dataesr/scientific-paragraphs-categorization huggingface dataset:
Procedures for Different Outcomes Treatment aspects are listed below. Prognosis (seizure frequency, mortality, suicide, and complications). A detailed questionnaire was used to collect data from every participant. Although not validated in Cambodia, this questionnaire has been enormously used in other tropical populations  [6]. The seizure frequency for our survey was monthly and was self-reported, along with a confirmation from their suitable proxies. The seizure freedom for this survey was defined as no occurrence of seizure since last visit. Information on mortality (status, circumstances, date, and cause) was determined by conducting verbal autopsy from the immediate family member(s) of the patient. The cause of death was not specifically validated but any relevant documents that a patient's family might have had were asked to identify the plausible cause of death.
Direct method by asking open-ended questions was used to collect data on suicidal thoughts and/or attempts from the patients and was confirmed from their proxies. This was part of the questionnaire and was asked at each visit and to every patient. Suicidal thought was defined as thoughts about suicide or any unusual preoccupation with suicide. This ranged from fleeting to detailed planning, role playing, self-harm and attempts. This was required to have a direct correlation to epilepsy or its treatment. The questionnaire mentioned just above was used to collect data on the epilepsyrelated complications and adverse events (AEs) as well. Complications were any physical comorbid event (burning, falls, injuries, etc. ) that occurred as a direct result of epilepsy, irrespective of their type. The complications were recorded for a follow-up period and not for a lifetime of the patient.
Analyses The main outcome variable was number of seizures. Data entry was carried out by using Epi-info (Epi-info 3. 5, Center for disease control and prevention, USA) and data was analyzed using STATA version 9. 1 for windows  [18]. Seizure numbers were averaged for each time period and a change in this seizure frequency was determined with respect to different time-points and treatment periods. Confidence interval for number of seizures was also determined, and so is the statistical significance (p value) for a change in seizure frequency by using t-test. Complications were estimated for each (and overall) time point, according to the type of complications, and expressed in simple frequencies. A statistical significance of a change from the onset to the end of primary-treatment period, and between periods of primarytreatment and treatment-continuation was determined through chi-squares and respective p values.
All animals were videotaped 5 times before the beginning of the protocol in order to quantify and characterize normal baseline locomotor activity with EthovisionH and The ObserverH software respectively (Noldus, The Netherlands) (Fig. 1A ). Briefly, animals were transported from their home cage to a custom-made video cage without bars and continuously filmed for 6 hours. Baseline locomotor activity was quantified as total distance travelled (TDT) in meters and averaged across all different baseline films using Ethovision  [22, 23]. Nine primates received daily intramuscular injections of 0. 2 mg/kg MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, Sigma-Aldrich, France) for 7 consecutive days (Fig. 1A ), the remaining 3 being kept as intact controls. Cycles of MPTP intoxication were repeated if the desired level of parkinsonism was not achieved in the first 7 days.
LID Recordings Quantification of L-DOPA-induced dyskinesias was performed with The Observer XT specialized software (Noldus, The Netherlands)  [24]. The 6 hour recordings of animals on and off L-DOPA treatment were used to manually score the total number of dyskinesias. The analysis yielded a time-encoded event log of abnormal behaviours that allowed us to validate the pharmacokinetics of L-DOPA and the incidence of abnormal involuntary movements in all our LID primates over 6 hours. Following relevant clinical scales used in PD patients and primates  [25, 26] , dyskinesias were manually scored in 7 different body parts: upper limb (right or left); lower limb (right or left); trunk; neck and face. After 5 months of L-DOPA administration the LID count was stable, and animals (n = 6) were kept on a maintenance regime consisting of a daily oral dose of 600 mg of L-DOPA (mean 6 s.
Expression differences were calculated using the amplification rate of the target as evaluated from serial dilutions of whole-brain cDNA and corrected for differences in cDNA input in reference to the expression level of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA, assumed to be constant throughout the brain. Differences between control and experimental samples were calculated using the DDCt method. All experiments were carried out on two replicates of each sample. Primer sequences were designed using Oligo 6. 3 software and are reported on table  S1.
