dataesr/scientific-paragraphs-categorization huggingface dataset:
statistical analysis SPSS software (http://www-01. ibm. com/software/analytics/ spss/) was used for all analyses, and significance was assumed at p < 0. 05. The distribution of the percentage improvements did not follow a normal distribution (Shapiro-Wilk test, p = 0. 002 for global improvement). For this reason, and because of the small number of patients in each group, we used non-parametric tests. Spearman's rank correlation test was used for correlation analyses. The Wilcoxon signed-rank test was used for group comparisons and the Kruskal-Wallis test was used to compare scores across more than two groups. A mixed three-factor ANOVA was used to determine the effect of (i) the type of stimulation (root versus transcranial), (ii) the day of stimulation (day 1 or day 2), and (iii) the intervention group (group 1 or 2).
Experimental Procedures Expression vector construction. The coding sequence of ZIKV RdRp domain used in this study corresponds to the SPH2015 strain that has been optimized for codon usage using the GENEius software (Eurofins Genomics GmbH) followed by Pro codon optimization for bacterial expression (Genbank No. KY364193). The adapted gene harbored an internal BamHI recognition site that was subsequently removed and the sequence corresponding to an 8xHis tag was added in 5′ of the sequence. The corresponding DNA coding for a 72 kDa protein was obtained by gene synthesis (Eurofins Genomics GmbH, Munich) and inserted in the multi-cloning site of the pET-21a vector between BamHI and XhoI sites. Expression and purification of ZIKV NS5 RdRp domain. Rosetta cells were transformed with the pET-21a-ZIKVRdRp and bacteria are grown on LB plates containing ampicillin (100 µg/ml) and Chloramphenicol (34 µg/ml) overnight at 37 °C.
Liquid junction potentials were not corrected. Cultures were continuously perfused with artificial cerebrospinal fluid (aCSF) (140 mM NaCl, 1. 25 mM NaH 2 PO 4 , 3. 5 mM KCl, 2 mM CaCl 2 , 1 mM MgCl 2 , 13 mM glucose; bubbled with 95% O 2 /5% CO 2 (pH 7. 4). Mini excitatory post-synaptic currents (mEPSCs) were recorded at a holding potential of -70 mV and continuously perfused with tetrodotoxin (TTX; 500 nM) to block sodium channels, bicuculline (10 μM) to block GABA A receptors and CGP55845 (1 μM) to block GABA B receptors. Signals were recorded using a Multiclamp 700B (Axon instruments) and sampled at a frequency of 20 kHz (filtered to 10 kHz) using a Digidata 1550A (Axon instruments). Recorded traces were filtered further using Clampex software to a frequency of 1 kHz using an online bessel filter.
Experimental data were recorded with software IOX v2. 9 from Emka Technologies. The decrease in contraction force of the hemi-diaphragm muscle following toxin addition was calculated as a percentage of the contraction immediately prior to toxin addition and a four-parameter logistic curve fitted to the data using GraphPad Prism (version 6. 07, GraphPad Software, La Jolla California USA). From the curve fitted to the data, the times to 10% (t 10 ) and 50% (t 50 ) diaphragm paralysis were estimated.
Data handling and statistical analysis All data are expressed as individual data or as mean ± standard error of the mean (s. e. m. ) of n independent experiments. All concentration-effect data were fitted to a four-parameter logistic equation (Eq 2): Y ¼ Bottom þ ðtop À bottomÞ 1 þ expðlogðIC50 À XÞ Ã slope ðEq 2Þ For statistical analysis, significant differences between BoNT/B1, rBoNT/B1 and rBoNT/ B1 (S201P) were determined using a one-way ANOVA with Dunnett's post-hoc test, where appropriate. All data processing and statistical tests were performed using GraphPad Prism software (version 6. 07, GraphPad Software, La Jolla California USA).
The Inhibition of glutamate release from rat cortical neurons. Primary rat cortical neurons were incubated for (A) 24 hours (30 fM-3 nM) or (B) 5 hours (3 pM-30 nM) with rBoNT/B1 or rBoNT/B1 (S201P). Cells were pre-incubated with assay medium containing TFB-TBOA (excitatory amino acid transporter inhibitor) for 30 minutes before washing and assessment of basal and stimulated glutamate release for 5 minute periods using assay medium containing 5 mM or 60 mM potassium, respectively. Glutamate content of cell superfusates was determined using an Amplex Red fluorometric assay. Data were normalised to the glutamate release obtained from un-treated cells (Un-Tr) and fitted to a four-parameter equation. The concentration of each toxin required for 50% maximal inhibition (pIC 50 ) of glutamate release was determined from the fitted curves for (C)  24   potency of the toxins, defined as the ED 50 , (the dose calculated to induce a mean DAS of 2) was 1.
