dataesr/scientific-paragraphs-categorization huggingface dataset:
For all lesion experiments, a control period of at least 30 min was respected before electrophysiological data were collected, and the location and extent of lesions were verified by microscopic inspection after each experiment. Electrophysiological data analysis and statistics. For single-experiment analyses, event correlations were generated from the raw electrophysiological recordings by setting event detection thresholds just above resting activity before the onset of an episode of fictive locomotion during which all suprathreshold activity was transferred into the corresponding Spike2 event channel. Event correlations were used to evaluate the phase relationship between the activities of selected nerve pairs during fictive swimming, with synchronous activity corresponding to a central peak in the corresponding cross-correlogram, whereas recurrent rhythmic bursting was indicated by regular satellite peaks on either side of the maximum.
Correlation coefficients indicating the strength of coupling between the activities in nerve pairs were calculated in Matlab version 7. 1 (Mathworks). For multiple-experiment comparisons, the temporal relationships between discharges in the same nerve pairs in different preparations were assessed by circular phase analysis of pooled data using Oriana 2 software (Kovach Computing Services). The mean vector and its length r indicated the preferred phase and the strength of coupling, respectively. For nonuniform distributions (tested with the Rayleigh's uniformity test, Z), phase values were plotted as the grand mean of the individual means of relative burst onsets throughout individual locomotor episodes. The effects of specific lesions on phase relationships were evaluated by using the Watson-Williams F test to determine the equivalence of two mean vectors and the Mardia-Watson-Wheeler test to assess for differences in sample distributions.
25 with CsOH. Stimuli were generated and signals acquired using a Digidata 1320 digitizer (MDS/Axon Instr. ), with pClamp 8. 0 software (MDS/Axon Instr. ). After seal formation and cell membrane rupturing, capacitance currents were minimized using the amplifier circuitry and 75-80% series resistance compensation was routinely applied. The sampling frequency was 5 kHz for the ramp protocols and 10 kHz for the step protocols; signals were filtered at 1 kHz (voltage ramps) or 5 kHz (step). The recordings with voltage-clamp and space-clamp errors (i. e. the presence of unclamped action currents) were excluded from the analysis. The junction potential error was not corrected. I NaP was evoked using slow voltage ramps that depolarized the membrane from 270 to +20 mV, with a slope of 50 mV s 21 and a total duration of 1.
Data analysis The data were analyzed using pClamp8 (MDS-Axon Instr. ) and Origin 7. 5 (Origin Lab. ). Conductance-voltage (g-V) relationships (activation curves) were calculated from the currents recorded applying voltage ramps using the equation g = I Na /(V-E Na ), in which I Na is the recorded Na + current measured at potential V, and E Na the calculated equilibrium potential. The normalized activation curves were fit to Boltzmann relationships in the form G/G max = 1/{1+exp[(VK-V)/k]}, where G max is the maximal peak conductance, G the peak conductance at each test voltage, V K the voltage at which half-maximal activation is reached, and k the slope factor. The steady-state inactivation curves were fit to Boltzmann relationships in the form: I/I MAX = 1/{1+exp[(V K -V)/ k]}+b, where I/I MAX is the relative current, V K the voltage of halfmaximal inactivation, k the slope factor and b the baseline.
The development of inactivation was evaluated by fitting the data points with bi-exponential functions in the form y = y 0 + A 1 exp(t/t 1 ) + A 2 exp-(t/t 2 )+baseline. Simulation curves of inactivation kinetics were generated with tri-exponential functions, adding a time constant and imposing the values of the parameters; they were then fit with bi-exponential functions as for the experimental data. Dose response curves were fit with rectangular hyperbolas. Fits were achieved using the Levenberg -Marquardt algorithm with Origin 7. 5. The data are given as mean values 6 SEM, and were statistically analyzed using paired t-test or ANOVA (the logarithmic transformation was used when data were compared as ratios); non-parametric tests (Wilcoxon or Kruskal-Wallis) were also used for comparison and gave similar results.
