dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank the  Functional Genomics at Nestlé Institute of Health Sciences  (led by  Patrick Descombes)  for their support in DNA sequence analysis. We also thank  Mathieu Membrez  for Caco2 cell culture advice and  Roger Hunter  for critical reading of the manuscript (both at  Nestlé Institute of Health Sciences ). This work was supported by the  Région Ile-de-France (CORDDIM)  and the  Société Francophone du Diabète (SFD). This work was also supported by grants to G. R. S. from the  Canadian Institutes of Health Research  ( 811812 ) and the  Canadian Diabetes Association  ( 846130 ). G. R. S. is a Canada Research Chair in Metabolism and Obesity and the  McMaster University J Bruce Duncan Chair in Metabolic Diseases.
Real human RNA-seq We illustrate key features of CIDANE on two human RNA-seq data sets from the ENCODE project  [21]. Besides the overall performance in terms of recall and precision, we demonstrate CIDANE's capability to recover transcripts invisible to existing methods and its ability to exploit different levels of annotation to improve the assembly. The two strand-specific samples obtained from whole B cells in blood (GEO accession GSM981256) and CD14positive monocytes (GSM984609) comprise 90 million and 120 million 76-bp paired-end reads, respectively, and were aligned using TopHat2. The same data sets were used in  [18]  to assess StringTie's performance and we apply, consistently with our other benchmarks, the same evaluation criteria as  [18]. We compared transcript predictions to a collection H of well-curated 171,904 transcripts in 41,409 protein-coding and noncoding genes that was created by the authors in  [18]  by merging all annotated genes from databases RefSeq  [30] , Ensembl  [31] , and the UCSC Browser  [32].
We expect that CIDANE will provide biologists with accurate transcript predictions from the very large, complex data sets that currently emerge from RNA-seq experiments. Such a high-resolution RNA-seq data interpretation is essential for any type of downstream analysis and will help to expand the catalog of genes and their splice variants. (a) (b) (c) CIDANE is free open-source software released under the GNU GPL license, and has been developed and tested on a Linux x86_64 system. CIDANE's source is available from https://bitbucket. org/canzar/cidane.
The Dutch reference data were used for the Dutch children and young adults  [24, 25] , and the French reference data for height and weight and the Cole BMI reference data were used for the French patients  [26, 27]. All SDS values were calculated with Growth Analyser (version 4. 0; www. growthanalyser. org). The Medical Ethics Committees of the 3 participating centers approved the study. Written informed consent was obtained from parents of PWS. For obese and controls, written informed consent was obtained from themselves and, if they were younger than 18 years, also from their parents or custodians.
Assays Plasma AG and UAG levels were assessed in duplicate (10-50 lL per well) in one laboratory using two-step double-antibody sandwich EIAs, obtained from SPIBio (Bertin Pharma, France; A05306 and A05319, resp. ). Assays were performed according to manufacturer's instructions. In summary, standards, quality controls, and samples were incubated in the plate for 2 h at room temperature without tracer. After a 39 wash, tracer antibody was added and incubated for 2 h at room temperature. Following a 59 wash, Ellman's reagent was added and incubated for approximately 45 min until satisfactory color development. Finally, the absorbance was measured at 405 nm using a VictorX4 plate reader (Perk-inElmer, Groningen, Netherlands). Data were analyzed using Graphpad Prism 5 (La Jolla, California). A sigmoidal third-order (cubic) polynomial fitting was used to determine concentrations from the calibration curves.
Statistics Statistical analysis was performed by the Statistical Package for Social Sciences (version 20. 0; SPSS, Chicago, IL). Data are expressed as median [interquartile range (IQR)]. Differences between the groups were calculated using Kruskal-Wallis tests when comparing three groups and Mann-Whitney U tests when comparing two groups. Patients with PWS in each nutritional phase were compared with age-matched healthy controls. Obese PWS, defined as BMI [?2 SDS, were compared with obese controls. AG and UAG levels and AG/UAG ratios were log-transformed (natural logarithm), as they were not normally distributed. In PWS patients, we cross-sectionally assessed linear correlations between ghrelin levels and other parameters using Spearman's rho correlation coefficient (q). As levels of AG and UAG decreased with age, linear regression analysis was used to compare groups with adjustment for age.