Imaging I. Positron emission tomography scans. PET scan acquisition was performed under propofol anaesthesia (1 mg/kg/hour). Animals were placed in a PET dedicated stereotactic-like animal holder with the head resting on a mouth bar, fixed by blunt ear bars. Temperature was maintained at 37uC using a feed-back coupled heating blanket, and the respiration rate, pO 2 , pCO 2 and cardiac rhythm were continuously monitored. 18 F-DOPA radiotracer (6-[18F] Fluoro-L-Dopa, 200+/230 MBq) was injected intravenously at the start of data acquisition. Imaging was performed on a non-human primate dedicated PET scanner with a 1. 5 mm axial resolution 4% sensitivity, the FOCUS 220 (Siemens), using a time coincidence window of 6 ns and energy discrimination levels between 350 and 650 keV. Data were acquired during 90 min and list mode data were sorted in 9 frames of 10 min.
The attenuation correction factors were measured with an external 68 Ge source before radiotracer injection. The emission sinograms (i. e. each frame) were normalized, corrected for attenuation and radioactivity decay, and reconstructed using Fourier rebinning (FORE) and ordered subset expectation maximization (OSEM) 2D (16 subsets and 4 iterations). Data analyses were performed using the in-house built and freely available software Brainvisa (http://brainvisa. info/ index_f. html). Left and right putamen were individually segmented on summed 18 F-DOPA PET images using intensity scaling, including pixels with an intensity of 80% of the maximum intensity value within a defined volume. A spherical region (300 mm 3 ) was placed in the occipital cortex as a reference region. Time activity curves representing the mean distribution of the tracer concentration (Bq/cc) within the caudate, putamen and occipital cortex in function of time were then analysed using the Patlak graphical method  [28].
Statistical Analysis I. Behavioural data. Analysis of variance on raw data indicated heterogeneous LID baseline from a monkey to another one (ANOVA: p = 0. 0002). Since all LID animals were filmed under IRC and, after a washout period, under vehicle, each animal was compared with itself. Accordingly, the LID raw data was normalised by deriving the percentage of effect on the LID. No LID being considered as 100% of effect and the LID[PEG400] for an animal at a treatment period being considered as its 0% of effect at this period. The general formula is: LID [%effec- t] = 100*(LID[PEG400]-LID[raw data])/LID[PEG400]. Stu- dent's t test was used to compare the percentage of effect on LIDs and TDT in relation to 0% (no effect). II. RT-PCR, histology and PET. All data was analyzed with Student's t test or one-way ANOVA followed by Fisher's PLSD post hoc test.
Effect of Amantadine on Dyskinesias and Locomotor Behaviour Although the primate model chosen for this study has been extensively used to evaluate therapeutic strategies for PD, we wanted to confirm that our dyskinetic primates responded to treatment with amantadine, the NMDA glutamate receptor antagonist most widely used in the clinic to reduce LIDs  [18]. Three doses of amantadine were tested acutely based on published results in non-human primates  [30, 31, 32, 33]. Locomotor activity was quantified using Ethovision software and the incidence of abnormal movements was rated using The Observer software. All LID animals were given L-DOPA and an acute injection of either vehicle or a given dose of amantadine (2. 5, 5 and 10 mg/kg) respecting a 10-day washout period between treatments. Results indicated that amantadine significantly reduced dyskinesia score by approximately 30% only at the 10 mg/kg dose (p,0.
Effect of IRC Treatment on Dyskinesias and Locomotor Behaviour Figure  4A  summarizes the effect observed on dyskinesias for all acute doses of IRC-082451 tested in our LID primates. The 2. 5 mg/kg dose had no beneficial effect on the number or type of dyskinesias following L-DOPA treatment. In contrast, a significant 43% reduction of the total number of dyskinesias (p,0. 01) was observed at the 5 mg/kg dose suggesting an antidyskinetic effect of the compound. Animals also responded acutely to the 10 mg/kg dose showing a 25% reduction in dyskinesias (p,0. 05) (Fig. 4A ). Figure  4B  shows there was no significant effect of IRC-082451 on spontaneous locomotor activity across all acute treatments tested. An example of the time-encoded analysis of dyskinesias in a single animal using The Observer software is reported in figures 4C (PEG) and D (IRC).
