dataesr/scientific-paragraphs-categorization huggingface dataset:
The effects included in the final model are indicated by f. Significant effects are in bold. Sample sizes for the whole dataset are 87 observations, 71 pairs. Sample sizes for the restricted dataset are 54 observations, 47 pairs. The effects included in the final model are indicated by f. Significant effects are in bold. Analyses were performed on 69 pairs. Reference habitat is forest interiors. Increases in elevation coincide with changes in many critical ecological variables and, as a result, elevational gradients have been used to better understand the effects of ecology on parental care. Cooler temperatures, shorter breeding seasons and lower food availability at high altitude are often associated with lower annual fecundity  (Badyaev, 1997; Sandercock et al. , 2005; Bears et al. , 2008; Boyle et al.
ACKNOWLEDGMENTS We are very grateful to the following interns for helping with data collection field and from video recordings:  Amandine Sieper ,  Kilian David ,  Laurie Abou-Cajal ,  Aourell Lanfrey , Kiara L'herpinière,  Meidhi Khelifi ,  Baptiste Averly ,  Louis Bliard ,  Maeliss Hoarau ,  Virginie Mercier ,  Shirley Laurent ,  Aurélie Nouri ,  Sebastian Bekker ,  Purabi Deshpande ,  Christel Blot ,  Pauline Clin ,  Quentin Carbonnier ,  Clément Rul ,  Robin Bhattacharyya-Dickson ,  Madeleine Barr ,  Manon Broadribb ,  Amy Gresham ,  Ben Murphy ,  Sophie Porta ,  Solenn Auquiére ,  Nils Serventis ,  Camille Paillard ,  Lauréne Michel ,  Émeline Garnier ,  Jessica Mulvey ,  Murielle Vergniol ,  Benjamin Begou ,  Thomas Vulvin , and  Noé Rehspringer. We would like to thank the two reviewers  Kat Bebbington  and  Amelie Fargevieille  for their comments and suggestions that greatly improved the quality of this manuscript.
FUNDING This work was supported by The  Region Midi-Pyrenees  grants to AC and AR, a  MESR  ( Ministére de l'Enseignement supérieur et de la Recherche ) Ph. D. scholarship to LL, fellowship grants from the  Région Midi-Pyrénées  and the  Centre national de la Recherche  scientifique and a  Natural Environment Research Council  to the  University of Exeter  to AB, an  IRC Government of Ireland Postdoctoral Fellowship and Ulysses  grant to  JS , and  ANR-JCJC Net-Select  and  HFSP RGP0006/2015  grants to AC. This work was supported by the  Laboratoire d'Excellence (LABEX)   TULIP  ( ANR-10-LABX-41 ) and  IAST  through  ANR  grant  ANR-17-EURE-0010  ( Investissements d'Avenir program ).
Acknowledgements We thank  Dr Emilie Bouissou , Obstetrician at  CHT-Medipole, New Caledonia ,  Dr Susan Jacobs , Obstetrician,  Dr Bruce Adendorff ,  Anaesthetist , and  Dr Matthew Bayfield ,  Cardiothoracic Surgeon  at  Royal Prince Alfred Hospital in Sydney. Slide sets: A fully edited slide set detailing this case and suitable for local presentation is available online as Supplementary data. Consent: The author/s confirm that written consent for submission and publication of this case report including image(s) and associated text has been obtained from the patient in line with COPE guidance.
Dietary exposure assessment to new constituents In line with Regulation (EU) No 503/2013 the applicant provided dietary exposure estimates to CP4 EPSPS, CSPB, NPTII, Cry1A. 105, Cry2Ab2, Vip3Aa20, and PMI proteins newly expressed in MON 87427 9 MON 87460 9 MON 89034 9 MIR162 9 NK603 maize. Dietary exposure was estimated based on protein expression levels reported in this application for the five-event stack maize treated with the intended herbicide, the current available consumption data and feed practices, the foods and feeds currently available on the market and the described processing conditions. Table  7  describes the protein expression levels used to estimate both human and animal dietary exposure. Protein Tissue/developmental stage Grains/R6 (lg/g dry weight and lg/g fresh weight) Forage/R5 (lg/g dry weight) CP4 EPSPS  (b)  15.
