dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments Acknowledgments The Interaction and Knowledge project was partially supported by the  Instituto de Inovação Educacional , medida  SIQE 2  (project  n°. 7/96 ) in 1996/1997 and  1997/1998 , and by the  Centro de Investigação em Educação da Faculdade de Ciências da Universidade de Lisboa  since  1996. The  MuM -Project  (  Mathematics learning  under conditions of multilingualism ) at  TU Dortmund University  was partially funded by the  BMBF , grant  01JG1067. We thank the teachers, students, and colleagues who helped to conduct the different projects underlying this chapter. Acknowledgments RB's data collection was funded by the  Social Science and Humanities Research Council of Canada. RB is grateful to  Adil Dsousa  and  Élysée Cadet  for their assistance. All four authors are grateful to the participants in their research projects.
Participants Data for our study was collected between September 2012 and June 2014, we only included patients that respected the following criteria (i) female patients, (ii) diagnosed with AN or BN and (iii) with a Body Shape Questionnaire (BSQ) score lower than or equal to 110, or above 140. A total of 123 patients out of 234 recruits were included in the study. Fifty-three (53) had a score on the BSQ lower than or equal to 110, whereas 70 had a score on the BSQ above 140. The flow chart of patient selection is presented in Fig  1.
Measures Since this study was preliminary and exploratory in nature, a large range of variables was retained, all were useful in characterizing an ED and the psychopathology of the patients. Socio-demographic data. The data collected concerned age, sex, marital status and professional status. Eating disorder characteristics. Structured clinical interview:A standardized assessment of ED, specifically developed for our cohort, was performed by qualified and experienced staff members. Patients were asked about the history of their EDs (duration of ED, lowest body mass index (BMI), current ED (type of ED, current BMI), presence of associated behavior (vomiting, use of laxatives or appetite suppressants, problematic exercise, potomania, self-mutilation), personal history of physical and/or sexual abuse and family history of addictive behavior.
Variables to be included in the final models were selected using a p < 0. 05 criterion. The corresponding odds ratio and associated 95% confidence interval were estimated. Discrimination of the final logistic models, which describes the models ability to differentiate between "low" versus "high" BSQ scores, was assessed using the area under the Receiver Operating Characteristic (ROC) curve and the goodness-of-fit of the model was assessed using the Hosmer-Lemeshow test. The statistical analysis was carried out with SAS 9. 1 and R statistical software (SAS Institute, Inc. ). The conditions of validity were verified for all of the tests and models.
etiology of the onset and clinical course of GTS, investigate the neurobiological underpinnings of GTS and related disorders, translate research findings into clinical applications, and establish a pan-European infrastructure for the study of GTS. This includes the challenges of (i) assembling a large genetic database for the evaluation of the genetic architecture with high statistical power; (ii) exploring the role of gene-environment interactions including the effects of epigenetic phenomena; (iii) employing endophenotype-based approaches to understand the shared etiology between GTS, OCD, and ADHD; (iv) establishing a developmental animal model for GTS; (v) gaining new insights into the neurobiological mechanisms of GTS via cross-sectional and longitudinal neuroimaging studies; and (vi) partaking in outreach activities including the dissemination of scientific knowledge about GTS to the public.
GENETICS, EPIGENETICS, AND GENE EXPRESSION The first Genome-wide Association Study (GWAS) to investigate the role of single nucleotide polymorphisms (SNPs) in GTS did not manage to identify SNPs that meet the genome-wide significance level for association to GTS, however, four additional GWAS for GTS are currently underway [coordinated by the Tourette Association International Consortium for Genetics (TSAICG), European Multicentre Tics in Children Studies (EMTICS), Netherlands twin register (NTR) and deCODE] and the future meta-analysis of these datasets is expected to provide important insights into the etiology of the disorder (Figure  1 ;  Paschou, 2013; Scharf et al. , 2013). Furthermore, in recent years, four independent GTS cohorts have been examined, studying the role of Copy Number Variants (CNVs) in GTS  (Sundaram et al.
