dataesr/scientific-paragraphs-categorization huggingface dataset:
According to duration and energy expenditure, PA level was classified as low, moderate, and high. The French IPAQ-LF was used to test the concurrent validity of the GPAQ. It contains 27 items designed to assess the frequency and duration of PA in 4 domains: during work, transportation, household activities, and leisure time, then time spent sitting. 22 The IPAQ-LF scores PA in terms of energy expenditure (MET), intensity (low, moderate, high, and sedentary), and duration (min/day, min/week). The ActiGraph accelerometer, model GT3X+ (ActiGraph, Pensacola, FL, USA), was used as the criterion measure. The device is worn at the waist and measures and records the changes in acceleration and deceleration movements in 3 axes (antero-posterior, superio-inferior, and medial side). Data for measuring acceleration and deceleration are stored in non-volatile flash memory and can be read by using ActiLife software.
Accelerometer data were scored using ActiLife 6 Data Analysis Software (ActiGraph) to assess time spent at various PA intensity levels (moderate and vigorous in min/day). Freedson's Adult VM3 (2011) cut-off points were used to determine several PA levels: light: 0À2690 counts per minute (cpm); moderate: 2691À6166 cpm; vigorous: 6167À9642 cpm; and very vigorous: 9643À1 cpm. Minutes spent at each intensity level were averaged across valid days. Non-wear periods were identified as 60 consecutive minutes with no movement data (0 counts). 23 ll calculations were based on 60 s epochs; an epoch is a userdefined time-sampling interval used to filter the acceleration signal. In this study, we used 7-day PA questionnaires, so only data with 10 h of wear time per day for 7 days were considered valid and included in the analysis.
24, 25 ociodemographic data such as age, sex, and education (high school or higher education) and socioprofessional status (student or staff) were collected. Anthropometric data including height (in m) and weight (in kg) were reported by each participant for calculating body mass index (BMI, kg/m 2 ), then participants were classified by BMI level: underweight (BMI <18. 5 kg/m 2 ), normal weight (18. 5À24. 9 kg/m 2 ), overweight 25. 0À29. 9 kg/m 2 ), and obese (30 kg/m 2 ). All data (except accelerometer data directly transferred into ActiLife software) were entered into an electronic case report form (CRF) created with Epidata 3. 1 (The EpiData Association, Odense, Denmark).
Statistical analysis Data analysis involved use of SAS Version 9. 4 (SAS Inst. , Cary, NC, USA). Qualitative variables were reported as relative frequency and quantitative variables as mean § SD or median. The Kolmogorov-Smirnov test was used to assess the normality of data distribution. For participants who declared changing their PA, paired Student's t test was used to evaluate the difference in total PA between the 2 visits. Because the activity measured by the GPAQ includes work and household activities, it was compared to the sum of work and household PA measured by the IPAQ-LF. TestÀretest reliability was tested by the Kappa coefficient for categorical data and the intraclass correlation coefficient (ICC) for quantitative data. Spearman correlation was also calculated for quantitative data to compare with previous studies.
11À14  Non parametric correlation coefficient was used because of non-Gaussian distribution for most of PA-score. For one of the GPAQ's question, one answer modality was overrepresented and the correlation was not concordant with the observed agreement (when visualizing the data, the agreement seems good but it was not observed when assessed with ICC and Spearman correlation). Thus the variable was converted into a discrete variable, and the prevalence-adjusted and bias-adjusted Kappa (PABAK) was used to assess the agreement. 26 Concurrent validity was examined by comparing data for the GPAQ and IPAQ-LF at D0 and D8  19  with the Spearman correlation coefficient and its 95% confidence interval (CI) for quantitative data and the Phi coefficient for qualitative data. Criterion validity was examined by comparing minutes of PA obtained with the GPAQ to accelerometer-obtained data at D8 by the Spearman correlation coefficient and its 95%CI.
Criterion validity Accelerometer data were considered valid for 87 of the 92 participants (5 participants did not wear an accelerometer for at least 10 h per day over 7 days). Criterion validity was assessed by comparing total PA time spent in vigorous-intensity activity, or in moderate-intensity activity, or sitting per day reported with the GPAQ and derived from accelerometer counts. Poor but significant correlations for sedentary time (r = 0. 42, p < 0. 01) and total vigorous PA (r = 0. 38, p < 0. 01) were observed (Table  5 ). Bland-Altman findings revealed that the GPAQ underreported total PA, with a mean difference between the GPAQ and accelerometer data of 443. 95 § 157. 46 min/week (Fig. 1B, D ). Limits of agreement for the 2 instruments were wide, with the difference between 286. 5 min/week and 601.
