dataesr/scientific-paragraphs-categorization huggingface dataset:
Two ratios (4:1 and 1:1) of the CALNN: CCALNN-HA2 or CALNN: HA2-NNLACC peptides were used to form the gold nanoparticles self-assembled monolayers. HeLa cells were then incubated separately with one of the resulting four types of nanoparticles (10nm diameter, 6nM) for 4h, fixed and imaged by TEM. The electron microscope images presented in Fig. 4A-D  (datasets available on figshare  [72] [73] [74] [75] ) do not show significantly different behaviours. Indeed, neither of the attachment orientations of the HA2 peptide showed a cytosolic release of the nanoparticles (compare Fig. 4A  to Fig. 4B  and Fig. 4C  to Fig. 4D ), with most of the particles inside endosomes or at their vicinity. For both orientations, varying the quantity of HA2 peptides present on the gold core did not show an improvement of the quantity of free cytosolic nanoparticles.
(F) Quantification of the internalisation of gold nanoparticles for the conditions shown in (A-E), measured via the mean photothermal intensities of individual cells (over 40 cells for each condition, each data point represents one cell). All conditions are significantly different from one another except the pair (1% TAT, 10% dHA2-1% TAT). Dataset available on figshare (10. 6084/m9. figshare. 1088379). doi:10. 1371/journal. pone. 0121683. g001.
(E) Cells incubated with 10% CCALNN-dHA2 + 1% CALNN-TAT coated nanoparticles. (F) Quantification of the internalisation of gold nanoparticles for the conditions shown in (A-E), measured via the mean photothermal intensities of individual cells (over 40 cells for each condition, each data point represents one cell). All conditions are significantly different from one another except the pair (1% TAT, 10% dHA2-1% TAT). Dataset available on figshare (10. 6084/m9. figshare. 1088379). doi:10. 1371/journal. pone. 0121683. g001.
Identification of studies The objective was to conduct a pooled analysis of individual participant data. Studies were eligible to join this collaborative group if they had data on circulating carotenoids, retinol, or tocopherols measured in blood samples collected before the diagnosis of prostate cancer for at least 75 cases (for at least one biomarker under investigation by the collaborative group). Studies were identified through searches using the terms carotenoid, retinol, vitamin A, tocopherol, vitamin E, and prostate cancer on computerized bibliographic systems, including PubMed, Web of Science, Cochrane Library, and CancerLit; through the reference lists of publications identified in this search; and through discussions with colleagues.
Melbourne Collaborative Cohort Study (MCCS): Cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian National Health and Medical Research Council grants 209057, 251553, and 504711 and by infrastructure provided by Cancer Council Victoria. Multiethnic Cohort: Supported by National Cancer Institute grants P01 CA 33619, R37 CA 54281, and 1-UM1-CA164973. Prostate Cancer Prevention Trial: Supported by National Cancer Institute and NIH, CA37429 and P01 CA108964. Prostate testing for cancer and Treatment trial: Funded by the United Kingdom National Institute for Health Research Health Technology Assessment Programme (projects 96/20/06, 96/20/99, www. hta/1230); the views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health.
The University of Bristol Integrated Epidemiology Unit is supported by the Medical Research Council and the University of Bristol. The Bristol Nutrition Biomedical Research Unit is funded by the National Institute for Health Research and is a partnership between the University Hospitals Bristol National Health Service Foundation Trust and the University of Bristol. SU. VI. MAX, SUpplémentation en VItamines et Minéraux Anti-oXydants trial: Supported by the Direction Générale de la Santé (French Ministry of Health) for laboratory assays.
This is supported by the fact that two orders of magnitude less dust were recovered compared with the carbon wall. A special effort was made to accurately quantify the reduction in long-term fuel retention with the JET-ILW, already measured in gas balance experiments, through postmortem analysis. These results were used to validate the WallDYN code  [44]  and to allow a meaningful extrapolation to ITER. The code simulations reproduce both the reduction in fuel retention and the observed migration pattern. The remaining long-term retention is caused by implantation and co-deposition with beryllium and residual impurities. Shortterm retention gained relative importance with respect to the low level of long-term retention and impacts on the recycling properties of both beryllium and tungsten and local plasma properties.
