dataesr/scientific-paragraphs-categorization huggingface dataset:
Western blotting HeLa Kyoto were lysed using ice-cold lysis buffer (50 mM Tris, pH 7. 5, 1% NP-40, 0. 1% Na-deoxycholate, 150 mM NaCl, 1 mM EDTA + 1X Phosphatase Inhibitor Cocktail). For Western blotting equal amounts of HeLa cell extracts (10 µg) were subjected to SDS-PAGE and resolved, then wet-blotted on X Cell 2 Mini Cell apparatus (Invitrogen GmbH) onto nitrocellulose membranes, and subsequently incubated with primary antibodies. Rab5c was detected using a a rabbit primary antibody directed against Rab5c (Sigma HPA003426-100UL, 1/1000) was incubated with the membrane overnight at 4°C and, after washing with PBS-Tween buffer, incubated with an anti-rabbit HRP-conjugated secondary antibody (1/10,000, 30 min). Bands were detected with enhanced chemiluminescence Western blotting detection reagents (GE-Healthcare RPN 2106V1, 1:1, 1 min exposure time).
Finally, without removing the PBS/DAPI/CMB mixture, 90 μl of 0,04% sodium azide was added to each well. Imaging was carried out on a Cell Voyager CV7000 automated spinning disk microscope (Yokogawa) using a 40X/0. 95NA objective. 8 fields of view (416 μm x 351 μm, 0. 1625 μm/pixel) per well were acquired and conditions were tested in triplicates to yield 24 images per condition. Image analysis was carried out using the lab custom built software Motion Tracking.
Structural illumination microscopy For SIM, cells were imaged with a 60x, NA 1. 42 oil objective on a Deltavision OMX v4 BLAZE (GE) equipped with 405, 488, 568, 642 nm lasers and four independent sCMOS cameras. Spherical aberration was minimized by choosing an immersion oil with a refractive index giving symmetrical point spread functions. Image stacks were acquired with 95 MHz, 0. 125 μm z-steps and 15 images (three angles and five phases per angle) per z-section and a 3D structured illumination with stripe separation of 213 nm and 238 nm at 488 nm and 594 nm respectively. Image reconstruction was done using the Deltavision softWoRx 7. 0. 0 software with a Wiener filter of 0. 0005-0. 001 and wavelength specific OTFs specific for the mounting media.
Electron tomography, reconstruction and registration Double-axis tilt-series (-60 / +60 degrees) were acquired at 9,400x magnification on a Tecnai F30 transmission electron microscope operated at 300kV, using an UltraScan1000 CDD (2k x 2k) camera (Gatan, CA, USA) and the SerialEM software (Mastronarde, 2005). 3DMOD software (v. 4. 9. 8, University of Colorado, CO, USA) was used for tomogram reconstruction (using the weighted back-projection algorithm) and endosome segmentation. For segmentation the z-axis increment of 3 was applied to compensate for the collapse along a z-axis during a step of methyl cellulose embedding and drying of sections. certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. SMLM images were oriented with respect to low mag (2,300x-3,900x) montage EM overview images in the ICY software (v.
1. 9. 10. 0, the Pasteur Institute, France) using bacteria embedded in the section as fiducials visible in both imaging modalities. The non-rigid transformation was applied for alignment. Tomograms were roughly aligned to the low mag overview EM image using distinct ultrastructural features (nuclear envelope, plasma membrane). In order to assign SMLM signals to an endosome model, the two datasets were compared when aligned side by side. To indicate endosomal compartmentalization, ultrastructural models were colour-coded. Green, representing Tfn, was used for tubules. Red, magenta, and orange, all representing EGF, indicated ILV, ILV continuous with the limiting membrane, and sorting microdomains, respectively. Selected examples of reconstructed tomograms and ultrastructural models are included as.
Acknowledgements We thank the  MPI-CBG light microscopy facility  for access and technical assistance especially  Bert Nitzsche ,  Britta Schroth-Diez  and  Jan Peychl ; the  TransgeneOmics facility , especially  Anne-Kristin Heininger ,  Ina Poser  and  Mihail Sarov  for the design, generation, and maintenance of the BAC lines; the  Electron microscopy facility , especially  Tobias Fürstenhaupt  for introduction to tomography;  Ina Nuesslein ,  Julia Jarrells  and  Christina Eugster  from the  MPI-CBG FACS facility  for assistance with the flow cytometry;  Marc Bickle  from the  Technology Development Studio  for assistance in the Yokogawa imaging. In addition, we thank  Andreas Müller  for valuable discussion and technical help with image registration. This work was financially supported by the  German Research Foundation (DFG) (grant #  112927078 ,  TRR 83 TP23 ), the  European Research Council (ERC)  (grant # 695646 378 ) and the  Max Planck Society (MPG).
