dataesr/scientific-paragraphs-categorization huggingface dataset:
For example, habitat suitability can be modeled using vegetation response models (such as VEG;  Belyazid et al. , 2019 or PROPS; Dirnböck et al. , 2018) , that are particularly designed to process output from process-based models as input information, but it can be also modelled by species distribution models that are particularly designed for large-scaled input datasets (e. g. ,  Noce et al. , 2017). Information generally needed in any environmental study (such as soil and terrain variables) has been obviated in this diagram. to understand combined effects of O 3 with other emerging environmental factors. There is also an urgent need to generate fluxbased standards and critical levels for forest protection taking into account the sensitivity of dominant forest tree species. Because of its limitations, the AOT40 index should not be adopted as default for risk assessment  (Agathokleous et al.
Because of ForestGEO's extensive biological monitoring, unique databases, and the partners' expertise, it promises to enhance society's ability to evaluate and respond to the impacts of global climate change. To date, unfortunately, the distribution of forest monitoring sites within ForestGEO appears non-homogeneous (Figure 1). Indeed, boreal and tropical forests are less represented among monitoring sites and there is a disproportionate number of monitoring sites in the Northern Hemisphere (NH), particularly in Europe, and fewer sites in the Southern Hemisphere (SH).
data assimilation system and forecasting model throughout the reanalysis period. The latest European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses are produced through the EU-funded Copernicus Climate Change Service (C3S). Forecasts are freely available through the C3S Climate Data Store. The most recent ECMWF reanalysis dataset is the ERA5 Back Extension, providing data from 1950 to 1978. The Copernicus Atmosphere Monitoring Service (CAMS) provides continuous data and information on atmospheric composition. The service describes the current situation, forecasts the situation a few days ahead, and analyses consistently retrospective data records for recent years. CAMS supports many applications in a variety of domains including health, environmental monitoring, renewable energies, meteorology, and climatology.
, 2012 ; Figure  1A ). Antisense therapy is a translational research topic in medicine and currently the focus of many clinical trials in oncology, myopathies, Huntington's and many other diseases  (Crooke et al. , 2018). For example, a phase 1a clinical trial has been completed for the treatment of solid cancers by an antisense oligonucleotide targeted to the mitochondrial-encoded lncRNA ASncmtRNA and a phase 1b clinical trial is currently under way  (ClinicalTrials. gov ID#: NCT02508441, 2015 -2018). This and many other clinical trials have demonstrated that the concept of antisense therapy is coming of age and will be further developed in the near future due to its low toxicity, high specificity and low production costs. The interest of RNA silencing has been previously established in vitro to curb the replication of highly pathogenic RNA viruses such as Ebola (reviewed in  Kim et al.
Antisense oligonucleotides gapmer design and selection We designed ASO gapmers targeting viral gRNA and the corresponding positive-sense subgenomic RNAs (sgRNAs) (Figures  1A-C ). The design pipeline contemplated three complementary strategies as described in section "Materials and methods": (i) with the use of a specific algorithm (LNA GapmeR algorithm R ), we designed ASO Gapmers with 100% phosphorothioate (PTO) backbones and locked nucleic acids (LNA) modifications on the 5 and 3 ends to enhance their *Four ASO gapmers selected among all the predicted ASOs (Supplementary Table  1 ) and synthetized to be tested. stability (Supplementary Figure  1 ); (ii) we verified that each predicted ASO targets a unique sequence, fully conserved among SARS-CoV-2 variants using the NCBI database; and (iii) we checked the predicted gRNA secondary structure around the ASO binding sites in order to determine the accessibility of each ASO to its gRNA target.
The best binding site conformations, corresponding to the lower secondary structure stability of the viral RNA target sites, were found for ASO-ORF1b (Supplementary Figure  3 ) and ASO-N in the N-3 UTR region (Supplementary Figure  4 ). Their binding sites are mainly located along single-stranded loop regions, providing easy access for ASO binding. ASO-5 UTR is the only ASO predicted to target the 5 UTR and the secondary structure of its binding site lies on a 50% double-stranded RNA segment (Supplementary Figure  5 ). For ASO-ORF1a, the conformation of its target site along a double strand may be less accessible for binding and subsequent cleavage (Supplementary Figure  6 ). We also computed the ASO design on a second SARS-CoV-2 sequence (GenBank MN988668 in the NCBI database of SARS-CoV-2 genomes) and we found identical sequence conservation in the binding sites of the four selected ASO candidates ASO-5 UTR, ASO-ORF1a, ASO-ORF1b and ASO-N (Supplementary Figure  7 ).
