dataesr/scientific-paragraphs-categorization huggingface dataset:
and the following command: `RGAugury. pl -p {peptides. fa} -e 1e-5 -c 10 -pfx {output}`. The latest versions of all the databases and tools used by RGAugury were downloaded as of April 2020 following the installation instructions provided in the RGAugury online repository [48]. Briefly, this pipeline enables to identify different major RGA families (NBS encoding; RLP: membrane associated receptor like proteins; RLK: surface localized receptor like protein kinases: RLK). Based on the presence or absence of some domain structures (CC: coiled-coil, TIR: Toll/Interleukin 1 Receptor, NB-ARC: nucleotide binding site activity regulated cytoskeleton; LRR: leucine rich repeat), the NBS encoding proteins were.
Acknowledgements This work was supported by the  Genoscope , the  Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA) and France Génomique  ( ANR-10-INBS-09-08 ). We acknowledge the  BrACySol BRC (INRA Ploudaniel, France)  that provided us with the seeds of B. napus cv. Darmor-bzh. The authors are grateful to  Oxford Nanopore Technologies Ltd  for providing early access to the PromethION device through the PEAP, and we thank the staff of  Oxford Nanopore Technology Ltd  for technical help.
Availability of supporting data Darmor-bzh is a French winter variety, freely available in Plant Genetic Resources BrACySol (Rennes, France). The Illumina and PromethION sequencing data and the Bionano optical maps are available in the European Nucleotide Archive under the following projects PRJEB39416 and PRJEB39508. The genome assembly, gene predictions and a genome browser are freely available at http://www. genoscope. cns. fr/plants.
Assay protocol Serum samples (100 μL per well) were diluted 1:100 in a proprietary assay buffer and tested in duplicate (Fig. 1B ). The plates were incubated 1 h at 37 °C on a microplate shaker (VWR International) at 300 rpm, and washed three times (200 μL/well) with PBS pH 7. 4, containing 0. 1% of Tween 20 (Sigma). For conjugation, 100 μL of proprietary conjugate buffer was added to each well, followed by 1 h incubation at 37 °C in the dark. After washing, 50 μL of insoluble TMB (Calbiochem®, Merck) was added to each well and incubated for 15 min in the dark. After a final washing step with 200 μL of mQ water per well, any trace of residual water was removed by incubation for 15 min at 37 °C. Images of individual wells were captured by a microplate reader (Clair®, Sensovation AG) operated by the software Sensospot® (Sensovation AG).
Data analysis The MI cut-off values and associated diagnostic performance of each antigen target were determined by receiver operating characteristic (ROC) analysis (GraphPad Prism® 7). The diagnostic specificity was evaluated on negative samples detection rate over time (DPI -7 to 42) for each antigen was evaluated on positive samples collected from homologous inoculation group. The analytical specificity of each antigen was evaluated on samples collected between DPI 7-42 DPI from heterologous inoculation groups. Onway ANOVA with Dunnett's correction was used for multiple comparisons with alpha = 0. 05 (GraphPad Prism® 7). Specifically, we compare the antibody response between inoculation groups by day post inoculation for each antigen target.
| Sample Data from participants enrolled in the Whitehall II imaging substudy were examined. A detailed description of this cohort has been published previously  (Filippini et al. , 2014). In brief, these individuals were originally recruited in 1985 as part of a cohort of 10,308 civil servants based in London  (Marmot & Brunner, 2005) , and have since been regularly assessed (at 5 year intervals) on a range of lifestyle, biological, and cognitive variables. Between 2012 and 2016, a random sample of 800 individuals were invited to undergo an MRI brain scan and comprehensive cognitive battery, as part of the Whitehall II imaging substudy  (Filippini et al. , 2014).
| Associations with lifestyle trajectories LCGA was employed to evaluate whether the sample could be subdivided into trajectory classes based on repeated measures of lifestyle index scores (Section 2. 5). This is a widely used method that has previously been applied to identify trajectories of sleep  (Zitser et al. , 2020)  and BMI  (Vistisen et al. , 2014)   restricted maximum likelihood with robust SEs was used. Full information maximum likelihood was also employed to estimate parameters in the presence of missing data  (Enders & Bandalos, 2001). All lifestyle index scores were standardized prior to the LCGA to minimize biases introduced by variation in the questionnaire between the prior phases and MRI scan. The model with best fit was identified based on achieving the lowest Akaike information criterion (AIC), Bayesian information criterion (BIC), and sample-size adjusted BIC (aBIC), with an entropy value ≥0.
