dataesr/scientific-paragraphs-categorization huggingface dataset:
■ ACKNOWLEDGMENTS The authors are grateful to  Prof. Peter J. Sadler  ( University of Warwick ) for the use the KiloArc and  Prof. Alison Rodger  ( University of Warwick ) for the use of the infrared spectrometer. The authors also thank  Prof. Timothy S. Zwier  ( Purdue University ) and  Dr. Tolga N. V. Karsili  ( Technische Universitaẗ Munchen ) for useful discussions. L. A. B. thanks the  Engineering and Physical Sciences Research Council (EPSRC)  for providing a studentship under Grant  EP/F500378/1  through the  Molecular Organisation and Assembly in Cells Doctoral Training Centre and the Centre for Scientific Computing at the University of Warwick  for providing computational resources. M. D. H. thanks the  University of Warwick  for an EPSRC studentship. S. E. G. thanks the  Warwick Institute of Advanced Study  for postdoctoral funding.
Participants All subjects were prospectively enrolled from 2011 to 2014 at our MS center. Written informed consent was obtained prior to participation. The main population of interest consisted of thirty-seven persons with CIS (PwCIS) enrolled prospectively after approval by the local institutional ethics review board (NCT01865357) between 2 to 6 months after a first clinical event compatible with a demyelinating inflammatory syndrome. At least two clinically silent lesions with 3 mm minimum diameter were needed for inclusion. One had to be cerebral (ovoid or periventricular), while the other could be located in spine or brain. Exclusion criteria: contraindications to MRI, presence of other neurologic, psychiatric or systemic diseases, steroid treatment within one month, starting or stopping antidepressants or anxiolytic treatments within 2 months of MRI and neuropsychological examination.
We pooled these data with data from a MS study (NCT01207856) to analyze patients with long lasting disease as a positive control. Thirty-two persons with MS (PwMS) diagnosed according to the 2005revised McDonald criteria  [20]  were included (27 relapsing-remitting, 3 secondary progressive and 2 primary progressive form of MS). Exclusion criteria were dementia (Mini Mental State Examination <27), other neurologic or psychiatric disorders, drug or alcohol abuse, relapse and/or steroid treatment within 2 months, or severe depression (Beck Depression Inventory >27). A total of seventy-six healthy control (HC) subjects, included as negative controls, were free of neurologic, psychiatric, or systemic diseases, and drug or alcohol abuse. Fifty-four subjects were tightly matched for age, sex and educational level to PwCIS, to calculate cognitive z-score (see below).
The impedance was kept below 5 kO. An electro-oculogram (EOG) was recorded to detect artefacts related to eye movements and blinking. The EEG and EOG datasets were digitized with a sampling rate of 512 Hz and recorded with EEProbe software (ANT Software BV). EEG analysis. The EEG datasets were analyzed with EEProbe software. The procedure was the same as that described in Bocquillon et al. [14]. The raw data waveforms were bandpass filtered by convolving them with a finite-impulse response filter and a Hamming window. The half-power cut-offs were 0. 1 and 30 Hz. EEG epochs that contained eye movements or blink artifacts were automatically detected, then manually classified as either blinks or eye movements and separately corrected with the EEProbe regression algorithm. Whenever the subject missed a target stimulus or responded to a distracter stimulus, the event was excluded from the EEG analysis.
The waveforms (analyzed from 100 ms pre-stimulus to 900 ms poststimulus) were averaged separately for the standard, distracter and target conditions. For each epoch, a baseline correction was performed by using data from 100 ms prior to the stimulus. The N200 peak was defined as the largest negative deflection in the standard, distracter and target stimuli waveforms within the 160-400 ms time window and was thus referred to as the standard-, distracter-and target-elicited N200, respectively. The N200 amplitude was defined as the voltage difference between the baseline and the largest negative peak in the analyzed time window. Latency was defined as the time between stimulus onset and the largest negative peak. Amplitude and latency measures were performed for the three midline electrodes (Fz, Cz and Pz).
swLORETA N2 source localization. Source localization for N2 was performed according to the swLORETA procedure described in our previous study of P3  [14]. The swLORETA solutions were computed with ASA software (ANT Software BV) for each time point within a 40 ms time window around the N2 peak (referred to as the "peak window") in each condition and each participant. We then calculated the mean value of the swLORETA analysis for all time points. The same calculation was performed within a 40 ms time window during the baseline period (-70 to -30 ms, referred to as the "baseline window"). The swLOR-ETA solutions were computed using a three-dimensional grid of points (or voxels) representing the signal's possible sources. Furthermore, solutions were restricted to the grey matter by selecting only voxels in which the grey matter probability was not equal to zero (based on the probabilistic brain tissue maps available from the Montreal Neurological Institute  [47] [48] [49] ).
