dataesr/scientific-paragraphs-categorization huggingface dataset:
46262) for 30 seconds. Every scan is the average of 2 micro-scans, AGC was set to 1 × 10 6 , and maximum ion IT was set to 50 ms. LPA, lysophosphatidylinositol, and LPS were detected in the 2:1 extract, by negative ion mode FTMS as deprotonated ions by scanning m/z = 400-1,100 Da, at R m/z = 200 = 280,000, with lock mass activated at a common background (m/z = 529. 46262) for 30 seconds. Every scan is the average of 2 micro-scans, AGC was set to 1 × 10 6 , and maximum ion IT was set to 50 ms. All data were acquired in centroid mode. All lipidomics data were analyzed with the lipid identification software LipidXplorer  (79). Tolerance for MS and identification was set to 2 ppm. Data postprocessing and normalization to internal standards were done manually in Microsoft Excel. For the sake of simplicity, only the pertinent data are displayed (LysoPLs, triglycerides, and CE-Chol) and normalized to the total lipid identified.
Acknowledgments This work was funded by grants from  l'Agence de la Biomédecine (Appel d'offre Recherche et Greffe)  and  La Fondation du Rein  ( Prix Michel Olmer ). HL is supported by  SIRIC CARPEM. Address correspondence to:  Nicolas Pallet ,  INSERM  UMRS1138,  Centre de Recherche des Cordeliers, 15 rue de l'Ecole de Médecine , 75006  Paris, France. Phone: 33156092435; Email: nicolas. pallet@aphp. fr.
Data availability Expression profiling by high-throughput sequencing for human kidney transplant biopsies is available at GEO (GSE126805). Expression profiling by high-throughput sequencing for mouse IRI (bulk RNA-Seq) is available at GEO (GSE98622). snRNA-Seq data of mouse IRI are available at GEO (GSE151167 and GSE139107). Expression profiling by array for human diabetic kidneys is available at GEO (GSE30122). Expression profiling by high-throughput sequencing for UmodC147W/+ kidneys and UMOD-expressing epithelium are available at GEO (GSE1102566). Transcriptomic data for human CKD patients and healthy donors are available at Nephroseq at the data set titled "Ju CKD TubInt. " Raw data of metabolomic and lipidomic analyses and clinical data are available from the corresponding authors upon reasonable request.
2021 ) and the timings of the HCS crossings determined from magnetic sector measurements taken in situ at PSP. In the present case, the magnetic maps from the Air Force Data Assimilative Photospheric flux Transport (ADAPT) model  (Arge et al. 2010 (Arge et al. , 2011 (Arge et al. , 2013) )  for April 16 12:00 UT (8th realisation) and March 1 12:00 UT (11th realisation) were selected assuming a source surface height of 2. 0 R and 2. 5 R , respectively. The vertical (radial) projection of PSP orbit onto the solar disk is plotted in cyan; the stars indicate several dates at PSP. The magenta surfaces represent the projections of the regions scanned by WISPR-I at the time of the two images shown in Fig. 2 , with a solid line indicating the location of the Thomson sphere extracted at = 22 •. A108, page 4 of 22 the above transients originate from and propagate within the streamer belt, we identified two possible source regions that have an inclination consistent with the April 2021 and March 2022 events observed by WISPR.
e. the 10 R case treated with the 2. 5D set-up). Having simulation snapshots at a higher cadence than WISPR could also help to get a better match by allowing the synthetic images to mimic the 'blurring' effect of exposure time. Furthermore, simulation duration of more than one day would be preferable to maximise the scientific output. This can easily be achieved in a 2. 5D context, but implies large amounts of data in full 3D modelling set-ups, a challenge to reach with modern computational facilities.
Acknowledgements. The authors are indebted to an anonymous referee whose valuable suggestions greatly improved this work. This research has been funded by the  European Research Council (ERC)  under the grant agreement  DLV-819189. This research was also supported by the  Research Council of Norway , project number  324523 , and through its  Centres of Excellence  scheme, project number  262622. A. K. was supported by  NASA's Parker Solar Probe  mission under contract  NNN06AA01C. The authors are grateful to  Nicholeen Viall  and  Angelos Vourlidas  for insightful discussions, and the WISPR team for providing the data. The Wide-Field Imager for Parker Solar Probe (WISPR) instrument was designed, built, and is now operated by the  US Naval Research Laboratory  in collaboration with  Johns Hopkins University/Applied Physics Laboratory, California Institute of Technology/Jet Propulsion Laboratory, University of Gottingen, Germany ,  Centre Spatial de Liege, Belgium  and  University of Toulouse/Research Institute in Astrophysics  and Planetology.
