dataesr/scientific-paragraphs-categorization huggingface dataset:
e. checking the bibliography of the key full-text papers for further potential relevant studies) and an update of the literature search performed following the same search strings and criteria on 21 November 2017. Similarly, studies on the adverse effects of PCDD/Fs and DL-PCBs in experimental animals (subquestion 2, narrative approach and subquestions 3 and 9, structured approach) were identified by performing an ELS in two different databases (Web of Science and PubMed), followed by a selection for relevance according to the eligibility criteria and data extraction as set in Annex A. 1. This task was outsourced to an external contractor (contract: NP/EFSA/BIOCONTAM/2016/07). The search strings and outcome of the selection for relevance steps are shown in the external scientific report of wca environment  Ltd (2018).
Farm and companion animals risk assessment Studies on the adverse effects of the target compounds in farm and companion animals (subquestions 16 and 17, structured approach) were identified by performing an ELS in two different databases (Web of Science and PubMed), followed by a selection of relevance according to agreed eligibility criteria and data extraction as set in Annex A. 1 to this scientific opinion. This task was performed by EFSA staff in collaboration with members of the Working Group. The search strings and outcome of the selection for relevance steps are shown in Annex A. 2. The outcome of this exercise was complemented with further studies found by snowballing during the development of the opinion. Studies on the toxicokinetics in farm and companion animals and on the transfer of the target compounds from feed to animal-derived food products (subquestions 18 and 19, structured approach) were identified by performing an ELS in two different databases (Web of Science and PubMed), and further selection for relevance as set in Annex A.
Feed consumption data In the absence of a comprehensive database on the amounts or types of feed consumed by livestock in the EU, estimates of feed consumed for each of the main categories of farmed livestock and companion animals are based on published guidelines on nutrition  (Carabano and Piquer et al. , 1998; NRC, 2007a,b; Leeson and Summers, 2008; McDonald et al. , 2011; EFSA FEEDAP Panel, 2012; OECD, 2013) , together with expert knowledge of production systems in Europe. For many farmed livestock and companion animals, their nutritional requirements are provided in commercially manufactured complete (compound) feeds. Where sufficient (reliable) data on the concentrations of PCDD/Fs and DL-PCBs in compound feeds have been provided, these have been used to estimate exposure. However, where insufficient compound feed data were available, the CONTAM Panel identified example diets and feed inclusion rates, and used concentrations of PCDD/Fs and DL-PCBs in individual feed materials to estimate P95 and mean exposure both LB and UB.
Food consumption data The EFSA Comprehensive European Food Consumption Database (Comprehensive Database) provides a compilation of existing national information on food consumption at individual level. It was first built in 2010  (EFSA, 2011a; Huybrechts et al. , 2011; Merten et al. , 2011). Details on how the Comprehensive Database is used are published in the Guidance of EFSA  (EFSA, 2011a). The latest version of the Comprehensive Database 17  was used with subjects classified in different age classes as follows: • Infants: < 12 months old • Toddlers: ≥ 12 months to < 36 months old • Other Children: ≥ 36 months to < 10 years old • Adolescents: ≥ 10 years to < 18 years old • Adults: ≥ 18 years to < 65 years old • Elderly: ≥ 65 years to < 75 years old • Very Elderly: ≥ 75 years old. Two additional surveys provided information on specific population groups: 'Pregnant women' (≥ 15 years to ≤ 45 years old; Latvia) and 'Lactating women' (≥ 28 years to ≤ 39 years old; Greece).
Human exposure assessment The method used to perform the human exposure assessment is described in the strategy in Annex A. 1 of this Scientific Opinion. The CONTAM Panel considered that only chronic dietary exposure had to be assessed. As suggested by the EFSA Working Group on Food Consumption and Exposure (EFSA, 2011a), dietary surveys with only one day per subject were excluded from the current assessment because they are not adequate to assess repeated exposure. Similarly, subjects who participated only 1 day in the dietary studies, when the protocol prescribed more reporting days per individual, were also excluded from the chronic exposure assessment. When, for one particular country and age class, two different dietary surveys were available only the most recent one was used. For calculating the chronic dietary exposure, food consumption and body weight data at the individual level were accessed in the Comprehensive Database.