Acknowledgements This work was funded by a  Marie Curie International Reintegration Grant  ( IRG 230976 , to DR). D. R. was supported by a  Ramon-Y-Cajal fellowship  from the  spansih Ministerio de Ciencia e Innovación  and the  Avenir program  from  INSERM. P. R. -O. was supported by a  Marie Curie International Incoming Fellowship  (IIF253873) and  CONACyT , México. Published: 8 July 2013.
Hamster Kiss1r amplicons were obtained using primers designed to frame a specific region of the Kiss1R cDNA based on the previously published rat sequence (AF115516, 328-638 bp; 5 CTGGGCGACTTCATGTGCAAGTT 3 and 5 TATAGGGCCAGCAGGTTGTAGAG 3 ). PCR amplified products of the predicted size (263-bp) were purified and ligated into the pCR2. 1 cloning vector (Invitrogen). Identity of the clone was confirmed by sequencing (AGOWA) and the obtained sequence was deposited in GenBank (accession number GQ872419). The Syrian hamster Kiss1r cloned sequence shares 94 and 92% identity with the corresponding sequence of the known Kiss1r genes of mice and rats, respectively. In situ hybridization with both sense and antisense [ 35 S]UTPlabeled Kiss1r riboprobes was performed on 20 µm thick frozen hamster brain sections containing the main part of the diencephalon.
Behavioral tests and video-oculography Animal housing. All mice were housed in individually ventilated cages (type "MICE"; Charles River) with a 12 h light/dark cycle (lights on from 7:00 A. M. to 7:00 P. M. ). Food and water were freely available to the animals. Experimental cohorts of n control ϭ 12 (including six wild-type, one Raldh1 ϩ/Ϫ , two Raldh3 ϩ/Ϫ , and three Raldh1 ϩ/Ϫ ;Raldh3 ϩ/Ϫ mice, which were not different among each other in all tested parameters and thus their data were pooled), n Raldh1Ϫ/Ϫ ϭ 11, n Raldh3Ϫ/Ϫ ϭ 7, and n Raldh1Ϫ/Ϫ;Raldh3Ϫ/Ϫ ϭ 7 were constituted from male and female mice, with which behavioral tests were performed between 12 and 20 weeks of age. With the exception of the open-field test and video-oculography, which were performed with a dedicated group of animals (see below and Results), all animals were tested in a battery of behavioral tests.
8 A). Once the yaw testing was completed, the table was tilted 15°offvertical axis with the mouse in a nose-down position. Off-vertical axis rotation responses were tested in the dark (constant velocity, 50°/s; 10 complete cycles) in randomized clockwise and counterclockwise directions. Eye-and head-position signals were sampled at 1 kHz, digitally recorded (CED power1401 MkII; Cambridge Electronics Design) with the Spike 2 software and later exported into MATLAB (MathWorks) programming software for offline analysis. Analysis procedures were similar to those reported previously (VOR and off-vertical axis rotation:  Beraneck et al. , 2012; OKR: Chevallier et al. , 2013). Semicircular canal time constants in response to velocity steps (tau) were extracted from the desaccaded horizontal slow-phase eye position.
The eye position, EHp(t), was fitted to the equation EHp(t) ϭ EHp max ϫ [1 Ϫ exp(Ϫt/tau)] using custom-made MATLAB routines based on the curve fitting toolbox "fit" function with a nonlinear least-square method. Statistical analyses. To evaluate potential interactions between Raldh1 and Raldh3 null mutations, two-way ANOVAs with Raldh1 and Raldh3 genotype as two independent variables and behavioral responses as dependent variables were performed. Post hoc statistical comparisons of behavioral performance in Raldh1 Ϫ/Ϫ and Raldh3 Ϫ/Ϫ mice were performed using the protected least significant difference test or Student's t test for two-group comparisons. Post hoc test results are indicated in the corresponding figures together with the number of animals used for each experiment. Analyses of turning/tilted head behavior and swim ability were performed using the 2 test.
