dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The study was facilitated by the  Government of Ghana  through the  Ghana Health Service. ARTIC  donated the primers used for the study. All data storage and analyses were performed on Zuputo®, the  University of Ghana 's high-performance computing cluster. We acknowledge the Community and Public engagement members;  Kyerewaa A. Boateng  and  Simon Donkor ,  Andrew M. Nantogmah  and the entire WACCBIP and  UHAS   COVID-19 Teams. The study was funded by a grant from the  Rockefeller Foundation  ( 2021 HTH 006 ), an  Institut de Recherche pour le Développement (IRD)  grant (ARIACOV),  African Research Universities Alliance (ARUA) Vaccine Development Hubs  grant with funds from  Open Society Foundation , a  Wellcome/African Academy of Sciences Developing Excellence in Leadership Training and Science (DEL-TAS) grant  ( DEL-15-007  and  107755/Z/15/Z : G.
Data availability The raw sequencing data (n = 1077) is available on the European Nucleotide Archive (PRJEB49489). Our previous data  9  (n = 46) are also available on GenBank with accession numbers ranging from MT890204-MT890249. The sequences and basic metadata information such as age, gender, location and sample collection date is freely available at GISAID (https://www. gisaid. org). All accession numbers for GISAID, GenBank, and European Nucleotide Archive are provided in Supplementary Data 1. The summary/ analysis tables used to generate the piecharts/stacked plots are available at https://github. com/misita-falcon/SARS-CoV-2-Manuscript-2021 (https://doi. org/10. 5281/zenodo. 6375851). The WHO dataset is available on the WHO website (https://covid19. who. int/ WHO-COVID-19-global-data.
csv). The reference genomes (GenBank number: MN908947. 3 and LR757998. 1) were obtained from Nextrain Github page (https://github. com/nextstrain/ncov/blob/master/data/references_sequences. fasta), but can also be obtained from GenBank (https://www. ncbi. nlm. nih. gov/nuccore/MN908947. 3, https:// www. ncbi. nlm. nih. gov/nuccore/LR757998. 1). Population and Housing Census data were obtained from the Ghana Statistical Service (GSS) (https://www. statsghana. gov. gh) and the map was downloaded from the Ghana Open Data Initiative (https://data. gov. gh/ dataset/shapefiles-all-districts-ghana-2012-216-districts).
2  B1 to 2 C3 and Fig. 4 ). Finally, selected individual Landau levels were resolved by means of so-called modulation of intensity by zero effort (MIEZE), a type of neutron spin-echo spectroscopy (Fig. 3 ). Owing to its incommensurate, multi-k nature, the magnon spectra and the magnetic response tensor of the skyrmion lattice could not be computed in spin wave simulation packages such as SpinW. We therefore developed the necessary simulation tools. Details of the procedures on all software tools are given in (17). The source code is provided as supplementary material  (39). The results of our theoretical calculations are shown on the right side of Figs. lines are the calculated quantitative magnon spectra E(q), whereas the magnetic response tensor χ ′′ ij (q, E) is shown in color shading. The latter is related by means of the fluctuation-dissipation theorem (eq.
Energy and momentum transfers are provided in two corresponding scales. The gray-shaded box marked scan (iv) denotes the location where the MIEZE data were recorded. CW: clockwise mode; CCW: counter-clockwise mode; BM: breathing mode; GM: Goldstone mode; HM1 to HM3: helimagnons of the conical state. Theoretical analysis tools: The magnon spectra and magnetic response tensor were calculated within linear spin wave theory as summarized in Sec. 7. The simulations were for a left-handed skyrmion lattice. For the determination of the excitation spectra over the wide range of exci-tation energies and momentum transfers addressed in our study, a theoretical framework had to be set up that allowed to identify the ground state of an incommensurate, long wavelength, multi-k structure. This is not possible within present-day numerical implementations of linear spin wave theory, such as SpinW  (44).
S6. We refer to this scattering geometry as setup 1. Data were recorded in the skyrmion lattice phase of MnSi around the (110) nuclear Bragg peak in an applied magnetic field directed along the vertical [001] axis. In the experiments at LET a magnetic field µ 0 H = 180 mT was applied at a sample temperature T = 28. 1 K. For these measurements the spectrometer was set up with an incident neutron energy of E i = 3. 2 meV. This corresponds to an energy resolution of 80 µeV at the elastic line. The locations of the traces in momentum space along [110] and [1 10] are denoted q ⊥,1 and q ⊥,2 , respectively. While q ⊥,1 cuts across a skyrmion lattice peak, q ⊥,2 is located between two skyrmion lattice peaks. Additional scans along [100] and [010] are denoted q ⊥,3 and q ⊥,4 , respectively. The experimental data recorded at LET for q ⊥,1 are shown in Fig.
