dataesr/scientific-paragraphs-categorization huggingface dataset:
CellCelector clonal isolation 24-well nanowell plates (ALS, Germany) were coated with vitronectin (Gibco) and centrifugated for 5 min at 1258 g (to eliminate micro-bubbles) prior to incubation at 37 °C for 1 h. Approximately 3000 cells were seeded per well (4300 square-shaped nanowells in total in a well of a 24-well plate). Seeded cells are randomly distributed in nanowells following Poisson distribution resulting in ~ 30% of nanowells occupied with single cells. After cell seeding, plates were centrifuged again for 3 min at 100 g to allow all cells to be captured in nanowells. Nanowells with seeded cells were automatically scanned on the CellCelector system (ALS, Germany) on D0 just after cell seeding. Identification of single cell nanowells on D0 was performed using a specific image analysis algorithm using CellCelector software (v3.
Flow cytometry Cells were dissociated with TrypLE (ThermoFisher) and stained with TRA1-81-AF647 (Biolegend) or SSEA-4-PE (Miltenyi Biotec) and corresponding isotypes from the same suppliers. For intracellular markers, cells were fixed with 4% PFA following dissociation. Cells were treated with PBS 0. 1% tritonX100 and then incubated overnight with OCT3/4 (Santa Cruz, sc-5279, 1:100) and LIN28A (R&D SYSTEMS, AF3757, 1:200). The day after, cells were washed and incubated with corresponding secondary antibodies (Invitrogen). Acquisitions were done with a MACSQuant analyzer (Miltenyi Biotec) and data were analyzed using the FlowJo software.
Immunofluorescence After fixation with 4% PFA for 15 min at room temperature, cells were incubated overnight at 4 °C with the following primary antibodies: OCT3/4 (Santa Cruz, sc-5279, 1:100), LIN28A (R&D SYSTEMS, AF3757, 1:200), Pericentrin (Abcam, ab28144, 1:200) and ALMS1 (Abcam, ab84892, 1:200). Appropriate Alexa fluorescent secondary antibodies (Invitrogen) and DAPI were added for 1 h. Image acquisitions were performed on a Zeiss LSM880-Airyscan Confocal Microscope driven by the Zeiss Zen black software.
Multiplex fluorescence in situ hybridization (mFISH) karyotype analysis Cells were blocked in metaphase with colchicine (Eurobio) for 90 min and then they were detached with trypsin. After centrifugation, the supernatant was removed and cell pellet was suspended and warmed in a hypotonic solution for several minutes and then fixed with a Carnoy fixative. Drops of the cell suspension were spread on glass slides and let to dry. mFISH 24Xcite probe (MetaSystems) and ProLong Gold Antifade Mountant with DAPI (Thermo Fisher Scientific) were used for mFISH staining. Seventy metaphases were acquired with Metafer Meta-Systems software coupled to an AxioImager Zeiss Z2 microscope furnished with a camera cool cube and 10X and 63X objectives. Images were analyzed with Isis software (MetaSystems).
Single cells grow in adherence inside nanowells and form colonies pickable using a robotized arm To identify single cells in nanowells and collect single cell-derived clones, we used the CellCelector ™ automated system composed of a standard inverted fluorescent microscope equipped with a camera, a motorized stage and a robotized arm with a mounted thin glass capillary (Fig. 1C-E ). This system is associated with a software that allows precise detection of single cells in nanowells and selection of single cell-derived colonies. In order to validate the ability of this system to recognize, select and pick hPSC clones, we generated two knock-in hPSC lines with constitutive expression of GFP or mCherry, the transgenes being inserted into adeno-associated virus integration site 1 (AAVS1) locus (Additional file 1: Fig.
Acknowledgements Some elements of figures were created using Servier Medical Art templates (https:// smart. servi er. com), which are licensed under a Creative Commons Attribution 3. 0 Un-ported License. The authors greatly acknowledge Peggy SANATINE from institute  GENETHON , part of the  OCCIGEN facility of Genopole (Evry, France ), first French biocluster dedicated to genetic diseases and biotherapies, for precious help in the cell sorting of fluorescent cells.
