dataesr/scientific-paragraphs-categorization huggingface dataset:
The proteomics data have been deposited to the ProteomeXchange Consortium  (Vizcaino et al. , 2014)  via the PRIDE partner repository with the data set identifier PXD001805  (Radoshevich et al. , 2015a). Interestingly, these proteins have not yet been reported to be targets of ISGylation. Following interferon treatment, ISG15 modified twelve additional proteins distinct from those that were ISGylated after overexpression without treatment (Figure  4C-E , Figure  4 -source data 1, depicted in red). Three of these proteins are known targets of ISGylation following interferon treatment in the aforementioned screens. The other nine are novel substrates of ISGylation. To gain more insight into the role of ISGylation of the modified substrates following overexpression, we performed a gene ontology (GO) analysis of the thirty ISGylated proteins.
5. ISGylation modifies ER and Golgi proteins and increases canonical secretion. (A) Gene ontology (GO) analysis of ISGylated proteins enriched following ISG15 overexpression (blue) relative to all proteins identified in this analysis (light gray) and all human proteins as annotated by the Uniprot/Swiss-prot database (dark gray). (B) Nickel affinity purification of ISG15 in empty-vector control or ISG15 overexpression cells followed by α-ISG15, α-MAGT1, and α-RTN4 immunoblot. Input is 0. 1% of the initial affinity purification volume. Higher molecular weight species corresponding to ISGylated RTN4 or MAGT1 are indicated. (C) Cells were fixed and immunostained with α-PDI antibody (green), with α-TGN46 (red) and Hoechst (blue). Cells with four or more large puncta were enumerated as cells with PDI clusters, a minimum of 100 cells were counted per experiment, and data are shown as percentage of cells with PDI clusters; AVG ± SEM.
Data analysis was performed with MaxQuant (version 1. 4. 1. 2)  (Cox and Mann, 2008)  using the Andromeda search engine  (Cox et al. , 2011)  with default search settings including a false discovery rate set at 1% on both the peptide and protein level. Spectra were searched against the human proteins in the Uniprot/Swiss-Prot database (database release version of January 2014 containing 20,272 human protein sequences, www. uniprot. org) with a mass tolerance for precursor and fragment ions of 4. 5 and 20 ppm, respectively, during the main search. To enable the identification of SILAClabeled peptides, the multiplicity was set to three with Lys 4 and Arg 6 settings in the medium channel and Lys 8 and Arg 10 in the heavy channel, allowing for a maximum of 3 labeled amino acids per peptide. Enzyme specificity was set as C-terminal to arginine and lysine, also allowing cleavage at proline bonds and a maximum of three missed cleavages.
, 2014)  via the PRIDE partner repository with the dataset identifier PXD001805. GO terms enrichment analyses were performed using Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resources  (Huang da et al. , 2009). qRT-PCR, RNASeq, and SDS-PAGE Total RNA was isolated using an RNAeasy kit (Qiagen). 1 μg of RNA from each condition was reverse transcribed using the iScript cDNA synthesis kit (Biorad), and qRT-PCR was performed using SsoFast EvaGreen supermix (Biorad) on a CFX384 Real-Time System with a C1000 Touch Cycler (Biorad). Data were then analyzed using the ΔΔCT method relative to GAPDH levels for each sample. For RNASeq uninfected LoVo cells were compared to LoVo cells infected with L. monocytogenes strain EGD-e for 24 hr. The experiment was performed in triplicate, and total RNA following infection was isolated using an RNeasy kit (Qiagen).
Samples were subsequently checked for quality and sent to Fasteris for library preparation and analysis. The RNASeq data has been uploaded to Array Express with the accession E-MTAB-3649  (Radoshevich et al. , 2015b ; https://www. ebi. ac. uk/arrayexpress/ experiments/E-MTAB-3649/) entitled 'ISG15 counteracts Listeria monocytogenes infection'. For SDS-PAGE analysis, samples were lysed following one wash in 1× PBS with 2× Laemmli buffer. The cells were scraped in the sample buffer, resuspended and boiled at 95˚C for 5 min. Prior to running the samples on a gel, they were sonicated two times for 8 s each to disrupt DNA. For SDS-PAGE following a nickel-affinity purification, proteins were eluted with the following buffer (200 mM imidazole, 5% SDS, 150 mM Tris-HCl pH 6. 7, 30% glycerol, 720 mM β-mercaptoethanol, and 0.