Normalization of the scattering intensity To normalize the magnetic scattering for a quantitative comparison with theory, the data were corrected for non-magnetic contributions such as coherent and incoherent nuclear scattering, as well as spurious effects and multiple scattering due to the sample holder and the cryomagnet following the well-established method described in Ref. (54). For this procedure, four data sets were collected. First, we determined the scattering intensity I SkL,28. 1 K of the sample at T = 28. 1 K within the skyrmion phase. Second, a reference data set, I para,40 K , was recorded at T = 40 K in the paramagnetic phase well above the ordering temperature to isolate the nuclear scattering. Following this, two more background data sets were collected at the same temperatures as the two data sets with sample, however, using an empty sample holder, i.
Polarized neutron triple-axis spectroscopy Polarized neutron triple-axis spectroscopy (TAS) was performed in order to obtain direct spectroscopic evidence of the broad density of magnon modes perpendicular to the skyrmion lattice plane and its polarization dependence as compared with the well-defined individual excitations parallel to the skyrmion lattice. In addition these measurements served to provide evidence for the non-reciprocal character of the excitation spectra. Polarized triple-axis measurements allow to separate magnetic and nuclear scattering unambiguously. Finally, these measurements offer a straightforward way to rule out the presence of spurious scattering, this way generating data sets amenable for a critical comparison with theory.
For practical reasons, we pre-calculated the dynamical structure factors on a four-dimensional grid comprising the (Q, E) coordinates centered around the (110) Bragg peak. In turn, for the actual resolution-convolution we only needed to calculate the instrumental resolution for each coordinate and query the grid for the corresponding dynamical structure factor. The precalculation of the grid was performed at the Linux cluster computing facility at the ILL. Taken together, the resolution denoted by the black bars shown in the figures displaying the experimental data represent the incoherent energy width of the triple-axis spectrometer. Experimentally, the resolution function may be measured using a perfectly isotropic scatterer such as vanadium and the Bragg reflections of MnSi. Theoretically, it is given by the onedimensional Gaussian width obtained after three subsequent projections of the four-dimensional resolution ellipsoid along all three Q directions as explained above.
Graphically, the resolution may be estimated taking the maximum extent in Q of the projected resolution contour lines shown in Fig. S18. Our resolution calculation and data analysis software, Takin,  (57) (58) (59) (60)  is free and opensource. Its C++ code as well as that of its associated library  (70)  are available online at https://code. ill. fr/scientific-software/takin. The source code repository for the skyrmion calculation plugin for Takin, which was used to calculate the spectra and dynamical structure factors presented in our study may be found at https://code. ill. fr/scientific-software/takin/plugins/mnsi. A compilation of all source codes as used for the work reported in this paper is available online (39).
e. , effectively larger energy transfers  (72). As the limit of vanishingly small Fourier times leads beyond the spin-echo approximation, we wish to emphasize that the dynamical range covered in our study of MnSi is extremely well-behaved and perfectly consistent with the spin-echo approximation. For the MIEZE measurements sample 2 was oriented with the cylinder axis vertical and the magnetic field parallel to the neutron beam, respectively. In turn, a 001 axis was vertical. The orientation of the cylinder was chosen such that a 110 was horizontally perpendicular to the beam as depicted in Fig. S22. Data were recorded for a temperature of 28. 5 K and an applied field of 180 mT [Fig. S23 (A)] , where the largest elastic scattering intensity of the skyrmion peaks was found. The field was applied along the wave vector k i of the incident neutrons.
S26 (B ). These intensities provided an important point of reference when fitting the experimental data. Summarized in Tab. S4 are the calculated values of the imaginary parts of the magnetic response tensor, χ ′′ j , and the dynamical structure factor, S j , of the skyrmion lattice (j = SkL) Figure  S25 : Calculated magnon dispersion in the conical phase of MnSi  (25, 46). Panels A and B show the dispersion branches perpendicular (q ⊥ ) and parallel (q ) to the helical wavevector k h , respectively. The temperature T = 27. 5 K and the magnetic field µ 0 H = 170 mT are selected to be in close proximity to the skyrmion phase. Panel A corresponds to the setup used at RESEDA for the measurement of the dispersion in the skyrmion phase. The gray shaded area labelled scan (iv) marks the parameter range where the MIEZE data was recorded, cf.