5 kg/m 2 , stable throughout the growth period, physiological menstruations without oral contraceptives and a stated desire for weight gain. Fourteen normal weight controls (mean BMI between 19 and 25 kg/m 2 ) without any eating disorders were also evaluated. In CTs and controls, all data were collected during the follicular phase of cycle. None of the subjects had documented intense physical activity, chronic or congenital disease, and none of them were taking any medication. Preliminary estimation of physical activity with MONICA Optional Study of Physical Activity Questionnaire was performed in order to exclude subjects with intense physical activity  [17].
Subjects Seven French-born rhesus macaques (Macaca mulatta), aged 4-11 years, participated in the study: two male-female dyads paired in adulthood, unsuccessfully in one case (dyad 1, the two animals were housed side by side but not together due to the male's unpredictable bouts of aggressiveness), successfully in the other case (dyad 2, the two animals had been living together for 3 years at the start of the experiment), and a triad of same-age females living together since birth. The monkeys had free access to water and received normal daily food rations of fresh fruits and monkey chow (40-130 kcal/kg/day) after testing completion. All animals were familiarized with handling and testing procedures for 4 weeks before the present data were collected. Data from the female triad were partially presented in  Monfardini et al.
The findings were summarized in two ways. In the meta-analytic approach, heritability results across cohorts were normalized using a standard error (SE)weighted model to yield meta-analytical estimates of heritability. In the mega-analytic approach, all the data was shared and synthesized pedigree was used to directly estimate heritability  (Kochunov et al. , 2014). Here, we applied the ENIGMA-DTI protocol to HCP DTI data to report the whole-brain and regional estimates heritability of FA values in the HCP sample in voxel-wise and region-of-interest based tests. Then, we compared the global and regional heritability estimates in HCP to the joint-analytic estimates previously reported by ENIGMA-DTI. Finally, we took advantage of the high spatial resolution of HCP acquisition to study the heritability pattern of the white matter periphery, where the common 2 mm or larger resolution of standard DTI scans leads to artificial lowering of FA magnitude in regions of diverging fibers due to partial voxel averaging effects  (Basser et al.
Subjects ENIGMA-DTI processing of FA images and heritability analyses were performed in 481 (194/287 M/F) participants of the Human Connectome Project (HCP) for whom the scans and data were released in June 2014 (humanconnectome. org) after passing the HCP quality control and assurance standards  (Marcus et al. , 2013). The details of this release are available in the HCP reference manual 1. The participants in the HCP study were recruited from the Missouri Family and Twin Registry that includes individuals born in Missouri  (Van Essen et al. , 2013). All HCP participants are in young adult sibships of average size 3-4 that include an MZ or DZ twin pair. Subjects ranged in age from 22 to 36 years (29. 1±3. 5 years). This age range is chosen because it corresponds to the period after neurodevelopment is completed and before the onset of neurodegenerative changes.
Diffusion data collection and preprocessing Diffusion data was collected at Washington University St Louis using a customized Siemens Magnetom Connectome 3 Tesla scanner with a 100 mT/m maximum gradient strength and a 32 channel head coil. Details on the scanner, image acquisition and reconstruction are provided in  (Ugurbil et al. , 2013)  and (https://www. humanconnectome. org/documentation/ S500/HCP_S500_Release_Reference_Manual. pdf). Diffusion data were collected using a single-shot, single refocusing spin-echo, echo-planar imaging sequence with 1. 25 mm isotropic spatial resolution (TE/TR=89. 5/5520 ms, FOV=210×180 mm). Three gradient tables of 90 diffusion-weighted directions and six b=0 images each, were collected with right-to-left and left-to-right phase encoding polarities for each of the three diffusion weightings (b=1000b=2000, and 3000 s/mm 2 ).