This applies not only to eel from contaminated rivers and lakes, but also to various fatty fish species from, e. g. the Baltic Sea. When included in the occurrence data this may result in an overestimation of the exposure from such fish in areas where they are not consumed, and vice versa. Fish from, e. g. the Baltic Sea should be monitored to a higher extent and as such there may be a bias towards relatively high levels in the data submitted to EFSA. However, when compliant with the MLs (including measurement certainty), this fish can be put on the EU market and as such it seems not correct to exclude them from the database. It is known that in the EU, the large majority of the salmon and trout on the market is farmed, and it is widely consumed. 18 In order to investigate the impact of excluding wild salmon and trout from the data set, exposure was calculated including and excluding wild salmon and trout (see  Section 3.
5. 1). For matching the occurrence and the consumption data, occurrence data from samples of solid tea and herbs for infusions, and infant formulae were converted to the corresponding beverages by applying specific factors (75 and 8, respectively) which are commonly used in other similar EFSA opinions. To perform the exposure assessment, the occurrence data that are expressed on a fat weight basis, were combined with the fat per cent of the consumed foods as it is reported in the national consumption surveys in the Comprehensive Database. Fat contents available in the Comprehensive Database are included according to the national composition tables of Member States. Where the fat content was missing in the consumption database, the random hot-deck imputation method was used to complete this information.
Norwegian Mother and Child Cohort (MoBa) The MoBa is a prospective population-based pregnancy cohort that includes 95,000 pregnant women and their 114,000 children born between 1999 and 2008  (Magnus et al. , 2006 (Magnus et al. , , 2016)). The women filled in questionnaires throughout pregnancy and donated blood and urine in the second trimester. Furthermore, parents replied to questionnaires at regular time points while children were growing up (e. g. 6 months, 18 months and 3 years). Maternal exposure to PCDD/Fs and DL-PCBs  (year 2002-2009, n = 83,524)  has been assessed by a semiquantitative FFQ and a database on concentrations of PCDD/Fs and DL-PCBs in food in Norway  (Caspersen et al. , 2013). Maternal median dietary intake was 3. 92 (interquartile range (IQR) 2. 59) pg WHO 2005 -TEQ/kg bw per week (LB).
Blood sample for routine TSH analysis was usually taken about 3 days after birth. This was also the case in the smaller subgroup, but for this group the timing of blood TSH was missing for several of the children whose mothers had high plasma TCDD levels (M. Bonzini, 2016-2017, see documentation submitted to EFSA). Timing of blood TSH sampling is important since TSH may decrease with a factor of 5-10 during the first 2-3 days after birth  (Alexander, 2017; Steinmaus et al. , 2010). It is unlikely that timing has confounded the large group-based study, but in the small substudy with individual TCDD levels, missing data on timing of blood TSH makes the quantitative association between TCDD levels and TSH uncertain in this subgroup. The larger, area-based study provides relatively strong support for an association for prenatal/perinatal exposure to TCDD and increased blood TSH in neonates, but it lacks individual dioxins biomonitoring data.
(1999). A jobexposure matrix was developed for assigning an exposure score to each worker, which was the basis for grouping workers in septiles. There was no information on smoking or other potential confounders. Cox-regression showed an increasing trend for mortality in ischaemic heart disease with the following point estimate HRs in septiles 2-7: 1. 23, 1. 34, 1. 30, 1. 39, 1. 57 (95% CI 0. 96-2. 6) and 1. 75 (95% CI 1. 1-2. 9). However, also lung cancer risk tended to increase with the TCDD exposure score, making the lack of smoking data problematic. In a subsequent paper  (Steenland et al. , 2001) , the TCDD exposure for the exposure scores was estimated (in a risk assessment of cancer). A cumulative exposure score of 10,000 would correspond to 19,000 pg/g-years (lipid adjusted). This means that a cumulative exposure score of 20,000, which was the cut-off between septiles 6 and 7 in  Steenland et al.
