dataesr/scientific-paragraphs-categorization huggingface dataset:
Functional Aaeg Dcr2 generated diverse but consistent true 21 nt vsiRNAs during SFV infection To explore the possibility that Aaeg Dcr2 loss-of-function mutations affected population-level diversity of SFV vsRNA we conducted a differential transcript abundance analysis using edgeR (Fig  7 ). To determine this, we treated all the SFV-mapped small RNA reads (16-46 nt) as unique transcripts and generated count tables with normalized reads for all vsRNAs or 21 nt vsRNA subset (S7D Fig). Counts were then normalized for library size using the weighted trimmed mean of M-values (TMM) method and visualized in a multi-dimensional scaling (MDS) plot of the samples. MDS plots can be viewed as a type of unsupervised clustering where distances correspond to average log-fold changes between each pair of samples.
Moreover, specific polymorphisms we identified in the helicase and Rnase IIIB domain from Dcr2 haplotype sequences retained their antiviral activity, indicating that the functionality of these Dcr2 domains is important. These data strengthen the argument of the importance of conserved functions of these domains in Aaeg Dcr2. The AlphaFold based prediction of Aaeg Dcr2 opens new opportunities for understanding targeting, and processing of dsRNA. Two areas of significant difference between Dmel Dcr2  [38]  and our model were observed, highlighting possible insights into Dcr2 structure (S3 Fig). First, the region from amino acids 1018-1069 is visualized in our model as a mostly unstructured loop, spanning between the two modules. Taken together with the low pLDDT values from AlphaFold (suggesting low confidence in local predictions for this region) and the absence of density in this region in the EM map, it seems reasonable to suggest that this region is flexible and disordered.
Plasmids and mutagenesis Site-directed mutagenesis of a previously developed pPUb-myc-Dcr2  [46]  expression plasmid of a myc-tagged WT Aaeg Dcr2 (GenBank ID: AAW48725; coding sequence GenBank ID: AY713296) under the control of PUb promoter  [72]  was performed. In-Fusion cloning (Takara Bio) was performed following the manufacturer's suggestions using mutagenesis primers designed with 15 bp extensions homologous to target vector ends (S5 Table ). The mutations were based on previous studies on Dmel Dcr2 that disrupted its activity. The helicase domain mutations (K39N, Y232G, and G448R; Fig 1B ) were part of known conserved amino acid motifs I, IV, and VI  [47]  across helicase sequences that have been identified in Dmel Dcr2  [35, 37, 38, 40]. The RNase IIIA and IIB mutations (D1198A, E1341A, D1444A, and E1548A; Fig  1B ) were based on conserved residues observed during domain IIIA and IIIB dimerization that have been investigated in Dmel Dcr2 and Dcr1  [37, 48].
To identify the conserved residues for mutagenesis in Aaeg Dcr2, multiple sequence alignment of reference sequences of Dmel Dcr2 (GenBank ID: NP_523778), H. sapiens Dcr1 (Gen-Bank ID: NP_085124), and Ae. albopictus Dcr2 (GenBank ID: NP_001339903) together with Aaeg Dcr2 WT was performed (Fig 1B, top panel) using Clustal Omega in Geneious Prime v. 2021. 1. 1. For the helicase mutants, PCR with mutagenesis primers was performed on pPUbmyc-Dcr2 and allowed to recombine after In-Fusion reaction. For the RNase III mutants, the mutations were collectively introduced using a single construct (mtR3) from a synthetic dsDNA fragment (Eurofins). The pPUb-myc-Dcr2 plasmid was first linearized by inverse PCR, and the PCR amplified mtR3 construct mixed in an In-Fusion reaction (Takara Bio) to allow recombination.