75 μM and 700 μM respectively) for 48 hours. The culture medium was removed and the plates were incubated for 14 days in 5% CO 2 incubator at 37°C and 95% humidity in the absence of 5-FU and rutin treatment for detecting obvious colonies. The culture medium was changed every 2 days. Then the plates were rinsed with PBS and fixed with 70% ethanol. The staining of colonies was done with a mixture of 0. 5% crystal violet in 50:50 methanol:water for 30 minutes. The plates were rinsed with water and left for drying at room temperature. Then, ImageJ software (web-based open source software) was used to evaluate the colonies. The plating efficiency (PE) was measured using the following formula: number of colonies/number of seeded cells ×100 and surviving fraction (SF) was determined by (number of colonies/number of seeded cells × PE control) ×100.
The primers were designed with Oligo 6. 0 (Molecular Biology Insights, Cascade, CO, USA) and confirmed by the blast (NCBI). The primers were obtained from (Macrogen Company, South Korea). The expression of p53 gene was done using Rotor-Gene 3000 (Corbett, Australia). RT-qPCR program consisted of an initial denaturation stage of 95°C at 10 minutes. Then, a three-step program was developed for 40 cycles including 95°C for 10 seconds, 62°C for 15 seconds, and 72°C for 20 seconds, respectively. GAPDH (glyceraldehyde-3-phosphatedehydrogenase) a housekeeping gene, was used as an endogenous control gene for the normalization of p53 expression. The relative quantity of the target gene was determined using the 2 -ΔΔCT method. 26 stern blot PC3 cells were plated into 6 dishes (6× 10 5 cells/dish) in RPMI 1640 medium supplement with 10% FBS, 1% pen/ strep and incubated overnight in 5% CO 2 incubator at 37°C and 95% humidity.
Statistical analysis All data were presented as mean ± standard deviation (SD) in triplicate experiments. Statistical analysis of the data was done using SPSS software version 20 (SPSS Inc. , Chicago, IL, USA) and GraphPad Prism 6 (GraphPad software, San Diego, CA). Kruskal-Wallis and Dunn's test were used to estimate the statistical analysis between the treated and the control groups for real-time PCR, Annexin V assay, clonogenic assay, and MTT assay. The p value less than 0. 05 was considered significant. For gene expression analysis, the data were normalized to GAPDH and results were expressed as fold change. The relative levels of quantitative gene expression were estimated with 2 -∆∆CT method. A melting curve analysis of each product was generated to ensure the purity of the amplification product of each reaction.
The emergence of ARV-resistance mutations was observed during the trial and briefly described, but the relationship between NNRTI plasma concentrations and the emergence of resistance was not investigated. Here, we analyzed subgroup datasets from the CARINEMO trial, which provided a unique opportunity to explore the factors associated with viral replication and the emergence of resistance mutations while on ART. These data also offered the possibility to assess the relationship between viral replication, ARV plasma concentrations and the emergence of resistance mutations. The identification of risk factors of virological escape at week 48 in a well-characterized and homogeneous population is critical to prevent treatment failure in settings where the best timing for routine HIV-RNA still needs to be assessed.
Trial background The CARINEMO trial (ClinicalTrials. gov identifier: NCT00495326) was conducted in three health centers located in Maputo, Mozambique, from 2007 to 2011; a full description of the trial is available from Bonnet et al. 3. Participants were randomized to NVP or EFV (without lead-in dose) and received either a fixed-dose combination of NVP (400 mg/day), lamivudine and stavudine (Triomune ® ) or EFV (600 mg/day) plus lamivudine and stavudine started 4 weeks after anti-TB treatment initiation and for a duration of 48 weeks. In August 2010, stavudine was replaced by zidovudine. For TB, all patients received a fixed-dose combination of isoniazid (H), rifampicin (R), ethambutol (E) and pyrazinamide (Z) for 2 months, followed by 4 months of isoniazid/rifampin. Four ethics committees approved the study protocol: the Comite Nacional de Bio-Etica para a Saude (Maputo, Mozambique), the Medecins Sans Frontieres Ethics Review Board (Zurich, Switzerland), the Comite de Protection des Personnes (Saint Germain-en-Laye, France), and the Columbia University ethics review committee (New York, NY, USA).
