dataesr/scientific-paragraphs-categorization huggingface dataset:
DIRL protein n°Bacteria species Coloration of Gram UniprotAccession number of DIRL Secondary metabolism clusters via AntiSMASH version 6. 0 Protein size (AA) Identity % with AtDIR6 (clustalW) (%) Similarity % with AtDIR6 (%) Peptide signal prediction size (AA) by The SignalP 5. 0 tool S-S bridge prediction position/probability Score by AlphaFold N-Glycosylation prediction in prokaryotes via Glycopp with score > 0,8 Bacterial family number via phylogenie results 1 Streptomyces sp. Root1304.
| CONCLUSION Morphological integration and the related concept of modularity describe the ways in which different modules or parts of an organism integrate to form a functioning system. Conditional activation of the Fgfr2 S252W mutation in either mesoderm or neural crest-derived tissues provides a unique dataset to explore whether targeted variation in signaling alters the structural relationship between components of the skull. Our findings emphasize the impact of localized, modular genotypic effects on phenotypic variation, and covariation patterns.
| Data and analyses We analyzed 28 cranial landmarks defined by their coordinate location in 3D space (Figure  1  and Table  2 ) measured on high-resolution micro computed-tomography (μCT) images of the mice in our sample. These landmarks were divided into regions derived from mesoderm (14 landmarks) and neural crest (14 landmarks). 22 All landmark data were collected by YH. Only landmarks that were consistently repeatable across our sample and measurement error free were included in the subsequent analyses. 7 The μCT images were acquired at the Center for Quantitative X-Ray Imaging at Pennsylvania State University, with a pixel size of 0. 0135 Â 0. 0135 mm and slice thickness of 0. 0156 mm. Image reconstruction was done on a pixel grid of 1024 Â 1024 in 16 bit and reduced to 8 bit. Isosurfaces to represent all cranial bones were reconstructed from the 8 bit μCT images using the software package Avizo 6.
Once computed, they were visualized on isosurfaces of the cranial CT-scans (details below). Next, we performed a principal component analyses (PCA) of all the cranial landmarks used in this study to examine the overall shape variation across the different mouse models. This allows for a better understanding of how the Fgfr2 +/S252W mutation affects global shape variation. PCA uses an eigenvalue decomposition of the covariance matrix resulting in mutually orthogonal dimensions assembled according to the amount of variance explained by each axis. Each axis represents a principal component that explains a portion of the variance in the dataset, with the first component accounting for the largest amount of variance in the sample. 28 ast, we conducted a two-block partial-least squares (2B-PLS) analysis to examine the pattern of integration between regions derived from mesoderm (Block 1) and neural crest (Block 2) across all samples.
Employing both these analyses allows us to compare potential differences in patterns of covariation between the two blocks as well as overall cranial variation across our sample. Shape changes were visualized along the respective 2B-PLS axes via wireframe diagrams in MorphoJ. 33 All statistical analyses were performed in MorphoJ and R programming software. The μCT data used in this study are available on FaceBase. Landmark data are available on NS's website.
ACKNOWLEDGEMENTS We thank  Dr Claudio Basilico  for use of the mouse models analyzed here. We also thank  Dr Susan Motch Perrine ,  Tiffany Kim , and  Hongseok Kim  for managing and imaging the micro-CT data. We are very grateful to  Dr Joan Richtsmeier  for her insightful comments on earlier drafts of the article. This study was supported in part by grants from the  NIH: NICHD   R01-HD038384 ;  NIDCR R01-DE018500 ,  R01-DE018500-S2 ,  R01-DE022988 ; and  NIAMS AR051358.
2  | LRF BS disruption and KLF1 BS creation in the HBG1/2 promoters of SCD HSPC-derived erythroblasts. a Experimental protocol used for base-editing experiments in non-mobilized SCD HSPCs. A BE-, a sgRNA-and a GFP-(optional for enzyme plasmids that do not contain a GFP cassette) expressing plasmid were cotransfected in SCD HSPCs and 18 h post-transfection GFP + cells were FACS-sorted based on GFP medium (med) and high (high) expression. b C-G to T-A or A-T to G-C base-editing efficiency, calculated by the EditR software in samples subjected to Sanger sequencing. The LRF 4C editing profile was obtained by pooling data from CBE-NRCH-, CBE-SpG-and CBE-SpRY-treated samples. Data are expressed as mean ± SEM (n = 12 (LRF 4C), n = 4 (LRF 8C), n = 4 (LRF 2T med), n = 4 (LRF 2T high), n = 3 (KLF1 med), n = 4 (KLF1 high) biologically independent experiments, 4 donors).
