dataesr/scientific-paragraphs-categorization huggingface dataset:
AUTHOR CONTRIBUTIONS SLL conceived, designed experiments, researched data, and wrote the manuscript. JA and MD conceived, designed experiments, researched data, and reviewed and edited the manuscript. MM, LV, and AF acquired data, analyzed data, and reviewed the manuscript. FG, SD, and JB recruited patients and reviewed the manuscript. GS analyzed data and reviewed the manuscript. OH, MCM, and RA reviewed and edited the manuscript. SLL is the guarantor of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
ACKNOWLEDGMENTS We thank  Pr R. Bucala  ( Yale University, New Haven, USA ) for providing MIF À/-and WT MEFs, as well as neutralizing MIF antibodies and isotype controls. We thank  Dr Isabelle Dugail  ( INSERM UMRS 1166 , team 6  Nutriomics, Paris, France)  for providing 3T3-L1 cells. We thank the  staff of Centre Hospitalo-Universitaire d'Angers  for analysis of clinical data of METABOL cohort. We thank  J-C Gimel  ( INSERM U1066 ,  MINT Team, Angers, France ) for providing access to NTA technology. This work was supported by a research grant from  Société Francophone du Diabète ,  Inserm, Université d'Angers and Centre Hospitalo-Universitaire d'Angers. JA and MD are recipients of a doctoral fellowship from  French Ministry of Education and Research.
Statistical analysis. Data were expressed as median with interquartile range. Comparisons of different groups were done via Kruskal-Willis test with Dunn's correction for data that did not pass D' Agostino & Pearson normality test or a one-way ANOVA with Dunnett correction for data that did pass D' Agostino & Pearson normality test. All analyses were done using GraphPad Prism 7 statistical software (GraphPad Software). A p value of < 0. 05 was considered as statistically significant.
90; p < 0. 0001). A similar high correlation between IL-1β and LPSs introduction was also observed (r = 0. 92; p < 0. 0001) (Fig. 1B ). In contrast, no correlation was seen to exists between conventional E. coli LPS and MPLA (TNF: r = 0. 29; data not shown) or between highly purified LPS and MPLA (TNF: r = 0. 26; Fig. 1C ). However, there was a significant correlation between hpLPS and MPLA when IL-1β was analyzed (r = 0. 63, p < 0. 0001). Similar observations were made when a highly purified rough Re LPS was used and compared to highly purified LPS (r = 0. 94, p < 0. 0001) or MPLA (r = 0. 28, ns) in terms of TNF production (Fig. 1D ) or IL-1β production (data not shown). Importantly, neither cLPS, hpLPS, nor MPLA, at the concentrations used, significantly affected the viability of the adherent cells compared to the controls (medium alone) as assessed by the MTT assay.
Signaling pathways involved in response to LPS and MPLA. The Syk pathway has been recently demonstrated to be associated with a LPS-co-receptor (namely CD300b)  13. We investigated whether a Syk inhibitor (compound R406) could help discriminate between LPS and MPLA induced activation (Fig. 9 ). TNF and IL-1β productions induced by all the LPSs were altered by the addition of the Syk inhibitor. As expected, the compound R406 fully prevented cytokine productions induced by zymosan, but it did not have a clear effect on MPLA induced TNF and IL-1β production. Various Western blot analyses were carried out with the aim to differentiate the activation of human monocytes via LPS versus MPLA. Of note, we failed to find any significant differences in ERK1/2, p-38 MAP kinase, JNK, and IκBα phosphorylation (data not shown).
Flow cytometry Cells were acquired using a custom-built 20 parameter FACSAria II (BD Biosciences) and analyzed with FlowJo software (Tree Star). The commercial mAbs used in this study are listed in Supplemental Table  I. Killer cell lectin-like receptor subfamily G member 1 (KLRG1)-AF488 was a kind gift from Prof. H. Pircher (University of Freiburg). Intracellular staining was performed using a FOXP3/Transcription Factor Staining Buffer Set (eBioscience). For the detection of cytokines, samples were depleted of regulatory T (TREG) cells using CD25 microbeads (Miltenyi Biotec) prior to stimulation with PMA (50 ng/ml) and ionomycin (750 ng/ml) for 6 h in the presence of brefeldin A (10 mg/ml) for the final 4 h. Streptavidin-QD605, streptavidin-BV605, or streptavidin-allophycocyanin (BD Biosciences) were used with biotinylated anti-CCR8 clones 433H or 414B (American Type Culture Collection) to detect CCR8 expression as reported previously  (17).
