dataesr/scientific-paragraphs-categorization huggingface dataset:
Background: Using case-vignettes, we assessed the perception of European infection control (IC) specialists regarding the individual and collective risk associated with antimicrobial resistance (AMR) among inpatients. Methods: In this study, sixteen case-vignettes were developed to simulate hospitalised patient scenarios in the field of AMR and IC. A total of 245 IC specialists working in different hospitals from 15 European countries were contacted, among which 149 agreed to participate in the study. Using an online database, each participant scored five randomlyassigned case-vignettes, regarding the perceived risk associated with six different multidrug resistant organisms (MDRO). The intra-class correlation coefficient (ICC), varying from 0 (poor) to 1 (perfect), was used to assess the agreement for the risk on a 7-point Likert scale.
Study design and data We developed 16 case-vignettes based on real MDRO cases in hospitals, using a standard list of items. The case-vignettes were previously piloted and tested within the team of main investigators (GB, NTM, RA, ET, J-CL, AH). Each participant scored five randomly-assigned case-vignettes to allow assessments of the agreement across participants. For each vignette, the participants were questioned on their perception of the individual and collective risk associated with MDRO clinical cases according to a numerical 7-class Likert-type scale, ranging from "No risk" (score 1) to "High risk" (score 7)  [10]. The individual risk was defined as the occurrence of a negative outcome for the colonised or infected patient. The collective risk was defined as the probability of MDRO acquisition for contact patients (i.
Individual, organisational and national factors Participants completed a questionnaire developed to evaluate the AMR control strategy in their hospital. The 11 criteria selected for this form were informed by the IPC core components  [11] , including questions on the management (i. e. presence of IPC committee), resources, training programmes and AMR surveillance (Supplementary Table  S2 ). The local hospital epidemiology was assessed by the number of bacteraemia with the six selected MDROs observed in 2015 categorised in 0, 1-10 and > 10 episodes. Data on national epidemiology were extracted from the European Centre for Diseases prevention and Control (ECDC) surveillance atlas of Infectious diseases, providing the percentage of resistant isolates per species (resistant strains out of all strains) among invasive infections in 2015, and the Center for Disease Dynamics, Economics & Policy (CDDEP) resistance map 2016 for Turkey, and Serbia (Supplementary Table  S3 ).
Data management and statistical analysis The perceptions assessed through the seven-point Likert scale were dichotomised on one to five versus six and seven. A high-risk perception was attributed for six and seven versus low/neutral risk for the remaining five quotations. In the same way, items of the individual cognitive factors for compliance with AMR control measures, and the perception of the organisation and work conditions in hospitals were considered positive for six and seven ("agree and strongly agree") versus negative for the remaining five quotations. The analysis of factors associated with the risk perception was performed at the individual level. An aggregated score was calculated for each individual, organisational or national factor corresponding to the mean of quotations for each domain (aggregation of 11 criteria for the local IPC organisation, six criteria for the perception of individual IC compliance, seven criteria for teamwork, nine criteria for perception of management, seven criteria for stress and chaos, and two criteria for well-being and work conditions).
MDRO situations are often complex, typically requiring discussion and collegial decision making to adapt the strategy to the current context (clinical, setting, and resources). Second, the vignettes were scored via an online database. The vignettes were built from real cases, but the perception and decision making may be different than in the reality. Moreover, despite definitions provided for each criteria, the variability of answers may be explained by the variability of reading and understanding of case-vignettes presented in English language. Third, in some countries we did not reach the 16 expected IC specialists for participation. Finally, participants in each country were solicited by national leaders in the field of AMR surveillance and prevention. This recruitment method potentially induced selection bias with a majority of participants working in universities or large hospitals.
Acknowledgements We thank  Enrique Castro-Sanchez , and  Tim Rawson  for their contribution to the review of case-vignettes. Austria:  Brigitte Stoiser ,  Susanne Equiluz-Bruck ,  Rainer Gattringer ,  Markus Winkler ,  Viktor Lenhart ,  Magda Diab-Elschahaw ,  Andrea Grisold. Finland:  Risto Pietikäinen ,  Ville Lehtinen ,  Esa Rintala ,  Harri Marttila ;  Janne Mikkola.
