dataesr/scientific-paragraphs-categorization huggingface dataset:
Methods Studies. The Study of Colorectal Cancer in Scotland (SOCCS) (1999-2006) is a case control study designed to identify genetic and environmental factors associated with non-hereditary colorectal cancer risk and survival outcomes. Approval for the study was obtained from the MultiCentre Research Ethics Committee for Scotland and Local Research Ethics committee, and all participants gave written informed consent. All methods were performed in accordance with the relevant guidelines and regulations. The study has been described in detail elsewhere  46. The present study includes a subset of 633 patients with pathologically confirmed colorectal adenocarcinoma and 478 age and gender matched controls. We randomly split the data into a training set used to find statistically significant biomarkers (625 patients, 468 controls) and a validation set used to discriminate CRC from control (  8  Blood was collected post-surgery and transferred to the research centre within 72 hours of sampling.
FINRISK. A second serum sample set to investigate risk factors in the Finland population  47  was used. Population data were searched for patients with incident CRC during 10 years follow-up. Individuals were sampled before developing CRC. 40 individuals (mean age 60 (interquartile range 52. 8-68. 71)), who developed CRC and no other chronic disease, were identified and included in the study. 80 age and sex matched controls (median age 60. 32 (interquartile 54. 7-68. 8)), who remained healthy during follow-up period, were selected from the same population and serum N-glycans were analysed.
Experimental protocol. A detailed structural analysis and quantification of oligosaccharides in human plasma was performed using a HTP platform for N-glycan analysis -UPLC hydrophillic interaction liquid chromatography (HILIC) with fluorescence detection -a technique that separates structures on the basis of their hydrophilicity  23, 24. This well-established protocol was further developed, optimised and automated on a robotic platform  48. Several bioinformatics tools were developed to assist the analyses, including modelling algorithms, statistical methods and database matching in GlycoBase  49  , a library containing H/UPLC HILIC data for many 2AB labelled N-linked and O-linked glycans (https://glycobase. nibrt. ie/). Briefly, the glycoproteins in the plasma samples were denatured and the attached glycans released by PNGase F.
Computational procedures. Statistical analysis. Clinical characteristics among patients and controls were compared using a Tukey honest significant difference (HSD) test with ANOVA for all continuous variables. Peak areas are compositional data (presented as a % of the total area under the graph) and therefore the constant-sum constraint (CSC) occurs. The CSC means individual variables do not vary independently, violating common assumptions upon which standard statistical analyses are performed. This was avoided by performing a log transform, log(Peak i )/(100-Peak i ), on all peak areas  52. To calculate the P-values we controlled for covariates by creating a linear regression model with available covariates: age, family history and gender for the SOCCS set and age for the FINRISK set. For categorical variables Fisher exact tests were performed.
To confirm the accuracy of the model, a perceptron model was optimized on the training set and the optimized model was used to classify CRC on the validation set. Predicting the presence or absence of CRC is a binary classification problem with discriminative power indicated by area under the Receiver Operating Characteristic curve (referred to as AUC)  54. Prediction models were deemed statistically different by bootstrapping the AUC using the pROC package  55.
Acknowledgements The authors wish to thank  Cancer Research UK  ( Programme Grant  No. C348/A12076 ), ET has a  Cancer Research   UK Career Development Fellowship  ( C31250/A22804 ). Glycan analysis was partly supported by  European Commission GlycoBioM  (contract # 259869 ), IBD-BIOM (contract # 305479 ), HighGlycan (contract # 278535 ), MIMOmics (contract # 305280 ),  HTP-GlycoMet  (contract # 324400 ),  IntegraLife  (contract # 315997 ), GastricGlycoExplorer (contract # 316929 ) and GlyCoCan (contract # 676412 ) grants. IW was supported by  A*STAR's Joint Biomedical Research Council Strategic Positioning Fund (GlycoSing).
^Approx. derivedfrom21. dataset (625 CRC vs. 468 control). ' All peaks': 42 peak areas. ' All peaks + clinical': 42 peak areas, BMI, age, gender, smoking status, physical activity, NSAIDs intake, Kcalorie intake and CRP. ' All peaks + CRP': 42 peaks areas + CRP only. 'Clinical only': BMI, age, gender, smoking status, physical activity, NSAIDs intake, Kcalorie intake and CRP. 'Clinical -CRP' used all clinical features except family history and CRP. P-value column: '*' best model, P-value AUC different from best model.