An average was selected over a summary score due to being less biased in the presence of missing data (as individuals with either four or five phases of lifestyle data were included in the analyses). In order to derive comparable β estimates, all variables were standardized prior to the linear regression analyses. The associations were first examined adjusting for chronological age only (Model 1), and if the associations were significantly different from zero (α level of. 05), they were followed up by analyses adjusting for age as well as CAG/BAG, and additional factors known to influence brain and cognitive health in aging, including sex (e. g. ,  Ritchie et al. , 2018) , education (e. g. , Boller, Mellah, Ducharme-Laliberté, & Belleville, 2017), ethnicity (e. g. ,  Gavett et al. , 2018) , and BMI (e.
DATA AVAILABILITY STATEMENT The study follows MRC data sharing policies (https://www. mrc. ac. uk/ research/policies-and-guidance-forresearchers/data-sharing). In with these guidelines, data from the Whitehall II Imaging Sub-study will be accessible via the Dementias Platform UK (https:// portal. dementiasplatform. uk/) 430 after 2019. Data from the Whitehall II Study is available through formal request to the data sharing committee (https://www. ucl. ac. uk/iehc/research/epidemiologypublic-health/research/whitehallII/data-sharing).
(Bennett & Madden, 2014;Bråthen et al. , 2020;Grady, 2012)ocs. io/en/latest)wasusedto predict brain age based on the MRI measures described in Section 2. 3. 1, and cognitive age based on the cognitive tests described in Section 2. 4 (excluding premorbid IQ). The XGBoost model is based on a decision-tree ensemble algorithm that includes advanced regularization to reduce overfitting(Chen & Guestrin, 2016), and uses a gradient boosting framework where the final model is based on a collection of individual models (https:// github. com/dmlc/xgboost). To optimize hyperparameters, a randomized search was performed with 10 folds for each model, with scanned parameter ranges set to maximum depth:(Bennett & Madden, 2014;Bråthen et al. , 2020;Grady, 2012), number of estimators: [60, 220, 40], and learning rate: [0.
Sequence quality assessment and trimming. The quality of the raw sequence data was checked via FASTQC. The sequence files were then trimmed using tools in Trimmomatic-0. 36  (23). The following were removed: Illumina TruSeq3 single-ended adapter sequences, bases with a quality score lower than three at the start and end of a read, bases that had an average quality per base of <15 calculated using a sliding window to average four bases, and any reads that were shorter than 36 bases. The reads were single-ended and qualities were ASCII characters equal to the Phred quality plus 33. Mapping and counting reads. HiSat2  (24)  was used to build indexes from the Reference Consortium Mouse Build 38 (mm10) and to align sequence reads to the genome. The resulting. bam files were sorted and indexed with SAMtools  (25).
The locations of putative PAS (AATAAA, ATTAAA and AAGAAA)  (31)  and CPE (TTTTAT, TTTTAAT, TTTTACT, TTTTAAAT, TTTTAAGT and TTTTCAT) (32) sequences were determined via the Find Individual Motif Occurrences tool  (33)  that is part of the MEME Suite  (34) ; only exact matches were used for downstream analysis. Python scripts were written to calculate the distance of each CPE from each PAS for individual 3 UTRs. Data visualization. ggplot2  (35)  was used to create the multi-dimensional scaling (MDS) plots used to visualize sample-to-sample distances, and translation activation and repression time course plots. All other data were plotted using GraphPad Prism 8.
However, a sizable group of mRNAs whose translation is activated during meiosis instead is activated transcriptionally at the S-to-M-phase transition. Although limited, overlap is also detected when translation repression during meiosis is compared with changes in translation during mitosis. Manual curation of the data from multiple datasets confirms that decreased translation of Cdk1 and increased translation of Bub1b occur during meiosis (Supplementary Figure  S4 ).
A switch in the pattern of maternal mRNA translation is detected at the time of meiotic re-entry During Pro I, maternal messages display a broad spectrum of translation efficiencies (TEs) (Figure  3A ), defined as the  ← ------------------------------------------------------------------------------------------- attachment (6 h, late pro-metaphase I), or a fully attached, Met I-bipolar spindle (8 h, Met I). (B) Total mRNA levels and differential ribosome loading during meiotic progression as compared to Pro I. Oocytes were matured in vitro and collected at 0, 2, 4, 6 and 8 h post-meiotic resumption. Total RNA samples were collected prior to RiboTag-IP for each time point. cDNA libraries were prepared from total and ribosome-bound RNA samples, RNA-Seq was performed, and the data processed and analyzed as described in 'Materials and Methods.
