dataesr/scientific-paragraphs-categorization huggingface dataset:
Moreover, the improvement in balancing ability correlates with the mitigation of SAS. This finding supports the idea that white noise improves body stability in patients with vestibular problems  (Mangiore, 2012). More importantly there is evidence that supports that white noise functions as a countermeasure to decrease SAS  (G alvez-García, 2015). The aforementioned techniques (GCS, GVS and white noise) have a positive impact on balance ability, decreasing SAS. Interestingly, this constitutes direct evidence in support of the postural instability theory  (Riccio and Stoffregen, 1991) , where it has been postulated that SAS is produced by an inability to learn how to maintain postural stability. Nevertheless, the mitigation of SAS could come from other sources, especially considering that the aetiology of this phenomenon is not entirely clear and could be due to several reasons.
As the main aim of this research, we want to test an additional source of stimulation that does not affect balance ability as a possible countermeasure to decrease SAS: distraction from sickness. Thus, a source of stimulation that does not deteriorate driving performance will reduce participants' awareness of SAS symptoms (i. e. , stomach discomfort, eyestrain, etc. ). This hypothesis is based in previous evidence. For example, Reed-Jones (2011) compares a condition of unilateral and congruent GVS (reflecting what the participants can feel during a curve in naturalistic situations) with the opposite situation (unilateral stimulation that provided the opposite vestibular experience). He shows a similar pattern of results in both conditions, concluding that electrical stimulation can distract from the sickness and cause a decrease in SAS.
In addition, this attentional disengagement hypothesis can explain, for example, why different types of stimulation, like acupuncture, decrease SAS (e. g. ,  Wesley and Tengler, 2005). Nevertheless, it is important to remark that this explanation based on distraction would be additive to the aforementioned literature supporting the idea of motion induced by a different form of stimulation (e. g. , GCS and AS) as the cause of SAS mitigation. Thus, the attentional disengagement hypothesis can coexist with evidence regarding the increase of postural control to mitigate SAS. We want to remark that testing the attentional disengagement hypothesis is crucial in order to provide evidence of SAS as a multifactorial syndrome, which can be dealt with via several different countermeasures. In order to test the attentional disengagement hypothesis, we study how tactile stimulation (TS) influences SAS, as TS is not shown as bothersome in previous studies on tactile  attention (e.
Finally, it should be noted that TS is an inexpensive and simple technique to mitigate SAS (i. e. , the application of TS only requires a tactile device synchronised with the simulator to provide a tactile signal during curves), which is fundamental for the recommendation of this technique for future interventions to reduce SAS. An additional aim of this research is to investigate how TS affects driving performance. Previous research (G alvez  -García, 2015; G alvez-García et al. , 2015; Reed-Jones et al. , 2009)  had failed to find an effect of external techniques that decrease SAS (i. e. , GCS and auditory stimulation) on driving performance. We hypothesise that TS will improve SAS without a positive impact on balancing ability, attending to the attentional distraction from sickness.
After each drive, participants exited the vehicle for a rest period of 5 min and completed the SSQ. We measured SAS using the Simulator Sickness Questionnaire (SSQ;  Kennedy et al. , 1993). The questionnaire was composed of 16 symptoms that the participant had to rate on a scale from none (0) to severe (3). We analysed the SSQ total scores provided by the questionnaire in the two different stimulation conditions.
Design The different conditions for delivering the stimulation were manipulated as the independent variable (no stimulation, TS). SSQ total scores were measured as the dependent variable. The exclusion criterion was an SSQ total score of more than 2. 5 standard deviations (SDs) from the mean. No data were excluded from the analysis. In addition, head sway was measured as a dependent variable. This was defined following previous studies (G alvez-  García, 2015)  as the SD of head movements (measured in pixels) along the X-and Y-axes during the curves in the two experimental conditions. Finally, four driving variables were measured to assess the differences in driving behaviour between the two experimental conditions: average speed (km/h); accelerator percentage (percentage of depression of the accelerator pedal); brake percentage (percentage of depression of brake pedal) and SD of the steering variability angle during the curves.
