dataesr/scientific-paragraphs-categorization huggingface dataset:
For this CoJo analysis we used 1000 genomes phase 1 imputed data from Blue Mountain Eye Study (BMES) population cohort comprising 2582 individuals of European ancestry to calculate linkage disequilibrium (LD) patterns. We used the software GTOOL-v0. 7. 5 (http://www. well. ox. ac. uk/%7Ecfreeman/software/gwas/gtool. html) to convert BMES IMPUTE2 data (both SNPs and Indels) to the plink format. This conversion changes A/T/G/C/I/D/R based allele coding to 1 or 2 (first and second allele). We extracted variant IDs, hg19 genomic locations and converted A/T/G/C/ I/D/R (from 1/2 based allele coding) for all 16,666,330 available variants (MAF > 0. 01) from BMES data and merged it with the European-specific meta-analysis result file based on hg19 genomic location. Further quality checking was done by plotting the allele frequencies of the allele 1 of variants in chromosome 22 in the BMES cohort and European-specific meta-analysis summary file.
The edited European-specific meta-analysis summary file with 1/2 allele coding was used as an input for the CoJo analysis. In the CoJo analysis we considered 5 × 10 -8 as the genome-wide significant threshold. We did not perform CoJo analysis in the Asian studies because the various Asian sub-studies (Indian, Malay, Chinese) had differing ancestry within Asia and we did not have access to a suitably large (i. e. , N > 2000) reference genotype data set for each Asian sub-population. Gene-based analysis. We performed gene-based association testing using the VEGAS2 software  20. VEGAS2 is an extension of the VErsatile Gene-based Association Study (VEGAS) approach  59  that uses 1000 genomes reference data to estimate LD between variants and provides a test using a more flexible gene boundary.
For this analysis, we considered '-10 kbloc' parameter, which assigns all variants in the gene or within 10 kb on either side of a gene's transcription site to compute a gene-based P-value. We performed analysis using the default '-top 100' test that uses all (100%) variants assigned to a gene to compute gene-based P-value. We used 1000 Genomes phase 1 European and Asian populations to compute LD between variants for European-specific and Asian-specific gene-based analysis respectively. Finally, we meta-analysed the European-specific and Asian-specific gene-based results using Fisher's method for combining P-values. Analysis of case-control cohorts. We tested the lead CCT-associated SNPs in two keratoconus datasets with 933 cases and 5946 controls and two POAG datasets with 5008 cases and 35,472 controls.
Details of the disease cohorts can be found in the Supplementary Note 1. For both keratoconus and POAG we meta-analysed the association results for individual study samples using a fixed effect approach. The significance threshold for replication was established using the Bonferroni method for multiple testing correction. CCT-associated loci and Mendelian diseases. We assessed whether the CCTassociated loci overlapped with candidate genes for rare Mendelian diseases. For this analysis we downloaded the most up-to-date annotations of genes to the Mendelian disease from the Online Mendelian Inheritance in Man (OMIM) portal  60  on 26th July 2016. We converted the genomic locations of CCT-associated variants from hg19 (or GRCh37) to the GRCh38 human genome build using the software liftOver  61, 62  and extracted all gene transcription start sites that lie within the 1 mega-base (Mb) on either side of a given variant.
Identifying regulatory variants. Using the software HaploReg (version 4. 1) 25 and RegulomeDB v1. 1  22  , we investigated regulatory annotations for variants in LD (r 2 > 0. 8, 1000 genomes CEU) with the CCT-associated SNPs. To prioritize functional SNPs, we first used HaploRegv4. 1 to extract all variants in LD with the 54 independent index SNPs and examined whether variants overlapped with regulatory elements of the ENCODE data, with the caveat that those do not include corneal tissue or cell lines data. We then used the RegulomeDB score to assess their potential functional consequence, as described previously  63. Tissue-enrichment and gene prioritization analyses were performed with the DEPICT 23 framework, using independent CCT genome-wide significant SNPs. We also investigated the expression of functionally relevant genes in associated loci using the Ocular Tissue Database, https://genome.
uiowa. edu/otdb/, in which gene expression is indicated as Affymetrix Probe Logarithmic Intensity Error (PLIER) normalized value (with normalization in PLIER as described in Wagner et al. ,  43  ). Further, we used GARFIELD to assess enrichment of CCT association signals in regulatory features, using the 1005 features extracted from ENCODE, GENCODE and Roadmap Epigenomics projects provided by the software developers. Pathways analysis based on VEGAS2 gene-based P-values. We adopted the resampling approach to perform pathway analyses using VEGAS2 derived genebased P-values considering a '-10 kbloc' and '-200 kbloc' parameters respectively. The latter was performed to capture a larger number of nearby genes, in case the causal SNP or SNPs operate via long distance effects on genes in the wider region.
