dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical Analysis SAS and JMP software were used for all statistical computations (SAS Institute, Cary, NC). A Wilcoxon signed-rank sum test was used to determine whether there was a statistically significant increase or decrease in EPIC scores between baseline and 6 months, 1 year, 2 years, and 3 years after treatment. This same series of scores and timepoints was entered into multiple regressions to adjust the effect of pre-treatment TURP by controlling for the baseline score (continuous), risk, use of hormones, diabetes, and age (, vs. 60). Fisher's exact test was performed on select items in the EPIC questionnaire related to urinary incontinence, and urinary irritative/obstructive symptoms were dichotomized to differentiate more specific QOL outcomes over time. The Kaplan-Meier product limit function was used to estimate freedom from posttreatment grade 3 GU.
WOMAC A was assessed at weeks 1, 2, 3, 12 and 26. Other scores were obtained only at baseline, W12 and W26. The number and percentage of improved patients at week 1 and 2 were also studied, as well as the level of improvement. Patients had to grade their improvement from 0 (none) to 3 (high). Improved patients (who responded 2 or 3) had to quantify the level of improvement (<25%, 25-50%, 50-75% and >75%). Analgesic consumption and adverse events were recorded at each visit. Statistical analyses were performed, from the Intent-to-treat (ITT) population, using XLStat 2015 Addinsoft software. The homogeneity of the two treatment groups was evaluated using non-parametric tests. The normality of variables was assessed using Shapiro-Wilk test. If normality, they were evaluated by analysis of variance.
Acknowledgements The study was funded by  LABRHA SAS, Lyon, France. The " HAppyvisc Study Group " included all investigators and coinvestigators of the study:  Drs Ardizzone Marc ,  Bernard Jean-Paul ,  Berthier Michel ,  Balblanc Jean-Charles ,  Bouysset Maurice ,  Caumon Nicolas ,  Charrin Jeanne ,  Colson Frederic ,  Despaux Jacques ,  Dusan Robert ,  Forestier Romain ,  Françon Alain ,  Gagnard Anne ,  Gerrud Sylvie ,  Guillemot Anne ,  Jalby Jocelyne ,  Kandil Franck ,  Laine Marc ,  Liens Daniel ,  Lohse-Walliser Anne ,  Mornand Yves ,  Noel Eric ,  Ollagnon Henri-Olivier ,  Perard David ,  Rambaud-Lequin Catherine ,  Rey Benedicte ,  Souchon Jean Francois ,  Toulemonde Gwendoline ,  Ferreira André ,  Markus Françoise ,  Camilleri Jean-Philippe ,  Milon Eric ,  Sparsa Laetitia ,  Tulli Regis ,  Bosque-Proton Annie ,  Legré-Boyer Virginie ,  Renzulli Jean-Georges ,  Ferrazzi Véronique ,  Roch-Bras Françoise ,  Monod Pierre ,  Roquefort Jean ,  Hacene-Beniddir Anissa ,  Fulpin Jean ,  Plantamura Alain ,  Cautiello Christian ,  Colcombet Clémence ,  Augé Benoit ,  Brault Isabelle ,  Letho-Gyselinck Hélène ,  Thomas Philippe ,  Gautier-Piquemal Marie-Charlotte.
If a DU was reported, a patient visit was organized so that the physician could confirm or exclude the presence of a DU. Data management was performed centrally, and data quality was rigorously monitored. Consistency of the source data with the clinical database was verified for critical variables for 3 randomly selected patients per site (or fewer, if fewer patients had been enrolled). Data were reviewed regularly. The CAP study was led by an independent steering committee (see the Supplementary Materials, available on the Arthritis & Rheumatology web site at http://onlinelibrary. wiley. com/doi/10. 1002/art. 39718/abstract). The complete list of CAP study investigators is also given in the Supplementary Materials. This study was conducted in accordance with the Declaration of Helsinki and its amendments, followed the Guidelines for Good Clinical Practice of the International Conference on Harmonisation, and was approved by the local institutional review boards and ethics committees.
ACKNOWLEDGMENTS We thank our colleagues for sending their patients to our  Scleroderma Clinics  and our patients for their trust and unconditional commitment. We also thank  Harald Heinzl  ( CeMSIIS, Medical University of Vienna, Vienna, Austria ) for statistical consultation and assistance with the bootstrap analysis, as well as the wider group of statisticians for their contributions (see Supplementary Materials, available on the Arthritis & Rheumatology web site at http://onlinelibrary. wiley. com/doi/10. 1002/art. 39718/abstract).