Discussion This research had two aims. First, we wanted to test whether TS could distract attention from the sense of sickness and cause a decrease in SAS. In addition, we wanted to investigate how TS affected different driving variables. The results confirmed that TS mitigated SAS. When we compare the SSQ total scores in the no stimulation condition (60) vs. the TS condition (35), a significant improvement of 41% was found. It should be noted that SSQ scores above 20 indicated significant discomfort  (Webb et al. , 2009)  and, in our experiment, SSQ total scores for TS was 34, which reflected that, although TS mitigated SAS symptoms, they did not fully disappear. Previous studies showed a larger symptom reduction using techniques that affect balance ability (i. e. , AS for head sway; G alvez-García, 2015) in line with postural instability theory  (Riccio and Stoffregen, 1991).
This reflected that, to reduce SAS, an improvement in balance ability should be at least considered. In the current study, there was no significant improvement in balance ability when TS was applied when compared with the no stimulation condition (12. 52 and 12. 16, respectively). Nevertheless, an important finding arose from the reduction of SAS with TS; it was possible to reduce SAS without the aforementioned improvement in body balance. We strongly believed that this was due to the subjects being distracted from the symptoms; the stimulation could have distracted the participants from being conscious of their sickness. More concretely, given that the perception of discomfort was prominent in the conscious experience, electric stimulation could have simply made participants less aware of their knowledge of SAS symptoms (i.
e. , stomach discomfort, eyestrain, etc. ; Reed-Jones, 2011). As we mentioned in the Introduction, this could have partially explained why the stimulation with acupuncture (here, we do not differentiate between acupressure, acupuncture and electroacupuncture) decreased motion sickness symptoms of nausea and vomiting  (Stern et al. , 2001; Warwick-Evans et al. , 1991)  and, more specifically, SAS  (Cox et al. , 2011; Wesley and Tengler, 2005). In addition to the attentional disengagement hypothesis, other attentional factors could co-exist. For example,  Seno et al. (2009 Seno et al. ( , 2011) )  found that the severity of the induced self-motion sensation produced by visual simulation could be moderated by attention. Therefore, as Reed-Jones (2011) implied, the distraction produced by stimulation could reduce the sensation of motion and limit conflict between visual and the other senses.
Another attentional factor that could influence the mitigation of SAS is the improvement of this cognitive process through stimulation (any type). For example,  Chu et al. (2013)  found that simulator exposure increased SAS and decreased concentration, showing that GCS was a good countermeasure to enhance concentration, as the participants made fewer cognitive test errors. In short, it was shown that the attentional disengagement hypothesis and, more generally, attentional factors could be a plausible explanation for SAS. As we have pointed out before, this explanation could coexist with other possible explanations (i. e. , postural instability theory;  Riccio and Stoffregen, 1991). In any case, our pattern of data showed that SAS was not a simple phenomenon that only affected body balance factors, but also other processes, such as attention.
Future interventions could combine different sources of stimulation that affect SAS improving body balance (e. g. , GCS and AS) and attentional factors, such as TS. It might be possible to combine all those effects to minimise SAS. The driving performance variables showed no difference between the no stimulation and TS conditions. This finding was in line with previous literature that did not show any significant driving performance variable differences when several techniques were applied, like GCS (G alvez  -García, 2015; G alvez-García et al. , 2015; Reed-Jones et al. , 2009)  and white noise  (G alvez-García, 2015). In any case, it is important to note that TS did not adversely affect any driving variable, which is a fundamental point for its recommendation for future interventions reducing SAS.
Finally, we conclude by highlighting the applicability of our research. We have corroborated TS as efficient countermeasures at reducing the effects of SAS in a fixed-base simulator. The beneficial effects of this economical and easily accessible technique should aid researchers in implementing best practises for participants receiving simulator-based training. The identification of attentionrelated factors as a potential explanation of how different sources of stimulation may reduce simulator sickness is fundamental. Here, if one of the keys to mitigating SAS is to make participants less aware of their symptoms, a wide range of stimulating devices could easily be used and integrated into the simulation setup. Nonetheless, it should be highlighted that the intensity of the stimuli signal should lightly distract attention from the symptoms because otherwise, it might deteriorate driving performance.