MAPK inhibition triggers RHOB induction in BRAF-mutant melanoma cells Next we addressed whether RHOB induction by PLX4032 in BRAF-mutant melanoma cells was related to BRAF inactivation. We found that BRAF inhibition with siRNA or with the PLX4032-unrelated BRAF V600E inhibitor SB590885 increased RHOB protein levels in WM266-4 cells (Figure  2A, 2B ). Inhibition of the BRAF substrate MEK with AZD6244 or AS703026 also resulted in an increased RHOB expression in those cells (Figure  2B ). These results indicate that BRAF inactivation causes RHOB overexpression in BRAF-mutant melanoma cells. In melanomas, the MAPK pathway is frequently hyperactivated by mutations in the BRAF gene (approximately 50% of melanomas) but also in NRAS (18%), KIT (9%), HRAS (2%) or KRAS (2%) genes (COSMIC database). We therefore examined the impact of PLX4032 and MEKi on RHOB expression in wild type BRAF melanoma cells harboring mutations in NRAS (WM1346 and SK-MEL2 cells), KIT (WM3211 cells) or KRAS (WM1791C cells).
Western blot analysis Cell extracts were analyzed by Western blotting with the following primary antibodies against RHOB, RHOA, BRAF, ERK1/2 (Santa Cruz Biotechnology); RHOC, p-ERK (T202/Y204), p-AKT (S473), AKT, PARP, Cleaved Caspase-3, Caspase-3, c-Jun, p-c-Jun (S63), p-p38 (T180/Y182), p38, pJNK (T183/Y185), JNK (Cell Signaling Technology) or actin (Chemicon). Detection was performed using peroxydase-conjugated secondary antibodies and chemi-luminescence detection kit (Clarity TM ECL, Biorad) on autoradiographs or with ChemiDoc TM MP Imaging System (Bio-Rad). Quantifications were done for three independent experiments with ImageLab software (Bio-Rad) and normalized to actin.
Apoptosis analysis DNA fragmentation was detected by a modified TUNEL procedure using the ApopTag ® Fluorescein In Situ Apoptosis Detection Kit (Millipore). Positive cells were counted by fluorescence microscopy. For subG1 analysis, DNA content was assessed by staining ethanol-fixed cells with propidium iodide and monitoring by FACSCalibur TM (BD Biosciences). The number of cells with subG1 DNA content was determined with the ModFit software.
ACKNOWLEDGMENTS This research was supported in part by  Genentech , the  "Institut National de la Recherche Medicale" INSERM , the " Fondation Recherche et Innovation Thérapeutique en Cancérologie ". We thank  Bettina Couderc  and  Catherine Bouchenot  for the generation of the adenovirus expressing RHOB. We also thank  Magali Farella  for BRAF and NRAS cell line sequencing,  Stéphanie Cabantous  for critically reading the manuscript and  Lourdes Gasquet  at the  Claudius Regaud Institute animal facility.
, 1996)  at a dilution of 1:10,000. The lower part of the membrane was probed with either anti-␥-Tub (QG-17; Sigma-Aldrich, dilution 1:20,000) to analyze membrane fractions or anti-␣-Tub (T6199; Sigma-Aldrich, 1:40,000 dilution) to analyze soluble fractions. Western blots were routinely developed using the ECL system (Life Technologies). Protein levels were quantified using ImageQuant TL software (GE Healthcare). Following normalization to loading controls, the levels of each APPL-reactive band were expressed as relative to the total amount of APPL detected in heterozygous Appl d /ϩ;MBSw/ϩ flies from the same Western blot experiment. Three independent protein extractions were quantified 10 (membrane fractions) and 11 (soluble fractions) times on four independent Western blots. Statistical analyses.
To get an insight into this interaction, we first analyzed whether the memory deficit induced by KUZ overexpression in Appl d /ϩ;MBSw/kuz flies was linked to a modulation of endogenous Appl expression. Appl mRNA level was similar in Appl d /ϩ;MBSw/ϩ and Appl d /ϩ;MBSw/kuz flies (Fig. 5A ), showing that the mechanism by which KUZ exacerbates the memory deficit is not through modulation of Appl transcription, but rather through APPL processing. We next analyzed the effect of KUZ overexpression on APPL protein steady-state levels. Western blots were performed after fractionation of fly head lysates. As expected, the data show that APPL-secreted forms revealed in the soluble fraction were enriched upon KUZ overexpression (Fig. 5B ). In addition, we observed that fulllength APPL (fl-APPL) levels present in the membrane fraction were decreased by 30% in Appl d /ϩ;MBSw/kuz compared with Appl d /ϩ;MBSw/ϩ control flies (Fig.
