dataesr/scientific-paragraphs-categorization huggingface dataset:
La demivie de ce cocktail dans la circulation sanguine étant de 11 heures, les auteurs de cette étude proposent que les sénothérapies du futur ne nécessiteront pas d'être prescrites en continu au patient âgé souffrant de maladie dégénérative, mais par intermittence. À la différence des cellules tumorales, les cellules sénescentes ne se divisent pas. Elles s'accumulent lentement dans les tissus atteints. Un traitement par intermittence est donc envisageable. Citons encore d'autres essais cliniques en cours : le TAME (targeting aging with metformin), menée par la fondation américaine de recherche sur le vieillissement, avec la mise en place d'un essai clinique multicentrique en double aveugle, pour estimer les effets de la Metformine ® sur la longévité chez l'homme ; l'essai de la fisetine (NCT03325322) sur la fragilité des femmes âgées, qui semble prometteur ; et, enfin, celui utilisant le UBX0101 ® (NCT04349956), de la biotech Unity, en phase II, pour le traitement de gonarthrose modérée à sévère en application intra-articulaire.
Les prothèses corticales Les premiers travaux de Brindley et Lewin dans les années 1960 ont permis d'apporter la preuve qu'une stimulation électrique à la surface du cortex visuel peut induire une perception visuelle  [7]. Les études suivantes ont confirmé ces résultats, montrant même la possibilité de reconnaître des formes avec un implant ne comprenant que 100 électrodes  [8, 24]. Malheureusement, la perte progressive de cette vision retrouvée chez les patients n'a pas permis de poursuivre ces études. Néanmoins, de nouveaux essais ont été récemment réalisés, en utilisant, soit des électrodes placées en surface du cortex (NCT03344848), soit des électrodes.
Des essais cliniques ont été récemment initiés par la société française Gensight Biologics, sur des patients aveugles atteints de rétinopathie pigmentaire (NCT03326336). Le patient traité portera des lunettes qui transformeront en images monochromes, les informations visuelles reçues de l'environnement, à un très fort niveau de luminance au pic de photosensibilité de la protéine. Pour réduire les niveaux de luminances requis par cette approche optogénétique, certains groupes ont tiré parti des différences de sensibilité d'opsines humaines en ciblant des neurones non photosensibles, afin de leur conférer une sensibilité à la pénétrantes (NCT02983370). L'implant de surface est produit par la société 2nd Sight qui, à partir de l'implant rétinien Argus II, a développé une version corticale, dénommée Orion.
Bien entendu, l'analyse du génome nécessite un échantillon d'ADN des cas et d'un certain nombre de témoins non atteints. C'est un autre objectif de l'ONAB de collecter et centraliser des échantillons de tissu (sang, biopsie d'oreille, ou tout autre tissu nucléé) pour les rendre disponibles pour les analyses génétiques et génomiques. Quant aux animaux utilisés comme « contrôles », il s'agit d'animaux représentatifs de la variabilité de la race et on utilise généralement ceux pour lesquels un génotype est disponible. Bien que certains soient susceptibles de porter la mutation délétère recherchée à l'état hétérozygote, leurs génotypes seront pour la plupart différents de ceux des animaux atteints. La puissance de l'analyse repose sur le nombre de ces « contrôles », et la collection de génotypes conservés dans les bases de données de l'INRA, en particulier dans l'espèce bovine, est à cet égard particulièrement précieuse.
Dans ce cas, l'anomalie se traduit par une baisse de fertilité et passe généralement totalement inaperçue. Cette catégorie d'anomalie est sans doute assez fréquente car de nombreux gènes, critiques pour le développement, peuvent en être responsables. Aucun échantillon biologique n'est récupérable et l'approche décrite dans cet article ne peut pas être mise en oeuvre. Une approche spécifique, reposant sur la fouille de grandes bases de données de génotypage, est décrite dans l'article  de Fritz et al (2016 ce numéro).
Human tumor data analysis The presence of BCOR mutations and indels was integrated from our previous medulloblastoma studies  (Kool et al. 2014; Northcott et al. 2017; Waszak et al. 2020 ). These mutations were mapped onto NP_001116857. 1. Where available, the IGF2 gene expression was checked using RNA-seq data and Affymetrix data. Additionally, the BCOR somatic indel in sample MB12 was confirmed via RNA-seq alignment data. However, we only detected 2% of reads with the missense mutation in MB234. FPKM gene expression values from selected tumor samples from INFORM were compared across entities (BCOR-WT group 3/4 medulloblastoma, BCOR-WT SHH medulloblastoma, CNS-HGNET-BCOR, and CCSK).