For mutations based on Dcr2 haplotypes (S2 Table ) identified from Ae. aegypti mosquitoes collected from various geographical origins, three mutations in the helicase domain were generated, N246D (negative net charge), Q253K (positive net charge), and N246D/Q253K (neutral net charge). One mutation in the RNase IIIB domain H1514N was also generated. These were based on identified SNPs (S3 Table ) between the haplotype sequences and a reference WT Dcr2 (GenBank ID: AY713296). In making the constructs, pPUb-myc-Dcr2 was first subjected to double restriction enzyme digest using NruI and Esp3I (New England Biolabs) for the helicase mutations or SmaI and FseI (New England Biolabs) for the RNase IIIB mutant. The double restriction enzyme digest linearized the plasmid and excised the fragments of Dcr2 intended for PCR mutagenesis.
Phased haplotypes were reconstructed using the PHASE algorithm implemented in DnaSP v. 5  [75]. Thirteen Dcr2 haplotype sequences were identified (GenBank ID: MW924847 to MW924859; S2 Table). To determine SNPS  (Fig 2A and S3 Table) , the 13 haplotype sequences were aligned to a WT Dcr2 sequence (GenBank ID: AY713296, previously cloned into by pPUb-myc-Dcr2) using MUSCLE  [76]. Putative amino acid sequences of haplotypes were used to generate unrooted phylogenetic trees constructed using the Neighbor-Joining method following the Jukes-Cantor model with 1000 bootstrap replicates  [76] [77] [78]. The consensus tree (Fig  2B ) is presented with corresponding % consensus support for each node and substitution rates. All sequences were analyzed and visualized in Geneious Prime (v. 2020. 1). In silico analysis prediction on the effect of the different mutations on Aaeg Dcr2 function (S1 Table ) was performed in SIFT  [49]  available at https://sift.
Generating a putative Aaeg Dcr2 structure The WT sequence of Dcr2 (GenBank ID: GenBank record AAW48725) was issued as a query to DeepMind's AlphaFold structure inference algorithm v. 2. 0. 1  [79] , using template models 1 through 5 and not restricting available templates. The resulting models were examined and in accordance with overall model quality predictions summarised in mean pLDDT value with the highest quality model selected for further analysis. Structural analyses were performed in Chi-meraX  [80]. Domain positions were assigned and labeled by color based on GenBank sequence annotations and predictions from InterProScan in Geneious Prime v. 2021. 1. 1. Residues of interest were also labeled and contacts, hydrogen bonds, and distances estimated using builtin functions. Plots of error metrics (predicted local distance difference test and predicted aligned error) were produced using AlphaPickle  [81].
Mapped fastq reads from individual libraries were converted, processed, and enumerated in bash (v. 3. 2). The resulting dimensions of the counts table for all 16-46 nt vsRNA species and 21 nt vsRNAs were 398,279 and 23,934, respectively. Count tables were then imported to the differential gene expression package edgeR (v. 3. 30. 3)  [85]  in the R Studio (v. 1. 3. 1073) environment and normalized for library size using the weighted TMM method in calcNormFactors() and filtered for a minimum count of 5 with filterByExpr(). To explore the relationship between samples, an MDS plot of the edgeR normalized count tables with plotMDS(top = 500) of both the SFV vsRNAs and 21 nt vsRNAs was constructed. A heatmap of the log-transformed TMM normalized 21 nt vsRNAs was produced using pheatmap (v. 1. 0.
Acknowledgments We thank  Diego Ayala ,  Christophe Paupy , and  Davy Jiolle  ( IRD-MIVEGEC and CIRMF ) for initially providing the mosquito colonies from Cameroon and Gabon;  Veasna Duong  and  Amelie Vantaux (Institut Pasteur du Cambodge)  for initially providing the mosquito colonies from Cambodia;  Anubis Vega-Rua  ( Institut Pasteur de la Guadeloupe ) and  Isabelle Dusfour  ( Institut Pasteur de la Guyane ) for initially providing the mosquito colonies from  Guadeloupe and French Guiana. We also thank  David Bhella  ( MRC-University of Glasgow Centre for Virus Research ) for helpful discussions and support with structure prediction.