Transcriptome analysis Total RNA was isolated using a Qiagen RNeasy Micro Kit (Qiagen), and cDNA was generated using a SMARTer Kit (Clontech). Libraries were prepared using a Nextera Kit (Illumina). Next-generation sequencing was performed using the Illumina HiSeq 2500 System with TruSeq Technology (Illumina). Transcriptomes were characterized via paired-end, 50 bp RNA sequencing (RNA-Seq) runs (10 samples per lane), ensuring at least 30 3 10 6 mapped reads per sample. Analysis of gene expression was first evaluated using TopHat  (21)  and Cufflinks  (22). A paired analysis was then performed, whereby data were mapped to the human assembly (Homo_sapiens. GRCh38) using the Burrows-Wheeler Alignment tool  (23) , and raw read counts per gene/transcript were assigned using featureCounts  (24).
Molecular analysis of TCR usage TCR clonotyping was performed using a template-switch anchored RT-PCR  (27). Amplicons were subcloned, sampled, Sanger sequenced, and analyzed as described previously  (28). Assembly of TCR sequences from short-read RNA-Seq data was performed using MiXCR software  (29) , and postassembly repertoire analysis was performed using VDJTools  (30). For repertoire overlap, similarity was measured as the clonotype-wise sum of the geometric mean frequencies and calculated as: F 2 ij ¼ + N k¼1 ffiffiffiffiffiffiffiffiffiffiffiffi ffi w ik w jk p ; where w ik and w jk are the frequencies of clonotype k in samples i and j, respectively, and N is the total number of overlapping clonotypes.
To test the idea that CCR8 + and CCR8 2 skin T cells differ phenotypically as a consequence of Ag exposure rather than differentiation status, we conducted an unbiased molecular analysis of expressed TRB gene rearrangements in each subset using a template-switch anchored RT-PCR  (45). Irrespective of CCR8 expression, skin T cells were highly polyclonal, although clonotypic diversity within the CD4 + subset was markedly restricted in one case (donor 24; Fig. 7B , Supplemental Fig. 2 ). Among all three donors tested, only one TCRb amino acid sequence was shared between the CCR8 + and CCR8 2 fractions within the CD4 + and CD8 + T cell subsets (donor 26; Fig. 7B ). To extend these findings with greater coverage, we used MiXCR software to assemble CDR3b sequences from the RNA-Seq data  (29). In line with our initial analysis, we found that the CCR8 + and CCR8 2 fractions were polyclonal and displayed similar levels of diversity within both the CD4 + and CD8 + T cell subsets (Fig.
ACKNOWLEDGMENTS We thank the staff of the  Collider-Accelerator and Physics Departments at Brookhaven National Laboratory  and the staff of the other PHENIX participating institutions for their vital contributions. We acknowledge support from the  Medium Energy Nuclear Physics Program in the Office of Nuclear Physics in the Office of Science of the Department of Energy , the  National Science Foundation ,  Abilene Christian University Research Council, Research Foundation of SUNY, and Dean of the College of Arts and Sciences, Vanderbilt University (U. S. A) ,  Ministry of Education, Culture, Sports, Science, and Technology  and the  Japan Society for the Promotion of Science (Japan) ,  Conselho Nacional de Desenvolvimento Científico e Tecnológico and Fundação de Amparo à Pesquisa do Estado de São Paulo (Brazil) ,  Natural Science Foundation of China (People's Republic of China) ,  Croatian Science Foundation and Ministry of Science and Education (Croatia) ,  Ministry of Education, Youth and Sports (Czech Republic) ,  Centre National de la Recherche Scientifique ,  Commissariat à l' Énergie Atomique , and  Institut National de Physique Nucléaire et de Physique des Particules (France) ,  Bundesministerium für Bildung und Forschung ,  Deutscher Akademischer Austausch Dienst , and  Alexander von Humboldt Stiftung (Germany) ,  J.