Human dietary exposure 29 Dietary exposure was estimated across different European countries on different population groups: young population (infants, toddlers, 'other children'), adult population (adolescents, adults, elderly and very elderly) and special populations (pregnant and lactating women). For the purpose of estimating dietary exposure, the levels of newly expressed proteins in MON 87427 9 MON 87460 9 MON 89034 9 MIR162 9 NK603 maize grains were derived from replicated field trials (four replicates from five locations) in the 2014 US growing season. Mean values (fresh weight) are considered as the most adequate to estimate dietary exposure (see Table  7 ). Since no specific consumption data were available on commodities containing, consisting of or obtained from MON 87427 9 MON 87460 9 MON 89034 9 MIR162 9 NK603 maize grains, a conservative scenario with 100% replacement of conventional maize by the GM maize was considered.
Consumption figures for all relevant commodities (e. g. corn flakes, sweet corn, popcorn, etc. ) were retrieved from the EFSA Comprehensive European Food Consumption Database (EFSA consumption database). 30 Maize oil was excluded from the assessment since no proteins are expected to be present in the oil. For the acute dietary exposure estimations, the applicant assigned to the processed commodities the mean value reported for the newly expressed proteins in maize grains. This is a conservative approach as neither recipes nor the effect of processing is considered on the final concentration of newly expressed proteins. Summary statistics from the EFSA consumption database were used. 31 cute dietary exposure in high consumers within each dietary survey and age class was estimated by summing the exposure derived from the 95th percentile consumption for the dominant food commodity  32  among consumers only and those exposures derived from the mean consumption of the remaining food categories in the total population (EFSA, 2015).
3. 5. Risk assessment of the subcombinations 37 Subcombinations previously assessed in the frame of other applications are discussed in Section 3. 5. 1. The strategy followed for the subcombinations that have not been previously assessed (Section 3. 5. 2) has been described by the GMO Panel. 38 In this case, the risk assessment takes as its starting point the assessment of the single maize events, and uses the data generated for the five-event stack as well as all the additional data available on subcombinations previously assessed by the GMO Panel (Table  2 ).
4. 1. 3 and Appendix A). Therefore, there was no indication of an interaction at protein expression level. In addition, expression data from the two-event stack maize MON 89034 9 NK603 (EFSA GMO Panel, 2009), the three-event stack MON 87427 9 MON 89034 9 NK603 (EFSA GMO Panel, 2017a) and the four-event stack MON 87427 9 MON 89034 9 MIR162 9 NK603 (EFSA GMO Panel, 2019) were similar to those observed in each of the single maize events or showed in general the expected higher levels for CP4 EPSPS. This supports the conclusion that interactions affecting the expression levels of the newly expressed proteins are not expected in the 14 subcombinations not previously assessed and included in the scope of application EFSA-GMO-NL-2016-134.
Conclusion Since no new safety concerns were identified for the previously assessed subcombinations, the GMO Panel considers that its previous conclusions on these maize subcombinations remain valid. For the remaining 14 subcombinations included in the scope of application EFSA-GMO-NL-2016-134, no experimental data have been provided. For these subcombinations, the GMO Panel assessed the possibility of interactions between the events and concluded that these combinations would not raise safety concerns. These subcombinations are therefore expected to be as safe as and nutritionally equivalent to the single maize events, the previously assessed subcombinations and the five-event stack maize.
The GMO Panel concludes that the five-event stack maize, as described in this application, is as safe as and nutritionally equivalent to its non-GM comparator and the non-GM reference varieties tested. The GMO Panel concludes that there is a very low likelihood of environmental effects resulting from the accidental release of viable grains from the five-event stack maize into the environment. Since no new data on the eleven subcombinations previously assessed that would lead to a modification of the original conclusions on their safety were identified, the GMO Panel considers that its previous conclusions on these maize stacks remain valid. For the remaining 14 subcombinations included in the scope of application EFSA-GMO-NL-2016-134, no information has been provided. The GMO Panel assessed possible interactions between the events in the 14 subcombinations, and concludes that these combinations of events MON 87427, MON 87460, MON 89034, MIR162 and NK603 would not raise safety concerns.
Highest acute dietary exposure to CP4 EPSPS, CSPB, NPTII, Cry1A. 105, Cry2Ab2, Vip3Aa20, and PMI proteins (lg/kg bw per day) estimated across European dietary surveys and different age classes. Section 2. 4. 30 http://www. efsa. europa. eu/en/data/food-consumption-data 31 Summary statistics from the EFSA Comprehensive European Food Consumption Database accessed in September 2016.