This image was produced (by JW) with Ingenuity pathway analysis software and shows how the proteins encoded by the candidate genes reported to be associated with GTS are linked with each other. Please see legend for description of what each symbol and color represents. ADRA1A, adrenoceptor alpha 1A; ADRA2A, adrenoceptor alpha 2A; ADRA2C, adrenoceptor alpha 2C; BTBD9, BTB (POZ) domain containing 9; CaMKII, calcium/calmodulin-dependent protein kinase II; CCT8, chaperonin containing TCP1, subunit 8 (theta); CNTNAP2, contactin-associated protein-like 2; COMT, catechol-O-methyltransferase; CTNNA3, catenin (cadherin-associated protein), alpha 3; CTTNBP2, contactin binding protein 2; CUL3, cullin 3; DBH, dopamine beta-hydroxylase (dopamine beta-monooxygenase); DLGAP3, discs; large (Drosophila) homolog-associated protein 3; DRD1, dopamine receptor D1, DRD2, dopamine receptor D2, DRD3, dopamine receptor D3, DRD4, dopamine receptor D4, ERK 1/2, extracellular signal-regulated kinases 1/2; HDC, histidine decarboxylase, HNF4A, hepatocyte nuclear factor 4 alpha; HTR2A, 5-hydroxytryptamine (serotonin) receptor 2A; G protein-coupled; HTR2C, 5-hydroxytryptamine (serotonin) receptor 2C; G protein-coupled; IL1RN, interleukin 1 receptor antagonist; KCNE1, potassium channel voltage gated subfamily E regulatory beta subunit 1; KCNE2, potassium channel, voltage gated subfamily E regulatory beta subunit 2; LHX6, LIM homeobox 6; MAOA, monoamine oxidase A; MRPL21, mitochondrial ribosomal protein L21; MRPL3, mitochondrial ribosomal protein L3; MYC, v-myc avian myelocytomatosis viral oncogene homolog; NLGN4X, neuroligin 4, X-linked; NRXN1, neurexin 1; OFCC1, orofacial cleft 1 candidate 1; PPARA, peroxisome proliferator-activated receptor alpha; RCAN1, regulator of calcineurin 1; PSEN1/2, presenilin 1/2; SLC1A3, solute carrier family 1 (glial high affinity glutamate transporter), member 3; SLC6A3, solute carrier family 6 (neurotransmitter transporter); member 3; SLC6A4, solute carrier family 6 (neurotransmitter transporter), member 4, SLITRK1, SLIT, and NTRK-like family, member 1; TPH2, tryptophan hydroxylase 2; YWHAB, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, beta.
Project 2 Investigation of the Role of CNVs as Genetic Susceptibility Factors Involved in the Pathogenesis of GTS and Co-morbid Disorders (Rayan Houssari, Juan Ignacio Rodriguez Arranz, Mehar Arumilli, and Zeynep Tümer, Kennedy Center, Copenhagen University Hospital, Rigshospitalet) The aim of this project is to untangle novel molecular genetic mechanisms underlying GTS and related disorders, by using bioinformatic network analysis of CNVs combined with phenotype data of 261 GTS-patients residing in Denmark. All the patients were assessed by experienced clinicians at the Tourette Clinic, Copenhagen University Hospital for GTS, OCD, and ADHD using validated diagnostic instruments  (Mol Debes et al. , 2008). Furthermore, information about other family members was collected through interviews revealing approximately 77% of the families to be multiplex with at least two family members affected by GTS or one of the common comorbidities.
Through collaboration with the FP7-HEALTH project EMTICS, a special focus is placed on group A streptococcal infections and stress as a possible trigger for tic onset. EMTICS also offers us access to genome-wide genotype data of 1000 patients (followed up on a monthly basis for 12 months) as well as gene expression data on 200 GTS patients that are followed up for tic exacerbation and remission in an attempt to correlate with environmental factors. Gene-expression and correlation with environmental triggers is also investigated in a cohort of first degree relatives of patients with GTS that develop tic symptomatology within a 3-year follow-up period. Furthermore, the first ever epigenome-wide association study for tics, analysing data from the NTR, has been carried out  [55]. This study comprised the largest epigenetic data collection so far undertaken (411,469 autosomal methylation sites, assessed in 1678 individuals).
, 2015) , as mentioned in project 3. Project 5 Integrated Genetic Networks Underlying Comorbid GTS and OCD (Joanna Widomska, Jan Buitelaar, Geert Poelmans, and Jeffrey Glennon, Radboud University Medical Center, Nijmegen) The aim of this project is to determine the extent of "genetic overlap" in terms of shared underlying gene pathways and molecular signaling cascades between GTS and OCD and to provide further insights into how aberrant processes underlie these genetically related, clinically overlapping but still distinct neurodevelopmental disorders. Combining literature search approaches with diverse bioinformatics analytic tools (e. g. , Ingenuity Pathway Analysis), top candidate genes emerging from GWASs of GTS  (Scharf et al. , 2013) , OCD  (Stewart et al. , 2013; Mattheisen et al. , 2015) , and corroborating genetic evidence including data from recurrent and "genome-wide" CNV studies, candidate gene studies, miRNA expression data, animal models, and gene expression studies are selected and evaluated.