The output mode profiles of the photonic lanterns were obtained with an IR camera, XEVA-1. 7-320 from Xenics. The intensity distributions were analysed with the Xeneth 2. 6 software from Xenics, obtaining the signal intensities per pixel. Mode purity values were obtained by normalizing each mode profile with respect to its maximum intensity value. The ratio between the minimum and maximum normalized intensities along the spatial distribution  19  was obtained from: MAX MIN  10   Transfer matrices were measured using a swept wavelength interferometer (SWI)  32  with spatial diversity. Light was launched into each input fibre of the MUX while measuring the output power for each output of the DEMUX photonic lantern. The transfer matrix plots were obtained using the normalized intensities at the inputs and outputs of the PLs.
the average nucleotide BLAST identity (ANI<80%), indicated that this isolate belonged to a new species. Results on the pairwise amino acid identity (AAI>70%) and on the percentage of conserved proteins (POCP>68%) with currently known Listeria species, as well as on biochemical characterization, confirmed that the strain constituted a new species within the Listeria genus. The name Listeria costaricensis sp. nov. is proposed for the novel species, and is represented by the type strain CLIP 2016/00682 T (=CIP 111400 T =DSM 105474 T ). The GenBank/EMBL/DDBJ accession numbers for the draft genome sequence of strain CLIP 2016/00682 T are FXUT01000001-FXUT01000044.
1. 5 [28]. 16S rRNA gene phylogenetic analysis showed highest similarity with L. floridensis (98. 71%; Fig. 1 ), i. e. at the lower cut-off value previously proposed for species delineation based on 16S sequence similarity (98. 7-99. 0%; [29, 30] ). Maximum likelihood phylogeny based on the amino acid sequences of Listeria core genes (Fig. 2 ) placed the novel taxon within the L. fleishmannii, L. floridensis and L. aquatica clade (Listeria sensu lato). Species identification was determined by whole-genome pairwise average nucleotide and amino acid BLAST identity comparisons (ANI and AAI, respectively) against Listeria species reference genomes deposited at NCBI database, using the enveomics package  [31]. The percentage of conserved proteins (POCP) was calculated as described by Qin et al.
API Listeria tests were recorded after incubation at 37 °C for 24h. API50CH tests were recorded after 2, 5, 10 and 15 days of incubation at 30 °C. Results are summarized in Table  1. CLIP 2016/00682 T fit the API Listeria numerical profile 2730 of Listeria ivanovii (identification at 99. 7%; bioMérieux API web database, version 04/2017) with divergent tests for Darylamidase and glucose-1-phosphate. Interestingly, according to its phenotypic profile (Table  1 ), isolate CLIP 2016/00682 T clustered together with Listeria grayi and the subgroup of Listeria sensu stricto (Fig. 4 ). Susceptibility to a wide range of antibacterial agents was determined with the disk diffusion method on Mueller-Hinton agar plates (Bio-Rad), using the interpretative criteria and recommendations from the French Microbiology Society and the European Committee on Antibiotic Susceptibility Testing  [42, 43].
This work was supported by Institut Pasteur, INSERM and the Vicerrectoría de Investigación y Extensión-Instituto Tecnológico de Costa Rica (Research Project VIE-1510068). Distance estimation was obtained by the model of Kimura 2-Parameter [45]. Selected members of Brochothrix genus were used as outgroup. Positions containing gaps and missing data were eliminated, resulting in a total of 1071 positions. Branch lengths represent the number of nucleotide substitutions per site and bootstrap percentages of 1,000 replicates are shown. GenBank accession numbers are provided in brackets. The newly Listeria costaricensis isolate is highlighted in bold.