Acknowledgements We thank  Drs Sandra Pellegrini ,  Jon Huibregtse ,  Gia Voeltz ,  Sabrina Jabs ,  Matthew Albert ,  Scott Werneke ,  Jayanta Debnath , and  Thierry Heidmann  for generously providing reagents, and  Dr Sandra Pellegrini  for critically reading the manuscript. We thank  Edith Gouin  for production of antibodies,  Dr Christophe B écavin  for generating the heat map for the proteomics data and for help uploading the RNASeq data. We thank  Mikael Koutero  and  Andrzej Prokop  for help with the RNASeq data. We thank  Dr Georges Azar  for help with FACS. We thank  Drs Nathalie Rohlion ,  Alessandro Pagliuso , and  Fabrizia Stavru  for helpful discussions and the  Pasteur Proteomics Platform.
Research capacity building and training of laboratory technicians and general practitioners are integral parts of these on-going field activities. The introduction of ACT is another challenge facing Mauritania. One of the key issues is the cost of ACT, which is 20 times higher than the cost of conventional therapy, such as quinine ($2. 44 per adult dose). Population migration from sub-Saharan endemic countries constitutes another challenge where no official measures for controlling malaria prevalence among these migrants exist. Mauritania still does not have a reliable database on malaria epidemiology. A nationwide malaria indicator survey is being planned to fill this gap in 2015. Updated information and maps on malaria burden and Plasmodium species distribution are critical for guiding national efforts to improve laboratory diagnosis, implement rapid and effective treatment, and coordinate and plan malaria elimination from the country in the near future.
The emergence of AE in patients with immunosuppressive therapy On the other hand, a significant number of AE cases have been reported for the past 15 years in patients who received organ transplantation or were treated for malignant or chronic inflammatory diseases  (Gruener et al. , 2008; Kayacan et al. , 2008; Gaultier et al. , 2009; Geyer et al. , 2011; Weiner et al. , 2011; Kern et al. , 2011; Dentan et al. , 2012). AE cases in patients with cancer, malignant haematological disorders, chronic inflammatory diseases, transplantation, and AIDS, before or at AE diagnosis, were extracted from the population-based AE French registry database (1982-2012)  (Chauchet et al. , 2014). Fifty patients were found with such immunosuppression (IS)-associated conditions among 509 AE cases diagnosed from 1982 to 2012.
Background Tumors, including hematologic malignancies, can use the PD-1 pathway to evade immune surveillance. Pembrolizumab, a highly selective, humanized monoclonal antibody that blocks interaction of PD-1 with its ligands PD-L1 and PD-L2, has demonstrated robust antitumor activity and a manageable toxicity profile in advanced solid tumors. In earlier data, pembrolizumab demonstrated efficacy in Hodgkin lymphoma (HL)  [1]. KEY-NOTE-013 (ClinicalTrials. gov, NCT01953692) is a multicenter, nonrandomized, open-label, multicohort Phase Ib trial designed to assess safety and efficacy of pembrolizumab in patients with hematologic malignancies.
glabra. In the case of snail co-infections, prevalence was specified for each parasite species. A v 2 test was used to determine levels of statistical significance. Prevalences noted in the same type of habitats were first compared. In a second analysis, the differences between C. daubneyi values and those noted for F. hepatica in furrows, road ditches and pools were assessed because snail samples were collected over the same period of time (March). All the analyses were done using StatView 5. 0 software (SAS Institute Inc. , Cary, NC, USA). The nomenclature adopted by Correa et al. [7]  and that by Jones  [21]  were used in the present study to identify lymnaeid and paramphistome species, respectively. Of the 17,647 adult snails collected from the 206 habitats over the 2 years, three plagiorchiid, one echinostomatid, one fasciolid, one notocotylid and one paramphistomid species were found (Table  1 ).
Immature infections without free cercariae were also noted. Those belonging to C. daubneyi, F. hepatica and H. cylindracea were easily recognized because of our experience and were classified with the corresponding snails harbouring mature infections. In contrast, those of the other digenean species were considered separately, taking into account the presence of rediae or secondary sporocysts. Xiphidiocercariae were also noted in the foot of several snails but their characteristics did not allow precise identification of the plagiorchiid species. Eleven double infections with C. daubneyi and F. hepatica were noted (data not shown). Table  1  gives the distribution of habitats from which infected lymnaeids were collected. Snails harbouring larval forms of F. hepatica and/or C. daubneyi were found, respectively, in 14.