Five chloroplast genomes from plants of the Brassicaceae family are available in sequence databases (Arabidopsis thaliana, Arabis hirsuta, Brassica napus, Capsella bursa-pastoris, Draba nemorosa), but few data have been deposited for A. alpina. The only plastome sequences available for this species came from phylogeographic studies  (Koch et al. , 2006; Ansell et al. , 2011; Karl et al. , 2012) , where the trnL-trnF region of the chloroplast genome was amplified by polymerase chain reaction (PCR) and sequenced in order to acquire phylogenetic data about A. alpina populations. The first published cp genome sequence was from Nicotiana tabaccum  (Shinozaki et al. , 1986). Timeconsuming procedures were required at that time to purify plastome DNA and to sequence generated fragments  (Sato et al.
Clustering was performed using SEED 1. 4. 1  (Bao et al. , 2011)  with no mismatch, and three overhanging residues set up. The resulting processed data set was subjected to DNA fragment assembly using the WGS 6. 1 assembler (wgs-assembler. sourceforge. net) (Myers et al. , 2000). The default overlapper ovl was used. Software's default error rate gave good results with our data set. UtgErrorLimit was set up to 2. 5 for Illumina sequences as suggested by the WGS developers.
Genome annotation and sequence alignments Annotation of A. alpina chloroplast genome was performed on the Dual Organellar GenoMe Annotator (DOGMA) website (http://dogma. ccbb. utexas. edu) (Wyman et al. , 2004). Each annotated gene was manually checked for start and stop codons or intron junctions to correct errors and ensure accurate annotation of the genome. The annotated GenBank format sequence file was used to draw the circular map using GenomeVx (http://wolfe. ucd. ie/GenomeVx) (Conant and Wolfe, 2008). A complete chloroplast genome comparison was performed with mVISTA program in LAGAN mode (http://genome. lbl. gov/vista/ mvista)  (Dubchak and Ryaboy, 2006)  using GenBank format files as input. ClustalW2 enabled the alignment of complete chloroplast genome sequences (http://www. ebi. ac.
Contig alignment and scaffolding based on paired-end data enabled to gain a complete circular A. alpina cp genome sequence (Fig. 1 ) (GenBank accession number: HF934231). Having sequenced total DNA from 23 other A. alpina samples, a similar approach was conducted with sequences obtained from three other individuals from different locations. Independent de novo assembly for the three samples (Table  1 , individuals 6, 9, and 24) led to a similar genome sequence assembly, except for some individual polymorphisms (see below). The assembly process is therefore reproducible from one individual to the other. The organization of the assembled genome is conserved when compared with other Brassicaceae cp genome using whole genome alignment (Fig. 1 ). Annotation of the A. alpina cp genome was successfully performed (Fig.
Arabidopsis thaliana Capsella bursa-pastoris Brassica napus Draba nemorosa Fig. 3. Complete chloroplast genome phylogeny of Brassicaceae. Plastome sequences were aligned using ClustalW2 (http://www. ebi. ac. uk/Tools/msa/clustalw2), and a tree was drawn using the R package Pegas  (Paradis, 2010). Some transition-transversion bias has been detected in chloroplast genes  (Morton et al. , 1997; Guhamajumdar and Sears, 2005)  but was not detected in cp genomes from the Lemnoideae family  (Wang and Messing, 2011)  or A. alpina in this work. Mutations detected in the A. alpina cp genome were mainly located in the unique regions, LSC and SSC, with an average of one SNP per 808 bp. As mentioned above for interspecies sequence comparison, IR regions appeared more conserved than the unique region of the cp genome.
