dataesr/scientific-paragraphs-categorization huggingface dataset:
The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (500 replicates) are shown next to the branches  (Felsenstein, 1985). Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the JTT model, and then selecting the topology with superior log likelihood value. This analysis involved 16 amino acid sequences. There were a total of 567 positions in the final dataset. Evolutionary analyses were conducted in MEGA X  (Kumar et al. , 2018). The tree has been rooted with Selaginella moellendorffii CYP711A1 (SmCYP711A1). At: A. thaliana; Bd: B. distachyon; Hv: Hordeum vulgare; Os: O. sativa; Sm: S. moellendorffii. Protein sequences used in this analysis are available under the following accession numbers: AtCYP711A1, OAP07831.
Construction of B. distachyon Lines Overexpressing BdCYP711A29 and Selection of BdCYP711A29 TILLING Mutants Following Agrobacterium tumefaciens-mediated transformation of the B. distachyon Bd21-3 ecotype (see section "Materials and Methods"), two independent homozygous BdCYP711A29 overexpressing lines were recovered (data not shown),. In addition, a null segregant, NS-11. 26, that is a plant regenerated from the in vitro culture steps but devoid of the transgene, was selected to be used as a control (Table  1 ). RT-qPCR experiments were conducted to verify the expected overexpression of the BdCYP711A29 gene in spikes, leaves and roots. As shown Bradi1g75310), BdCYP711A30 (Bradi4g08970), and BdCYP711A31 (Bradi4g09040) genes in different organs of the Bd21-3 (WT) ecotype of B. distachyon: roots and leaves were collected from 3 week-old plants under hydroponic conditions in 1 /2 MS liquid medium and spikes were collected at mid-anthesis on plants grown in pots under standard conditions.
, 2014) , the third one encodes a phenylalanine ammonia lyase, recently renamed BdPAL6 (Bradi3g47110,  Cass et al. , 2015)  and the last one codes for a uridine diphosphate (UDP)-glucosyltransferase shown to be involved in the conjugation of DON into DON-3-O-glucose (Bradi5g03300,  Pasquet et al. , 2016). The expression of these four defense genes was first assessed on healthy spikes. Very low basal levels of expression prevented proper comparison of the expression levels in healthy plants of the different genotypes (data not shown). Nevertheless, relative expression of the four marker genes could be quantified after spray inoculation by the F. graminearum FgDON + strain. The 96 hpi time-point was chosen because it corresponds both to the infection time-point used in the transcriptomic analysis of B.
This analysis involved 16 amino acid sequences. There were a total of 567 positions in the final dataset. Evolutionary analyses were conducted in MEGA X (Kumar et al. , 2018). The tree has been rooted with Selaginella moellendorffii CYP711A1 (SmCYP711A1). At: A. thaliana; Bd: B. distachyon; Hv: Hordeum vulgare; Os: O. sativa; Sm: S. moellendorffii. Protein sequences used in this analysis are available under the following accession numbers: AtCYP711A1, OAP07831. 1; BdCYP711A5, XP_003571126. 1; BdCYP711A6: XP_003560652. 1; BdCYP711A29, XP_003562092. 2; BdCYP711A30: XP_003575594. 2; BdCYP711A31, XP_010237353. 2; HvCYP711A5, BAJ97619. 1; HvCYP711A6, KAE87888859. 1; HVCYP711A29, BAJ98237. 1; HvCYP711A30, KAE8810993. 1; OsCYP711A2, XP_015633367. 1; OsCYP711A3, XP_015644699. 2; OsCYP711A4, XP_015642272.