Three-dimensional computer reconstructions of vestibular organs Three-dimensional (3D) reconstructions of the inner ear were generated from ϳ280 serial sections of E18. 5 wild-type and Raldh3 Ϫ/Ϫ fetuses. Images of serial sections were captured with a light microscope (Leica DMLB) equipped with a CoolSNAP digital camera and software. Sections were first aligned to correct xy misalignments using the "Linear Stack Alignment with SIFT" plugin of Stephan Saalfeld (Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany) available on Fiji (http://pacific. mpi-cbg. de/wiki/index. php/Fiji). Thereafter, 3D reconstructions were generated using Imaris (Bitplane). A volume rendering software (Amira from TGS) was used to visualize and rotate three-dimensional datasets. The surface of the dorsal semicircular canal cross-section was calculated with Fiji from 20 measurements obtained from three mutant and three control mice used for the 3D reconstructions.
Subjects This study was conducted in 20 healthy volunteer blood donors enrolled from a pool of volunteers set up by the General Clinical Center of University hospital of Amiens, France. All subjects gave their full written informed consent, and the study was approved by the University Hospital ethics committee (Comitede Protection des Personnes Nord-Ouest 2 ou CCP Nord-Ouest 2) (nu2011-A01449-32) and l'Agence Francaise de SecuriteSanitaire des Produits de Sante(AFSSAPS). Volunteers were examined by the same staff throughout the study. A questionnaire was used to collect data on each volunteer's medical history, smoking and drinking habits, and medication (previous and present). Body height and weight were measured using a stadiometer and a balance scale. BMI was calculated as weight/height2 (kg/m2).
Similarly, Kruskal-Wallis test was used to compare more than two independent samples. When the test was significant, post hoc comparisons were performed with Mann-Whitney test and p values were adjusted with the Holm method. Univariate and multivariate linear regression models were used to analyze factors associated with total and surface CaSR expression. Data obtained simultaneously for V1 and V2 (V1+V2) and for V2 and V3 (V2+V3) were pooled. The significance level was 5% for all analyses. The significance level was 20% for univariate linear regression models, and 5% for multivariate linear regression models. SAS software version 9. 2 (SAS Institute, Cary, NC) and R 2. 14. 1 software were used for all analyses.
Objectives: This article provides an overview of the Upper Limb International Spasticity (ULIS) programme, which aims to develop a common core dataset for evaluation of real-life practice and outcomes in the treatment of upper-limb spasticity with botulinum toxin A (BoNT-A). Here we present the study protocol for ULIS-II, a large, international cohort study, to describe the rationale and steps to ensure the validity of goal attainment scaling (GAS) as the primary outcome measure. Methods and analysis design: An international, multicentre, observational, prospective, before-andafter study, conducted at 84 centres in 22 countries across three continents.
To do this, however, we will need to build a consistent body of data that captures clinically important changes at an individual level and is of sufficient size and generalisability to interrogate for future answers to these critical questions. The challenge lies in how to engage clinicians across the globe, to engage in a single common approach to data collection. The Upper Limb International Spasticity (ULIS) study programme represents the first step towards this aim. This manuscript provides an overview of the programme and presents the rationale and protocol for the ULIS-II study. The study results for ULIS-II will be presented separately.
OVERVIEW OF THE ULIS PROGRAMME AND RATIONALE The ULIS programme consists of a series of international observational studies to describe current clinical practice in the application of BoNT-A in the management of upper limb spasticity. The ultimate aim is to work towards the development of a common core dataset for prospective systematic recording of longitudinal outcomes that could inform the development of a large international database of sufficient size and breadth to support future interrogation and subset analysis. A founding principle of establishing common datasets is to embed them as closely as possible in real-life current clinical practice. ▸ The first stage of the programme (ULIS-I)  34  was an international, cross-sectional survey, which was designed to document clinical practice across four continents with respect to treatment and outcome evaluation.
▸ The second stage (ULIS-II) (described here) is a large, before-and-after, prospective, observational cohort study to record goal attainment as a primary outcome following one cycle of BoNT-A. This has also served to develop expertise in GAS and refine an electronic case report form (e-CRF). ULIS-II has recently completed recruitment and is now in the process of analysis. ▸ Following further refinement of the dataset and tools, a third stage is planned to expand the cohort and to capture the broader benefits of treatment in a fully generalisable sample recorded longitudinally over several cycles of treatment. This is currently in the planning and preinvestigation phase. How ULIS-I informed the rationale for ULIS-II ULIS-I was an international, cross-sectional, noninterventional survey to document (from a review of current practice and reported intentions) the clinical profiles, treatment goals and reported outcome evaluation in consecutive adults attending treatment with BoNT-A for upper limb spasticity.