Differentiation of OPCs was assessed by incubation with NP for 24 h and then the media refreshed and differentiation assessed after 4 days in culture, by assessment of myelin basic protein expression (MBP) (species: rat, 1/300 Serotec MCA409S) by immunofluorescence staining as MBP is a main protein component of the myelin sheath and a marker of mature oligodendrocytes, and staining immature OPC with anti-NG2 antibody (species: mouse, 1/100, Millipore MAB5384). All cultures were fixed with 4% PFA for immunofluorescence analysis. Confocal z-stacks were acquired using Leica SPE confocal microscope with a x40 lens, using Leica acquisition software, and analysed using Image J software. For all experiments we carried out 3 experiments (from 3 separate rat litters) with duplicates for each treatment in each.
Measurements and statistics We used the gold standard method of detection and measurement of remyelination e measurement of both the percentage of myelinated fibres within a lesion and the thickness of the myelin sheaths by electron microscopy. To count the percentage of myelinated fibres in the lesion, we took ten photographs from random, non-overlapping fields within each lesion, accounting for at least 1000 axons per mouse, with 5 mice per group (n ¼ 5), and analysed blinded to the treatment group. To measure g-ratios, we traced the axonal circumference and the whole fibre circumference (using a graphics pad and pen) of all myelinated axons in 5 nonoverlapping random fields within the lesion (at least 100 axons per mouse), and divided the two values. Again we used 5 mice per group (n ¼ 5), and analysed the data blinded to the treatment group.
To quantify remyelination, we used the gold standard method of measurement of both the percentage of myelinated axons within the lesioned area and the myelin thickness relative to axon diameter (g-ratio) by electron microscopy. The g-ratio of a normal mature myelinated axon is constant at ~0. 7 since myelin thickness is tightly regulated according to axon size. In the context of remyelination, g-ratios approaching 1. 0 reflect thinner and less mature myelin. The experimental data in Fig. 4  shows representative electron micrographs taken 18d and 25d post lesion for the  three experimental groups (Fig. 4a ). The percentage of myelinated fibres per lesion was significantly higher in the NG2-targeted LIF-NP group (L/T) compared to either the empty-NP (E/T) group or the non-targeted LIF-NP (L/NonT) group at 25 days post lesion (Fig.
We added NP intralesionally, as proof of concept confirming the powerful potential of this delivery system as a targeted approach to deliver bioactive molecules for in situ myelin repair. For translation into clinical use it is notable that NP delivered intravenously can cross the BBB  [29, 30] , at least in rodents, or can be delivered intranasally directly to the CNS  [31, 32]  bypassing the BBB, supporting the concept that intravenous or intranasal delivery of LIF-NP targeted to NG2 may promote remyelination of demyelinated lesions. Moreover, the nanoparticle platform used here is already in clinical trials (e. g. Clinicaltrials. gov NCT01812746, NCT01792479).
Acknowledgements AW is funded by a  Scottish Senior Research Fellowship , and by a grant from the  UK Regenerative Medicine Platform  ( MR/M007588/ 1 ). SR was funded by an  ERASMUS scholarship. SMM is in receipt of  NIHR i4i Award II AR 1109. We very much thank  Steve Mitchell  for his help with electron microscopy. The authors confirm that there has been no significant financial support for this work that could have influenced its outcome.
Data variables, sources of data and data collection Data were collected between April and June 2014. The socio-demographic and clinical characteristics of patients included age, parity, residence (rural/urban), mode of admission (direct admission/referral from health centres), and maternal indication for C-section or MOI. Maternal and neonatal health outcomes were woman alive (yes/no), child alive (yes/no), as reported in hospital medical records. C-section rate was calculated by using the number of c-section performed during the year (numerator) and the expected number of births in the same year (denominator). Unmet obstetric needs (needs of MOI-actual MOI) were computed as follows: MOI represented the number of surgical procedures performed (Fig 1 ) and Absolute Maternal Indication represented the diagnoses established by the health care team (Fig  1 ).
Data analysis Data collected from patient's files was double entered by two independent encoders into a file using EpiData Entry software (version 3. 1, EpiData Association, Odense, Denmark). The two data files were compared and discordances resolved by cross-checking with the paper registers. Data were analysed using STATA 13 software (STATA Corporation, College Station, TX, USA). Frequencies (%) were calculated to describe patients' characteristics and maternal and child outcomes. Pearson's Chi Square (χ2) and Fischer's exact test were used to compare proportions of study outcomes between the two years. The level of significance was set at p = 0. 05 with a 95% confidence intervals.