(D) Calculated magnon spectra E(q) and spectral weight of the structure factor inferred from χ ′′ ij (q, E) in the conical phase. In (C) and (D), color shaded lines represent χ ′′ ij (q, E) in setup 2 used for polarized TAS, where red and blue denote the two spin-flip processes, SF(+-) and SF(-+), respectively. Energy and momentum transfers are provided in two corresponding scales. The gray-shaded box marked scan (iv) denotes the location where the MIEZE data were recorded. CW: clockwise mode; CCW: counter-clockwise mode; BM: breathing mode; GM: Goldstone mode; HM1 to HM3: helimagnons of the conical state.
Acknowledgments We wish to thank the staff at the  Institute Laue Langevin ,  Heinz Maier-Leibnitz Zentrum ,  ISIS Neutron and Muon Source ,  Paul Scherer Institut , and  SNS Oak Ridge  for support. We wish to acknowledge support by  E. Villard ,  P. Chevalier , and  J. Frank , as well as the instrumental control system by  J. Locatelli. We are, moreover, grateful for the IT support at the ILL cluster computing facility. We thank  M. Kugler  for the initial implementation of the model. A. B. and C. P. are supported through the  DFG  in the framework of  TRR80  (project  E1 , project-id 107745057),  SPP 2137 (Skyrmionics)  under grant number  PF393/19  (project-id 403191981),  ERC  Advanced Grants No. 291079  (TOPFIT) and 788031 (ExQuiSid), and  Germany 's excellence strategy EXC-2111 390814868.
R. G. is supported by the  DFG  under grant No. GE 971/5-1. M. G. is supported by the  DFG  in the framework of  SFB 1143  (project  A07 ; project-id 247310070), as well as grant numbers  GA 1072/5-1  (project-id 270344603) and  GA 1072/6-1  (project-id 324327023). Work by D. M. F. and M. J. was supported by the  LANL Directed Research and Development (LDRD) program  via the  Directed Research (DR)  project " A New Approach to Mesoscale Functionality: Emergent Tunable Superlattices  ( 20150082DR )". Early work by M. G. and J. W. on the spin wave theory was supported by the  Institute for Materials Science at Los Alamos  ( RR2015 ). This research used resources at the  Spallation Neutron Source , a  DOE Office of Science User Facility  operated by the  Oak Ridge National Laboratory. The data sets collected at LET have the DOIs:  10.
, San Diego, CA, USA). Trimming of sequencing raw reads and overall quality assessment was conducted using the pipeline AQUAMIS  [34]. For single-nucleotide polymorphism (SNP) analysis, the pipeline snippySnake (https: //gitlab. com/bfr_bioinformatics/snippySnake; accessed on 25 May 2021), based on Snippy (https://github. com/tseemann/snippy; accessed on 25 May 2021), was used. Three separate SNP analyses were carried out for the three different Listeria species found so as not to distort the analysis with interspecies variability. Optimal reference genomes for SNP analysis were automatically identified via the mash-based search included in the snippySnake workflow. Accordingly, NZ_CP026043. 1 (strain FDAARGOS_58) was used as reference for the analysis of L. mono cy togenes strains, NC_003212.
1 (strain Clip11262) was used as reference for the analysis of L. innocua strains, and NZ_LT906444. 1 (strain NCTC11857) was used as reference for the analysis of L. welshimeri strains. Complete linkage clustering of SNP distance matrices was performed in R. Trees were exported using the phylogram package and visualized in iTOL  [35]. Strains with single-digit SNP differences were rated as likely to be related to one another. The BakCharak pipeline (https://gitlab. com/bfr_bioinformatics/bakcharak; accessed on 27 May 2021) was used for MLST determination (database: pubMLST), as well as for screening of sequences for antimicrobial resistance genes (database: NCBI resistance gene database) and virulence factors (database: VFDB).
Acknowledgments: The authors thank the slaughterhouses for their cooperation in sampling and the  Institut Pasteur teams for curation and maintenance of BIGSdb-Pasteur databases  at http://bigsdb. pasteur. fr/;accessed on 23 January 2022. A big thank you to the whole team of the working group  Meat Hygiene ,  FU Berlin  for the laboratory work and help in sampling. Furthermore, many thanks to  Jan-Robin Redel  at the  German Federal Institute for Risk Assessment  for his technical assistance and  Yves van der Stede  from  EFSA  for his critical comments on the draft article. The publication of this article was funded by  Freie Universität Berlin.
