dataesr/scientific-paragraphs-categorization huggingface dataset:
36 2. 68 0. 01 2007 67 0. 54 0. 52 3. 72 0. 04* 68 0. 39 0. 38 2. 94 0. 03 Nder 2007 89 0. 54 0. 53 3. 71 0. 01 152 0. 38 0. 36 2. 85 0. 06* Ndieumeul 2007 15 0. 54 0. 47 3. 77 0. 12* 17 0. 37 0. 33 2. 94 0. 11* Mbodjene 2007 18 0. 54 0. 60 3. 43 -0. 11* 21 0. 39 0. 44 2. 72 -0. 13* Southeast Senegal Assoni 2011 154 0. 50 0. 45 3. 55 0. 12** 168 0. 35 0. 32 2. 85 0. 09** Southwest Mali Kokry-Bozo 2007 / / / / / 73 0. 45 0. 42 3. 31 0. 06* doi:10. 1371/journal. pntd. 0003998. t003 DMS1: microsatellite dataset 1. DMS2: microsatellite dataset 2. N μsat : number of successfully genotyped parasites. Hs: unbiased expected heterozygosity. Ho: observed heterozygosity. AR: Allelic richness. # : minimum of 10 alleles used for rarefaction. ## : minimum of 14 alleles used for rarification. Statistical significant F.
, 2011). This evaluation will inform the development of a non-animal testing strategy for skin sensitisation potency predictions. The resulting strategy will ultimately become an essential part -along with consideration of exposure and other information such as bioavailability or metabolism -of a data integration approach for the skin sensitisation safety assessment of cosmetic ingredients. Here we document the first of three phases to develop such a non-animal testing strategy. Sixteen test methods were identified for systematic evaluation, following a review of the available scientific literature. The aim of this evaluation was to gain comparable detailed understanding of the test methods that would allow promising methods to be prioritised for further in-depth evaluation. Therefore, a common set of criteria was assessed involving test method characterisation and standardisation.
Direct peptide reactivity assay (DPRA, Procter & Gamble) The DPRA is a chemistry-based assay that evaluates reactivity of a test compound using two synthetic model peptides including a lysine or cysteine residue. A solution of peptide and test substance in a ratio of 1:10 for cysteine and 1:50 for lysine is incubated for 24 h. After the incubation period, the remaining concentration of the free peptide is measured by high performance liquid chromatography (HPLC) with gradient elution and ultraviolet (UV) detection at 220 nm. Depending on the data obtained from triplicate reactions, averaged peptide depletion of cysteine, lysine or both are used in classification tree models to identify substances as sensitising or non-sensitising. In addition, the prediction model allows the allocation of the protein to the reactivity classes minimal, low, moderate and high  (Gerberick et al.
Peroxidase peptide reactivity assay (PPRA, Procter & Gamble) The PPRA was developed from the DPRA in order to better identify potential pro-and pre-haptens. Eight concentrations of chemical are tested -instead of one concentration as in the DPRA. The cysteine peptide is incubated for 24 h in the presence and absence of horseradish peroxidase/hydrogen peroxide (HRP/P), whilst the lysine peptide is used only without HRP/P. Following incubation, all concentrations are processed for analysis by HPLC/mass spec-trometry (MS)/MS (maximum concentrations of test compound: 5 mM for cysteine, 25 mM for lysine). From the concentrationresponse peptide depletion data the effective concentration of a test substance that depletes peptides by 25% (i. e. , EC25) is estimated by fitting a three-parameter log-logistic model.
Epidermal equivalent (EE) potency assay (VU University medical Centre) The epidermal equivalent (EE) potency assay aims to classify sensitiser potency using epidermal equivalents, which requires prior identification of a substance as a sensitiser. In the literature, the NCTC 2544 IL-18 assay has been used to provide this information. Substances (spread on filter papers) are topically applied to the EE at a range of 12 concentrations for 24 h. The effective chemical concentration required to reduce cell viability by 50% relative to vehicle-exposed culture (EE-EC50) is calculated using the MTT assay. The EE-EC50 are then assigned to a potency category using a prediction model correlating previous results with local lymph node assay (LLNA) data  (dos Santos et al. , 2011; Gibbs et al. , 2013).