ENIGMA-DTI processing ENIGMA-DTI protocols for extraction of tract-wise average FA values were used. These protocols are detailed elsewhere  (Jahanshad et al. , 2013)  and are available online http:// enigma. ini. usc. edu/protocols/dti-protocols/. Briefly, FA images from HCP subjects were nonlinearly registered to the ENIGMA-DTI target brain using FSL's FNIRT  (Jahanshad et al. , 2013). This target was created as a "minimal deformation target" based on images from the participating studies as previously described  (Jahanshad et al. , 2013). The data were then processed using FSL's tract-based spatial statistics (TBSS; http://fsl. fmrib. ox. ac. uk/fsl/ fslwiki/TBSS) analytic method  (Smith et al. , 2006)  modified to project individual FA values on the hand-segmented ENIGMA-DTI skeleton mask.
Heritability measurements: Analysis of additive genetic variance The variance components method, as implemented in the Sequential Oligogenic Linkage Analysis Routines (SOLAR)-Eclipse software package (http://www. nitrc. org/projects/ se_linux) was used for all individual cohort heritability estimations. In short, the algorithms in SOLAR employ maximum likelihood variance decomposition methods and are an extension of the strategy developed by  (Amos, 1994). The covariance matrix Ω for a pedigree of individuals is given by: (1) where σ g 2 is the genetic variance due to the additive genetic factors, Φ is the kinship matrix representing the pair-wise kinship coefficients among all individuals, σ e 2 is the variance due to individual-specific environmental effects, and I is an identity matrix (under the assumption that all environmental effects are uncorrelated among family members).
Inverse Gaussian transformation was also applied to ensure normality of the measurements. Outputs from SOLAR include the heritability value, the significance value (p), and the standard error for each trait (ROI or voxel). All heritability analyses were conducted with age, sex, age*sex, age 2 , and age 2 *sex included as covariates. Registered HCP users can replicate our analyses using the web version of SOLAR-Eclipse software (www. humanconnectome. org) Variation in heritability estimates in HCP vs. ENIGMA Meta-SE and mega-genetic joint-analytic heritability estimates from ENIGMA-DTI were compared to and evaluated as predictors of heritability estimates in HCP subjects. Specifically, we used a z-test to evaluate whether the heritability estimates for the HCP subjects fell within the confidence intervals for the estimates of heritability derived by meta and mega analysis pooling methods.
62; p<10 -10 , for meta-and mega-analysis estimates, respectively; Figure  5 ). Voxel-wise variations in heritability were tested as a function of FA magnitude, distance and their interaction (eq 3 and 4). FA and distance were significant predictors of voxelwise heritability values in both HCP and ENIGMA cohorts (Table  2 ). Higher heritability values corresponded to higher FA values (Figure  6 , top row) and voxels located near the center of the MNI array space (Figure  6 , bottom row). Together, these factors explained 25% of variability in heritability values in HCP subjects and 32% and 41% of variability in the meta-and mega-genetic estimates of heritability in the ENIGMA-DTI dataset, respectively. Testing of the interaction model (eq 4) demonstrated that FA x distance term was not significant (p=0.
The trends in the HCP and ENIGMA-DTI cohorts were similar but for one substantive difference: the interaction between FA and distance was significant in ENIGMA, but not so in HCP sample. Overall, our study demonstrated highly robust estimates of additive genetic variability in HCP data. The joint-analytic estimates of heritability derived by ENIGMA-DTI group were highly predictive of the variance in regional heritability estimates in the data collected by HCP. Together this suggests the consistency of additive genetic contribution to FA values. This posits FA as a promising phenotype for future gene discovery studies. Replication of our analyses and further genetic analyses in the HCP subjects can be performed using a web-version of SOLAR-Eclipse available at HCP web-based analysis portal.
