dataesr/scientific-paragraphs-categorization huggingface dataset:
Patients Patients included for this study were seen in the Department of Neurology out-patient clinic of the Penn FTD Center and data were retrieved from The Integrated Neurodegenerative Disease Database (INDD)  (18)  at the University of Pennsylvania. All patients had a clinical diagnosis of PPA involving prominent language difficulty and minimal evidence of impairment in other cognitive domains  (19)  based on a semi-structured clinical history, a complete neurological evaluation, and a detailed mental status assessment. From among 131 individuals with a diagnosis of PPA in INDD who also had CSF data, we restricted participants in the current study to those that met strict clinical diagnostic criteria for a specific variant of PPA (1) as adapted recently for lvPPA  (14). In this study, a diagnosis of lvPPA included deficits of word-finding difficulty in continuous speech with impaired phonological loop functioning measured by a short forward digit span.
T1 MRI images were preprocessed using antsCorticalThickness  (22). Each individual dataset was deformed into a standard local template space in a canonical stereotactic coordinate system. Registration was performed using a diffeomorphic deformation that is symmetric to minimize bias toward the reference space for computing the mappings and topology-preserving to capture the large deformation necessary to aggregate images in a common space. The ANTs Atropos tool used template-based priors to segment images into 6 tissue classes (cortical gray matter, white matter, CSF, deep gray structures, midbrain, and cerebellum), and generated the probability images of each tissue class  (23). Here we focused on cortical gray matter probability (GMP) images that were transformed into MNI space, and downsampled to 2 mm isotropic voxels.
This voxel size approximates the true thickness of cortex, although at the cost of less robust p-values due to a larger number of comparisons. We smoothed the data using a 2 sigma full-width half-maximum Gaussian kernel before analysis. Voxelwise analyses of GMP were performed using the non-parametric randomize tool implemented in the FMRIB Software Library (FSL: http://fsl. fmrib. ox. ac. uk) with 10,000 permutations that is equivalent to an analysis protecting for multiple comparisons. We report clusters that survived p < 0. 01 with a minimum of 150 adjacent voxels. We report two sets of t-tests: First, we examined each patient group (lvPPA, naPPA, svPPA) relative to controls; and second, we examined each CSF-subgroup relative to controls (low-Aß 1-42 , hi-Aß 1-42 ).
Micro-XRPD mapping μ-XRPD data collection was done at the microprobe hutch of the Hard X-ray micro/nanoprobe beamline 1 See Ref  [17]. (P06) of the PETRA III storage ring (DESY, Hamburg, Germany)  [21] , using a primary photon energy of 21 keV, which is selected by means of a Si(111) double crystal monochromator. A Kirkpatrick-Baez mirror optic was employed to focus the beam, achieving a size of 0. 5 × 0. 5 μm 2 (h × v). A Keyence optical microscope equipped with a perforated mirror allowed for positioning of the sample. Diffraction signals were recorded in transmission geometry using an EIGER X 4M area detector (Dectris Ltd. , Switzerland). Calibration of the diffraction setup was performed by means of a LaB 6 reference sample. The total size of the sample was of the order of 500 × 600 μm 2 and was embedded in resin and polished prior to analysis.
Data processing Crystalline phase distribution maps (both macroscopic and microscopic) were obtained by full pattern refinement using the XRDUA software package  [22]. The individual diffractograms were fitted to a background term and a linear combination of peak groups  [23]. Each peak group contained the Bragg peaks of one crystalline phase and has three parameters that were refined during the fit process: the sample-detector distance, a scaling factor and a width factor. The scaling factor is proportional to the total volume of scattering material for a given phase and is shown in the distribution maps presented in this work. The software packages PyMCA and DataMuncher were used to create the elemental distribution maps (see  [24]  for details). To avoid overlap between Pb-L and As-K XRF signals, the K β -line of As was employed for mapping this element.
Another study member recorded all of the data on an Excel spreadsheet as each exam progressed. Even one mistake resulted in a failed attempt. Possible mistakes included failed arcs and sweeps, not using enough gel, or mis-positioning the probe. A complete report of mistakes is included in the results section, and we employed standardized definitions of each mistake to ensure consistency between the trainees. After each complete attempt, study members explained the mistakes each participant made and answered any questions. Participants continued performing the protocol until they performed it perfectly two consecutive times without error. After this, if time permitted, each subject performed the protocol on the opposite hemithorax until one perfect attempt. Following the training, a brief survey was completed.
