dataesr/scientific-paragraphs-categorization huggingface dataset:
Background. Recently, molecular assays have been demonstrated to be reliable for rapid detection of CPE directly from positive blood cultures, reducing significantly the time for identification. Few studies have tested their performance on rectal swabs and no comprehensive conclusion have been reached regarding their utility for infection control management. Aim. Tto review and assess the overall diagnostic test accuracy of PCR for the detection of CPE in rectal swabs. Methods. We searched the electronic database PubMed, up to October 1, 2019, without language restriction or publication date restrictions. We began by defining the concepts of the research questions: "Carbapenemase-producing Enterobacteriaceae", "molecular testing", "test detection" and "rectal screening". Two reviewers independently screened studies, extracted data, and assessed quality using the QUADAS-2 instrument.
Statistical analysis All the analyses of diagnostic accuracy were performed using STATA 15. 0 software  28  with function metandi 29 or R 3. 5  30  with package meta4diag. 31 The bivariate meta-analysis model  32  was used to estimate the pooled results of sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR) with their corresponding 95% confidence intervals (CIs). Bivariate random-effects regression model assumes that the logit transformed sensitivities and specificities of the included studies follow a bivariate normal distribution around a common mean of logit-transformed sensitivity and specificity, incorporating any correlation that might exist between logit sensitivity and logit specificity. 32 The number of patients testing positive among the diseased patients in a particular study is assumed to follow a binomial distribution, as is the number of patients testing negative among the non-diseased patients.
The structure of the ZIKV NS5 MTase was built by homology modelling using SWISS-MODEL  [28] [29]  and the compounds in the NCI Diversity Set V database docked in the S-adenosyl methionine (SAM) binding site in order to identify molecules that might disrupt the activity of the enzyme. A set of 40 best ranking molecules were initially identified, among which the urea 6 emerged as the best candidate due to its favorable interactions with the SAM binding site. The urea 6 was thus evaluated in enzymatic inhibition assays against ZIKV NS5-MTase, showing an IC 50 of 35 μM (Table  1 ). A similar IC 50 of 38 μM was observed when 6 was assayed against DENV NS5-MTase. Due to the novelty of the structure when compared to known flavivirus inhibitors, the urea 6 was thus selected as a hit compound for further studies.
Acknowledgements This work was supported by the  European program H2020  under the  ZIKAlliance  project (grant agreement  734548 ), the  EVAg Research Infrastructure  (grant agreement  653316 ) and by the  French research agency ANR  ( VMTaseIn , grant  ANR-ST14-ASTR-0026 ). DC gratefully acknowledges  EPSRC  ( Global Challenges Competition King's College London ) and  Royal Society  ( RG160870 ) for research funding and financial support. We thank  Caroline Collard ,  Charlotte Vanderheydt  and  Elke Maas  for their assistance in the acquisition of the antiviral data. C. V. get a fellowship from the  National Research Agency ANR  under the program RAB-Cap and W. A. from the infectiopole Sud.
Whole Exome Sequencing Approximately 37 Mb (214,405 exons) of the Consensus Coding Sequences (CCS) were enriched from fragmented genomic DNA by >340,000 probes designed against the human genome (Nextera Rapid Capture Exome, Illumina) and the generated library sequenced on an Illumina NextSeq or HiSeq 4000 platform (Illumina) to an average coverage depth 70-100X. An end to end inhouse bioinformatics pipelines including base calling, primary filtering of low quality reads and probable artefacts, and annotation of variants was applied. All disease causing variants reported in HGMD®, in ClinVar or in CentoMD® (class 1) as well as all variants with minor allele frequency (MAF) of less than 1% in ExAc database were considered. Evaluation was focused on exons and intron boundaries +/-20. All relevant inheritance patterns were considered, provided family history and clinical information were used to evaluate eventually identified variants.