PIDs were defined according to the European Society for Immunodeficiencies (ESID) criteria. Common variable immunodeficiency (CVID) was diagnosed according to the ESID/Pan-American Group for Immunodeficiency (PAGID) criteria or revised ESID criteria  [15, 16]. For each patient group described above, information was requested on how frequently patients attended the clinic for monitoring and assessment, which screening and monitoring tests were used and how often and which treatments were administered at their centre for patients with PID. Data on how many patients received different therapies (in addition to IgG replacement therapy), including prophylactic antibiotics, steroids and other therapies such as rituximab, were collected. The proportion of patients treated with each therapy was calculated as a percentage.
The genome of human papillomavirus type 23 (HPV-23; family Papillomaviridae, genus Betapapillomavirus, species Betapapillomavirus 2, type 23) was assembled by deep sequencing from nasopharyngeal swabs. The assembled genome is 2. 7% divergent over its full length from the single complete genome of HPV-23 in GenBank (accession no. U31781). We named the strain HPV-23/Lancaster/2015.
T he family Papillomaviridae consists of more than 120 viral types divided into 49 genera  (1). Within the genus Betapapillomavirus, type 23 of species Betapapillomavirus 2 (HPV-23) is represented in GenBank by a single complete genome (2) composed of a circular double-stranded DNA of 7. 3 kb (accession no. U31781), as well as two shorter fragments  (3, 4). HPV-23 is a clinically significant papillomavirus, having been implicated in epidermodysplasia verruciformis (2), skin cancer (5), ocular syringoma (6), nongenital seborrhoeic keratosis  (7) , breast cancer  (8) , and toenail onycholysis  (9). Volunteers were recruited from a general practice surgery and a general hospital in Lancaster, UK (54. 05°N, 2. 80°W). Nasopharyngeal swabs were taken between 16 December 2014 and 25 February 2015.
Ethical approval was granted by the UK National Research Ethics Service, reference 14/LO/1634, NIHR Clinical Research Network (UKCRN) portfolio, ID 17799. All methods were carried out in accordance with the relevant guidelines and regulations. Pooled RNA from 51 swabs was deep sequenced using an Illumina Nextera XT library and HiSeq 2500 system (SRA GenBank accession no. SRP092324). An HPV-23 genome was assembled using Bowtie 1. 1. 1 (10)  and BWA 0. 7. 12-r1039  (11) , with U31781 as the template. The assembled genome is 7,317 bases in length, differing from U31781 by 188 substitutions (2. 7%). A 6-base deletion in the new genome starts at position 5418, within the L2 gene. A further single-base deletion occurs at position 7193, in the 3= direction from the L1 gene. The predicted protein sequences are derived by reference to U31781 and differ at 62 amino acid residues (2.
ACKNOWLEDGMENTS K. V. A. received a  Service Increment from Teaching (SIFT) studentship  from  University Hospitals of Morecambe Bay (UHMB) National Health Service (NHS) Foundation Trust ,  United Kingdom , and performed this work as part of the requirements for the degree of Master of Science (M. Sc. ). Rosetrees Trust ,  United Kingdom , provided additional funding for deep sequencing (grant  M395 ).
Minipreparations of plasmid DNA were done using the NucleoSpin Plasmid kit (Macherey-Nagel, Du ¨ren, Germany). Five positive clones containing inserts of approximately the expected size were arbitrarily selected for each sample and sequenced on both strands. The SSU rDNA gene sequences obtained in this study were deposited in GenBank under accession numbers KR259402 to KR259512 (S1 Table ). The sequences obtained were compared with all Blastocystis sp. homologous sequences available from the National Centre for Biotechnology Information (NCBI) using the nucleotide BLAST program. The STs were identified by determining the exact match or closest similarity against all known mammalian and avian Blastocystis sp. STs according to the last classification by Alfellani et al. [19].