The reported proteomic analysis determined that down-regulation of protein expression is one of the components related to kiwifruit ripening inhibition by O 3 , as O 3 causes widespread down-regulation of protein abundance of ATP-citrate lyase, kiwellin and pectin acetylesterase precursor  [17, 19]. Further research is necessary to characterize kiwifruit ripening and the specific roles of O 3. This study thoroughly investigates 1-MCP and O 3 signaling in kiwifruit ripening physiology through a systematic analysis at the physiological and molecular level. Physiological data collected during ripening when fruits were exposed to either ambient air or exogenous ethylene are combined with proteomic and transcriptional approaches.
Kiwifruit protein changes and functional classification To characterize the current biological system, large scale analysis of kiwifruit proteome was performed in the outer pericarp tissue (green flesh) of kiwifruit stored for 6 months and subsequently ripened 8 d at 20 °C (Figs. 1  and 2 ). Following comparative 2DE-analysis (Fig. 4a, b ) and nanoLC/MS/MS, we identified 127 proteins that differentially accumulated among treatments, of which 48 were up-accumulated and 79 were down-accumulated (Fig. 4b ). Identified proteins were predominantly related to disease/defence (39. 2%), followed by energy (20. 8%), protein destination/storage (7. 5%), cell structure/cell wall (5. 8%) and signal transduction (5%) (Fig. 4b ). A complete list of the protein identification, including peptide sequences, accession number, subcellular localization and matching criteria is presented in Additional file 4: Table  S1.
9b ). BiNGO 2. 44  [21]  software was used to predict statistically significant categories in over-or under-represented biological pathways and molecular functions of kiwifruit undergoing ripening inhibition and stimulation (Fig. 10 ). The enriched Gene Ontology (GO) lists of biological pathways (Additional file 7: Table  S2 ) and molecular functions (Additional file 8: Table  S3 ) of identified and annotated kiwifruit proteins are provided. The statistically significant over-represented biological pathways in ripening inhibited kiwifruit were the response to stress (p = 9. 78E-06) and the response to cadmium and metal ion (p = 2. 53E-05 and 6. 34E-05, respectively) (Fig. 10a , Additional file 7: Table  S2a ). In kiwifruit treated with ethylene in order to stimulate ripening, the major groups were the response to stress (1.
Immediately after 1-MCP treatment, fruits of both groups were cold-stored (0 °C, 95% RH) in two separate cold rooms in which ethylene was oxidized by catalytic ethylene oxidation (Swintherm model BS 500, Fruit Control Equipments s. r. l. , Milano, Italy). Cold room atmosphere was ambient (control) or enriched with 0. 3 μL L -1 ozone through a dedicated system of continuous ozone generation and monitoring (oxygen generator model SEP-100, ozone generator model COM-AD-04 and ozone analyser model MP-6060, Anseros Klaus Nonnenmacher GmbH, Tübingen, Germany). Ethylene concentration in the cold storage rooms was monitored and was below the accepted threshold concentration for commercial kiwifruit storage (10 nL L -1 ) and not significantly different from each other (data not shown). After 2, 4 and 6 months, fruits were removed from cold storage and held at 20 °C (90% RH), where kiwifruit ripening was analyzed either immediately, or after 2, 4, 6, 8, 10, 12 and 14 d.
Kiwifruit ripening physico-chemical changes Firmness of pericarp and core tissue was determined using a fruit texture analyzer (model 53,205, T. R. Turoni srl, Forlì, Italy) and expressed as newtons (N) following the methodology previously described  [4]. Soluble solids concentration and TA were assessed as described  [4]. Dry matter content was measured in 2 mm thin cylindrical slices from 3 biological replications of 10 fruits as described  [44]. Mean values of physicochemical data (3 biological repetitions) were subjected to analysis of variance (ANOVA) and least significant differences (LSD) (P = 0. 05) calculated using the statistics package SPSS 22. 0 for Mac OS X (SPSS, Chicago, IL, USA).
Protein in-gel digestion and identification by mass spectrometry Selected spots of interest on the 2D-gels were stained, isolated and tripsin digested as described  [4, 19, 49]. Database searches were conducted against the Cornell University kiwifruit protein database (http://bioinfo. bti. cornell. edu/cgi-bin/kiwi/download. cgi) containing 39,004 protein sequences and the National Center for Biotechnology Information (NCBI) databases using BLASTp analyses and MASCOT software as described  [4, 19]. Validation of significant differences through the two-way hierarchical clustering was done with Permut Matrix software. Zero-mean and unit-standard deviation was used for the row-by-row normalization of data. Analysis was performed using Pearson's distance and Ward's algorithm. Identification criteria, among the positive matches, included at least 2 different peptide sequences of over 6 amino acids with an individual score above 20.