A. K. was funded by the  UK Medical Research Council  ( MC_UU_12014/8 ). R. J. G. was supported by a  British Council Newton   Fund grant ,  ID 279705176 , under the  DOST-Newton PhD Scholarship partnership ; the grant is funded by the  UK Department for Business, Energy and Industrial Strategy ,  Philippines Department of Science and Technology-Science Education Institute , and the  University of the Philippines Visayas  and delivered by the  British Council. For further information, please visit www. newtonfund. ac. uk. L. L. was supported by  Agence Nationale de la Recherche  (grants  ANR-16-CE35-0004-01 ,  ANR-17-ERC2-0016-01 , and  ANR-18-CE35-0003-01 ) and the  French Government 's  Investissement d'Avenir program Laboratoire d ' Excellence Integrative Biology of Emerging Infectious Diseases  (grant  ANR-10-LABX-62-IBEID ).
The authors acknowledge valuable discussions with  Julia Stawarz ,  Jeffersson Agudelo Rueda ,  Daniel Verscharen ,  Lorenzo Matteini ,  Domenico Trotta ,  Francesco Califano ,  Giuseppe Arrò , and the members of the Solar Orbiter Science Working Groups. L. F. and D. B. are supported by the  UK Science and Technology Facilities Council (STFC)  grant  ST/T00018X/1. A. M. thanks the  Belgian Federal Science Policy Office (BELSPO)  for the provision of financial support in the framework of the  PRODEX Programme  of the  European Space Agency (ESA)  under contract No. 4000134474. G. L. acknowledges funding from the  KULeuven Bijzonder Onderzoeksfonds (BOF)  under the  C1  project  TRACESpace , from the  European Unionʼs project DEEP-SEA  (grant agreement  955606 ), and from  NASA  grant  80NSSC19K0841.
Other Descriptive Data Age, gender, weight, and height, body mass index (BMI) were recorded. Physical activity status was also characterised according to the participant's self-report: participants who reported recreational physical activity or sports activity for 4 or more hours per week were considered physically active, while patients who did not achieve this cut-off were considered physically inactive. Discomfort at tested limb was evaluated after each test using a numeric rating scale. Participant was asked to rate discomfort from 0 to 10, understanding that 0 is equal to no discomfort and 10 is equal to the worst possible discomfort.
Analysis Statistical analysis was performed using Graphpad Prism (version 9. 0 for Mac OSX, Graphpad Inc. , San Diego, CA, USA). Qualitative parameters were expressed as counts and percentages. Normality was assessed using the Shapiro-Wilk test. As some datasets did not pass the normality test, results were expressed as medians with interquartile ranges [P25 and P75] for quantitative parameters and comparisons were performed using nonparametric tests. Paired data were compared using Wilcoxon test. Unpaired data were compared using Mann-Whitney test. Correlations between measures were tested using Spearman test. Performances of the seated and fixed measurements were compared with the reference method (supine position with non-fixed configuration) using Bland-Altman analysis. The same analysis was used to compare the performances of the fixed configuration with the non-fixed configurations, considered arbitrarily as the reference method.
Study Area The study area covered the western Mediterranean region, including distribution ranges of D. pictus and D. scovazzi in northwestern Africa (659,784 km 2 ), D. pictus in Sicily (27,711 km 2 ), and the Iberian Peninsula and southern France (699,546 km 2 ). Corsica and Sardinia were excluded from the analysis because they are both occupied by endemic Discoglossus species (D. montanelli and D. sardus, respectively) with no contact zones with the D. pictus range. Protection regimes within the Iberian Peninsula and southern France were defined on the basis of the Natura 2000 GIS database  [28]. In this area, Natura 2000 includes 781 sites covering nearly 20% of the territory. Among these sites, 189 are explicitly targeted to protect Habitats Directive Annex II species D. galganoi galganoi (167 sites) and D.