Sequence conservation of antisense oligonucleotide gapmers targets in severe acute respiratory syndrome coronavirus 2 variants of concern In order to predict the efficiency of the four selected ASO candidates on the main identified VOCs, we performed ASO sequence alignments against all the SARS-CoV-2 genomes The four ASO gapmers were 100% complementary (plus/minus strand) with all VOCs according to analyses on BLAST Coronavirus and BLAST against gRNA sequences of the main VOCs (Alpha, Beta, Delta and Omicron strains). available on the NCBI Genbank and GISAID Tracking of hCoV-19 Variants databases, using the BLAST tool (see details in Materials and Methods). Interestingly, the four ASO gapmers displayed 100% complementarity (strand ±) to all the available SARS-CoV-2 variants (Table  1 ). We also aligned the four ASO gapmers against the genomes of the main VOCs and, in particular, the latest most common variants detected in Europe (Omicron BA.
Perspectives of antisense oligonucleotides for antiviral therapy For therapeutic applications, an advantage of short 15-20mer ASO is their high ability of being physiologically absorbed into cells in vivo by transfection-free delivery (gymnosis) when the ASOs are administered at high dose and purity  (Lobos-González et al. , 2016). In general, injected ASOs display low toxicity; for example, a clinical trial in oncology demonstrated that subcutaneous injection of ASO up to 800 mg is welltolerated and high-dose ASOs can be naturally delivered into cells (ClinicalTrials. gov ID#: NCT02508441, 2015-2018). However, in another clinical trial, reversible renal and liver toxicity was observed at a very high dose of 10 mg/kg per week during 4 weeks  (Bianchini et al. , 2013). Interestingly, for respiratory tract infections, ASOs can be administrated by direct intratracheal delivery through aerosol inhalation.
LNA nucleotides obey Watson-Crick base-pairing rules and establish stable A-helices with good base-stacking  (Petersen et al. , 2002). This modification increases the melting temperature Tm (+ 2-8 • C per LNA base) and it confers nuclease resistance to oligonucleotides, increases their stability and potency in cells and, importantly, provides high specificity for binding to RNA targets  (Bondensgaard et al. , 2000). PTO, on the other hand, is a backbone modification in which one non-bridging oxygen atom in the α-phosphate group is replaced by sulfur (Supplementary Figure  1A ), thereby conferring higher resistance to nucleases. Design of ASO gapmers was based on the reference SARS-CoV-2 genome (NCBI Genbank Database, 2020, ID# MN908947,  Wu et al. , 2020 ; Figure  1B ). ASO prediction was performed with a proprietary algorithm (LNA GapmeR R ) on 5,000 base stretches covering the 5 UTR, ORF1a, ORF1b, and N genomic regions.
For each RNA target submitted, a score was computed to sort 10 ASO candidates. After selection of the best ASOs, according to their molecular score and position on the viral genome (5 UTR, ORF1a, ORF1b, and N), we checked their specificity against the virus by searching putative off-targets with perfect alignment on the whole human transcriptome (Megablast with highly similar sequences option). The ASOs with the best scores were sorted into two categories: « Excellent design » or « Good design ». In the present study, we kept only « Excellent design » ASOs with scores ordered from 1 to 4. We computed the ASO design on each of the isolated sequences according to the annotations of the viral genome (NCBI Genbank Database, 2020, ID# MN908947); in addition, we checked the reproducibility of the results on another SARS-CoV-2 sequence (NCBI Genbank Database, 2020, ID# MN988668).
N-CoV RT-qPCR analysis and relative expression normalization RT was performed as described above and qPCR was performed on a QuantStudio 12 K Flex Real-Time PCR System (Applied Biosystems) using the SYBR green PCR master mix. Amplification plots were analyzed using the QuantStudio 12 K Flex software, both for determination of Ct values and for melting curve analysis, which was applied in order to assess amplification specificity and the potential occurrence of dimers. For each primer pair, PCR efficiency was evaluated using serial cDNA dilutions. An equivalent of 500 pg of cDNA was used as template for each sample, and two technical replicates were run. The qPCR results of target gene N-CoV were analyzed by the 2 -CT method  (Livak and Schmittgen, 2001)  and expressed as fold-change relative to ASO-C.