Standardised mortality ratios (SMRs) were calculated with the population of Hamburg as reference. Exposure to TCDD was estimated from yearly work histories, and serum (or in some cases fat) analyses of TCDD in 275 workers  (Flesch-Janys et al. , 1998). There was also exposure to other PCDD/Fs  (Flesch-Janys et al. , 1998). The overall SMR for cardiovascular mortality was 1. 16 (95% CI 1. 02-1. 3, 251 deaths) in men and 0. 74 (95% CI 0. 6-0. 9, 58 deaths) in women. The median estimated cumulative TCDD exposure was 77 pg/g-years (lipid adjusted) in men and 20 in women. No information was available on potential confounders, but smoking prevalence in a subgroup of workers did not differ from that of the general population. Two studies published data on cardiovascular disease and risk factors in workers exposed to TCDD at a Czech plant producing 2,4,5-trichlorophenoxyacetic acid (TCPA) in the 1960s.
The all cancer incidence was not different from that expected in any of the contaminated zones (A, B and R). There was no clear pattern of cancer cases in terms of time since the incident or the zone of exposure due to the small number of cases. Warner et al. (2002)  using data from the Seveso Women's Health Study showed that individual serum TCDD levels correlated with breast cancer incidence at 20 years after the incident. The hazard ratio (HR) for breast cancer increased to 2. 1 and was associated with a 10-fold rise in serum TCDD. The average time from exposure to breast cancer development was 15. 2 years after the explosion. The sample size in this study was small (15 cases) and the average age of the population studied was only 40 years, which is relatively young for development of breast cancer.
The results in this study indicate that the NOAEL for TCDD in rainbow trout was 0. 0108 lg TCDD/kg fish per day. Rainbow trout were exposed by single i. p. injection to TCDD doses of 0 (vehicle), 1, 5, 25 or 125 lg TCDD/kg bw  (Spitsbergen et al. , 1988a). After 80 days, there was no mortality in the control or the lowest dose group, and 20%, 90% and 95% mortality in the 5, 25 and 125 lg TCDD/kg bw groups, respectively. The 80-day LD 50 was determined to be 10 lg/kg bw. Another group of rainbow trout were injected (i. p. ) with 0, 0. 1, 1 or 10 lg TCDD/kg bw. Gross and microscopic lesions were present in fish at the highest dose, but not in the other groups. Haematological effects included reduced numbers of leucocytes and thrombocytes in fish treated with 1 or 10 lg TCDD/kg bw compared to the control group; no haematological data were presented for the trout exposed to 0.
In relation to this issue of the external dose, the outcome of the EU SYSTEQ project is of interest  (Larsson et al. , 2015). This project dealt with the issue that once present in the body, relative potencies of congeners may change. Higher potencies (so-called consensus toxicity factors) than the WHO 2005 -TEFs were e. g. observed  for 2,3,4,7,8-PeCDF  and 1,2,3,4,7,8 -HxCDF, both congeners that may contribute much to TEQ levels. In addition, also species differences in relative potencies are important. For example, it was shown that various types of human cells, both primary cells and cell-lines, are much less sensitive to PCB-126 than suggested by the TEF of 0. 1. The CONTAM Panel noted that this is based on endpoints like induction of CYP 1A1, 1A2, 1B1, AHRR and EROD activity. However, according to the database with REPs used in the last TEF evaluation, a similar situation seems to apply to mice, with lower potency of PCB-126 when focusing on CYPs and related activities  (Haws et al.
Occurrence data submitted to EFSA A total of 1,006,148 results (individual congeners) from 46,982 samples on PCDD/Fs and DL-PCBs on food and feed were available in the EFSA database. The CONTAM Panel decided to only consider the samples taken after year 2010. Thus, 176,351 result from preceding years  (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009)  were excluded from the original data set. The resulting data set included a total of 824,905 analytical results corresponding to 35,252 samples submitted to EFSA between 2010 and December 2016. Data providers were contacted to clarify a number of possible inconsistencies which were identified during the data check. The following modifications were made to the initial data set based on the feedback received: • All results were converted to the unit of measure (pg/g) laid down in Commission Regulation (EC) No 1881/2006 33 as subsequently amended.
Feed The presence of high levels of PCDD/Fs and/or DL-PCBs in feed or materials used for feed production has been the source of a number of contamination incidents in the feed and food chain (see  Section 1. 3. 1). The European Commission's former  SCAN (2000)  evaluated the contribution of PCDD/Fs and PCBs in feedingstuffs to the contamination of food of animal origin. Only levels of PCDD/Fs were reported as the database for DL-PCBs was scarce. Feed groups considered were vegetable feed materials (including, e. g. roughage, roots and tubers and cereals), feed materials of animal origin (including, e. g. fishmeal, fish oil, meat and bone meal, animal fat), other feed material (including trace elements, macrominerals, binders and anticaking agents) and soil. Fish oil and fishmeal were the most contaminated feed materials (mean PCDD/Fs values ranging from 0.