Flow cytometry measurements confirmed the presence of HbF reactivation in all the edited samples. For LRF 2T and KLF1, we also observed a lower frequency of HbS-expressing cells (Fig. 3l, m ) compared to controls. Similar results were observed for pooled BFU-E colonies (Supplementary Fig. 11d, e ). Fig. 3  | RNA-mediated base editing in SCD HPSCs. a Experimental protocol used for base-editing experiments using BE mRNAs in SCD HSPCs (2 plerixaformobilized donors and 1 non-mobilized donor). A BE mRNA and a chemically modified sgRNA were co-transfected in SCD HSPCs. Cells were differentiated into mature RBCs or underwent a CFC assay. b-e C-G to T-A (b, c) or A-T to G-C (d, e) base-editing efficiency, calculated by the EditR software in samples subjected to Sanger sequencing at early (Day 6) or late (Day 13) time points during the in vitro erythroid differentiation protocol.
CBE-SpRY mRNA was co-transfected with the LRF_bs_2 sgRNA (LRF 8C profile) and A-T to G-C (b) base-editing efficiency, calculated by the EditR software in βthalassemic erythroblasts subjected to Sanger sequencing. Data are expressed as mean ± SEM (n = 2 biologically independent experiments, peripheral bloodderived non-mobilized HSPCs from 2 donors harboring the CD39/IVS1-110 G > A and CD 8/9 + G/IVS1-110 G > A mutations, respectively). c Frequency of InDels, measured by TIDE analysis, for base-edited samples subjected to Sanger sequencing. Data are expressed as mean ± SEM (n = 2 biologically independent experiments). d CFC frequency for control (transfected with TE buffer) and base-edited samples. Data are expressed as mean ± SEM (n = 2 biologically independent experiments, 2 donors). No statistical differences were observed between control and edited samples (two-way ANOVA).
donors). b C-G to T-A or A-T to G-C base-editing efficiency, calculated by the EditR software in mobilized HD HSPC samples subjected to Sanger sequencing 12h-, 24h-, 48h-, and 6 days posttransfection. Data are expressed as mean ± SEM (n = 2-3 biologically independent experiments, 2-3 donors). c Frequency of InDels, measured by TIDE analysis, for control, base-and Cas9-edited samples. Data are expressed as mean ± SEM (n = 3 biologically independent experiments, 3 donors). ***P = 0. 0005 (ordinary one-way ANOVA with Dunnett correction for multiple comparisons). d Frequency of the 4. 9kb deletion, measured by ddPCR, for control, base-and Cas9-edited samples. Data are expressed as mean ± SEM (n = 3 biologically independent experiments, 3 donors). ****P ≤ 0. 0001 (ordinary one-way ANOVA with Dunnett correction for multiple comparisons).
HSPCs were purified by immunomagnetic selection with AutoMACS (Miltenyi Biotec) after immunostaining with the CD34 MicroBead Kit (Miltenyi Biotec). Fortyeight hours before transfection, CD34 + cells were thawed and cultured at a concentration of 5 × 10 5 cells/ml in the "HSPC medium" containing StemSpan (STEMCELL Technologies) supplemented with penicillin/ streptomycin (Gibco), 250 nM StemRegenin1 (STEMCELL Technologies), and the following recombinant human cytokines (PeproTech): human stem-cell factor (SCF) (300 ng/ml), Flt-3L (300 ng/ml), thrombopoietin (TPO) (100 ng/ml), and interleukin-3 (IL-3) (60 ng/ml). The AncBE4max_NAA plasmid was created by replacing the sequence encoding the PAM interaction domain of the SpCas9 nickase (SpCas9n) with the one of the SmaCas9  64. The sequence encoding the SmaCas9 domain was codon optimized by using the Genscript codon optimization software and obtained by gene synthesis (Genscript).
27). Data were acquired through QX200 analyzer (Bio-Rad) and results were analyzed with QuantaSoftTM Analysis Pro (Bio-Rad). A positive droplet count threshold was set at 30 to allow proper calculation of copy/µL concentration through the application of the Poisson distribution. The frequency of chromosome loss was calculated as the ratio p/q arm (CARS/PODL1) copy concentrations. Supplementary Table  3  lists the primers used for ddPCR.
Library preparation was performed using the original adapters and primers according to the previous work  68. End-repair reaction was performed using NEBNext Ultra End Repair/dA Tailing Module and adapter ligation using NEBNext® Ultra™ Ligation Module, as previously described  69. Amplification steps were then performed following the GUIDE-seq protocol previously described  68. Libraries were sequenced with a MiSeq sequencing system (Illumina) using the Illumina MiSeq Reagent kit V2-300 cycles (paired-end sequencing; 2 × 150-bp). Raw sequencing data (FASTQ files) were analyzed using the GUIDE-seq computational pipeline  70. Identified sites were considered bona fide off-targets if a maximum of seven mismatches against the on-target were present and if they were absent in the background control.