Expression of four housekeeping and seven target genes (NADPH-quinone oxidoreductase 1, Aldoketoreductase 1C2, Interleukin 8, Cytochrome P450 1A1, Aldehyde dehydrogenase 3A, Heme-oxygenase 1, Glutamate cysteine ligase catalytic subunit C) is monitored after topical exposure of the model skin tissues to the test substances at a range of six concentrations (0. 1, 5, 100, 250, 500, and 2500 lM) for 24 h. Concentrations, which result in cell viability of less than 50% compared to the vehicle control, are disregarded for the determination of the sensitising potential/potency. Finally, a gated algorithm is used to transform the viability, gene induction and glutathione reactivity data into a toxicity index for each substance. This method covers key event 1 (in terms of protein reactivity) and 2 (in terms of keratinocyte activation) in the skin sensitisation AOP.
(2014)  and LLNA (EC3, categorised in 5 classes) data. EC3 values will be harvested from existing publications and qualify for inclusion only if certain criteria, including the specification of the vehicle, test concentrations and stimulation indices, are fulfilled. Variability associated with replicate EC3 values will be taken into account. To reach this aim of developing a non-animal testing strategy for potency prediction, three phases frame our efforts (Fig. 2 ). The outcome of the first of these phases, the evaluation of existing test methods supporting prioritisation for further consideration is presented here. Sixteen test methods with data in common for a set of 10 substances were considered during this evaluation. With the exception of test methods developed by member companies of Cosmetics Europe (i.
e. DPRA, h-CLAT, MUSST and PBMDC) that provided existing data from non-blinded testing, coded substances were tested. However, for calculation of the predictivity of most methods including these four, available data on additional chemicals were considered (in most cases P40 substances, Table  4 ), so that potential impact of coded versus non-coded testing on predictivity become marginal. With the cooperation of the test method developers, additional information relevant to a pre-defined list of criteria that addressed a number of parameters including the level of standardisation, existing test data, potential for throughput, transferability and accessibility was systematically collated. The outcome of this evaluation was reviewed by each test method developer, discussed at a workshop with the method developers, and ultimately informed the prioritisation of test methods for phase II of the evaluation process.
It is planned that test results from all eight phase II methods for all substance will be available. For each test method the data considered most useful for the testing strategy composition will be defined. This implies that the potential contribution of read-out parameters -instead of currently applied prediction models -to the strategy will be explored, especially for the methods that on hazard assessment. For example, for the DPRA relative cysteine and lysine depletion will be used. It has to be noted that properties of the data of the various methods differ. While the methods of first priority have a few relevant read-outs to be captured, this will be more complex for other methods, such as Sens-IS or GARD that measure an array of genes. Variability of the methods will be accounted for.
Predictive performance will be assessed correlatively/probabilistically against the reference human and LLNA data or a combination thereof. Although efficiency and other factors, such as availability or duration, may -at least at this stage -not be accounted for, it is nevertheless expected that the strategy will comprise a limited number of test methods. In the third phase of the framework, applicability domain issues specifically relevant for substance used by cosmetic industry will be addressed. It is anticipated that for inherently problematic substance types, such as natural extracts, dyes or polymers, further data may be required in order to provide sufficient evidence that the testing strategy works for these substance types or to optimise the adaptation of the strategy. The resulting non-animal testing strategy for skin sensitisation potency predictions will be combined with bioavailability and skin metabolism data, exposure consideration and in exceptional cases with data from T cell activation assays, to satisfy the ultimate goal of a data integration approach for skin sensitisation safety assessment of cosmetic ingredients.
TesƟng of challenging cosmeƟc substances Focused tesƟng to explore applicability domains of the prioriƟsed test methods to opƟmise the tesƟng strategy Fig. 2. Cosmetics Europe's three-phase framework for development of a non-animal testing strategy for skin sensitisation potency prediction (CLP: Classification, Labelling and Packaging; GHS: Globally Harmonised System). In phase I 16 non-animal test methods were evaluated based on predefined criteria detailed in Table  1. In phase II an extensive database will be generated comprising more than 100 chemicals, for which human data and LLNA EC3 values are available. This resulting data set will used to develop a test strategy for predicting hazard identification and characterisation (potency) with non-animal test methods only. In phase III the test strategy will be optimised after challenging the prioritized methods with compounds of specific interest for cosmetic industry (e.