Quantitative RT-PCR Validation of the Results To validate the RNA-seq data, the expression level of nine genes was determined using quantitative RT-PCR (Figure  4 ). Even though the Log2 fold change varied to some extent between the RNA-seq data and the quantitative RT-PCR data due to technical differences and limitations, the expression trend of the tested genes was consistent between the two data sets. This indicates that the RNA-seq results are a reliable resource for further analysis. S2  for comparison; n. d. means that this gene was not differentially expressed in the RNA-seq dataset at the 12 h timepoint. Data are the mean +/-S. D. of three independent experiments; * means a significant difference with a corresponding control with p < 0. 001 and # means significative difference between 24 h and 12 h treated timepoints with p < 0.
Acknowledgments The authors thank  Antonin Moreau  and  Julien Lumeau  for help with the aluminum deposition. This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement  723241 ) and from the  Agence Nationale de la Recherche (ANR)  under grant agreement  ANR-17-CE09-0026-01.
HPLC Analysis of AEVM HPLC analysis of the studied extract was performed using a LaChrom Elite system (VWR-Hitachi, Radnor, PA, USA) equipped with two L7100 pumps, a L7200 autosampler, a L2450 diode array detector (DAD) performing the wavelength scanning from 200 nm to 600 nm, and EZ Chrom Elite software (Agilent Technologies, Massy, France). AEVM (1 mg/mL) was chromatographed with a reversed phase Interchim ® UP3ODB C 18 column (150 × 4. 6 mm, 5 µm particle size). Gradient elution was developed with a mobile phase composed of water containing 1% phosphoric acid (A) and MeCN (B). The gradient was set as follows: 0-10 min, 9% B; 10-25 min, 9-12% B; 25-40 min, 12-16% B; 40-45 min, 16% B; 45-50 min, 16-40% B; 50-55 min, 9% B. A flow rate of 1 mL/min and an injection volume of 20 µL were selected.
Statistical Analyses The statistical significance of difference was analyzed by one-way ANOVA followed by Fisher's Least Significant Difference (LSD) test and p values of 0. 05 or less (p ≤ 0. 05) were considered statistically significant. All data are indicated as the mean ± standard error of the mean (SEM). The AGEs assays were performed in quadruplicate, and all other spectroscopic and chromatographic analyses were done in triplicate.
Among the low hanging fruits identified for AMS actions within LMIC, dissemination of educational material through internet may be one of the most efficient and cost-effective. This, of course, requires careful consideration of the objectives, and the targets, as the messages must be adapted to the context. Several initiatives have shown that clever use of modern communication tools may indeed disseminate educational material, about the importance of careful use of antimicrobial agents: - an innovative education and research platform that, for the first time, offers academia and industry the opportunity to submit their educational resources for peer review and publication, allowing healthcare workers a global access to peer-reviewed quality assured educational resource through this and an associated database of WHO indexed non-peer review free resources from across the globe (http://bsacjac-amr.
Results Increased hypoxia gene signature in chronic hepatitis B. To determine whether there is any association between hypoxic responsive transcription and CHB, we performed Gene Set Enrichment Analysis (GSEA) on microarray data from a cohort of chronic HBV infected patients (n = 90) that were free of cirrhosis or HCC and uninfected control subjects (healthy, n = 6)  41. We used a panel of 43 hypoxia gene signatures obtained from the Molecular Signatures Database (MSigDB v 7. 0)  42  , that included hypoxia upregulated genes from diverse tissues and cancer types. We observed a significant enrichment (FDR < 0. 05) of 19 gene sets in the CHB cohort (Fig. 1a ). Since hypoxic-transcriptional responses can vary between cell and tissue types  43  and none of the MSigDB signatures were liver-derived (Supplementary Table  1 ), we analysed an RNA-sequencing (RNA-seq) transcriptome of human hepatoma derived HepG2 cells  44  (0.