All subjects signed informed consent before performance of any procedures. The original ADMIRE-HF study design only included recording of the names of concomitant medications. For the present study, investigators were requested to review available records and provide the total daily doses of all cardiac medications included on the original study case report forms. Some investigators declined to participate in this data collection effort, and records for a small number of subjects could not be located. Dosing data for some subjects were obtained from review of case report forms and source documents submitted as part of the adjudication process in the original study. Of the 961 subjects with efficacy data (24 subjects were removed for protocol violations or incomplete imaging data), beta blocker dosing data were submitted for 707 subjects.
Data for an additional 73 subjects were obtained through records review. The analyses for these 780 subjects and the 78 who were not taking beta blockers (total of 89% of the efficacy population) provide the basis of the present report. Beta blockers used by the 780 study subjects were as follows: carvedilol: 438, metoprolol: 211, bisoprolol: 99, atenolol: 28, nebivolol: 3; propranolol: 1. Beta blocker dosages were converted into carvedilol-equivalent doses  19  using the factors presented in Table  1. Analyses were then performed using dose as a continuous variable and in quartiles.
Cox proportional hazards modelling was used to assess the relationship between outcomes and beta blocker dose as a continuous variable before and after adjustment for the variables found to be significantly associated with each endpoint. Kaplan-Meier survival analyses were performed to estimate 2-year event probabilities, with differences between groups assessed using the log-rank test. A P value <0. 05 was considered statistically significant for all comparisons. All analyses were performed using Medcalc v12. 6-13. 0 (Medcalc Software, Ostend, Belgium).
22 In HF-ACTION, allcause mortality did not show a dose-related benefit with beta blocker therapy when adjusted for other clinical variables, in particular when exercise capacity was added to the model. 19 In SENIORS, the effect of nebivolol vs. placebo was found only in the goups of patients receiving the highest doses (>50% maximal dose) of beta blocker. 23 There was no effect in the groups receiving less than 5 mg/day. However, SENIORS included only patients aged more than 70 years with both low and preserved LVEF. Recently, the CIBIS-ELD study 14 evaluated the tolerability of bisoprolol and carvedilol in elderly patients; only 31% of patients were able to reach target doses. Figures are poorer in registries: Data from the OPTIMIZE-HF registry showed that, in patients hospitalized for HF, the mean daily dose of beta blockers before hospital admission was one-half the recommended target dose.
A FACSCalibur (Becton Dickinson, San Jose, CA, USA) with an aircooled argon laser providing an excitation at 488 nm was used. For each sample 5000 events were acquired at a fluorescence emission of 620 nm (FL3). The cell population was electronically gated in a FSC/SSC dot plot and the fluorescence frequency distribution histogram was obtained. The percentage of dead cells was determined as the proportion of cells with an elevated fluorescence using a marker. Data collection and analysis were performed the CellQuest Pro software (Version 4. 0. 1). The results were expressed in percentage of viable cells. Differences between controls and treated groups were evaluated by one-way and two-way ANOVA followed by Dunnett's post hoc test. To evaluate correlations of inter-relationships of genes of interest a Spearman rank order correlation analysis was conducted and results are summarized in Table  3.
In this context, Delipidol® (BioEurope Solabia, France) has been selected as a test molecule to develop and optimise data mining approaches to rapidly and accurately chemical map the skin model to evaluate its kinetics of penetration by means of Non negative constrained least squares (NCLS) analysis. Although primarily used previously in the digital dewaxing of Raman and Infrared spectra recorded from partially chemically dewaxed tissue samples [30] and background subtraction [31], the Copyright line will be provided by the publisher method is an attractive data analytical option, delivering abundance fraction (concentration) estimation of chemical and biological agents that exist in the mixture form  [32]. Ultimately, distribution maps and penetration profiles can be obtained from the Raman datasets, providing crucial information about the ACI diffusion and distribution in the skin, consequently supporting the translation of Raman Confocal Imaging to industrial application for screening and identification of the next relevant candidates for cosmetic product development and optimization.