A poor criterion-related validity for the GPAQ as compared with accelerometer data was shown. These results are comparable to Cleland et al. 12  and Bull et al. ,  11  who demonstrated correlations with accelerometer data ranging from 0. 19 to 0. 48 and ¡0. 20 to 0. 40, respectively, whereas results from Hoos et al. 14  showed correlations from 0. 32 to 0. 52. According to Bland-Altman analysis, the GPAQ seems to underestimate total PA as compared with the accelerometer. This finding can be explained by the GPAQ including only PA that lasts at least 10 min, whereas the accelerometer measures all activities regardless of duration. This result was already found in studies comparing questionnaires to objective measures of PA. 31  In this study and according to Bland-Altman analysis, the GPAQ seemed to underestimate sedentary time as measured by the accelerometer.
Acknowledgments This study was undertaken in the  University of Lorraine. Interviews were conducted in a local area serviced by the faculty for this purpose. The authors thank the following for their assistance and contribution to the development and achievement of this research: Marc Braun: Dean  of the  Faculty of Medicine of Nancy ;  Nathalie Richard: HR Manager  of the  Faculty of Medicine of Nancy , who participated in the dissemination of the information message to staff;  Angelo Tonelli: Responsible  for service real estate, furniture, maintenance and security of the  Faculty of Medicine of Nancy , who ensured the place for interviews;.
Design and sampling The study was a cross-sectional household survey with a multi-stage sample as recommended by WHO where a sampling frame is not available  [31]. A list of villages was extracted from the Institut Nationale de la Statistique Appliquée à l'Economie (INSAE) data base and a three-degree stage sampling procedure was used: village, household and child. In the OKT area, 137 villages were identified encompassing 48,538 households and 45,264 children under five. In the DCO area, 136 villages were identified containing a total of 37,178 household and 57,284 children under five. We assumed that around 25% of the total of the villages per study area. Thus, 35 villages were randomly selected in each health district to participate in this study. A cluster was defined as village of residence.
Data collection Data collection teams and supervisors received a six-day training focused on the administration of the questionnaire and sampling procedures. Two teams of field surveyors were created per study zone. The local language varied between the northern and southern regions therefore different data collection teams were used for each region. They were trained to use pictures showing ACT boxes or packaging to interview mothers or caregivers about ACT usage during cases of fever. The pictures included the types of ACT commonly used in Benin, ACT deployed by NMCP in the study area. After obtaining written informed consent, a questionnaire was asked to the mother or guardian of the child included in the study. All questionnaires were reviewed by the supervising team. During the interviews, detailed socio-demographic information of the mother or caregiver (age, school level, occupation) was collected.
Data management and analysis All collected data was entered and checked for errors using the Access 2003 program while a statistical analysis was completed using SAS version 9. 3 (SAS Institute Inc. , Cary, NC, USA). An analysis was done in each area to understand the specific issues of malaria control in each endemic region in the hope of providing an adequate local solution. Median and quartiles were calculated for continuous variables and percentages for categorical variables. Social and demographic characteristics were described for mothers and children. Knowing that children received ACT after six months of age, the type of ACT usage (use and correct use) was calculated in this age group. Logistic regression, taking into account the cluster random effect, was used to test an association between i) characteristic of mother and child and ii) use of ACT in febrile children.
Study limitation The major limitation of this study is the overestimation of declared febrile children as malaria diagnosis was not simultaneously done. However, with a high self-medication, it is difficult to conclude the over or underestimation of malaria cases. There are possible limitations to the accuracy of the measurement of "use of ACT", and "correct use of ACT" based on caregiver responses. However, the caregivers were solicited over a short two-week period of recall to help increase accuracy. Nevertheless, the perception of fever by caregivers may have influenced their search for care and/or the first treatment given. This consideration could lead to an underestimation of ACT use. However, this data was collected under real conditions of drug use and these inevitable parameters must be considered consistently in this type of study.
