dataesr/scientific-paragraphs-categorization huggingface dataset:
ROMA score for pathway activity For the pathway activity evaluation, Representation and quantification Of Module Activity (ROMA) (See https://github. com/sysbio-curie/Roma) (Martignetti et al. , 2016)  was also employed as alternative to the Moonlight Z-score. For each module under analysis, the algorithm applies Principal Component Analysis (PCA) to the sub-matrix composed of the expression values of the signature genes across samples. Then ROMA evaluates the module overdispersion by verifying if the amount of variance explained by the first principal component of the expression sub-matrix (L1 value in ROMA) is significantly larger than that of a random set of genes of the same size. This thus represents an unsupervised approach, that can be also used in combination to the supervised Z-score to detect concordant signals.
Case study n. 1c (Quantification of genes effect on Biological Functions (BF) data-driven by ROMA-score We computed the activity score of biological processes potentially modulated by OCG and TSG using ROMA (Representation and quantification Of Module Activities)  (Martignetti et al. , 2016)  , a gene-set-based quantification algorithm, for more details see Methods. As a case study, we applied ROMA to the BRCA dataset of TCGA (table: module_scores. xls). This approach revealed substantial similarity with the results obtained by Moonlight Z-score. Case study n. 2: Characterize intertumoral (between tumors) genomic epigenomic and transcriptomic heterogeneity in cancer tissue by identifying dual role genes. In this case study, we used the expression levels of genes in all the samples obtained from TCGA / GDC with IlluminaHiSeq RNASeqV2 in 18 normal tissues (NT) and 18 cancer tissues (CT) according to the TCGA criteria ( Table  1  ).
Acknowledgements We are grateful to  Matthieu Defrance ,  Kridsadakorn Chaichoompu ,  Kristel Van Steen ,  Benjamin Haibe-Kains  for suggestions and scientific advices in the  Moonlight  project. The project was supported by the  BridgeIRIS  project [http://mlg. ulb. ac. be/BridgeIRIS], funded by  INNOVIRIS, Region de Bruxelles Capitale, Brussels, Belgium , and by  GENGISCAN: GENomic profiling of Gastrointestinal Inflammatory-Sensitive CANcers , [http://mlg. ulb. ac. be/GENGISCAN]Belgian FNRS PDR ( T100914F  to A. C. , C. O. and G. B. ) EP group was supported by a grant from  LEO Foundation  (grant number  LF17006 ) and  InnovationFund Denmark  (grant number  5189-00052B ).
TCGA GEO Validation Cancer TP NT DEG* Dataset TP NT Platform DEG** Common BLCA 408 19 2937 GSE13507 165 10 GPL65000 2099 896 BRCA 1097 114 3390 GSE39004 61 47 GPL6244 2449 1248 CHOL 36 9 5015 GSE26566 104 59 GPL6104 3983 2587 COAD 286 41 3788 GSE41657 25 12 GPL6480 3523 1367 ESCA 184 11 2525 GSE20347 17 17 GPL571 1316 406 GBM 156 5 4828 GSE50161 34 13 GPL570 4504 2660 HNSC 520 44 2973 GSE6631 22 22 GPL8300 142 129 KICH 66 25 4355 GSE15641 6 23 GPL96 1789 680 KIRC 533 72 3618 GSE15641 32 23 GPL96 2911 939 KIRP 290 32 3748 GSE15641 11 23 GPL96 2020 756 LIHC 371 50 3043 GSE45267 46 41 GPL570 1583 860 LUAD 515 59 3498 GSE10072 58 49 GPL96 666 555 LUSC 503 51 4984 GSE33479 14 27 GPL6480 3729 1706 PRAD 497 52 1860 GSE6919 81 90 GPL8300 246 149 READ 94 10 3628 GSE20842 65 65 GPL4133 2172 1261 STAD 415 35 2622 GSE2685 10 10 GPL80 487 164 THCA 505 59 1994 GSE33630 60 45 GPL570 1451 781 UCEC 176 24 4183 GSE17025 11 53 GPL570 2487 955 4.
The Mann-Whitney U test was used to compare the study population with the reference population. Analyses were performed using SAS Version 9 (SAS Institute, Inc. , Cary, NC, USA) and statistical analysis was conducted externally by Stalphamis (Le Bourg, France). P<0. 05 was considered to indicate a statistically significant difference. A comprehensive study of the ALSAQ-40 score, ALSAQ-40 evolution and the evolution of the ALSAQ-40 score based on each item was performed. For descriptive analysis, the following parameters were investigated: Strength, percentage, distribution, minimum, 1st quartile, median, 3rd quartile, maximum, mean, standard deviation and 95% confidence intervals. For comparative analysis, Student's t test was used to compare final M and R scores. The equality of variance was verified using the folded F test.