Acknowledgment We would like to thank  Dr. Carlos Valer ,  Dr. Egoavil , the health workers, and patients at the  Huayanay Health Center , the  Potrero Health Center , the  Pavayoc Health Center , and the  Santa Ana Health Center  for their hospitality and participation in this investigation. We would like to thank  Dr. Solomon Kim ,  Mauricio Salazar ,  Sarah Klingenberger ,  Nadezhda Kiriyak , and  Gwen Mack  for their assistance with videos, illustrations, and figures. We would like to thank  Dr. Vikram Dogra  and  Dr. Deborah Rubens  for their support in the project.
Sorting efficiency was investigated with constant hydrodynamics conditions (F emulsion = 20 μL h -1 and F oil = 700 μL h -1 ) by applying a 20 kHz AC field from 0 to 1 kV (Agilent 33210A function generator connected to a Trek 623B high voltage amplifier). Droplets were imaged at 13000 fps using a high-speed camera (Phantom v210) and movies were analyzed using the Phantom Camera Control software (PCC 2. 1. 4). Details of the image processing and data analysis are given in the ESI. †.
Acknowledgements J. -C. B. acknowledges the support from the  ERC  ( FP7/2007-2013/ERC Starting Grant 306385-SofI ), from the  French  state in the frame of the "Investments for the future",  Programme IdEx Bordeaux ,  ANR-10-IDEX-03-02 , from the " Région Aquitaine " and from the  Institut Universitaire de France. We would like to thank  Dr. Ouriel Caen  and  Dr. Valérie Taly  ( Univ. Paris Descartes)  for fruitful discussions.
Statistical Analysis. Results are expressed as the mean ± standard deviation (SD). Normality was checked using Kolmogorov-Smirnov's test. The assumption of homogeneity of variance was assessed using the Bartlett F-test. When the conditions of normality and homogeneity of variance were respected, one-way (to analyse data between the groups) or two-way mixed model ANOVAs with repeated measures (group, time, and group×time interaction) were run and a Newman-Keuls post hoc test was applied when the ANOVA reached significance level (p < 0 05). All data were analysed using the Statistica software.
Acknowledgments This study was supported by  (i) the "Région Auvergne-Rhône-Alpes " ( PREVAMIC  project), (ii) the  French government IDEX-ISITE  initiative  16-IDEX-0001  ( CAP 20-25 ) and I- SITE  project ( CAP 2025 ) of the  University of Clermont Auvergne, (iii) INSERM  ( U1071 ) and  INRA  ( USC-2018 ), and (iv) grants from the  Association F. Aupetit (AFA).
Acknowledgments We would like to thank the  Department of Human Genetics, LUMC , for the STR DNA analysis and the  Laboratorium voor Diagnostische Genoomanalyse (LGDA) ,  LUMC , for the karyotyping analysis. This work was supported by the  Netherlands Organ-on-Chip Initiative , an  NOW   Gravitation  project funded by the  Ministry of Education, Culture and Science of the government of the Netherlands  ( 024. 003. 001 ).
Introduction Heart transplantation offers the most effective therapy for patients with end-stage heart failure but is severely limited by organ shortages and, in some cases, by patient comorbidities  [1]. The use of mechanical circulatory support, and in particular left ventricular assist devices (LVAD), has been shown to offer a valuable therapy for these patients but only indicate for mono-ventricular heart disease compared to an optimal medical management  [2]. Nowadays, 2,500 patients are implanted annually in the USA with mechanical circulatory devices and the INTER-MACS registry database includes over 20,000 patients  [3]. The Carmat Total Artificial Heart (C-TAH) was developed as a heart replacement device in new Physiological Heart Replacement Therapy for patients at risk of imminent death from bi-ventricular failure.
Clinical feasibility study of Carmat Total Artificial Heart implantation This was a single-arm, prospective, non-blinded and non-randomized study of 4 patients conducted in 4 four French centers. The study was approved by the French National Agency for Medicines and Health Products Safety, and the Paris' Regional Ethics Committee. The study was registered in the European Databank on Medical Devices (CIV-FR-13-09-011615). Plasma from Heartmate II patients were sampled according to register number 1922081. All patients had signed the informed consent, and the study was performed in accordance with the Declaration of Helsinki  [30].