, 2013; Brouwer et al. , 2012; Glahn et al. , 2013). The ethnic diversity in the HCP sample may also add shared environmental aspects of FA variance to the apparent genetic influence. Lastly, the higher quality of the HCP DTI data likely reduces the measurement error and thus contributes to higher heritability estimates. Further research will be needed to assess the specific contributions to high heritability from these three factors. That being said, the heritability estimates in HCP are compatible with those collected in cohorts with similar study design  (Kochunov et al. , 2014). Importantly, the joint estimates of heritability from the ENIGMA-DTI studies were predictive of the regional pattern of additive genetic contribution to FA values in the HCP subjects. This suggests that the regional pattern of additive genetic variance in FA values is similar across populations.
, 2013). Advanced, diffusion tensor-based spatial registration techniques have been advocated as an alternative approach to register DTI data  (Wang et al. , 2011)(Zhang and Arfanakis, 2013). Tensor-based alignment techniques such as those implemented in (http://dti-tk. sourceforge. net) use the similarity in voxel-wise diffusion tensors to drive multi-subject alignment. We studied if the use of this advanced warping approach might lead to high heritability estimates by repeating voxel-wise heritability analyses using the DTI-TK tensor-driven TBSS approach. This was executed using standard parameters and 1-mm isotropic resolution. DTI-TK uses the full tensor model for spatial alignment, and FA values are calculated at the final step. We observed that the tensor-based warping approach produced significantly (p<10 -6 ) higher FA values at the core (distance=10-40mm from center) and at the periphery of the brain (distance=40-80mm) (Figure  1S ).
However, the tensor-based warping produced significantly lower voxel-wise heritability estimates compared to the FA-warping approach (average h 2 =0. 20 vs. 0. 34, p<10 -10 ). Moreover, its voxel-wise heritability values showed a strong decline with distance (Figure  1S ) and FA magnitude explained 64% of the variance. Clearly, tensor-based registration led to higher average FA estimate, but it did not result in a better intersubject overlap especially in areas of more complex fiber geometry near the periphery of the brain. This tensor-based analysis was only performed in the HCP sample because additional research is needed to demonstrate the stability of the this registration techniques when aligning multi-site data collected using DTI protocols with variable spatial resolutions and number of directions.
Similar errors are also likely to be observed in the areas of high intersubject variability such as near periphery of the brain. Bach et al. offered several recommendations, including the use of a study-specific template and manual review and editing of the skeleton image. Both of these recommendations were implemented in ENIGMA-DTI protocol  (Jahanshad et al. , 2013). Overall, the manuscript affirms the validity of ENIGMA-DTI approach in HCP data collected with a highly advanced diffusion weighted imaging protocol. However, it is important to understand the methodological caveats. This study illuminated these limitations from the genetic imaging perspective and our findings can help to define the set of regional phenotypes that can be reliably extracted from multi-site data collected with diverse imaging protocols.
CONCLUSION The ENIGMA-DTI FA homogenization protocol was tested in the state-of-the-art data collected by the HCP. This research helps to define the genetic search space for future localization of risk factors that affect white matter integrity in behavioral, neurological, and neuropsychiatric disorders. Limiting genetic searches to the traits that show significant and replicable heritability will improve confidence in outcomes of these analyses and reduce the number of degrees of freedom. In agreement, we showed that both global and regional heritability estimates from pooled approaches were highly predictive of the heritability pattern in a new cohort derived using state of the art neuroimaging methods. We also demonstrated that genetic contribution is replicable and high for the core white matter areas and that environmental contributions are greater in the vicinity of the variable convolutions of cerebral cortex.
Acknowledgments This study was supported by  R01 EB015611  to PK,  R01 HD050735  to PT,  MH0708143  and  MH083824  grants to DCG and by  MH078111  and  MH59490  to JB. Additional support for algorithm development was provided by  NIH   R01  grants  EB008432 ,  EB008281 , and  EB007813  (to PT). JES is supported by a  Clinical Research Training Fellowship  from the  Wellcome Trust  ( 087727/Z/08/Z ). AMM is supported by a  NARSAD   Independent Investigator Award  and by a  Scottish Funding Council Senior Clinical Fellowship. This work was supported in part by a  Consortium grant  ( U54 EB020403 ) from the  NIH Institutes contributing  to the  Big Data to Knowledge (BD2K) Initiative , including the  NIBIB  and  NCI. Data were provided by the  Human Connectome Project ,  WU-Minn Consortium  (Principal Investigators:  David Van Essen  and  Kamil Ugurbil ;  1U54MH091657 ) funded by the 16  NIH Institutes  and Centers that support the  NIH Blueprint for Neuroscience Research ; and by the  McDonnell Center for Systems Neuroscience at Washington University.