During the 2 years of study, the presence of F. hepatica was regularly noted in snails living in 7 furrows (out of 17 habitats with infected L glabra) and 5 road ditches (out of 11). This was also observed for C. daubneyi (7 furrows/14, 3 road ditches/7), H. cylindracea (4 pools/7) and O. ranae (2 pools/5, 4 ponds/ 7). In the other types of habitats, the presence of snail infections was more sporadic (data not shown). Table  2  gives values for each type of snail habitat and each digenean infection. Of the 17,647 L. glabra collected from the five types of habitats, a total of 321 infected snails were noted. The highest overall prevalence of all digenean infections was noted in furrows (3. 8%), followed by pools (1. 7%) and ponds (1. 6%) by decreasing order. In the other two types of habitats, prevalence was < 1%.
Methods Population Our prospective cohort included singletons born to pregnant women who were enrolled before 29 weeks of gestation in the Malaria in Pregnancy Preventive Alternative Drugs (MiPPAD) clinical trial (NCT00811421) comparing sulfadoxine-pyrimethamine and mefloquine as intermittent preventive treatment of malaria in pregnancy (IPTp). The study was conducted in the district of Allada in Benin. One thousand and five HIV-negative pregnant women attending their first ANC visit in the health centers in each of the three sub districts of Allada (Sekou, Allada and Attogon) were recruited. Detailed inclusion and exclusion criteria in the MiPPAD trial are explained elsewhere. [7]  All live born children of recruited pregnant women who survived to 12 months were invited for neurocognitive assessment in the TOVI study (Fon language: Tovi means Child from the country).
Variables Pregnant women. Socio-demographic and clinical data were collected at three ANC visits; at recruitment (first ANC visit), during the 2 nd dose of IPTp (second ANC visit, at least one month after recruitment) and at delivery. At first ANC visit, information on gravidity, gestational age, anthropometric data and socio-demographic characteristics including age, education, and occupation were collected. Details of biological assessments for pregnant women and how prepregnancy BMI was calculated have been described in an earlier publication. [7]  More specifically, data on maternal helminth infection comes from a parallel cohort study (Anemia in Pregnancy: Etiologies and Consequences "APEC") which was nested within the MiPPAD trial. [20]  At ANC visits, women were given IPTp, iron and folic acid as part of the ANC package in Benin.
The  Eunice Kennedy Shriver National Institute of Child Health & Human Development (NIH/ NICHD ) funded The TOVI study, grant  R21-HD060524. The MiPPAD trial (NCT00811421) was co-funded by the  European and Developing Countries Clinical Trials Partnership  ( EDCTP-IP. 07. 31080. 002 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
4E ). To further confirm these findings, we examined the NF-kB target gene expression. RT-PCR was performed for mRNA expression of IL-6 and IL-8 (CXCL8). As shown in Figure  4F  induction of both IL-6 and IL-8 expression in response to treatment of BLM and MV3 cells with imiquimod was found. Taken together, these data demonstrate the ability of imiquimod to trigger the NF-jB pathway and its effector genes in melanoma cells.
Imiquimod-induced ROS accumulation results in the activation of ASK1-JNK/p38 and NF-jB pathways To address the mechanism of how imiquimod triggers the activation of ASK1-JNK/p38, we examined whether the inhibition of ROS accumulation impacts the imiquimod-enhanced activation of ASK1 and its downstream pathways. Cells were pre-treated with N-Acetyl Cysteine (NAC), the scavenger of ROS, 1 hr prior to the exposure to imiquimod. Flow cytometry analysis of ROS accumulation and Western blot analysis were performed. Figure  5A  demonstrates that NAC largely inhibits imiquimod-induced ROS accumulation. Moreover, data of Western blot analysis (Fig. 5B  and C ) demonstrate that NAC largely inhibits imiquimod-induced phosphorylation of ASK1, JNK and p38 in BLM cells. Similar results were noted in MV3 cells (data not shown).
Acknowledgements This study was supported by a grant from  German Research Foundation/DFG  ( HA 5081/3-1 ),  German Cancer Foundation  ( 10-2202-Ha1 ),  Germany  and from L'Alsace contre le cancer, France to  M. Hassan. Work  in the laboratory of M. Leverkus is funded by  EU Horizon 2020  ( MelPlex ESR network , Project 5), and grants of the  German Research Foundation/DFG  ( Le 953/6-1, 953/8-1 ,  RTG2099 Project 9  and  10 ).
In parallel to decreased or delayed inflammation in skin from IL-1α KO mice, collagen formation, after its     4. (f) IL-1α is required for correct expression of wound healing related genes after skin DNA damage. RNA was extracted from the formalin-fixed, paraffinembedded (FFPE) skin tissue sections and qPCR for the indicated genes was performed to monitor gene expression after cDNA synthesis. Data is expressed as mean ± SD of three independent samples. breakdown by UV (Fig. 4d , Supplementary and Figure  S4b ) and expression of Matrix Metallopeptidase 9 (MMP-9) (Fig. 4e  and Supplementary Figure  S4c ) seem to be impaired 18 h post radiation in the skin of IL-1α KO mice, suggesting that IL-1α deficiency delays wound healing and tissue remodeling after UV induced skin damage. In addition, IL-1α seems to be essential for the expression of several wound healing related genes (e.