NGS-targeted sequencing of on-and off-target sites On-target sites (HBG1/2 promoters) were PCR amplified using the Phusion High-Fidelity polymerase (New England BioLabs) and the GC buffer (New England BioLabs). Amplicons were purified using Ampure XP beads (Beckman Coulter). Illumina-compatible barcoded DNA amplicon libraries were prepared using the TruSeq DNA PCR-Free kit (Illumina). PCR amplification was then performed using 1 ng of the double-stranded DNA ligation product and Kapa Taq polymerase reagents (KAPA HiFi HotStart ReadyMix PCR Kit, Kapa Biosystems). After a purification step using Ampure XP beads (Beckman Coulter), libraries were pooled and sequenced using Illumina NovaSeq 6000 system (paired-end sequencing; 2 × 100-bp). Targeted deep sequencing data were analyzed using CRISPResso2  71.
The NuQuant system (Nugen) was used to quantify the RNA-seq libraries. An equimolar pool of the final indexed RNA-Seq libraries was prepared and sequenced using the Illumina NovaSeq 6000 system (paired-end sequencing; 2 × 100-bp). A total of ~50 millions of passing filter pairedend reads were produced per library. Read quality was verified using FastQC (v. 0. 11. 9  72  ). Raw reads were trimmed for adapters and low-quality tails (quality < Q20) with BBDuk (v. 38. 92  73  ); moreover, the first 10 nucleotides were forcetrimmed for low quality. Reads shorter than 35 bp after trimming were removed. Reads were subsequently aligned to the human reference genome (hg38) using STAR (v. 2. 7. 9a  74  ). Raw gene counts were obtained in R-4. 1. 1 using the featureCounts function of the Rsubread R package (v.
2. 6. 4  75  ) and the GENCODE 38 basic gene annotation for hg38 reference genome. Gene counts were normalized to counts per million mapped reads (CPM) and to fragments per kilobase of exon per million mapped reads (FPKM) using the edgeR R package (v. 3. 34. 1  76  ); only genes with a CPM greater than 1 in at least 3 samples were retained for differential analysis. Differential gene expression analysis was performed using the glmQLFTest function of the edgeR R package, using donor as a blocking variable. RNA editing analysis was performed accordingly to GATK Best Practices for RNA-seq variant calling (GATK v4. 2. 2. 0). In brief, lanelevel FASTQ files were two-pass aligned to the hg38 human reference genome with STAR  74  (v2. 7. 2a) using parameters to specify the Read-Group and output the aligned BAM file sorted by coordinate.
The gating strategy used to assess enucleated cells is shown in Supplementary Fig. 19. Flow cytometry analysis of apoptotic cells was performed using PE-conjugated Annexin V (1/10 559763, BD Pharmingen). The gating strategy used to assess apoptotic cells is shown in Supplementary Fig. 21a, b. Flow cytometry analysis of reactive oxygen species (ROS) was performed using H 2 DCFDA (D399, Invitrogen). The gating strategy used to assess ROS is shown in Supplementary Fig. 21c, d. Flow cytometry analyses were performed using Fortessa X20 (BD Biosciences) or Gallios (Beckman Coulter) flow cytometers. Data were analyzed using the FlowJo (BD Biosciences) software.
HSPC xenotransplantation in NBSGW mice NOD. Cg-Kit W-41J Tyr + Prkdc scid Il2rg tm1Wjl /ThomJ (NBSGW) mice were housed in a pathogen-free facility. Control or edited mobilized healthy donor or non-mobilized SCD CD34 + cells (0. 4 to 1. 2 × 10 6 cells per mouse) were transplanted into nonirradiated NBSGW male and female mice of 5 to 6 weeks of age via retro-orbital sinus injection. NBSGW male and female mice transplanted with non-mobilized SCD CD34 + cells were conditioned with busulfan (Sigma, St Louis, MO, USA) injected intraperitoneally (10 mg/kg body weight/day) 24 h, 48 h and 72 h before transplantation. Neomycin and acid water were added in the water bottle. 16 to 20 weeks after transplantation, NBSGW primary recipients were sacrificed. Cells were harvested from bone marrow, thymus, spleen, and blood, stained with antibodies against murine and human surface markers [murine CD45 (1/50 mCD45-VioBlue), Miltenyi Biotec; human CD45 (1/50 hCD45-APCvio770), Miltenyi Biotec; human CD3 (1/50 CD3-APC), Miltenyi Biotec; human CD14 (1/50 CD14-PE-Cy7), BD Biosciences; human CD15 (1/50 CD15-PE), Miltenyi Biotec; human CD19 (1/100 CD19-BV510); human CD235a (1/50 CD235a-PE), BD Biosciences] and analyzed by flow cytometry using the MACSQuant analyzer (Miltenyi Biotec) and the FlowJo software (BD Biosciences).