Supported by  Actelion Pharmaceuticals. Dr. Smith 's work was supported by  FWO  research grant  1. 5. 217. 13N ;she also is recipient of an  FWO Senior Clinical Investigator fellowship. Dr. Cutolo  has received research funding through the  University of Genoa  from  Actelion Pharmaceuticals, Bristol-Myers Squibb , and  Horizon. Dr. Herrick  has received consulting fees and/or speaking fees from  Actelion Pharmaceuticals and Apricus  (less than $10,000 each) and research grants from  Actelion Pharmaceuticals. Dr. Distler  has received consulting fees from 4D Science,  Active Biotec ,  Dr. Becker  has received speaker's fees and/or honoraria from, and has served as a consultant to,  Actelion Pharmaceuticals  (less than $10,000; unrelated to the present study). Dr. Carpentier  is a member of the  Actelion Pharmaceuticals SAS France  scientific committee on digital ulcers.
This osteosarcoma selective effect was independent of FGFR1 or FGFR2 amplification status and was also apparent when FGFR1 or FGFR2 amplified tumor cell lines were excluded from the analysis (AZD4572, p = 7. 2 3 10 À3 and PD173074, p = 4. 3 3 10 À2 ; Figures  2C  and 2D ). Furthermore, the osteosarcoma selective nature of PD173074 was confirmed by a reanalysis of PD173074 sensitivity data derived from 660 tumor cell lines (Garnett et al. , 2012) (Figure  2E ; p = 1. 4 3 10 À3 ). Taken together, these results suggested that FGFR inhibitors might show some utility in osteosarcoma, but that factors in addition to FGFR1 and FGFR2 amplification might explain drug sensitivity in this setting. We also assessed the possibility that KGDs could be identified that were associated with specific subtypes of cancer.
Integrating Data on Protein-Protein and Regulatory Interactions Facilitates the Interpretation of Genetic Dependencies The set of KGDs associated with cancer driver gene alterations can be used to frame testable hypotheses, such as ''mutation in gene A drives dependency upon a gene B. '' However, without further information, there are a number of potential mechanistic explanations for each genetic dependency. In model organisms, the problem of interpreting such dependencies has been addressed by integrating information from protein-protein  (Beyer et al. , 2007)  and kinase-substrate interaction databases  (Fiedler et al. , 2009). To facilitate a mechanistic understanding of KGDs and to provide additional guidance for the design of subsequent experiments, we annotated our list of KGDs according to whether they involved known protein-protein interactions  (Chatr-Aryamontri et al.
Our aim in providing this data and illustrating its potential utility is to present starting points for further work. As with any large functional data set, it is important to point out where elements of the technology used might influence the interpretation of the data. In general, siRNA mediated gene silencing is transient, when compared to, for example, short hairpin (sh) RNA mediated RNAi. With this in mind, we used a relatively short cell culture period between transfection and cell viability assessment (a 4 to 7 day period). Nevertheless, we cannot predict whether longer-term cell culture or longer-term gene silencing might result in a somewhat different profile of genetic dependencies. Furthermore, we used an ATP-based assay of cell viability in the screens. Some modes of cell inhibition exist that might have been missed using this method.
Similarly, the increased availability of protein expression data sets (e. g. ,  Lawrence et al. , 2015; Moghaddas Gholami et al. , 2013)  may provide further opportunities for the development of additional integrative approaches. Finally, to make our resource as useful to the community as possible, we have made all of the data described in this manuscript available (https://cansar. icr. ac. uk/), alongside the computational scripts used to integrate data (https://github. com/GeneFunctionTeam/cell_line_functional_annotation). EXPERIMENTAL PROCEDURES siRNA and Small Molecule Screening Cell lines were transfected with a plate-arrayed siRNA library targeting 714 kinases and kinase-related genes (Dharmacon SMARTpools). Positive control (siPLK1) and multiple negative controls (siCON1 and siCON2; Dharmacon, catalog numbers D-001210-01-20 and D-001206-14-20) and AllStar (QIAGEN, catalog number 1027281) were included on every plate.