Dynamic STRAIN Experiments In the dynamic experiments, aluminium beams were embedded on both sides: on side was screwed to a vibration exciter (Type 4809 from Brüel & Kjaer, Naerum, Denmark and the other side was screwed to a mechanical piece, linked with an optical table (Figu 5). In this way, the natural frequency of the beam was sufficiently far away (>100 Hz) be able to only study the bonded FBG behaviour, as the beam response remained flat the studied [10:100] Hz frequency range. The FBGs were glued close to an embedded sid as it is in these areas that the deformations in the beam are greater. Finally, because of th too-slow acquisition rate of the OFDR (lower than 0. 2 Hz), it was not possible to study th dynamic strain transfer using this method. An accelerometer (352C33 from PCB Piezotronics, Depew, NY, USA) fixed in the ax of the vibration exciter allowed us to record the applied acceleration to the aluminiu beam, through the data acquisition system LAN-XI from Brüel & Kjaer, and the associate software BK Connect.
Additionally, as for the static experiments, the FBG data were re orded through the Gator interrogator system, at a sampling frequency of 19 kHz. Experimentally, the dynamic tests consisted of applying a sinusoidal displaceme of constant amplitude to the beam, at frequencies from 10 to 100 Hz. Four experimen were carried out, with four different constant displacements: 0. 028 mm, 0. 055 mm, 0. 08 mm, and 0. 14 mm. These displacement values were chosen in accordance with the perfo mance of the vibration exciter, which had a 4 mm displacement limit and a 44. 5 N for limit (Figure  6 ). These performances led to a maximum achievable acceleration of: An accelerometer (352C33 from PCB Piezotronics, Depew, NY, USA) fixed in the axis of the vibration exciter allowed us to record the applied acceleration to the aluminium beam, through the data acquisition LAN-XI from Brüel & Kjaer, and the associated software BK Connect.
Additionally, as for the static experiments, the FBG data were recorded through the Gator interrogator system, at a sampling frequency of 19 kHz. Experimentally, the dynamic tests consisted of applying a sinusoidal displacement of constant amplitude to the beam, at frequencies from 10 to 100 Hz. Four experiments were carried out, with four different constant displacements: 0. 028 mm, 0. 055 mm, 0. 085 mm, and 0. 14 mm. These displacement values were chosen in accordance with the performance of the vibration exciter, which had a 4 mm displacement limit and a 44. 5 N force limit (Figure  6 ). These performances led to a maximum achievable acceleration of: a max = F limit m e + m sample = 44. 5 0. 06 + 0. 015 ≈ 594 m/s 2 (11) where F limit is the maximum force the exciter can provide, m e is the mass of the exciter moving element, and m sample is the mass of an aluminium sample.
L-Ara4N is not essential for polymyxin adaptation Unlike other species such as Escherichia coli and Acinetobacter baumannii, the addition of L-Ara4N to the lipid A was sufficient to confer polymyxin resistance to both selected in vitro mutants and clinical strains of P. aeruginosa  [22]. The strain IHMA87 lacks the entire arn operon encompassing the deletion of approx 8. 8 kb between genes algA and fruA, corresponding to PA3551 and PA3560 in PAO1 (Fig. 1A ). To evaluate the frequency of this event, we compared genomes available on the NCBI database belonging to groups 3 (n=23), 4 (n=64) and 5 (n=38) with a set of strains of groups 1 (strain PA14, n=8) and 2 (strain PAO1, n=7). Interestingly, only a subset of strains of group 3 carried the deletion of the arn locus reminiscent to the IHMA87 genome, whereas 31.
tRNA coding sequences, frequently found as hotspots for genetic remodeling  [29, 30] , are present just downstream of mipA (Pseudomonas genome database;  [31] ). As the ParR regulon has been largely investigated  [9, 12, 32] , the ParR binding consensus sequence using the bioinformatics tool MEME could be defined (Fig. 3B ). A perfect ParR binding site, conserved across the reference strains, was identified upstream the ATG of mipB. We examined whether the regulation of mipB is direct using purified ParR protein and electrophoresis mobility shift assay (EMSA) on a predicted promoter region of PA1797 (PAO1). In agreement with the recent genome-wide binding pattern of ParR  [32] , we showed a direct binding of ParR to the promoter of PA1797, which is improved when ParR is phosphorylated (Fig.