Pathway analysis using Ingenuity Pathway Analysis. To select the genes included in the IPA®, we extracted the genes +/-200 kb of the lead SNP and further chose those that were expressed in the cornea (Supplementary Table  12 ). Corneal expression levels were retrieved from the Ocular Tissue Database  43. A gene list including 162 genes was used to run the IPA "Core-Analysis". Parameters of the analysis included (1) the Ingenuity Knowledge Base (Genes only) as the reference set, (2) including direct and indirect relationships, (3) experimentally observed, (4) from mammal species, (5) using all tissues and cell lines. Results were corrected for multiple testing using the Benjamini-Hochberg multiple testing correction as implemented in IPA. URLs. GARFIELD software is available in a standalone version at http://www.
Inside each block, we presented the Think, No-Think and Baseline items either with a block design (Study 1) or using a randomized order (Study 2). Each scene was presented on full-screen during 3 seconds, after that a SAM valence rating scale appeared under a reduced version of the picture and participants had to report their affective rating of the scene. Heart rate was recorded during the whole procedure. We illustrate the valence rating task for a single trial presentation with the corresponding heart rate activity. The object illustrating the memory cue are from the BOSS data base and the pictures illustrating the paired scenes are free-use pictures taken from the internet for illustrative purpose.
Given that we observe a stronger cardiac deceleration in response to negative scene in the pre-TNT evaluation, this post-TNT deceleration would suggest a stronger emotional reaction which follows memory suppression. Indeed, images categorized as sad were reported as more intrusive than disgusting ones and were not more forgotten than baseline following the TNT phase (see Fig. 2 ). This pattern of findings suggests that direct suppression was ineffective for these stimuli. This difference cannot be explained by a lower emotional valence, based on the rating provided by either the NAPS database  (Riegel et al. , 2015)  or by our participants. Previous works proposed that, when unsuccessful, memory suppression could indeed worsen the distressing symptoms  (Davies and Clark, 1998; Shipherd and Beck, 2005).
We recorded the electrocardiogram (ECG) using the Biopac MP36R Data Acquisition system and its PC software AcqKnowledge 4. 1 during the full duration of this task (˜20 min. ). Although the presentation of these data goes beyond the scope of this paper, the electrodermal activity (EDA), were also recorded. All the participants undertook this emotional rating task in the morning (8 a. m) and were familiarized with the task settings using 10 independent images selected in the NAPS database. After an initial resting block of 2 min. , the 72 images used in the think/no-think procedure (including baseline items) were presented according to two blocks of Neutral and Negative scenes whose order was counterbalanced across participants. The presentation of these two main blocks was further separated by a resting block of 2 min.
However, we kept emotion and neutral conditions presented in separated blocks to control for long term autonomic change induced by emotions that may spread over and modulate cardiac response to neutral scenes. In addition, we also restricted the subjective assessment of emotional response to the valence rating task (and removed the arousal scale). This last change explains the difference in mean response time between Study 2 and Study 1. Think/no-think task. Electroencephalographic (EEG) activity was recorded during the think/no-think task of Study 2 (data not reported here). Application of the EEG cap (Electrical Geodesics, INC. , Hydrocel Geodesic Sensor Net) was fast (about 15mn) causing very trivial delay between learning and TNT task. After the offset of each of the Think or No-Think trial cues, participants reported the extent to which the associated scene had entered awareness by using a 3-points scale, instead of binary yes/no choice in Study 1, corresponding to the labels: never, briefly, often.