Study design After obtaining the approval of the Johns Hopkins Institutional Review Board, we conducted a cross-sectional, questionnaire-based survey of mental and physical health among house staff entering clinical residency training programs at Johns Hopkins Hospital in June 2009. Incoming house staff were invited to participate during orientation by completing a confidential, voluntary questionnaire. In addition to the questionnaire, data regarding demographic characteristics as well as non-fasting serum lipid profiles were obtained from routine University Health Services intake data. All participants provided written informed consent.
Data analysis Data were summarized as percentages for Likert items or mean (± standard deviation) for non-Likert items. Results were analyzed overall and between females and males using chisquare and t-test for categorical and continuous variables, respectively. When assumptions were not met for these statistical tests, Fisher's exact or Wilcoxon rank-sum test were used instead as appropriate. All analyses were conducted in SAS (SAS Institute Inc. , Cary, NC).
Materials and methods Data were gathered prospectively from the National Hernia Repair Register in Poland (KROPP-http://kropp. org. pl), which is an IT tool available to surgeons in Poland that aims at collecting detailed data from patients undergoing surgical treatments. Participation in the register is voluntary. In the database, answers to more than 92 meticulous questions are recorded; participation is mainly dedicated to centers interested in herniology. The data were collected prospectively from 146 patients who underwent TAPP repairs in the general surgery department within the last 3 years (from 1st Nov 2013 to 31st Oct 2016). The exclusion criteria were of age below 18 years, incarcerated hernia surgery, and conversion to open surgery. The collected data included information regarding patients' age, sex, occupation, sport activities, hernia duration, incarceration incidents, and hernia size.
Combined effects of most important water quality parameters on MFI 40 The combined effects of the three most important parameters, namely turbidity, biopolymers and conductivity, on MFI 40 values were investigated using the method of response quadratic surface regression. This regression method was used because it could deal with the two-order main effects and two-way interaction effects of the variables  (Hill & Lewicki ). Based on the 42 datasets of various SEFs collected, three quadratic response surface regression equations illustrated in Equations (  5 )-(  7 ) were generated to interpret the combined effects of turbidity/DOC, turbidity/chloride and DOC/chloride on MFI 40 , respectively. R 2 values of these regressions were close to 0. 6, which indicated the reliability of these regressions.
The filtration cycle and membrane material were identical to that of the laboratory-scale ZeeWeed-1 unit. The fouling performance of these two systems was assessed by fouling rate, which was calculated as the slope of TMP increase with time over the filtration process. As suggested by Doyen et al. (), the filtration and fouling phenomena that occur during this short time interval would influence the long-term fouling. The fouling rate was then correlated to feed the fouling index measured at the same time. Establishment of fouling predicting approach by MFI 40 and operating flux To establish a fouling predicting model based on the feedwater MFI 40 and flux, a model-building dataset of 13 filtration runs fed by various makeup feedwaters at different fluxes was designed according to the Box-Behnken design.
Biochemical Enzyme Assays. A subset of F1 An. funestus generation (nonexposed to insecticide) stored at -80 ∘ C until use was used for biochemical enzyme assays. Enzymatic activities of cytochrome P450, esterases ( and ), and glutathione S-transferases (GST) were measured according the protocol described by Brogdon et al. [29]  and by Hemingway et al. [30] , and slightly modified by Sangba et al. [31]. Absorbance was measured using a spectrophotometer type "Multiskan GO and SkanIt Software/Serial number 1510-05171" (https://www. thermofisher. com/us/en/home/life-science/lab-plasticware-supplies/lab-plasticware-supplies-learning-center/lab-plasticware-supplies-resource-library/skanItsoftware-protocols-multiskan-go. html). In the absence of An. funestus susceptible strain, the An. arabiensis strain from the Institut Pasteur de Madagascar known to be susceptible to all insecticides was used as control  [28].