The insertion or deletion of a C (±1 nt) in the homopoly-C stretch of the LRF 2T profile was separated from the overall frequency of InDels, as it was considered a sequencing error (Supplementary Note 2). Data are expressed as mean ± SEM (n=3 biologically independent experiments, 3 donors). **** p£0. 0001 (Ordinary One-way ANOVA with Dunnett correction for multiple comparisons). c. Frequency of the 4. 9-kb deletion in BFU-E and CFU-GM pooled colonies, measured by ddPCR, for edited and control (transfected with TE buffer, or with a base editor enzyme plasmid alone or with CBE-SpRY plasmid and a sgRNA targeting the unrelated AAVS1 locus) samples. Data are expressed as mean ± SEM (n=3 biologically independent experiments, 3 donors). ** p=0. 0030; **** p£0. 0001 (Ordinary One-way ANOVA with Dunnett correction for multiple comparisons).
Acknowledgements This work was supported by state funding from the  French National Research Agency (Agence Nationale de la Recherche)  as part of the  Investissements d'Avenir program  ( ANR-10-IAHU-01 ), the  Fondation Bettencourt Schueller , the  Paris Ile de France Region  (under the  "DIM Thérapie génique" initiative ), the  European Research Council  ( 865797 DITSB ), and the  AFM-Telethon  (grants  22206  and  22399 ). We thank  Christine Bole  and the  Imagine Institute's genomics facility  for the generation of the NGS data and  Ryo Kurita  and  Yukio Nakamura  for contributing to the HUDEP-2 cell line.
Data availability The RNA-seq data generated in this study and supporting the results of this article have been deposited and are available in the Gene Expression Omnibus repository under the accession number GSE191135. The WES data generated in this study and supporting the results of this article have been deposited and are available in the BioProject repository under the accession number PRJNA850889. The GUIDE-seq data generated in this study and supporting the results of this article have been deposited and are available in the BioProject repository under the accession number PRJNA752948. Source data are provided with this paper.
Instrument development and validation included anticipated end users of the questionnaire (ie, smokers and switchers without COPD) to ensure that the resulting questionnaire would be valid for use with these populations. Former smokers and participants who reported a diagnosis of COPD or another respiratory symptom-related disease (eg, asthma) were also included for purposes of the psychometric evaluation. Data from the psychometric evaluation also provided an opportunity for exploratory analyses examining how respiratory symptoms reported by switchers compared with symptoms reported by smokers and former smokers.
Analytic Plan A GRM  [17]  was fit in Mplus using the weighted least-squares estimator and θ parameterization. The GRM's assumption of the ordinality of response categories was empirically evaluated by fitting a generalized partial credit model  [18, 19]. To evaluate the GRM's assumption of unidimensionality, a Monte Carlo simulation (parallel analysis) with 10,000 randomly generated data sets was conducted using a principal components analysis extraction method. Test information and reliability were evaluated within the context of the GRM. The stability of the RSES was evaluated by calculating an ICC between RSES scores from the time 1 and time 2 surveys. Convergent validity was evaluated by calculating a Spearman correlation between RSES scores and self-reported global health status and by evaluating RSES scores by diagnostic status via independent-samples t tests.
0). The database registered age, gender, presence or absence of comorbidities and site of residence (Greater Buenos Aires or not). Information on SARS-CoV-2 infections was obtained using RT-PCR or antigen test until 1 April 2022. During the study period only symptomatic cases were tested, according to the standards established by the Province of Buenos Aires. Information about hospitalisations and death was recorded until 28 April 2022. The date of confirmed-laboratory SARS-CoV-2 infections was identified by symptom-onset date or, if not available, the date of the sample collected for the COVID-19 test. Number of positive tests in the past, total number of previous tests, dates of hospitalisations and death were registered.
Pylon software (Basler, Germany) was used to control the camera and to configure all of its settings. The filter was used to narrow down the range of wavelengths passing through the liquid in the reactor to approach a monochromatic beam (∼500 nm, for which the absorbance was high enough for measurement accuracy) and to link the intensity of light to the concentration of Rose Bengal lactone, according to the Beer-Lambert law (Equation (1)), where A is the instantaneous absorbance, I is the instantaneous light intensity, I o is the light intensity through the blank (water), C is the concentration of Rose Bengal lactone, l is the optical path length, and ε λ is the molar attenuation coefficient. The latter coefficient was obtained from the calibration. An image was recorded every 10 s (acquisition frequency of 0.