Statistical Analysis The global normality test for A1/A2 yielded P = 0. 357, suggesting normal distribution. The difference in A1/A2 lameness values between sham and groove limbs was determined using a one-way ANOVA followed by the Dunnett test. Biochemical values were normally distributed, and their variances were equal, as revealed by the Levene test. Biochemical data were analyzed with a two-way repeated-measures ANOVA (post hoc test using winner). Cytology scores were not normally distributed and were analyzed with non-parametric two-way repeated-measures ANOVA. Radiographic, macroscopic, cytologic and histologic scores were represented by the median ± median absolute deviation. Radiographic data were analyzed using the Kruskal-Wallis test with a Wilcoxon pairwise comparison. Macroscopic and microscopic scores were analyzed with a Wilcoxon signed-rank test.
phagocytophilum infection  [23]. The pattern of mRNA and protein levels for the five Ago paralogs described in I. scapularis  [16]  differed from those observed for Tudor-SN, providing additional evidence for the different role of these molecules in response to pathogen infection in ticks (Fig  3A ). The fact that particular transcripts or proteins were not found in transcriptomics or proteomics data could be due to several factors. It could be that these transcripts or proteins are difficult to detect due to technical problems associated with current technologies and databases. However, if a particular transcript or protein is found in one of the samples but not in others, then it is very likely that mRNA or protein levels were too low to be detected in these samples, which is equivalent to showing no significant differences between infected and uninfected ticks.
Annotation of putative Tudor-SN in I. scapularis For annotation of putative Tudor-SN, I. scapularis genome sequence assembly JCVI_ISG_i3_ 1. 0-NCBI reference sequence NZ_ABJB000000000 (GenBank accession ABJB010000000; http://www. ncbi. nlm. nih. gov/nuccore/NZ_ABJB000000000) was used. Gene identifiers were obtained from VectorBase (www. vectorbase. org) and compared to the corresponding pathways in Drosophila melanogaster, Anopheles gambiae, Aedes aegypti and Homo sapiens. The Conserved Domain Database (http://www. ncbi. nlm. nih. gov/cdd) was used for the annotation of functional units in I. scapularis Tudor-SN. Multiple sequence alignment was conducted using ClustalW2 (http://www. ebi. ac. uk/Tools/msa/clustalw2/) and BLAST (bl2seq; http://blast. ncbi. nlm. nih. gov) for amino acid and nucleotide sequences, respectively.
Transcriptomics and proteomics analyses Transcriptomics and proteomics analyses were conducted using duplicate RNA and protein samples extracted from uninfected and A. phagocytophilum-infected I. scapularis nymphs and adult female guts and salivary glands as previously described  [23]. Briefly, RNA sequencing was done using 100 bp paired-end reads on Illumina Hiseq 2000 (CD BioSciences, Shirley, NY, USA). TopHat  [42]  was used to align the reads to the I. scapularis (assembly JCVI_ISG_i3_1. 0; http://www. ncbi. nlm. nih. gov/nuccore/NZ_ABJB000000000) reference genome. Raw counts per gene were estimated by the Python script HTSeq count (http://www-huber. embl. de/users/ anders/HTSeq/) using the reference genome. The raw counts per gene were used by DEGseq  [43]  to estimate differential expression at P<0.
4. 0. 29, Thermo Fisher Scientific) using a Uniprot database containing all sequences from Ixodida (May 17, 2013). Peptide identification was validated using the probability ratio method  [45]  and false discovery rate (FDR) was calculated using inverted databases and the refined method  [46]  with an additional filtering for precursor mass tolerance of 12 ppm. Only peptides with a confidence of at least 95% were used to quantify the relative abundance of each peptide determined as described previously  [47]. Protein quantification from reporter ion intensities and statistical analysis of quantitative data were performed as described previously using QuiXoT  [48, 49]. For iTRAQ data, only the intensity of the reporter ions within 0. 4 Da windows around the theoretical values was considered for quantification.
Reporter intensities were corrected for isotopic contaminants by taking into consideration the information provided by the manufacturer. The intensity of the reporter peaks was used to calculate the fitting weight of each spectrum in the statistical model as described previously  [49]. Outliers at the scan and peptide levels and significant protein-abundance changes were detected from the z values (the standardized variable used by the model that expresses the quantitative values in units of standard deviation) by using a false discovery rate (FDR) threshold of 5% as described previously  [49]. Results were the mean of two replicates. All relevant data including accession to transcriptomics and proteomics mediated data can be found in Ayllón et al. [23].