Acknowledgments The SARS-CoV-2 strain BetaCoV/France/IDF0372/2020 was supplied by the National Reference Centre for Respiratory Viruses, hosted by  Institut Pasteur (Paris, France ) and headed by  Prof. Sylvie van der Werf. The human sample from which the BetaCoV/France/IDF0372/2020 strain was isolated was provided by  Dr. X. Lescure  and  Prof. Y. Yazdanpanah  from the  Bichat Hospital, Paris, France. The SARS-CoV-2/ZsGreen plasmid (MW289908) was generously provided by  Wilson-Rihn Laboratories from the Centre for Virus Research Institute of Infection, Immunity and Inflammation, MRC-University of Glasgow. Human HEK-293T/ACE2  cells were generously provided by  Mélanie Lavie ,  Université de Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, France. VeroE6/TMPRSS2  kidney cells were generously provided by  Olivier Schwartz  ( Institut Pasteur, Paris ).
HSQC NMR spectroscopy The NMR samples were made by dissolving 50 mg of lignin in 0. 5 mL of deuterated DMSO-d 6. A Bruker AV-Neo (AV-III) spectrometer equipped with a 5 mm BBO probe-head capable of producing magnetic field pulse gradients in the z-direction of 54 G cm À 1 was used to record all NMR spectra. Frequencies were 400. 03 MHz for 1 H NMR and 100. 58 MHz for  13  C NMR. The HSQC spectrum of the GA-lignin was also recorded using the standard pulse sequences from Bruker, except that 32 scans were used. All the spectra were then processed using the software Bruker TopSpin 3. 6. 1.
Surface tension measurements The water/air surface tension or water/oil interfacial tension of each GA-lignin solution were measured using the pendant drop method. A sample of each solution was inserted in a 1 mL syringe and loaded onto a Krüss DSA 30 drop shape analyzer. The drops were created and visualized using the Krüss Advance software (v. 1. 6. 2. 0). Each surface/interfacial tension value was obtained using a standardized procedure. First, a drop was created and expanded until it fell. The volume at which the drop fell was recorded. Then, a second drop was created that had approximately 90 % of the volume of the first drop as measured by the Krüss software. The drop was left to stabilize for three minutes before measuring the surface or interfacial tension value.
Photos and illustrations. Images were taken with a Canon EOS R camera fitted with the MPE 65 macro lens, attached to a Stackmaster macro rail (Stonemaster: https:// www. stonemaster-onlineshop. de/). Illumination was with three LED segments SN-1 from Stonemaster. Images of the median lobe of aedeagus and paramere were made with an Olympus BX61 microscope using a Q-imaging Camera (15. 2 64 Mp Shifting Pixel, Diagnostic Instruments Inc. ) with Image Pro Plus (Media Cybernetics, Bethesda, MD, USA, http://www. mediacy. com/imageproplus). Images taken on different focal planes were then stacked with Helicon Focus 4. 77TM software. Georeferencing. The geographic position data were extracted from Google Earth (http://earth. google. com) and are given in decimal degrees. Our map is based on Bleich, Gürlich and Köhler: Verzeichnis und Verbreitungsatlas der Käfer Deutschlands (http://www.
Acknowledgements This work was supported by grants from the  Bayerisches Staatsministerium für Wissenschaft und Kunst/ SNSB Innovativ. Mrs. C. Gevatter  of the  Regierung von Oberbayern, Munich, Germany  is thanked for providing the relevant permits. We would like to thank  Mrs. D. Feige  from the  Landratsamt Garmisch-Partenkirchen  for her support in the context of this investigation. Jiří Hájek  (Prague) and  Günther Wewalka  (Vienna) are thanked for reviewing and critically reading the manuscript. Alexandre Alié  is thanked by MM for logistical help. Garth Foster (Ayr,  Great Britain ) is thanked for the linguistic correction of the manuscript, and  Kirill Makarov  and  Robert Forsyth  for editing the final draft of our work.