9 mg/kg of intravenous rtPA and argatroban administered as an intravenous bolus of 100 lg/kg followed by a perfusion of 1 lg/ kg per minute over 48 hours. 25  Sixty-five patients (average age 63AE14; median National Institutes of Health Stroke Scale score of 13) with a proximal intracranial arterial occlusion were included in this study between May 2003 and August 2010. The activated partial thromboplastin time target was 1. 75 times the control under argatroban. A complete or partial arterial recanalization was seen in 55% of the patients at 2 hours and in 78% at 24 hours. Symptomatic intracranial hemorrhage occurred in 3 patients (4. 6%) and 7 patients (10. 8%) died within the first 7 days, mainly as a result of extensive cerebral infarction. These preliminary safety data regarding the association of argatroban and intravenous rtPA have led to additional studies.
Study Design The PRIME (ClinicalTrials. gov: NCT00364013) and 20050181 (NCT00339183) were international, open-label phase III studies in which patients were randomized (1:1) to receive FOLFOX4 (PRIME) or FOLFIRI (20050181) with or without panitumumab. Full details of these studies have been published previously. 18, 19 n brief, eligible patients were adults with metastatic adenocarcinoma of the colon or rectum, and an ECOG performance status of 0 to 2. In PRIME, patients were previously untreated, whereas those in 20050181 had previously progressed while receiving, or within 6 months of, 1 previous fluoropyrimidine-based mCRC therapy. In both studies, panitumumab was administered as an intravenous infusion of 6. 0 mg/kg on the first day of each 14-day cycle. The present analysis focused on patients with RAS WT mCRC (ie, tumors WT for KRAS/NRAS exon 2 [codons 12 and 13], exon 3 [codons 59 and 61], and exon 4 [codons 117 and 146]).
After a diagnosis of colorectal cancer (CRC), approximately 50% of patients will present distant metastasis. Although significant progress has been made in treatments, most of them will die from the disease. We investigated the predictive and prognostic potential of APC11, the catalytic subunit of APC/C, which has never been examined in the context of CRC. The expression of APC11 was assessed in CRC cell lines, in tissue microarrays (TMAs) and in public datasets. Overexpression of APC11 mRNA was associated with chromosomal instability, lymphovascular invasion and residual tumor. Regression models accounting for the effects of well-known protein markers highlighted association of APC11 protein expression with residual tumor (odds ratio: OR = 6. 51; 95% confidence intervals: CI = 1. 54-27. 59; P = 0.
Moreover, in contrast to the other catalytic core subunit APC2, which was shown to be down-regulated in various cancer types, APC11 expression has never been investigated previously in cancer. In the current study, based on different mRNA and protein expression analyses (RT-qPCR, western blot, TMA of 82 primary colorectal cancer tissues, CCLE  29  and TCGA 30 datasets), we aimed at delineating the involvement of APC11 expression in CRC tumorigenesis. Overexpression of APC11 is significantly correlated with chromosomal instability (while no association was found for the expression of the other catalytic subunits APC2 and APC10). A significant association is observed between APC11 expression and lymphovascular invasion and residual tumor. High levels of APC11 protein in primary colorectal tumors is specifically correlated with metastasis at diagnosis.
904; 95% CI = 0. 561-1. 458; vs. cancer cells: mean mRNA = 1. 583; 95% CI = 1. 344-1. 864; P for comparison = 0. 022). Though not statistically significant, the expression of APC11 also appeared to be associated with TP53 gene status with mutated TP53 cell lines exhibiting higher mean levels of APC11 mRNA than TP53 WT (mutated TP53: mean mRNA = 1. 70; 95% CI = 1. 152-2. 507; vs. TP53 WT: mean mRNA = 1. 18; 95% CI = 0. 872-1. 60; P for comparison = 0. 059). Similar observations were made in the Cancer Cell Line Encyclopedia (CCLE) dataset  29  (Fig. 2d ), where a significant correlation was found between APC11 mRNA expression and the FGA status (Fraction Genome Altered) in 59 CRC cell lines (r = 0. 28, P = 0. 034). No correlation with the FGA status was observed for the other catalytic subunits APC2 and APC10 (Supplemental Fig.