Despite the attractive properties of the lupin grain as a food source, this legume of the Genistoid clade has only recently been domesticated  [6] , with current elite cultivars having a very narrow-genetic base  [7]. Thus there is a considerable potential to improve the quality of the lupin grain and its yield. A number of genetic and genomic resources have recently been developed for narrow-leafed lupin to accelerate crop improvement. These include the generation of various BAC libraries  [8, 9] , transcriptome datasets  [10, 11] , a comprehensive reference genome  [12] , various re-sequenced cultivars  [13] , large sets of molecular markers and two dense genetic maps  [11, 14, 15]  as well as BAC-FISH cytogenetic markers assigning each linkage group to a chromosome  [16]. The generation of in depth transcriptome datasets for a number of different tissue types  [10, 11] , combined with a quality reference genome assembly  [12] , enables the investigation into the small RNA complement of narrow-leafed lupin.
The number of plant miRNAs deposited in public databases such as miRBase has increased rapidly over the last two decades  [37]. Over 20 miRNA families are conserved amongst the angiosperms with a large number of these targeting genes encoding transcription factors, which regulate important aspects of plant growth and development  [37, 38]. Plants also contain a number of lineage specific miRNAs. New miRNA genes can be formed via a number of mechanisms including the duplication of existing miRNA genes, the inverted duplication of protein coding genes or through transposable elements  [39]. Linage specific miRNAs are generally found as single copy genes, have a high birth-death rate, low expression and have few if any targets  [40]. As such, most new linage specific miRNAs are often considered to be 'transient' or evolutionary neutral  [41].
Identification of argonaute and dicer-like genes in the narrow-leafed lupin genome The lupin genome assembly (version 1. 0;  [12] ), was interrogated with sequences of Dicer-like (DCL1-4) and Argonaute genes (AGO1-10) from Arabidopsis thaliana and their predicted homologs in Medicago truncatula, L. japonicus and Glycine max described in  [42]. As an additional line of evidence, Hidden Markov Model (HMM) analysis using conserved PFam and InterPro term domains were used to search for DCL and AGO genes encoded in the annotated gene set of the narrow-leafed lupin genome. Phylogenetic trees for the DCL and AGO genes were generated using the ETE 3 software with the standard_raxml workflow  [49]. This used Clustal Omega as the aligner  [50]  and RAxML for phylogenetic tree prediction  [51]. RNA isolation, small RNA isolation and generation of small RNA sequencing libraries Total RNA was isolated from the foliar and seed tissue using Trizol reagent (Invitrogen, Carlsbad, CA) as described by  [11].
The generation of TruSeq smallRNA libraries (Illumina, San Diego, CA) was performed according to manufacturer's recommendations using the TruSeq small RNA library sample preparation kit with an input amount of 1 μg total RNA and sequenced using an Illumina MiSeq. The raw data for each of the libraries were deposited in GenBank under BioProject ID: PRJNA299755. Computational analysis of small RNAs, miRNA identification and differential expression analysis Adapters were trimmed using cutadapt (-m18 -M28 -q30 -trim-n -discard-untrimmed)  [52]. Untrimmed reads, reads shorter than 18 nts or reads larger than 28 nts were discarded and flanking N bases were removed from each read  [52]. Additional filtering was performed by removal of reads that mapped to rRNA, tRNA, and snoRNA using bowtie 1. 1.
2 [53]. For miRNA identification, we used the ShortStack 3. 8. 5 software  [54]  on the clean sRNA reads. We further filtered the predicted sRNA clusters to include only those where > = 80% of reads are within 20-24 nts of length. This is the recommended procedure in Short-Stack to avoid degradation products. We also included only sRNA clusters with at least 2 reads per million (RPM). We used the read counts returned by ShortStack for all predicted sRNA clusters and used edgeR  [55]  to assess which are differentially expressed at any of the infection stages versus germinated spores (FDR < 0. 05, fold change > 2). The conserved and novel miRNAs were aligned to the cv. Tanjil reference genome assembly with Short-Stack  [54]  and their scaffold coordinates used to place the miRNAs onto the narrow-leafed lupin pseudochromosomes and visualised using the MapChart v2.
Changes in expression profiles following gene duplication events can facilitate functional diversification, therefore we examined the expression profiles of the AGO genes using the transcriptome datasets of five narrow-leafed lupin tissue types (root, stem, leaf, flower and seed) previously described  [11]. Each of the AGO genes were expressed within the tissues examined, with a subset of LaAGO genes highly Trees were predicted using the ETE 3 software  [49]  expressed within the seed (Additional file 3: Figure  S1A ). In particular, three members of the narrow-leafed lupin LaAGO4 family (LaAGO4a, LaAGO4c and LaAGO4d) showed notably higher expression levels in the seed tissue compared to the other tissue types. LaAGO1b also exhibited notably higher expression level in the seed compared to other tissue types.
