dataesr/scientific-paragraphs-categorization huggingface dataset:
ANALYSES AND DATA REDUCTION Neuroimaging data were pre-and post-processed using SPM5 (Wellcome Department of Cognitive Neurology, London, UK, implemented in Matlab 7. 1; MathWorks, Inc. , Natick, MA, USA). Functional data were realigned, motion corrected, re-sliced, and coregistered to the individual T1 volume by means of segmentation fitting. Analyses were done on spatially normalized (stereotactically transformed into MNI ICBM152-space) and smoothed images (8 mm full width at half maximum (FWHM) Gaussian kernel) with a final voxel size of 3 × 3× 3 mm. In this first level analysis, condition-specific beta values (parameter estimates) were estimated for both the body odor condition and odorless air condition on an individual level by entering the two runs as separate sessions and using the full 20 s blocks as event of interest for each condition.
001. We subsequently performed directed region of interest analyses within areas of significance in the whole group analyses by extracting parameter (beta) values at the specific neostriate areas of interest using an 8 mm search sphere. We then assessed differences within these areas, based on the extracted parameter estimates, using pairedsamples t-tests and Pearson correlations in the statistical software SPSS. Finally, as a control for general group differences, we assessed whether the two groups differed in respect of their neural response to the clean air condition within a separate model using a simple t-contrast to maximize power. All imaging statistical analyses were thresholded using a cluster criterion of three voxels and whole brain analyses corrected using a false discovery rate (FDR) of p < 0.
ACKNOWLEDGMENTS Supported by the  DDELTAS (Dijon-Dresden European Laboratories for Taste and Smell -LEA 549 ), underwritten by the  Centre National de la Recherche Scientifique-Paris  and the  Technische Universität Dresden , and awarded to  Benoist Schaal  and  Thomas Hummel. Johannes Frasnelli  is supported by a postdoctoral fellowship by the  Canadian Institutes of Health Research (CIHR).
This electrode was connected to a taste amplifier (TastePROBE DT-02,  [31] ), which triggered upon contact a 2 seconds recording bout with a 16 bits data acquisition board (DT9803, Data Translation, USA) sampling data at 10 kHz, under the control of a custom program (dbWave;  [32] ). Data were further amplified (6500) and filtered (10-2800 Hz) with a CyberAmp 320 amplifier (Axon Instruments, USA). The number of spikes occurring during each recording was detected using dbWave and exported to a spreadsheet for further analysis. Unpaired Student t-tests were used to check for significant differences between the indicated pairs of data.
SBS Patients Ethics statement: The Human Investigations Committee of Hospital Saint-Louis in Paris approved the study (n: 031048) in January 2004. All patients gave their written informed consent to participate in this study. This prospective study was performed between January 2006 and January 2011. Patients were enrolled and monitored in our nutrition support unit, an approved centre for intestinal failure and Home Parenteral Nutrition, located at Lariboisiere and Beaujon hospitals (Paris and Clichy respectively). Clinical and demographic information were collected from the case records. Data included: sex, age, and medical history, SBS aetiology, characteristics of past surgical procedures, and characteristics of intestinal tract. All patients received gastric anti-secretory drugs (IPP) but none had pancreatic enzyme treatment and cholestyramine.
Dietary The patients were asked to maintain their usual intake. Under the supervision of trained dieticians, patients noted the type, amount or weight of foods they ingested at each meal, including snacks and nibbling for 3 days during the week preceding sample collection. The daily intake of total calories, proteins, carbohydrates (total, complex and simple), fat, fibre and alcohol were calculated with BilnutH software (Bourgerette P, Rolshansen M. BILNUT 4. 0. SCDA Nutrisoft. Le Hallier 37390 Cerellers, France). The mean intake for each macronutrient and fibre were expressed as the percentage of total g/day oral intake.
Biological analysis Routine biological data included serum albumin, transthyretin, electrolytes and C Reactive Protein (CRP). The anion gap was calculated from measured electrolytes as the sum of serum chloride and bicarbonate concentrations subtracted from the sodium and potassium concentrations [(Na + +K + )-(Cl 2 +HCO3 2 )]. Faecal sam-ples (200 mg fractions) were stored in sterile tube at 280uC until further processing.