5% acetic acid) at a flow rate of 250 nL/min over 60 min. MS data were processed into peak lists by DTASuperCharge 2. 0b1 (part of the MSQuant 2. 0b7 software environment) and searched with Mascot 2. 2 against the mouse International Protein Index protein database (IPI, version 3. 68) combined with frequently observed contaminants and concatenated with the reversed versions of all sequences. The MMD for monoisotopic precursor ions and MS/MS peaks were restricted to 5 ppm and 0. 6 Da, respectively. The enzyme specificity was set to trypsin (with a maximum of 2 missed cleavages) allowing cleavage of the N-terminal to proline and C-terminal to aspartate. Modifications were cysteine carbamidomethylation (fixed), as well as protein lysine acetylation, serine/threonine/tyrosine phosphorylation, deamidation (asparagine and glutamine) and methionine oxidation (variable).
Total RNA was extracted using the RNeasy FFPT kit (QIAGEN) and 500 ng of total RNA was used for cDNA synthesis using the RevertAid H Minus First Strand cDNA Synthesis Kit (Thermo Scientific). qPCR reactions were all preformed with LightCycler 480 II real-time PCR (Roche). All qPCR primers were previously described in Kim et al. 2013  29. Data were normalized to the expression of the housekeeping gene β -actin. Digital Image Analysis. Digital images were prepared for analyses using the ImageJ. In each image, the area of interest (collagen-blue) was selected and separated from the rest of the field using the Color Threshold tool and analyzed according to hue, saturation and brightness settings. The number of stained pixels was then divided by the number of pixels in the rest of the tissue, in order to calculate the percentage of collagen-specific staining.
Acknowledgments Ron N. Apte  was supported by the following grants:  FP7: Cancer and Inflammation (INFLA-CARE) ,  Israel Ministry of Science (MOS)  jointly with the  Deutsches Krebsforschungscentrum (DKFZ), Heidelberg, Germany , the  Israel Science Foundation  funded by the  Israel Academy of Sciences and Humanities (ISF) , the  United States-Israel Bi-national Foundation (BSF) , the  Israel Cancer Association  and the  Israel Ministry of Health Chief Scientist's Office. Elena Voronov  was supported by the  FP7: Cancer and Inflammation  and the  Israel Science Foundation ,  Israel Cancer Association , the  Israel Ministry of Health Chief Scientist's Office , the  United States-Israel Bi-national Foundation (BSF) , and the  Israel Science Foundation  funded by the  Israel Academy of Sciences and Humanities (ISF).
Genome-wide genotype data were first generated using Illumina Human 610-Quad BeadChips and then imputed by MACH  (25)  against the 1000 Genome Project dataset (http://browser. 1000genomes. org/ index. html). The Institutional Review Board of MGH and the Human Subjects Committee of the Harvard School of Public Health approved the study. To confirm the findings, we replicated the analyses in other lung cancer studies. The top ranked SNPs from the discovery phase were replicated within ILCCO with a two-stage replication approach. First, in silico replication was conducted in those groups that have GWAS and asbestos exposure data, including a study conducted at the University of Texas MD Anderson Cancer Center (MDACC)  (26)  and the Beta-Carotene and Retinol Efficacy Trial (CARET), a randomized chemoprevention trial of heavy smokers or asbestos-exposed workers at high risk of lung cancer  (27).
Genotype data were obtained using Illumina HumanHap3000 v1. 1 BeadChips and imputed by MACH (25) using the 1000 Genome Project dataset. Institutional Review Board approvals were obtained from MDACC and the Kelsey-Seybold Clinic. The CARET study included heavy smokers and asbestos-exposed men who were current or former smokers. The details of the recruitment of the CARET study and the baseline characteristics of the asbestos-exposed subcohort were described previously in Omenn et al. (27)  and Cullen et al. (28) , respectively. In brief, asbestos-exposed men were eligible for enrollment during the years 1989-1993 if they were between 45 and 69 years of age, were current smokers or had quit smoking within the previous 15 years, and had documentation of exposure. Genotype data were measured by Illumina 379Duo and imputed by MACH using the 1000 Genome Project dataset.