To investigate the biological function of Pf-DNMT2, we developed assays to explore our mutant clones H9 and E11. We first assessed Pf-DNMT2 activity on DNA using liquid chromatographytandem mass spectrometry (LC/MS-MS). We included two independent biological replicates of the 3D7-WT control strain and each of the two DNMT2KO clones, H9 and E11. In parallel, DNA from the yeast Saccharomyces cerevisiae, known to be devoid of DNA methylation  (19) , and DNA from human keratinocyte cell line HaCaT were used as negative and positive controls, respectively. The DNA mass spectrometry data show a 30% decrease in the global levels of 5-methyldeoxycytidine (5mdC) in the two DNMT2KO clones (0. 055%) compared to the 3D7-WT (0. 08%) strain (P = 0. 0153) (Fig. 2A  and Fig. S1 ). In addition to LC/MS-MS, enzyme-linked immunosorbent assay (ELISA)-based 5mdC detection in genomic DNA (gDNA) gave similar reductions in 5mdC in the two KO clones (Fig.
PlasmoDB. org) and may be responsible for function in malaria parasites. In addition to RNA-BS-seq, we adopted a mass spectrometry-based approach to quantify the levels of tRNA cytosine methylation in tRNA isolated from DNMT2 mutants and the 3D7-WT control. Digested tRNA was injected into an Agilent 6490 triple quadrupole mass spectrometer to analyze ribonucleoside modifications. Our mass spectrometry-based quantification showed reduced m 5 C signals (4. 25-fold) in parasites lacking Pf-DNMT2 (Fig. 2D ). This observation is consistent with the predicted function of Pf-DNMT2 in m 5 C tRNA methylation and corroborates our RNA-BS-seq data (Fig. 2B  and C ). Unexpectedly, our MS data also showed a striking decrease in other tRNA cytosine modifications in DNMT2 mutants including mC (m 3 C or m 4 C) and the hypermodification m 4 Cm (Fig.
No homologous angiogenin gene was found in the P. falciparum database PlasmoDB. Furthermore, it remains unknown if tRNA Asp (GTC) -derived fragments in Pf-DNMT2 mutants may have regulatory functions in gene expression as has been reported for a number of eukaryotes  (48, 49). This observation opens a new field of research to investigate the tRNA Asp (GTC) nuclease cleavage and the potential role in protein expression in this pathogen. Conclusion. Here, we identified a specific writer of cytosine methylation of tRNA that safeguards homeostasis of malaria parasite protein synthesis. Pf-DNMT2KO parasites show a shift in metabolic pathways, such as glycolysis, that prime parasites for being destabilized by certain types of cellular stress identified in this work. The biology of reversible and dynamic tRNA modifications and their corresponding writers have been studied widely in several organisms  (50).
Asexual parasite proliferation in the presence of DHA. 3D7-WT and Pf-DNMT2 KO clones H9 and E11 were synchronized, and cultures containing 0. 5% rings were incubated at 2% final hematocrit, with serial 7-point, 2-step dilutions of dihydroartemisinin (DHA) (starting concentration: 50 nM) for 72 h. Parasite proliferation was determined using SYBR green assay as described previously  (52). DHA IC 50 was calculated from three independent experiments using GraphPad Prism 8. qRT-PCR quantification of ap2-g gene expression. RNA was harvested from synchronous parasites after lysis in 0. 075% saponin in PBS and resuspension in QIAzol reagent. Total RNA was extracted using the miRNeasy minikit and performing on-column DNase treatment (Qiagen). Reverse transcription was achieved using SuperScript VILO (Thermo Fisher Scientific) and random hexamer primers.
Heat maps were visualized in R using package ggplot2. Northern blot analysis of Asp (GTC) tRNA stability. Total RNA was harvested from highly synchronous trophozoite stage 3D7-WT and DNMT2 mutant parasites (from both nonstressed and stressed conditions) and separated on 15% Tris-borate-EDTA (TBE) urea gels in order to better resolve the small RNA population. RNA was transferred to positively charged nylon membranes sandwiched by 0. 5Â TBE-soaked blotting papers, using Trans-Blot Turbo (Bio-Rad) (45 min at 300 mA). RNA membranes were then UV cross-linked and baked for 30 min at 80°C. RNA membranes were blocked and incubated with specific 39-Asp (GTC) tRNA (CTCCGAGACCGGGAATTGAACCCGGGTCTTC-biotin) or 5S rRNA (CAGAGTTCTGATGGGATCTGGTGTGGCC-biotin) biotinylated DNA probes overnight at 42°C in ULTRAhyb ultrasensitive hybridization buffer (Ambion).
