dataesr/scientific-paragraphs-categorization huggingface dataset:
Review methodology The current paper reviews the available recent advances in the therapeutic potential, the molecular mechanisms of action and the signaling pathways of emodin. The PubMed/Medline, Scopus, Google scholar, TRIP database, Springer link, Wiley and SciFinder databases were chosen for the collection of articles published in English using the next MeSH terms: "Emodin/metabolism", "Emodin/pharmacology", "Humans", "Models, Biological", "Mutagens/metabolism", "Mutagens/ pharmacology", "Oxidation-Reduction", "Animals", "Apoptosis". In vitro and in vivo pharmacological studies were screened and subsequent studies from the year 2014 to January 2021 have been collected. Inclusion criteria: preclinical experimental studies were included that analyzed data on the bioavailability, pharmacokinetics of emodin, and molecular mechanisms of action, regarding the most important antioxidant, anti-inflammatory, neuroprotective and anticancer/chemoprotective effects.
Emodin in clinical trials One of the main problems of plant-derived bioactive compounds is that although there is much in vitro or preclinical evidence of their therapeutic potential, clinical trials are scarce or give inconclusive results. The case of emodin is not an exception, and to date, there are practically no studies in humans that validate the results observed in other types of studies. A clinical trial (NCT00801268) was designed to investigate the efficacy of Tripterygium wilfordii Hook. f. extract (60 mg/d) using emodin (100 mg/d) as an active comparator for autosomal dominant polycystic kidney disease (ADPKD). However, although the study began in 2008, to date there are no data available on the results obtained. The only preliminary data are those of an uncontrolled trial, where 9 proteinuric ADPKD patients were treated with T.
wilfordii for 6 months  [145]. The results evidenced that the treatment stabilized kidney function and reduced proteinuria. In a second clinical trial (ChiCTR-TRC-14004653) the effects of emodin were investigated against peripheral blood neutrophil apoptosis in patients with acute pancreatitis. As in the previous study, there are no published data on the results obtained. On the other hand, several studies have analyzed the possible effects of various plant extracts rich in emodin, but as they have a complex composition, they do not allow us to determine whether the results obtained are derived from emodin or surely, from the combination of the different bioactive compounds  [146, 147].
J. S. -R. contributed to designing the review. J. H. -B. , S. K. , K. P. , A. P. M. , M. M. -M. , D. S. A. , Z. Y. , A. Y. , contributed to collecting the paper from online databases. J. S. -R. , A. S. , M. M. , C. H. , D. C. , W. C. C. contributed to writing, editing, and revising the manuscript. J. S. -R. , W. C. C, C. H. , A. S. , and D. C. made the revision and final edits on the manuscript. J. S-R, C. H. , D. C. supervision. All the authors read and approved the final version of the manuscript.
Since in France, national regulation mandates that school canteens serve a weekly vegetarian meal to reduce school canteens' environmental impact in addition to previous regulations imposing nutritional composition guidelines. However, a lunch without meat is often perceived as inadequate to cover the nutritional needs of children. The present study aims to assess the nutritional quality and greenhouse gas emissions (GHGE) of vegetarian and non-vegetarian school meals served in primary schools in Dijon, France. The catering department provided the composition of meals served in. Nutritional content and GHGE were retrieved from national food databases. The portion size of each meal component was the standard portion size recommended by the relevant French authority (GEMRCN). Meals were classified into vegetarian meals, i.
The view that "a meal without meat is not a real meal" also seems to be widely shared among school catering actors. It also raises the question of potential degradation of nutritional quality, as suggested by Vieux et al. (16) , although nutrient profiling methods have shown that vegetarian and nonvegetarian main dishes offered in primary schools in France were generally of good nutritional quality  (22). In addition, a recent simulation study based on a database of 2,316 school dishes demonstrated that the best trade-off for decreasing the environmental impacts of school meals without altering their nutritional quality was a frequency of 12 vegetarian meals over a total of 20 meals  (23). Reduction of meat consumption in school canteens is key to building more environmentally friendly food systems, but evidence based on the analysis of school meals from real life is still needed to convince catering actors, parents and children of the nutritional quality of vegetarian meals.
