dataesr/scientific-paragraphs-categorization huggingface dataset:
3,3=-Diaminobenzidine (DAB) was dissolved in PBS at a concentration of 0. 34 mg/ml, and 0. 3% H 2O2 was added just before use. After 20 min incubation, sections were washed with ultrapure water and counterstained with hematoxylin. After 5 min rinsing under running tap water, sections were dehydrated in ethanol and covered with mounting medium. Airways were digitally photographed and analyzed using Image J software (National Institutes of Health, Bethesda, MD). The positively stained area (m 2 ) was normalized to the square of the basement membrane length (m 2 ). For evaluation of emphysema, paraffin sections were stained with hematoxylin and eosin. Mean linear intercept (MLI) was determined as a measure of alveolar airspace size as described previously  (22) , using 20 -25 photomicroscopic images (magnification, ϫ200) per slice.
Further simulations were then carried out to determine the changes required in the six parameters above to generate similar changes to those observed in the dose-response curves of human COPD-and LPS-challenged guinea pig PCLS. The parameter changes identified in this way enable inference of the structural changes that could have occurred to generate the observations. The MATLAB scripts for running model simulations as described here can be obtained by contacting the corresponding author of Hiorns et al. (12). Data analysis. Data are expressed as means Ϯ SE. An n ϭ 1 represents the average of the measurements of each airway classification per animal. A power analysis (1-2 ϭ 40, ϭ 30, ␣ ϭ 0. 5, power ϭ 0. 8) determined that nine animals were to be included per group for the constriction experiments.
Image acquisition Confocal images of fixed embryos were acquired on an upright Leica SP8 confocal microscope using the resonant fast mode and either an oil x63 (aperture 1. 4) or x20 (aperture 1. 4) objective. Confocal stacks were analyzed using ImageJ software. Figures were prepared using Adobe Photoshop software. Quantification of the number and position of Tg(dusp6:d2EGFP) positive parapineal cells The position and number of parapineal cells positive for the Tg(dusp6:d2GFP) transgene were analyzed using ROI Manager tool on ImageJ software as previously described  (Roussigneet al. , 2018). The mean intensity of the d2EGFP staining was quantified in an area corresponding to the cell nucleus and the same intensity threshold was used in the different experimental contexts to determine if a cell was Tg(dusp6:d2EGFP) positive or not.
The total number of parapineal cells was estimated at 32 hpf by counting nuclei in the parapineal rosettes using Topro-3 nuclear staining. Quantification of the number and position of gfi1ab, sox1a, tbx2b positive parapineal cells The position and number of gfi1ab, sox1a or tbx2b positive parapineal cells were analyzed using the Multipoint tool on ImageJ software and determined as the centre of the cell nucleus detected with the Topro-3 nuclear staining as previously described  (Roussigneet al. , 2018). The position of each parapineal cell was measured relative to the brain midline (reference origin = 0) as determined by a line passing along the lumen of the epiphysis. For each embryo, we calculated the number of labeled parapineal cells and their mean position. To avoid any bias, data in.
Statistical analysis Statistical comparisons of datasets were performed using R Studio or GraphPad Prism software. For each dataset, we tested the assumption of normality with Shapiro-Wilks tests and variance homogeneity with F tests. As datasets on the number of parapineal cells were usually normal and often of unequal variances, they were compared using unpaired Welch t-tests; means (± SEM) are indicated as horizontal bars on dot plots. Data on parapineal mean position usually did not distribute normally (because of few embryos with the parapineal on the right) and were compared using the Wilcoxon rank sum non-parametric tests; we also compared parapineal mean position datasets with Welch t-tests using absolute values to discriminate between a defect in laterality (i. e. left-right randomization of parapineal migration) and a defect in migration per se (i.
Acknowledgements We are grateful to all members of the  Blader lab , especially  Elise Cau  and  Julie Batut  for critical reading of the manuscript and  Aurelie Quillien  for insightful discussions. We also thank  Eric Theveneau  and  Matthias Carl  for critical reading of the manuscript, as well as  Xiaobo Wang  and  Steve W Wilson  for their input. We thank  Brice Ronsin  from the  Toulouse RIO Imaging platform  and  Aurore Laire  for fish care. This work was supported by the  Centre National de la Recherche Scientifique (CNRS) , the  Institut National de la Santeet de la Recherche Medicale (INSERM) ,  Universitede Toulouse III (UPS) , the  Fondation pour la Recherche Medicale (FRM ;  DEQ20131029166 ), the  Fondation ARC  ( PJA 20131200173 ), the  Agence nationale de la recherche  ( ANR-16-CE13-0013-01 ) and the  China Scholarship Council  ( CSC No.