LC/MS-MS and data analysis for proteomics. Peptides were separated by reverse-phase HPLC (Thermo Easy nLC1000) using a precolumn (Thermo) and a self-pack 5-mm tip analytical column (15 cm by 5 mm C 18 ; New Objective) over a 140 min gradient before nanoelectrospray using a Q Exactive HF-X mass spectrometer (Thermo). The mass spectrometer was operated in a data-dependent mode (see Text S1 for more details). Western blot analysis. For the analysis of Pf-Alba4 expression, 3D7-WT and DNMT2 mutants were synchronized and total extracts were prepared from two biological replicates of each strain. For the analysis of DNMT2 episomal expression, parasites were synchronized and harvested at the ring, trophozoite, and schizont stages, and cytoplasmic and nuclear extracts were prepared as previously described  (7).
ACKNOWLEDGMENTS A. Sinha  and J. L. acknowledge support from the  Singapore-MIT Alliance (SMA)  Graduate Fellowship and MOE Tier 2 grant  MOE2018-T2-2-131. Proteomics work was performed in part in the  Center for Environmental Health Sciences BioCore , which is supported by  Center  grant  P30-ES002109  from the  National Institute of Environmental Health Sciences. We also acknowledge  Peiying Ho  and  Tan Tse Mien  for providing support at  SMART  laboratories in Singapore. F. N. is supported by a  Pasteur Cantarini fellowship. A. Sinha  acknowledges financial support from the  Singapore-MIT Alliance (SMA)  Graduate Fellowships. P. B. A. acknowledges the DIM1Health 2019 grant from the  Région Ile de France  to the project EpiK for the LC/MS-MS equipment. We acknowledge  Gretchen Diffendall  for the scientific proofreading of the manuscript.
Data availability. All the proteomics data can be found in PRIDE (PXD024769) and Table  S4. All the raw tRNA mass spectrometry-based data can be found in the following repository: https://chorusproject. org/ anonymous/download/experiment/-9216109305439230312. tRNA bisulfite sequencing reads are available at the NCBI Sequence Read Archive (SRA) under BioProject number PRJNA723151.
Acknowledgments This work was supported by the  National Key R&D Program of China  ( 2017YFC0405205 ), the  National Natural Science Foundation of China  (No. 41621002 ,  41971047 ,  41790425 ,  4161101120 ). The authors thank  Prof. Li Yiping  from  Hohai University  for the determination of EFDC parameters,  Prof. McWilliams ,  James C. from  University of California, Los Angeles , and  Prof. Sun Shufen  from  Institute of Atmospheric Physics, Chinese Academy of Sciences  for scientific suggestions.
Code and data availability The source code of the EFDC model is freely available from https://github. com/dsi-llc/EFDCPlus. The software named EFDC_Explorer 8. 3 was purchased from DSI LLC (https://www. eemodelingsystem. com/). The configurations, inputs and outputs of the EFDC model for all simulated episodes are available from https://doi. org/10. 5281/zenodo. 5180640 (Wu,   2021). The source code of the SWAN model is freely available from http://swanmodel. sourceforge. net/. The source code of the WCCM model is available from https://doi. org/10. 5281/zenodo. 5181451 (Wu and Qin, 2021)  with restricted access because of the copyright protection. The access of the source code of the WCCM model is granted by first author or corresponding author. Alternatively, a frozen version of the code of the WCCM model with the configurations, inputs and outputs of the model as used in this paper is freely archived from https://doi.