Identification of dicer-like orthologs within the lupin genome We also examined the Dicer-like gene complement within narrow-leafed lupin. Plants contain four Dicer-like (DCL) families (DCL1-4)  [63]. Here we identified seven DCL genes in the narrow-leafed lupin genome including three gene members for DCL2, two members for DCL3 and a single gene member for DCL1 and DCL4, all of which exhibited close homology to other legume DCL genes (Fig. 1a ; Additional file 3: Table  S2 ). We also examined the expression profile of the narrow-leafed lupin DCL genes using the transcriptome datasets described above (Additional file 4: Figure  S1B ). LaDCL1 and LaDCL4 were highly expressed in all tissue types examined. LaDCL2a, LaDCL2b, LaDCL2c and LaDCL3a were also highly expressed, though differences in expression levels were observed between tissue types.
Identification of conserved miRNA sequence within the small RNA datasets Identification of miRNA and small RNA sequences was undertaken using the ShortStack software  [54]. Briefly, ShortStack performs alignment of small RNA-seq data as well as annotation and quantification of small RNA-producing genes. ShortStack predicts miRNAs using a range of stringent criteria, in line with  [68]. Using ShortStack, we identified a total of 56 miRNAs within the lupin small RNA datasets, of which 43 were classified into 16 known miRNA families. 13 miRNAs did not have a hit to a known miRNA and were thus classified as novel miRNAs (Table  1 ). The predicted miRNAs were predominately 21 nt in length (73. 2%), with lower proportions of 20 nt (8. 9%) and 22 nt (12. 5%) miRNAs present within the datasets. Furthermore, 75% of the predicted miRNA sequences contained a 5′ uridine nucleotide bias in accordance with observations in A.
Identification of novel miRNA sequence within the small RNA datasets We also found evidence for a novel miRNA complement within narrow-leafed lupin, namely 13 miRNAs predicted by ShortStack that do not share significant sequence similarity with known miRNA families deposited on miRBase (Table  1 ). Of the 13 novel miRNAs, we found two to be up-regulated in seed (NovmiR12 and NovmiR13) (Fig. 3 ). The novel miRNA sequences were predominately 21 nt (61. 5%) or 22 nt (23. 1%) in length, with a higher proportion of 22 nt sequences comparatively to the conserved miRNAs (21% are 21 nt in length, 9. 3% are 22 nt in length). We also observed a 5′ uridine nucleotide bias in 53. 9% of the novel miRNA sequences. An additional class of DCL3 dependent 24 nt long miRNAs, which direct DNA methylation at target loci and also at their own loci through association with AGO4, has been described in rice  [74, 75].
miRNA target identification Putative miRNA targets were identified using the psRNATarget software and narrow-leafed lupin transcriptome datasets previously generated by our laboratory. Using stringent parameters (expectation cut-off score of 2. 5), 49 putative unique targets for the conserved miRNAs were identified (Additional file 6: Table  S4 ). Whilst some bona fide targets may not be identified by using stringent parameters, this was considered to be preferable than the inclusion of large numbers of false positive targets within our datasets. A large proportion of genes encoding for transcription factors (40. 4%) were identified as putative miRNA targets. Analysis of the InterPro terms revealed the presence of several different classes of transcription factors within our datasets including; GROWTH-REGULATING FAC-TOR (GRF) transcription factors, SBP-box transcription factors, MYB transcription factors and Zinc finger domain proteins (Additional file 6: Table  S4 ).
The remaining targets encoded proteins involved in various other cellular processes. We identified 20 unique genes that were putatively targeted by novel miRNAs (Additional file 7: Table  S5 ). We did not identify targets for five of the novel miRNAs (NovmiR03, NovmiR06, NovmiR07, NovmiR09 and NovmiR12). Only 20% of the identified targets for the novel miRNAs encoded transcription factors (MYB and BIM1 transcription factors and B3 domain-containing proteins). The remaining targets encode proteins with a diverse array of functions. Among these targets we found proteins annotated as a molybdate transporter 1, a calcium-transporting ATPase 8, a TMV resistance protein N, a lysine-specific demethylase JMJ16 and a nudix hydrolase protein (Additional file 7: Table  S5 ). The functional diversity of proteins targeted by linage Fourty three lupin miRNAs belong to a total of 16 known miRNA families and 13 novel lupin miRNAs were predicted.