3) [35]. The following organisms and sequences available at GenBank were used in the Tudor-SN phylogenetic analysis: I. scapularis (XP_002415051); Daphnia pulex (EFX77404); Nematostella vectensis (XP_001635744); Strongylocentrotus purpuratus (XP_798852); D. rerio (NP_878285); Pongo abelii (NP_001125262); H. sapiens (BAD92747); Oryctolagus cuniculus (XP_002712124); Mus musculus (NP_062750); A. aegypti (XP_001654799); Xenopus laevis (NP_001079606); Hydra magnipapillata (XP_ 002163890); Culex quinquefasciatus (XP_001848537); Tribolium castaneum (XP_974879); Nasonia vitripennis (NP_001153329); D. melanogaster (NP_612021); Seriola quinqueradiata (BAC65164); D. yakuba (XP_002092984); Bombyx mori (NP_001182009); Caenorhabditis.
This research was supported by grants  BFU2011-23896  and the  European Union   FP7   ANTIGONE  project number  278976  (JdlF). NA was funded by  Ministerio de Educacion y Ciencia, Spain. VN was funded by the  European Social Fund  and the  Junta de Comunidades de Castilla-La Mancha  (Program FSE 2007-2013), Spain. RS was supported by the project  Postdok_BIOGLOBE  ( CZ. 1. 07/2. 3. 00/30. 0032 )and by the Grant 13- and feeding but no strong evidence for a role in innate immune responses to pathogen infection was found. 12816P (GA CR). OH was supported by the  Grant Agency of the Czech Republic  grant no. 13-27630P  and  European Union   FP7   MODBIOLIN  project number  316304. CR and LBS were supported by the  United Kingdom Biotechnology and Biological Sciences Research Council 's  National Capability Grant  to the  Pirbright Institute.
Invasive aspergillosis (IA) has poor prognosis in immunocompromised patients. Skin manifestations, when present, should contribute to an early diagnosis. The authors aimed to provide prevalence data and a clinical and histologic description of cutaneous manifestations of primary cutaneous IA (PCIA) and secondary CIA (SCIA) in a unique clinical series of IA and present the results of an exhaustive literature review of CIA. Cases of proven and probable IA with cutaneous manifestations were retrospectively extracted from those registered between 2005 and 2010 in a prospective multicenter aspergillosis database held by the National Reference Center for Invasive Mycoses and Antifungals, Pasteur Institute, France. Patients were classified as having PCIA (i. e. , CIA without extracutaneous manifestations) or SCIA (i.
Data Source The prospective active Surveillance des Aspergilloses Invasives en France (SAIF) network is a French anonymous centralized database (National Reference Center for Invasive Mycoses and Antifungals, Institut Pasteur, Paris) relying on voluntary (as the declaration of IA cases is not mandatory) but systematic declaration of IA by mycologists from predefined university hospitals in France. 5 On the standardized anonymous declaration, a web-based file, practitioners had to systematically mention the presence of skin involvement. All records with cutaneous involvement for January 2005 to July 2010 were extracted and analyzed.
Selection of Patients Proven and probable cases of IA were retained according to the EORTC/MSG definition criteria (criteria published in 2002 for the period 2005-2007  10  and published in 2008 for 2008-2010). 1  We first extracted from the database all cases with notified cutaneous involvement. Then, we systematically reviewed patient charts. We included patients with cutaneous lesions in accordance with previously published lesions suggestive of cutaneous aspergillosis  8  or infectious dermatitis (ie, papules, nodules, necrosis, pustules, ulcerations, and/or suppuration), then classified patients as having proven or probable CIA as follows: (1) Proven CIA was defined by a skin biopsy showing histologic evidence of compatible hyphae and/or positive mycological culture of the skin biopsy.
(2) Probable CIA was considered in patients with proven or probable IA and skin involvement clinically compatible with an infectious origin but no histologic features of fungal infection and no positive skin culture biopsy. To consider these patients as having probable CIA, a positive cutaneous mycological sample taken by swab, however, was needed. The following data were recorded from files for patients with proven or probable CIA: age, sex, underlying disease, clinical features and localization of cutaneous lesions, time between cutaneous lesion appearance and the skin biopsy, fungal identification, treatment, and 3-month survival. Skin biopsies were retrospectively reviewed by a dermatopathologist of our team (NO) with blinding to the type of CIA (primary or secondary). Two groups of patients were defined: those with PCIA (ie, presenting a unique skin lesion and no visceral involvement) and those with SCIA, characterized by the association of skin and visceral involvement or the presence of multiple cutaneous lesions (in 2 or more noncontiguous areas) suggestive of disseminated disease even in the absence of organ involvement.