Funding The research was funded by the  National Institute for Health Research Health Protection Research Unit (NIHR HPRU ) in Healthcare Associated Infection and Antimicrobial Resistance at  Imperial College London  in partnership with Public Health England (PHE). The views expressed are those of the author(s) and not necessarily those of the  NHS , the  NIHR , the  Department of Health or Public Health England. GB has received an  Early Career Research Fellowship  from the  Antimicrobial Research Collaborative at Imperial College London , and acknowledges the support of the Welcome trust. RA is supported by a  NIHR  Fellowship in knowledge mobilisation. The support of  ESRC  as part of the  Antimicrobial Cross Council initiative  supported by the seven UK research councils, and also the support of the  Global Challenges Research Fund , is gratefully acknowledged.
Magnetometry Magnetometry was employed on 4 to 7 August 2011 across three grids to assist in selecting the locations for test pit excavations. It was performed using a Geometrics G-856AX proton precession magnetometer. The magnetometry grids were laid out using tape measures, with the corners subsequently mapped using a total station. Magnetic field intensity samples were taken at 1 m intervals. Transects were performed in a single direction and a single corner of the grid was sampled at the end of each transect to record fluctuations in background magnetism. Data were downloaded from the instrument and corrected for diurnal variation and other background magnetism fluctuations. While in the field, a basic magnetic field map was prepared using MagMap2000 software. Subsequent to fieldwork, the data were georeferenced using total station data and the maps shown in this report were created using ArcGIS 10.
Tradeware ceramics High-fired glazed ceramics at Leki Wakik are classified as tradeware ceramics and were analysed using a macroscopic (visual) comparative analysis. A Canon EF 100mm f/2. 8 Macro USM lens was used to take photo-macrographs (up to 1:1 magnification) of both exterior and interior surfaces as well as fabric cross-sections of the sherds. These photo-macrographs allowed for a finer resolution of diagnostic details that are otherwise difficult to observe and record with the naked eye. Forty-seven metric and non-metric variables were recorded. Non-metric data (i. e. provenance, vitrification level, fabric texture, fabric, glaze colours and others) were assessed based on the analyst's (Tse Siang Lim) knowledge and familiarity with high-fired glazed ceramics produced in China and Mainland Southeast Asia.
This data should be treated as preliminary and, hence, should not be used in comparisons with other high-fired glazed ceramics outside of the Leki Wakik assemblage without caution. As per standard taxonomical practice in the analysis of high-fired glazed ceramics, the Leki Wakik sherds have been preliminarily classified according to typologies based on their respective glaze and body colours and, in the case of Polychrome and Blue and White sherds, glaze colourdecoration combination. Additional information on tradeware ceramic analysis methods is provided in Supplement 1.
Invertebrate faunal remains Marine and freshwater shells and shell fragments were identified to the lowest taxonomic level possible using the ANU Archaeology and Natural History (ANH) and the Museum and Art Gallery of the Northern Territory malacology collections. The names were standardised to conform with the current listing on the online database, the World Register for Marine Species. The shell assemblages were quantified by weight (g), minimum number of individuals (MNI) and number of identified specimens (NISP). The MNI method quantifies one repetitive feature per taxon throughout the assemblage, thereby avoiding the inflation associated with fragmentation commonly seen when using NISP counts  (Classen 1998) ; for this reason, it is the primary mode of quantification used in the analysis.
Acknowledgements This research work was supported by  JSPS   JP19H00833 ,  JP19F19720 ,  JP16H06441 ,  JP17H02749 , and  JST Mirai   JPMJMI19A1 ,  CREST JPMJCR19Q4. B. S. thanks  JSPS  for the postdoctoral fellowship ( P19720 ) and  Dr David Berthebaud  ( CNRS ) for the constant support. R. V. R. V. thanks  Dr Leila Rubia  ( De Montfort University, UK ) and  Ms Christine Celeste Chua-Nakar  for their help and  Mr Makito Nakatsu  and  Dr Hidehiko Tanaka  from  NIMS  for the technical support.