Selection of contributing centres Contributing centres were rigorously selected on the basis that they: ▸ Demonstrated a reasonably high and consistent level of data recording and outcome measurement as part of their routine clinical practice. ▸ Routinely collected at least one standardised measure of spasticity (Ashworth scale or Tardieu scale). ▸ Were formally trained in the use of GAS prior to recruitment. Training in SMART goal setting and the use of GAS In preparation for the ULIS-II study, a comprehensive GAS training programme was carried out across all participating centres. This programme not only educated clinicians who were unfamiliar with the use of GAS but also formed an essential part of the validation process for the use of GAS in ULIS-II. First, a common training programme was established with a set of training tools, including: ▸ The practical guide to GAS, outlining the GAS-light method described previously  28  -A set of standard training slides in the form of a Microsoft PowerPoint presentation.
Development of the e-CRF A further purpose of ULIS-II was to develop and refine the e-CRF for capturing a standardised dataset. In ULIS-I, we identified the most commonly used approaches to record assessment, treatment and outcome evaluation. Learning from this experience, we addressed ways of reducing the information and making it understandable by investigators in all countries. This was achieved through small international group workshop discussions with key investigators (including authors LTS, KF and JJ), followed by circulation and feedback on the draft (case report form, prior to the start of development of the electronic version). The e-CRF was presented in one language only (English) to avoid introducing variance through translation. Investigators therefore needed to be adequately proficient in the English language to complete the form, although goal statements could be completed in To ease passive upper body dressing (<25% assistance) 1 month after injection To improve ease of dressing upper limb Improve carry angle from 25°to 0°when walking 1 month after injection Elbow extension To reduce upper limb pain during rest and passive range of motion (<4/10 on VAS) 1 month after injection To improve pain To relieve thumb in palm and ease nail clipping (taking less than 20 min) 1 month after injection Easier thumb and finger extensions Sitting at the table, to grip fork and spoon to move them to mouth and eat 1 month after injection To improve grasp and release function of the hand SMART, specific, measurable, achievable, realistic and timed; GAS, goal attainment scaling; VAS, visual analogue scale.
Goal quality ratings were derived from the WHO ICF domain rating (A=4, A/B=3, B=2 and C=1) and the SMART rating ('++'=4, '+'=3, '+/-'=2 and '-'=1). Each centre was assigned two goal quality ratings and the graph shows the medians for each participating country. the native language. Site monitors provided support for any interpretational queries. The e-CRF was posted on the internet to facilitate access to all participating countries. It was developed on a customised software that supported electronic and interactive data collection, as well as online edit checks to ensure data accuracy and quality. Wherever possible, it included dropdown value lists and check-box options to minimise ambiguity, and it also provided automated calculation of the GAS T-score.
Separation of time 1 and 2 data In this before-and-after study, time 1 acts as a 'within patient' control. GAS rating requires the investigator to be able to view the goals set at time 1, so it was important to maintain the independence of time 1 and time 2 data as far as possible. The e-CRF software did not have the facility to lock the time 1 data prior to completion of the follow-up form, which would have prevented the opportunity for retrospective changes. However, it did have an inbuilt tracking facility. Site monitors were responsible for reviewing the tracking log to ensure that no post hoc changes were made that could have influenced outcome evaluation.
STRENGTHS AND LIMITATIONS 4] [25] [26]  It will expand our understanding of the types of goals that are and are not likely to be achieved following treatment with BoNT-A. Importantly, it sets in train a methodology that is practical for use in routine clinical practice, which will be used in future studies to expand the clinical dataset to one of sufficient size to interrogate for answers to the important questions including: 1. The identification and selection of patients most likely to benefit from treatment. 2. The most effective approaches to muscle selection, injection technique, etc. 3. The most useful approaches to outcome measurement. Goal setting is a complex process, which requires skill and experience on the part of investigators-both to coin the SMART goal description and also to be able to predict the likely outcome of the intervention and its timescale.