20 breast cancer models were screened in a 96-well-plate format while the remaining cell lines were screened in a 384-well-plate format (Table  S1A ). All screens were performed in triplicate. Cell viability was estimated as cells reached 70% confluency (normally 4-7 days after transfection) using a CellTiter-Glo assay (Promega). Data processing and quality control was performed using the cellHTS2 R package  (Boutros et al. , 2006). Further details, including small molecule sensitivity testing, are provided in the Supplemental Information.
Data Integration Data from HINT  (Das and Yu, 2012), BioGRID version 3. 4. 128 (Chatr-Aryamontri et al. , 2015) , and KEA protein-protein interaction databases were used  (Lachmann and Ma'ayan, 2009). Kinase-substrate interactions were obtained from KEA  (Lachmann and Ma'ayan, 2009) , PhosphoSitePlus  (Hornbeck et al. , 2015)  and  (Cheng et al. , 2014). High confidence (combined score >0. 7) functional interactions were obtained from the STRING database (Version 9. 1;  Franceschini et al. , 2013). Gene expression relationships were obtained from Pathway Commons  (Cerami et al. , 2011). The shortest_path function in NetworkX  (Hagberg et al. , 2008)  was also used. Further details are provided in the Supplemental Information.
ACKNOWLEDGMENTS We thank  Ultan McDermott  from the  Wellcome Trust Sanger Institute  for sharing DNA sequencing data prior to publication. This work was funded by  Cancer Research UK  (grant number  C347/A8363 ),  Breast Cancer Now ,  UCSF , and The  EU   FP7 project EurocanPlatform  (grant number  260791 ). C. J. R. is a  Sir Henry Wellcome Fellow jointly  funded by  Science Foundation Ireland , the  Health Research Board , and the  Wellcome Trust  (grant number  103049/Z/13/Z ) under the  SFI-HRB-Wellcome Trust Biomedical Research Partnership. We acknowledge  National Health Service (NHS)  funding to the  National Institute for Health Research (NIHR) Royal Marsden Hospital Biomedical Research Centre.
Purpose Ranibizumab, an anti-vascular endothelial growth factor, and dexamethasone, a corticosteroid, have been shown to be effective in treating macular oedema secondary to retinal vein occlusion (RVO) (central RVO (CRVO) and branch RVO (BRVO)). Their real-world usage, however, has yet to be compared. We therefore evaluated ophthalmology visits for both drugs using US patient-level data. Methods The IMS Health Real-World Data Medical Claims database was used to identify treatment-naive patients receiving ranibizumab intravitreal injections or dexamethasone intravitreal implants between June 2010 and February 2014 who had 12 months of follow-up data. The primary outcome measure was the mean number of all ophthalmology visits for the two drugs in patients with CRVO and BRVO. Secondary outcome measures included a comparison of treatment visits, non-treatment visits, and time intervals between visits.
5, 6 This causes a breakdown of the blood-retinal barrier and increases vascular permeability,  6  leading to complications such as MO and retinal ischemia, ultimately resulting in vision loss. 3 [9] [10] [11]  Ranibizumab (Lucentis) is a humanized, VEGF antibody fragment that binds and neutralizes multiple isoforms of VEGF. 11 The efficacy and safety of ranibizumab intravitreal injection were assessed in two randomized, phase three clinical trials (BRAVO and CRUISE, ClinicalTrial. gov Identifiers NCT00486018 and NCT00485836, respectively), in which patients with BRVO and CRVO were administered the study drug once per month for 6 months and compared with sham-treated individuals. 12, 13 In both studies, a higher proportion of patients treated with ranibizumab experienced improvements in vision relative to baseline than individuals who received sham injections (Po0.
5 mg (0. 05 ml solution) administered as a single intravitreal injection once per month in the USA. 21 examethasone, a water-soluble corticosteroid, has also been shown to be efficacious in the treatment of patients with CRVO and BRVO. 22 Dexamethasone is delivered directly to the vitreous cavity by an intravitreal implant (Ozurdex). 23 A sham-controlled clinical trial (GENEVA, ClinicalTrial. gov Identifier NCT01660802) of dexamethasone implant demonstrated significant improvements in BCVA scores and in the percentage of eyes with an improvement of at least 15 letters in BCVA in patients with CRVO and BRVO, compared with shamtreated patients, from day 30 to day 90 after treatment initiation (Po0. 001). 22 However, results from this trial have also shown that the incidence of ocular adverse events was significantly higher in patients treated with dexamethasone implant than in sham-treated individuals.