For microvesibles (MV) quantification, thawed plasma samples were 1/10 diluted in physiological serum and stained with anti-human fluorochrome-coupled antibodies for MV phenotyping: Annexin V Pacific Blue (ebioscience) and CD41 Fluorescein isothiocyanate FITC (FITC, Beckman Coulter). Fluorescent calibrated beads Megamix-Plus SSC (Biocytex) were used to define MV size based on side scatter parameter according to manufacturer instructions. MV concentrations were assessed by addition of an internal calibrator, AccuCount fluorescent particles (Shperotech) with a known concentration of particles per volume. Acquisitions of stained MV and calibrated beads were performed with a LSR Fortessa SORP cytometer (Becton Dickinson). Analyses were done with FlowJo 10 software (TreeStar).
No significant increase of plasma quantification of remnant glutaraldehyde was observed after implantation or during the follow-up. In conclusion, we demonstrated here the safety of the hybrid membrane regarding the mechanical aging, the calcification issues, and the impact of the membrane pulsatile movement on blood components. Safety confirmation of our findings will follow-up in the up-coming pivotal clinical study of the C-TAH (NCT02962973) implantation in 20 patients with end-stage biventricular heart failure.
Timing of administration of the study treatment First administration of the study treatment (vildagliptin or placebo) will be performed within hours prior to patient departure to the operating room. The dosage of vildagliptin will conform to the marketing authorization of data in its indication in the treatment of diabetes in kidney transplant patients. Patients will receive a half dose of therapy until they have a glomerular filtration rate greater than 50 ml/min of (MDRD equation). Patients will receive one oral tablet in the morning and one in the evening (100 mg per day) or just one in the morning (50 mg per day) for 2 months.
Study visits As presented in Fig. 1  (Additional file 1), the study will include five visits (D0, D8, M3, M6, and M12) corresponding to those taking place in the context of the current follow-up after a kidney transplant. During these visits, clinical examination and a blood test will be conducted as part of the study to collect necessary clinical data in each center on case report forms and to determine the different dosages in the hospital laboratories, respectively. Blood glucose will be controlled and, if necessary, hyperglycemia will be treated according to current recommendations, regardless of the group and the study. The HRQoL will be estimated using the ReTransQoL questionnaire and the health-utility with the EQ-5D questionnaire (EuroQol questionnaire with five dimensions). The benefits of prevention of NODAT will be evaluated by estimating the cost of patient care during the first year of transplantation (care, medicines, medical examinations, hospitalization, etc.
Primary outcome analysis The intention to treat (ITT) population will be used for efficacy parameter analysis (all randomized patients whatever the eligibility criteria and treatment received). A Z score test with pooled estimate for variance estimation will be used to compare the estimated proportion of diabetic patients 1 year after transplantation between the two arms. A Lan-DeMets alpha spending function with O'Brien and Fleming boundaries (function ASSESSMENTS: Physical examination X X X X X Collect of necessary clinical data Blood sample X X X X X OGTT (primary endpoint) X X X X Fasting Glucose test (primary endpoint) X X X X X M2 D0 M2 D0 D0 M12 Glycated hemoglobin (HbA1c) test X X X X X Questionnaire ReTRANSQUOL X X X X X X Cost-effectiveness ratio (EQ-5D).
Secondary outcome, exploratory, and sensitivity analyses Selected efficacy analyses will be repeated in the per protocol population (i. e. , subset of the ITT population meeting the following criteria: all eligibility criteria fulfilled, at least one dose of allocated treatment administered). The safety population will be used for reporting the safety and treatment exposure data. A modified ITT population will be used for HRQoL analysis, considering all randomized patients with at least the baseline HRQoL questionnaire available. Continuous variables will be summarized using descriptive statistics, i. e. , the number of patients with available data (n), mean, median, standard deviation (SD), 25-75% quartile (Q1-Q3), minimum, and maximum. Continuous variables could be transformed to categorical variables using the median or using conventional cut-offs from bibliography or clinical practice.