Statistical analyses The statistical comparisons were performed with Statistica V10 software  [20]. When the experimental situations respond to a Gaussian distribution (averages of weight of dried plants leaves), the statistical comparisons were analyzed using the one-way ANOVA test. When the experimental situations didn't show a Gaussian distribution (% inhibition of mosquito adult emergence), the Kruskal Wallis test was used. The expected mortality  [21]  for the azadirachtin + NPK fertilizer mixture was calculated by 1 -(frequency of adults surviving on azadirachtin) × (frequency of adults surviving on NPK fertilizer). It is considered to be synergy (positive interaction) when the observed mortality is significantly higher (Fisher's exact  test) than the expected mortality. The insecticide susceptibility tests were analyzed according to the method of Finney  [22]  by using Probit ® software  [23].
| Diversity and structure analysis Fifty-one cacao tree accessions representative of 11 distinct genetic groups of the T. cacao species (identified by  Motamayor et al. , 2008)  were taken as controls for the calculation of diversity and population structure (Dataset S1). The phylogenetic tree was generated using DARwin software  (Perrier & Jacquemoud-Collet, 2006). The genetic distances were calculated using the Dice coefficient and the Neighbour-Joining method.
| Linkage disequilibrium calculation Linkage disequilibrium (LD) between pairs of SNPs was calculated with Haploview 4. 2  (Barrett et al. , 2005)  and the LD decay was plotted using the 'ggplot2' R package according to  Sardos et al. (2016)  protocol. The LD decay between pairs of SNPs plotted for each chromosome (Figure  S1 ) show that the r 2 value decreases by half around 600 kb. Given that 1 MB corresponds to around 2 cM  (Loor, 2007) , the LD decay of this population is around 1. 2 cM. We decided to use this 600-kb limit to determine the confidence interval of associations. For each positive marker we reported an association area of plus or minus 300 kb, that is, an association area of 600 kb. If two or more associated markers have overlapping confidence intervals, they are grouped in a single association zone.
| GWAS analysis SNPs with no missing data and a MAF greater than 5% were selected for the GWAS. The final dataset is composed of 5337 SNP markers. The data set is available in the database tropgene (http://tropgenedb. cirad. fr/tropgene/JSP/interface. jsp?module=COCOA) at the study named 'Cocoa_Amazonie_Ecuador_aroma'. A GWAS analysis was performed to associate SNP markers with biochemical traits (202 phenotyped accessions Â 5337 markers) and with sensory (159 phenotyped accessions Â 5337 markers) traits using TASSEL v5. For all the traits, a mixed model (MLM) was carried out with a structure matrix, determined by running a PCA (principal component analyses integrated with TASSEL v5 software), considered as a fixed effect, and also with a kinship matrix considered as a random effect as covariates to control the false-positive rate.
The option of not compressing and re-evaluating the components of variance for each marker was chosen. The kinship matrix was inferred using the Identity by State (IBS) pairwise method proposed by Tassel v5. The threshold was determined using the R package Simple M based on the Bonferonni correction  (Gao et al. , 2008 (Gao et al. , , 2010)). The threshold corresponds to a p value of 1676 Â 10 À5. The confidence interval of the associations was chosen according to the LD. The physical maps plotting the association areas were created using SpiderMap v1. 7. 1 software  (Rami, 2017). Candidate genes were identified in a region of 300 Kbp (around the associated markers) using the T. cacao genome sequence V2  (Argout et al. , 2017). This window size of 600 kb was chosen based on the decrease of LD depending on physical distance along chromosomes estimated from the studied cacao Ecuadorian population.
| Biochemical traits To study the biochemical determinism of cocoa flavours, the volatile compounds contained in the fermented-dried beans were determined by GC-MS. All the compounds identified and their already known aromas are shown in Dataset S2. Strong positive correlations (between. 8 and 1) were identified between several volatile compounds. In contrast, no strong negative correlations (between À. 8 and 1) were identified (Figure  S2 ). The strong correlations were observed between biochemical compounds with similar structures. PCA were performed. These analyses show a continuous variation within the population for the concentrations of volatile compounds (Figure  S3a ). Axis 1 is mainly influenced by the concentration of cis  2, 1,.
| Sensorial traits A sensory study of the liquors of each cocoa genotype was conducted in which 33 criteria were evaluated (Dataset S3). The three notes, savoury/umami, mouldy and smoky, were not detected in any of the genotypes. Three strong positive correlations (between. 8 and 1) could be observed between the different sensory characteristics. In contrast, no strong negative correlations (between À. 8 and 1) were identified (Figure  1 ). The results of the PCA performed on the sensory data also show a continuous variation within the population (Figure  S3b ). Axis 1 is mostly influenced by the roast degree score, the cocoa score and the bitterness score. Axis 2 is mostly influenced by the note 'fruit-tropical', the note 'Grassy, Green, vegetal, Herbal' and the note 'Fruit-Dried'.