Study design This was a retrospective study using insurance claims data entered by physicians in the USA into the IMS Health Real-World Data (RWD) Medical Claims database (managed by IMS Health, Plymouth Meeting, PA, USA). Information about the database is published elsewhere. 36 atient data used in this study were anonymized to comply with the Health Insurance Portability and Accountability Act (HIPAA). The study was also designed and implemented in accordance with the Guidelines for Good Pharmacoepidemiology Practice (GPP) of the International Society for Pharmacoepidemiology (ISPE) and the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. 37.
Study population Patients were included in the study if they had received ranibizumab intravitreal injection or dexamethasone intravitreal implant and had a concomitant diagnosis of CRVO or BRVO between June 2010 and February 2014. Diagnoses were defined using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM);  38  CRVO was defined as ICD-9 362. 35 and BRVO as ICD-9 362. 36. The first claim for either ranibizumab injection or dexamethasone implant was defined as the patient's index date. Eligible patients were subdivided according to the index diagnosis (CRVO or BRVO). Data from September 2009 to January 2015 were extracted to ensure at least a 9-month pre-index period and a 12-month follow-up period. Patients were excluded if any of the following criteria were met: (i) patient was younger than 18 years of age at index date; (ii) physician administering the index medicine did not submit monthly medical claims during the 9-month preindex period and during the 12-month post-index period; (iii) patient received one or more anti-VEGF injections or dexamethasone implants during the 9-month pre-index period; (iv) patient received one or more anti-VEGF injections or dexamethasone implants other than index treatment during the 12-month follow-up period in either eye; (v) patient did not have a claim record after the end of the 12-month follow-up period.
Statistical analysis The mean (standard deviation (SD)) was used for continuous variables and n (%) for categorical variables to describe patient characteristics at baseline and outcome measures between treatment groups. Differences in baseline characteristics between treatment groups were compared using the Student's t-test, Wilcoxon signedrank test or chi-squared test, as appropriate. The generalized linear model (GENMOD procedure) using negative binomial distribution compared the number of visits and intervals between treatment groups, adjusting for patients' baseline characteristics. A P value of o0. 05 was considered statistically significant. Statistical analyses were performed with SAS 9. 4 (SAS Institute Inc. , Cary, NC, USA).
Discussion This non-interventional, patient-level claims database study is the first to compare treatment patterns between ranibizumab injection and dexamethasone implant for patients with CRVO or BRVO in the USA. The main finding of this study is that individuals with CRVO or BRVO who received ranibizumab injections had a mean of approximately one more visit to their ophthalmologist during the first 12 months of treatment than patients treated with dexamethasone implant (all ophthalmology visits). The mean number of treatment visits in the first 12 months was also higher in patients who received ranibizumab injection than in those who received dexamethasone implant; however, the mean number of non-treatment visits was higher in patients who received dexamethasone implant than in those who received ranibizumab.
One potential explanation for this could be the increased frequency of ocular adverse events (cataracts and elevated intraocular pressure) associated with dexamethasone treatment. In clinical trials, the frequency of ocular adverse events was higher in dexamethasone-treated individuals than in those who received sham injections, although the increase in intraocular pressure was usually transient. 24, 34, 41 hysicians are thus more likely to screen for such adverse events in patients treated with dexamethasone. Therefore, it could be argued that the visit burden of both treatments is not likely to be substantially different in routine clinical practice. One strength of this study is that it utilized large-scale, routinely-collected population data from one of the largest medical claims databases in the USA.
Of claims submitted to the IMS Health RWD Medical Claims database, 95% are available to view within 3 weeks of the Eye submission date. The sensitivity analyses support the main findings of this study, and demonstrate that the results presented here are not confounded by the restriction to index provider. Furthermore, the data presented on the number of ranibizumab injections received by patients with CRVO are similar to figures published elsewhere,  36  demonstrating the reproducibility of the methods used. This study has also highlighted that the manner in which therapeutic agents are used in routine clinical practice may differ significantly from the label recommendations, emphasizing the importance of real-world evidence studies. The nature of the study has led to several limitations. First, some of the baseline characteristics for patients treated with ranibizumab injections differed from those treated with dexamethasone implant and could have therefore introduced unknown bias.