Phylogenetic analysis of the 16S rRNA gene based on the maximum likelihood method. This work was supported by Institut Pasteur, INSERM and the Vicerrectoría de Investigación y Extensión-Instituto Tecnológico de Costa Rica (Research Project VIE-1510068). Distance estimation was obtained by the model of Kimura 2-Parameter [45]. Selected members of Brochothrix genus were used as outgroup. Positions containing gaps and missing data were eliminated, resulting in a total of 1071 positions. Branch lengths represent the number of nucleotide substitutions per site and bootstrap percentages of 1,000 replicates are shown. GenBank accession numbers are provided in brackets. The newly Listeria costaricensis isolate is highlighted in bold. Legends to figure FIGURE 1. FIGURE 2. Abbreviations: AAI average amino acid BLAST identity ANI average nucleotide BLAST identity BAM Bacteriological Analytical Manual BHI Brain Hearth Infusion BLAST Basic Local Alignment Search Tool BLEB Buffered Listeria Enrichment Broth MOX Modified Oxford Agar N50 minimum contig length covering 50% of the genome POCP percentage of conserved proteins WHOCCL World Health Organization Collaborating Centre for Listeria.
Maximum likelihood phylogenetic analysis based on the concatenated amino acid sequences of 243 core genes present in all Listeria species. [46]ance estimation was obtained by the model of WAG[46]. Branch lengths represent the number of amino acid substitutions per site and bootstrap percentages of 1,000 replicates are shown. GenBank accession numbers are provided in brackets. The newly Listeria costaricensis isolate is highlighted in bold. FIGURE 3.
Custom software using the OpenCV package for Python was then used to count the cells that did not join aggregation centers. The error of automatic cell counts was estimated by taking samples of images of cells in various densities, manually and automatically counting them, and fitting a linear Gaussian model with slope 1 and intercept 0 (S3B Fig). The standard deviation of the fitted model was taken as the automatic counting error. Total plated cell counts in each sample were estimated by counting the nonaggregated 5% dilution of the corresponding stock suspension and multiplying by the dilution factor of that particular sample. We do not assess differential loner viability, which might effectively increase the difference in loner allocation between strains. Loner map construction. After the position of each loner cell was determined from the composite images, a representation of the entire experimental area was created by plotting at the position of each loner cell a semitransparent black circle of 200 μm diameter (about 20 times the diameter of a cell) (Figs 1C, 4D and S2A Fig).
Analogous with  [12] , we fit this maximum survival time, as well as the functional shape of the survivorship curve using experimental data  [15] , to obtain S t ð Þ ¼ e À ðmtÞ B À e À ðmT sur Þ B 1 À e À ðmT sur Þ B ; ð4Þ where μ is the rate of decrease of the survival probability and B is a parameter that modulates the decay of S with time. At the end of the starvation phase, we obtain the populations of surviving loners and spores of each strain i as X L i ðt þ T st Þ ¼ X L i ðtÞSðT st Þ; ð5AÞ X SP i ðt þ T st Þ ¼ X SP i ðtÞe À dT st : ð5BÞ The lengths of the starvation periods T st are either constant (deterministic environments, in which the length of each starvation period coincides with its mean value) or drawn from an exponential distribution with a mean � T st that gives the expected length of the starvation periods.
For each of the pairs, we calculated the number of spores from the density of loners, SP w(b) = s A(P w(b) ρ 0ρ L,w(b) ). Notice that B does not depend on the choice of s (fraction of aggregated cells that become spores) and A (area of the simulated aggregation territory), but it does depend on the initial cell density because of the plateau in loner density. Data were deposited in the Dryad repository: https://doi. org/10. 5061/dryad. zs7h44j4k [60]. For initial plating densities above 7. 5 × 10 4 cells/cm 2 , aggregation occurs for all strains and substrates. To test whether above this critical cell density, the decision to aggregate is contextindependent, those samples with high initial plating densities (solid circles) were used to fit linear Gaussian models with zero intercept (dashed lines).