| Identification of significant association areas in relation to floral notes A total of 39 association areas were detected to compounds known to have a floral note and 9 other associations were detected linked to the floral notes, detected by sensory analysis (Figures  S4  and S5 ). Associations were detected on all chromosomes except chromosome 4 (Dataset S4). Seven areas of co-locations between different biochemical compounds as well as between biochemical compounds and sensory notes were observed (Table  1 ). Two volatile compounds seem to be more related to the presence of orange blossom notes: the cisbeta-ocimene and the o-xylene (they are both known to have floral notes; Dataset S1).
| Areas of association detected in relation to fruity notes A total of 194 association zones were detected in relation to volatile compounds known to have a fruity note and 39 linked to fruity notes detected by sensory analysis (Figures S4ÀS7). Areas of association were detected on all chromosomes (Dataset S4). Among the 56 areas of co-locations between the different traits, 26 of them display colocations between volatile compounds and sensory notes (Table  2 ): Diethyl butanedioate, nonan-2-one, 2-pentylfuran, ethyl lactate, trimethyl-oxazole, pentyl acetate, heptan-2-ol, 2,3,5-trimethylpyrazine and ethyl 2-hydroxy-4-methylpentanoate seems to be more related to over fermented/rotten fruit notes. Diethyl butanedioate, hexyl acetate, limonen, 1,2-propanediol diacetate and nonan-2-one seems to be more related to fruit dark notes.
| Areas of association detected in relation to woody and spicy notes A total of 76 association areas were detected in relation to volatile compounds known to have a woody and/or spicy note and 10 linked to the woody and/or spicy notes detected by sensory analysis (Figures  S4-S7 ). Areas of association were detected on all chromosomes (Dataset S4). Eleven areas of co-location were detected between different volatile compounds and between volatile compounds and sensorial notes (Table  4 ). Camphene and alphaterpinene seem to be more related to the presence of spice tobacco notes.
| Areas of association detected in relation to empyreumatic notes We could identify 66 association zones related to volatile compounds known to have an empyreumatic note (caramel, brown sugar,    S7 ). Areas of association were detected on all chromosomes (Dataset S4). Twenty areas of co-locations were observed (Table  5 ). The 2,3-dimethyl-5-ethylpyrazine, 2,5-dimethylpyrazine and 1-methylhexyl acetate seem to be more related to the presence of sweet, caramel notes. The 3-methyl-2-(2-methyl-2-butenyl)-furan and 1-methylhexyl acetate seems to be more related to the roast degree. T A B L E 2 (Continued).
| Identification of candidate genes involved in the different biosynthetic pathways of aromatic compounds detected in the Amazonian population In each association zone, a search was undertaken for candidate genes involved in the synthesis of the compounds in the association. Candidate genes involved in general plant defences were also observed. The biosynthetic pathways previously described in other plants appear to be valid in cocoa. Schemes summarising these biosynthetic pathways that may be present in cocoa and the involvement of candidate genes in these pathways have been produced. The 1824 candidate genes identified are listed in Dataset S6. Of the candidate genes detected, 53 are in common with previous GWAS studies on the aroma traits of the modern Nacional population (Dataset S6)  (Colonges, Jimenez, Saltos, Seguine, Loor Solorzano, Fouet, Argout, Assemat, Davrieux, Cros, et al.
| Candidate genes involved in general plant defences Plants synthesise volatile compounds for various purposes including defence  (Ponzio et al. , 2013). The molecular mechanisms governing these hormonal networks are largely unknown but recent studies have shown their implications in defence responses  (Denancé et al. , 2013) , which is why we have selected, as candidate genes, the genes listed in Table  6. Other candidate genes were found in areas of association. Their function is illustrated in Figure  8 , and all genes are included in the Dataset S6.
ACKNOWLEDGEMENTS We thank the  I-Site MUSE, Valrhona  and the  U. S. Department of Agriculture  ( USDA-ARS ), for their financial support of this project. This work, part of the  MUSE Amazcacao  project, was publicly funded through  ANR  (the  French National Research Agency)  under the ' Investissement d'avenir' programme  with the reference  ANR-16-IDEX-0006.