Collection of Data In total, 1410 cases of proven or probable IA were registered in the SAIF database, and 21 had cutaneous involvement noted (Figure  1 ). Six patients were excluded after systematic analysis of corresponding medical charts [cutaneous manifestations not consistent with cutaneous infection (drug reaction), N ¼ 4; unavailable chart, N ¼ 1; no histologic or mycological criteria, N ¼ 1]. We included 15 patients, allowing to estimate to 1. 06% the prevalence of skin lesions in proven or probable IA. According to our definitions, 13 patients presented proven CIA (skin histology findings, N ¼ 9; positive mycological culture of skin biopsy, N ¼ 13) and 2 probable CIA (positive swab culture). Five patients had PCIA and 10 had SCIA.
Epidemiological Data and General Conditions The median age of patients was 56 years (range 1-90) and 9 (60%) were men; 12 (80%) had an underlying hematological malignancy and 4 (26%) a solid organ transplant (2 liver transplant, including a patient also with hematological malignancy, 1 heart, and 1 kidney transplant). Visceral involvement in SCIA included the central nervous system (2/10), pulmonary (7/10), cardiac (1/10), and sinus (1/ 10). In 5 patients of PCIA, no systemic involvement was recorded. Fever defined by temperature >38 8C was present in 5/10 SCIA and 5/5 PCIA cases. Septic shock was reported in 2/10 SCIA cases (1 because of Escherichia coli infection and 1 not documented) and 1/5 PCIA cases (not documented). In total, 1/5 patients with PCIA had an intravenous catheter adjacent to the fungal cutaneous lesion.
HEV-only infection experiment A transmission trial with HEV only has been carried out before the co-infection experiment  [25]. The experiment was conducted in Anses air-filtered level-3 biosecurity facilities. Briefly, sixty-eight SPF Large-White piglets were used for the experiment. Eight pigs were kept as negative controls and the others were allocated to six rooms containing two pens per room. Rooms 1 to 3 were used to evaluate direct and environmental transmission, whereas Rooms 4 to 6 were used to examine between-pen transmission. The inoculated pigs received orally 10 8 ge (genome equivalent) under a volume of 10 mL of a genotype 3 HEV suspension (strain FR-SHEV3e, Genbank access number JQ953665). Individual fecal samples were collected four days before inoculation and three times per week from 0 to 39 days postinfection (dpi) when the pigs were killed for necropsy.
Room 2 contained 2 pens separated by a solid partition to prevent contamination of a pen by the other one (Figure  1 ). The average weights at weaning (sd) were 9. 5 kg (2. 7), 9. 3 kg (1. 6), 9. 3 kg (2. 3) and 9. 3 kg (1. 4) for Controls and groups #1, #2 and #3 respectively. In each pen, 3 piglets were inoculated with both HEV and PRRSV at day 0. For inoculation, piglets to be inoculated were grouped in a pen and they were put in contact with their corresponding pen-mates at day 1. The 3 inoculated piglets received the following: (i) orally 10 8 ge under a volume of 10 mL of a genotype 3 HEV suspension (strain FR-SHEV3e, Genbank access number JQ953665) prepared according to the protocol previously described in Andraud et al. [25]  (ii) and by nasal route 2. 5 mL per nostril of a PRRSV suspension (strain PRRS-2005-29-24-1 "Finistere", genotype 1, subtype 1) titrating 10 5 TCID 50 /mL.
Data collection Individual fecal samples were collected three days before inoculation and three times a week until the end of the experiment (49 dpi). Blood samples were collected before inoculation and once a week until the end of the experiment. Clinical examination was also performed (clinical signs, rectal temperature, feces consistence, weight, food consumption and trough cleanliness were recorded daily). Euthanasia was carried out by intravenous injection of 1 g/ 50 kg live weight of Nesdonal® (thiopental-sodium, Merial, Lyon, France) followed by exsanguination. Necropsy was performed and liver samples were taken. Because HEV is a zoonotic agent, strict biosecurity measures were applied to prevent any transmission from pigs to animal technicians.