Filtering of mutations To remove false-positive calls and identify the point mutations that appeared during the growth passages, we removed all calls that had less than 3 supporting reads. We found that in some areas, the sequenced strain was highly divergent from the reference genome deposited in the database. In these cases, only a small percentage of the reads from these regions were able to align, and none of the calls in these regions were reliable. To filter out these unreliable calls, they were also removed if they occurred in regions with less than 10% of the average depth to avoid false positives in highly diverged regions. Finally, since point mutations will be unique to only a single strain, all calls that were shared by multiple strains were removed. Putative single nucleotide variants and small indels were identified using callVariants (from the bbmap package v37.
Availability of data and materials Strains used in this study are listed in Additional file 9: Table  S5  and available at the Fungal Genetics Stock Center (http://www. fgsc. net/asperg. html). The last passage of the mutation accumulating lines is available on request to the laboratories (A. flavus from Keller lab, A. fumigatus from Braus lab and A. nidulans from Cánovas lab). The SRA accession numbers for the genome sequences are listed in Additional file 10: Table  S6 ).
Primers were synthesized using the sequences provided in the publication by Verweij et al. 14  (GenBank accession numbers AY028262 and AF 279916). TaqMan exogenous internal positive control (Applied Biosystems ™ , Foster City, CA) was used to exclude the presence of PCR inhibitors. PCR was deemed negative when no amplification could be recorded or above a threshold of 40 cycle threshold (Ct).
0 keV) using a monochromated X-ray beam with an energy slightly below the absorption edge (19. 9 keV) for the SAXS measurements and scanning up to 20. 3 keV for the XANES measurements. Scattering intensities were collected with a 2D MAR detector positioned at 1. 97 m from the sample to allow for a usable q-range of 0. 3 < q < 4. 0 nm-1 (corresponding to a spatial resolution of 1. 5-20 nm) and transmission was measured with a photodiode positioned in the beamstop of the SAXS detector. XANES spectra were normalized and fitted by linear combination fitting, using the oxidic and fully sulfided (after 2 h at 350 °C) spectra as references. EXAFS data was normalized and processed with Athena software as described in the SI. [17] SAXS data was processed and reduced using FIT2D software and consisted primarily of normalization, transmission correction, data integration (to 1D) and background subtraction (of the cell filled with pure γalumina at the corresponding temperature).
Patients And Methods Patients We performed a retrospective analysis of data collected in real time from COPD patients undergoing a home-based PR program between January 2010 and June 2017 in Northern France. The study population included 459 patients (Figure  1 ) who were referred by their pulmonologist because of disabling dyspnea experienced during activities of daily living, despite optimal treatment, including drugs, LTOT, NIV, or continuous positive airway pressure (CPAP). Pulmonary function tests were performed at baseline. Forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV 1 ) were measured by spirometry. Values are expressed as percentages of the predicted normal values. The patients were offered the opportunity to participate in the home-based PR program, and their decision was based on personal preference and/or unavailability of a local PR program.
The quality of the linear models was verified by analysis of residuals. In the case of non-normality of residuals, the data were log-transformed. Multiple imputation was performed on these factors to limit the impact of missing data. All analyses were adjusted for confounding factors (age, sex, living arrangement, socioprofessional status, smoking status, and FVC). The significance threshold was set at 0. 05. All analyses were performed using SAS software version 9. 4 (SAS Institute, Cary, NC, USA).
The following data were prospectively collected: age; sex; underlying disease; PJP prophylaxis; other medications including glucocorticoids taken during the past month; type of symptoms and symptom duration at PJP diagnosis and time from symptom onset to hospital admission. Secondary, the clinical data were collected for all patients from medical records: laboratory findings (white blood cell count; absolute neutrophil count; C-reactive protein [CRP] level; BAL fluid findings including the cell profile assessed by an independent cytologist on centrifuged BAL fluid samples prepared with the Wright-Giemsa and Perls stains to allow the determination of macrophage, lymphocyte, neutrophil, eosinophil, and basophil counts); presence of P. jirovecii and/or other fungi and/or bacteria and/or viruses (influenza viruses, respiratory syncytial virus, adenovirus, cytomegalovirus) were recorded at PJP diagnosis.