Introduction Oral squamous cell carcinoma (OSCC) is the most common malignancy of the head and neck  [1]  with estimated global deaths from oral cancer of 177,000 in 2018  [2]. Despite advances in diagnostic techniques and treatment modalities, the overall survival of patients with head and neck cancer has not improved significantly over the past 20 years  [3]. The evaluation of the clinical characteristics and anatomical extent of the tumour as well as its relationship to host tissues plays an important role in the prognosis of oral squamous cell carcinoma. Many studies stress importance of documenting the histological features in the pathology reports of resected oral cancer specimens  [4]. In the UK, it is recommended that the information is gathered synoptically in the format of the RCPath dataset for histopathological reporting of mucosal malignancies of the oral cavity although the prognostic influence of each core data item, despite being supported by best available evidence, is unclear on a quantitative basis and difficult to apply with absolute confidence when deciding on treatment modalities in multidisciplinary meetings.
Bryne et al. later developed a system of invasive front grading (IFG) with 5 histological features including host response  [8]. These models have not been successfully due to small sample sizes, heterogeneous tumour sites and evaluation of different specimen types (biopsies only and resection specimens only)  [9]. More recently, studies by Woolgar et al. have further explored prognosticators for local regional recurrence, lymph node metastasis and distant metastasis  [6] [7] [8]. In 1998, the UK RCPath developed detailed guidelines together with the standard minimal dataset proforma  [10] ,  [11]  many of the core data parameters are supported by the evidence from studies conducted by  Woolgar. In 2005, Brandwein-Gensler and co-workers introduced a histological risk assessment model purported to having superior prognostic value in comparison to previously described systems  [9].
Materials and Methods The institutional review for human subject research reviewed and approved this study. One hundred and thirty-four patients with oral squamous cell carcinoma treated with primary resection between 2009 and 2014 were included in the study to allow a minimum follow-up time of 5 years. The pathology reports were reviewed retrospectively and target cases were identified by applying the inclusion and exclusion criteria. The inclusion criteria were: complete demographic and clinical data, T1 T2 (7th edition) OSCC treated with surgery with or without post-operative oncology therapy, availability of slides, paraffin embedded blocks and followup data of at least 5 years for survival. The exclusion criteria were as follows: T3 & T4 primary tumours, recurrences, secondary tumours, oropharyngeal tumours including tongue base and tonsil, depth of invasion of less than 1 mm, nonconventional squamous cell carcinoma, squamous carcinoma with prominent intraductal component and patients seropositive for HIV.
Cases with positive lymph node metastasis in accompanying neck dissections were included. All pathology slides from the resection specimens were retrieved and reviewed. All H&E stained slides from tumour resections were independently reviewed by 3 pathologists blinded to the demographic data and outcomes. The slides were scored according to the 3 components of the risk model: Worst pattern of invasion (WPOI), lymphocytic host response (LHR) and perineural invasion (PNI) and then categorised according to the total combined score. Individual analyses by consultant pathologists were verified by a consensus meeting at multi-headed microscope. RC Path minimum dataset items were transcribed from the original pathology report. Age, gender, date of surgery, TNM stage was collected on Microsoft access databases.
For patients treated with accompanying neck dissection (n = 85) the presence or absence of lymph node metastasis was recorded along with the presence and absence of extracapsular spread. Ethics approval and access to histology slides and clinical data was approved from the local tissue governance team (SR679). The cases were selected consecutively with unknown outcomes. The endpoints assessed were local recurrence (LR), regional recurrence (RR), distant recurrence (DR) and recurrence free survival (RFS). Cross tabulations, Mann Whitney tests and Chi squared tests were used to assess correlations between 1 3 histopathological risk model, prognosticators in the RCpath dataset and outcomes. Continuous data was summarised using means and ranges (minimum and maximum). Categorical data by using frequency counts and percentages.
Inter observer variability was assessed using kappa statistics. Oncological outcomes were expressed using the Kaplan-Meier method. Univariate analysis of outcome was performed using the Log-Rank test and multivariate analysis using the Cox regression model. Hazard ratios were calculated using a univariate Cox regression model, with 95% confidence intervals. Results were considered significant at the p < 0. 05 level. All calculations were done using SPSS.