The β-barrel has a cross-section of ∼ 25 Å×22 Å and is ∼40 Å in height. Using PDBeFold  [45]  and FoldSeek  [46] , MipA structure superimposes on several structures from PDB such as OmpG (PDB entry: 2X9K;  [47] ), and NanC (PDB entries: 2WJR, 2WJQ;  [48] ) with root-mean-square deviation (rmsd) values of 2. 55 and 2. 58 Å, two porins from E. coli involved in the N-acetylneuraminic and maltodextrin transport, respectively. MipA also superimposes onto the barrel domain of the intimin protein from E. coli (PDB entry: 5G26;  [49] ) and the lipid A deacylase LpxR of Salmonella typhimurium (PDB entry: 3FID;  [50] ) with rmsd values of 2. 33 and 3. 01 Å, respectively. Using FoldSeek, several predicted structures by AlphaFold as β-barrels with 12 transmembrane β-strands and the lateral gate superimpose onto MipA; these proteins belonging to different species of Gram-negative bacteria.
aeruginosa with partially overlapping regulons  [9, 12]. But ParR was the only response regulator binding to mipBA promoter in all three strains tested (PAO1, PA14 and IHMA87;  [32] ). MipB and MipA proteins are associated with the membrane and form a complex in vitro. MipA localization in Caulobacter crescentus was dependent on MreC, a proposed scaffold protein in bacterial elongasome  [56, 57]. Moreover, MipA was proposed to be tethered to both outer and inner membrane through interaction with MltA and PBP1b  [58]. In P. aeruginosa, MipA appears to be embedded in the outer membrane, in line with its fold in β-barrel containing 12 β-strands that superimposes on the NanC and OmpG porins  [47, 48]. Structural predictions showed that MipA harbors a negatively charged inner channel in its center where several conformations of PMB and PME molecules can be docked, reminiscent to the crystal structure of the LSD1-CoREST bound to PMB (PDB entries: 5L3F and 5L3G;  [55] ).
Phylogenetic analysis 144 P. aeruginosa genomes were retrieved from the Refseq database on the NCBI platform. New annotations were generated when needed. Altogether, the database included 8 genomes from phylogenetic group 1, 7 from group 2, 68 from group 4, 38 from group 5 and 23 from group 3. This database was remodeled with the addition of clinical strains sequenced by the French National Reference Center for Antibiotic Resistance, Besançon. Distances between genomes were established using Mash v2. 3  [78]  and a phylogeny was generated with mashtree v1. 2. 0  [79]. Mashtree uses any common sequence file and calls the neighbor-joining (NJ) algorithm which is implemented in the software QuickTree  [80]. Search for genes of interest was performed using the Sequence Extractor plugin of BioNumerics 7.
Protein predictions and genetic neighbor analysis Signal peptides were predicted using SignalP 5. 0  [86]. The 3D structure predictions of MipB and MipA/MipB complex were performed using AlphaFold  [39]  and AlphaFold-Multimer  [53]. Pymol was used to calculate electrostatic surface potential and generate figures. WebFlaG was used to study genetic neighbors of mipA  [70]. MipA FASTA sequence from MipA-IHMA87 was imputed and a list of 50 homolog was searched by BlastP in the Atkinson lab reduced database.
9 μm, Dr. Maisch). The MS and MS/MS data were acquired using Xcalibur (Thermo Fisher Scientific). Peptides and proteins were identified by Mascot (Matrix Science) through concomitant searches against the NCBI database (P. aeruginosa strain: IHMA879472 taxonomy, March 2021 download) and a homemade database containing the sequences of classical contaminant proteins found in proteomic analyses (human keratins, trypsin, etc. ). Trypsin/P was chosen as the enzyme and three missed cleavages were allowed. Precursor and fragment mass error tolerances were set at respectively at 10 and 20 ppm. Peptide modifications allowed during the search were: Carbamidomethyl (C, fixed), Acetyl (Protein N-term, variable) and Oxidation (M, variable). The Proline software version 2. 2. 0  [89]  was used for the compilation, grouping, and filtering of the results (conservation of rank 1 peptides, peptide length ≥ 6 amino acids, false discovery rate of peptide-spectrummatch identifications < 1%  [90] , and minimum of one specific peptide per protein group).
Proline was then used to perform a MS1 label-free quantification of the identified protein groups based on razor and specific peptides. Statistical analysis was then performed using the ProStaR software version 1. 30. 5  [91]. Proteins identified in the contaminant database, proteins identified by MS/MS in less than two replicates of one condition, and proteins detected in less than three replicates of one condition were discarded. After Log2 transformation, abundance values were normalized by vsn (variance stabilizing normalization) method before missing value imputation (slsa algorithm for partially observed values in the condition and DetQuantile algorithm for totally absent values in the condition). Statistical testing was then conducted using Limma, whereby differentially expressed proteins were sorted out using a Log2 (fold change) cut-off of 1 and a p-value cut-off of 0.