Determination of Specificity and Efficiency of the PCR Assay To determine the specificity of the MSRV-type set of primers and probe  [29] , real time PCR assays were performed on serial dilutions of MSRV env and syncytin-1 plasmids (available at Geneuro S. A, Geneva, Switzerland) confirming that it was able to detect MSRV env (GenBank accession number: AF331500) but not syncytin-1 (Accession number: AC000064). A standard curve of serial dilutions of human genomic DNA was used to determine the efficiencies of MSRV env and RNAse P PCR assays (Supporting information: Figures  S1  and S2 ). Efficiency of MSRV env assay was determined also by a standard curve of MSRV plasmid (Supporting information: Figure  S3 ). Both MSRV standard curves (plasmid and genomic DNA) had similar slopes. The slopes were 23.
C), consisting of human DNA with a known copy number of MSRV env DNA, and a negative control; they were analyzed for both genes. The assays for the detection of RNAse P and MSRV-type env were considered acceptable in each sample when: 1) No amplification was detected in the negative controls; 2) Ct of RNAse P was lower than Mean +2*S. D of Ct RNAse P of all samples; 3) the duplicates of each sample had less than 5% of variability. GenexH (MultiD analyses AB, Sweden) software was used to normalize sample Cts according to the efficiencies of each assay and also to the Cts of the I. P. C in each round. The exact number of copies of MSRV-type was determined by interpolation of Cts in a standard curve of serial dilutions of MSRV plasmid (available at Geneuro S. A); the exact number of RNAse P copies per reaction was determined by interpolation of Cts in a standard curve of genomic DNA.
Statistical Analysis Statistical analyses were performed with SPSS 15. 0. Chi-Square test was used to compare qualitative variables. As MSRV load (MSRV-type env copies/pg of DNA) was not normally distributed (Kolmogorov-Smirnov test) a log 10 transformation of the data was made. Data are expressed as mean [95% confidence interval for the mean]. ANOVA test was used for comparison of groups. To compare patients with a high MSRV DNA load with the rest, a cut-off was calculated: Cut-Off = Mean +2*S. D (log 10 MSRV-type env copies/pg DNA) Blood Donors ; (Cut-Off = 2. 22, corresponding to 165 copies/pg of DNA) thus, representing significantly increased values from the normal range in a healthy population. Clinical variables were compared between patients with a MSRV-type load above and below the cut-off.
The present method includes normalization with a single-copy gene (RNAse P), verification of similar efficiencies for target and normalization gene assays and interplate calibration  [36]. Moreover, our data were systematically analyzed with a real-time PCR software (GenexH, MultiD analyses AB, Sweden). This method therefore avoids biases such as differences in DNA load or integrity, or resulting from interplate variability. The stratification by group and sex (Figure  1B ) revealed that MSRV-env DNA load varies with the disease status of MS patients and with the gender. When considering differences between patients and controls, MS women (n = 112; Mean = 115 [108-122] MSRV copies/pg of DNA) had increased genomic load compared to control women (n = 70; Mean = 101 [95-108] MSRV copies/pg of DNA; ANOVA; p = 0.
009). Similarly, MS men (n = 66; Mean = 101 [94-108] MSRV copies/pg of DNA) also had increased MSRV-env copies compared to control men (n = 54; Mean = 79 [72-86] MSRV copies/pg of DNA; ANOVA; p = 2. 77e-6). When considering gender among MS patients, MSRV DNA copy number was elevated in women compared to men (ANOVA; p = 0. 007) but, interestingly, among controls as well (ANOVA; p = 1. 24e-6). Elsewhere, determining the exact number of MSRV-type copies per genome is difficult both in silico and ex-vivo. Alignment of our primers and probe sequences on Ensembl database resulted in a potential detection of 39 copies spread in 17 chromosomes: 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 19, 20, 21 and X. However, this number can change according to the specificity of the BLAST. On the other hand, the number of MSRV-type copies can be different from one cell to another in MS patients, since expression of MSRV-env together with reverse transcriptase and retroviral particles is limited to a subpopulation of cells  [37].
In fact, as shown by Brudek et al. [38] , only a percentage of monocytes and B-cells displayed an increased expression of HERV-W in active MS patients compared to controls. For these reasons, we have expressed our results in MSRV-type copies per pg of DNA, and not per cell. The different loads of MSRV env DNA between men and women among control individuals could be related to the HERV-W env copies present in chromosome X (at least two per chromosome, as detected after alignment on Ensembl database), since they would be detected in duplicate in women. The more elevated MSRV load in MS patients' DNA may then indicate that, in MS, the MSRV pathogenic copy can retrotranpose in PBMCs with active MSRV reverse-trancriptase  [39]  and, eventually integrase  [30]  through recombination/integration events.