Species Data Native-range data for D. pictus included 76 occurrences from Algeria and Tunisia (presence-only data:  [29]  and unpublished data from P. geniez) and 115 occurrences from Sicily (among 373 10 × 10 km atlas cells:  [30] ). Northern African data also provided 113 occurrences for D. scovazzi from Morocco (presence-only data:  [31]  and unpublished data from P. geniez) (Figure  1 ). European invaded-range data for D. pictus included 59 occurrences from southern France (presence-only data:  [9, 32]  and 59 occurrences from Spain (among 7720 10 × 10 km atlas cells: [33]) (Figure  1 ). Spanish data also provided occurrences for D. galganoi jeanneae (500), D. galganoi galganoi (860), E. calamita (2463), P. punctatus (790), and P. ibericus (261). Finally, Portuguese data completed the Iberian distribution for D.
AUC measurement is independent of the threshold at which the model's prediction is considered and values range from 0 to 1; AUC scores close to 1 mean perfect model predictions, while AUC scores close to 0. 5 indicate predictions no better or worse than random. The potential problems raised by Lobo et al. on the use of AUC as a measure of model performance were considered to be minor because AUC was used to rank models obtained from the same dataset and within the same geographical area according to their predictive performance  [49]. We applied an ensemble-forecasting framework by computing a consensus of single-model projections (from models with AUC > 0. 7 using AUC values as model weights) using a weighted average approach  [50]. To determine the potential range of affectation of D. pictus in the Iberian Peninsula, native-range predictions were built using North African and Sicilian data and projected to new geographical areas in southern Europe.
These models were built using only occurrence data from the native range where the species was in equilibrium with the environment. Here, agreement between observed and predicted distribution within the invaded range was assessed using AUC scores, which were computed using invaded-range occurrence samples  [51]. Differences between current and future climatic suitability scores were used to measure changes in climatic suitability, yielding positive changes when future scores were larger than current scores, and negative changes in the opposite case. To allow comparisons between species, scale values from current and future climatic suitability predictions were homogenized using standard scores (i. e. , difference between raw climatic suitability score and mean climatic suitability score, divided by the climatic suitability standard deviation).
Their profile is recorded while a magnet is approached (Figure  1 -figure supplements 3 and 4). Assuming that a multicellular cohesive aggregate can be modelled as a continuous elastic medium (as supported by confocal imaging, Figure  1b ), surface tension and magnetic forces in volume compete to determine the equilibrium shape  (Kalantarian et al. , 2009)  while Young's modulus is at stake for the contact area  (Mazuel et al. , 2015; Figure   1c , Figure  1 -figure supplement 3). The height, the width of the aggregate and the ending points of the contact zone are pointed in the Tensio X application (Figure  1 -figure supplement 3), a dedicated MATLAB interface we developed to fit the obtained profile. The elasticity and the capillary parameter c = Mv grad(B) γ ( Mv , γ , and B denote the magnetic moment per unit of volume, the spheroid surface tension, and the magnetic field, respectively)  (Kalantarian et al.
C2C12 cell culture C2C12 WT (CRL-1772; RRID:CVCL_0188) were obtained from ATCC and cultured in Dulbecco's modified Eagle's medium (DMEM, Gibco), supplemented with 1% Penicillin-Streptomycin (P/S, Gibco) and 10% fetal bovine serum (FBS, Gibco). Their identity has been authenticated by COI assay. C2C12 A21V (stably transfected with empty vector), desWT-Cl29 (stably expressing exogenous human WT desmin), and desD399Y-Cl26 (stably expressing exogenous human D399Y desmin) were cultured in 1% P/S, 20% FBS, 1 mg/mL geneticin (10131027, Gibco) and 2 µg/mL puromycin (P7255, Sigma-Aldrich) as described in  Segard et al. , 2013. All cell lines were tested negative for mycoplasma contamination.