Data collection and database information This study focused on meals served in 2019 (January to December) to children in primary schools in Dijon, France (n = 249). In this context, school meals delivery is organized by the municipality service. The central kitchen of Dijon produces and serves 4,000 meals every day to children aged 6 to 11 years (plus 4,000 for preschool aged children and municipality staff) distributed among the 38 primary school canteens  (24). Meals were developed by a dietician and respected the GEMRCN frequencies. The central kitchen provided the list of the food items included in each dish analyzed in this study. An example of a meal series for 1 month is available in the Supplementary Table  S1. Three databases were created from the collected information: the meal database, the dish database and the recipe database (data are available here: https://osf.
io/fk7cq/). The meal database contained the 249 meals served in 2019 corresponding to five meals served per week (excluding weekend) during the school period and school holidays. A meal was composed of five or four components, among a starter, protein dish, side dish (e. g. , fries, starches, vegetables or legumes), dairy product, and dessert, with a 30-or 40-g portion of bread. Meals were split into two main categories: vegetarian (n = 66, all components without meat or fish) and non-vegetarian (n = 183). The dish database contained 434 distinct dishes, including 65 starters, 129 protein dishes, 60 sides, 69 dairy products and 71 desserts. Each dish had a name and a code. All http://www. dijon. fr/Dijon-au-quotidien/Enfance-petite-enfance/ Cantine-Inscription dishes were classified as vegetarian (without meat or fish) or non-vegetarian.
Moreover, the meals were categorized based on the subcategory of the protein dishes. Five different subcategories were defined based on their level of GHGE  (25) , from the most to the least emitting: beef, veal and lamb; pork and poultry; fish; eggs and/or cheese; and vegan (i. e. , plant-based foods only). Each dish was composed of one of several food items (e. g. , pork and curry sauce, eggs and mayonnaise). The 433 food items were included in the recipe database and identified by a name and a code. The portion size of each food item (in grams) was established by the central kitchen and closely related to the GEMRCN recommendations for primary school children  (15). All food items had an edible portion equal to one except for melon (0. 7), banana (0. 8), clementine (0. 7), tangerine (0.
7), orange (0. 8) and chicken thigh (0. 8). The nutritional composition of each food item was estimated using two French food nutrient composition reference tables: CIQUAL 2020 and CALNUT 2020  (26). The GHGE (in kilograms of CO 2 equivalent) of each food item was based on the AGRIBALYSE v3. 0 table providing reference data on the environmental impacts of agricultural and food products obtained through life cycle analysis, comprising the following contributions to GHGE: agriculture, transport and packaging  (27). Interoperability between the CIQUAL and AGRIBALYSE databases (same food products with same coding system) makes it possible to record both nutritional and environmental footprint information. A dietician performed the pairing of each food item from the central kitchen with items from these two databases.
Description of school meal nutritional quality and environmental impact Data from 249 meals were considered for the present analysis. The average weight of a meal was 464 g (SD 64), and the average energy content was 659 kcal (SD 125) representing 33% of the recommended daily energy intake for children aged 6 to 11 years old (i. e. , 2,000 kcal). The average greenhouse gas emissions (GHGE) of a meal was 1. 8 kgCO 2 eq (SD 1. 0). The.
Strengths and limitations The present study has several limitations. First, we used nutritional and environmental indicators from CIQUAL, CALNUT and AGRIBALYSE databases that include values on average food items. We evaluated meal environmental impact based on GHGE but we did not use other indicators such as eutrophication, acidification, toxicity, biodiversity which may encompass other important impacts on our planet. Moreover, one must note that AGRIBALYSE database did not provide a distinction between organic and conventional food items, although their impacts may differ. For nutritional evaluation, we did not consider actual food items composition but average food items composition from the French reference databases. Nutrient content may vary especially for salt and fat depending on culinary practices.
This study has several strengths. First, it was based on a unique database of meals served in one primary school canteen system during a one-year period. For the first time, the nutritional quality and GHGE were conjointly estimated for actual meals within one system. Based on the availability of yearly data, further studies could examine the evolution of nutritional quality and GHGE over several periods or seasons throughout the year or over several years. More globally, in the context of a current initiative of the Dijon catering system toward more sustainable food systems, these data provide a baseline estimation to follow the evolution of Dijon school catering during the coming years. Moreover, integrating other indicators reflecting other dimensions of sustainable food systems  (48)  such as attendance at school canteens, food waste, meal cost and children's liking of meals, could provide a holistic view to go toward more sustainable school meals.