Acknowledgments This research was conducted through the  Structured Operational Research and Training Initiative (SORT IT ), a global partnership led by the  Special Programme for Research and Training in Tropical Diseases at the World Health Organization (WHO/TDR ). The model is based on a course developed jointly by the  International Union Against Tuberculosis and Lung Disease  ( The Union ) and Medécins sans Frontières. The specific SORT IT programme which resulted in this publication was jointly developed and implemented by: the  Operational Research Unit (LUXOR) ,  Médecins Sans Frontières ,  Brussels Operational Center, Luxembourg; the Centre for Operational Research, The Union, Paris, France; the Centre for International health, University of Bergen, Norway; the institute of Tropical Medicine, Antwerp, Belgium; The University of Nairobi ,  Kenya  and the  University of Chester ,  United Kingdom.
Statistical analysis Linear regression lines of Smurf proportion during aging were determined using at least 16 individual points (4 time points and 4 replicates per time point) in GraphPad Prism version 5. Correlation of the datasets was assessed using the Pearson test for linear regressions as implemented in the software. Comparison of slopes and testing for non-null slope values were done using GraphPad Prism. Median lifespans were tested for significant differences using the Wilcoxon test implemented in R version 3. 1. 2. All statistical tests were two-sided.
15]-, characterized by significantly different lifespans showing T 50 values ranging from 32 to 57. 7 days (Fig 4A). Using the previously described methodology to identify Smurf flies, we isolated Smurfs at different ages (15, 23, 33, 41, 47, 55 and 62 days) from the 6 populations of DGRP flies presented in Fig 4A and monitored their remaining lifespan (Fig 4B). Although these survival curves don't totally overlap they are highly similar, with T 50 values showing no significant differences with the drsGFP large dataset (Fig 4C). Thus, under our experimental conditions, the remaining life expectancy (T 50 ) of flies in the phase 2 of life, or Smurfs, is almost constant whatever their genotype or the age at which flies underwent the phase 1/phase 2 transition and significantly decreased compared to the non-Smurf flies of the same genotypes.
Subject Five MS patients underwent a weekly MRI follow-up for 2 months (eight MRI examinations). To be included in this study, patients had to be untreated for at least one year and have at least one active gadolinium-enhanced lesion during the 6 months preceding study enrollment. Patients were excluded if they presented with other brain comorbidities (microangiopathy, ischemic stroke), had contraindications to undergo MRI (pace-maker, cardiac vasculopathy, claustrophobia, allergy to contrast agent, and pregnancy) or renal insufficiency with low creatinine clearance. This longitudinal prospective study (Clinical-Trials. gov Identifier: NCT00861172) was approved by the local ethics committee (CPP Lyon Sud-Est IV) and the French Health Products Safety Agency (AFSSAPS). All patients signed an informed consent form approved by the ethics committee.
Data processing Parametric maps of ADC, fractional anisotropy (FA), as well as axial and radial diffusivities were computed after correcting for image distortions using the MEDINRIA software  (Toussaint et al. 2007 ). Parametric maps reflecting relative cerebral blood volume (rCBV), were performed on a remote station (Easy Vision). Inventory of the whole lesions developed during the 8 weeks of the study was performed using MIPAV software (Medical Image Processing And Visualization, downloadable from: http://mipav. cit. nih. gov/). Lesion volumetry was realized for each time point and for each active lesion with a semiautomatic method based on intensity thresholding. 3D enhanced T1-weighted images were used to achieve this inventory. All listed WM lesions were confirmed on 3D FLAIR images to rule out any enhancement artifacts or vasculature confounding.
Each sample was analyzed in duplicate. The primers and the probe targeting the hotspot F1174L (3520, T>C) were purchased from Biorad, whereas the primers and the probes specific for the hotspots F1174L (3522, C>A) and R1275Q (3824, G>A) were designed using Pri-mer3Plus software and are described in Table  1. They were used to a final concentration of 900 and 250 nmol/ L, respectively. Each experiment contained positive and negative controls as well as no template controls. The cases showing a mutation were confirmed in a second experiment. Droplets were scored as positive or negative based upon their fluorescence intensity which was determined by gating a threshold using positive and negative controls as well as no template controls. Although in theory, one positive droplet should score the sample as positive, a minimal number of six positive droplets was defined to classify a sample as positive.