Also, size and shape of inclusion were extracted from inclusions after image segmentation. Parameters that were normalized to an infection state without IAV inclusions (3hpi) are indicated by a dashed horizontal line. Above each boxplot, same letters indicate no significant difference between them, while different letters indicate a statistical significance at α = 0. 05. All data are displayed in Table  S1 (sheet1   (A -H) A549 cells stably expressing GFP, or Rab11a-WT were infected at a MOI of 3 with PR8 virus and, at the indicated time points, were fixed, and analysed by immunofluorescence using an antibody against NP (as a proxy for vRNPs). (C -H) Each dot is the average value of measured parameters per cell, and the continuous black lines are non-linear fitted models for all data. Above each boxplot, same letters indicate no significant difference between them, while different letters indicate a statistical significance at α = 0.
Determining inclusion topology and thermodynamics To determine the total concentration of vRNPs (NP as proxy) transported to the cytoplasm in relation to vRNPs produced in the nucleus (   ), a sum of slices of z-stacked images were used, otherwise, single plane images were analysed for other parameters. We used a custom (Fiji Is Just) ImageJ 2. 1. 0/1. 53p script for image processing using the following pipeline: (1. ) Segment cell periphery. (2. ) Segment and remove nucleus from the cell to make the cytoplasm. (3. ) From the cytoplasm, segment inclusions (4. ) Analyse the cytoplasm, nucleus, and inclusions for number and topological shape descriptors (5. ) Using the appropriate segmented region, measure the mean fluorescence intensity (as proxy of concentration) of cell, nucleus, cytoplasm, and cytoplasmic inclusion (See Figure  1B ).
Differential analysis of protein solubility Solubility is defined as the ratio of NP40-and SDS-derived abundances of proteins. This ratio was computed for all proteins measured in a dataset. The log2 transformed protein solubility was compared between different conditions (time points of infection or different cell line at 12 hours post infection) using limma. Proteins with |log2(fold change) | > 0. 5 and adjusted p-value (Benjamini Hochberg) < 0. 1 were considered significantly changed.
Gene ontology over representation analysis Differential abundant or soluble human proteins from infection time course or different cell line datasets were used for GO term "Biological processes" and/or "Cellular Compartments" overrepresentation analysis using clusterProfiler (R Bioconductor)  (Yu et al. , 2012). All identified proteins in each dataset served as the background. Standard settings were used for representing enriched GO terms (p-value cutoff: 0. 05, Benjamini-Hochberg procedure for multiple testing adjustment and q-value cutoff of 0. 2).
QUANTIFICATION AND STATISTICAL ANALYSIS After testing for homogeneity of variance, homogenously distributed data were assessed by parametric test using One-way ANOVA, followed by Tukey multiple comparisons of means. In contrast, non-homogenous data were assessed by non-parametric test with statistical levels determined after Kruskal-Wallis Bonferroni treatment. Alphabets above each boxplot represents the statistical differences between groups. Same alphabets indicate lack of significant difference between groups while different alphabets infer a statistically significant difference at α = 0. 05.
Mascot 2. 4 (Matrix Science) against a database containing Homo sapiens Uniprot FASTA ((proteome ID: UP000005640, downloaded on 14 May 2016) and Influenza A virus (strain A/Puerto Rico/8/1934 H1N1, proteome ID: UP000009255) along with known contaminants and the reverse protein sequences (search parameters: trypsin; missed cleavages 3; peptide tolerance 10 ppm; MS/MS tolerance 0. 02 Da; fixed modifications included carbamidomethyl on cysteines and TMT16plex on lysine; variable modifications included acetylation of protein Nterminus, methionine oxidation and TMT16plex on peptide N-termini).
ACKNOWLEDGEMENTS This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No. 101001521 ). Salary support from FCT : T. A. E, D. B. , V. M. are funded by PhD fellowships ( PD/BD/128436/2017 ,  PD/BD/148391/2019  and  UI/BD/152254/2021 ) and S. V. C by D. L. 57.
FIJI This paper https://imagej. net/software/fiji/ R This paper https://www. r-project. org/ Trackmate plugin  (Ershov et al. , 2022; Tinevez et al. , 2017)  https://imagej. net/plugins/trackmate/ limma  (Ritchie et al. , 2015). https://bioconductor. org/packages/rele ase/bioc/html/limma. html ClusterProfiler (R Bioconductor)  (Yu et al. , 2012). https://bioconductor. org/packages/rele ase/bioc/html/clusterProfiler. html isobarQuant https://doi. org/doi:10. 18 129/B9. bioc. isobar https://www. bioconductor. org/package s/release/bioc/html/isobar. html Data availability and code availability • The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (PubMed ID: 34723319) partner repository with the dataset identifier PXD034778. o Reviewer account details: o Username: reviewer_pxd034778@ebi.
ac. uk o Password: BprURfLw • All computer code or algorithm used to generate the results reported in the paper are available at 10. 5281/zenodo. 7292888. • All experimental data shown in Figure 1-8 and Figure S1-2 is available from the corresponding author upon request. Sequences of described viruses are accessible from the NCBI virus under accession number GCF_000865725. 1. Source data are provided with this paper in 10. 5281/zenodo. 7292888.