EEG recording EEG activity was recorded continuously by GES 300 amplifier (Electrical Geodesics, INC. ) using an EGI Hydrocel Geodesic Sensor Net (HGSN-128) with dense array of 128 Ag/AgCl sensors  (Tucker, 1993). Impedances were kept under 100 k  (Ferree et al. , 2001) , and EEG channel was referenced to a vertex reference Cz and ground to CPPZ (fixed by the EGI system). The signal was sampled at 20 kHz frequency with a 24-bit A/D and was online (hardware) amplified and low pass filtered at 4 KHz. The signal was filtered by a Butterworth low pass Finite Inpluse Response (FIR) filter at 500 Hz and sub-sampled at 1 KHz. Electrooculogram was recorded using four electrodes placed vertically and horizontally around the eyes. EEG data were processed offline using Netstation 4. 4. 2 (Electrical Geodesics Inc.
For the 'Think' condition, we selected only trials where the participant reported a successful memory reactivation (feedback = 1). We kept all available 'No-Think' trials and extracted the power for each epoch in the high theta frequency band [5-9 Hz] in order to replicate results from Waldhauser et al. (2014). To do so we similarly applied 2x5 Morlet wavelets in frequencies ranging from 5 to 9 Hz with a width of 5 cycles. After this procedure, we cropped the epochs from -0. 5 s to 3. 0 s to avoid edge artifacts and baseline corrected by subtracting the mean of the response in the interval from -500 to 0 ms. The resulting time-frequency data were then down-sampled to 10 ms time-bins for further analysis.
Statistical analysis Analysis were performed using custom Python scripts (Python 3. 6) together with specific modules for EEG analysis  (Gramfort, 2013)  and R packages (R version 3. 4) for factorial analysis  (Singmann et al. , 2016)  and effect size calculation  (Torchiano, 2017). Robust correlations were performed using the correlation toolbox  (Pernet et al. , 2013)  implemented in Matlab 2017b (The Mathworks). Figures, scripts, statistical analysis and the data reported in this paper are made available at: https://github. com/legrandnico/cardiac control. Behavior. Items that were not correctly recalled during the final test before TNT were systematically excluded from later analyses (Study 1: 1. 2%; Study 2: 1. 1%). We analyzed behavioral results with ANOVA integrating all the available factors and tested specific hypothesis with planned comparisons.
The stimuli were selected from the same database than Study 1 with half of the critical scenes rated as Neutral (mean valence: 5. 79; SD valence: 0. 84; mean arousal: 4. 78; SD arousal: 0. 71) and the other half as Disgust (mean valence: 3. 15; SD valence: 0. 68; mean arousal: 6. 35; SD arousal: 0. 48).
Reconstruction of the Amniota ancestral genome The ancestral Amniota genome was reconstructed using the AGORA (Algorithm for Gene Order Reconstruction in Ancestors)  [18]  (https://github. com/DyogenIBENS), which is routinely used to reconstruct ancestral gene order presented in Genomicus since Ensembl release 53. The Amniota reconstruction used here is available for download on the ftp site of the Genomicus webserver  [23]  (ftp:// ftp. biologie. ens. fr/pub/dyogen/genomicus/69. 10/ and  [42] ). AGORA takes as input the gene orders, gene orientations, and gene trees from 61 extant metazoan genomes available in release 69 of Ensembl (2012/11/15). The 61 species are listed in the Additional file 1: Table  S4  and include 40 mammals, 3 birds, 1 reptile, 1 turtle, 1 amphibian, 1 coelacanth, 1 lamprey, and 8 teleost fish among vertebrates, and 2 Cionas, 1 fruit fly and 1 nematode.
Results The automated Design-Build-Test-Learn pipeline. The Design stage of the pipeline includes an integrated suite of novel software tools. For any given target compound, tools for automated pathway and enzyme selections are RetroPath  9  and Selenzyme 10 (http://selenzyme. synbiochem. co. uk), respectively. Reusable DNA parts are then designed with the simultaneous optimization of bespoke ribosome-binding sites and enzyme coding regions using the in-house-developed PartsGenie software  11  (https://parts. synbiochem. co. uk). Genes and regulatory parts are combined in silico into large combinatorial libraries of pathway designs, which are statistically reduced using design of experiments (DoE) to smaller representative libraries. Such libraries allow the efficient exploration of the design space resulting in tractable numbers of samples for laboratory construction  12, 13  and screening  14, 15  , alleviating the need for high-throughput systems.
