acs. org/doi/10. 1021/acs. jproteome. 9b00851. Table  S1. Database generated for protein identification including 252,212 entries. Table  S2. Home-made A. pisum CP database identified using CutProtFamPred. Table  S3. List of oligonucleotides used in this study. Table  S4. A. pisum proteins identified in antennae. Table  S5. A. pisum proteins identified in legs. Table  S6. A. pisum proteins identified in wings. Table  S7. A. pisum proteins identified in stylets. Table  S8. Proteins distribution in A. pisum cuticular structures. Table  S9. Analysis of GO terms enrichment for proteins identified in the Core Proteome of antennae, legs, wings, and stylets. Table  S10. GO terms enrichment in antennae.
The mathematical background of this approach can also be consulted in Appendix A. The flipping ratios obtained on beamline D3 at two different temperatures were refined using FullProf (Rodrı ´guez-Carvajal, 1993; Frontera & Rodrı ´guez-Carvajal, 2004; the programs of the FullProf suite can be obtained at http://www. ill. eu/sites/fullprof). It is worth noting that the FullProf program calculates the magnetic structure factor in a simplified manner, since it supposes that only the component along the vertical axis contributes. The calculated versus observed flipping ratios obtained with each model above and below the order temperature are shown in Fig. 3. In order to obtain the nuclear structure factors F N , an accurate structural model was determined at 45 K, in the paramagnetic phase, from single-crystal neutron diffraction on the D19 diffractometer (Can ˜adillas-Delgado et al.
We observed that several datasets, recorded with different recording setups, contained spectrotemporal features highly correlated with those of the sound produced by or delivered to the participants, especially within the high-gamma band and above, strongly suggesting a contamination of electrophysiological recordings by the sound signal. This study investigated the presence of acoustic contamination and its possible source. Approach. We developed analysis methods and a statistical criterion to objectively assess the presence or absence of contamination-specific correlations, which we used to screen several datasets from five centers worldwide. Main results. Not all but several datasets, recorded in a variety of conditions, showed significant evidence of acoustic contamination. Three out of five centers were concerned by the phenomenon.
Human recordings 2. 1. 1. Participants The present study was conducted as part of the Brainspeak clinical trial (NCT02783391) approved by the French regulatory agency ANSM (DMDPT-TECH/MM/2015-A00108-41) and the local ethical committee. It is primarily based on electrophysiological recordings obtained in 3 patients at the Grenoble University Hospital: a 42year-old (P2) and a 29-year-old (P3) males undergoing awake surgery for tumor resection, and a 38year-old female (P5) implanted for 7 days as part of a presurgical evaluation of her intractable epilepsy. These three participants gave their informed consent to participate in the study. We further included datasets obtained by four other centers in China, Germany, Switzerland and the USA. Firstly, a 22-year-old male participant (CN) suffering from intractable epilepsy requiring surgical treatment was recorded at the Second Affiliated Hospital of Zhejiang University.
These procedures were followed from the guide and approved by the Second Aliated Hospital of Zhejiang University, China. Participant CN gave written informed consent after detailed explanation of the potential risks of the research experiment. Secondly, two additional datasets were acquired at Frankfurt University. A 33-year-old bilingual Russian and English-speaking male patient suffering from a left frontal anaplastic astrocytoma (D1) and a 36-year-old native German speaking female suffering from an anaplastic glioma (D2) were recorded. Participants D1 and D2 gave written informed consent after detailed explanation of the potential risks of the research experiment, which were approved by the ethics committee of the medical faculty of Goethe University (GZ 310/11). Thirdly, two patients with drug-resistant epilepsy were recorded extra-operatively at Geneva University Hospitals: a 49-year-old woman (CH1) and a 50-year-old man (CH2).
Both gave written consent to participate in speech production and processing experiments, which were approved by the local ethics committee (Commission cantonale d'éthique de la recherche, Geneva, Switzerland). Finally, datasets were recorded from three patients, a woman aged 18 (US1), a man aged 42 (US2), and a man aged 21 (US3), at the University of Washington (Seattle, WA, USA). All three patients participated in a purely voluntary manner, after providing informed written consent, under experimental protocols approved by the Institutional Review Board of the University of Washington  (#12 193). Patient data was anonymized according to IRB protocol, in accordance with HIPAA mandate  (Miller 2019).