This may be in particular relevant for fish, regarding its contribution to exposure. Certain fish species (e. g. salmon and herring) from the Baltic area were shown to contain much higher levels than those reported by countries close to other fishing areas (see Section 3. 2. 1). It was decided not to remove these data from the database or selectively use them for certain consumption surveys, since at least part of this fish can be exported to other European countries, provided that they are compliant with the legal limits. Furthermore, some food surveys from countries surrounding the Baltic Sea indicated frequent consumption of herring, which may be locally caught. It is also not clear what fraction of the fish in countries around the Baltic Sea is imported from other areas. It is also possible that the consumption of other commodities produced and consumed locally in high contaminated areas (e.
The CONTAM Panel considered this uncertainty small for the exposure assessment based on mean levels in all salmon/trout in the database. However, on an individual basis, the CONTAM Panel noted that the impact on exposure can be large when fatty fish, e. g. from the Baltic Sea is regularly consumed. It has to be considered that almost all occurrence data come from official food and feed control and thus were mainly generated to check for compliance with legal limits. Therefore, the sensitivity of the applied analytical methods are generally fitted to check compliance to the legal limits and not necessarily to background levels. This is to some extent covered by the performance criteria for analytical methods applied in official control and also used for data selection. Since the differences between LB and UB levels were not substantial, this should have made a minor contribution to the uncertainty.
Consumption data Uncertainties and limitations related to the use of the EFSA Comprehensive Food Consumption Database have already been described by EFSA (EFSA, 2011a) and are not further detailed in this Scientific Opinion. These relate to the use of different dietary survey methodologies, standard portion sizes, representativeness of samples included in surveys, or to the inclusion of consumption surveys covering only few days to estimate high percentiles of chronic exposure. This last point would lead to an overestimation of the P95 exposure.
• In case of occurrence data expressed on a fat weight basis, the contamination level was combined with the fat per cent of the consumed foods, as reported in the national consumption surveys in the Comprehensive Database. Where the fat content was missing, the random hot-deck imputation method (see  Section 2. 3. 1. 4) was used to input a value. This could lead to both over-and underestimation of the exposure. For the exposure assessment, the CONTAM Panel applied criteria to reduce the uncertainty in the levels and inherent exposure assessment. The main criterion is that the LOQ should be fivefold lower than the ML for PCDD/F-TEQ, or threefold lower than the AL for DL-PCB-TEQ. Another criterion for the acceptable difference between LB and UB, previously applied by EFSA, was omitted because it resulted in the possible removal of levels in the lower part of the distribution.
ACKNOWLEDGMENT This work was financially supported by  EC  through the  ERC Proof-of- Concept  project  FlexNanoOLED  ( GA-766936 ) and the  Marie Curie ITN  project  iSwitch  (GA No. 642196 ), the  Labex  project  CSC  ( ANR-10-LABX-0026 CSC ) within the  Investissement d'Avenir program   ANR-10-IDEX-0002-02 , and the  International Center for Frontier Research in Chemistry (icFRC).
Study Population and Experimental Design This was a prospective, longitudinal cohort study of male adult (≥18 years) military recruits who had recently arrived in the UK from Nepal. The Nepalese vaccination policy for TB is to immunize once at birth with BCG and the latest estimates of TB incidence in Nepal are 154 (136-174) per 100,000 population  (27). Participants were recruited between 2012 and 2015 and routine entry screening data were collected, including full blood count, stool analyses for gastrointestinal parasites (GIP), and serology for Strongyloides stercoralis infection. LTBI status was determined by IGRA testing using the T-SPOT. TB enzyme-linked immunospot (ELISPOT) assay (performed by Oxford Immunotec, Abingdon, United Kingdom). IGRA testing was repeated 3-6 months after the completion of treatment for GIP to assess its impact on IGRA conversion rates.