5281/zenodo. 7292888 Penicillin-Streptomycin Recombinant DNA Biowest Cat#L0022-100 Solution GFP-NP This paper N/A Dimethyl (DMSO) mcherry-NP sulfoxide BioLabs This paper Cat#B0515A N/A Formaldehyde, extra pure, solution 37-41%, AR grade NP photoactivatable cherry- Acros This paper Cat#10231622 N/A (Fisher Chemical) photoactivatable GFP-NP This paper N/A Fetal Bovine Serum, ThermoFisher Cat#10500064 qualified, heat inactivated, Brazil (Gibco™) Nucleozin Target Mol Cat#282T7330 1,6-Hexanediol Aldrich Cat#240117-50G Triton-X-100 Sigma Cat#X100 Dako Faramount Aqueous Agilent Technologies Cat#S3025 Mounting Medium Complete protease Merck Cat#11836170001 inhibitor cocktail PhosphoStop Merck Cat#4906837001.
Amplicons were purified with ExoSAP-IT (Applied Biosystems) according to the manufacturer's instructions and sent for sequence analysis (Baseclear, Leiden, The Netherlands). Resulting sequences were analysed using BioNumerics v7. 6 (Applied Maths NV, Sint-Martens-Latem, Belgium) and the spa types were assigned by use of the RidomStaphType database (Ridom GmbH, Würzburg, Germany). 16S ribosomal RNA sequencing of nasal microbiota. The impact of decolonization on the nasal microbiome and the recovery of the microbiome structure after decolonization were examined by means of 16S rRNA metabarcoding. Amies medium from each nasal swab container was stored at -80 °C on the day of receipt at the study laboratory in Rotterdam, NL, then sent at -80 °C to the microbiome analysis laboratory in Lyon, FR.
PCR adapters were removed with cutadapt v. 2. 1 (Martin 2011) then dereplicated using vsearch v. 2. 12. 0 29 with the sizeout option. For species assignment, reads were aligned to sequences of NCBI blast 16S_ribosomal_RNA database (version date 03. 12. 2020) using Blastn v. 2. 11. 0+  30, 31  , keeping a maximum of 20 reference targets. Read counts per bacterial species were normalized to account for taxon-specific variations of the copy number of 16S rRNA genes using NCBI rrnDB-5. 5 database based on the mean gene copy number in the taxon. To optimize the resolution of sequencing read taxonomic assignment, we used in-house bioinformatic software publicly available at https:// github. com/ rasig adelab/ taxon resol ve. Briefly, when a read matches sequences from several species with identical alignment scores, taxonomic assignment pipelines typically output the higher taxonomic level such as the genus (e.
g. , Staphylococcus spp. when a read matches S. aureus and S. epidermidis). This loss of information can be problematic when species-level discrimination is important. To prevent losing species-level information, the taxonresolve software assigns reads with uncertain species to groups of species rather than to genera. Bacterial species deemed present from contaminating sources such as kits reagents and found in negative controls, mostly from the Bacillus genera, were removed. A total of 1376 species or group of species were retained. The rarefaction curves corresponding to the sequencing effort to assess the species richness within samples are shown in Supplementary Fig. 3. Most samples reached a plateau after 40,000 sequences. Given the small sample size compared to the number of variables and species considered in this study, no hypothesis testing was performed, and we provide a descriptive assessment of the results.
In figures, 95% confidence intervals of the means were computed based on normal approximation, after log transformation for CFU/ mL and log odds transformation for quantities restricted to the [0, 1] interval, such as proportions. In microbial diversity analyses, we retained the 9 most prevalent bacterial species and pooled the other species into an 'Others' category. To assess the disruption and possible recovery of the microbiota, the divergence of sampled microbiota relative to the initial, pre-treatment microbiota (D0) was assessed using the Bray-Curtis dissimilarity at each sampling time point relative to the first sample of the same patient. Software code of the analyses are available at https:// github. com/ rasig adelab/ macot ra-metab arcod ing. Data are available at https:// zenodo.