Data sources and search strategy The PubMed/Medline, Cochrane and Embase databases were searched from 8 to 11 November 2019 by equations created with the librarians of the Clermont-Ferrand Faculty of Medicine (NPD) and the Paris Descartes Faculty of Medicine (MC and IB) (Appendix 2). The SuDoc, LiSSa and BDSP databases were searched with the terms ''prescription'' and ''general medicine''; the term ''nonprescription'' referred to drugs with optional medical prescriptions. An additional manual search was performed on Google Scholar, European health agency websites, in European MD databases and in bibliographies of selected studies.
Strengths and limitations Most of the qualitative studies were French  (16 of 17). It is possible that the fact that prescription-free consultations are rare in France encourages exploratory studies with qualitative methods. The comparison of figures between countries is not adjusted for many organisational and cultural elements, but trends are researched longitudinally. Qualitative studies could also be limited by social desirability bias in patient responses. The studies were assessed using quality grids, and only those with a quality score above 50% were retained. This selection ensured the quality of the data on which this work was based. One of the strengths of our work was the inclusion of both quantitative and qualitative studies to contextualise the rate of GP prescription-free consultations and patients' perceptions.
The pharmaceutical industry GPs who receive a medical visit from a member of the pharmaceutical industry have fewer consultations without a prescription, which is the only statistically significant criterion  [14, 30]. GPs could be supported in rational drug prescribing  [30]. The Swedish Wise List contains 200 essential medicines for primary care, prescribers and the public  [31, 32]. In France, there is no list of essential medicines, and the public database of medicines that allows the general public and health professionals to access data and reference documents on marketed medicines (government website) is underused  [33]. In 2011, the French National Authority for Health (HAS) mentioned the poor information provided to general practitioners on recommended nondrug therapies  [33]. It cited measures to be implemented similar to the solutions presented in the articles in our review (preventive consultations, advice sheets).
The TULIP project (https://anr. fr/Projet-ANR-18-CE31-0023) aims to produce radioactive ion beams of short-lived neutron-deficient isotopes using fusion-evaporation nuclear reactions in an Isotope Separator On Line (ISOL) system. A Ni target was chosen to produce Rb and Sn isotopes, and was bombarded, respectively, by Ne and Cr primary beams at energies close to the Coulomb barrier. Owing to the Target Ion Source System (TISS) configuration, the operational TISS temperature had to be close to 1300°C. Several tests were performed to determine a configuration able to cope with the constraints related to the TISS, target and beam. This article presents a brief description of the TULIP principles and objectives, and the development of the Ni target. 4 µm Ni target 200 µm Graphite Catcher Rb + RIB 22 Ne beam Hot cavity.
Data collection, structure determination and refinement X-ray diffraction data were collected at 100 K using synchrotron radiation (Supplementary Table  2 ) at Soleil (France) and processed using XDS  58  and AIMLESS from the CCP4 suite  59. A 2. 35 Å dataset from a Glp crystal soaked in Cl 4 K 2 Pt was used to solve the structure by SAD phasing using Phaser  60  and automatic model building with Buccaneer both from the CCP4 suite. The structures of Glp alone and in complex with FtsZ CTD were refined through iterative cycles of manual model building with COOT  61  and reciprocal space refinement with Phenix  62. The final crystallographic statistics and the PDB deposition codes of the atomic coordinates and structure factors are shown in Supplementary Table  2. Structural figures were generated with ChimeraX  63.
Protein identification and data analysis PatternLab for Proteomics V (PatternLabV) was used to perform peptide spectrum matching and label-free quantitation analyses on the Article https://doi. org/10. 1038/s41564-023-01473-0 basis of extracted-ion chromatograms (XIC)  67. XICs were obtained by integrating the intensity of a given peptide's ion current over a narrow mass-to-charge window as a function of retention time. For the SepF interactome, a target reverse database was generated using the Cglu ATCC13032 proteome downloaded from UniProt (November 2018), to which the sequences of Scarlet, SepF-Scarlet, SepF K125E/F131A -Scarlet and the most common contaminants in proteomics experiments were added. For the GLP interactome and the global proteome, a target reverse Cglu ATCC13032 database downloaded from UniProt (November 2021) including the most common contaminants in proteomics was used.