Discussion In the present study, we used the data of a large randomized clinical trial assessing two drugs of the NNRTI class in combination with anti-TB drugs. Our findings showed that very low drug plasma concentrations early after treatment initiation (week 12) were predictive factors of virological escape and the emergence of resistance mutations at week 48. Low drug concentrations may be explained by a suboptimal adherence or a potent drug interaction when patients receive other drugs such as rifampicin. Recently, it was suggested that the wave of ART treatment failure primarily affecting resource-limited countries should be considered as a fourth epidemic  6. This epidemic, accompanied by the emergence of ARV drug resistance, could affect 3 to 5 million individuals between 2020 and 2030  7.
Indeed, the P10 at week 12 was 1253 ng/ml for the EFV component, whereas concentrations below 1000 ng/ml were sufficient in earlier studies  21  to predict treatment failure. Furthermore, the ENCORE1 study showed the efficacy of the 400 mg EFV daily dose, suggesting also that the efficacy cut-off might be lower than 1000 ng/ml  22. We hypothesized that the high frequency of CYP2B6 genetic polymorphism in individuals of African descent may explain a population concentration distribution above that observed in Caucasian patients by Marzolini et al. 21. This study has some limitations. First, in the CARINEMO clinical trial, data were collected at fixed time points and HIV-1 RNA and plasma drug concentrations started to be measured for all patients at week 12. This limited the assessment of earlier effects on virological escape and the emergence of resistance mutations in the very first weeks of treatment initiation.
Acknowledgments We thank the medical, research team and patients from the trial sites:  Centro de Saúde de Alto Maé, Hospital Geral de Mavalane, Hospital Geral de José Macamo in Maputo, Mozambique ; the  Instituto Nacional de Saúde ;  Médecins sans Frontières -Switzerland  ( MSF-CH ), Mozambique; the  International Care AIDS Program (ICAP)  in Maputo and the  Agence nationale de recherches sur le sida et les hépatites virales (ANRS)  (for the funding of the trial). CARINEMO -ANRS 12146 clinical trial study group  Ilesh V. Jani MD PhD ,  Nádia Sitoe Bsc ,  Adolfo Vubil Bsc MSc ,  Maria Nhadzombo ,  Fernando Sitoe ,  Delário Nhumaio ,  Odete Bule  ( Instituto Nacional de Saúde, Mozambique );  Rui Bastos MD  and  Elizabete Nunes MD  ( Hospital Central, Maputo, Mozambique );  Paula Samo Gudo MD MPH  ( National Tuberculosis Control Program, Mozambique );  Josué Lima MD  and  Mie Okamura (International Center for AIDS Care and Treatment Programs, Mozambique) ;  Laura Ciaffi MD ,  Agnès Sobry MD ,  Mariano Lugli  and  Bruno Lab  ( Médecins Sans Frontières -Switzerland, Mozambique );  Avertino Barreto MD  ( Mozambique National AIDS Service Organisation, Mozambique );  Christophe Michon MD  ( Regional Hospital, Annecy, France );  Alexandra Calmy MD PhD  ( Médecins Sans Frontières ;  Division of Infectious Diseases, Geneva University Hospital, Geneva, Switzerland );  Alpha Diallo  ( ANRS pharmacovigilance unit, France );  Christine Rouzioux PharmD PhD  ( Paris-Descartes University ,  EA3620 ,  Sorbonne Paris Cite, APHP, Necker Hospital, Paris, France ).
13 Such methods are particularly suitable when randomisation is not feasible and to produce data for the effect of interventions in realworld settings. Additionally, we analysed improvement of key indicators related to programme organisation. The Jujuy setting has been extensively described elsewhere. 8, 11 The province is located in northwest Argentina and has around 673 000 inhabitants; 85% of the population live in urban areas and 32% are poor; its public health system includes a tertiary referral hospital, 300 primary health-care centres, 18 diagnostic centres, and five treatment services. Health services are free for the population not covered by the social security sector (eg, informal workers and their families).