org/10. 5281/zenodo. 5181754 (Wu    and Qin, 2021). The dataset of measured water level and current is available from https://doi. org/10. 5281/zenodo. 5184459 (Hu and Wu,   2021)  with restricted access. The access of the dataset is granted by first author or corresponding author. The other datasets used in this paper are included in the simulated episodes on zenodo (e. g. https://doi. org/10. 5281/zenodo. 5180640).
pathways of NAFLD, including the lanosterol synthase gene (LSS) associated with glutathione peroxidase activity (Gpx) levels, the mitochondrial pyruvate carrier-1 gene (MPC1) and the sphingolipid transporter-1 gene (SPNS1) associated with hemoglobin levels, the transforming growth factor-beta-induced gene (TGFBI) and the micro-RNA 129-1 (MIR129-1) associated with IL-6 and the granzyme B gene (GZMB) associated with IL-10 levels. Within the MAST4HEALTH randomized clinical trial (NCT03135873, www. clinicaltrials. gov) Mastiha supplementation improved the TAS levels among NAFLD patients with severe obesity. We identified several novel genome-wide significant nutrigenetic interactions, influencing the antioxidant and inflammatory status in NAFLD.
Genome-wide genetic data was also obtained from all participants, to investigate gene-by-Mastiha interactions. NAFLD patients with severe obesity (BMI > 35kg/m 2 ) taking the Mastiha had significantly higher total antioxidant status (TAS) compared to the corresponding placebo group (P value=0. 008). We did not observe any other significant change in the investigated biomarkers as a result of Mastiha supplementation alone. We identified several novel gene-by-Mastiha interaction associations with levels of cytokines and antioxidant biomarkers. Some of the identified genetic loci are implicated in the pathological.
Genotyping and Imputation Samples were genotyped on the Illumina GSA microarray at the Queen Mary University of London Genome Centre. Standard quality control (QC) procedures (variants call rate < 98%, Hardy Weinberg Equilibrium (HWE) p-value < 10 -6 ) were applied to exclude poorly genotyped variants. The final dataset comprised of 95 samples and 661,221 variants. Principal component analysis was performed on the genotyping dataset and the first 5 principal components (PCs) were retained for use in downstream analysis. Imputation to the HRC (Haplotype Reference Consortium) and 1000 Genome panels was performed on the Michigan server  (26). Standard post-imputation QC was applied, all monomorphic and badly imputed variants (INFO<0. 4) were removed and the two imputation datasets were merged.
We additionally stratified our samples into two categories based on their baseline BMI levels: Class I obesity (BMI≤ 35 kg/m 2 , n=65) and Class II or III obesity (BMI> 35 kg/ m 2 , n=33), as we have previously done  (23). All ANCOVA models were implemented in R; adjusted means of selected outcomes were calculated via the "lsmeans" package in R. Due to the high correlation among the investigated outcomes, we only considered multiple testing for the 3 model analysis and therefore report significance at P value ≤ 0. 016. For the gene-by-Mastiha interaction analysis, we first applied a linear regression model per outcome and adjusted for the corresponding baseline levels of each biomarker, age, sex, center and the first 5 genetic principal components. We obtained the residuals from each of these linear regression models and scaled them (mean=0, SD=1), before using them as the dependent variable in the gene-by-Mastiha interaction analysis.
For each outcome residuals, we performed a genome-wide interaction scan with the GxEScan software  (27). Each genetic variant was tested for interaction with the trial group (coded as 1 for the Mastiha group and 0 for the placebo) using the equation: Y= b 0 + b G G + b E E + b GxE GxE + ϵ. We tested the null hypothesis b GxE =0. We excluded interaction association results with <30 samples, a minor allele count <10 and implausible interaction effect sizes (b GxE GxE ≥ 4). We report significant interactions at a genomewide significance level (P value ≤ 5e-08). The index variant per locus was defined at a 500kb window and was annotated with the nearest gene using BioMart from ENSEMBL. Based on power calculations, we had 80% statistical power to detect a minimum effect size difference (effect size=difference in means/pooled SD), between the two treatment groups at the end of the trial, of 0.