Mouse model gene expression analysis RNA extraction Tissue was homogenized using the Tissue Master 125 homogenizer (OMNI International) and/or QIAshredder (Qiagen). RNA was extracted with RNeasy mini kit (Qiagen) following the supplier's instructions. For measurement of RNA quantity, ND1000 Spectrophotometer (NanoDrop Technologies) and/or Agilent 2100 Bioanalyzer was used. RNA-seq libraries were processed and sequenced on a HiSeq V4 (SR 50) by the DKFZ Genomics Core Facility. RNA-seq analysis Transcriptome profiling (reads alignment to mm10 reference, quality control and gene expression counts computation) was performed using RNA sequencing data from Ptch1 +/-(N = 3) and Ptch1 +/-;Bcor ΔE9-10 (N = 3) medulloblastoma tumor models as described previously  (Pajtler et al. 2019 ). Differentially expressed genes were detected using DESeq2 R package with applied limits: minimum P-adj 0.
05, minimum log 2 FC 0. 5. Additional extended transcriptome profiling from Ptch1 +/-(N = 5) and Ptch1 +/-; Bcor ΔE9-10 (N = 4) medulloblastoma SHH tumor models was performed with Affymetrix microarray 430v2. The differentially expressed genes were detected using Limma package  (Ritchie et al. 2015)  and sorted using p-adj limit for the top 1000 selection. DAVID gene ontology analysis was applied to the RNA-seq and Affymetrix data with a focus on biological processes and KEGG pathways. The mouse tumor models were compared with the ICGC medulloblastoma RNA-seq cohort (n = 170). Ortholog selection was performed using the biomart R package via corresponding Ensembl database annotation. After batch effect adjustment with Combat  (Leek et al. 2012) , unsupervised clustering was performed with ward.
6. 2. Next, the general quality control and read alignments statistics collection was performed using Qualimap v2. 2 toolkit mode BAM QC  (Okonechnikov et al. 2016). The coefficients from Drosophila spike-ins were computed based on the alignment statistics and applied to adjust to the reads distribution per sample. For peak calling Macs 1. 4 tool  (Zhang et al. 2008 ) was applied with corresponding background included as input and using P-value limit 1 × 10 -9. Differential peaks were detected using DiffBind R package  (Ross-Innes et al. 2012)  with minimum P-adj of 0. 05.
Acknowledgments We thank  Annarita Patrizi ,  Ana Banito ,  Mija Blattner-Johnson , and  David T. W. Jones  for their scientific input and discussions. Support by the  GPCF Antibody Unit (Dr. Ilse Hofmann) ,  DKFZ Light Microscopy Facility , and  DKFZ Genomics Facility  is gratefully acknowledged. This work was supported by a  Deutsche Forschungsgemeinschaft  grant ( KA4472/1-1 ) and a grant from the  Japan Agency for Medical Research and Development (AMED ;  JP20ck0106534h0001 ) to D. K. , a  Heinrich F. C. Behr Stipendium  to N. V. B. , and  National Institutes of Health  grants  5R01CA071540  and  R01HD084459  to V. J. B. Author contributions: N. V. B. , P. A. N. , and D. K. conceived the project. L. M. K. , N. V. B. , J. C. , P. B. G. S. , M. V. , S. v. R. , L. S. , B. S. , R. S. , and D.
Méthodes Une recherche bibliographique à partir de la base de données pubmed, a été effectué de façon indépendante par deux des auteurs (AF et MF) avec les mots clefs suivants : « MICI », « maladie de Crohn », « rectocolite hémorragique », « fertilité », « infertilité », « grossesse », « chirurgie », « colectomie », « anastomose iléoanale », « prééclampsie », « retard de croissance intra-utérin », « petit poids pour l'âge gestationnel », « mort foetale in utero », « malformation foetale », « poussée », « thalidomide », « biothérapie », « anti-TNF », « infliximab », « adalimumab », certolizumab », « golimumab », « 5-ASA », « tofacitnib », « vedolizumab », « ustekinumab », « voie d'accouchement », « continence ».