Data sources Since 2010 in Jujuy, any instance of screening, diagnosis, or treatment using public health services has been registered in the national screening information system (SITAM). 16 The HPV laboratory used SITAM to manage samples at entry; the samples of individuals that did not comply with the recommended age range or screening frequency were not processed. Women were informed about why their test was not analysed and were reminded of the date of their next HPV test. The protocol was approved by the CEMIC Institutional Review Board (protocol number 1186). De-identification of the databases protected the identity of participants. Verbal informed consent was obtained according to the national regulations for standard medical practices (Patient's Rights Act 26. 529). Specific consent was not required for statistical analysis of aggregated de-identified data.
Statistical analysis Mean age as a continuous variable was compared between the cytology-based period and HPV-based period using the Wilcoxon rank-sum test. Multivariable logistic regression was used to measure the magnitude of the effect of HPV testing on CIN2+ detection compared with cytology-based screening, after adjusting for age and health insurance status. To account for potential selection into the intervention group and minimise bias, we developed a second model using PSM. Included variables were age (in years) and health insurance status. Functionality of PSM requires datasets with no missing values. To handle missing data, we used average imputation for age (six missing cases) and random imputation for health insurance (13 missing cases). The matching algorithm chosen was the nearest neighbour algorithm, using a caliper value of 0•1 SD.
Acknowledgments This Article presents independent research funded by the  Argentinian National Cancer Institute. The analysis of follow-up was partly funded by the  National Argentinian Council of Scientific and Technologic Research  (Project  PIP 0337/2013 ). The views expressed are our own and not necessarily those of the  Argentinian National Cancer Institute , the  Ministry of Health , or Jujuy's Ministry of Health. We thank the team of the  National Program of Cervical Cancer Prevention  for its participation during the project. We also would like to acknowledge  Mariana Curotto  and  Julieta Zalacain Colombo  for their assistance during the analysis, and  Maria Antonia Rodriguez  for her comments on the first version of the manuscript.
Data collection The data were collected by two methods in one single visit: a physician-administered questionnaire and case report forms. A structured, self-reported questionnaire administered to the participating physicians was first developed in English, and it was translated into the local languages and back-translated into English by a blinded translator for ascertaining validity. The pre tested questionnaire was designed to assess the current practices in the diagnosis and management of children with fever and/or acute pain. The 21-item questionnaire also inquired about physicians' demographic and professional characteristics, the perceived reasons for unsatisfactory effect of pain/fever treatment, and the unmet needs in the management of fever and pain. The information that was collected on standardized case report forms included patients' demographic and anthropometric characteristics; their medical history; the etiology, characteristics (duration and body temperature) and management (non pharmacological and pharmacological) approaches of fever; and the etiology, characteristics (duration and intensity), and management (non pharmacological and pharmacological) approaches of acute pain.
Sample size estimation and statistical analysis Since this study aimed to describe the real-world treatment patterns in pediatric patients with fever and/or acute pain, most findings were reported as proportions. To detect a proportion of 50%, at a 95% CI with the maximum marginal error of estimate not exceeding 7%, a sample size of 196 patients in each study country was estimated as appropriate. Assuming that data might not be available for 15-20% of patients, the estimated number of patients in each country was 240. Data were analyzed separately according to the reported illness (patients with fever, patients with acute pain, and patients with both fever and acute pain), and according to age (between 3 and 24 months, between 2 and 6 years, between 6 and 12 years, and between 12 and 16 years).
A descriptive analysis of the categorical variables was presented as counts and percentages, and continuous variables were presented as mean and SD. Data were statistically analyzed by using the non parametric Kruskal-Wallis test (for quantitative variables), the Chi-squared test, or Fisher's exact test (for qualitative variables), as appropriate. All tests were two-sided, and a p-value <0. 05 was considered significant. Statistical analyses were conducted using SAS 9. 3 (SAS Institute Inc. , Cary, NC, USA).
Ethics approval and informed consent This study was approved by the Ministry of Higher Education, Research and Innovation (France). Ethics approvals were obtained from the local institutional review committee of each participating center, and the legal guardians of all participants gave written informed consent. Every effort was made to ensure protocol standardization and adherence, including translation of the questionnaire into languages specific to each region, on-site monitoring, and centralized database management. This study was conducted in accordance with the Declaration of Helsinki and the Good Epidemiological Practice.