Data handling Data analysis was performed using Matlab (Mathworks, USA). Before statistical analysis, Raman spectra were subjected to linear baseline correction (in house rubber band with only 2 nodes)  [34]  then vector normalised. In line with previous analyses of human skin tissue sections  [11] , K-means clustering analysis was then used to analyze the spectral variation in spectral image of the tissue sections  [35]. It groups the spectra according to their similarity, forming clusters, each one representing regions of the image with identical molecular properties. The distribution of chemical similarity can then be visualized across the sample spectral image. The number of clusters (k) has to be determined a priori by the operator before initiation of the classification of the data set.
K centroids are defined, ideally as far as possible from each other, and then each point belonging to a data set is associated to the nearest centroid. When all the points have been associated with a centroid, the initial grouping is done. The second step consists of the calculation of new centroids as barycentres of the clusters resulting from the previous step. A new grouping is implemented between the same data points and the new centroids. These operations are repeated until convergence is reached and there is no further movement of the centroids. Finally, k clusters are determined, each containing the most similar spectra from the image. Ultimately, colors can be attributed to each cluster and false colors maps can be constructed to visualize the organization of the clusters in the original image.
[36]  Principal Component Analysis (PCA) is a multivariate analysis technique that is widely used to simplify a complex data set of multiple dimensions  [37]. It allows the reduction of the number of variables in a multidimensional dataset, although it retains most of the variation within the dataset. The other advantage of this method is the derivation of PC loadings which represent the variance of each variable (wavenumber) for a given PC. Analysis of the loading of a PC can give information about the source of the variability inside a dataset, derived from variations in the chemical components contributing to the spectra  [38]. In this work, PCA is used to either highlight the biochemical changes between skin layers identified by means of K-means clustering or intra-variability observed in spectra isolated from the stratum corneum.
Lysates were clarified by centrifugation, and equal amounts of total protein were incubated overnight at 4°C with anti-FLAG antibody immobilized on protein G Plus agarose beads. Beads were washed with lysis buffer, boiled in Laemmli buffer, and analyzed by Western blotting. Western blotting. Samples for our Western blotting analysis were separated on 10% or 4-to-12% bis-Tris SDS-PAGE gels (Invitrogen) and transferred to polyvinylidene difluoride membranes for 1 h at 100 V and 4°C. Blotting was performed as described elsewhere  (51). To quantify changes in tubulin levels during infection, the ratio of tubulin to HSP70 was obtained for each noninfected and infected sample. The data were then normalized to the results with the noninfected sample, which were set as 100%. Immunofluorescence. For our immunofluorescence analysis, HeLa cells were fixed with 4% paraformaldehyde in cytoskeleton buffer (10 mM morpholineethanesulfonic acid, 138 mM KCl, 3 mM MgCl 2 , 2 mM EGTA, 0.
Coverslips were then washed and mounted with ProLong Diamond antifade reagent (Invitrogen). Images were acquired using a Nikon TiE inverted fluorescence microscope with a 60ϫ oil immersion lens and Elements software (Nikon). Images were processed using ImageJ (NIH). To measure the length of the Golgi complex, z-stacks were acquired in 0. 3-m sections and deconvolved. Length measurements were acquired by tracing the Golgi complex of infected cells from maximum intensity projections to capture the Golgi complex in all planes via the Elements software (Nikon). A minimum of 100 cells per condition for each experiment was measured. ARF1-GTP binding assay. For the ARF1-GTP binding assay, HeLa cells were infected for 24 h with WT or CT813 KO Chlamydia strains. The cells were then lysed as described above.
ACKNOWLEDGMENTS We thank  J. Keen ,  L. Sigal ,  C. Snyder , and  L. Ma , as well as the members of the  Paumet laboratory , for their critical discussions. We are grateful to  Dave Mead  for the mass spectrometry analysis. J. W. and F. P. conceptualized the project; J. W. , M. M. W. , A. N. , C. A. D. , J. C. , T. H. , and F. P. designed the experiments; J. W. , M. M. W. , A. N. , C. A. D. , M. C. , C. M. S. C. , and F. P. performed the experiments; J. W. and F. P. wrote the original manuscript; J. W. , M. M. W. , A. N. , T. H. , J. C. , and F. P. reviewed and edited the manuscript; J. C. , T. H. , and F. P. acquired the project funding; F. P. supervised the project. This work was supported by grants  AI073486  and  AI116983  to F. P. and by the  Intramural Research Program  of the  NIAID/NIH  ( T.