Baseline Characteristics Ninety-eight patients were randomized to take Mastiha (n=41) or placebo (n=57) for 6 months (CONSORT FLOW DIAGRAM in Data Sheet 1). Out of the 98 volunteers in the MAST4HEALTH trial (NCT03135873)  (23) , 87 (88. 8%) completed the intervention. Baseline characteristics are presented in Table  1. We observed nominally significant differences between the two groups at baseline for circulating IL-1a, IL-2, IL-4, and TNF-a (Table  1 ).
ETHICS STATEMENT FUNDING This project received funding from the European Union's Horizon 2020 research and innovation program MAST4HEALTH under the Marie Skłodowska-Curie grant agreement no 691042. SV-S was supported partly by Agence Nationale de la Recherche, programme d'Investissements d'avenir (PIA), grant number ANR-15RHU-0004 and GEENAGE project (Functional Genomic, Epigenomic and ENvironment interplay to IMPACT management of healthy and pathological AGEing)" within the frames of the French PIA project "Lorraine Universitéd'Excellence"-LUE, reference ANR-15-IDEX-04-LUE. PD: This work was part of the research themes contributing to the translational research portfolios of the Barts Biomedical Research Centre funded by the UK National Institute for Health Research (NIHR).
ACKNOWLEDGMENTS We are grateful to patients for participating in this clinical trial and to all researchers involved in the study. More specifically, from  UNS :  Iva Barjaktarevic ,  Mladen Bjelan ,  Stefan Stojanoski  and  Bojan Vukovićand  from  CNR :  Elisabetta Spagnolo ,  Cinzia Dellanoce ,  Marina Parolini ,  Luca Belli  and  Angelo Vanzulli.
The India craton hence nearly "pins" the India plate, such that its northern part moves in the opposite direction to the plume-induced push. Computation assumes torque balance between plume push and shearing over asthenosphere; frictional resistance at plate boundaries is neglected and computed convergence of several hundred km at the northern end of the plate boundary is a maximum estimate. Ten degree grid spacing; locations of plates, lithosphere thickness and the plume are reconstructed in a slab-fitted mantle reference frame  45. Methods: Kinematic reconstruction -The kinematic restoration of Neotethyan intraoceanic subduction was made in GPlates plate reconstruction software (www. gplates. org)  51. First, we systematically restored stable plates using marine geophysical data from the Atlantic and Indian Ocean, and then restored continental margin deformation that occurred following the arrival of continental lithosphere below the oceanic lithosphere preserved as ophiolites.
Acknowledgments: DJJvH, MM, DG, AP, and  ELA  were funded through  European Research Council Starting Grant 306810 (SINK)  to  DJJvH. DJJvH , KP and PJMcP were funded through  Netherlands Organization for Scientific Research (NWO) Vidi  grant  864. 11. 004  to  DJJvH. DJJvH  acknowledges  Netherlands Organization for Scientific Research (NWO)   Vici grant   865. 17. 001. BS and CGa received funding from the  Research Council of Norway through its Centres of Excellence funding scheme , project number  223272. BS received additional funding from the  innovation pool of the Helmholtz Association  through the " Advanced Earth System Modelling Capacity (ESM )" activity. CG was funded through  Discovery Grant  ( RGPIN-2014-05681 ) from the  National Science and Engineering Research Council of Canada.
Both the chi 2 test statistical analysis and hypergeometric analysis with Benjamini-Hochberg correction were used to test the hypothesis that teleost genes that are orthologs of human MA and HI genes remained more in duplicate than the whole genome. All the statistical tests conducted in our study were performed in R. Moreover, the Panther database (http://www. pantherdb. org/) was used to study the gene ontology of teleost genes that are orthologs to human HI genes, and Fisher's test with Benjamini-Hochberg correction was used to classify genes according to the family.