Funding This research was funded by a grant to SN (Danone International Prize on Alimentation 2018, grant #DA20180125001), a grant from the Dijon Municipality in the frame of the Dijon Alimentation Durable 2030 initiative (grant #00006226-29dmact11), which supported the PhD fellowship of JD, and a grant of the Caisse des dépôts et consignations through the Territoires d'innovation funding scheme (grant #00005065). Funders were not involved in the data analysis plan.
Acknowledgments We are thankful to  Bertrand Llorente  for critical reading of the manuscript and thoughtful suggestions. This work was supported by the  European Research Council  ( ERC Consolidator Grant   772505 ). This work is also part of the  Interdisciplinary Thematic Institute IMCBio , as part of the  ITI 2021-2028 program  of the  University of Strasbourg ,  CNRS  and  Inserm , supported by  IdEx Unistra  ( ANR-10-IDEX-0002 ), and  EUR  (IMCBio  ANR-18-EUR-0016 ) under the framework of the  French Investments for the Future Program. J. S. is a Fellow of the  University of Strasbourg Institute for Advanced Study (USIAS)  and a member of the  Institut Universitaire de France.
UNIPROT (http://www. uniprot. org/) is used as reference for protein information in addition to literature. a Protein sizes are given in kDa and for full proteins, i. e. including the transit peptide for mitochondrial and chloroplastic MP (truncated for heterologous expression); b The number of TM helices listed here has either already been demonstrated or predicted with software (such as TNHMM or psipred) with the FASTA sequence published in Uniprot. Tables 2, 3 and 4 display respectively non-exhaustive lists of prokaryotic MPs (homologous or heterologous expression) and of eukaryotic MPs expressed in L. lactis with the NICE system. They include studies of functionally active proteins in which expression yields were not determined. The tables do not display, for some proteins, the percentage of expressed proteins when not available, and of functional proteins out of the proteins expressed; indeed, this information is seldom reported since such a ratio is difficult to measure and necessitates isolating native proteins as controls.
Microarray and data analysis The microarray was performed as previously described  [26]  with data submitted to NCBI's Gene Expression Omnibus (GEO series accession number GSE112086). Briefly, RNAs were extracted using an RNeasy Mini Kit (QIAGEN SA, France) with a DNase I step, then labeled using Cyanin-3 CTP (Agilent Technologies) and hybridized on chips containing 45000 probes (4x44K Whole Human Genome). After hybridization, slides were washed and scanned with a pixel size of 5 μm using the DNA Microarray scanner G2505C. The raw data were extracted (Extraction Software 10. 5. 1) and processed using GeneSpring GX 14. 9 software (Agilent Technologies). A selection filter of both statistical value p<0. 01 (t-Student test) and an absolute value of fold change (FC) greater than 1. 5 was used to identify differentially expressed genes.
Statistical analysis The statistical analyses of the data were performed using GraphPad-Prism software (version 6. 0). The results are presented as the ± standard error of the mean (SEM). The Mann-Whitney U test was used for flow cytometry, the two-way ANOVA test for E-cadherin quantification and transcriptional analysis, and a nonparametric Kruskal-Wallis with Dunn's multiple comparison test for group comparison. A p value <0. 05 was considered statistically significant.
Previously published RNA-Seq data for L4  [62]  genomes were used to perform combined analysis. Datasets are available in ArrayExpress (https://www. ebi. ac. uk/arra yexpress/) with the following accession numbers: E-MTAB-6540 for L4 RNA-Seq; E-MATB-10686 for Sf9 RNA-Seq and E-MTAB-10721 for ChIP-Seq experiments.
H3K9me2 ChIP-Seq analysis Raw reads from fastq files have been filtered using cutadapt software which trims remaining adapters, low quality (phredscore <35) and short length sequences (<40 nt). Corresponding samples alignments were performed using stringent parameters with Bowtie2 (--endtoend -verysensitive,  [38] ) against Sf9  [57]  and L4 genomes  [55]. We next divided the genomes into bins of 50 bp so Deeptools software  [66]  could predicts the aligned reads abundance associated to each of them using -bamCoverage option. Bigwig files similarity was measured using Deeptools -bigwigcorrelate option. A Pearson correlation was calculated for each compared condition (e. g Sf9 ChIP-seq replicate n • 1 against Sf9 ChIP-seq replicate n • 2, Sf9 input replicates n • 1 against Sf9 ChIP-seq replicate n • 1 etc.