Statistical analysis Data were statistically analyzed using Graphpad prism 9. For multiple comparisons, a one-way ANOVA or Kruskall-Wallis test was performed depending on the data normality (Shapiro test), followed by a Tukey or a Dunn's test for normally and non-normally distributed dataset, respectively. To compare two groups, a Student t-test or a Mann-Whitney test was applied depending on the normality of the data.
Acknowledgements This work was supported by grants from  Agence Nationale de la Recherche  ( ANR-18-CE11-0019 ) and from  GRAL , funded through the  University Grenoble, Alpes graduate school (Ecoles Universitaires de Recherche)   CBH-EUR-GS  ( ANR-17-EURE-0003 ). P. aeruginosa IHMA87 was obtained from the  International Health Management Association, USA. MJM received a Ph. D fellowship from the  French Ministry of Education and Research. The proteomic experiments were partially supported by  Agence Nationale de la Recherche  under projects  ProFI (Proteomics French Infrastructure ,  ANR-10-INBS-08 ) and  GRAL , a program from the  Chemistry Biology Health (CBH) Graduate School of University Grenoble Alpes  ( ANR-17-EURE-0003 ). We also thank undergraduate students  Claire Lapouge  and  Florine Borrel  for their technical help during experiments.
For the geometry, a python script was developed to define in the MCNP format the thousands of solids that constitute the 8155 U-pipes of the HX bundle according to the technical drawings. Regarding the source definition, the default surface source capability of MCNP does not allow the emission from tori or more complex geometries  [9] , therefore a specific feature was developed in the D1SUNED code  [10]. As the ACP accumulation in HXs is a potential issue also in nuclear fission power plants, the methodology here described can be considered valid and extended to study in detail its contribution to the radiation levels in such plants.
Radiation source characterization The characterization of deposited ACPs in a nuclear environment is a complex evaluation based on multiple operational parameters over a time span that encompasses the reactor lifetime. To build the radiation source computational model, we took the most recent study of the deposited ACPs in the ITER primary cooling circuit  [11]. This study applied the code Oscar-fusion v1. 3, which is a derivation for fusion applications of Oscar, a code developed by CEA, EDF, and Framatome for the design and operation of nuclear power plants  [6]. The main inputs required by the code are physical and chemical models, nuclear reaction rates, cooling and filtering operation history, and the nodal scheme of the cooling system. The irradiation scheme was defined considering the ITER SA-2 scenario.
Therefore, a Python script was developed to automatically define the inner piping directly in the MCNP format. The script took as input a set of parameters that were gathered from the technical drawings, namely the pipe diameter, and length, the spacing and pattern of their disposition, and the number of pipes per line. The MCNP cells representing the pipes were integrated with the simplified model to produce the detailed model. The degree of realism obtained with the complete model can be observed by comparing the original technical drawings with the plot sections of the MCNP model in Fig. 4.
Acknowledgments This work has been carried out within the framework of the  EUROfusion Consortium , funded by the  European Union  via the  Euratom Research and Training Programme  (Grant Agreement No  101052200 -EUROfusion ). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the  European Union  nor the  European Commission  can be held responsible for them. We appreciate the support given by:  MINECO  for the funding of  Juan de la Cierva-incorporación program  2016; and the funding under  I+D+i-Retos Investigación , Prj. ENE2015-70733R ;  Comunidad de Madrid  under  I+D en Tecnologías ,  Prj. TECHNOFUSI ÓN  ( III )-CM,  S2018/EMT-4437 ;  ETS Ingenieros Industriales-UNED   2020 programme ; and  UNED  for the funding of the predoctoral contracts (FPI).
Others focus on reaching a solution or creative idea to a research question through competition, such as the events using data from The Alzheimer's Disease Neuroimaging Initiative (ADNI), where teams competed to predict mild cognitive impairment (MCI) conversion to Alzheimer's Disease  4. The first combined 'GP2/IPDGC Hackathon 2021' event provided teams with a choice of nine PD genetics and genomics analysis topics. The focus of the GP2/IPDGC Hackathon was not competition, but training, networking, collaboration, and the development of tools that would be useful to the broader research community. As part of an open science initiative, the Accelerating Medicines Partnership Parkinson's Disease Program (AMP PD, https://amppd. org/) 5 aims to identify and validate biomarkers by providing researchers access to a large, harmonized dataset that includes clinical, genomic, transcriptomic, and proteomic data.