ALK mutation detection in tumor samples by Sanger sequencing and ddPCR and Illumina Deep sequencing Among the 111 cases previously evaluable by ddPCR on circulating DNA, the Sanger sequencing was performed on 101 DNA tumor samples containing more than 50% of malignant cells. The 10 other tumor samples were not available or containing a low proportion of tumor cells. Among the 101 tumors studied, the mutation F1174L (exon 23) was identified in five cases and the mutation R1275Q (exon 25) was detected in nine cases. All ALK mutations detected by Sanger sequencing were also identified in circulating DNA. All ALK mutations were somatic since no mutation was detected in corresponding normal DNA samples (data not shown). The proportion of mutated cases after analysis of DNA tumors samples by Sanger sequencing was lower than the ratio of mutated cases detected by ddPCR in plasma samples.
Overall, a total of 17 patients showed one or two ALK mutations after analysis of DNA tumor samples by ddPCR (Table  2 ). In 40 tumor samples defined as WT after analysis of circulating DNA, no mutation was found in the hotspots of the exons 23 or 25. Mutant to WT ALK ratio was ranged from 16. 7% to 41% for the cases identified by the ddPCR system and Sanger sequencing, whereas it decreased to 0. 07% for the samples detected only by ddPCR. To validate the data obtained by ddPCR, the tumors of patients showing ALK mutations detected in plasma or tumor samples were analyzed by deep sequencing using Illumina HiSeq2500 technology in a blinded study. A good concordance was observed between both techniques although for two cases, mutations were only detected by deep sequencing (PT4 (R1275Q, 3824,G>A) and PT14 (F1174L(3522,C>A) (Tables  2  and 3 ).
Discussion In this report, we present the feasibility of screening for the presence of two hotspot ALK mutations in NB patients by analysis of circulating DNA obtained from 200 lL of serum or plasma samples collected at diagnosis using ddPCR system. The basis for successful circulating DNA detection is the selection of an isolation method that ensures extraction of a sufficient amount of quality DNA. As shown by different teams  [24, 25] , the choice of commercial kits is important and QIAampDNA Micro Kit and QIAamp MinElute Virus Vacuum Kit (Qiagen) were described as more suitable. We have confirmed these results (data not shown). It was crucial for our study to use a minimal quantity of blood, as it is difficult to collect a large volume of blood since the patients with NB tumors are young (age often below 7 years with a majority being between 2 and 5 years).
To our knowledge, this is the first study showing the detection of rare mutant alleles from only few milliliters (200 lL) of serum or plasma. Overall, circulating DNA was isolated from 114 patient blood samples and interpretable in 111 cases. The ALK mutation was identified in 21. 62% of patients. This high frequency of ALK mutations is consistent with the previous study published by Sausen et al. in which 10 cases showed ALK mutation among the 41 NB samples analyzed by next-generation sequencing analysis  [26]. Our aim was to compare the data obtained from circulating DNA to the data obtained by Sanger sequencing (exon 23 and exon 25) of tumor DNAs. Among the 111 cases, the Sanger sequencing was possible in 101 tumor DNA samples containing >50% tumor cells. ALK mutation was identified in 14 cases (13.
Acknowledgments We thank the  Biological Resource Center of Centre L eon B erard (Lyon, France ) and following colleagues:  C. Berger ,  C. Bergeron ,  F. Dijoud ,  C. Faure-Conter ,  J. Kanold ,  D. Plantaz ,  D. Ranch  ere, and  P. Thiesse , for contributing blood and tumor samples and  V. Attignon  for critical reading of the manuscript.
Funding Information This work was supported by grants from the  Saone et Loire Committee of the French National League against Cancer. , PHRC  IC2007-09 ,  EuroSARC 287 ,  LYRIC INCA DHOS 4664 ,  Labex DevweCan   ANR-10-LABX-0061 ,  EuroSarc FP7-278472. GS received funding from the  Annenberg Foundation.