Lactobacillus-specific primer design Primers targeting different Lactobacillus species (L. mucosae, L. delbrueckii subsp. bulgaricus, L. crispatus, L. gasseri/johnsonii, L. reuteri) were based on specific region of the 16S ribosomal DNA sequences aligned using the Blastn program of NCBI database and design using Primer-express Version 2. 0 (Applied-biosystems) (Table  1 ). Primer specificities were challenged in silico against sequences in Ribosomal Database project II using the probe match program. Primer specificities were then firstly assessed by real-time qPCR amplification against DNA from dominant faecal species or closely related species and secondly using PCR amplification followed by visualisation on agarose gel (Table  S1 ). Amplification and detection were carried out in 96-well plates with Syber-Green PCR 26 master mix (Applied-Biosystems).
Experimental conditions of real-time qPCR Total bacterial DNA was extracted from 0. 15 g to 0. 2 g of faecal samples using a bead-beating method G'NOME DNA extraction kit (Mp Biomedicals, Illkirch) as described by Furet et al  [34]. Faecal DNAs were dissolved in 150 ml Tris-EDTA buffer and stored at 220uC. The real-time qPCR was performed using the ABI7000 sequence detection system apparatus and 7000 system software version 1. 2. 3 (Applied-Biosystems). Amplification and detection were carried out in 96-well plates with Taqman universal 26PCR master mix or with Syber-Green PCR 26 master mix (Applied-Biosystems). Each reaction was run in duplicate in 25 ml with 0. 2 mM primers, 0. 25 mM of each probe and 10 ml DNA samples. Amplifications were carried out using the following profile: 1 cycle at 95uC for 10 min, followed by 40 cycles of 95uC for 30 s, 60uC for 1 min.
Standard curve was generated by plotting cycle threshold (Ct) versus cell number of reference strain in the qPCR assay. Using cycle threshold (Ct) values in the linear range of the standard curve, faecal bacterial cells were interpolated from each standard curve generated in the same experiment. Then, results were expressed in bacterial cell/g faeces as mean and standard errors. When results were expressed in percentage of total bacteria, bacteria (expressed in bacterial cell/g faeces) was compared to all bacteria (expressed in bacterial cell/g faeces) and expressed as %. two-sided. The critical level of statistical significance was set at p,0. 05. Data were analyzed with the SAS 9. 1 statistical software for windows (SAS Institute Inc. , Cary. NC).
Acknowledgments We thank  Harry Sokol  for their advice and  Jean Charles Miquel ,  Jerome Bailleux  and  Marine Le Roux  for their technical assistances (AgroPar-isTech, MICALIS  UMR1319 ,  Commensal and Probiotics-Host interactions Laboratory, Jouy-en-Josas, France). We acknowledge  Amy Whereat  for her assistance in proofreading and editing the manuscript.
The genus Haemaphysalis is mostly prevalent in tropical areas and is characterized by small size inortate ticks with short mouthparts (brevirostrate)  [6]. Of particular concern is the impact of H. longicornis in the livestock industry in Japan and other East Asian countries, mainly due to the transmission of the anemia-causing intraerythrocytic protozoa, Theileria sergenti and Th. buffeli. Two isoforms of a thrombin inhibitor, madanin-1 and madanin-2, sharing 79% amino acid sequence identity, were identified in salivary gland cDNA libraries of H. longicornis ticks  [7, 8]. Given the lack of sequence similarity to other inhibitors, madanins were classified as a distinct family -family I53 -of the MEROPS database  [9]. Madanins display two clusters of acidic residues in the N-terminal two thirds of their amino acid sequence, conferring on them an overall acidic character (theoretical pI of 4.
Thrombin inhibition assays The inhibition of the amidolytic activity of titrated  [20]  bovine a-thrombin (GE Healthcare) was followed spectrophotometrically using Tos-Gly-Pro-Arg-p-nitroanilide (Roche) as chromogenic substrate. Assays were performed using 1 nM thrombin and increasing concentrations (0-200 mM) of substrate in the presence of recombinant proteins (0-800 nM). Reactions were carried out at 37 uC in 50 mM Tris-HCl pH 8. 0, 50 mM NaCl, 1 mg/ml bovine serum albumin, and monitored at 405 nm for 1 hour on a Synergy2 multi-mode microplate reader (Biotek). The reactions were started by addition of enzyme. The inhibition constant, K i , was determined by fitting the data to the competitive inhibition model (GraphPad Prism 5), with R 2 parameters of 0. 989 (madanin-1) and 0. 992 (madanin-2).