The SOFA score on day 1 and the ratio of the arterial partial pressure of oxygen over the fraction of inspired oxygen (PaO 2 /FiO 2 ) on day 1  [19]  were recorded for each patient at PJP diagnosis. Anti-PJP medications, adjuvant glucocorticoid therapy, oxygen supplementation, and ventilatory support provided at admission were documented. Finally, patient outcomes including 90-day mortality were recorded. The collection of follow-up data ended in December 2017.
A history of glucocorticoid exposure is an often reported risk factor for PJP in HIV-negative patients  [41, 42]. Among our patients, over half were receiving glucocorticoid therapy at the diagnosis of PJP, in a mean prednisone-equivalent dosage of 20 mg/day. Adjuvant glucocorticoid therapy was given to most severe patients who failed antibiotic treatment alone. Given the history of glucocorticoid exposure, the effects of adjuvant glucocorticoid therapy were difficult to assess. The role for adjuvant glucocorticoid therapy in patients with PJP is debated  [26, [43] [44] [45] [46] [47]  and is currently being assessed in a prospective study (ClinicalTrials. gov Identifier: NCT02944045). Serum LDH level at PJP diagnosis was associated with poor outcomes in HIV-positive and HIV-negative patients in several studies  [48].
Methods Patients Epidemiologic, clinical, and radiologic data were retrospectively reviewed from the adult (n = 197)  10  and pediatric (n = 76) French cohorts of MOG-IgG-positive patients diagnosed between January 2014 and January 2018. MRI was performed in the clinical setting including axial and sagittal images of the brain and spinal cord obtained by T1-, T2-, fluid attenuated inversion (FLAIR), and T1-weighted postcontrast sequences. For experiments, sera from MOG-IgG-positive patients with CN involvement and controls were used. As controls, we selected 1 MOG-IgG-positive patient with an exclusive CNS involvement, 1 healthy control, and 1 double-seronegative (MOG and aquaporin-4 [AQP4]-IgG-negative) NMOSD patient.
Standard protocol approvals, registrations, and patient consents The study was approved by the Ethics Committee of the University Hospital of Lyon, France. All patients provided their informed consent to participate in the study. This study was conducted within the framework of Observatoire Français de la Sclérose en Plaques (OFSEP). Because of national confidentiality requirements, only anonymized data, not pseudonymized data, can be shared. Although anonymization techniques might result in impoverishment of data (Article 29 of Directive 95/46/EC, Opinion 05/2014 on Anonymization Techniques-0829/14/EN WP 216), data used for this study were only pseudonymized. However, access to OFSEP data to conduct a scientific project is possible by following the OFSEP data access process (ofsep. org/en/ data access) and with respect to French law.
Study funding This study was supported by a grant from the  ARSEP Foundation  and a grant provided by the  French State  and handled by the  "Agence Nationale de la Recherche ", within the framework of the  "Investments for the Future" program , under the reference  ANR-10-COHO-002   Observatoire Français de la Sclérose en Plaques (OFSEP) , by the  Eugene Devic Foundation against Multiple Sclerosis (EDMUS Foundation ), and the patient association " Déchaine Ton Coeur". Appendix 1 Author  contributions.
Error analysis All statistical uncertainties in the correlation functions, and similarly for other variables, were determined from bootstrapping described here. From the complete dataset from which the representative correlation function g is determined (see Eq. (  1 )), subsets (fractional size η) are sampled with replacement and analysed identically to produce a distribution of outcomes G. A robust estimate of the standard error of the mean (correlation function in this case) is then given by σ ḡ = η • Var(G), independent of the sampling size.
The authors would like to thank  Alain Aspect ,  Michael Barson ,  Danny Cocks ,  Matteo Fadel ,  Karen Kheruntsyan ,  Wolfgang Mittig ,  Margaret Reid ,  Jacob Ross  and  Tilman Zibold  for insightful discussions. This work was supported through  Australian Research Council (ARC)   Discovery Project grants   DP120101390 ,  DP140101763  and  DP160102337. DKS is supported by an  Australian   Government Research Training Program Scholarship. SSH is supported by  ARC   Discovery Early Career Researcher Award   DE150100315. JC is supported by Project no. 2017/25/Z/ST2/03039 , funded by the  National Science Centre, Poland , under the  QuantERA  programme.