At the end of the cell cycle, cells exited mitosis and rebudded after forming a new septin ring, but kept the old septin collar and unconstricted CAR at the bud neck (Fig. 3b ). This prevented formation of a septum between the two dividing cells that in most cases shared a common cytoplasm, as shown by transmission electron microscopy (Fig. 3c ). Introducing the CDC14 TAB6-1 allele in GAL1-DMA2 ; f YEPD at 32 °C). At various time points after release (time 0) cells were collected for FACS analysis of DNA contents. FACS data were plotted after gating out the debris as illustrated in Supplementary Fig. 12  cells did not improve their ability to split septin rings or to constrict the CAR (Fig. 4e ). These data confirm that DMA2 overexpression interferes with, without blocking, some aspects of mitotic exit  31.
5c ), suggesting that Nud1 ubiquitination by Dma2 might silence MEN signaling. Upon DMA2 overexpression Nud1 ubiquitination was enhanced most markedly between late mitosis and G1 (Supplementary Fig. 10a ). Furthermore, it could be steered upon GAL1-DMA2 induction in cells arrested in mitosis by nocodazole treatment, but not in cells arrested in S phase by hydroxyurea (Supplementary Fig. 10b ). Altogether, these data suggest that Nud1 might be a direct ubiquitination target of Dma1/2 in late M and G1 phase. We then investigated the consequences of DMA2 overexpression on the SPB recruitment of MEN factors specifically in anaphase, when the presence of MEN factors at SPBs reaches its peak. To this end, we calculated the ratio between the fluorescence intensity of MEN proteins tagged with GFP and that of the constitutive SPB component Spc42 tagged with mCherry.
Indeed, while wild-type cells transiently showed Mob1-GFP at the bud neck in 43/70 cells during the time frame occurring between its appearance and disappearance at SPBs, only 5/60 GAL1-DMA2 cells did so (Fig. 5e ). As an additional readout of MEN activity at SPBs, we monitored the Cdc15-dependent Nud1 phosphorylation on Ser78  16  throughout the cell cycle of wild-type and GAL1-DMA2 cells. Remarkably, while Nud1 S78 phosphorylation peaked in late mitosis in wild-type cells, consistent with previous data  16  , it was largely suppressed upon DMA2 overexpression (Fig. 5f  and Supplementary Fig. 11b ). Furthermore, total Nud1 Fig. 5  Dma1 and Dma2 promote Nud1 ubiquitination and inhibit recruitment of MEN factors to SPBs. a-c Ni-NTA pulldown assays were carried out using cell extracts from strains with the indicated genotypes expressing Nud1-3PK at endogenous levels and overexpressing either untagged ubiquitin or Histagged ubiquitin from the CUP1 promoter.
The selected region of interests (ROIs) were then used to measure fluorescence intensities in the GFP channel with the ImageJ Analyze Particles tool. Min intensities were considered as cytoplasmic fluorescence, while max intensities corresponded the maximal pixel values within SPBs. Data were finally plotted according to the following equation: (max GFPmin GFP )/(max mCherrymin mCherry ). Buds and mother cells were distinguished on the basis of the alpha factor-induced shmoo-shaped morphology of mother cells. Still digital images were taken with an oil immersion 100× 1. 4 HCX Plan-Apochromat objective (Zeiss) with a Coolsnap HQ2 CDD camera (Photometrics) mounted on a Zeiss AxioimagerZ1 fluorescence microscope and controlled by the MetaMorph imaging system software. Z stacks containing 11 planes were acquired with a step size of 0.
3 µm and a binning of 1. Z stacks were max-projected and calibrated using ImageJ. For time-lapse video microscopy cells were mounted on 1% agarose pads in SD medium on Fluorodishes and filmed at controlled temperature with either a 100× 1. 45 NA oil immersion objective mounted on a Spinning disk CSU-X1 Andor Nikon Eclipse Ti microscope coupled to an iXon Ultra camera controlled by the Andor iQ3 software (Figs. 1b, 2a, 2c, 3b, 4a-e and Supplementary Figs. 1a-d  3D structural illumination microscopy (SIM). Cells were grown to log phase in YEPD at 25 °C, washed three times with BRB80 buffer (80 mM PIPES pH 6. 9, 1 mM MgCl2, 1 mM EGTA), mounted on Concavalin A-coated coverslips and fixed with 4% formaldehyde for 15 min, followed by two washes with BRB80-NH 4 Cl (BRB80 with 50 mM NH 4 Cl). 3D-SIM was performed with an OMX DeltaVision equipped with Evolve 512 EMCCD cameras.