Characteristics of the small RNA population throughout seed development To examine the involvement of small RNAs during seed development, we undertook a comprehensive analysis of the narrow-leafed lupin small RNA populations using Illumina Small RNA-Seq technology. At each seed developmental stage examined, the small RNA populations were mainly comprised of 24 nt sequences, with 21 nt sequences also abundant within the datasets. Similar compositions have been reported within a variety of tissues from other legumes such as M. truncatula  [85]  and chickpea  [76] , though within the developing soybean seed, each of the 21, 22 and 24 nt small RNA populations were all highly abundant  [86]. The enrichment of the 24 nt small RNA population within narrow-leafed lupin seed, is consistent with heterochromatin siRNAs, derived from transposons and repetitive genomic elements, being a major class of small RNAs within plants  [17].
Novel narrow-leafed lupin-specific miRNA complement expressed throughout narrow-leafed lupin seed development Newly evolved miRNAs, once integrated into regulatory networks, can contribute to morphological and physiological diversity within the plant, and thus represent avenues for agronomic trait improvement. As such, we were interested in examining the novel narrow-leafed lupinspecific miRNA complement throughout narrow-leafed lupin seed development. We identified a total of 13 narrow-leafed lupin specific novel miRNAs in our datasets that were between 21 and 24 nt in length. Novel miRNAs were represented by a single sequence variant and transcribed from a single genomic location, consistent with observations in other plant species  [40, 41]. According to the current model of plant miRNA evolution, newly emerged miRNA have a high turnover rate, with many miRNA being lost soon after their formation  [41].
Availability of data and materials The datasets generated and/or analysed during the current study are available in the GenBank repository, under BioProject ID: PRJNA299755, where the short read archives for the smallRNA data can be found under numbers SRX2635181-SRX2635189 (Leaf: SRX2635189; Stem: SRX2635188; Root: SRX2635187; Flower: SRX2635186; Seed 4-8DAA: SRX2635185; Seed 9-12DAA: SRX2635184; Seed 13-16DAA: SRX2635183; Seed 17-20DAA: SRX2635182; Seed 21-24DAA: SRX2635181).
In the prospective, non-interventional nationwide epidemiological trial on Ankle-Brachial Index (Get-ABI Study), every fifth (21 %) of 6,880 patients aged 65 or older had an ABI of < 0. 9 or clinical manifestation of PAD  [14]. Investigating 4,814 subjects aged 45 to 75 in the general population, the Heinz Nixdorf Recall Study identified an ABI of < 0. 9 in 6. 4 % (men) and 5. 1 % (women), increasing to 8. 2 % and 5. 5 % when asymptomatic forms of PAD were additionally taken into consideration  [15]. The PAD Awareness, Risk, and Treatment: New Resources for Survival (PARTNERS) Program produced prevalence data of patients at risk (aged ! 70 years or 50to 69year-old smokers or patients with diabetes) in primary care. In this study, 29 % of the overall population showed a decreased ABI or manifest PAD  [16].
The "Reduction of Atherothrombosis for Continued Health" (REACH) registry  [51]  is a multinational database registering the frequency of atherothrombotic disorders and atherothrombosis-associated risk factors in clinical practice. With some 68,000 patients in 44 countries, it is the largest atherothrombosis registry in geographical terms and also by its patient sample size. After one year of followup, subjects with symptomatic PAD already showed a significantly higher mortality rate than those with coronary artery or cerebrovascular disease: 2. 4 % in PAD patients vs. 1. 8 % in CAD. The annual amputation rate was 1. 3 % and the annual intervention rate for vascular interventions was 10 % among PAD patients  [31]. The annual rates of major amputation in Europe have shown a decrease, reducing from 4.
While 10-year follow-up data of the UKPDS has suggested a significant reduction in overall mortality, other studies have revealed no significant reduction in cardiovascular mortality by approximating the HbA 1c value to normal by way of intensified diabetes treatment. These include Action to Control Cardiovascular Risk in Diabetes (ACCORD  [157] ), Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE  [158] ), Veterans Affairs Diabetes Trial (VADT  [159] ), Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation Post-trial Observational Study (ADVANCE-ON  [160] ). The inconsistent database regarding the advantages of close-to-the-norm HbA 1c stabilization is the reason for querying the lowest possible HbA 1c target values and turning toward more individualised treatment strategies.