Results The study group comprised 134 patients with primary T1 (n = 82, 61%) and T2 (n = 52, 39%) oral squamous cell carcinoma (TNM7). This consisted of 83 male and 51 female patients, aged between 22 and 88 years (mean age 63. 4 SD 13. 2). The clinical and demographic data are shown in Table  2. The follow-up ranged from 1 to 96 months with a mean of 53. 5 months (SD 39. 6). Eighty-three patients were recorded as still being alive while 51 patients had died giving an overall survival of 62%. Forty-three patients were reported to have disease progression and 91 were free of disease at last follow-up fragment. Eight patients had died of disease within 50 months. Twelve patients had local recurrence, 42 (31%) had locoregional recurrence of which 20 were classified as high risk according to the risk model but due to the small numbers there was no statistical significance found.
004). The overall size and depth of invasion were recalibrated to satisfy the criteria for TNM 8 staging. Thirty-four tumours previously designated as T1 would now be classified as T2 and 30 T2 tumours would now be classified as T3 according to TNM 8th edition. A Mann Whitney test showed that the worst pattern of invasion (p = 0. 01), perineural invasion (p = 0. 0001) and the overall risk score (p = 0. 0001) were significantly greater in the tumours reclassified as T3 by depth of invasion. Risk scoring did not demonstrate an association between disease progression and the overall score or any of the 3 individual parameters as shown in Table  4. The Chi squared tests did not show a significant association between disease progression and the prognostic features recorded in the dataset (Table  5 ).
The inter-observer agreement among the 3 pathologists was moderate to strong when measured against the consensus score (k range = 0. 45-0. 82). However, the scores showed weak to moderate agreement in WPOI, LHR, PNI and overall scores when comparing the pathologist score against each other as appears. A spearman's rank-order correlation (Table  6 ) was carried out to determine the relationship between the WPOI scores and the RCPath dataset classification of pattern of invasion. There was a strong positive correlation between noncohesive pattern and the more aggressive WPOI scores which was statistically significant (rs = 0. 325, p = 0. 0001).
All together, these results demonstrated that diet change drives the development of microbial consortium in a unique manner, yet food-associated microbes cannot compete with highly specialised termite gut microbiota for a niche. Comparison of de novo metatranscriptomic and metagenomic reconstructions. The de novo MT was applied to nest LM1 and co-assembling reads from three samples (LM1_1, LM1_2 and LM1_8) yielded 603,579 open reading frames (ORFs), mainly representing partially reconstructed gene transcripts. The de novo MG reconstruction was also applied to colony LM1 at sampling point LM1_8 and it yielded 211,724 ORFs annotated on 64,347 contigs for the total assembly size of 177,5 million base pairs (Mbp). For both datasets, initial public database-dependent taxonomic classification of genes and gene transcripts pointed to the abundance of Firmicutes (Supplementary Fig.
4 ), what contrasted the results of community structure analysis. Subsequent binning of MG contigs and phylum-level annotation of the resulting bacterial bins allowed assigning correct taxonomic origin, confirming the metagenomic abundance of Spirochaetae and Fibrobacteres (Fig. 1c ; Supplementary Fig. 5 ). Following mapping of RNA reads to the MG assembly (referred to as "RNA-seq" analysis), we could confirm transcriptional dominance of these two bacterial phyla as well. Incomplete public databases and extensive horizontal gene transfer were previously proposed as the origin of this misclassification  9. Based on the classification of genes and transcripts to broad functional categories such as KEGG ontology profiles (KOs), congruency between the de novo MG and MT reconstructions was high (Supplementary Fig.
The de novo MG reconstruction resulted in close to 7000 different cazymes, 43. 6 % of which were assigned to 86 GH families (Supplementary Fig. 6  and 7 ). Although there was a good correlation between the distributions of identified glycoside hydrolases to different GH families (Pearson R 2 0. 83), roughly 150 cazymes identified in the de novo MT were also reconstructed from the assembled metagenome. Novelty of reconstructed cazymes was evidenced through sequence comparison to NCBI refseq database, and a metagenomic dataset previously generated for Nasutitermes sp. 15  (Supplementary Fig. 4 ). In the latter case, average amino acids identity for the 943 query hits equalled 65. 4 ± 19. 9 %, pointing to the diversity of microbial cazymes in guts of different termite species, even those phylogenetically closely related.