After consulting the NYQUIST calculator to determine the ideal Voxel size, 25 Z-stacks of 0. 125 μm thickness were acquired with a 100× Plan SuperApochromat 1. 4 objective and an immersion oil with 1. 519 refraction index. Raw data were processed with SoftWoRx and the quality of SIM-reconstructed images was assessed by the SIMcheck plugin of ImageJ.
Logarithmically growing cells were fixed with 3% paraformaldehyde and 0. 5% glutaraldehyde in 0. 1 M sodium phosphate buffer pH 7. 4 (PB) for 2 h at room temperature, then washed three times with PB buffer and incubated in 1% of Na meta-periodate in 0. 1 M PB at room temperature for 30 min. After washing, cells were resuspended in 50 mM NH 4 Cl. Cells were subjected to a gradient of ethanol before being embedded in LR White resin and let to polymerize for 2 days at 60 °C. Samples were sectioned at 100 nm, collected on 100 mesh copper grid supported with carbon/formvar (EMS, USA), and stained with Uranyl Acetate in MeOH for 4 min, followed by Sato's lead citrate for 2 min. Ultrathin sections were examined with a JEM-2200FS electron microscope at 100 kV equipped with a TemCam-F416 CMOS camera and controlled by the software package EM-MENU.
Acknowledgments We are grateful to  A. Amon ,  Y. Barral ,  E. Bi ,  E. Conibear ,  F. Cross ,  R. Deshaies ,  A. Fatica ,  D. Finley ,  E. Johnson ,  M. Kanemaki ,  J. Kilmartin ,  H. Leonhardt ,  F. Luca ,  G. Pereira ,  J. Pringle ,  D. Stillman ,  R. Visintin , and  W. Zachariae  for providing reagents; to  N. V. Gounko  at the  IMB-IMCB Joint Electron Microscopy Suite  for assistance with TEM specimen preparation; to members of  Piatti's lab  for useful discussions; to  E. Schwob  and  A. Devault  for critical reading of the manuscript. This work has been supported by the  Fondation ARC for Cancer Research  (grant  PJA 20141201926  to S. P. ) and the  Merlion Exchange Program  to S. P and G. R. D. T. was supported by an  Erasmus Placement traineeship. We acknowledge the imaging facility MRI, member of the national infrastructure  France-BioImaging  supported by the  French National Research Agency  ( ANR-10-INBS-04 , "Investments for the future").
Heteroplasmy and MtDNA Content Measurements The heteroplasmy level of the KSS deletion was measured by qPCR with the Bio-Rad qPCR iCycler CFX96™ as described  (30)  and always included two calibration series corresponding to either only wild type or all (wild type and deleted) mtDNA. The level of heteroplasmy was then calculated as the % = (1-mtDNAwt/total) × 100. To measure the mtDNA copy number by qPCR, the mitochondrial gene MT-RNR1 (12S rRNA) and nuclear gene TST (thiosulfate sulfurtransferase) were quantified; each assay included two calibration series for absolute quantification. Data obtained on independently cultivated cells (n = 3) by 3-4 independent qPCR measurements were statistically processed using the two-tailed Student's t-test; values of P ≤ 0. 05 were considered to be statistically significant.
Microscopy Colocalisation analyses were performed by either confocal microscopy of fixed permeabilized samples with the Zeiss LSM 700 system with antibodies against Cas9 or TOM20 (presented in the result section) or super-resolution PALM/STORM with Cas9 antibodies and the co-expressed fusion TWINKLE-mEos2 (not presented here but providing similar results). The images were analyzed with ImageJ software.