, see Supplementary Fig. S3 ). Samtools software allows the reading of SAM files and their concatenation  [42]. We merged replicates corresponding the Sf9 ChIPseq experimental condition to obtain one file for all reads sequenced. Same procedure was applied to Sf9 inputs replicates, L4 ChIP-seq replicates and L4 input. H3K9me2 whole genome peak detection has been assessed with MACS2 callpeak using the following parameters: -broadpeak -f BAM -g 340000000 -n -down-sample (Y. [97] ). Here, MACS2 algorithm predicts large histone peaks detection using a statistical Poisson distribution. Peaks were annotated using Bedtools software (--intersect) after functional annotation of genomic elements. More specifically, the correspondance of H3K9me2 peaks (listed in a Bed files) with the annotation of functional elements (also listed in a Bedfile) was achieved using Bedtools -intersect option.
Genome functional element annotation We used published S. frugiperda transcriptome  [41]  for Sf9 and L4 gene annotations using Scipio software  [33]. It predicts gene exons by detecting intron/exon junctions with the BLAT algorithm. CDS were reconstructed using Bedtools -groupby function. Introns were annotated by subtracting CDS-exons positions (Bedtools -subtract). RNA-Seq data were filtered, concatenated et aligned on the genome with the same methods as described for H3K9me2 ChIP-Seq samples. Expression analysis has been performed with Stringtie software (  [63] ; parameter: stringtie 'bam files' -G genereference. gtf -e). Output in transcript per millions (TPM) was converted to log2 to determine active pool genes (log2(TPM) > 1) from inactive ones (log2(TPM) ≤1). Annotation of UTRs in each genome assembly was inconsistent between the different software used (such as Maker, exUTR, getUTR or KLEAT).
H3K9me2 genome-wide distribution in Sf9 and L4 genomes To investigate the presumptive genome-wide localization of Raw, filtered reads and their alignments using Bowtie 2 Software. S. Nhim et al. heterochromatin and its dynamic in S. frugiperda, we performed ChIP-Seq experiments against the H3K9me2 chromatin mark in Sf9 cells as well as in L4 caterpillars. We first tested the specificity of the mouse anti-H3K9me2 antibody (ab:1220) by immunofluorescence experiments in Sf9 cells. We observed a strong nuclear signal that disappears during metaphase (Supplementary Fig. 1 ). This is a well-known characteristic of this mark, which is usually shielded by Histone H3 Serine 10 Phosphorylation during mitosis  [15, 30, 64]. We also performed western-blot on chromatin samples showing a 17 kDa band corresponding to the mark in both samples (Supplementary Fig.
Introduction Peatlands store a disproportionate amount of the global terrestrial carbon (C), covering approximately 3% of the earth's surface yet accounting for between 15 and 30% of the world's soil C stock  [1, 2]. Around 80% of the peatlands are in temperate-cold climates in the northern hemisphere. The remaining peatlands are mostly found in tropical-subtropical climates, including south-east Asia  [3] [4] [5] , central Africa  [6] , and South America  [7, 8]. Nonetheless peatlands are still often dramatically underrepresented in efforts towards comprehensive global soil databases  [9] [10] [11]. This is likely due to both a lack of measurements taken to describe organic soil properties compared with mineral soils, as well as under-sampling of peatlands in remote regions. Peatland C stocks have been most widely estimated for northern peatlands, with Gorham's  [1]  estimate of 455 Gt C being the most widely accepted value.
Statistical analysis Linear mixed models were used to examine patterns of C, N, C:N, OM, and C:OM among peatland habitats, utilizing R 3. 5. 2 [34]. Models for each response variable included depth in the peat profile, peatland type, and a peatland type x depth interaction as fixed effects. Each model also included individual peat core, 1 km diameter and 100 km diameter spatial clusters as random intercept effects, to account for samples from the same core, wetland or region being less independent from each other than samples from much more distant locations. Spatial clusters were generated with the leaderCluster package  [35] , using latitude and longitude coordinates for the coring locations. Our aim was to conduct large-scale comparisons among broad peatland classes, using a specific depth increment within an individual core as the fundamental sampling unit; therefore, defining individual cores, and the spatial clusters as random effects helped statistically control for local-scale variation in unmeasured factors, and controlled for differences in coring methods and sampling location selection approaches among collaborators, that are not of interest to our inference.