The hypoxic cultures were returned to 20% oxygen. After 10 or 20 min, cells were lysed and screened for HIF-1α or HIF-2α and housekeeping gene β-actin expression by western blot, uncropped blots are available in Supplementary Fig. 5 (e ). The data is shown from a single experiment and is representative of three independent experiments and represents mean ± standard deviation. Normality distribution was assessed by D' Agostino-Pearson test; 2-way-ANOVA with Bonferroni correction was applied with p < 0. 05 deemed as significant. in differentiated HepaRG-HBx WT cells (Fig. 2b ). Thus we confirm that HBx in this model system is functionally active. As a control for these experiments we generated HepaRG cells encoding HBx with three nonsense mutations (HepaRG-HBx STOP ). To assess whether HBx can promote or stabilize HIF expression we treated HepaRG-HBx WT or HepaRG-HBx STOP cells with Tet and cultured at 1% oxygen, a typical oxygen concentration used to model hypoxia ex vivo, or standard 'normoxic' laboratory conditions of 20% oxygen for 24 h.
5b ). To further validate our conclusions we used the chimeric human liver FNRG mouse model  56  to assess whether HBV infection would induce HIF signaling in this model. Female FNRG mice 56 between 8-12 weeks of age were transplanted with 0. 5 × 10 6 cryopreserved adult human hepatocytes by intrasplenic injection and monitored for engraftment by measuring human albumin levels in the serum (at least 0. 1 mg human albumin per mL in peripheral blood). Engrafted animals were infected with 0. 5 million genome equivalent (GE) copies of HBV per mouse and were monitored for HBV replication. Once stable viremia was established (minimum 5 × 10 7 GE mL -1 of serum) the mice were sacrificed and livers harvested from HBV infected (n = 4) and uninfected (n = 3) animals for RNA isolation and RNA-seq. Analyzing these RNA-seq data sets showed minimal evidence for an increase in hypoxic transcriptional activity in the HBV infected livers (Fig.
Discussion In this study we identified increased hypoxia gene signatures in a CHB cohort in the absence of cirrhosis or HCC. We confirmed hypoxic gene expression using MSigDB derived gene sets and recently reported signatures from HepG2  44  and PHH data sets  45. We noted an increase in HIF-1α mRNA levels, consistent with their transcriptional regulation by inflammatory mediators such as TNFα. Given previous reports that HBx can stabilize HIFs  [32] [33] [34] [35] [36] [37] [38] [39] [40] 57  , we investigated whether functionally active HBx could regulate endogenous HIF-1α and HIF-2α mRNA, protein and transcriptional activity in vitro. We found minimal evidence for HBx regulation of HIFs in three independent model systems: an inducible HepaRG-HBx cell line; an Ad-HBx transduced cell, and in de novo infection of HepG2-NTCP or PHHs.
Guerrieri et al. identified and validated a role for HBx in regulating genes involved in endocytosis, predominantly members of the Ras-related in brain (Rab) family  9. Anti-HBx chromatin immunoprecipitation studies   2 ) in transcriptomic data of HBV infected primary human hepatocytes  55  , HBV infected human liver chimeric mice and a CHB cohort (b). Fold change was calculated for each of the 80 genes in HBV infection against the healthy controls, where the dotted line represents a twofold change. For the CHB cohort, fold change was calculated from the raw Affymetrix, differential expression was tested using multiple t-tests and significance determined by (adjusted p value < 0. 05). identified HBx binding sites that included RAB1A, RAB2B and RAB5B promoters and none of the validated Rab genes were listed in our hypoxic gene set (Supplementary Table  2 ).
After adding 600µL of Buffer RLT, tissue was homogenized using the TissueLyser LT (Qiagen) for 5 min at 50 Hz. Total RNA was extracted following the protocol of the RNeasy mini kit. HBV infected human chimeric mice and RNA-sequencing. Mock and HBV infected mice were sacrificed and livers harvested for RNA isolation and RNA-sequencing at the Beijing Genomics Institute (BGI, Hong Kong). RNA purity was assessed with a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific) and integrity determined using a 2100 Bioanalyzer Instrument (Agilent Technologies). Sequencing was performed on a BGISEQ-500 (Beijing Genomics Institute, Hong Kong) employing the PE100 mode to produce raw paired-end reads of 100 bp and SOAPnuke (v1. 5. 2) software to filter out non-human sequencing reads, as previously reported  57, 68, 69.