Analytic strategy and SNP selection for replication We restricted the analysis to current and ex-smoking Caucasians. The discovery phase included 833 Caucasian cases and 739 Caucasian controls from the Harvard Lung Cancer Study. Quality control for the SNP data was applied to the genetic data from all stages including the discovery and replication stages. SNPs were excluded from further analysis if: (1) p<1×10 -6 for Hardy-Weinberg equilibrium among controls; (2) the minor allele frequency (MAF) was <1%; and (3) the call rate was <90%. The threshold for gene-environment interaction studies from GWAS was yet to be determined due to the few large studies with replication to assess a threshold standard  (33). We used the discovery phase to prioritize SNPs to determine if interactions are considerable and worthy for further replication.
The top associated SNPs were first identified by the discovery phase if the asbestos-gene interaction terms where p<5×10 -5 as determined by likelihood-ratio tests (LRTs) and if the SNPs passed quality control. The identified top ranked SNPs were then replicated by a two-stage approach, including in silico replication among those groups that had both GWAS and asbestos exposure data and de novo genotyping among the groups with available DNA samples and with detailed asbestos exposure information. The asbestos-gene interaction terms p-value < 0. 05 was considered statistically significant during the replication stage. The SNPs that were statistically significant during the in silico replication were then de novo genotyped. The in silico replication included a total of 1,548 cases and 1,527 controls (1,154 cases and 1,137 controls from the Texas Lung Study and 394 cases and 390 controls from the CARET study).
Statistical analysis Genotype frequencies among controls were tested for departure from Hardy-Weinberg equilibrium by the Pearson χ 2 test (df=1). The selected participants' characteristics were evaluated using χ 2 and t tests as appropriate. Likelihood-ratio tests were used to determine whether the asbestos-gene interaction terms departed from a multiplicative interaction model. Multiple logistic regression with additive genetic effect models were used to assess the associations between lung cancer risk and the interaction effects of asbestos exposure and genetic polymorphism using PLINK, version 1. 07  (39). Descriptive statistics were analyzed using SAS® software version 9. 3 (Cary, North Carolina) and R version 3. 1. 1 (The R Project for Statistical Computing, Vienna, Austria; http://www.
03) (Table  2 ). De novo genotyping was conducted for the four SNPs that were successfully replicated in the CARET study. The genotyping failed for the polymorphism rs13053856 in the ICARE study, however the three remaining polymorphisms were replicated with interaction terms p<0. 05 (rs11090910, rs11703832, and rs12170325). The summary of the in silico functional predictions and annotations of these identified SNPs are summarized in Table  3. The polymorphisms rs13053856, rs11703832, and rs12170325 lie at strong enhancers in several cell lines, including the lung fibroblasts NHLK, mammary epithelial HMEC, epidermal keratinocyte NHEK, and skeletal muscle myoblast HSMM, and are likely to affect binding, histone marks, and DNAse sensitivity. To garner sufficient power, stratified analyses of these four SNPs (rs13053856, rs11090910, rs11703832, and rs12170325) were conducted among a pooled dataset.
In the pooled dataset, each unit increase in the natural log-transformed asbestos exposure score was associated with an age-, sex-, smoking status-and center-adjusted Odds Ratio (aOR) of 1. 10 (95% CI = 1. 05-1. 16; p=1. 42 × 10 -4 ) in association with lung cancer risk and aORs of 1. 07 (95% CI = 1. 01-1. 14; p=3. 28 × 10 -2 ) and 1. 19 (95% CI = 1. 11-1. 28; p=6. 39 × 10 -7 ) in association with lung adenocarcinoma and squamous cell lung cancer risk when stratified by disease subtype (Table  4 ). Without considering the genetic effects, the significant asbestos exposure effects were observed in men but not in women (Table  4 ). When stratified by MIRLET7BHG genotypes, asbestos exposure was significantly associated with lung cancer risk among the subjects with MIRLET7BHG variant allele(s) (Table  5 ).
Smoking is a potential confounder for asbestos and most people with asbestos exposure are exposed to smoking simultaneously. Gene-smoking interaction effects by asbestos status were also tested to assess if there was gene-smoking interaction effects in the absence of asbestos exposure. We observed gene-smoking interaction effects only among asbestos exposed subjects (rs12170325 p=0. 03 by LRT; df=1) and a null association in the absence of asbestos exposure. However, after correction for multiple comparisons, this result was not statistically significant. Persons who are exposed to smoking and asbestos simultaneously show more severe deleterious effects of their cells  (64, 65). Our data suggests the potential roles of asbestos exposure and MIRLET7BHG polymorphisms in the context of smoking in lung cancer risk.