Boomsma and Danielle Cath, Utrecht University and Vu University Medical Center) This study uses data that has been gathered by the NTR over the last 25 years, on twins, and family members (n = 16,896 individuals with SNP, epigenetic and expression data in subsamples), including a range of phenotypic data from questionnaires and genetic data. Structure equation model fitting procedures are used to model the phenotypic resemblance between family members and the relative contribution of genetic and environmental factors to variation and covariation among traits. Also, genome-wide association methodologies are being used to disentangle the genetic architecture underlying the etiology of GTS traits by estimating SNP heritability and polygenic risk scores for example. Project 7 Developing Algorithmic Prediction Models for GTS and Related Disorders (John Alexander and Peristera Paschou, Democritus University of Thrace) With the continuous development of state of the art technologies for generating large amounts of genomic data, there is a need to develop new methodologies in order to identify promising SNPs, and candidate genes for further experimental validation.
Using genetic data available for GTS and related disorders, this project develops, and applies new methodologies to scan high throughput genomic data (Genome Wide Association data, next generation sequence data, and microarrays). For example, using meta-analysis data comprised of 1285 GTS cases, and 4964 controls ancestry-matched to the GTS sample from the first GWAS  (Scharf et al. , 2013) , we perform pathway, proteinprotein interaction and gene-ontology analysis in order to dissect the molecular mechanisms underlying GTS. Furthermore, using novel bioinformatics tools for SNP based and gene based functional analysis, we perform candidate gene prioritization, gene set enrichment, and tissue enrichment analysis. We also construct functional interaction networks using combined information from the enriched functional and pathway results.
NEUROIMAGING Our three (human) neuroimaging projects are highly complementary with similar techniques used across all sites so as to allow for the cross-comparison of findings with limited methodological confounding factors. Projects 11 and 12 even pool data for certain comparisons. Each project utilizes MRS to evaluate the role of the glutamatergic system; T1-weighted structural magnetic resonance imaging (MRI) to examine structural brain differences; functional MRI (fMRI; resting state and task specific) data to interrogate the functional coupling between cognitive, limbic, and sensory-motor CSTC networks; and diffusion-weighted MRI (dMRI) data to inspect the structural connectivity. Each project does, however, differ in the populations under investigation and aims to address different unknown areas regarding GTS neurobiology.
Project 10 Structural and Functional Neural Correlates of Pediatric GTS and ADHD (Natalie Forde, Jan Buitelaar, and Pieter Hoekstra, University Medical Center Groningen) Few neuroimaging studies of GTS have investigated brain structure and function in children with even fewer longitudinal studies tracking the development of GTS  (Ganos et al. , 2013). Furthermore, the similarities and differences between ADHD and GTS have yet to be explicitly tested  (Plessen et al. , 2007). For this study structural, functional (resting state and task-dependent stop-signal and reward tasks) and dMRI data are acquired alongside MRS for glutamate and glutamine concentrations, neuropsychological, and phenotypic data from 180 children between 8-12 years of age (60 GTS with or without ADHD, 60 ADHD only, and 60 healthy controls).
Common and unique neural correlates of GTS and ADHD are elucidated. Furthermore genetic data is acquired and will be analyzed as part of the EUfunded TACTICs project. Lastly a 3 year follow-up has been granted where the same battery of tests, including MRI, will be undertaken to allow the course of GTS and ADHD to be investigated. The neural correlates of GTS and OCD have scarcely been compared and contrasted despite the high rate of co-occurrence  (Freeman et al. , 2000). This project is to investigate how altered glutamatergic function (as measured with MRS) is related to changes in structure (T1-and diffusion-weighted) and function (resting state and task-dependent stop-signal task) of the CSTC circuits in adult patients with GTS and OCD in comparison to healthy individuals. A similar range of neuroimaging, neuropsychological and phenotypic data to the above is acquired from adults with GTS, OCD and healthy controls (n = 20 per group).