5 dataset. We tested normalized z-scores for association with LRRK2 carrier disease status. Mean ± standard deviation of unadjusted PRS scores were higher in PD LRRK2 mutation carriers (-0. 0166 ± 0. 004), compared to control LRRK2 mutation carriers (-0. 0182 ± 0. 004) and controls (-0. 0180 ± 0. 004), suggesting that PD LRRK2 mutation carriers share a common polygenic risk profile with idiopathic PD (iPD), contrary to control LRRK2 mutation carriers (Fig. 2a ). Project 2 (pathway and cell enrichment pipeline). We aimed to create a pipeline to annotate GWAS summary statistics to test the enrichment of biological pathways and cell types. Analyses were performed on the Terra platform using the most recent PD GWAS summary statistics  7. We created a pipeline to correctly format the GWAS summary statistics for a common annotation tool Functional Mapping and Annotation of Genome-Wide Association Box 1 Glossary for unfamiliar terms.
Unified Parkinson's disease rating scale (UPDRS) A rating tool used to gauge the severity and progression of PD in patients. Studies (FUMA)  12  , then downloaded the formatted data and uploaded it to FUMA. We also ran the WEB-based GEne SeT AnaLysis Toolkit (WebGestalt) directly on Terra using the WebGestaltR package  13. We selected the nearest genes to the GWAS significant SNPs (P < 5 × 10 -8 ) from Nalls et al. 2019 GWAS summary statistics. Using WebGestaltR, we conducted an overrepresentation analysis and gene set enrichment analysis. We identified 97 unique genes from the genome-wide significant hits in the PD GWAS summary statistics. We generated summary data for these PD genes annotated by biological processes, cellular components, and molecular functions (Fig. 2b ). There was no significant enrichment of any Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway gene sets in the overrepresentation analysis (FDR P < 0.
For Project 3: Colocalization pipeline, we considered colocalization analysis with a posterior probability of colocalization in H4 (PPH4) greater than 0. 8 to be significant. We utilized the coloc R package  21, 22  and summary statistics from ref. 7. We used eQTL data from a cerebellar cortical meta-analysis of four cohorts  23  , publicly available from the AMP-AD Knowledge Portal  24. As an example for our pipeline, we extracted the region ± 500 kb around DYRK1A, nominated in Nalls et al. 2019, from the GWAS summary statistics and eQTL data. To visualize the results, we employed the eQTpLot R package  25  , which can generate different plots for GWAS and eQTL signal colocalization, as well as the correlation between their p values and enrichment of eQTLs among variants and LD of loci of interest, allowing efficient and intuitive visualization of gene expression and trait interaction.
We used our previously generated results for DYRK1A and whole brain eQTL as an example for creating visualizations using this package. (Fig. 3a ). Project 4 (network generations and visualization pipeline). We sought to develop a Leiden network and subsequent visualization pipeline for transcriptomic and genomic data to identify and visualize both a priori and complex phenotype gene regulatory networks. The Leiden algorithm is one option for community detection of networks and can be faster and return more reliable results than the more well-known Louvain algorithm  26. We relied on the leidenalg  27  package in Python to produce weighted and unweighted networks on GWAS summary statistics and then visualized the resulting networks. (Fig. 3b ). Data used consisted of AMP PD genomic, transcriptomic data, and public eQTL data from the eQTL catalog  28  and PD summary statistics from the most recent PD GWAS  7.
We designed this visualization to inform progress and inspire others to contribute to this initiative. In the form of a one-page dashboard developed with the opensource Python software Streamlit, the visualization includes separate maps for complex and monogenic cohorts. was critical to include easy-to-use search and discovery aspects built into the dashboard. If a user knows the name of a particular cohort, then they can pull up information for that cohort that populates the rest of the dashboard. The user can also filter by general methods such as cohort size or country. This design is used internally and externally on the GP2 website (https://gp2. org/cohort-dashboard/) to inform those interested in the progress of GP2's cohort integration (Fig. 4a ). Project 7 (IPDGC GWAS loci browser expansions).
To facilitate investigations of nominated risk variants, members of IPDGC have created a PD GWAS locus browser (https://pdgenetics. shinyapps. io/ GWASBrowser/) that makes relevant statistics and datasets available to the public  30. Throughout the hackathon, our team continued the development of this browser through the addition of new datasets and features. To identify secondary association signals at each locus from the Nalls et al. 2019 study, we performed conditional analysis using the Genome-wide Complex Trait Analysis (GCTA) tool  31, 32. Locus zoom plots were added to display the results of this conditional analysis (Fig. 4b )  33. Power calculations were done for each risk variant by Nalls et al. 2019 to determine if the findings were sufficiently powered. To do so, we followed methods used by the Genetic Association Study Power Calculator tool (https:// csg.