S1 ). Between October and June (the main pre-breeding and breeding seasons), the core at-sea Mediterranean distribution of the Menorcan population fell further east than that of Mallorcan birds, showing more similarity to that of Yelkouan shearwaters (Fig. 3 ). 13 C values of feathers grown during the non-breeding period differed significantly between the three populations (Table  1 ). Hierarchical clustering analysis identified two distinct isotopic groups from δ 15 N and δ  13  C data (Fig. 4 ; Supplementary Fig. S2 ). Isotopic values in P6 feathers sampled from tracked Balearic shearwaters that spent the non-breeding period in Mediterranean and Atlantic waters differentiated into separate clusters. A similar pattern was observed for P1, with most Mallorcan and Yelkouan shearwaters falling into the ' Atlantic' and 'Mediterranean' clusters respectively, and Menorcan shearwaters spanning both although predominantly falling within the Mediterranean cluster.
5 ). The δ 15 N values of some Mediterranean-assigned birds were lower than the sampled prey space, potentially indicating some exploitation of lower trophic level prey, or migratory movements into food webs further east than our sampling range. δ δ =. × +. × +. D N C δ δ =. × -. × -. D Mediterranean N C ( ) 14 Phenology and plumage variation. Phenological attributes were extracted from immersion data collected for all birds tracked with geolocators and used in spatial analyses of migration behaviour, plus an additional two Yelkouan shearwaters for which only partial light data were recovered. Geolocator data indicated that the timing of key annual cycle events for tracked individuals from all three populations was variable (see Supplementary Fig. S3  and Table  S2 ). Small sample sizes at the Menorcan colony prevented statistical comparisons of phenology within year.
Geolocation light data were processed with BAStrak software (British Antarctic Survey, Cambridge, UK), using a light threshold of 10. Light curves were manually assessed and discarded in the presence of obvious light interference during sunrise and sunset transitions. Data were filtered to remove dark periods of <4 hrs, unreliable fixes around the equinoxes (10 days on the winter side, and 5 days on the summer side), unrealistic locations >52° and <30°N, and locations associated with unrealistic travel distances based on a maximum travel speed of 55 km h -1 55. The sensitivity of individual devices to different sun elevation angles (EA) was calibrated during the late incubation and chick-rearing period, when it was assumed that the birds' movements were centred near the colony. The angle that resulted in the smallest locational bias, and/or fewest points on land, during this period was used for each geolocator (EA: -3.
0° to -4. 0°). Balearic shearwaters predominantly attend colonies between October and June, but do not begin incubating until the early spring  33. To investigate phenology of the focal populations, we defined the start and end dates of the non-breeding period as the birds' last and first night visits to the colony, respectively. Following  33  , night visits were identified as periods of continuous night-time dryness in the geolocator salt-water immersion trace (≥2 hrs), while day time visits to the colony were identified as complete daytime darkness in the light trace. The median first night visit for birds with a full year of recovered data was used as the end of the non-breeding period for birds whose activity loggers had failed prior to their return to the colony. Both activity and light data were used to estimate laying date, based on patterns of asynchronous daytime visits to the colony between pair members (or when only one pair member was tracked, the onset of regular daytime visits lasting ≥2 days in males, and first colony visit after the post-laying exodus in females).
As events later in the breeding cycle (i. e. migration leaving date) are susceptible to breeding failure (which was not measurable for most birds from Menorca and France due to accessibility constraints), we compared only the first cave day visit, laying date and last cave day visit (estimated hatch date), which can be inferred consistently. The core non-breeding areas of individual birds from Menorca were determined using fixed kernel density estimation (KDE) in the 'KernSmooth' package in R  66  (data projection: lambert conformal conic; cell size: 1 × 1 km). Optimised KDE bandwidths were obtained for each bird using the multivariate plug-in selector in the 'ks' package in R  67, 68. Seasonal population-level KDEs (3-monthly intervals) were also obtained for the three populations for periods with sufficient comparable data (June, July-September, October-December, January-March).