Data collection and processing Crystals were harvested from the CrystalQuick plates, cryoprotected in mother liquor supplemented with 35% PEG 3350, and flash-cooled in liquid nitrogen. Diffraction data from a single cryocooled crystal (100 K) were collected at beamline ID29  [21]  of the ESRF (Grenoble) on a Pilatus 6 M detector (Dectris) using a wavelength of 0. 9763 A ˚. One thousand frames were measured in 0. 2 u oscillation steps with a 611. 6 mm sample-to-detector distance and 0. 125 seconds exposure per frame. Diffraction data were integrated with XDS  [22] , scaled with XSCALE  [23]  and reduced with utilities from the CCP4 program suite  [24]. Data collection and refinement statistics are summarized in Table  1.
Structure determination and refinement The structure of the human a-thrombin?madanin-1 complex was solved by molecular replacement with Phaser  [25]  using the coordinates of free human a-thrombin as search model (PDB entry 3U69  [26, 27] ). Alternating cycles of model building with Coot  [28]  and of refinement with PHENIX  [29] _ENREF_45 were performed until model completion. For one thrombin molecule the final model comprises residues T Gly1F to T Asp14L (chain L, light chain) and T Ile16 to T Gly149D and T Gly150 to T Glu247 (chain H, heavy chain). For the other thrombin molecule the final model comprises residues T Ala1B to T Asp14L (chain B, light chain) and T Ile16 to T Glu146 and T Gly150 to T Phe245 (chain A, heavy chain). A fragment of madanin-1 comprising M Ala51 to M Arg54 (Ala-Lys-Pro-Arg) was modeled (chain M) in complex with one of the protease molecules present in the asymmetric unit (chains L and H).
Crystal structure of thrombin in complex with a postcleavage madanin-1 fragment The three-dimensional structure of human a-thrombin in complex with a cleavage fragment of madanin-1 was determined by X-ray crystallography at a resolution of 2. 6 A ˚. The crystals belong to the orthorhombic space group P2 1 2 1 2 1 and contain two proteinase moieties and a madanin-1 fragment in the asymmetric unit. Each of the two proteinase moieties adopts a structure very similar to that of active ligand-free human thrombin (  [27] , PDB entry 3U69), with a r. m. s. d. of 0. 33-0. 43 A ˚(249-251 aligned Ca atoms) for thrombin chains AB and LH, respectively, with most differences being attributable to crystal packing effects. One of the thrombin molecules (chains A and B) is ligand-free, while at the active site of the other proteinase molecule (chains L and H) there is interpretable electron density for madanin-1 residues Ala51 to Arg54 (Figure  7A ).
This work was funded by national funds from Fundaca ˜o para a Cieancia e a Tecnologia (Portugal) through grants  PTDC/BIA-PRO/70627/2006  ( EU-FEDER  funding through the  Operational Competitiveness Programme (COMPETE)   FCOMP-01-0124-FEDER-007076 ), and  NORTE-07-0124-000003  - Cell Homeostasis Tissue Organization and Organism Biology (EU-FEDER  funding through  Programa Operacional Regional do Norte (ON. 2 -O Novo Norte) ,  under Quadro de Refereancia Estrategico Nacional (QREN) ), and the postdoctoral fellowship  SFR/BPD/46722/2008  (to A. C. F. ). The funding bodies had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Setting and participants The ICU has 10 single-bed rooms and admits about 400 patients each year. Family members can visit around the clock, stay as long as they wish, and participate in patient care with the nurses. The ICU has a patient/nurse ratio of 2. 5. The day team includes five full-time physicians and four residents. The criterion for including ICU workers in the study was experience with ICU diaries. To develop a comprehensive understanding of our study question, we used a sample of ICU healthcare workers who acquired experience with ICU diaries between May 2008 and November 2009, the earliest period of diary use in our ICU. In each category of participants (physicians, nurses, and nursing assistants), new participants were included until data saturation occurred.