Our suite of design tools can be easily deployed in other biofoundries. All designed parts and plasmids are deposited from a centralized ICE repository providing the transition from Design to Build. Automated worklist generation for ligase cycling reaction assembly can facilitate standardizing the Build step. The data tracking systems underpin the transition from Build to Test and Learn. Efforts from several groups on standardization of the SOPs/software protocols to provide common platforms and transferability are therefore enabling technologies for the integration as far as they remain open source. As they become community standards, such standard protocols will be incorporated into our pipeline. The aim of the pipeline is to perform rapid prototyping in order to identify the best combination of genetic parts leading to high producer strains.
Our first application of the pipeline targeted flavonoid production pathways expressed in E. coli. Flavonoids are among the most structurally diverse classes of natural products  19  , and pinocembrin serves as a key precursor to this diversity  20. Automated enzyme selection for the pinocembrin pathway had already been validated using our RetroPath 21 software and served as a compatible start point for the rest of the pipeline. The four selected enzymes (phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS) and chalcone isomerase (CHI) (all from Arabidopsis thaliana) and 4-coumarate:CoA ligase (4CL) (from Streptomyces coelicolor, strain ATCC BAA-471/A3(2)/M145)) convert L-phenylalanine to (2S)-pinocembrin with the requirement for malonyl-CoA (Fig. 2 ). In order to efficiently explore the design space, an initial library covering a wide range of variants was designed with the following parameters: four levels of expression by vector backbone selection; varying the copy number from medium (p15a origin) to low (pSC101 origin) and including a strong (P trc ) or a weak promoter (P lacUV5 )  22.
In order to assess the production capabilities of the prototype selected by the pipeline, we performed additional screening for optimal chassis, growth media, and strain. The three best-performing pathways from the second library (3382, 3353, and 3391) were screened in triplicate in nine different E. coli strains, including K-12, B, and W strains derivatives (Fig. 3a  and Supplementary Data 5). A dramatic range in pinocembrin production titers was observed (from 0. 1 to 34. 7 mg L -1 ), with K-12 strains displaying the highest titers. Pathway 3382 was the highest producer across the top-performing strains, consistent with the library screens conducted in DH5α. The MDS42 strain with pathway 3382 produced the highest median titer of 30. 4 mg L -1 , representing a five fold increase with respect to the titer obtained in DH5α.
Gene parts were designed with the PartsGenie web application  11  (http://parts. synbiochem. co. uk). RBS translation initiation rates were set to 15,000  28  , CDS were codon optimized for expression in E. coli, and 5′ and 3′ sequences were optimized for assembly via the ligase cycling reaction  16. Parts were also designed to be compatible for BglBrick  22  and Golden Gate assembly  29. All part and plasmid designs were formatted in the Synthetic Biology Open Language (SBOL) version 1  30  and are available from our ICE repository (https://ice. synbiochem. co. uk)  17, 18. A combinatorial approach was utilized in designing synthetic plasmids expressing each pathway, using a formalized design of experiments (DoE) method. Our design strategy tried to minimize the number of samples by selecting sets of optimal combinatorial libraries to explore the design space determined by the target chemical-producer pathway to be imported into a chassis organism.
We assayed target compound titers from triplicate colonies using a 96-well plate HTP-LC-MS/MS (QqQ) quantitative system based on fast chromatography and automated MRM data extraction for selective Q1Q3 transitions for each compound. Hamilton Star robotics platforms have been optimized for the efficient assembly of DNA pathways and the analysis of downstream combinatorial libraries. Equipped with both 8 channel and 96 head liquid handling, integrated PCR (TRobot), colony picking, growth and induction methods and metabolite extraction from cultured supernatant (Supplementary Fig. 1 ). Automated worklist packages generated from our Design software provide the complete recipes required for automated pathway assembly, coupled with integrated barcode reading for quality control and sample tracking.
Part preparation. DNA parts (Supplementary Table  3 ) were synthesized by commercial vendors (Life Technologies, Germany; Gen9, USA; Twist Biosciences, USA) and amplified using part specific 5′-phosphorylated primers (Integrated DNA Technologies, Belgium; Supplementary Data 1). PCR reactions were treated with DpnI (NEB), spin column-purified, analyzed by gel or capillary electrophoresis, quantified using a Nanodrop (ThermoFisher) and diluted to 75 nM with deionized water for ligase cycling reaction assembly. Parts were made fresh for each assembly and stored at 4 °C for <5 days. Plasmid assembly. An automated pipeline was created on the robotic platforms to reduce human error and ensure consistency and accuracy of assembly. Parts were produced by commercial DNA synthesis vendors followed by PCR amplification and processing.