Data Management of the study Clinical data management is performed at the Methodology and quality of life unit in oncology of University Besançon hospital using SAS version 9. 4 (SAS Institute, Cary, NC, USA). Originals of all study-related report forms will be stored in the study headquarters at the trial site (according to the respective national laws). The data will be provided as SAS® files to the statistical team for data analysis using SAS version 9. 4 and R software version 2. 15. 2 (R Development Core Team, Vienna, Austria; https://www. r-project. org/). Investigators store all administrative documents, patient identification logs, signed patient consent forms, copies of the data documentation forms, and common study documentation. Original data for study patients (medical records) will be stored.
This number of patients may still vary at 6 months and one year post-transplant  [6]. The main criterion is the number of patients with diabetes at one year. The onset of diabetes at other times (3 and 6 months) as well as abnormal glucose indicators (fasting glucose, OGTT, glycated hemoglobin) at each time will be assessed as secondary endpoints. These data will also be correlated with the clinical events (occurrence of acute rejection, infection, graft loss, and patient death at 3, 6, and 12 months after transplantation), the medical history, and the biological assessment of the patients.
Statistical Analyses All data are presented as means ± standard deviation (SD). Data were analyzed using Statistica for Windows software (version 6. 0, StatSoft, Inc. , Tulsa, OK). Values for physical and biochemical parameters were normalized to 100%. Once the assumption of normality was confirmed using the Shapiro-Wilk W-test, parametric tests were performed. Anthropometric measures and dietary data between BR and End-R periods were analyzed using paired Student's t test. For all physiological, biochemical, and perceptual data, a two-way ANOVA with repeated measures [Sessions (BR or End-R) × time (Baseline, 0, 24, 48, and 72 h post exercise)] was performed. When appropriate, post hoc comparisons were used with the Bonferroni test. Power calculation was made using G*Power v. 3  (Faul et al.
Some limitations inherent to the experimental protocol of this study warrant mention. First, the statistical power is very low (around 40%) due to the small sample size in the present study. However, this limitation is tempered by the use of professional players in our study. It was deemed necessary to recruit professional soccer players as the LIST mod was based on data collected on top-level soccer players. Another major limitation of the present study is the absence of a control group (e. g. , soccer players not fasting during Ramadan). But it should be noted that obtaining non-fasting participants in countries with a Muslim majority is not feasible due to ethical and practical reasons. Therefore, the majority of studies on Ramadan fasting conducted in Muslim countries used pre-Ramadan values as control/baseline condition.
A calibration test consisting of five registration points was performed before each set of stimuli. The calibration test was repeated if the examiner considered one of the five points not valid according to the eye-tracker criteria (recorded gaze extrapolating the limits of the calibration-designed area or absence of recording for one of the five points). All participants matched general recording quality criteria, based on the amount of valid and missing data, as indicated by Tobii Studio software. The participants were instructed that they would see a sequence of clips and all they had to do was watch them. Since we have used stimuli composed of short clips extracted from a popular French commercial film (Le Petit Nicolas), at the end of the eye-tracking sessions, participants were asked if they were familiar with the presented film clips and confirmed have seen it once.
MRI scans. All MRI exams included T1-weighted and ASL sequences and were acquired on a General Electric Signa 1. 5 T MRI scanner in the Necker Hospital. We acquired a 3D pseudocontinuous arterial spin labeling (3D pcASL) sequence using a fast spin echo acquisition with spiral filling of the K space (TR/TE: 4453/10. 96 msec, 8 spiral arms x 512 sampling points, post-labeling delay: 1025 msec, flip angle: 155°, matrix size: 128 × 128, slice thickness: 4 mm, Field of View: 24 × 24 cm, 40 contiguous axial slices, duration: ≈ 5 mins). CBF quantification from ASL tagged and control images was performed and warranted by General Electric 3D ASL software (Zaharchuk G, 2009). Anatomical sequences were used only for spatial normalization of ASL sequences.
statistical Analysis Eye tracking. In each movie clip, areas of interest (AOIs) were defined around the eyes of the characters. The number of fixations in each AOI was recorded using the Tobii Studio software. A fixation event was defined by the Tobii fixation filter based on a 0. 42 pixels/ms threshold. The number of fixations was calculated for all participants. The number of fixations to the eyes was selected since it is an absolute variable that informs exploratory behavior towards a defined region: a higher number of fixations indicates that people are likely to further explore the region  25. Importantly, the number of fixations to the eyes and total amount of time spent looking at the eyes are strongly correlated (R = 0. 79; p = 4. 206e-08). In both studies, the number of fixations to the eyes were pooled together from all clips providing an individual score of the number of fixations to the eyes.