To identify GLP interactors, we compared the proteins recovered from Cglu or Cglu_Δglpr with Cglu_Δglp strain. PatternLab's Venn diagram statistical module was used to determine proteins uniquely detected in each biological condition using P < 0. 05 (ref. 68). In addition, pairwise comparison between Co-IPs and controls was performed using the XIC browser on the basis of the Benjamini-Hochberg theoretical estimator to deal with multiple t-tests and the following conditions: maximum parsimony, minimum number of peptides of 1, minimum number of MS1 counts of 5 and log 2 FC > 1. 8. Enrichment factors for SepF interactors were calculated as the ratio of the normalized spectral abundance factor of each interactor in the interactome to that in the proteome. To compare the recovery of SepF interactors in pull-down analyses of SepF-Scarlet and Sep-F K125E/F131A -Scarlet strains, the signal (ΣXIC of detected peptides in each replicate) was normalized by the signal of SepF in the corresponding sample.
Images were collected using Zen Blue 2. 6 (Zeiss) and analysed using the software Fiji  69  and the plugin MicrobeJ  70  to generate violin plots and fluorescence intensity heat maps. Heat maps represent the averaged localization of the mNeon-tagged protein on a representative cell. For all analyses, the Cglu strain corresponds to Cglu + empty plasmid. For Cglu_Δglpr + GlpR-mNeon, only cells showing a mean intensity of mNeon fluorescence >35,000 were considered, to discard cells that lost the plasmid.
Protein database assemblies For the sequence analyses in Actinobacteria, we assembled two databases representing all Actinobacteria diversity present at the National Center for Biotechnology (NCBI) as of February 2021: ACTINO_DB (244 taxa) and ACTINO_REDUCED_DB (113 taxa from ACTINO_DB). For ACTINO_DB, we selected 5 species per class, except for class Corynebacteriales, where we selected 5 species per order (Supplementary Table  3 ). For the phylogenetic analyses in Bacteria, we assembled a database on the basis of the one provided in ref. 73. We reduced the taxonomic sampling to 76 species by removing all candidate phyla (Supplementary Table  4 ).
Homology searches and mapping To identify all MoeA homologues in the ACTINO_DB, we used HMM profile searches. We used the HMMER package (v. 3. 3. 2) 74 tool 'jackhmmer' to look for homologues of Glp and GlpR in all the proteomes, respectively using the GenBank 75 sequences BAB98276. 1 and BAB98278. 1 as query. The hits were aligned with mafft (v. 7. 475)  76  using default parameters. Alignments were manually curated, removing sequences that did not align. The hits obtained by jackhmmer might not include sequences that are very divergent from the single sequence query. For this, the curated alignments were used to create HMM profiles using the HMMER package tool 'hmmbuild'. Curated HMM profiles for Glp and GlpR were used for a final round of searches against the ACTINO_DB and Bacteria databases, using the HMMER tool 'hmmsearch'.
Phylogenetic analyses The alignments of Glp homologues (including all MoeA paralogues) were trimmed using BMGE (v. 1. 2)  79   68. Proteins enriched in SepF Co-IPs when compared to controls were identified using pairwise comparison module of Patternlab V based on XIC intensities. 20, 22 and 98 proteins were detected as SepF interactors in Cglu/α-SepF (strain/antibody), Cglu_SepF-Scalet/α-SepF and Cglu_SepF-Scalet/α-Scarlet respectively. 12 proteins were common to all of Co-IPs, and for 11 of them an enrichment factor in relation to the total proteome could be calculated, and thus represent the core SepF interactome (Supplementary Table  1 ,a and Fig. 1a ). One additional interactor, the hypothetical protein Cgl1805, could not be detected in the proteome and no enrichment factor could thus be reported.
Acknowledgements We thank the core facilities at the  Institut Pasteur C2RT, P. England ,  B. Raynal ,  S. Brûlé  ( PFBMI );  P. Weber ,  C. Pissis ,  A. Mechaly  ( PFC ), and  J. Fernandes  and  A. Salles  ( UtechS PBI / Imagopole , supported by  France   BioImaging ;  ANR-10-INSB-04 ; Investments for the Future);  P. Campagne  from the Bioinformatics and Biostatistics Hub from the IP-C3BI; the synchrotron source  Soleil (Saint-Aubin, France ) for granting access to the facility and the staff of Proxima 1 and  Proxima 2A  beamlines for helpful assistance during X-ray data collection. Molecular graphics were done with ChimeraX, developed at  UCSF  with support from  NIH  ( R01-GM129325 ) and  NIAID. This work was supported in part by grants from the  Agence Nationale de la Recherche (ANR, France) , contracts  ANR-18-CE11-0017  (P.