SUMMARY The importance of the ULIS programme lies in its staged approach to development, which both educates participating centres and ensures that the final core dataset will capture the cultural diversity of worldwide clinical practices in which it will be used. ULIS-II is not the final step, but marks an important phase in the development of the programme. Despite the recognised limitations at this stage of development, ULIS-II will provide a unique and important set of information regarding the treatment and outcomes from BoNT-A in real-life management of poststroke upper limb spasticity worldwide. Through the process described above, we have developed a methodology that will not only help to ensure credibility of results from ULIS-II, but will also underpin future studies and inform other clinical trials and cohort studies in this context.
Acknowledgements The authors would like to also acknowledge the editorial assistance of  Suzanne Patel  at  Ogilvy Healthworld  in the preparation of the manuscript. Contributors All authors were involved in the planning of the study. LTS was the lead investigator and wrote the first draft of this manuscript. LTS, KF and JJ were involved in data collection and assembly of data for goal validation, manuscript review and critique, and the final approval of the manuscript. BZ and PM were involved in the concept and design, data analysis, manuscript writing, manuscript review and critique and final approval of the manuscript. Funding Ipsen Pharma  provided financial support for this study. Financial support for manuscript preparation was also provided through the  Dunhill Medical Trust. Competing interests LTS, KF and JJ all received honoraria and conference attendance fees from  Ipsen  for the undertaking of this research.
The neocortical sheet composes the global anatomical model together with the amygdalo-hippocampal complex and several central grey nuclei and related structures (putamen, thalamus, reticular perithalamic nucleus (RPN), lateral geniculate nucleus (LGN) and external pallidum (EGP)). The model pipeline creation is based on the works of Chupin et al. [29]  and Yelnik et al. [30]  and uses the Brainvisa software  [31]  http:// brainvisa. info/. The electrophysiological properties in the model are CDs distributed at each location defined by the global anatomical model. As usual, neocortical source orientations are constrained to the local normal of the cortical mantle at each vertex location of the gray-white matter interface. Central regions of the neocortical tessellation that correspond to the corpus callosum and residual brainstem parts from MRI segmentation are manually removed from the global source space.
As mentioned at the beginning of the simulations setup, seven healthy volunteers participated in this study. The MEG session was composed of a block-designed EO/EC paradigm, with each block lasting for 30 s, for a total duration of 5 minutes per condition. MEG signals are recorded on a 151-channel CTF whole-head system, at a 1250 Hz sampling rate. The data are first band-pass filtered within the individual alpha band of each subject. For each subject, distributed source imaging is performed using the DBA model and the three inverse operators. Student t-tests are used to detect modulations of source amplitudes by contrasting the eyes opened vs. eyes closed conditions. All of the source maps are registered and normalized to the MNI reference template for group statistical analysis. Group average source maps are then thresholded at p,0.
The results are shown for the three inverse methods, wMNE (1 st column), sLORETA (2 nd column) and dSPM (3 rd column). Note that the colorbar does not start from zero and that the structures sizes are modified to make the sources more visible. See Figure  1B  for a medial view of the relative position of the structures. B. Histograms of DLE g (x-axis in cm) distributions for all sizes of hippocampus patches (1 to 5 cm 2 ). Note that the y-axes are normalized to be comparable. doi:10. 1371/journal. pone. 0059856. g005 Causal Modeling  [53]. Nevertheless, the increase in sensor numbers combining numerous gradiometers and magnetometers from the newest MEG systems accompanied by good hardware and software noise subtraction techniques could allow us to expect greater sensitivity to subcortical generators.
These approaches could be adapted to volume-based structures such as the amygdala or thalamus (mainly composed of non-oriented cells). Finally, other parameters, such as the number of subjects or experimental paradigms, could also be evaluated. In our experimental protocol, a large amount of data are recorded to contrast Eyes opened/Eyes closed conditions, in which cortico-thalamic modulations are strong enough to be detected. These results encourage us in our ability to detect subcortical activity, especially for regions that are assumed to contribute very weakly to MEG. However, the thalamic activations are found but are not accurate in the posterior parts of the thalamus, which is expected because of previous studies  [47]. This result showed the limited spatial resolution that is sustainable by MEG in these very deep structures.