A. Overall architecture The HEARTEN overall architecture is presented in Fig. 1. Through the mHealth application all the data from the sensors and other patient related data, will be gathered and transmitted to the HEARTEN cloud infrastructure, where the data mining and analytics will be implemented to provide critical information to all ecosystem actors. Specifically, the main components of HEARTEN system are: (i) the sensors, (ii) the mHealth application, (iii) the databases, (iv) the Knowledge Management System (KMS), (v) the Dynamic Patient Communication Protocol (DynPCP)  [19]  platform, and (vi) the cloud platform. All sensor and patient related data will be sent to the mobile application of the user. HEARTEN design includes two different types of data: (i) Personal Data which are related to the users (patients, doctors, caregivers, etc.
) that permit to build a registry of all the users and, (ii) Sensors Data. For these data two different types of databases are needed: (i) Relational Database based on MySQL for all the Personal Data and (ii) NoSQL Database based on mongoDB for all the unstructured raw data retrieved from the sensors and parsed from the applications (raw and processed data will be stored in different collections). The data are transmitted to the KMS where the data mining and the analytics will be implemented to extract rules and provide patterns regarding biomarker detection/medication intake, physical activity, nutrition, blood pressure and heart rate measurements. The DynPCP based on the different patient communication protocols (European Society of Cardiology guidelines  [20] ), the outcomes of the KMS and the patient's medical data will send notifications to the corresponding actors of HEARTEN environment.
C. Data Collection For the implementation of data mining approach and the discovery of interesting and useful patterns of patients' adherence, data from retrospective and prospective patients will be utilized. These data will be gathered from Universita di Pisa (Italy) and Servicio Andaluz de Salud (Spain). The enrolled patients will be asked to use the sensors in a home environment. The annotated data that will be gathered include:  Measurements of breath and saliva biomarkers from the sensors.  Measurements from the heart rate, respiration, weight scale, blood pressure, activity, and body temperature sensors. More specifically, data gathering will consist of four phases. In the 1 st phase, retrospective data from HF patients will be used. In the 2 nd and 3 rd phase, prospective data from HF patients will be collected that will include measurements of heart rate, respiration, weight scale, blood pressure, activity, and body temperature while in the 4 th phase, additional data from breath and saliva sensors will be collected.
D. Data Mining HEARTEN system will address all the issues that HF patients experience through efficiently and effectively monitoring their status and providing patterns and knowledge extraction. Several data mining techniques will be customized and stored into the cloud for analysis of the data of the patients in two phases  [24]. In the first phase, the data of the patients will be used for creating the data mining structures, developing and training the predictive models, whereas based in the grouping of patients, already defined models will be utilized for providing trends of HF patients' non adherence. More specifically, the everyday activities of a patient will be examined and analyzed so as to develop the personalized profile of adherence. In parallel, patients that have similar disease and lifestyle characteristics, receive the same treatment or have the same adherence behaviour will be used for developing the predictive models for alert provisioning and decision support for the patients, the caregivers and the healthcare professionals.
The Executive Committee had full access to all of the data in the study and takes responsibility for the integrity of the data, the accuracy of the data analysis, and the writing of this report. Approval from ethics committees at all participating sites and informed consent from all patients were obtained. During the trial, additional serum samples were obtained at prespecified visits in 394 of 467 sites. Serum FGF23 concentrations were measured from these stored samples by a Luminex-based microbead assay (HBNMAG-51K, Millipore, Billerica, MA) that uses polyclonal capture and detection antibodies. The levels with the Millipore assay were tightly correlated with levels by the Kainos intact assay (Figure I in the online-only Data Supplement) in internal validation studies performed at Amgen.
Acknowledgments We thank the EVOLVE study trial investigators and the patients. EVOLVE investigators: Argentina:  J. Santos ,  C. Najun Zarazaga ,  I. Marin ,  N. Garrote ,  A. Cusumano ,  N. Peñalba ,  E. Del Valle ,  L. Juncos ,  J. Martinez Saye ,  L. Lef ,  V. Altobelli ,  G. Petraglia ,  G. Rosa Diez ,  W. Douthat ,  J. Lobo ,  C. Gallart ,  A. Lafalla ,  G. Diez , July 7, 2015  Drs Wheeler  and Herzog; Mitsubishi:  Dr Wheeler ; MRC:  Dr Wheeler ; Otsuka:  Dr Wheeler ;  Pfizer :  Drs Mahaffey ,  Correa-Rotter ;  Reata Pharmaceuticals :  Drs Chertow  and  Correa-Rotter ; Relypsa:  Dr Herzog ;  Roche :  Dr Correa-Rotter ; Sandoz:  Dr London; Sanofi :  Dr Wheeler ; Satellite Healthcare:  Dr Chertow ; Shire:  Drs Floege ,  London , and Wheeler;  UCB Celltech :  Dr Wheeler ; UCL:  Dr Wheeler ; Vifor:  Drs Floege  and  Wheeler; ZS Pharma :  Drs Herzog  and  Wheeler.