Real-time dynamics Local density x i (t) is the number of individuals in patch i at time t. To determine x i (t), we performed an algorithm that divided the data according to the time of night. For each replicate, we retrieved the position of each marked weevil, and consequently we knew the exact local density x i (t) and the local sex ratio of patch i at any time t. From the population dynamics of the patches in the original data, we calculated the local density x i (t) of each patch as the mean of all the local densities observed in the time interval [t; t + Dt] in patch i. We applied the same procedure for calculation of the sex ratio. We assigned the value 1 when the weevil had moved between patches during Dt and the value 0 when the weevil had not moved between patches. We thus assumed that the decisions of individuals to move were related to x i (t).
We first removed nonsignificant interactions and then removed nonsignificant variables. The selection procedure was continued until a model was found in which all effects were significant  (Zuur et al. 2009). All GLMMs were estimated using the glmer function in the "lme4" package  (Bates et al. 2012) , in which the maximum likelihood of parameters is approximated by the Laplace method  (Bolker et al. 2009 ). We also performed a Bayesian estimation of parameters of the best GLMM using the MCMCglmm package  (Hadfield 2010 ); see the Supporting information, Tables  S1  and S3 ) based on the deviance information criteria. MCMC offers the advantage of providing confidence intervals on parameters in a way that averages the uncertainty in the fixed and random effect parameters  (Bolker et al. 2009 ).
Data Deposit and Material Sharing The original dataset and the data describing real-time dynamics for each value of Dt can be downloaded at: http:// knb. ecoinformatics. org/knb/metacat?action=read&qformat= knb&docid=knb. 341. 1 and http://knb. ecoinformatics. org/ knb/metacat?action=read&qformat=knb&docid=knb. 345. 1.
X-ray reflectivity (XRR) studies were performed in-house using a PANalytical Empyrean Reflectometer with a wavelength of λ = 0. 154 nm. The experimental data were fitted with the software "X´Pert Reflectivity 1. 3, PANalytical" using Parratt's formalism, surface roughness was implemented by the model of Nevot & Croce  [13, 14]. Grazing incidence X-ray diffraction (GIXD) was performed using the W1 Beamline at HASYLAB (Hamburg) with a wavelength of λ = 0. 118 nm  [15]. The applied force was minimized so that stable imaging was possible without squeezing the organic layers. The AFM topographic data were visualized and analysed using the Gwyddion SPM software v2. 26. Optical microscopy was performed with an OLYMPUS BX51. Molecular dynamics (MD) simulations were performed using LAMMPS in combination with the CHARMM General Force Field v.
2b7  [16, 17]. Density functional theory (DFT) calculations were carried out using the Vienna Ab Initio Simulation Package (VASP) using PAW potentials with an energy cut-off of 345 eV  [18] [19] [20] [21]. The k-mesh was generated automatically by using a Monkhorst-Pack scheme. Single crystals of DOTT were grown from toluene solution. Suitable crystals for X-ray structural analyses were selected and mounted on the tip of a glass fibre. Diffraction data were collected at 100 K and 296 K on a Bruker D8 Kappa diffractometer equipped with a SMART APEX II CCD detector. MoKα (λ = 0. 071073 nm) radiation was used either from a sealed tube (1040724) or from a microsource (1040725). Solution of the crystal structures with direct methods and structural refinement was performed by SHELXS-97  [22]. The space group assignments and structural solutions were evaluated using PLATON  [23].
DNA extraction and PCR conditions The cell lines stocks cryopreserved in liquid nitrogen, were thawed and cultured in 25 cm 2 tissue culture flasks using RPMI 1640 medium (Gibco/Invitrogen, USA), supplemented with 10% foetal calf serum (Gibco/Invitrogen, USA). Approximately 10 7 infected cells were centrifuged at 1500 g during 5 minutes and the cell pellet was washed in phosphate buffered saline (PBS). The final cell pellet was re-suspended in PBS and DNA was extracted using a Promega Wizard Genomic DNA Purification kit (Madison, WI, USA) according to the manufacturer's instructions. Extracted DNA was eluted in 100 μl of "Ultra Pure DNase/RNase-Free Distilled Water" (Gibco/Invitrogen, USA). Degenerated primers designed from the reference sequence of Gen-Bank accession number XM949625 (T. annulata, strain Ankara), cytoF (5' CAGGGCTT TAACCTACAAATTAAC3') and cytoR (5' CCCCTCCACTAAGCGTCTTTCGACAC 3') were used to amplify a 1092 bp of cyt b gene.