AsL-MRI. Structural T1-weighted and ASL images were analyzed using SPM8 (http://www. fil. ion. ucl. ac. uk/spm) implemented in Matlab (Mathworks Inc. , Sherborn, MA, USA). Briefly, structural T1 images were segmented into grey matter, white matter and cerebrospinal fluid using the VBM8 toolbox (http://dbm. neuro. uni-jena. de/vbm/). The ASL images were co-registered to the corresponding native grey matter images and spatially normalized to the MNI space using the deformation matrices from the segmentation process. The resulting ASL images were smoothed using an isotropic Gaussian filter of 8 mm. In Study 2, whole-brain, voxel-by-voxel statistical analyses were performed using a mass-univariates approach within the classical framework of the general linear model of SPM8. This approach provided an appropriate design to perform correlation analyses on the smoothed and normalized ASL images.
Study 2. Brain imaging study -correlation with eye-tracking data. To investigate whether the interindividual variability in social perception correlated with individual patterns of local rest brain function, we studied an additional non-overlapping group of 33 young healthy volunteers. Participants performed an eye-tracking session, and gaze pattern was measured using the same stimuli set described in the previous study (Fig. 1 ). In addition, participants underwent an MRI in which ASL-MRI was used to measure whole-brain CBF at rest, an index of local rest brain function. Analyses of the eye-tracking data in this second independent group confirmed a large interindividual variability in the number of fixations to the eyes (mean = 68. 6 ± 27. 1; range = 94). Interestingly, the variation in the number of fixations to the eyes followed a normal distribution (W = 0.
This needs to be considered in data evaluation and interpretation. For each river, one reach was selected and sampled for leaf litter (further referred as leaves), epilithic biofilms (biofilms), and sediments (details on material collection are provided in Supporting Information). After collection, field samples were further processed in the laboratory. Leaves and biofilms were oven-dried (60°C, 12 hr) to achieve constant mass, reduce variability from fluctuations in water content  (Boulton & Boon, 1991) , and ensure cellular death of the leaf tissue. Oven-drying mainly affects volatile and oxidizable compounds, which were not in the focus of our study. However, oven-drying may increase the amount of leached substances from leaves and biofilms (e. g. Gessner & Schwoerbel, 1989). Bed sediments were sieved (2 mm) and air-dried for 1 week.
The dry material was placed in transparent plastic bags, shipped to laboratories responsible for further analyses (see Acknowledgements), and stored in a dry and dark room until processing and analysis. Nine environmental variables were selected to analyze their association with leachate characteristics (Table  1 ). The variables were selected based on a conceptual understanding of the leaching process. As proxies of a regional-scale influence, we used the aridity index and potential evapotranspiration (PET) extracted from the Global Aridity and PET database (for details see  Datry et al. , 2018). River width, riparian cover (%, visually estimated as the proportion of river reach covered by vegetation), dry period duration (estimated either with water loggers or repeated observations, precision: 2 weeks), altitude, and land cover (%) of pasture, forest, and urban areas within the catchment were selected as proxies of local influence.
Biofilm leachates were excluded from the cross-climate comparison as the majority of samples were taken in the temperate zone (35 out of 41 samples). Variability in leached amounts (Hypothesis 1) was assessed based on interquartile difference (quartile three of data distribution minus quartile one) TA B L E 2 Total and relative leaching rates of nutrients and organic matter species from leaves and bed sediments of IRES (median). For abbreviations, see TA B L E 3 Ranking of environmental variables and substrates characteristics that explain variance in quantitative composition (A) and qualitative characteristics (B) of leachates at global and regional scales according to their value of VIP (variable influence on projection) in the PLS analysis. In order to identify the environmental variables and substrate characteristics driving the quantitative (amounts of nutrients and OM) and qualitative (DOM quality) characteristics of the leachates partial least squares (PLS) regression models were applied  (Wold, Sjöstrom, & Eriksson, 2001).