UPLC methods were optimized for the resolution of cinnamic acid and pinocembrin (flavonoids pathway) on a BEH C 18 column (2. 1 × 50 mm, 1. 7 μm; Waters), and THP, reticuline and scoulerine (alkaloids pathway) on an HSS T3 column (2. 1 × 50 mm, 1. 8 μm; Waters). Mobile phase A (water + 0. 05% formic acid) and mobile phase B (methanol + 0. 05% formic acid) were used at an operating temperature of 45 °C (flavonoids pathway) or 40 °C (alkaloids pathway). Instrument injection sequences were randomly generated by Excel-based data tracking and worklist generators. The optimized flavonoids LC gradient ran at a flow rate of 0. 6 mL min -1 , resulting in a total runtime of 2 min per sample. A linear gradient of 40-95% B (v/ v) was applied over 1. 5 min, before returning linearly to 40% B (v/v) over 1 min.
Binary MS/MS files were automatically transferred and archived with corresponding metadata using a data acquisition service. The binary MS/MS files were then transformed using Proteowizard  38  to open-source mzXML format files from which we extracted peak areas from selective MRM transitions and performed absolute quantification in an automated manner. Custom in-house scripts used for peak areas extraction are available online at https://gitlab. cs. man. ac. uk/mqbpwca2/RP2. Statistical analysis. In order to analyze the significance of the effects for each factor, we performed a standard least squares analysis. Promoters were considered as a categorical factor, plasmid copy numbers were considered as an ordinal factor with two possible values: low and high copy number. P values corresponded to the probability associated with an F-test of zero effect of the parameter.
All tests were carried out using JMP Pro 12. 2. 0 (SAS Institute). Box-plot elements in figures: center line, median; box limits, upper and lower quartiles; whiskers, 1. 5× interquartile range; points, outliers. Data management support. The integrated pipeline benefited from the support of a data management system consisting of commercial, open source, and bespoke data management platforms, which assisted in making the data FAIR (findable, accessible, interoperable, reusable)  39  throughout the pipeline. An instance of the open-source JBEI Inventory of Composable Elements (ICE) registry  16, 17  was used as registry of parts, plasmids, and strains. Recording of experiments was performed using shared electronic lab notebooks (http://www. labarchives. com). A data acquisition service was developed in house, which allowed data to be remotely transferred from laboratory instruments (e.
Acknowledgements All authors acknowledge the funding from the  UK Biotechnology and Biological Sciences Research Council  (BBSRC; http://www. bbsrc. ac. uk) and  UK Engineering Physical Sciences Research Council  (EPSRC; http://www. epsrc. ac. uk) under grant  BB/M017702/1 , " Centre for synthetic biology of fine and speciality chemicals (SYNBIOCHEM) ". J. L. F. acknowledges funding provided by  French National Research Agency  under grant  ANR-15-CE1-0008. C. G. and N. J. S. acknowledge funding from the  Biotechnology and Biological Sciences Research Council  (BBSRC; http://www. bbsrc. ac. uk) under grant  BBSRC BB/M013189/1  (DMMCore).
We present BOLDR, a modular framework that enables the evaluation in databases of queries containing application logic and, in particular, user-defined functions. BOLDR also allows the nesting of queries for different databases of possibly different data models. The framework detects the boundaries of queries present in an application, translates them into an intermediate representation together with the relevant language environment, rewrites them in order to avoid query avalanches and to make the most out of database optimizations, and converts the results back to the application. Our experiments show that the techniques we implemented are applicable to real-world database applications, successfully handling a variety of language-integrated queries with good performances.
which is intended to return the set of all employees which salary converted in USD is greater than 2000, will throw an error at runtime since LINQ fails to translate the function getRate to an equivalent database expression. One solution is to define getRate in the database, but this hinders portability and may not be possible at all if the function references runtime values of the language. A more common workaround is to rewrite the code as follows: db. Employee. AsEnumerable(). Where(x => x. sal >= 2000 * getRate("USD", x. cur)) But this hides huge performance issues: all the data is imported in the runtime of the language, potentially causing important network delays and out-of-memory errors, and the filter is evaluated in main memory thus neglecting all possible database optimizations.