The participants with OCD as well as the controls have been chosen from a previous local OCD study while those with GTS are newly recruited. Genetic data is collected to contribute to genetic analysis within other projects of the network and to perform imaging-genetic analyses. Neuroimaging and behavioral data are acquired from up to 40 adult patients before and after treatment with the pharmacological agent aripiprazole, an atypical antipsychotic agent which is commonly used to treat GTS. At the elemental level, we use Quantitative Susceptibility Mapping (QSM) techniques to investigate whether patients exhibit an altered distribution of iron concentrations within basal ganglia nuclei in comparison to 40 healthy controls. At the neurochemical level, we investigate the role of the glutamatergic system within corticostriatal regions using MRS at baseline and following treatment.
further acknowledge support by the European Union Seventh Framework Programmes  [TACTICS (FP7/2007 -2013 ), Grant Agr. No. 278948 and EMTICS (FP7/2007 -2013), Grant Agr. No. 278367]. CB was supported by the Merit-prize scholarship of Semmelweis University and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences BO/00987/16/5.
Study design and characteristics of participants One hundred subjects enrolled in ABOS (Biological Atlas of Severe Obesity, ClinicalGov NCT01129297) were included in a previous study which evaluated circulating kynurenines in obese women  [7]. The present work aims at determining tryptophan and kynurenine metabolite concentrations one year after bariatric surgery. After one year follow-up, data for ninety one participants were available (Fig  2 ). The selection criteria were previously described  [7]. Briefly, since circulating tryptophan and kynurenine metabolite concentrations were shown to be significantly different between men and women  [13]  and in order to avoid gender effect, we studied only women, which are more prone to undergo bariatric surgery. Participants had severe obesity (BMI = 46,3 ±6,3 kg/m 2 ) and met the criteria for bariatric surgery, as previously described  [6].
5 mmol/L and 2-h glucose < 7. 7 mmol/L and for type 2 diabetes: FG 7 mmol/L or 2-h glucose 11. 1 mmol/L. At inclusion, cases with type 2 diabetes were matched with normoglycemic controls on age and BMI. Patients with missing follow-up data were excluded from the final analysis. Overall, 47 women were diabetic and 44 were normoglycemic at inclusion and no significant difference for age and BMI between the two groups of remaining patients was observed (Table  1 ). The choice between laparoscopic adjustable gastric banding (AGB)  [12]  or Roux-en-Y gastric bypass (RYGB)  [14]  was left to the surgical candidates after having been informed about the risks and benefits of each procedure according to contemporary knowledge. 24 individuals (16 normoglycemic and 8 diabetic) chose AGB and 67 individuals (28 normoglycemic and 39 diabetic) chose RYGB.
Picolinic acid and quinolinic acid were simultaneously measured using gas chromatography-tandem mass spectrometry (GC-MS/MS), as previously described  [7]. Briefly, samples were mixed with internal standards (QUIN-D3 and PIC-D4, 2 μM) and methanol for protein precipitation. Samples were dried and then heated to allow derivatization with pentafluoropropionic anhydride (PFPA, Sigma Aldrich, Saint-Quentin Fallavier, France) and hexafluoroisopropanol (HFIP, Sigma Aldrich). The obtained derivatives were dried and dissolved in iso-octane and finally injected onto the GC-MS/MS equipment (Agilent 7890 coupled to Waters Quattro Micro GC, RAB293). Chromalinks software (Waters™) was used for data acquisition and processing. A linear mixed model was used to assess the association between KPm concentrations and the concentrations of ultrasensitive C-reactive protein (usCRP), an inflammatory marker.
This work was supported by grants from the  CNRS  (http://www. cnrs. fr/); the  "Société Francophone du Diabète "(http://www. sfdiabete. org/)," European Genomic Institute for Diabetes" (E. G. I. D. ,  ANR-10-LABX-46 ; http://www. egid. fr)and  European Commission  (http://ec. europa. eu). MF is supported by a doctoral grant from the " Conseil Régional du Nord-Pas de Calais " (http://www. nordpasdecalais. fr)and from the  "CHRU de Lille " (http://www. chru-lille. fr/). GJG is supported by the  Australian Research Council  ( ARCF20100397 )(http://www. arc. gov. au/).