Physicians collected anonymized data from their records regarding those patients who received incobotulinumtoxinA treatment. These data included treated indication, dose injected during each treatment cycle, length of time between treatments, and assessment of patient and physician satisfaction with incobotulinumtoxinA treatment. To assess the safety profile of incobotulinumtoxinA, the study also collected information from physicians on adverse drug reactions (ADRs) associated with its use in aesthetic indications.
Patients and methods study population Physicians invited to participate (n=3,375) were selected at random from a preexisting roster of physicians, which was developed from medical registers and other sources by a contract research organization (CRO). Those who participated were asked to provide data on patients who had recently received treatment with incobotulinumtoxinA for aesthetic indications. The study aimed to collect data from at least 600 patients from across Germany, France, and the UK.
Inclusion criteria To participate in this study, physicians were required to be using incobotulinumtoxinA for aesthetic indications (eg, treatment of facial wrinkles or dermatologic diseases) in routine practice and to have documented sufficient patient data regarding treatment with incobotulinumtoxinA. Patient data were deemed suitable for inclusion in this retrospective study if they reported the use of incobotulinumtoxinA for $1 aesthetic indication at least once before the treating physician had been invited to participate in this survey.
study design Physicians were contacted between July and September 2012. Those who considered themselves to be eligible and who agreed to participate were asked to document patients who fulfilled the inclusion criteria, beginning with the most recently treated patient (relative to the day the physician was invited to take part in the survey) and continuing with the next most recently treated patient, and so on up to a maximum of 15 patients per physician. Each physician was asked to document, retrospectively, all incobotulinumtoxinA treatment cycles per patient up to the day the physician was invited to participate in the study, so that all data were collected retrospectively. A treatment cycle refers to a patient visit to the physician in which $1 injection of incobotulinumtoxinA was administered for $1 indication.
Data collection Data were collected retrospectively by physicians and documented using an electronic Data Collection Form. Documented details included information on the physician, patients, and treatment cycles with incobotulinumtoxinA. Data on treatment cycles included the area treated, number of treatment cycles, time interval between treatment cycles, dose injected, as well as physician and patient satisfaction with treatment. Other information collected included physician specialism, country of practice, experience with BoNTs/ incobotulinumtoxinA, and whether they regarded room temperature storage as advantageous, as well as information on each patient's relevant medical history and concomitant medications, contraindicated diseases, and general health status. Expected ADRs (as described in the SmPC) were recorded, but the study also aimed to record unexpected ADRs should any have occurred.
statistical analysis Statistical analysis was descriptive, and as such, no formal estimation of sample size was made. All analyses were based on the full analysis set, which comprised patients who completed at least one treatment cycle and physicians who documented at least one such patient; the full analysis set was identical to the safety analysis set. Analyses of the data were conducted using summary statistics, and statistical analyses were performed by a CRO using the SAS ® software package, v9. 2 (SAS Institute, Cary, NC, USA).
study population Of the 3,375 physicians contacted from a large address pool, 123 who had used incobotulinumtoxinA expressed an interest in study participation. In total, 66 physicians fulfilled all study inclusion criteria (ie, responded, used incobotulinumtoxinA in routine practice, and had documented patient data available) and agreed to participate. Most physicians included in this study were dermatologists within a practice and/or hospital setting (Table  1 ). They were all experienced in the use of BoNTs in aesthetic practice: 98. 5% had been previously trained to inject any BoNTs and reported a median of 6 years' experience in using these treatments for aesthetic indications, while 93. 9% had been specifically trained to inject incobotulinumtoxinA, with a median of 3 years' experience in using this treatment for aesthetic indications.