QSPR model for determining pK a values In order to perform QSPR calculations for evaluating pK a values of the investigated cationic exchangers, two different training data sets were applied. In the rst part of the study, a training data set of 55 dissociation constants was used (see ESI, † data set I ¼ molecules from 1 to 55). The set of data was carefully selected from experimental data reported in literature by potentiometric titration in water. In particular, we paid attention to select pK a values determined under very close experimental conditions in terms of media, ionic strength, temperature, etc. This database and the corresponding references are reported in ESI. † The calculated molecular descriptors (1309 MDs) for these compounds were linearly correlated with the dissociation constants.
Controls were selected from the spouses or partners of preHD individuals or were gene-negative siblings, to ensure consistency of environments. For this study, we excluded participants who had manifest disease at baseline, were left handed or ambidextrous, or had poor quality diffusion-weighted imaging (DWI) data, as defined by visual quality control. With respect to missing data, 56 preHD and 65 controls had data at 3 time points, 28 premanifest and 24 controls had data at 2-time points, and 10 preHD and 9 controls had data at one time point. An Connections with the largest shortest weighted path length have a higher rate of degeneration and show significant (q < 0. 05) longitudinal change. Both cortico-striatal and interhemispheric connections showed significant (q < 0. 05) cross-sectional change, while neither intrahemispheric or intramodular connections showed significant (q < 0.
05) group differences. Red arrow indicates increasing path length with respect to connection type. Blue wedge indicates rate of degeneration: slow rate represented by thin wedge and fast rate represented by thick wedge. Full black arrow represents q < 0. 05; dashed black arrow represents P < 0. 05. LMER was used to account for missing data (see Statistics section), such that all data were included in the LMER analysis. See Supplemental Table  5  for baseline demographic information. For the rate of connection atrophy vs. shortest weighted path length (longitudinal) analysis, only preHD participants who had diffusion data from all 3 time points were included (56 preHD, 65 controls). See Supplemental Table  6  for demographic information of this cohort.
MRI Acquisition Data were acquired on 4 different 3T MRI scanners from 2 different manufacturers (Philips Achieva at Leiden and Vancouver and Siemens TIM Trio at London and Paris), both using a 12-channel head coil. T1-weighted image volumes were acquired using a 3-D MPRAGE acquisition sequence with the following imaging parameters: repetition time (RT) = 2,200 ms (Siemens [S])/ 7. 7 ms (Philips [P]), time of echo (TE) = 2. 2 ms (S)/3. 5 ms (P), fractional anisotropy (FA) = 10• (S)/8•(P), field of view (FOV) = 28 cm (S)/ 24 cm (P), matrix size 256 × 256 (S) / 224 × 224 (P), and sagittal slices 208 (S)/164 (P) to cover the entire brain with a slice thickness of 1. 0 mm with no gap. Diffusion-weighted images were acquired with 42 unique gradient directions (b = 1,000 sec/mm 2 ). Eight images with no diffusion weighting (b = 0 sec/mm 2 ) and one image with no diffusion weighting (b = 0 sec/mm 2 ) were acquired from the Siemens and Philips scanners, respectively.
Modular organization The cortex was split into distinct modules using the community Louvain algorithm  (13)  as implemented in the brain connectivity toolbox (BCT) (  54 ) version 2016-01-16. This was performed on a group connectivity matrix created by averaging connectivity matrices across all participants. As module assignment can vary between runs of the algorithm, the algorithm was run 1,000 times and the most common assignment chosen using a consensus approach, also implemented in BCT. We chose the default resolution parameter γ = 1, as this represents classic modularity. This resulted in a module partition number of 6. We also generated module partition numbers of 4 and 8 using γ = 0. 6 and γ = 1. 7, respectively, to ensure this parameter did not affect our key results (Supplemental Figure  1  and Supplemental Figure  2 ).