The specific structure of the LSTM model which consists of a LSTM input layer, a hidden layers with 200 neurons, and an output layer comprising four neurons applied to obtain R, is shown in Table  1. In this Lorenz twin experiment, two LSTM networks, respectively named as LSTM1000 and LSTM200 are designed with different input size of times series data. LSTM1000 is trained on a total of 1000 time steps for predicting the R matrix while LSTM200 makes use of only the first 200 time steps to simulate a realistic application where the time-invariant R matrix is estimated using historical data for improving future DA performance. The evaluation of both LSTM1000 and LSTM200, in terms of DA accuracy, is made using the full test dataset with 1000 times steps. By leveraging the LSTM model along with available observations, we can still perform DA algorithms even though R is not explicitly given.
) with the same range of parameters Φ R as for the LSTM training. Fig. 5  shows the elements of the estimated R matrix (i. e. ,r 0 , r 1 , r 2 and v R ) obtained by LSTM1000 and LSTM200, both trained on 103486 Lorenz system observation samples, and predicts on a test dataset of 10000 samples. The result of the D05 approach, with a calibration of r 0 , r 1 , r 2 and v R against the true value, has also been displayed in Fig. 5 (i-l ) in the same test dataset for comparison purposes. The blue circles are the LSTM/D05 prediction results, while the red line is the true value of the corresponding parameter. We observe that both LSTM1000 and LSTM200 prediction results fit very well to the predefined true value of each parameter, compared to the D05 tuning approach, especially for the error amplitude v R which is of most importance in covariance specification.
Based on these experimental results, we can conclude that the proposed LSTM approach is capable of predicting the observation matrix, in terms of both correlation coefficients and error amplitude, when time series observation data y t k are given. Fig. 6  and Table  2  illustrate the averaged DA performance along with R attained in different ways with 10000 observations in the test dataset. We remind that for each observation sample {y t k }, t k ∈ {0, • • • , t T }, 100 background trajectories are generated to perform EnDA. Among these algorithms, DI01 uses two iterations to correct the magnitudes of B and R by conforming to Eq. 15. Each D05 iteration calculates the innovation quantities (y -H(x a )) and (y -H(x b )) every 10 time steps through a DA procedure, and then applies Eq. 20 to attain the updated R for the corresponding Lorenz system.
Results Fig. 9  and Fig. 10  illustrate respectively the predictions results of LSTM1000 and LSTM200 against the true value on 10000 test examples in the test dataset, which demonstrate that the trained LSTM exhibits a good performance at predicting related values applied to compose R, including both marginal error variances (i. e. , the elements of the D vector) and the correlation scale length r. The prediction results of LSTM200 (Fig. 10 ) are almost as accurate as the ones obtained via LSTM1000 (Fig. 9 ). Training and evaluating the LSTM network using the first 200 time steps is sufficient to obtain an accurate estimation of the R matrix. The so composed R matrices, based on the prediction results from LSTM1000, are shown in Fig. 11  in comparison with the true R matrix and that obtained via D05( q = 3) after regularization.
In order to estimate the high dimensional R matrix in this application, D05 makes use of the DA residuals every 10 time steps, which is different from the final DA algorithm, in each of the three iterations. Four different sample R matrices in the test dataset are displayed in Fig. 11. We observe that both LSTM and D05 manage to acquire a similar covariance structure as the true R matrix while the considerable advantage of the LSTM approach can still be noticed. These results confirm the finding of Fig. 9  and Fig. 10  that LSTM can perform well in the parametric prediction of the R matrix even in high dimensional systems. To assess the performance of DA accuracy, the metric mse,(i) (cf. , Eq. 38) estimated using a set of 53 observation time series, is displayed in Table  4. Since it would take too much space to display the total mse,(i) i=0,1,••• ,800 of all state variables, we select only some of them demonstrated in Table  4 , together with the averaged value ¯ mse of all 800 cell coordinates in the field of u and v.