Models were fit with the lmerTest package  [36] , and fixed effects were tested with F-tests utilizing the Kenward-Roger approximation. Partial R 2 values for each fixed effect were obtained with the package r2glmm  [37]. Post-hoc comparisons were performed in emmeans  [38]. For each variable, each model was run with two different subsets of the data, including: 1) all cores in the data set containing data from the 10-20 and 30-40 cm depths (N = 958 samples, 479 cores), and 2) all cores in the data set with data from all three depths (10-20, 30-40, and 60-70 cm; N = 1062 samples, 354 cores).
Conclusions We established six broad peatland categories, consisting of ombrotrophic tropical peat swamps, minerotrophic tropical peat swamps, bogs, poor fens, intermediate fens, and extremely rich fens, that fell along an increasing pH gradient and were sampled in 24 countries across six continents. Peat C, N and OM values were relatively consistent within each category but varied considerably among the six peatland categories. Peat C concentrations were highest in bogs, poor fens and tropical peat swamps, while N concentrations were highest in minerotrophic peat swamps and intermediate fens. The C:OM ratio exhibited less variation among peatland category suggesting that differences in mineral content were largely responsible for differences in C concentration among peatlands. Peat C and C:N ratios in our data set followed a predictable pattern among broadly classified peatland categories, and data sets such as these may be used to better constrain global assessments of peat C and N in surface peat, especially when coupled with improved land cover classification.
76 (5, 113. 6) <0. 0001 5. 94 (5, 92. 9) <0. 0001 Depth 2. 28 (1, 430) 0. 1317 4. 34 (2, 696) 0. 0133 Peatland type X Depth 2. 77 (5, 430) 0. 0178 1. 14 (10, 696) 0. 3324 Carbon: Organic matter Peatland type 1. 06 (5, 60. 7) 0. 3917 2. 91 (5, 68. 8) 0. 0194 Depth 0. 01 (1, 430) 0. 9030 4. 05 (2, 696) 0. 0178 Peatland type X Depth 0. 76 (5, 430) 0. 5808 1. 10 (10, 696) 0. 3558 a Analyses were run on two versions of the dataset: 10-20/30-40 cm unfiltered = 10-20 and 30-40cm samples from all cores, 10-20/30-40/60-70 cm unfiltered = 10-20, 30-40, 60-70cm samples from cores containing all three depths. b All models also contained the random effects Core, 1km diameter spatial cluster and 100km diameter spatial clusters, but no hypothesis test was applied these variables. Peatland type = ombrotrophic peat swamp, minerotrophic peat swamp, bog, poor fen, intermediate to moderate rich fen, extremely rich fen.
The bacterial suspension was centrifuged for 10 min at 7,500 rpm and the pellet was homogenized in 180 l of ATL buffer (Qiagen). Bacterial DNA was extracted and purified with the Blood & Tissue kit (Qiagen) following the manufacturer's instructions. The entire 16S region was amplified by PCR and sequenced by Sanger sequencing as previously described  (Dickson et al. , 2017). Sequencing chromatograms were manually examined and assigned taxonomically at the genus level by BLAST alignment to the GenBank database (http://www. ncbi. nlm. nih. gov/BLAST).
Differential gene expression All analyses of transcript abundance were performed using R version 3. 6. 1 (R Core Team, 2014) and the Bioconductor package DESeq2 version 1. 24. 0  (Love, Huber, & Anders, 2014). Normalization and dispersion estimation were performed with DESeq2 using the default parameters and statistical tests for differential expression were performed applying the independent filtering algorithm. Differential expression between treatments for larval, pupal and adult stages was tested with a generalized linear model. For each pairwise comparison, raw p values were adjusted for multiple testing according to the Benjamini and Hochberg procedure  (Benjamini & Hochberg, 1995). Genes with both an absolute log 2 -transformed fold-change (log2FC) >1 and an adjusted p value <0. 05 were considered significantly differentially expressed.