1 µl of 5 µM HEX and FAM probes or 1. 1 µl of 5 µM FAM probe for singleplex assay (Table  2 ), and 5. 5 µl or 6. 6 µl of nuclease free water, for the duplex or singleplex assay, respectively. Only 20 µl of the mixture was used to generate droplets using the QX200 Droplet generator. Subsequently, the droplet suspension was transferred into 96wells plate and PCR amplification was performed on a T100 Touch thermal cycler (Bio-Rad) with the following program: 10 min at 95 • C followed by 40 cycles of 30 s at 94 • C and 60 s at 59 • C, ending with 10 min at 98 • C, at a ramp rate of 2 • C/s. After PCR, each reaction was analyzed by the droplet reader (Bio-Rad) and acquired data were treated with QuantaSoft software V1. 7 (Bio-Rad). Thresholds were set manually considering the double negative droplets cluster from the negative control and the FAM-and/or HEX-specific positive droplets cluster from the control strains.
, 1995). The citD gene encoding the citrate lyase acyl carrier protein was targeted to identify and quantify this biovar. This gene sequence is highly conserved among the biovar and regions with no polymorphism were chosen to design primers, R-citD and F-citD, and a FAMprobe, FAM-P cit , from 11 sequences retrieved from the GenBank database (Figure  1B  and Supplementary Table  S2 ).
Limits of Detection (LoD) and Quantification (LoQ) Limits of detection and quantification were determined by testing five DNA dilutions of a mixture containing the two species lactis (including the biovar diacetylactis) and cremoris. Each measurement was carried out in triplicate. For data analysis, the merge well function of QuantaSoft software was used to allow a more reliable, precise and accurate quantification based on "mega-wells" data, thus taking both intra-and inter-well variability into account. As no significant differences were found between singleplex and duplex assays, P lac and P cre probes were used in duplex with P tot probe. LoD corresponds to the lowest value of copies per microliter detected. It was defined as at least five positive droplets detected per well since the maximum number of positive droplets detected in negative controls was 4 (Table  4 ).
But the plasmid encoding CitP is sometimes missing while the chromosomal cluster citDEFXG is highly conserved among the strains that produce diacetyl  (Passerini et al. , 2013; Torres Manno et al. , 2018). For that reason, the citD chromosomal gene encoding the citrate lyase was chosen as target to highlight the diacetylactis biovar. As few sequences are currently available in the databases, it will be necessary to update primers and probe with data accumulated in the coming years. The specific objective of this study was to demonstrate that the gadB and citD targets described above can be used in digital droplet PCR assays to determine the proportions of the two species and the biovar in a starter or a dairy product. In contrast to qPCR, no standard curve with an external DNA calibrator is required and ddPCR shows little susceptibility to the inhibitors usually present in food matrices like dairy products  (Morisset et al.
According to the composition of these four freezing conditions, the common parameter that seems to be responsible for this difference is the size of the frozen fragments. Nevertheless, very few samples were included in these four freezing conditions, which may bias the statistical test. Viability rates were more likely to be directly related to the qualities of the rbF freeze-thaw procedure rather than to the freezing conditions of the original tissues. 1  and S1 ). Scale bar = 50 μm. (B) Box plot comparison of the times of rbF derivation during the two passages before freezing between cells issued from fresh tissue, frozen skin, and frozen cartilage. The mean values are indicated by black squares. The black error bars correspond to samples considered to be outliers according to descriptive statistics (GraphPad Prism8 software).
Quality of Frozen Tissue-Derived rbFs After two derivation passages, all rbF lines were frozen according to the standard protocol for fibroblasts (i. e. , a half-volume of FBS + 20% DMSO per half-volume of cell suspension in fibroblast medium) (Table  S2 ). Subsequently, most rbF lines were thawed, and the viability rates, growth rates,   1  and Table S1 ). Scale bar = 50 µm. (B) Box plot comparison of the times of rbF derivation during the two passages before freezing between cells issued from fresh tissue, frozen skin, and frozen cartilage. The mean values are indicated by black squares. The black error bars correspond to samples considered to be outliers according to descriptive statistics (GraphPad Prism8 software). The derivation speeds of frozen and fresh tissue-derived rbFs differed significantly (*** unpaired T test, p < 0.
All data from this study indicate the efficacy of a medium composed of CRYO3 and 4% DMSO for tissue and rbPSC cryopreservation, which was shown to yield biological results similar to than those associated with the traditional freezing medium composed of FBS and 10% DMSO  [18, 30, 49]. With respect to biodiversity preservation, as described above, we selected ear biopsies for their ease of sampling under most breeding conditions and their ability to be frozen with a minimum of processing. We determined the best slow-freezing cryopreservation parameters by comparing five conditions: (i) immediate freezing versus initial storage of biopsies, (ii) skin versus internal cartilage dissected from the biopsies, (iii) small versus large pieces of frozen tissue, (iv) synthetic versus biological freezing medium, and (v) low versus high percentage of DMSO.