1 Hz) and the total acquisition time was 1 day or more, depending on the time required to reach equilibrium. The size of the images was 1000 × 650 pixels² (1 pixel = 150 µm). Pylon software (Basler, Germany) was used to control the camera and to configure all of its settings. A = -log I I 0 = ε λ. l. C (1) The filter was used to narrow down the range of wavelengths passing through the liquid in the reactor to approach a monochromatic beam (~500 nm, for which the absorbance was high enough for measurement accuracy) and to link the intensity of light to the concentration of Rose Bengal lactone, according to the Beer-Lambert law (Equation (1)), where  is the instantaneous absorbance,  is the instantaneous light intensity,  is the light intensity through the blank (water),  is the concentration of Rose Bengal lactone,  is the optical path length, and  is the molar attenuation coefficient.
4 wt%. The range and levels of those three independent variables are presented in Table  1. The response variables are referred to as Recovery Yield of Lipids (wt%) and Recovery Yield of Polar molecules (wt%). The design was recorded a total of 45 experiments, subdivided in 24 cubic points, 18 axial points, and 3 center points. Those experiments were randomized in order to minimize the effects of a possible unexpected variability. The data from CCRD were analyzed by a multiple regression method to fit a second-order polynomial regression model containing the coefficients for linear, quadratic, and two factor interaction effects. The model equation of response (Y) with three independent variables (i, j, k) is described by the following equation (Equation (  1 )): Equation  (1). Second order polynomial equation of response (Y) with three independent variables (i, j, k) Y = β 0 + 3 ∑ i=1 β i + 3 ∑ i=1 β ii x 2 i + ∑ 2 i=1 3 ∑ j=i+1 β ij x i x j ( 1 ) where Y is the response variable, β 0 is the constant coefficient, β i is the linear coefficient, β ii is the quadratic coefficient, and β ij is the two factors interaction coefficient.
The accuracy of the model was determined with the analysis of variance (ANOVA), including the evaluation of the lack of fit, coefficient of determination (R2), and the Fisher test value (F-value). All statistical calculations were made for a confidence level superior at 95% (i. e. , with p < 0. 05). RSM and ANOVA results were generated by the Minitab 17 software (Pennsylvania, PA, USA). Student's tests for the kinetics of extractions were carried out with the software R (4. 0. 3 version).
Optimization of Recovery Yield of Lipids Using Desirability Function The Design of Experiments based on Central Composite Rotatable Design were used to generate second order polynomial equation, which can be exploited to define operative parameters in order to target or minimize or maximize response variable. The optimized conditions for Recovery Yield of Lipids by SC-CO 2 extraction of spent coffee grounds were assessed with the software Minitab V17 (Table  4 ). The optimal experiment to maximize RYL was performed in the following experimental conditions: Pressure = 284. 1 bars, Temperature = 66. 8 • C, and Moisture content = 6. 4 wt%. To ensure the validation of the model, the difference between measured and predicted RYL must be lower than 5%  [37]. Next, the RYL for measured and predicted data was reported as 94.
Optimization of Recovery Yield of Polar Molecules Using Desirability Function The optimized conditions for Recovery Yield of Polar molecules by SC-CO 2 extraction of spent coffee grounds were assessed with the software Minitab V17 (Table  4 ). The optimal experiment to maximize RYP was performed in the following experimental conditions: 270 bars, 40 • C and 60 wt% moisture content. The RYP for measured and predicted data are reported as 5. 50 and 6. 73 wt%, resulting in p-value: 0. 2247 (p > 0. 05, Table  4 ). The results from optimized conditions using desirability function are not acceptable, as the model does not fit with the reality with level confidence of 95%. Several hypotheses based on the effects of process parameters are pointed out, such as the important excess of water of 70 wt% of initial water mass due to low temperature (40.
Optimization of Recovery Yield of Polar Molecules Using Desirability Function The optimized conditions for Recovery Yield of Polar molecules by SC-CO2 extra of spent coffee grounds were assessed with the software Minitab V17 (Table  4 ). The op experiment to maximize RYP was performed in the following experimental condition bars, 40 °C and 60 wt% moisture content. The RYP for measured and predicted da reported as 5. 50 and 6. 73 wt%, resulting in p-value: 0. 2247 (p > 0. 05, Table  4 ). The r.