GH45 was only present in Fibrobacteres and it was the second most expressed GH family under Miscanthus diet. According to the CAZY database, nearly 95 % of proteins assigned to this family are of eukaryotic origin (Supplementary Fig. 10 ), and show endocellulase activity. Previously, GH45 CAZymes were characterised from lower termite symbiotic protists  19. Lytic polysaccharide monooxygenases (LPMOs) typically assigned to AA9 (fungal) and AA10 (predominantly bacterial enzymes) families  20  were neither present in the reconstructed metagenome nor metatranscriptome.
Bacterial 16S rRNA gene amplicon high-throughput sequencing and data analysis The bacterial 16S rRNA gene amplicon libraries were prepared using Illumina compatible approach as previously described  45. Briefly, modified universal primers S-D-Bact-0909-a-S-18 and S-*-Univ-*-1392-a-A-15 (ref. 46 ) and Nextera XT Index Kit V2 (Illumina) were used along with Q5 Hot Start High-Fidelity 2x Master Mix (New England Biolabs) to perform two-step polymerase-chain reaction (PCR). It allowed for selective amplification of the 484 bp long fragment of bacterial 16S rRNA gene V6-V8 region and simultaneous attachment of Illumina adapters and barcodes in the second step. Purified and equimolarly pooled libraries were sequenced along with PhiX control (Illumina) using MiSeq Reagent Kit V3-600 on in-house Illumina MiSeq Platform.
Usearch v. 7. 0. 1090_win64 software  47  was used for quality trimming, chimera check, singletons removal and assignment of the obtained preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. sequences to OTUs at 97 % similarity level. Taxonomic affiliation of the resulting OTUs was performed with SILVA database v. 128 (ref. 48 ). Raw sequences are available in the Sequence Read Archive (SRA) database under project number PRJNA587606. Resulting OTUs were deposited in GenBank under project numbers PRJNA586754 and PRJNA434195. Downstream analyses were performed with mothur  49  and R environment  50. Bacterial richness and diversity were calculated using respectively sobs and invsimpson indices. The dissimilarity of bacterial community structures was calculated using Bray-Curtis index.
De novo metagenomics and data analysis Sample LM1_8 was selected for metagenomic sequencing in order to reconstruct genomes/ larger genomic fragments of the dominant microbes in the Miscanthus-adapted microbiome. Prokaryotic DNA was enriched from the total hindgut DNA extract using NEBNext Microbiome DNA Enrichment Kit (NewEngland BioLabs). Following sequencing, over 170 Mbp raw reads were quality trimmed in CLC Genomics Workbench v. 9. 5. 2 (Qiagen), using a phred quality score of 20, minimum length of 50 and allowing no ambiguous nucleotides, resulting in close to 154 M quality-trimmed paired reads. Raw sequencing reads are available in the SRA database under project number PRJNA587423. Quality-trimmed reads were assembled using the CLC's de novo assembly algorithm in a mapping mode, using automatic bubble size and word size, minimum contig length of 1000, mismatch cost of 2, insertion cost of 3, deletion cost of 3, length fraction of 0.
9, and similarity fraction of 0. 95. The average contig abundance was calculated as DNA-RPKMs (reads per kilo base per million mapped reads). This type of normalization allows for comparing contigs (genomic fragments) coverage (abundance) values, as it corrects differences in both sample sequencing depth and contig length. ORFs were searched and annotated using the default pipeline integrated in the IMG/MER  51. Information about KEGGs and COGs assignment was retrieved based on the IMG/MER annotations. Metabolic pathways/modules were reconstructed using the tool integrated in the online version of the KEGG database  52. Initially, contigs were binned using myCC  53  what resulted in their separation preprint (which was not certified by peer review) is the author/funder. All rights reserved.