M. A. ) and  ANR-21-CE11-0003  (A. M. W. );  Agencia Nacional de Investigacion et Innovacion (ANII, Uruguay) ,  FCE_1_2019_1_155569  (R. D. ),  FOCEM-COF 03/11  (R. D. ),  ECOS-Sud France-Uruguay , contract  U20B02  (A. M. W. and R. D. ); and by institutional grants from the  Institut Pasteur , the  CNRS , and  Université Paris Cité. J. P. was funded through the  AMX programme  from the  Ecole Polytechnique. A. S. was part of the  Pasteur-Paris University  ( PPU) International PhD Program , funded by the  European Union 's  Horizon 2020 research and innovation programme  under  Marie Sklodowska-Curie  grant agreement no. 665807. Q. G. was funded by  MTCI PhD school  ( ED 563 ). A. R. was funded by  ANII, CAP (UdelaR)  and  PEDECIBA.
Data availability Atomic coordinates and structure factors have been deposited in the PDB with accession codes 8BVE (Glp) and 8BVF (Glp-FtsZ CTD ). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  81  partner repository with the dataset identifier PXD037255. All phylogenetic data used to produce our results are provided as Supporting Data at https://doi. org/10. 17632/265wyk8r3f. 1. All materials of this paper can be provided upon reasonable request. Custom scripts will be made available upon request. Source data for all relevant figures are provided with this paper.
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A description of any restrictions on data availability -For clinical datasets or third party data, please ensure that the statement adheres to our QQ!i. Qc Atomic coordinates and structure factors have been deposited in the PDB with accession codes 8BVE (Glp) and 8BVF (Glp-FtsZCTD). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE81 partner repository with the dataset identifier PXD037255 (http:// www. ebi. ac. uk/pride/archive/projects/PXD037255). All phylogenetic data used to produce our results is provided as Supporting Data under the following link: https://data.
Left: molecular weight markers (kDa); Lanes 1: mNeon-MoeA1 (sucrose); 2: mNeon-MoeA1 (gluconate); 3: mNeon-Glp (sucrose); 4: mNeon-Glp (gluconate); 5: mNeon-MoeA3 (sucrose); 6: mNeon-MoeA3 (gluconate). Extended Data Fig. 2 | Glp-FtsZ interaction. (a) BLI sensorgrams of FtsZ binding to immobilized Glp in the presence or absence of 1 mM GTP. (b) Normalized melting curves of Glp with or without 1 mM FtsZ CTD peptide as determined by a thermofluor assay. Glp was stabilized by 2 °C in the presence of FtsZ CTD. (c) The crystal structures of ligand-free (red) and FtsZ CTD -bound (blue and yellow ligand). Glp can be superimposed with an r. m. s. d. of 0. 64 Å for 392 equivalent Cα atoms. (d) Electron density map of FtsZ CTD bound to Glp monomer B contoured at 1. 2 σ. (e) Comparison of the Glp-FtsZ CTD complex (red, left panel) with the Gephyrin-GlyR complex (blue, right panel, PDB code: 2fts).
After calving, all cows received the same basal lactation diet once a day  (1. 60  Mcal of NE L /kg and 15. 6% CP). Both diets were fed as a total mixed ration. At -30 d before calving, cows were assigned to either a basal diet (control; 114 g/h/d ground corn; n = 20) or basal plus the Culture Classic HD yeast culture (YC; 100 g ground corn + 14 g of YC/d; n = 20). The treatments were top-dressed once a day from -31 ± 6 to 50 DIM. The cows were enrolled in the experiment from mid-September 2018 to early April 2019. Cows were fed using an individual gate system (American Calan, Northwood, NH, USA), and the intake of dry matter (DM) was recorded daily. Diets were formulated using the CNCPS model (v. 6. 55)  [15]  contained in the NDS professional ration formulation software (v. 6. 55; RUM&N, NDS Professional, Reggio Emilia, Italy).
In this study, the genes Golgin A5 (GOLGA5), Oxysterol Binding Protein Like 2 (OSBPL2), and Single-Strand-Selective Monofunctional Uracil-DNA Glycosylase 1 (SMUG1) were used as internal control genes (ICGs), as described by Moyes et al. [22]. The final gene expression data were normalized with the geometric mean of the 3 internal control genes. The stability of the ICG was assessed using the geNorm software  [23]  with a favorable final pairwise variation of 0. 17. Target genes measured are described in Supplemental Table  S2 , and these were related to inflammation (tumor necrosis factor alpha (TNFA), nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 (NFKB1), interleukin 1B (IL1B) and interleukin 10 (IL10), TNF receptor associated factor 6 (TRAF6), and myeloid differentiation primary response 88 (MYD88)), cell receptors and signaling (toll-like receptor 2 (TLR2), toll-like receptor 4 (TLR4), selectin-L (SELL), interleukin 1 receptor associated kinase 1 (IRAK1), Z-DNA binding protein 1 (ZBP1), integrin subunit alpha M (ITGAM), talin 1 (TLN1), and vinculin (VCL)), and oxidative stress (nuclear factor erythroid 2-related factor 2 (NRF2), superoxide dismutase 1 (SOD1), superoxide dismutase 2 (SOD2), and myeloperoxidase (MPO)).