For example, patients with CRVO who received ranibizumab were older than those who received dexamethasone implant (Po0. 001). This result was surprising because dexamethasone treatment is associated with an increased risk of cataract development,  42  and is therefore usually prescribed to older patients for whom the development of cataracts is intrinsically more common. 43 This side effect could therefore be viewed as less serious in older patients receiving dexamethasone treatment. This study also used physician-entered claims codes to assess treatment patterns. Therefore, misclassification by physicians was a possibility, although this is likely to have affected both groups equally. As the database is used for billing and reimbursement purposes, and not specifically for research use, it may not capture all information, including the purpose of each patient's visit to their physician.
We were therefore unable to assess the effect of treatment frequency on improvements or worsening in clinical outcomes. Finally, this study examined treatment patterns for patients in the USA, and the results may therefore not be applicable to other countries. In conclusion, this study is the first to compare treatment patterns between ranibizumab injection and dexamethasone implant in patients with CRVO and BRVO in the USA, using a large physician-entered medical claims database. In the first 12 months of treatment, patients who received ranibizumab intravitreal injection had a mean of approximately one more visit to their ophthalmologist than those who received dexamethasone implant, which was driven primarily by the high number of non-treatment visits for patients in the dexamethasone implant group.
Conflict of interest Sylvia Nghiem-Buffet and Stéphanie Baillif are consultants for Allergan, Bayer and Novartis. Stephane Regnier is an employee of Novartis Pharma AG, Basel, Switzerland. Adrian Skelly is an employee of Novartis Ireland Limited, Dublin, Ireland. Ning Yu is an employee of IMS Health, London, UK, funded by Novartis to perform the statistical analyses for this study, but was not involved in the collection of the dataset or in gaining access to it for the purposes of the study. Andrea Sodi is a member of the Novartis RVO advisory board.
Phylogenetic analyses To reveal the phylogenetic position of the two new genera, a matrix of aligned nucleotide sequences from four different phylogenetic markers (18S, 28S, rpb2 and tef1), and 219 representatives of Dothideomycetes and Eurotiomycetes, including two species from Lecanoromycetes as outgroup, was produced. The matrix of  Boehm et al. (2015)  was downloaded from  TreeBASE (www. treebase. org; submission No. S 16, 151)  and served as the matrix basis after removal of a few sequences. Sequences of six additional taxa were downloaded from the GenBank nucleotide database. These, together with the newly generated sequences, were manually aligned to the matrix of  Boehm et al. (2015) , or realigned with the server version of MAFFT (www. ebi. ac. uk/Tools/mafft). The resulting alignments were subsequently checked and refined using BioEdit version v.
The resulting combined sequence matrix contained 5721 nucleotide positions from four genes (1653 from 18S, 1230 from 28S, 1875 from rpb2, 963 from tef1). GenBank accession numbers of newly generated sequences are given in Table  1. For detailed phylogenetic analyses within the new family, the ITS-28S, rpb2 and tub2 sequences of all accessions sequenced were aligned and combined in a single three-loci matrix; for GenBank accession numbers see Table  1. This three-loci matrix contained 3657 nucleotide positions (1654 from ITS-28S, 1168 from rpb2 and 835 from tub2). For maximum likelihood (ML) analyses and Bayesian i n f e r e n c e ( B I ) o f t h e m u l t i -g e n e a n a l y s i s o f Dothideomycetes, unique model parameters were applied for each marker and codon (where applicable), with the dataset divided in eight partitions according to  Schoch et al.
(2009a). The general time reversible model, assuming a proportion of invariant sites and gammadistributed substitution rates (GTR + I + G), was selected as best model for all four genes (LSU, SSU, rpb2 and tef1) by Modeltest 3. 6  (Posada and Crandall 1998)  under the Akaike Information Criterion (AIC) and was implemented in the subsequent ML and BI analyses. The matrix of Stigmatodiscaceae was divided in three partitions according to the three loci. For ML analyses, fast tree searches were done with RAxML  (Stamatakis 2006)  as implemented in raxmlGUI 1. 3  (Silvestro and Michalak 2012) , using the GTRGAMMAI substitution model. 500 fast bootstrap replicates were computed using the GTRCATI substitution model. Bayesian analyses were performed on the large matrix of Dothideomycetes with the computer program MrBayes (version 3.