Data Analysis. For each insecticide, the percentage of KD and MR was determined. Since mortality in negative controls was always under 5%, no adjustment was performed for treated batches. The WHO 2017 criteria were used to evaluate the status of insecticide resistance (i. e. , 98-100% mortality indicates susceptibility and <98% mortality indicates that further investigation is required to confirm resistance)  [27]. Fifty and ninety-five percent KD times (KDT 50 and KDT 95 , respectively) were computed with probit regression models. Mortality rates expressed in (%) and 95% confidence interval were compared using Fisher exact test. The enzymatic activities of wild An. funestus were compared with that of the An. arabiensis strain from the Institut Pasteur de Madagascar known to be susceptible to all insecticides by Mann-Whitney test.
Acknowledgments We are grateful to  Mrs. Ann Allen  and  Dr Astrid Knoblauch  who reviewed previous versions of this manuscript. We also thank  Dr Paul Howell  and  Dr Melissa Avery  from  CDC-Atlanta  for CSP antibodies, PCR primers, and protocols. We also thank the personnel of  Unité d'Entomologie Médicale at Institut Pasteur de Madagascar  and the Tsararano villagers for their cooperation throughout the study. This work was supported by the  Department of International Affairs, Institut Pasteur International Network  ( G4   Group ), awarded by  Ousmane NDIATH.
ATLG/ATG Dose Dose and timing of ATLG/ATG administration vary substantially among transplant centers  (Bacigalupo et al. 2001; Finke et al. 2009; Walker et al. 2016; Kröger et al. 2016; Soiffer et al. 2017). The currently used doses of ATLG/ATG are calculated and validated in clinical trials, according to body weight. A strong rationale and some preliminary data  (Admiraal et al. 2017)  suggest that calculating the ATG/ATLG dose according to the cellular target, i. e. , the number of total lymphocyte before infusion of the first dose, can provide the optimal drug exposure and therefore maximize the benefit (GVHD decrease) over the potential risks (increase of relapses and infections). Since ATLG and ATG are different preparations arising from different manufacturing processes and different pulsed antigens, no dose equivalence can be established.
Sample A total of 441 participants formed the study population, with the sample collection taking place over one year between the months of November 2014 and November 2015. Data collection was performed by passive detection in the municipality's Basic Health Units, following phenotypic diagnoses using thick blood smears and prior to treatment. For the uninfected group, samples were also collected in the same municipality so that the participating individuals were froma similarbackground exposure conditions. After a parasitological evaluation, the subjects were divided into the following four groups: 1) patients with an intestinal parasite and malaria co-infection (n = 117); 2) patients with malaria who were negative for intestinal parasites (n = 30); 3) patients without malaria who were positive for enteroparasites (n = 143); and 4) patients who were negative for both (n = 151).
Statistical analysis Each volunteer's epidemiological data results, which were obtained from the questionnaire, was stored in an Epi-Info 3. 5. 1 database (CDC, Atlanta, GA, USA). The values for each group (malaria, co-infected, enteroparasite and endemic control), as well as the subgroups (helminths, protozoa and helminth-protozoa association), were expressed as a percentage. The age, residence time in Oiapoque (years) (RT), number of previous malaria episodes (NPE), period since last malaria (months) (PLM), haemoglobin levels (g/dL), parasitaemia (parasites/ L) and gametocytes were expressed as medians (1st and 3rd Quartile) using BioEstat 5. 3 statistical software. The differences between groups with regard to age, RT, NPE, PLM and haemoglobin were calculated using Tukey's test based on a one-way analysis of variance (ANOVA).
The Project obtained financial assistance from the following institutions with the responsibility of the respective researchers: Supported by the  Research Program  for the Unified Health System (PPSUS):  Shared Health Management ,  PPSUS, AmapaResearch Support Foundation AmapaState Support Support  well as on the profile of the cytokines that characterize the Th1 and Th2 patterns. However, co-infection increased TNF-α and IL-10 levels. Foundation (Public Invitation for Promotion of Research  001/2013 EPF 00007631 ) With resources for the support in the Collection and laboratory analyzes, under the responsibility of the researcher Margarete do Socorro Mendonca Gomes; Supported by the  laboratory of Microbiology and Immunology of the Federal University of Para  ´in the immunological analyzes of PvMSP119, under the responsibility of the researcher Maristela Gomes Cunha; Supported by the  Immunogenetic / Parasitology Malaria Laboratory of the Evandro Chagas Institute  for the analysis of cytokines under the responsibility of the researcher Ricardo Luiz Dantas Machado; Supported by the  Postgraduate Program in Biology of Infectious and Parasitic Agents of the Federal University of Para  ´for logistical support and general support under the responsibility of the researcher  Adriano Penha Furtado.