Background: Bronchopulmonary dysplasia (BPD) is a common complication of preterm birth. Very different models using clinical parameters at an early postnatal age to predict BPD have been developed with little extensive quantitative validation. The objective of this study is to review and validate clinical prediction models for BPD. Methods: We searched the main electronic databases and abstracts from annual meetings. The STROBE instrument was used to assess the methodological quality. External validation of the retrieved models was performed using an individual patient dataset of 3229 patients at risk for BPD. Receiver operating characteristic curves were used to assess discrimination for each model by calculating the area under the curve (AUC). Calibration was assessed for the best discriminating models by visually comparing predicted and observed BPD probabilities.
Results: We identified 26 clinical prediction models for BPD. Although the STROBE instrument judged the quality from moderate to excellent, only four models utilised external validation and none presented calibration of the predictive value. For 19 prediction models with variables matched to our dataset, the AUCs ranged from 0. 50 to 0. 76 for the outcome BPD. Only two of the five best discriminating models showed good calibration. Conclusions: External validation demonstrates that, except for two promising models, most existing clinical prediction models are poor to moderate predictors for BPD. To improve the predictive accuracy and identify preterm infants for future intervention studies aiming to reduce the risk of BPD, additional variables are required. Subsequently, that model should be externally validated using a proper impact analysis before its clinical implementation.
Data extraction and management The following data from all included validation and derivation studies were extracted independently by two reviewers (WO and MM): year of publication, region of origin, number of hospitals including patients for the derivation cohort, type of data collection (e. g. retrospective or prospective), period of data collection, number of predictors, patient characteristics (i. e. birth weight, gestational age, gender, inclusion of non-ventilated patients), on which postnatal day the original model was developed or validated, and the definition of BPD [e. g. oxygen dependency 28 days postnatal age (PNA) or at 36 weeks postmenstrual age (PMA)], the number of patients used for derivation of the model (not applicable for the validation studies) and the number of patients for internal and external validation when performed in the study.
The following additional items specific to the development of prognostic models were collected: modeling methods [e. g. logistic regression, by consensus, or classification and regression tree (CART) models], handling of continuous predictors and missing values, method of predictor selection, model presentation (e. g. nomogram, score chart, or formula with regression coefficients), model validation (e. g. internal and external validation), measures of calibration and discriminative ability (e. g. c-indices), classification measures (e. g. specificity and sensitivity, and positive and negative predictive values). The original equations or score charts were used to conduct quantitative external validation in order to assess the measures of calibration and discriminative ability of the retrieved models using the empirical data at hand.
The methodological quality of the studies that developed prediction models using an observational cohort was assessed using the STROBE statement. The presence or absence of report characteristics was independently assessed by two reviewers (WO and MO). Furthermore, as recommended, the statistical methods, missing data reporting, and use of sensitivity analyses were judged. From the information in the Results and Discussion sections of each report the inclusion and attrition of patients at each stage of the study, reporting of baseline characteristics, reporting of the study's limitations, the generalizability, and whether the source of funding was reported, were assessed and judged. High risk of bias was considered present when no descriptions of patient selection or setting, or no description of outcomes, predictors, or effect modifiers were found in the report.
Quantifying the predictive accuracy of the retrieved models in a large independent dataset The Prevention of Ventilator Induced Lung Injury Collaborative Group (PreVILIG collaboration) was formed in 2006 with the primary investigators of all RCTs comparing elective high frequency ventilation (HFV) with conventional ventilation in preterm infants with respiratory failure in order to investigate the effect of these ventilation strategies using individual patient data  [19]. Access to and management of the individual patient data from the PreVILIG database has been described in the published protocol  [20]. PreVILIG collaborators provided de-identified individual patient data to the PreVI-LIG Data Management Team. Access to the PreVILIG dataset was restricted to members of the PreVILIG Steering Group and Data Management Team.