Partial data collected during April and May were excluded here as these months coincided with logger deployment and recovery periods at some colonies, and thus contained periods of missing data and small sample sizes. Stable isotopes. The carbon and nitrogen stable isotope compositions of animal tissues reflect diet during tissue growth. Isotope compositions of individuals moving between isotopically distinct habitats can therefore provide information on the spatial location of feeding  46. To aid investigation of non-breeding movements, and support interpretation of the limited spatial data from Menorcan shearwaters, feather stable isotope data were collected from a larger number of birds at focal colonies. For the Mallorcan and Menorcan populations, primary flight feathers representing the early (P1) and central (P6) parts of the non-breeding season  38  were sampled from both tracked and untracked birds during spring 2012 and 2013 (Tracked birds, Menorca: n = 4, Mallorca: n = 32; Untracked birds, Menorca: n = 32, Mallorca: n = 9; feathers representative of diet during the 2011 and 2012 non-breeding periods).
Feather choice was based on extensive moult scoring of Balearic shearwaters from at-sea images and at colonies (see  69  ). To obtain reference isotope data for the western Mediterranean region, feather down from 40 Mallorcan chicks was sampled in June 2013. Feathers were washed in a solution of 0. 25 M sodium hydroxide, rinsed in successive washes of milli-Q water and oven dried at 50 °C until reaching constant mass. Samples were then cut into ~1 mm pieces prior to weighing. We then compared data from Balearic shearwaters to available temporally matching isotope values for Yelkouan shearwaters sampled from P1 feathers grown during 2011  35  (n = 33). Stable isotope analyses (SIA) of Balearic shearwater samples were carried out at the Natural Environment Research Council Life Science Mass Spectrometry Facility in East Kilbride, using a Flash HT elemental analyser (2012) or Elementar vario PYRO cube elemental analyser (2013) coupled with a Thermo Electro Delta XP continuous flow isotope ratio mass spectrometer.
Isotope ratios were expressed in delta notation in parts per thousand (‰), relative to international standards of δ 13 C (Pee Dee Belemnite, V-PCB) and δ 15 N (atmospheric N 2 , AIR). Multiple measurements of three internal laboratory standards (gelatine, alanine and glycine) in each SIA experiment indicated that measurement error was smaller than 0. 2‰ for δ 15 N and 0. 1‰ for δ  13  C. We used hierarchical clustering analysis with the Ward's minimum variance method on stable isotope data from P1 and P6 feathers (separately), to investigate the degree to which Balearic and Yelkouan shearwaters that used different non-breeding areas clustered together isotopically. To describe the distribution of stable isotope measurements in two-dimensional isotope space, standard ellipse areas (SEAc: corrected for smaller sample sizes), Bayesian approximations of standard ellipse areas (SEAb) and convex hulls were calculated for groups obtained via hierarchical clustering using the SIAR package in R  70, 71.
Discriminant function analysis (DFA) was then performed on P1 (Balearic and Yelkouan shearwaters) and P6 (Balearic shearwaters) isotope values, representative of the beginning and central parts of the non-breeding season  38  , to examine how well isotopic tracers discriminated between the non-breeding regions of birds, and allow predictions to be made for untracked birds. The isotope values of 38 tracked individuals for P1 (Mediterranean = 19, Atlantic = 19; no repeated individual measures) and 26 tracked individuals for P6 (Mediterranean = 8, Atlantic = 18; no repeated individual measures) were first used as training datasets to develop the discriminant functions, before predictions were made for 62 and 41 untracked birds for P1 and P6, respectively (P1 = 9 Mallorcan, 32 Menorcan, 21 Yelkouan; P6 = 32 Menorcan, 9 Mallorcan).
The obtained DFAs were validated using a jackknife leave-one-out cross-validation method on training data. In order to disentangle spatial and trophic influences on feather stable isotope compositions from the Mediterranean and Atlantic, isotopic ratios of P6 feathers from Mallorcan and Menorcan shearwaters, grown during the non-breeding season in 2012, were compared to fractionation-corrected isotope ratios in pelagic and demersal fish muscle samples (see Supplementary Table  S1  for sample details). P1 isotope values from Yelkouan shearwaters grown in 2011 (the nearest temporal match to sampled prey) were also presented as a comparison. As there are no published feather-prey muscle isotopic discrimination factors for adult Procellariiformes, the means of published discrimination factors for similar seabird species were applied to prey data (δ 15 N = 3.