Flow Cytometry Assessment of Viability Cell viability was assessed after thawing (P0) or after dissociation (P6 or fresh samples) by adding 5 µL of propidium iodide (1 mg/mL, Sigma Aldrich) to 200 µL of cell suspension 1 min before the analysis. The analyses were performed on a FACSCanto II cytometer (Becton Dickinson, Le Pont de Claix, France) and acquired using the FACSDiva software V9. 0 (Becton Dickinson, San Jose, CA, USA). The fluorescence was evaluated using a 488-nm excitation laser and a 650 ± 13-nm bandpass emission filter.
Infection Rate The ability of rbFs to produce iPSCs was evaluated at P4. This parameter was determined as the rate of cellular infection resulting from transduction with the GFP-expressing Sendai viral vector. Triplicates of 5 × 10 4 cells were plated on well of a 12-well plate in the presence of 250 µL of rbF medium and 5 µL of CytoTune-EmGFP Sendai Fluorescence Reporter (Life Technologies, Villebon-sur-Yvette, France) at a concentration of 1 × 10 6 pi/mL (multiplicity of infection: 5). Each plate was centrifuged (570× g for 1 h) and incubated overnight at 37 • C and 5% CO 2. One milliliter of rbF medium was added to each well, and the cells were cultured for 3 days before dissociation and analysis on a FACSCanto II cytometer equipped with FACSDiva software. The fluorescence was evaluated using a 488-nm excitation laser and a 530 ± 30-nm bandpass emission filter.
The qPCR efficiencies for both the target and reference genes were determined from the relative quantitative values for normalized target (calibrator) gene expression and calculated using StepOnePlus Software V2. 1 (Applied Biosystems, Foster City, CA, USA). In all cases, the expression of the target genes was normalized to that of the rabbit TATA-box binding protein (TBP) gene or mouse β-actin (Actb). The expression of target genes in the frozen samples was also normalized to that in fresh samples (reference samples), and the data were quantified using the ∆∆CT method. All qPCR assays were performed in triplicate and repeated in at least three independent experiments. The results are presented as the logarithmic fold change values. All primers used for qPCR are shown in Table  S1.
Differential Scanning Clorimetry The following media were analyzed by DSC: mESC, rbESC, and rbiPSC freezing media containing 0%, 5%, or 10% DMSO, and CryoStor ® CS10. The phase transitions of the freezing media were characterized using a power compensation DSC (Diamond DSC, Perkin-Elmer, Waltham, MA, USA) equipped with a liquid nitrogen cooling accessory (Cryofill) and Pyris software V11. 11. 1 (Perkin-Elmer, Waltham, MA, USA). The technical specifications of this DSC provided accuracy ranges of ± 0. 11 • C for temperature and ± 1. 10% for energy. The DSC was calibrated for temperature and energy at +2. 5 • C/min using two standards: the melting of pure bi-osmosed water ice (0 • C; 333. 40 J/g) and the crystallographic transition of solid-state cyclohexane (-87. 06 • C; 79. 58 J/g), which yielded a high data range of 720 mW.
Statistical Analysis The statistical analyses of tissue freezing conditions and tissue-derived rbF qualities were performed using GraphPad Prism software V8. 0 (GraphPad Inc. , La Jolla, CA, USA). A one-way ANOVA and Tukey's adjustment were used for multiple comparisons of qualitative variables (e. g. , tissues, treatments, piece sizes, media, and DMSO concentrations). The unpaired T test was used for simple comparisons between fresh and frozen tissues at a fixed error level of 5%. The statistical analyses of PSC freezing conditions were performed using R software V2. 14. 1 (R Development Core Team, Vienna, Austria). The results represent three replicates per condition and are presented as mean values ± standard deviations. The cell viability, growth recovery, and gene expression were analyzed using a linear model in which the medium, DMSO concentration and freezing method were included as fixed effects.
Cryo-EM Image acquisition Data collections of the three described molecular complexes were performed on three different instruments. The main complex (T. cruzi 43S PIC) was imaged (at the IGBMC EM facility, Illkirch, France) on a spherical aberration corrected Titan Krios S-FEG instrument (FEI Company) at 300 kV using the EPU software (Thermo Fisher Company) for automated data acquisition. Data were collected at a nominal under focus of À0. 6 to À4. 5 mm at a magnification of 127,272 X yielding a pixel size of 1. 1 A ˚. Micrographs were recorded as movie stack on a Gatan Summit K2 direct electron detector, each movie stack were fractionated into 20 frames for a total exposure of an electron dose of 30 e/A ˚2. The T. cruzi 43S PIC supplemented with ATP was imaged with the exact setup described above, but in the Netherlands's NeCEN EM facility, Leiden, which is not Cs corrected.