Collection and analysis of data In December 2009, we used semistructured in-depth interviews to assess ICU workers' perceptions of the 59 diaries kept in our ICU. The characteristics of the patients for whom diaries were established are described elsewhere  [1]. The interview was performed in the ICU in a quiet place by using an interview guide (Table  1 ) built by three physicians (MGO, CB, FP) and three ICU nurses (NC, SA, SB). All interviews were performed by the same physician (MGO), audio-recorded with the interviewees' permission, transcribed verbatim, and evaluated by using interpretative phenomenologic analysis  [11]. First, the transcripts were checked for accuracy against the audio recordings. Each transcript was read several times and then coded to identify initial themes, which were noted in the margins.
Acknowledgements We thank  A. Wolfe, MD , for helping to prepare this manuscript and the healthcare workers of our ICU for their participation. This study was supported by the  French Society for Critical Care (SRLF). The SRLF had no role in the design or conduct of the study; in the collection, management, analysis, or interpretation of the data; or in the preparation, review, or approval of the manuscript. All authors were independent of the funding institutions.
Analysis of PGG Content in MSKE The quantitative determination of PGG content in MSKE was carried out by using HPLC (Spectra System; Thermo Separation Products, Yokohama, Japan) equipped with a P1000XR pump, a SCM1000 vacuum degasser, an AS3000 autosampler and a UV6000 LP detector. The data were recorded and analysed with Chromquest ® PC software (Thermosystems Inc. , Lombard, IL, USA) with the Spectra System SN4000 unit. The Gemini-NX column (C18; 250 × 4. 6 mm i. d. , particle size 5 µm; Phenomenex Inc. , Torrance, CA, USA) with a guard column was used as a stationary phase. The elution gradient for the HPLC analysis consisted of two solvent compositions: 0. 48% phosphoric acid in a mixture of 80/20 (v/v) water/acetonitrile (solvent A) and 0. 48% phosphoric acid in a mixture of 70/30 (v/v) water/acetonitrile (solvent B).
Particle Size and Shape The size and shape of the dry beads were measured using an optical microscope (Motic ® BA 300, Wetzlar, Germany). In each batch, thirty beads were randomly selected for the study. After images of the beads were captured through a digital camera (Moticam 2300) connected with a microscope, the length and breadth of each bead were measured using the pre-calibrated image analysis program (Motic Image Plus, version 2. 0). The size of each bead was calculated from the average of these two dimensions  [25]. The average size of the beads from each batch was expressed as the mean diameter (mm) ± standard deviation (SD). The shape of the beads was represented by the ER, which was the quotient of length to breadth of the beads  [25]. An ER value of unity (ER = 1) represents a perfect spherical shape, while ER values between 1 and 1.
( a) pK sp values of the metal selenide complexes, taken from Seby et al. [12] , correspond to the equilibriums M 2+ +Se 2-u MSe (divalent cations) or 2 Ag + +Se 2-u Ag 2 Se (silver ion). Of note, in many cases, different pK sp values are available in the literature for a same complex. ( b) In the case of Fe 2+ , the pK sp value that we determined in this study from data in Fig. 2  is also shown. ( c) Sodium selenide (50 mM) was added to a mixture of metal ion (100 mM) and of either EDTA or NTA (1 mM). The sample was incubated anaerobically in a 50 mM MES buffer (pH 6. 0) for 3 h. Metals for which colloid formation was no longer observed in the presence of the chelator are labeled with ''-'' (minus). For the metals which still produced colloids, t 50 was measured. ( d) Effective equilibrium constants of the chelator-divalent metal complexes at pH 6.
After 10 min incubation at room temperature (180 min in the case of iron), the optical densities of the solution were measured at 340 nm. In the cases of cadmium, cobalt, copper, mercury, nickel, lead, silver and zinc, data were fitted to a onesite binding equation (least square minimization) assuming that the affinities between the constituents involved in complex formation were infinitely high. In the case of iron, data were fitted to the solubility product equation ([Fe 2+ ][Se 2-] = K sp ). Obtained pK sp value was 18. 560. 2. Manganese, magnesium and calcium did not modify the optical density of the sodium selenide solution. Data with manganese are shown as an example. doi:10. 1371/journal. pone. 0054353. g002 free silver ions (20 mM Ag + ) to kill all cells. Indeed, toxicity of free silver cations against S.