' The data are presented as volcano plots with log 2 (fold change) (LFC) CPM at each time point compared to 0 h and plotted against false discovery rate (FDR). Statistically significant increased (red) and decreased (blue) (FDR ≤ 0. 05) genes are reported as well as non-significant changes (gray). -1 ≥ LFC ≥ 1 are considered biologically significant and are marked by dashed lines. Two biological replicates of 200 oocytes per time point were used for this experiment. (C) Changes in the transcriptome and translatome during meiosis. Met I data are derived from the experiment described in (B), Met II translation data are from a deposited dataset generated from oocytes matured in vivo followed by polysome fractionation/microarray (polysome array)  (49, 65) , and Pro I-to-Met II total mRNA data were from a deposited dataset  (66).
Both DOWN (blue) and UP (red) genes were analyzed. The data were collected as described in (C). -1 ≥ LFC ≥ 1 with FDR ≤ 0. 05 are considered statistically significant. ratio between ribosome-bound and total mRNA levels  (51) ; there is a seven-fold difference when comparing the average TE of the 10% of mRNAs with the highest TEs (high-TEs) to that of the 10% with the lowest TEs (low-TEs). To validate that TE reflects rate of translation, we related these values to other available measurements in Pro I-arrested oocytes  (52, 53). High-TE messages have significantly longer poly(A) tails (≥70 nts) (Figure  3B ) and are associated with increased protein accumulation as assessed by mass spectrometry (Figure  3C ). GO analysis of low-and high-TE messages during Pro I reveals associations antithetical to those found during meiotic maturation (Figure  2A ).
Deposited TAIL-Seq data on poly(A) tail length of maternal mRNAs during Pro I (52) were associated with TEs during this time. Median values are represented by red lines and the 25% and 75% quartiles are represented by black, dashed lines. Statistical significance was evaluated by unpaired, two-tailed t-tests. ****P < 0. 0001. (C) Genome-wide relationship between TE and protein levels in Pro I-arrested oocytes. TE was calculated for individual mRNAs as described in (A). Deposited data on protein levels in Pro I-arrested oocytes as quantified by mass spectrometry (53) were compared to the TEs of maternal mRNAs. Median values are represented by red lines and the 25% and 75% quartiles are represented by black, dashed lines. Statistical significance was evaluated by unpaired, two-tailed t-test; ****P < 0.
The translation rate for each oocyte was calculated by linear regression of the reporter data (J) between 6 and 9 h. Mean ± SEM is reported. Statistical significance was evaluated by Kruskal-Wallis test; ****P < 0. 0001 and ns: not significant. (L) Accumulation of YPet-Oosp1 in Pro I-arrested CPEB1 +/+ , CPEB1 +/-and CPEB1 -/-oocytes. Oocytes were collected from hormoneprimed wild type, Zp3-Cre T Cpeb1 F/+ , and Zp3-Cre T Cpeb1 F/F mice. Experimental conditions were as described in (E). Each point is the mean ± SEM of individual oocyte traces obtained in two separate experiments. The total number of oocytes analyzed is in parentheses. (M) Translation rates of YPet-Oosp1 in Pro I-arrested CPEB1 +/+ , CPEB1 +/-and CPEB1 -/-oocytes. The translation rate for each oocyte was calculated by linear regression of the reporter data (L) between 6 and 9 h.
0001. (C) Translation repression of the YPet-Zp2 reporter during meiosis resumption requires GVBD and CDK1 activation but not PKA activity. After microinjection of the YPet-Zp2 reporter, oocytes were released in cilostamide-free medium and incubated with a CDK1 inhibitor (5 M dinaciclib) or a combination of CDK1 and PKA inhibitors (Rp-cAMPS) from the time of release (0 h). The translation rate for each oocyte was calculated by linear regression of the reporter data between 3 and 6 h. In another group, dinaciclib was added after GVBD at 2 h into incubation. Statistical significance was evaluated by unpaired, two-tailed t-tests; ns: not significant; **P = 0. 0053. (D) Deletion mutagenesis of the Ccnb2 3 UTR. Pro I-arrested oocytes were collected, microinjected with oligoadenylated YPet-CcnB2 short or reporters fused to Ccnb2 3 UTRs with progressive deletions along with a polyadenylated mCherry reporter.