Clean reads (FASTQ files) were uploaded to Partek Flow (version 8. 0, build 8. 0. 19. 1125; Partek Inc. , St. Louis, MO, USA), quality-controlled, and aligned to the human genome (hg38) with STAR-2. 6. 1d aligner software. Genes were quantified using the transcript model Ensembl Transcripts release 91 and differential expression determined with DESeq2 (3. 5). Microarray analysis was performed with Partek Genomics Suite (v6. 6) as previously described  70. Scatter dot plots of fold change values were plotted with Graphpad Prism version 8. RNA-seq data are deposited in the GEO archive at NCBI, with the accession number GSE145835 and entitled: Transcriptional profiling of hepatocytes isolated from chronically HBV-infected human liver chimeric mice. Gene set enrichment analysis. GSEA was performed with GSEA_4.
0. 3 71 using publicly available Affymetrix microarray datasets  41, 49  from Gene Expression Omnibus (GEO) (accessions: GSE83148, GSE14323). Gene sets were derived from HepG2 RNA-seq data  44  downloaded from GEO (GSE120886) or PHH RNA-Seq accessed from the published Supplementary Material 45. To determine whether HBV infection induces hypoxia-responsive genes, we interrogated the mRNA expression patterns of the liver chimeric mice RNA-Seq dataset for the top 80 hypoxia-induced genes as identified in HepG2 hepatic cells  44. In-house datasets were compared with RNAseq  55  from HBV-infected primary human hepatocytes. Data were retrieved from GEO (accessions: GSE120886, GSE93153, GSE118295). For consistency, all datasets were re-analysed with the same Partek Flow bioinformatic pipeline. Microarray analysis was performed with Partek Genomics Suite (v6.
Acknowledgements We thank  Peter Ratcliffe  for his support and advice throughout this project and  Massimo Levrero  for helpful discussions and invaluable insights on HBx. We thank  Peter Balfe  for critical reading of the manuscript. Research in the McKeating laboratory is funded by  Wellcome Trust   IA 200838/Z/16/Z  and  MRC  project Grant  MR/ R022011/1. Collaborative research in the Protzer and McKeating laboratories was funded by  EU   Horizon 2020 program  through the  Hep-CAR  consortium and the  Institute for Advanced Study  with the support of the  Technische Universität München  via the  German Excellence Initiative  and  EU   7th Framework Programme  under grant agreement number  291763. TM was supported by a clinical leave stipend by the  Else-Kröner Forschungskolleg "Microbial triggers as cause for disease" of Klinikum rechts der Isar, Technische Universität München.
Data availability RNA-seq data from HBV infected mice are deposited in the GEO archive at NCBI, with the accession number GSE145835 and entitled: Transcriptional profiling of hepatocytes isolated from chronically HBV-infected human liver chimeric mice. Our in-house data was compared with RNA-seq  55  from HBV-infected primary human hepatocytes and data retrieved from GEO (accessions: GSE120886, GSE93153, GSE118295).
We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children's behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference.
The table was developed in order to inform the control of a supervised-autonomous robot used in RET  [13] , but was also used to support assessment and analysis of SHT. A total of 3121 therapy sessions was recorded, covering 306 hours of therapy. While the clinical results from the evaluation are in the process of being published elsewhere, we here present a public release of the DREAM dataset, made available for download by the Swedish National Data Service, https://doi. org/10. 5878/17p8-6k13. Following the ethical approval and agreements with caregivers, this public release does not comprise any primary data from the study. Primary data refers to direct measurements, e. g. , video and audio recordings, of children in therapy. Instead, this public release comprises secondary data not revealing the identity of the children.
While this is far from the only mobile application for screening of ASD, we believe this initiative stands out by, in contrast to several other applications, being supported by published research and by sharing parts of the underlying databases publicly  [29]. Such datasets, covering for example traits, characteristics, diagnoses and prognoses of individuals diagnosed with ASD could be important assets, and are still very rare. Mobile applications could be excellent tools, for example during screening, not the least by being very accessible to the broader population. However, complete diagnosis and treatments require more information, and other forms of interaction, than what can be achieved with a mobile application. For example, coverage of the patient's behavior and social interactions are critical components for both improved understanding of ASD and development of new tools.