For participant P3, a 96-channel intracortical Utah microelectrode array (UEA, Blackrock Microsystems, USA) was inserted in the pars triangularis of Broca's area (figure  1 ), at a location that was subsequently resected to access the tumor for its removal. The pedestal serving as ground was screwed to the skull. Two wires with deinsulated tips were inserted below the dura, and one was used as reference. The electrodes were connected via a Patient Cable (Blackrock Microsystems, USA) to a FEA where signals were digitized at 30 kHz and further transmitted through an optic fiber to a NSP. Participant D1 received left perisylvian electrocorticography using an 8 × 12 electrode grid and two 2 × 8 electrode grids with 5 mm spacing (Ad-Tech Medical, USA). The ground electrode was the subgaleal needle electrode P4 and data were referenced against a frontocentral subgaleal needle electrode Fz and sampled at 5 kHz (four amplifiers connected to two headboxes; BrainAmp MR plus amplifier, BrainProducts, Germany).
Participant D2 received left perisylvian electrocorticography using an 8 × 12 grid electrode (Ad-Tech Medical, USA). The ground electrode was the subgaleal needle electrode C4 and data were referenced against a frontocentral subgaleal needle electrode Fz and sampled at 2048 Hz (two amplifiers 64 channels each, one headbox per amplifier, Micromed, Italy). Brain activity from participants P5, CN, CH1, CH2, US1, US2, and US3 was recorded in subchronic condition at the hospital. Participant P5 was implanted with a 72-electrode ECoG array (PMT Corp. , USA) covering a large portion of her left hemisphere as well as a 4-electrode strip (PMT Corp. , USA) over the left ventral temporal lobe and a 96electrode UEA inserted in the left ventral sensorimotor cortex (figure  1 ). An electrode of the strip was used as the reference and another as the ground.
The transcutaneous pigtails of the ECoG grids were connected to PMT pigtail adaptors and then to two headboxes (64-Channel Splitter Box, Blackrock Microsystems, USA) through individual touch-proof connectors. The headboxes were connected to a FEA linked to a NSP. The transcutaneous pedestal of the UEA was screwed to the skull and connected to a Cereplex-E headstage (Blackrock Microsystems, USA) ensuring signal amplification and digitization before transmission to a second NSP through a digital hub. For these intracortical recordings, the reference was a wire deinsulated at its tip and inserted below the dura, and the ground was the pedestal. Data from both electrode arrays was sampled at 30 kHz and recorded on the two synchronized NSPs. Participant CN was implanted with a 32-electrode clinical subdural ECoG grid (HuakeHesheng, China) in his right sensorimotor cortex for clinical monitoring and localization of his seizure foci (figure  1 ).
EEG signals for CH1 and CH2 were referenced to a subdermal wire electrode inserted at the vertex, digitized at 2048 Hz and recorded with a BrainQuick LTM system (Micromed, Italy). The Seattle participants all had subdural platinum electrode arrays (Ad-Tech Medical, USA) implanted over the left hemisphere in 6 × 8 (US1) and 8 × 8 (US2 and US3) rectangular arrays. These electrodes had 4 mm diameter (2. 3 mm exposed), 1 cm interelectrode distance, and were embedded in silastic. These data were recorded with Synamps2 amplifiers (Compumedics Neuroscan, USA) in parallel with clinical recording, sampled at 2 kHz (US1) or 1 kHz (US2 and US3). The data were exported from the amplifiers to the BCI2000 software environment on a separate laptop, using a TCP/IP protocol  (Schalk et al 2004).
Audio recordings In case of speech production tasks, the participant speech was recorded along with his or her neural data. For participants P2, P3 and P5, a microphone (SHURE Beta 58 A) was positioned at about 10-20 cm from the mouth. The signal was amplified using an audio interface (Roland OCTA-CAPTURE) and digitized by one of the NSPs, at the same rate and synchronously with the neural data (see figure  2(a) ). For participant CN, the played sentences were realigned with the neural signals using triggers indicating the start of the stimuli. D1's and D2's voices were recorded using a custom-made microphone (BrainProducts, Germany) connected to two bipolar EMG channels of the headboxes. For participants CH1 and CH2, the patient's produced speech or the sound delivered by the stimulus presentation portable computer positioned in front of the patient was captured with a battery-powered microphone (TCM160, AV-Leader Corp, Taiwan) and fed to an available analog input in the EEG amplifier through a custom-made jack-to-touchproof cable.