07% decrease in the loss of functional capacities, corresponding to a mean life expectancy increase of 52. 57 months (4. 38 years). In the present study, there was an increase in life expectancy of 38 months  (3. 16 years). Each study indicates that GEMALS is an effective method of treating ALS, with beneficial effects observed in 83% of patients in the previous report  (11)  and 83. 7% in the present study. In the previous study  (11) , the ALSAQ40 was reported; however, data regarding specific functions, including speech, were not available. In the present study, the effect of GEMALS treatment on specific functions was evaluated and significant improvements in breathing, walking, salivation, speech, swallowing and writing were observed. The glutamate release blocker Riluzole is, at present, the only authorized treatment for ALS; however, Riluzole treatment extends life expectancy by only a few months  (3).
Participants The study included data from clinically identified FCS participants who were screened and included in a phase 3 randomized placebo-controlled trial of volanesorsen (NCT02211209). Briefly, the trial duration was 52 weeks, and subjects were randomized 1:1 to receive either volanesorsen 300 mg SC or placebo injections. The primary outcome was percent change in TG levels at 13 weeks. Inclusion criteria for the clinical trial included a personal history of pancreatitis and with documented chylomicronemia or TG values exceeding 10 mmol/L and genetic testing or postheparin lipolytic assay consistent with FCS. Patients without pancreatitis could be eligible up to a maximum of 28% of all patients. The study enrolled adult patients (age $18 years) with a history of chylomicronemia as evidenced by documentation of lactescent serum in the fasting state, or fasting TG measurement $ 10 mmol/L (880 mg/dL).
Annotation and evaluation of observed variants Format for storing sequence and quality files derived from the MiSeq output were processed individually using a custom-automated workflow in CLC Genomics Workbench version 8. 5. 1 (CLCbio, Aarhus, Denmark) for sequence alignment, variant calling, producing a variant call format file, and target region coverage statistics. Variant annotation was performed using annotation tool for genetic variants  14, 15  using customized scripts (http://annovar. openbioinformatics. org/en/latest/). There is no consensus on the procedure to attribute causality or pathogenicity to FCS variants detected by nextgeneration sequencing. Fortunately, many variants detected in monogenic chylomicronemia genes have had a long history of archiving and annotation, as well as abundant publications of functional consequences.
For instance,. ] [18]  Annotated coding and noncoding (610 bp from adjacent exon) variants in variant call formats were first filtered to select the rare variants according to minor allele frequencies , 1% in 1000 Genomes Project (1 KG),  19  Exome Variant Server  20  or Exome Aggregation Consortium  21  databases. Polymorphism Phenotype Version 2,  22  Sorting Intolerant from Tolerant,  23, 24  and Combined Annotation Dependent Depletion 25 scores were used to evaluate the deleteriousness of the filtered coding variants. Splicing-based Analysis of Variants  26  and Automated Splice Site and Exon Definition Analyses  27  were used to identify rare deleterious splicing variants. Novel variants found in this study were determined to be likely causative when (1) they had no listed allele frequencies in 1 KG, Exome Variant Server or Exome Aggregation Consortium databases, no consensus genetic variant identification number in the National Center for Biotechnology Information database of single nucleotide polymorphisms, and/or were not reported in Human Gene Mutation Database or University College London familial hypercholesterolemia database; (2) for coding variants, a deleterious score for.
2 in silico algorithms; and (3) for noncoding variants, a deleterious score for. 1 in silico algorithm. Copy number variants, sometimes referred to as ''del-dup'' mutations, were determined using a custom bioinformatics approach. Hereafter, the term ''mutation'' is used interchangeably with ''rare definite or very likely causative variant'' for the sake of brevity. As controls for our annotation pipeline, we used sequence data from the 1 KG database. Standard criteria based on standards of the American College of Medical Genetics, and also on published functional studies where available, were used to assess the potential pathogenicity of identified mutations. Individuals with biallelic pathogenic mutations in LPL were classified as ''LPL-FCS'', whereas those with pathogenic mutations in the other genes were classified as ''non-LPL-FCS''.
Statistical analysis Statistical analyses were conducted using SAS v9. 4 (SAS Institute, Cary, NC). Between-group differences for mean quantitative traits were evaluated with Wilcoxon signed-rank test for nonparametric sample distribution, whereas differences in discrete traits were evaluated using chi-square analysis with Fisher's exact test. Statistical significance was defined as P ,. 05 for all comparisons. Our study sample afforded 84% power to detect a 50% difference in a quantitative trait whose standard deviation was 20% of the mean with 2-sided alpha 5 0. 05.