One example that clearly demonstrates the value of data-driven analysis of ASD is the work by Anzulewicz et al. [30]. The authors report a computational analysis of movement kinematics and gesture forces recorded from 82 children between 3 and 6 years old. 37 of these children were diagnosed with autism. The analysis revealed systematic differences in force dynamics within the ASD group, compared to the typically developed children included in the study. Unfortunately, this dataset has not been released publicly. Moving outside the autism spectrum, there are a couple of relevant datasets focusing on social interaction. One such example is the Tower Game Dataset  [31] , comprising multimodal recordings from 39 adults engaged in a tower building game. A total of 112 annotated sessions were collected, with an average length of three minutes.
It focuses specifically on rich dyadic social interactions. Similar to the data-set presented here, the Tower Game Dataset contains body skeleton and eye-gaze estimates. Additionally, the dataset is manually annotated with so-called Essential Social Interaction Predicates (ESIPs). The authors promise that "a dataset visualization software [. ] is available and will be released with the dataset"  [31] , but unfortunately the dataset does not appear to be publicly available online. Another dataset covering social interaction is the Multimodal Dyadic Behavior Dataset (MMDB)  [32, 33]. This dataset comprises audio and video recordings from semi-structured play between one adult and one child in the age of 1 to 2 years. To date, 160 sessions of 5-minute interaction from 121 children have been released.
Videos are annotated automatically for gaze shifts, smiling, play gestures, and engagement. An attractive aspect of this dataset is that the raw data streams are provided, including a rich set of 13 RGB cameras, one Kinect (RGBD) camera, 3 microphones, and 4 Affectiva Q-sensors for electrodermal activity and accelerometry, worn by both the adult and the child. Focusing instead on human-robot interaction, the UE-HRI dataset  [34]  is a recent example. It includes audio and video recordings of 54 adult participants engaged in spontaneous dialogue with the social robot Pepper. The interactions took place in a public space, and include both one-to-one and multi-party interactions. To our knowledge, the only public dataset covering children's interaction with robots is the PInSoRo dataset  [35].
This dataset concerns typically developed children not associated with autism, but shares a similar ambition to support a data-driven study of interaction. PInSoRo covers 45 hours of RGB video recordings, 3D recordings of the faces, skeletal information, audio recordings, as well as game interactions. In addition, the dataset comprises manual annotations of, for example, task engagement, social engagement, and attitude. In sum, several datasets related to the study of social interaction, human-robot interaction, and autism can be found in the literature. Some are also released publicly, but none of them reach the same size as the dataset we present here. While there are other datasets with a similar, or even richer, set of features, none of these cover children diagnosed with ASD. Under the label Behavior Imaging, Rehg et al.
[36, p. 87 ] explicitly argue for the need for such a dataset: We believe this approach can lead to novel, technology-based methods for screening children for developmental conditions such as autism, techniques for monitoring changes in behavior and assessing the effectiveness of intervention, and the real-time measurement of health-related behaviors from on-body sensors that can enable just-in-time interventions. Since children diagnosed with ASD are often sensitive to new clothing and wearable equipment, we consciously avoided on-body sensors. However, in other respects, we hope that the present work constitutes one important step towards a data-driven study of autism outlined by Rehg et al. [36].
Clinical evaluation and protocol The clinical evaluation of RET, from which the present dataset is gathered, was conducted between March 2017 and August 2018 at three different locations in Romania. 76 children, age 3 to 6 years, were recruited to the study, out of which 70 met the inclusion criteria and were randomly assigned one of two conditions, RET or SHT. Participants in both groups went through a protocol of initial assessment, eight interventions, and a final assessment. The effect of the treatment was assessed using the Autism Diagnostic Observation Schedule (ADOS), in terms of the difference between the initial and final assessments  [37]. Nine children did not continue the treatment beyond initial diagnosis, e. g. , as a result of high skill performance, leaving 61 children with an initial ADOS score between 7 and 20 in the study (RET n = 30, SHT n = 31).