Sixteen hours after microinjection, oocytes were either maintained in Pro I with cilostamide (empty circles) or allowed to mature (solid circles) and imaged for 6 hrs with a sampling frequency of 15 min. Data are reported as the fold change of the YPet/mCherry ratios as compared to 0 h. Each point is the mean ± SEM of individual oocyte traces obtained in two separate experiments. The total number of oocytes analyzed is in parentheses. (E) Insertion of a CPE in the 3 UTR of Zp2 (DOWN), prevents repression during meiotic maturation. Pro I-arrested oocytes were collected, microinjected with oligoadenylated compared to wild type oocytes (Figure  8F-G ). Moreover, depletion of CPEB1 resulted in higher translation rates prior to GVBD (Figure  8G ), confirming the role of this RBP in translation repression during Pro I.
The total number of oocytes analyzed is in parentheses. (F) Insertion of a CPE in close proximity of the PAS in the Oosp2 3 UTR prevents translational repression during meiotic maturation. Pro I-arrested oocytes were collected, microinjected with oligoadenylated YPet-Oosp2 or a reporter with a CPE inserted in the Oosp2 3 UTR along with a polyadenylated mCherry reporter. Oocytes were incubated for 16 hrs after microinjection, allowed to mature, and imaged for 16 h with a sampling frequency of 15 min. Data are reported as the fold change of the YPet/mCherry ratios as compared to 0 h. Each point is the mean ± SEM of individual oocyte traces obtained in three separate experiments. The total number of oocytes analyzed is in parentheses. (G) Detailed analysis of the relationship between translation patterns during meiotic resumption and the presence of CPEs in the 3 UTR.
The translation rate for each oocyte was calculated by linear regression of the reporter data (F) between 0 and 2 h or 6 and 10 h. Mean ± SEM is reported. Statistical significance was evaluated by Kruskal-Wallis test; ns: not significant; ****P < 0. 0001. (H) Accumulation of wild type Oosp1 and mutant Oosp1 YPet reporters during meiotic maturation. Pro I-arrested oocytes were collected and microinjected with oligoadenylated YPet-Oosp1 (circle), YPet-Oosp1(ΔCPE1) (square), YPet-Oosp1(ΔCPE2) (triangle) or YPet-Oosp1(ΔCPE1+2) (diamond) mRNA along with polyadenylated mCherry mRNA. After 16 h of recovery after microinjection, oocytes were allowed to mature, and imaged for 10 h with a sampling frequency of 15 min. Each point is the mean ± SEM of individual oocyte traces obtained in two separate experiments.
-FDR ≤ 0. 05). Only terms with FDR ≤ 0. 05 were considered. (B) Pairwise comparison of translation during meiosis and transcription during mitosis. FCs in translational efficiency (TE) from 0 h (Pro I) to 8 h (Met I) in our RNA-Seq dataset are plotted against FCs in RNA levels from S-phase to M-phase of a deposited dataset (50). (C) Heat maps comparing fold changes in translation of cell cycle components during meiosis in oocytes and fold changes in transcription or translation during the mitotic cell cycle. The data were collected as described in (B). Genes involved in the cell cycle are defined under GO:0007049.
Statistical significance was evaluated by unpaired, two-tailed t-tests; ns: not significant; **P = 0. 0053. (D) Deletion mutagenesis of the Ccnb2 3 UTR. Pro I-arrested oocytes were collected, microinjected with oligoadenylated YPet-CcnB2 short or reporters fused to Ccnb2 3 UTRs with progressive deletions along with a polyadenylated mCherry reporter. Sixteen hours after microinjection, oocytes were either maintained in Pro I with cilostamide (empty circles) or allowed to mature (solid circles) and imaged for 6 hrs with a sampling frequency of 15 min. Data are reported as the fold change of the YPet/mCherry ratios as compared to 0 h. Each point is the mean ± SEM of individual oocyte traces obtained in two separate experiments. The total number of oocytes analyzed is in parentheses. (E) Insertion of a CPE in the 3 UTR of Zp2 (DOWN), prevents repression during meiotic maturation.
ACKNOWLEDGEMENTS We are indebted to  John C. Wright  ( University of California, Berkeley ) for assistance with bioinformatics analyses, as well as  Elena Gochez  (San Francisco VA Health Care System) and  Emily Miller  ( Stanford University ) for assistance with some experiments. We thank  Dr Ra úl Méndez  and  Dr Gonzalo Fernandez-Miranda  (The  Barcelona Institute of Science and Technology ) for sharing the Cpeb1targeted mice.
DATA AVAILABILITY Raw sequences and TMM-normalized CPM values from the RiboTag/RNA-Seq experiment are available on NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE135525 (https://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc=GSE135525). Scripts used for statistical analysis of the RiboTag/RNA-Seq data and those used to calculate CPE and PAS distances are available on UCSF Box: https://ucsf. app. box. com/s/ k474fl8cvkfql5l8m4o2mxq4dg0kgb9g.