Statistics All statistical analysis was performed in MATLAB v8. 3. LMER was used as implemented in the MATLAB statistics and machine learning toolbox with the fitlme() function. An LMER was used, as it provides unbiased estimates under the assumption that the missing data is ignorable. LMER accounts for the dependence due to repeated measures, and our application was similar to a previous approach used in a longitudinal HD imaging study  (55). Suppose that Y ij is the connection strength for the i th participant ( i = 1,. , N) at the j th time point (j = 1,. , n i ), with time metric t ij = visit ij -1, so that t i1 = 0. Furthermore, group i is a dummy variable taking the value of 0 if a participant is in the control group and the value of 1 if preHD. Then the LMER model was shown as Equation 1 below: Y ij = α + βt ij + γ (group i ) + δ (group i ) (t ij ) + θX i + a i + b i t ij + e ij where Greek letters denote fixed effects; α is the control group mean at the first visit, β is the control group linear slope, γ is the mean difference among the preHD and control groups at the first visit (difference of intercepts), δ is the slope difference among the groups (rate of change difference), X i is the matrix of covariates (age, sex, site, education) with associated regression coefficient vector θ; a i and b i are random effects (random intercepts and slopes), and e ij is random error.
insight. jci. orghttps://doi. org/10. 1172/jci. insight. 92641insight. jci. orghttps://doi. org/10. 1172/jci. insight. 92641insight. jci. orghttps://doi. org/10. 1172/jci. insight. 92641Acknowledgments This study was funded by the  Wellcome Trust (GR, PMC)  ( 091593/Z/10/Z ,  103437/Z/13/Z ) and supported by the  National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre (BRC). Track-On HD  is funded by the  CHDI foundation , a notfor-profit organization dedicated to finding treatments for HD. See Supplemental Acknowledgments for Track-On HD details. Address correspondence to:  Sarah J. Tabrizi ,  UCL Huntington's Disease Centre, Department of Neurodegenerative Disease ,  UCL Institute of Neurology and National Hospital for Neurology and Neurosurgery, Box 104 ,  Queen Square , London  WC1N 3BG ,  United Kingdom.
Steinhof South of Steinhof, a 2 m deep trench was excavated close to the top of a molasse hill covered by till. According to  Ivy-Ochs et al. (2004) , who applied surface exposure dating on boulders at Steinhof, the Rhône Glacier reached the site during the global LGM and disappeared ∼ 24 ka. Seven discrete samples down to 190 cm were collected for the 10 Be depth profile (SH1 to SH7; Table  1 ). The sediment changes at 150 cm depth from a sandy loam with almost no pebbles, possibly a water lain till  (Dreimanis, 1979) , to a diamict  (Flint et al. , 1960a, b)  with unknown thickness but at least 400 cm. The decalcification depth was reached in a drill core at 360 cm depth. The hiatus expressed in the sediments is also confirmed in the XRF data and the grain size analysis (L. Wüthrich, unpublished data).
, 2015; Ruszkiczay-Rüdiger et al. , 2016). Constant denudation rates with depth indicate that the T eff = 1 λ + ( ρ ) • ε (2) is the attenuation length of neutrons (160 g cm -2 ). We also used the MATLAB code version 1. 2, published by  Hidy et al. (2010) , to calculate deposition ages, i. e. , the time when the glacier has left the area, denudation rates and inheritance for our sites. The code uses a Monte Carlo approach to find solutions for Eq. (  1 ). Apart from the measured 10 Be concentrations at specific depths, critical input parameters are the allowed age range (time, t), ranges for denudation rate (cm a -1 ) and inheritance (atoms g -1 ), as well as a denudation threshold. We used a reference production rate for neutrogenic spallation of 3. 93 atoms g -1 a -1 (Heyman, 2014) and the scaling model by  Lal (1991)  and  Stone (2000)  to calculate the production rate for each site.
Acknowledgements. We thank the  SNSF  for funding ( PZ00P2_131670 ,  PP00P2 150590 ). Marcel Bliedtner ,  Zsófia Ruszkiczay-Rüdiger ,  Imke Schäfer  and  Mareike Trauerstein  are thanked for proof reading and fruitful discussions. Gilles Rixhon  and an anonymous reviewer are thanked for their reviews.
Motors rotations are synchronized by means of an automation circuit (figure  7 ), depending on a motion controller LMC, so that, each motor starts the rotation at the same moment and the same velocity of the other ones. The synchronization program was accomplished by a specific software ''SoMachine'', associated to the controller LMC. In addition to this synchronization task, the controller ensures the communication with the different elements of the machine, such as: PC, the touch-screen (Human Machine Interface) and the different sensors used in measuring and adjusting the tests process. Two types of sensors were used in the machine: the first one is the tensile sensor, which measure the traction forces from 0 to 5N and the other one is position sensors used to adjust the starting position each The automatization principle of the experimental machine is presented in figure  7.