Figure2. Formation of metal-selenide colloids. To monitor the formation of metal-selenide colloids, mixtures containing sodium selenide (50 mM) and the indicated metal salt concentrations were prepared inside an anaerobic glove box. After 10 min incubation at room temperature (180 min in the case of iron), the optical densities of the solution were measured at 340 nm. In the cases of cadmium, cobalt, copper, mercury, nickel, lead, silver and zinc, data were fitted to a onesite binding equation (least square minimization) assuming that the affinities between the constituents involved in complex formation were infinitely high. In the case of iron, data were fitted to the solubility product equation ([Fe 2+ ][Se 2-] = K sp ). Obtained pK sp value was 18. 560. 2. Manganese, magnesium and calcium did not modify the optical density of the sodium selenide solution.
Acknowledgements. We thank  J Grassi  for his kind gift of Sha31 antibody. We gratefully acknowledge the mass spec team of  Z Lam  for skillful methodological assistance,  V Mutel  and  A Baudry  for critical reading of the manuscript. This work was supported by funds from the  Agence Nationale de la Recherche  ( ANR-06-BLAN-0288  and  ANR-10-BLANC-131201 ) and  INSERM (OK)  and a  EU grant  ( PRIORITY CT2009-222887 , JMT). EP was supported by a  Neuroprion Start-up  grant and a fellowship from the  Fondation de la Recherche Medicale. OK is a professor at the  UniversiteParis Sud.
Secondary outcome measures For clinical practice: Appropriate call-in of the NST; For clinical impact on children: -Incidence of complications linked to nutritional status during the hospital stay; -Evolution of nutritional status during the hospital stay; For economic measures: Mean length and cost of stay. Data concerning primary and secondary outcome measures were available at the patient level and were extracted from the medical records by an independent research team. The research team received handouts and training to become familiar with data collection. Data relative to the length of stay and the cost of treatment were obtained from the hospital's claims databases. The same data were gathered for the observational study and for the interventional study. In addition, we monitored the intervention process.
Data analysis of the cluster randomised trial All statistical analyses will be performed in Statistical Analysis System (SAS W ) software version 9. 2 (SAS Institute, Cary, NC). Analyses will be performed according to the intention-to-treat principle. All malnourished children screened in all clusters allocated to the intervention or control arm will be included in the analysis. In the event of multiple hospitalisations for the same patient, only the first stay of the study period will be retained. Baseline characteristics will be summarised by preand post-intervention period and treatment group using frequency (percentage) for categorical variables and means (standard deviation) for continuous variables. Clustering will be taken into account: a generalized estimated equations (GEE) approach will be used to analyse the impact of the multifaceted intervention on primary and secondary outcomes  [20].
A GEE Poisson regression model will be performed for count data (as number of daily weighings) and GEE logistic regression models for binary variables (as investigation of malnutrition etiology, management by dietician, nutritional supplementation, complication occurrence during hospitalisation). The paediatric departments will be entered as the clustering variable into each model. For the GEE Poisson, the length of stay will be used as an offset. An exchangeable correlation matrix will be specified to account for potential within-cluster homogeneity in outcomes: all pairwise correlations among children within departments are the same. Robust estimates of the standard errors will be obtained which ensures, provided the model is correct, that the estimates are consistent even if the working correlation matrix is not correct.
The impact of the multifaceted intervention will be adjusted for individual level characteristics included age, severity of malnutrition, comorbidities occurrence, complications occurrence and length of hospital stay after controlling for the collinearity between covariables. A Wald statistic will be used to test the significance of each coefficient in the model. The intervention effect will be expressed as adjusted odds ratio with its 95% confidence interval. GEE regression models will be fit using the SAS PROC GENMOD. Corresponding overall intra cluster correlation (ICC) coefficient was also estimated from GEE method using the CORRW option from the SAS PROC GENMOD. For each arm, comparison of outcome changes between pre-and post-intervention periods will be computed using a GEE regression model, integrating the clustering of children by department.
Time frame The six month observational study was carried out from September 2009 to February 2010. The six clusters were randomised in February 2010. Data from the randomised trial were gathered from March 2010 to August 2011 (18 months). The statistical treatment of these data is currently underway. Health care workers' access to the computerised malnutrition screening system was established at the beginning of the intervention study, in the clusters of the intervention arm. The awareness campaign for the health care workers and the leadership based strategy were conducted intensively during the first three months of the intervention study, in the clusters of the intervention arm. A support phase was conducted throughout the entire intervention period: this included the training of medical residents, the issuing of reminders to the teams regarding the use of the algorithm, and the organisation of department meetings in order to discuss the cases of malnourished children.