In another group, dinaciclib was added after GVBD at 2 h into incubation. Statistical significance was evaluated by unpaired, two-tailed t-tests; ns: not significant; **P = 0. 0053. (D) Deletion mutagenesis of the Ccnb2 3 UTR. Pro I-arrested oocytes were collected, microinjected with oligoadenylated YPet-CcnB2 short or reporters fused to Ccnb2 3 UTRs with progressive deletions along with a polyadenylated mCherry reporter. Sixteen hours after microinjection, oocytes were either maintained in Pro I with cilostamide (empty circles) or allowed to mature (solid circles) and imaged for 6 hrs with a sampling frequency of 15 min. Data are reported as the fold change of the YPet/mCherry ratios as compared to 0 h. Each point is the mean ± SEM of individual oocyte traces obtained in two separate experiments.
Inclusion criteria Types of studies and participants Studies, reported in peer-reviewed journals or conference abstracts, that included patients (> -18 years) with biopsy-proven or suspected NAFLD, with paired liver histology and index biomarker data were potentially eligible for this review. We made no further restrictions based on either year or language. Studies of participants with mixed etiologies were only included if the performance of the biomarker was separately reported in patients with NAFLD.
Search methods The following databases were searched: MEDLINE via OVID PubMed Embase via OVID (including conference abstracts) Science Citation Index CENTRAL (The Cochrane Library) A sensitive search strategy was developed in close collaboration with our search specialist (RS). Table  S3  shows the search strategy for MEDLINE. The final search strategy was adapted for different databases and initially used in August 2018. It was updated specifically for the ELF test in February 2019 and December 2019 (Fig. 1 ). To identify additional studies, we screened the reference list of related systematic reviews and the included studies. In addition, we contacted the academic and industry partners within the LITMUS consortium for any studies that were missed by our search strategy.
Data collection and analysis Selection of studies and data extraction Using Endnote, duplicate records were removed and titles of all records were screened by 1 reviewer (YV) while the second reviewer screened 10% of the titles independently. Abstracts and full texts were sought and independently assessed by 2 authors (YV and JL). In case of any disagreement, consensus was reached by discussion, first between 2 reviewers and if necessary, with a senior member of the team (MHZ). The screening phase was managed using the Rayyan software (https://rayyan. qcri. org). The following data were extracted by 1 author (YV/JL) and cross checked by the other author (JL/YV): study group characteristics, index test and reference test features, number of true and false positives, and true and false negatives for constructing classification tables.
Statistical analysis Classification tables were extracted or reconstructed for the performance of the index biomarker of each predefined target condition. For the analyses, we extracted the accuracy data on each cut-off point for which the data was available or could be calculated. Different studies could contribute a varying number of thresholds, as well as different sets of thresholds. Estimates of sensitivity, specificity, and corresponding 95% CIs were generated and graphically illustrated in forest plots. We planned to conduct a meta-analysis whenever more than 3 studies with enough information to create classification tables were available. We used a linear mixed effects model for modeling the multiple thresholds data of the individual studies, as recently proposed in "diagmeta" package in R.
51 he 95% CIs for sensitivity and specificity were estimated using the delta method. 50 We used a log-logistic model in our analyses to provide estimates of the 2 cumulative distribution functions of the test results, 1 within the disease-free and 1 within the diseased individuals, across all studies, accounting for the between study heterogeneity and correlation between the groups. Each data point was weighted with the inverse variance of the respective logit-transformed proportion. R for Windows (Version 3. 6. 0; R Foundation for Statistical Computing, Vienna, Austria) was used in all analyses. For sensitivity analysis, we investigated the influence of disease severity among study groups, by removing a study with a very high prevalence of advanced fibrosis. 52 We also assessed the effect of the test-biopsy time interval by removing studies with a long time interval between test and liver biopsy (mean: >12 months).
Search results The initial search of the electronic databases resulted in 9,066 references. After removing duplicates, we screened 6,220 titles and 778 abstracts. We found 265 full-text reports from the electronic searches and 18 studies from other sources. In total, we were able to include 17 studies that had evaluated the accuracy of the ELF test in patients with NAFLD: 13 with full-text reports  17, [23] [24] [25] [26] [27] [28] [29] [30] 34, 35, 52, 55  and 4 only reported in abstracts  22, [31] [32] [33]  (Fig. 1 ). Reasons for exclusion are provided in Table  S5.