Acknowledgments The authors would like to thank the following physicians, who participated as investigators in this studyfrom Algeria:  Pr Rachida Boukari ,  Dr Med Salah Djeha ,  Dr Nadyla Belaltech ,  Dr Nadiya Djabali ep Hamlaoui ,  Dr Karima Khabouza ,  Dr Ahcene Haroun ,  Dr Chafik Bouchene ,  Pr Chaouki Kadache ,  Dr Abdeldjalil Maoudj ,.
Among those, 60 (68. 2%) were replicated at a nominal threshold of 5%. Non-replication of the remaining 28 associations is likely explained by limited power in the replication dataset. Indeed, we observed a strong correlation (ρ = 0. 63) between the effect sizes of top SNP per region derived from METSIM and the strength of signal for the same variant in the Kettunen et al. 11  study (Supplementary Fig. 4 ). Eventually, when comparing the top SNPs from every region associated with at least one metabolite (N = 70, see next paragraph) with previous GWAS on coronary heart disease (CHD)  16  , body mass index (BMI)  17  , and type 2 diabetes (T2D)  18  , we observed substantial enrichment for nominally significant association. Given a false discovery rate (FDR) at 10%, we observed 30 significant genes for CHD, 5 for BMI, and 4 for T2D (Supplementary Data 6 and Supplementary Note 1), indicating some of these variants are also involved in the genetics of common diseases.
In our study, we considered 158 variables, including 150 raw measurements and eight ratios. Other available variables, which were mostly percentages, were not included in the study. Besides metabolic measurements, several variables were also available including drug treatment and large group of other phenotypes. All samples were genotyped for 665,478 SNPs using the Illumina OmniExpress chip. Genotype data went through standard quality control, filtering individuals with missing rate below 5%, and SNPs with missing rate below 5% or with P < 10 -5 in Hardy-Weinberg test. Metabolites profiling. We used a high-throughput serum NMR platform for metabolic profiling. Details of this platform have been published previously  58, 59  and it has been widely applied in genetic and epidemiological studies  60, 61.
This refined targeted metabolomics panel of > 100 serum metabolic phenotypes, includes lipoprotein subclass and lipoprotein lipids, fatty acids, and amino acids assessed by NMR from serum samples. Overall, 14 lipoprotein classes varying in sizes were analyzed including six classes of VLDLs, one class of IDLs, three classes LDLs, and four classes of HDLs. Within each lipoprotein particle, the concentrations of the following lipids were measured: total lipids, phospholipids, total cholesterol, cholesterol ester, free cholesterol, and triglycerides. Data pre-processing. In order to remove outliers without reducing sample size, we first applied inverse normal rank-transformation on every analyzed metabolite. This was done using the rntransform function in R package GenABEL  62. Because of potential confounding effect of statins use on metabolites, we excluded all statins users (1722 individuals) when analyzing LDL, IDL, Apolipoprotein B and cholesterol.
To estimate the number of effective tests, we first did a PC analysis of our 158 metabolites. Then, we calculated the number of PCs that explained 99% of the total variance. We obtained 39 effective tests. The significance threshold was then 1. 28 × 10 -9. Because of the great number of signals, we chose to summarize our results by genomic regions, corresponding to approximately independent LD blocks. We sliced the genome in 1703 independent regions based on a recombination map recently described by Berisa et al. 23. These regions are 10 kb to 26 Mb long, with an average size of 1. 6 Mb. For each region, we kept the SNP with the best p-value obtained by either STD or CMS. We then used the UCSC database to assign the closest gene to each SNP, with a maximum distance of 100 kb. GWAS of delta between baseline and follow-up.
We used data from baseline and follow-up studies to perform GWAS of the difference between the two time points, divided by the age difference. We called that variable Δ fb : Δ fb ¼ f À b age f À age b ð3Þ where f and b are metabolite measurements at follow-up and baseline, respectively. As for baseline data analysis, we used STD and CMS approaches, with covariates pre-selection based on AIC. Confounding factors used for the baseline analysis were also included as covariate in all Δ bf analyses. We did not adjust for baseline value in the main analysis. Interaction analyses. We performed two follow-up interaction analyses for subset of SNP-metabolite associations identified in the GWAS. First, we assessed SNP-byage interaction effect in both baseline and follow-up analyses for the subset of SNP showing significant effects on Δ bf in metabolite levels between baseline and followup (Δ bf ).