Acknowledgments R. A. H. has received operating grants from the  Canadian Institutes of Health Research (Foundation Grant) , the  Heart and Stroke Foundation of Ontario  ( G-15-0009214 ), and  Genome Canada through Genome Quebec  (award 4530). A. J. B. is supported by the  Clinical Investigator Program at the Schulich School of Medicine & Dentistry, Western University  and by the  Fernand Labrie Fellowship  of the  Canadian Society for Endocrinology. D. G. team received support from the ECOGENE21 biocluster. The authors would like to thank all study participants.
The PA14 ExoY variant has several additional amino acid substitutions (D110N, R141Q, S227N, and V320L) in addition to the changes affecting the C terminus. To exclude the possibility that these amino acid substitutions contribute to the largely diminished activity of the PA14 ExoY variant, we created a PA14 -PAO1 chimera, possessing the C terminus of the WT PAO1 toxin (PA14 ExoY residues Met-1 to Phe-373, then five amino acids from PAO1 ExoY, Phe-374 -Val-378). The C-terminal substitution restored full activity of the PA14 variant, indicating that the modified C terminus was the only reason for reduced activity of this toxin variant (Table  1 ). Interestingly, a blast search in the database of P. aeruginosa genomes (https:// www. patricbrc. org/; Ref. 45)  4  revealed 118 strains harboring the same frameshift mutation at the C terminus of ExoY (Table  S1 ).
Additional F-actin-binding assays were also performed in experimental conditions favoring the solubility of the ExoY proteins (i. e. high NaCl concentrations instead of low KCl; Fig. 2, D  and E ). These data confirmed the impaired interaction of the PA14, F367A, and L371G variants with F-actin (all exhibited K d values of Ͼ10 M), and similar binding of PA14 -PAO1 chimera and WT ExoY to F-actin (K d ϭ 1. 2 Ϯ 0. 2 and 1. 1 Ϯ 0. 3 M, respectively). Finally, we carried out independent binding studies using pulldown assays that fully corroborate the results from cosedimentation experiments (Fig. 2C ). Therefore, we conclude that the C-terminal mutations or deletions impair or completely abolish F-actin binding and, in turn, result in decreased enzymatic activity and diminished toxicity in our yeast model.
Another Salmonella effector, SipA, binds and stabilizes actin filaments hijacking target cell cytoskeleton to promote pathogen internalization. Low-resolution electronic microscopy studies revealed that a single SipA polypeptide connects adjacent actin protomers inside the interstrand cleft of actin filaments  (36). Similar to SipA, Vibrio parahemeolyticus VopV, an effector that is required for bacteria-induced enterotoxicity, binds to the interstrand cleft of actin filaments  (37). Unlike SipA or VopV, the C terminus of ExoY interacts with actin in close proximity to Asp-25 of actin. Therefore, these effectors unlikely share the same interaction sites with ExoY on F-actin. In silico analysis of ExoY-bearing strains present in the Patric database revealed a frequently occurring frameshift mutation in the exoY gene, which alters the extreme C terminus of the toxin.
5 mM, respectively. High ionic strength and pH 9 were chosen to maintain ExoY in a soluble form. Then 4 l of 0. 5 mg/ml ExoY variant (in 20 mM Tris, pH 9. 0, 500 mM NaCl) was added to 11 l of F-actin. The mixtures of preformed F-actin, MBP-fusion proteins, full-length ExoY variants, or peptides were incubated for 5 min at room temperature and were centrifuged at 100,000 ϫ g for 60 min at 4 °C. Supernatants and resuspended pellet fractions were analyzed by SDS-PAGE on 4 -12% precast gradient gels. Because of similar protein sizes of ExoY and actin (44 and 42 kDa, respectively), quantification of ExoY in the pellet fraction was derived from the amount of unbound ExoY measured by plotting intensity values across lanes, followed by calculation of the area under the curve using ImageJ software.
66 M fluorescent phalloidin buffered with PBS and 0. 5% of Triton X-100 at room temperature in the dark for 30 min, followed by two washes with PBS. We chose the phalloidin conjugated to a far red 670-nm fluorophore to ensure a signal separation from GFP. The cells were applied on concanavalin A-coated slides, mounted with FluoromontG, covered with round 1. 5-thickness cover glass, and immediately processed. Image acquisition was performed in Leica TCS SP5 confocal laser scanning microscope, with 63ϫ oil-immersion objective (NA 1. 4). Excitation was performed using argon (488-nm line) and HeNe lasers (633-nm line), and emission was recorded with hybrid (HyD) detectors. Leica Application Suite Advance fluorescence software was used to operate the microscope. Raw data were analyzed and processed in ImageJ.