Phylogenetic analysis of Blastocystis spp. isolates Nine of the SSU rDNA gene sequences obtained in the present study for eight Blastocystis sp. isolates exhibited low similarity ( 92%) with homologous sequences available in the databases. To clarify their identification via phylogenetic tools, these sequences were thus added to a large dataset including (i) 33 sequences of Blastocystis sp. isolates representing ST1 to ST10 and ST13 to ST17 (ST11 and ST12 SSU rDNA gene sequences are not yet available for this particular domain)  [25]  and (ii) 22 homologous sequences representing 7 potential NMASTs according to the recent phylogenetic analysis by Yoshikawa et al. [20]. The SSU rDNA genes sequences were aligned using the BioEdit v7. 2. 5 package (www. mbio. ncsu. edu/BioEdit/ bioedit. html).
To a lesser extent, a wide range of mammalian and avian STs was also previously described in several smaller-scale surveys conducted in zoological gardens  [19, 24, 25, 33]. The remaining nine SSU rDNA gene sequences obtained in the present study from eight Blastocystis sp. isolates exhibited 82% to 92% identity with homologous sequences available in databases, thus preventing direct subtyping of the corresponding isolates. Consequently, these sequences were added to an existing database including 55 homologous sequences from representatives of both mammalian/avian STs and so-called NMASTs, then applied to a phylogenetic analysis in order to clarify their relationships (Fig  1 ). With the exception of ST13 and ST17 (only one representative isolate), all mammalian and avian STs were represented by 2 to 4 isolates.
Concerning the 9 sequences obtained in the present study and exhibiting low identity with the homologous sequences available in databases, 2 of them, ZLB27 from aldabra tortoise and ZLC1 clone 2 from spur-thighed tortoise, grouped together (BP and BPP of 99% and 1, respectively) and clustered with two representatives of the NMAST II clade (KINIX2 and GECA2) with BP and BPP of 63% and 0. 99, respectively. This significant support suggested that ZLB27 and ZLC1 clone 2 sequences could be assigned to the reptilian NMAST II clade. Regarding the second sequence obtained from spur-thighed tortoise (ZLC1 clone 1), its clustering with the ZLB30 sequence from green iguana which currently represents the only representative of the reptilian NMAST IV was well supported (BP and BPP of 60% and 0. 94 respectively) and consequently, the ZLC1 clone 1 sequence was assigned to the NMAST IV clade.
Interestingly, the evolutionarily closely related NHP and human groups share a high prevalence of the parasite and the same predominance of ST1 to ST3 among isolates. Moreover, 32 of the 48 (66. 7%) sequences of isolates belonging to ST1 to ST3 identified from NHPs in the present study were shown to be 100% identical to homologous sequences available in databases from humans. Similarly, the sequences of one of the four ST4 isolates and of the two ST8 isolates from NHPs also exhibited 100% identity with those of humans. In contrast, the sequences of NHP isolates belonging to ST7 and ST5 were 98 and 97% similar respectively compared to those from humans. Therefore, the genetic identity of ST1 to ST4 and ST8 isolates from NHPs and humans, together with the high prevalence rate of Blastocystis sp.
Still among artiodactyls, representatives of Suidae could not be sampled in the present study, because they are not housed in the two French zoos. However, this animal group was shown to be frequently infected, primarily by ST1 and ST5, suggesting that pigs are likely to be natural hosts of these Blastocystis sp. STs  [24, 30, 35, 57]  (Table  3 ). The potential of pigs to act as zoonotic reservoirs was recently demonstrated by Wang et al. [30] , who found an unusually high prevalence of ST5 in both pigs and piggery staff in Australia, as well as sequence identity of ST1 and ST5 isolates from pigs and piggery workers. Therefore, close contact between pigs and their handlers may clearly increase the risk of zoonotic transmission of Blastocystis sp. ST1 and ST5 (Fig  2 ). For other mammalian groups, the current data are too limited to draw conclusions about a potential risk of zoonotic transmission, and the present study only reinforces the currently available databases.
Acknowledgments: Proceedings of a European Research Workshop in Digestive Oncology held in Barcelona, Spain, on Wednesday 29th June 2016. This workshop was endorsed by the  European Society of Digestive Oncology. The authors thank  ROCK Unlimited  for assistance with the preparation of this manuscript. Financial support for the European Research Workshop in Digestive Oncology and for this review article was provided by an educational grant from  Bayer Consumer Care AG.