A similar amount of each sample, or radiolabeled caffeine alone (positive control), was directly applied to a thin layer chromatography plate (Nano-SIL NH2/UV, Macherey-Nagel). The mobile phase used for the separation was composed of chloroform, dichloromethane and isopropanol (v/v/v 4:2:1). After migration, the plate was autoradiographed. The total amount of radiolabeled caffeine-derived metabolites was quantified by densitometry and normalized to non-metabolized caffeine using ImageJ (Software, NIH, Bethesda, MD, USA). Each experiment was conducted in triplicate for appropriate statistical analysis.
Statistical analyses For qPCR, transcript level ratios were compared between strains using the Relative Expression Software Tool (REST, REST-MCS beta software version 2) with 2000 iterations  [39]. For the radioactivity assay, the amount of caffeine metabolites was compared between control strains and transgenic or treated flies. Normal distribution and homoscedasticity of the variances were checked. In two-group comparisons, Student's t tests were performed for parametrically distributed data. When more than two groups were compared, ANOVA was performed for parametrically distributed data using R software.
Introduction: Attention deficit hyperactivity disorder (ADHD) is a neuropsychiatric pathology that has an important prevalence among young people and is difficult to diagnose. It is usually treated with methylphenidate, a psychostimulant with a mechanism of action similar to that of cocaine. Previous studies show that repeated use of psychostimulants during childhood or adolescence may sensitize subjects, making them more prone to later abuse of psychostimulant drugs such as cocaine and methamphetamine. Objective: To review experimental studies in non-human models (rodents and monkeys) treated with methylphenidate during infancy or adolescence and tested for reinforcing effects on psychostimulant drugs in adulthood. Method: Systematic collection of data was performed on four databases (Web of Knowledge, PsycARTICLE, PubMed and SciE-LO).
Systematic collection of data was performed in June In the conditioned place preference (CPP) paradigm, animals are administered a drug prior to being placed in one environment/context. In another session they are administered with a neutral substance (a vehicle injection) before being placed in an alternative environment. 8] [19]  Another recurrent behavioral paradigm is used to assess aversive properties of drugs. The conditioned taste aversion (CTA) task evaluates animals' tendency to reduce consumption of a usually preferred substance (e. g. , sucrose, saccharin, water). After several pairings of this substance with a specific drug, a reliable reduction in fluid intake is produced, thus conveying a learned association between the aversive effects of the drug and the taste of the substance.
2014 using the following electronic databases: Web of Knowledge (ISI), PsycARTICLE (APA), PubMed (MEDLINE) and SciELO (Scielo. org). Articles published between 2009 and 2014 were sampled using the following search strategy: (((Methylphenidate [Title]) OR (Ritalin [Title])) AND ((Animal [Title/Abstract]) OR (mice [Title/Abstract]).
Material and Methods Computations based on strictly local curve geometry were implemented to generate a whole set of single images of visual curves with variable symmetric curvature in the twodimensional image plane. Images of arcs, corresponding to lower and upper halves of ellipses, were derived mathematically through planar projection by affinity with circles (Figure  5 ). This computation permits generating curved lines in the 2D plane (using AUTOCAD or equivalent software) with consistent variations in 2D parameters (Figure  5 ) for sagitta, chordlength, and height-to-width ratio (ℎ/), an index which conveys spatial information relative to the visual area covered by a curve  [2, 3]. The experiments were conducted in accordance with the Declaration of Helsinki  (1964). Visual images for the experiments were generated in AUTOCAD.
ACKNOWLEDGMENTS Research carried out in RM laboratory is sponsored by the  Centre National de la Recherche Scientifique  and grants from the  Agence Nationale de la Recherche Scientifique , The  European Commission   FP7 Marie Curie Actions  grant no. 264508 , The  region Ile-de-France , The  Fondation Bettencourt Schueller and the charity France Parkinson.