For colocalization analysis, multicolor beads were used to correct for chromatic shift. Raw images were corrected and filtered using median filter with a pixel radius of 2, followed by background subtraction with a rolling ball radius of 10 pixels. Next, images were analyzed for colocalization with JACoP plugin (44). Mander's colocalization coefficients of 10 cells are reported. This value is a correlation between the fluorescence signal in two channels  (44). Fluorescence distribution on green (GFP or GFP-ExoY) and red (actin) channel was assessed by plotting intensity profile of a straight cross-section of a yeast cell. To assess the yeast actin content, the fluorescence intensity in the phalloidin channel was measured using ImageJ software in randomly chosen individual cells.
Acknowledgments-A. B. thanks  Dr. Cosmin Saveanu ,  Dr. Ina Attree , and  Dr. Yury Belyi  for fruitful discussions. We thank  Dorothée Raoux-Barbot  for technical support,  Dr. Violaine David  for critical reading,  Dr. Alexandre Chenal  for help in peptide design, and  Prof. Sabine Rospert  for the anti-RPS9 serum. We acknowledge the  Imagopole France-BioImaging infrastructure , which is supported by  French National Research Agency  Grant  ANR 10-INSB-04-01  (Investments for the Future), for advice and access to the Leica TCS SP5 system.
Abstract. We report a data set of biogeochemical variables related to carbon cycling obtained in the three branches (M y Tho, Hàm Luông, C ó Chiên) of the Mekong delta (B én Tre province, Vietnam) in  December 2003 , April 2004 , and October 2004. Both the inner estuary (upstream of the mouth) and the outer estuary (river plume) were sampled, as well as side channels. The values of the partial pressure of CO 2 (pCO 2 ) ranged between 232 and 4085 ppm, O 2 saturation level (%O 2 ) between 63 and 114 %, and CH 4 between 2 and 2217 nmol L -1 , within the ranges of values previously reported in temperate and tropical meso-and macro-tidal estuaries. Strong seasonal variations were observed. In the upper oligohaline estuary, low pCO 2 (479-753 ppm) and high %O 2 (98-106 %) values were observed in April 2004 most probably related to freshwater phytoplankton growth owing to low freshwater discharge (1400 m 3 s -1 ) and increase in water residence time; during the two other sampling periods with a higher freshwater discharge (9300-17 900 m 3 s -1 ), higher pCO 2 (1895-2664 ppm) and lower %O 2 (69-84 %) values were observed in the oligohaline part of the estuary.
Atmospheric pCO 2 values were retrieved from the National Oceanic and Atmospheric Administration Earth System Research Laboratory atmospheric measurement network database at the Guam station (Mariana Islands, 13. 386 • N 144. 656 • E) located in the Pacific Ocean, approximately at the same latitude as the Mekong delta. The atmospheric pCO 2 values were converted from dry air to humid air using the water vapour formulation as a function of salinity and temperature given by  Weiss and Price (1980). For the three sampling periods, the dry air CO 2 mixing ratio averaged 376 ± 4 ppm and the humid air CO 2 mixing ratio averaged 362 ± 3 ppm. For CH 4 , a constant atmospheric value of 1. 8 ppm was used. The Henry constant of CO 2 and CH 4 was computed from salinity and temperature according to  Weiss (1974)  and  Yamamoto et al.
Acknowledgements. We are extremely grateful to the  Research Institute  for Aquaculture No. 2  ( Ho Chi Minh City ) and the  B én Tre Fishery Department  for logistical support during the collection of samples. Freshwater discharge data were kindly provided by  Nguyen Hong Quang  from the  Vietnam National Satellite Center. This work was funded by the  Fonds National de la Recherche Scientifique (FNRS)  ( 1. 5. 066. 03 ); the publication charge was covered by the  Asia-Pacific Network for Global Change Research  ( CRRP2016-01MY-Park ) support to the special issue. We thank three reviewers for constructive comments on a previous version of the paper. Alberto V. Borges is a senior research associate at the FNRS. Edited by:  Ji-Hyung Park  Reviewed by: two anonymous referees.
Therefore, we adopted this definition and used parents' education level, occupational prestige, and income level to measure family SES. Parents' education level can be measured using scales of both diploma attainment and schooling years. Compared with data on schooling years, diploma data are relatively easy to collect because many students, especially those in lower grades, may not know or be able to calculate the number of years their parents have attended school. This may lead to missing or artificial data. To maintain accuracy in the measurement of parents' education level, we collected diploma data from students. The prestige of an occupation can be measured based directly on the occupational classification. However, this method tends to leave out new occupations and fails to reflect the class differentiation within one occupation.