S1 ). Akin results were obtained when restricting the analysis to the subset of the 42 TP53 wild-type-expressing CRC cell lines (data not shown). Moreover, no correlation was found between TP53 mutational status and APC11 mRNA expression in CCLE dataset (Supplemental Fig. S4a ). Protein expression. Semi-quantitative Western blot analysis of APC11 protein levels in colon cancer cell lines revealed a 60% concordance between mRNA and protein levels (Figs  2c  and S2 ). Four out of the 6 aneuploid colon cancer cell lines displayed high levels of APC11 protein, while 3 out of the 4 diploid cell lines showed lower levels of APC11 protein, comparable to levels found in the immortalized epithelial cell line HME-1 (Figs  2c  and S2 ). Thus, APC11 expression is associated with chromosomal instability in CRC cell lines.
APC11 expression in primary colorectal tumors. mRNA expression from TCGA datasets repository. A significant correlation between high expression of APC11 mRNA and high levels of FGA was observed in the primary CRC datasets from TCGA repository (r = 0. 21, P < 0. 001, Fig. 3a ). The expression of APC10 mRNA was not significantly correlated with the FGA status, while decreased APC2 mRNA levels appeared associated with the extent of FGA, though not notably (APC10: r = -0. 01, P = 0. 73; APC2: r = -0. 07, P = 0. 076, Supplemental Fig. S3 ). Similar results were obtained when restricting the analysis to the subset of 506 samples harboring a TP53 wild-type gene status (data not shown). Moreover, no correlation was found between TP53 mutational status and APC11 mRNA expression in TCGA dataset (Supplemental Fig.
S4b ). Clinical significance of mRNA expression. In TCGA CRC datasets, APC11 mRNA elevated levels were significantly associated with lymphovascular invasion (P < 0. 001, Fig. 3b ) and with residual disease (P = 0. 0071, Fig. 3c ) but not with AJCC tumor stages (Fig. 3d ). Overall survival analyses did not show any significance for APC11 mRNA expression as a predictive marker for patients with M0 or M1 disease (Fig. 3e, f ). Similar analyses were performed for APC10 and APC2 subunits. APC2 and APC10 mRNA levels were found associated with lymphovascular invasion, but no correlation was observed with residual disease, AJCC tumor stage, and overall survival, either for APC10 or APC2 (Supplemental Figs  S5  and S6 ). Protein expression in a series of 82 patients with primary CRC. The expression of the E3 ligase catalytic subunit APC11 protein was investigated using TMA consisting of 486 samples, including 191 pairs of cancer samples and corresponding normal mucosa  26.
al. (See Supplemental data). Evaluating the interest of APC11 with regards to the current CMS classification requires further studies and at this point, APC11 expression can't be considered as a key element to refine or modify molecular CRC classification. We also characterized the levels of APC11 regarding the chromosomal alterations status of CRC, including analyses of experimental data and public CCLE  29  and TCGA  30  datasets, and identified a strong correlation between high levels of APC11 and chromosomal instability. In the CMS classification, enriched cell cycle and proteasome transcriptomic signatures were found both in the CMS2 canonical subtype (CIN) and in the CMS1 MSI immune subtype  12. Over-enrichment of mutations in cancer drivers is seen in CMS1, with the exception of the 2 tumor suppressor genes APC and TP53.
In turn, as a feedback mechanism, it was reported that APC/C-Cdc20 activates the degradation of p21  37. These results suggest that p53 inactivation may abrogate the APC/C-Cdh1 activation response and may render cancer cells more permissive to Cdc20 overexpression. A recent study has shown that 39% (vs 28%) of tumors with an APC/C mutation  also harbors a TP53 mutation in a cohort of nine cancer types analysed  28. In CRC cell lines, high expression of APC11 appeared to be associated with mutated TP53 in our first analyses by RT-qPCR (P = 0. 059), however this result could not be replicated in public datasets. Alongside the presence of mutations, variation in some APC/C core subunits expression may disrupt the stochiometry of the complex thus affecting chromosome stability during tumor progression.
Real-time quantitative PCR (RT-qPCR) analysis. APC11 mRNA levels were assessed by conducting a two-step RT-qPCR in a LightCycler (Roche Molecular Biochemicals, Applied Science, Basel, Switzerland). Specific primer pairs used for PCR amplification were available commercially (Roche Applied Biosystems). All reactions were performed in glass capillaries (Roche Molecular Biochemicals) using the LightCycler FastStart DNA Master PLUS SYBR Green I kit and deionized water as a negative control. The Thermocycling program was as follows: 95 °C for 10 min, (45 cycles) at 95 °C for 10 s, 55 °C for 10 s, 72 °C for 6 s, 45 °C to 95 °C by increments of 0. 1 °C, followed by a cycle at 40 °C for 30 s. All standards and samples were analyzed in duplicate and experiments were repeated at least three times. Fluorescence data were analyzed with the LightCycler 4.