Background Hereditary angioedema (HAE) due to C1-inhibitor deficiency (C1-INH-HAE) is a rare, potentially fatal, bradykinin-mediated disease. Icatibant is a bradykinin B2 receptor antagonist originally approved in 2008 in the European Union and 2011 in the United States as an acute therapy option for HAE attacks in adults. Objective To compare demographics, disease characteristics and treatment outcomes of icatibant-treated HAE attacks in patients with C1-INH-HAE enrolled in the Icatibant Outcome Survey across six European countries: Austria, France, Germany, Italy, Spain and the UK. Methods The Icatibant Outcome Survey [IOS; Shire, Zug, Switzerland (NCT01034969)] is an international observational study monitoring the safety and effectiveness of icatibant. Descriptive, retrospective analyses compared IOS country data derived during July 2009-April 2015.
The EU indication was updated in 2011 to allow patient self-administration following appropriate training from HCPs. The safety and efficacy of icatibant in adults with C1-INH-HAE have been demonstrated in three phase 3 clinical trials  3, 4  and two openlabel extension studies. 5, 6 he Icatibant Outcome Survey (IOS) is an international, prospective, observational study (NCT01034969) established in 2009 to monitor the safety and effectiveness of icatibant in a real-world setting. Recent analyses of IOS data support the clinical trial findings  7, 8  and helped delineate real-world treatment with icatibant across registry countries, particularly with respect to the increasing adoption of patient self-administration. 9  However, the rarity of C1-INH-HAE has thus far limited IOS analyses of aggregated total patient data and precluded regional analyses and comparisons of both C1-INH-HAE characteristics and icatibant treatment patterns.
A steadily increasing enrolment in IOS of patients with C1-INH-HAE across IOS European countries presents an ideal opportunity to assess regional demographic data to better characterize the clinical picture of C1-INH-HAE. Moreover, a regional evaluation of icatibant treatment outcomes and physician practice patterns across EU member nations may help guide clinical decision-making by providing real-world evidence of the ways in which icatibant is utilized for the treatment of acute C1-INH-HAE attacks. The purpose of this analysis was to compare demographics, disease characteristics and treatment outcomes of icatibant-treated attacks in patients with C1-INH-HAE enrolled in IOS across six European countries: Austria, France, Germany, Italy, Spain and the UK.
Methods Patients with a diagnosis of C1-INH-HAE clinically confirmed by laboratory tests (C1-INH concentration and function), who were receiving or were a candidate for icatibant treatment, were included in this analysis. Data for this analysis were collected via physician-completed electronic forms at routine patient visits between July 2009 and April 2015. IOS is conducted in accordance with the Declaration of Helsinki and the International Conference on Harmonization Good Clinical Practice guidelines. Informed consent was obtained from all participants. The design of IOS has been previously described. 8 alyses Data were derived from an initial visit at IOS inclusion (baseline) and follow-up assessments. HAE attack characteristics included the baseline annual frequency and severity of icatibanttreated attacks.
The frequency of attacks was based on patient recall, and attack severity was evaluated according to symptom score attributed to attack interference with daily activities as follows: 0 = very mild interference with daily activities; 1 = mild interference with daily activities; 2 = moderate interference with daily activities and no other countermeasures required; 3 = severe interference with daily activities and with or without other countermeasures; and 4 = very severe interference with daily activities and with other countermeasures required. The method of icatibant administration (either self-administered or by HCP) was recorded. Icatibant treatment outcomes included time to administration, time to resolution and duration of attack. Treatment outcome data were only derived from attacks with complete data for all three outcomes.
Retrospective descriptive analyses were performed with patients grouped according to IOS country. Gender comparison used the Chi-square test while comparisons of age at IOS enrolment, age at diagnosis, age at first symptoms and delay in diagnosis used the Kruskal-Wallis test. Treatment outcome data (time to resolution, duration of attack) were analysed using a mixed model analysis of repeated measures, including time to treatment and country as covariates. Analysis of icatibant-treated attack severity was performed on attack severity data that were grouped into severe/very severe vs. very mild/mild/moderate using a generalized linear mixed analysis for repeated measures. Statistical testing was considered exploratory in this observational study, and no adjustment for multiplicity was performed.