Participants We used a cluster random sampling method to recruit 2294 middle-school students in grades 8 from 11 schools in Beijing and Guangzhou to participate in our study. Of this total, 1091 were from Beijing (male = 497, female = 594), and 1203 were from Guangzhou (male = 609, female = 583, unreported = 11). The present study was approved by the Research Ethics Committee, South China Normal University. All participants provided their oral informed consent before completing the measures. The data were collected and analyzed anonymously.
Measurements and Data Analysis We adopted a paper-pencil test and took the class as a group. Each participant received a pack of test questions, which included two parts of the reading test (a total of 26 questions) and a background questionnaire. The time allotted for the test was divided into two periods with a break between them. We used a balancing technique: half of the participants did the reading test first, and the other half did the background questionnaires first. The participants were allocated to these conditions randomly. We used BILOG, SPSS Version 21. 0, LISREL, and Mplus Version 7. 4 to analyze the data. First, we used the expectationmaximization algorithm to handle missing data in SPSS. Then, we tested hypothetical models using path analysis in Mplus with maximum likelihood estimation.
As for the moderating effect of learning motivation, importance should be attached to the effect of students' subjective initiative in removing the negative influence of family SES. School education and family education can arouse and maintain the learning motivation of children and encourage them to overcome the effects of harmful factors. This study found significant relevance between family SES and students' reading ability. However, we cannot understand this result in a simple and absolute way. First, we analyzed data only at the individual level, but the relation between SES and reading ability may vary based on higher level variables such as classes and schools. Second, all variables in this study were analyzed as observed variables. The results may be more accurate if potential variables were used in considering the measurement error.
[16] No exercise or a low level of exercise was considered a positive marker of frailty for physical activity. -Slowness was assessed by gait speed (time to walk 4 m). Score under 0. 8 m/s indicated positive marker for slowness. [7, 17] tients who had ≥3 markers were classified as frail, patients with 1 or 2 markers as pre-frail, and patients with no markers as not-frail. [7] 7. Data analysis Sample characteristics were detailed using mean/standard deviations for quantitative variables, and frequencies for qualitative variables. Two groups of individuals were constituted: "non-frail" (no marker of Fried phenotype); "frail and pre-frail" (≥1 marker). Comparisons between the 2 groups were performed using Student ttests for quantitative variables, and x 2 or Fisher exact tests for frequencies.
Results A total of 509 PHIV were screened among whom 502 were included: 365 (72. 7%) men and 137 (27. 3%) women. The 7 patients excluded because of a lack of data were 5 men and 2 women. Sixty percent of patients were between 50 and 59 years. HIVinfection lifetime was ≥25 years for one-fourth of the PHIV. Nadir CD4 count was <200 cells/mm 3 for almost half the PHIV and 438 (87. 3%) had undetectable viral load. Almost one-fourth (23. 7%) was at AIDS stage. Concerning the weight, on-third (34. 4%) were overweight or obese (BMI ≥ 25). Tobacco consumption was high (61. 5%). Almost half (49. 0%) of PHIV had deprivation. The prevalence of frailty and pre-frailty were 6. 3% and 57. 2%, respectively. Low physical activity and weakness were the main frailty markers, respectively, 49. 4% and 19. 9% (Table  1 ).
Acknowledgments Authors wrote this article on behalf of the  Visage group , and wish to thank the following persons for their active participation in this study:  Allegre T. , Chadapaud S. , Cohen-Valensi R. , Granet P. , De Jaureguiberry J. P. , Pellissier L, Pichancourt G. , Philibert P, Tollinchi F. All participating people gave permission to be named in this article.
Zeta potential data were recorded with a ZetaProbe from Colloidal Dynamics Inc. , which is based on the frequency-dependent electroacoustic effect. Shortly, an alternating voltage is applied to the suspension which causes charged particles to move back and forth at a mobility that depends on their zeta potential. The software calculates the zeta potential from the frequencydependent mobility using the O'Brien equation  (James et al. , 1992). Finally the values obtained were background corrected with a measurement of the filtrated aqueous phase. The zeta potential (-8. 1 mV ± 0. 9 mV) measured for the C-S-H reference (Ca/Si = 0. 8) is consistent with data from the literature  (Haas and Nonat, 2015; Labbez et al. , 2007; Viallis-Terrisse et al. , 2001).