Of this experienced population of physicians, 93. 9% saw either an "important advantage" or an "advantage" in being able to store incobotulinumtoxinA at room temperature. A total of 638 patients were included in this study, providing data from 1,437 treatment cycles in which there were 1,972 injections of incobotulinumtoxinA. Patients were between 18 and 65 years of age (mean ± standard deviation [SD]: 46. 6±10. 6) and were mostly female (83. 7%). The majority had a body mass index (BMI) in the normal range (mean ± SD: 23. 8±4. 2 kg/m 2 ) and rated their health status as "good" or "excellent" (Table  1 ). All physicians followed the SmPC with respect to contraindicated conditions and concomitant medications: no patient had any contraindicated condition present or received any contraindicated medication during the study.
Treatment satisfaction Across all treatment indications, 95. 4% of physicians regarded the success of incobotulinumtoxinA treatment as either "very good" (64. 8%) or "good" (30. 6%). Similarly, 97. 8% of physicians rated their satisfaction with incobotu-linumtoxinA treatment for GFL as "very good" (73. 2%) or "good" (24. 6%); this pattern was seen across individual dosing groups when satisfaction data were split according to dose injected (Figure  3 ). For patients, a similar level of treatment satisfaction with incobotulinumtoxinA was recorded across all indications, with 94. 9% stating that they were satisfied with the result. Indeed, for GFL alone, patients were satisfied with incobotulinumtoxinA treatment in approximately 95% of cases. This pattern was seen regardless of the dose injected (Figure  4 ).
Quantification of reactive oxygen species Reactive oxygen species (ROS) were detected using 5,6-chloromethyl-2′,7′-dichlorodihydrofluorescein diacetate acetyl ester (CM-H 2 DCFDA; InVitrogen, Ghent, Belgium). After 30 min of pre-incubation with 5 μM CM-H 2 DCFDA, the different drugs were added alone or in combination. After 24 h of culture, SCLC cell lines (5×10 5 cells per mL in 24-well plates) were harvested, washed with PBS and analysed by flow cytometry (FACS Aria; Becton Dickinson). ROS production was quantified using the fluorescence intensity of chloromethyldichlorofluorescein. 10 000 events were collected and analysed with the FACS Diva software (Becton Dickinson). Cells were also treated with 100 μM hydrogen peroxide or 10 mM N-acetylcysteine (Calbiochem), a free-radical scavenger, as positive and negative controls, respectively.
5. 3. 1). The statistical analyses were performed with Genespring GX, version 7. 3. 1 (Agilent Technologies). Additional normalisation steps were performed ( per spot: division by the control signal; per array: normalisation to the 50th centile; per gene: normalisation to the median). Transcripts that were not present in at least one sample were excluded from additional analyses. Welch's t-test was used to assess the statistical significance, excluding genes whose expression varied by a factor inferior to 2 across the sample set of interest. The threshold for statistical significance after Benjamini's correction for multiple testing was 0. 05. Real-time reverse transcription PCR mRNA levels were analysed by real-time quantitative reverse transcription PCR (qRT-PCR) as described previously  [19] , using the primers in table  1.
MicroRNA analysis MicroRNA (miRNA) expression was determined in triplicates using the TaqMan Low Density Array method (DNAVision, Gosselies, Belgium). Fluorescence data (Bioanalyzer 2100 Nano chip; Agilent Technologies) were normalised by means of two endogenous controls (RNU44 and RNU48). Results were expressed as fold change (2 -(mean(ΔCT(VAC+VPA))-mean(ΔCT(VAC)) , where CT is the cycle threshold). The Benjamini and Hochberg method was used for multiple testing corrections.
b, d and f) The remaining cell fraction was used to determine the rates of apoptosis by flow cytometry after ethanol fixation and propidium iodide staining. Data are represented as mean±SD of three independent experiments. For clarity, statistical tests between conditions and their associated control are indicated above individual conditions. *: p<0. 05 by paired Student's t-test; **: p<0. 01 by paired Student's t-test. adding VPA, both of them being involved in tumour invasion: miR-589 (fold increase of 441 with VPA, corrected p-value <0. 01) and miR-575 (fold decrease of 0. 018, corrected p-value <0. 05) (table  3 ).
b, d and f) The remaining cell fraction was used to determine the rates of apoptosis by flow cytometry after ethanol fixation and propidium iodide staining. Data are represented as mean±SD of three independent experiments. For clarity, statistical tests between conditions and their associated control are indicated above individual conditions. *: p<0. 05 by paired Student's t-test; **: p<0. 01 by paired Student's t-test.