Statistical Analysis Blood biomarkers and gene expression data were analyzed using the MIXED procedure of SAS 9. 4 (SAS Institute Inc. , Cary, NC, USA) using treatment, time (day or week), parity, and 2-and 3-way interactions with treatment as fixed effects and cow nested within treatment as a random effect. Parity and its interactions were tested and removed from the model when p > 0. 20. The exponential correlation covariance structure SP for repeated measures was used for the analysis of gene expression and blood biomarker data with the following model: y ijk = µ + D i + P j + DP ij + T k + DT ik + DPT ijk + α l + e ijkl where y ijk is the dependent, continuous variable; µ is the general mean; D i is the fixed effect of the treatment (i = 1 or 2, namely, control or YC); P j is the fixed effect of the jth parity (j = 2nd or 3rd), DP ij is the fixed effect of the ith treatment by the jth parity of the experiment interaction; T k is the fixed effect of the kth time (j = 1, 2, 3, or 4, namely, -30, 5, 15, and 30 DIM); DT ik is the fixed effect of the ith treatment by the kth time of the experiment interaction; DPTijk is the fixed effect of the ith treatment by the jth parity by the kth time of the experiment interaction; α l is the random effect of individual; e ijkl is the residual error.
Blood biomarker data were log-scale transformed if needed to comply with normal distribution of residuals and subsequently back-transformed. Gene expression data were transformed as fold change relative to -30 d and then log-transformed prior to statistical analysis. Data on day -30 were used as a covariate for blood biomarkers. Data were analyzed as repeated measures using the exponential correlation covariance structure (POW). The covariate of previous lactation milk yield was maintained in the model for all variables for which it was significant (p < 0. 05). Separation of least square means for significant effects was accomplished using the Tukey option within the MIXED procedure of SAS. Statistical significance was declared at p ≤ 0. 05 and tendencies at p < 0. 10.
Supplementary Materials: The following supporting information can be downloaded at: https://doi. org/10. 6084/m9. figshare. 21625175. v3, Table  S1 : GenBank accession number, hybridization position, sequence and amplicon size of primers for Bos taurus used to analyze gene expression by qPCR; Table  S2 : Genes selected for transcript profiling in bovine polymorphonuclear leukocytes (PMNL) and their biological functions 1 ; Figure  S1 : Independent analysis of the Parity × treatment effect in polymorphonuclear leukocyte mRNA expression of interleukin 10 (gene symbol IL10; p = 0. 04), Z-DNA binding protein 1 (gene symbol ZBP1; p < 0. 01), vinculin (gene symbol VCL; p = 0. 02), superoxide dismutase 1 (gene symbol SOD1; p = 0. 05). Difference in mRNA expression between YC cows and control in 2nd lactation cows is denoted by an asterisk (*) for IL10 (p = 0.
Effects of the thermal stress gradient To evaluate the EF-associated effects of thermal stress, we examined the relationships between distance of host populations from the warm edge range limit at Tenza Beach (Distance) and the following three variables: mussel shell length (Length), percent cover of endolithic infestation (Degradation), and number of barnacle epibionts on shells (Epibiosis). We also examined the relationships between Length and Degradation, Length and Epibiosis, and Degradation and Epibiosis. None of the four variables (i. e. , Distance, Length, Degradation, and Epibiosis) were normally distributed (Shapiro-Wilk normality test, W ranged from 0. 233 to 0. 988, p < 0. 001 in all cases), even after data transformations. GzLMs were used to determine the relationship between each pair of variables.
The relationship between Distance (independent variable) and Length was assessed using a GzLM with a Gaussian distribution and an identity link function (Relationship #1a on all individuals). Due to potential sitespecific variability in recruitment, we re-assessed this relationship by removing all settlers and recruits, defined as individuals that were <1. 0 cm in length  (Harris et al. , 1998; Radloff et al. , 2021) , from the dataset (Relationship #1b on post-recruitment-sized individuals). We further investigated this relationship by considering only adults, defined as individuals that were >3. 5 cm in length  (Harris et al. , 1998) , in the GzLM (Relationship #1c on adult-sized individuals). Next, the relationships between Distance (independent variable) and Degradation (Relationship #2) and Length (independent variable) and Degradation (Relationship #3) were both examined using a GzLM with a Poisson distribution and a log link function.