The L. tarentolae 43S PIC dataset was collected (at the IECB EM facility, Pessac, France) on a Talos Artica instrument (FEI Company) at 200 kV using the EPU software (FEI Company) for automated data acquisition. Data were collected at a nominal underfocus of À0. 5 to À2. 7 mm at a magnification of 120,000 X yielding a pixel size of 1. 21 A ˚. Micrographs were recorded as movie stack on a Falcon III direct electron detector (FEI Compagny), each movie stack were fractionated into 20 frames for a total exposure of 1 s corresponding to an electron dose of 40 e/A ˚2.
Image processing For all three datasets, drift and gain correction and dose weighting were performed using MotionCor2  (Zheng et al. , 2017). A dose weighted average image of the whole stack was used to determine the contrast transfer function with the software Gctf  (Zhang, 2016). The following process has been achieved using RELION 3. 0  (Zivanov et al. , 2018). Particles were picked using a Laplacian of Gaussian function (min diameter 300 A ˚, max diameter 320 A ˚). For the main dataset (T. cruzi 43S PIC), particles were then extracted with a box size of 360 pixels and binned three-fold for 2D classification into 200 classes, yielding 202,920 particles presenting 40S-like shape. These particles were then subjected to 3D classification into 10 classes. Two subclasses depicting high-resolution and 48S features have been selected for a second round of classification into two classes.
One class ended as a possible 48S complex (12910 particles, don't present densities for k-DDX60) and a second as a 43S+DDX60 complex (33775 particles). Refinement of the 43S-DDX60 complex yielded an average resolution of 3. 3A ˚. The 48S class was not analyzed any further. Determination of the local resolution of the final density map was performed using ResMap  (Kucukelbir et al. , 2014). The dataset of the T. cruzi 43S PIC supplemented with ATP was processed identically. However, the sample was more diluted compared to the above-described main complex, thus yielding less particles count after the first 2D classification (98,840 particles presenting 40-like shape). Following the similar classification/processing fashion and after 3D classification, 19700 particles were used to reconstruction a $4.
3A ˚43S PIC bound to ATP. Finally, the L. tarentolae 43S PIC dataset was processed also identically to the protocol described above. As the aim of this reconstruction is simply to validate the conservation of the architecture in leishmania, only a small dataset was collected, which after processing only yielded $10,000 particles that were then used to reconstruct the 43S PIC at 8. 1A ˚.
ACKNOWLEDGMENTS We thank  Christoph Diebolder  and  Ludovic Renault  ( NeCEN, Leiden, Holland ), as well as  Julio Ortiz Espinoza ,  Corinne Crucifix , and  Christine Ruhlmann  ( IGBMC, Strasbourg, France ) for assistance with data acquisition. We would like also to thank  Eder Mancera-Martinez  for her help in the sample's purification and the  High-Performance Computing Center of the University of Strasbourg  for IT support. The mass spectrometry instrumentation was funded by the  University of Strasbourg ,  IdEx ''Equipement mi-lourd '' 2015. This work was supported by  ERC - 2017-STG #759120 ''TransTryp''  (to Y. H. );  Labex   ANR-10-LABX-0036_NETRNA  (to Y. H. );  ANR-14-ACHN-0024 -CryoEM80S  (to Y. H. ); the  Grant of Excellence in Basic Research (EXPRO 2019 ) provided by the  Czech Science Foundation  ( 19-25821X  to L.
QUANTIFICATION AND STATISTICAL ANALYSIS For the mass-spectrometry analysis, proteins were validated on Mascot pretty rank equal to 1, and 1% FDR on both peptide spectrum matches (PSM score) and protein sets (Protein Set score). The total number of MS/MS fragmentation spectra was used to relatively quantify each protein (Spectral Count relative quantification). Proline was further used to align the Spectral Count values across all samples. The whole MS dataset was then normalized. Volcano plot presented in Figure  1  was obtained after manual validation of the results. For that end, we only consider proteins that present at least 5 spectra. Further validation was performed by analyzing the pre-initiation complex after further purification step using size exclusion chromatography. Quantification of binding experiments (GST-pulldown assay) was done using the Quantity One software (Bio-Rad).