Patient cohorts, tumor characteristics and immunohistochemical covariates (E-cadherin, Ki67, MLH1, MSH2, DCC, p53 and Bcl2) were previously publis hed  26, 27, 34, 58, 59. Information on the evolution of the tumor in terms of local or distant recurrences was registered prospectively. Overall, complete IHC comparative data could only be obtained for 82 individuals. Normal colon tissue samples were obtained from the Institutional Biological Resources Department of the Centre Léon Bérard (Comprehensive Cancer Center of Lyon, France) (agreement number DC-2008-99). All experiments were performed in accordance with relevant guidelines and regulations. Immunohistochemistry (IHC). Core specimens were taken in triplicate from formalin-fixed paraffin-embedded colon tumors and were arranged into TMA blocks as previously described  60.
The sections were counterstained with hematoxylin. A pathologist and a technician analyzed IHC stained tissues independently. Both the intensity of cytoplasmic staining (3 grades) and the percentage of positive cells were assessed. The intensity of staining was graded on a 3 point scale from 0 to 2: "0" reflected lack of immunoreactivity, "1" weak immunoreactivity and "2" strong immunoreactivity. Once the two investigators reached a consensus on some samples, they reviewed cases with discordant scores. Public data from CCLE and TCGA repository. Segmented copy-number data, mutation and mRNA expression data were obtained from the CCLE website  29  for the 59 CRC cell lines with mRNA data available, and from the cBio Cancer Genomics Portal 61 for the 174 rectal (READ) and 499 colon (COAD) tumour samples of TCGA repository.
Statistical analyses. mRNA expression in cell lines experiments. The log 2 mean mRNA expression of CRC cell lines was estimated using the following random effects model: μ α ε = + + Y log ( ) , ( 2 ) ij i i j 2 in which Y ij is the normalized APC11 RNA expression for measurement j of cell line i, μ is the overall mean across all samples and replicates after log 2 transformation, α i represents the random effects associated with cell lines and ε ij the unexplained error. The statistical significance of the α i term (i. e. biological variation) was estimated using a forward likelihood profile analysis based on the likelihood ratio (LR) test. Estimations were conducted using the maximum likelihood method and the nlme library of the R software  62. For likelihood ratio tests, the statistical significance level was set at P < 0.
Kaplan-Meier curves and the log-rank test were performed to analyze OS and DRFS stratified according to the expression of APC11 and the metastatic status of patients at diagnosis. OS was defined as the time elapsed from initial diagnosis to the last observation or to death from CRC. DRFS was defined as the time elapsed from initial diagnosis to metastatic relapse or death from CRC, or last observation if the patient was alive without metastasis. Cox regression models were fitted to estimate the effect of APC11 on OS and DRFS by unadjusted and adjusted hazard ratios (HRs). A Multiple Correspondence Analysis (MCA) was performed to describe graphically and synthetically the correlations between protein data measured by IHC. Protein data were used as active variables whereas clinical and histopathological data were used as illustrative variables (i.
e. not contributing to the construction of the dimensions) to offer a global and integrated picture of the protein and clinical/histopathological data. Analyses in the CCLE and TCGA public datasets. The FGA (fraction genome altered) was calculated from segmented copy-number data as the ratio of the sum of the lengths of all segments with signal above a predetermined threshold to the sum of all segment lengths. Due to contamination with non-tumour material in TCGA tumour samples, a threshold value of 0. 2 was used for TCGA tumour samples and a threshold value of 0. 3 was used for the CCLE cell lines which are purer  65. Correlation between mRNA expression and the FGA was quantified with Pearson's correlation coefficient and with both Wilcoxon's test and Student's t-test comparing expression levels of the samples at the two extremes quartiles of the FGA (Q75 vs Q25).
Acknowledgements The authors thank  Geneviéve Monges  for kindly providing TMA tissue sections;  Eric Tabone  for providing tumor biopsies;  Emilie Thomas  and  Janice Kielbassa  for bioinformatics process management; this research was supported by  La Ligue Nationale Contre le Cancer  (Grant  R16186CC ) and by  PULSALYS  (Grant  12L882LST ).