Erythropoiesis-stimulating agents (ESAs) are man-made forms of erythropoietin used in the treatment of anemia. This quick-scoping review of systematic literature reviews (SLRs) was conducted to define the clinical, economic, and health-related quality of life (HRQoL) outcomes for short-acting and long-acting ESAs in patients with chronic kidney disease-induced anemia (CKD-IA) and patients with chemotherapy-induced anemia (CIA). Embase, Medline, and the Cochrane Database of Systematic Reviews were searched from their establishment until October 2017. SLRs related to the use of short-acting and long-acting ESAs in the treatment of CIA and CKD-IA were included. Forty-eight studies met the inclusion criteria. The evidence suggests little difference in efficacy, HRQoL, and safety outcomes among ESA types.
The prevalence of CKD varies with age, gender, and ethnicity. A meta-analysis reported a mean prevalence of CKD of 7. 2% in persons aged ≥30 years and 23. 4%-35. 8% in persons aged ≥64 years  (Zhang and Rothenbacher, 2008). Anemia is a common complication of CKD that occurs due to the inability of the kidney(s) to produce enough erythropoietin to stimulate the production of RBC  (Alsalimy and Awaisu, 2014; Bonafont et al. , 2009; Vinhas et al. , 2012; Phrommintikul et al. , 2007). The National Health and Nutrition Examination Survey III study collected data in 2007-2010, which showed anemia was twice as prevalent in patients with CKD (15. 4%) compared with the general population (7. 6%). The prevalence increased from 8. 4% at CKD stage 1 to 53. 4% at stage 5  (Stauffer and Fan, 2014). Anemia will eventually occur in virtually all patients with CKD when they reach end-stage kidney disease (ESRD)  (Strippoli et al.
Search strategy The methodology describing the conduct of QSRs has been reported previously  (Pham et al. , 2014). In brief, the Embase® and MEDLINE® electronic databases were searched using the OvidSP interface from database inception to October 3, 2017. The Cochrane Central Trials Register, Database of Systematic Reviews, and other Cochrane Library assets were also searched over the same timeframe. All search strategies were conducted on October 3, 2017, with no restriction on publication date. The search strategy identified SLRs related to the use of short-acting and long-acting ESAs in the treatment of CIA and CKD-IA. These included terms for interventions of interest (i. e. , "erythropoietin", "erythropoiesis-stimulating agent", "ESA", "epoetin", and "recombinant erythropoietin") in CKD-IA and in CIA (i.
Study selection, data extraction, and study categorization A reviewer screened titles and abstracts of all studies identified according to the inclusion and exclusion criteria. A second reviewer performed a quality check of 10% of all screened studies to ensure compliance with the eligibility criteria. A senior researcher resolved any discrepancies. A similar approach was taken for extraction of all relevant data from the included studies. Where available, data extracted from full-text SLR publications included study author, ESA study type, time frame, sample size, study population (e. g. , age range, gender, comorbidities), primary treatment, comparator, outcomes (i. e. , outcomes for efficacy, HRQoL, safety, health resource utilization, convenience, and adherence), and summary/conclusions of the original SLR.
Optical Characterization of Flat and ASAHI Back Reflectors Before we proceed to study the optical properties of our nanostructured BRs, reference flat Ag/ZnO on glass substrates were fabricated and reflectance data were measured. Figure  3  shows the reflectance data from sputtered ZnO (0 to 160 nm) on 200 nm sputtered Ag on the glass. Figure  4a  shows the reflectance data of ASAHI BR with 0, 50, and 100 nm of ZnO. Figure  4b  shows the BEMA simulation model we used. Figure  4c, d.
Optical Characterization of Flat and ASAHI Back Reflectors Before we proceed to study the optical properties of our nanostructured BRs, reference flat Ag/ZnO on glass substrates were fabricated and reflectance data were measured. Figure  3  shows the reflectance data from sputtered ZnO (0 to 160 nm) on 200 nm sputtered Ag on the glass. Figure  4a  shows the reflectance data of ASAHI BR with 0, 50, and 100 nm of ZnO. Figure  4b  shows the BEMA simulation model we used. Figure  4c, d  show the simulated results for various thicknesses of the rough interface layer L2.