Gene Expression Microarray Transcriptomics Peripheral blood was collected in PAXgene © tubes and stored at -80 • C until required for whole blood transcriptomic studies as previously described  (33). Samples were subsequently thawed at room temperature for 2 h, total intracellular RNA was extracted using the Blood RNA Kit (Qiagen) and the purity and quantity of RNA was assessed prior to storage at -20 • C. Globin mRNA was depleted using the GLOBINclear Kit (Ambion), amplified and biotin-labeled using the TotalPrep RNA Amplification Kit (Illumina). RNA was purified and the quality assessed using an Agilent bioanalyser. Biotinylated cRNA was hybridized to Illumina HumanHT-12 (v4. 0) expression beadchips according to the manufacturer's instructions. Beadchips were scanned with an Illumina iScan bead array reader confocal scanner and data extracted using GenomeStudio software.
Microarray Analysis Raw, probe level summary values as exported from Illumina GenomeStudio 2011 of Illumina HumanHT-12 (v4. 0) microarrays were imported into R using beadarray  (35). Probes were background corrected followed by quantile normalization using the neqc command  (36). The analysis was restricted to probes with a detection p < 0. 05 in at least 10% of the samples and probes matching to GENCODE version 26 with at most 2 mismatches. A linear model was fitted using limma to determine differential expression including parameters for sample collection batch effects, as well as unobserved batch effects, by the inclusion of the first three surrogate variables as provided by the R package sva  (37, 38). Array quality weights were incorporated in order to account for between array quality differences  (37, 39).
Statistical Analysis Statistical analysis was performed using GraphPad Prism Software Version 6. 0 (GraphPad, La Jolla, CA, United States) and SPSS Statistics Version 22. 0 (IBM, United States). Specific statistical tests used are indicated in the results. For unsupervised clustering, one minus the Pearson correlation coefficient was used as dissimilarity metric to cluster samples, and complete linkage was used as the agglomeration rule.
Whole blood and PBMC MGIT using M. tb H37Rv was performed to assess mycobacterial control. Whole blood samples were available from uninfected controls (n = 9) and matched pre-and post-treatment samples from hookworm infected individuals (n = 13) (A). The relationship between mycobacterial net growth and hematology parameters was investigated. After testing for normality, Spearman's correlations were calculated between hematology data and all whole blood M. tb H37Rv MGIT results (n = 34) and showed a significant negative correlation growth and eosinophil count (B). MGIA was also performed using cryopreserved PBMC with matched pre-and post-treatment PBMC samples from individuals with hookworm infection (n = 12) and controls (n = 9) (C). For MGIT data, points represent the mean of duplicates; bars represent mean values with SD.
The crystallographic data for (o-Me 2 TTF) 2 NO 3 at 20 K were collected with an Oxford Diffraction Xcalibur3 diffractometer fitted with a two-dimensional Sapphire3 CCD detector using sealed monochromatic Mo K radiation source ( = 0. 71073 A ˚). The Xcalibur3 diffractometer was fitted with a helium-flow Helijet Oxford Diffraction cryostat. The crystallographic data for (o-Me 2 TTF) 2 NO 3 at 85 and 250 K were collected with a Rigaku Oxford Diffraction SuperNova diffractometer fitted with an Eos-S2 detector using microfocused monochromatic Cu K radiation ( = 1. 54184 A ˚). The SuperNova diffractometer was fitted with a nitrogen-flow Oxford Cryosystems 800Plus series device. At 20, 85 and 250 K, data collection, cell-constant determination and data reduction were performed using the CrysAlisPro software  (Rigaku Oxford Diffraction, 2015).
Only in the case of the 20 K data was the ISOR restraint applied to the anisotropic displacement parameters for some carbon sites of o-Me 2 TTF molecules. It is of importance that, at 250 K, the NO 3 À ion is disordered on an inversion centre. In the case of the 20 K data, the (o-Me 2 TTF) 2 NO 3 crystal structure contains a twocomponent twin model with a ratio of 0. 66:0. 34; the two components are related by the twin matrix (À1 0 0, 0 0 À1, 0 À1 0). On the other hand, the crystal collected at 85 K was not twinned, despite having undergone a phase transition. Alerts A and B in the CIF arise because of the disorder or possible disorder of the NO 3 À anions. CCDC deposition numbers 1562992-1562994 for the crystals measured at 20 K, 85 K and 250 K, respectively, contain the supplementary crystallographic data for this paper.