[Ca 2+ ] i measurements using CCD video-imaging system Video imaging of [Ca 2+ ] i was performed using an Axio Observer D1 (Zeiss) inverted microscope equipped with filters for monitoring GFP and RFP fluorescence, and epifluorescence oil immersion objectives (Plan Neofluar 100 × 1. 30, FLUAR 40X/1. 3 oil and FLUOR 20 × 0. 75, Zeiss). This allowed us to visualize and identity the SON neurones obtained from AVP-eGFP and OT-mRFP1expressing animals. The excitation light from a Xenon lamp passed through a Lambda D4 ultra-fast wavelength switching system (Sutter Instruments) with a maximum switching frequency of 500 Hz. The fluorescence intensity was detected by using a cooled CCD camera (AxioCam MRm, Zeiss) and the whole system was controlled by Zeiss ZEN Imaging software (2012-SP2/AxioVision SE64 Rel.
Data pre-processing Each [Ca 2+ ] i trace was first classified as oscillating or nonoscillating. Changes in [Ca 2+ ] i with an amplitude of at least 30 nM that occurred within 120 s (or faster) were considered to be "Ca 2+ events", and traces or parts of traces in which such events occurred repeatedly were considered "[Ca 2+ ] i oscillations". The threshold of 30 nM was used as a value sufficient for excluding the interference of the noise inherent in the signal. Only [Ca 2+ ] i traces with sustained oscillations lasting for at least 10 min were included in further analysis. Traces with strong trend or obvious artefacts were removed from the data set. To reduce noise, all data were filtered by a 2nd-order Butterworth low-pass filter with a cut-off frequency of 0. 5 Hz (with filter coefficients estimated by the MATLAB function butter and filtration performed by filtfilt).
MATLAB 2015a and its Statistics, Machine Learning, and Signal Processing toolboxes were employed in all numerical procedures. Although ratiometric measurements using Fura-2 reduce the effect of photo bleaching, some trend of it exists, especially in longer-lasting experiments. This is because signals from 340 nm and 380 nm do not bleach equally and the ratio is rising even without a change in [Ca 2+ ] i. We estimated this trend by averaging 55 traces with a duration of more than 15 min and fitting the averaged trace with a linear function of time. This gave a trend expressed as 0. 011 nM/s (or; 0. 66 nM/min). This increase was then subtracted from all individual traces.
Data analysis and statistical evaluation Four basic parameters were computed for each individual trace or its segment: the [Ca 2+ ] i baseline, the mean [Ca 2+ ] i level, the standard deviation of the trace, and the skewness of the [Ca 2+ ] i values. These parameters were computed separately for each trace segment corresponding to a defined physiological condition (for example, application of AVP). Only trace segments longer than 300 s were considered. An example of such evaluation is shown in Fig. 1. Differences between the trace segments were evaluated based on the four trace parameters defined above. For each parameter, the difference of its value before and after drug application was calculated for each cell trace (see example in Fig. 1 ). This difference was then averaged over the cells in the given group, and the paired t-test was used to determine if the difference was statistically significant.
The p-values reported in Results represent the significance level for rejecting the null hypothesis of zero difference. The MATLAB function t-test was used. In figures displaying data fitted by a linear approximation, leastsquares fitting were performed using the MATLAB function polyfit. As a measure of goodness of the linear fit we use the coefficient of determination R 2 calculated as R 2 = 1 - N k=1 c k -c k 2 N k=1 (c k -c) 2 , where c k denotes the measured [Ca 2+ ] i values and c k the values estimated by the linear approximation. In all [Ca 2+ ] i trace figures, the bars above the trace denote an application of test substances. Unless otherwise indicated specifically, the data are presented as mean values ± SEM (n = the number of observations).
Acknowledgements This work was supported by the grants  14-34077S  and  GACR P304/12/G069  from the  Grant Agency of the Czech Republic ,  GAUK 22214  from the  Grant Agency of Charles University in Prague , and by institutional support RVO# 67985823. CS and GD were supported in part by the  FP7 Initial Training Network Edu-GLIA program  ( PITN-GA-2009-237956 ). This publication is partly a result of the " Advanced Bioimaging of Living Tissues " project, registration number # CZ. 2. 16/3. 1. 00/21527 ,which was financed from the budget of the  European Regional Development Fund  and public budgets of the Czech Republic through the  Operational Programme Prague-Competitiveness. AV was supported by the  Wellcome Trust , by the  Alzheimer's research foundation (UK)  and by the grant (agreement from August 27, 2013 no.
The same two authors independently reviewed the full text of the remaining 84 records to select those useful for answering the following question: when, how, and for which population should an IO infusion be used in adults. Finally, a total of 49 records were retained by mutual consensus, and pertinent data were extracted to prepare independent drafts. Once this step had been completed, all authors met, reviewed the drafts together, resolved disagreements by consensus with all the authors, and decided on the final version.