Here, all the measurements were done with a spheroid radius in the range of this critical radius so that Young's modulus can be extracted. This modulus is extracted at the end of the elastic deformation while the surface tension is deduced from equilibrium shape. Tensio X is a dedicated MATLAB-generated application freely available to extract both surface tension and Young's modulus from initial and flattened profiles. Images of the initial and final state are first downloaded. The user has to define the initial radius, height, and width by pointing left/right and top/bottom frontiers of the spheroid on the two images. The radius of the contact zone is also extracted. The scale factor, magnetic force per unit volume, and an estimated surface tension value are entered. The obtained fit is then superimposed on the flattened spheroid image to check for its relevance and the deduced Young's modulus and surface tension are registered in a separate data file.
Acknowledgements The authors thank  Alexandre Fromain  for his help on VSM measurements and  Ali Abou Hassan  for providing us magnetic nanoparticles. This work was supported by the  Program Emergence(s) de la Ville de Paris  (Grant MAGIC Project). The study was partially supported by the  Labex Who Am I?, Labex   ANR-11-LABX-0071 , the  Université de Paris , Idex  ANR-18-IDEX-0001  funded by the  French Government through its Investments for the Future program , the  AFM (French Association for Myopathies)   AFM-22956 , and the  French Defense Procurement Agency (DGA-AID) France. We acknowledge the  ImagoSeine core facility  of the  Institute Jacques Monod  (member of the  France BioImaging ,  ANR-10-INBS-04 ) and  France Lam at the Cellular Imaging facility of IBPS  for her advice on deep penetration tissue imaging.
Test procedure In fracture mechanics, the resistance to cracking is described by expressing the crack tip opening displacement (CTOD) as a function of crack propagation Δa. Tests on CT specimens were performed using different orientation angles (0 • , 45 • and 90 • ). After precracking, the specimens were painted white to enhance contrast with the black background. Using the same Instron 1341 hydraulic tension/compression machine, the sample was attached to both jaws via two pins. The loading of the tension test was controlled using the INSTRON Wavemaker software, which records the movement of the cylinder and the applied force (DIAdem software). An Olympus camera (500i /s), with two lighting flashes, was used for image acquisition (Fig. 18 ). The camera is used to record the crack initiation on specimens.
The Control of Allergic Rhinitis and Asthma Test (CARAT) is a patientreported outcome measurement (PROM) assessing the control of asthma and allergic rhinitis (AR) at a 4 week interval. This systematic review aimed to evaluate the measurement properties of CARAT. Following PRISMA and COSMIN guidelines, we searched five bibliographic databases and retrieved studies concerning the development, assessment of properties, validation, and/ or cultural adaption of CARAT. The studies' methodological quality, the quality of measurement properties, and the overall quality of evidence were assessed. We performed meta-analysis of CARAT measurement properties. We included 16 studies. Control of Allergic Rhinitis and Asthma Test displayed sufficient content validity and very good consistency (meta-analytical Cronbach alpha = 0.
| Selection criteria We included original studies (i) assessing adolescents (aged 12 years and older) or adults with asthma and/or AR, and (ii. a) which concerned the development, assessment of properties (such as validity, reliability, consistency and responsiveness), and/or cultural adaption and validation of CARAT or (ii. b) in which such questionnaire was used simultaneously with other PROMs as a study endpoint, and (iii) which used CARAT to assess asthma and/or AR control with a 4week recall. We excluded reports available solely as conference abstracts, as recommended by COSMIN. 26  No restrictions based on publication date or language were applied.
| Search strategy A comprehensive search was performed in January 2022 in five bibliographic databases: Ovid/MEDLINE, Web of Science, Scopus, ClinicalTrials. Gov and the Cochrane Central Register of Controlled Trials (CENTRAL). The detailed search query may be found in Supplementary Table  1. References of the included studies were screened to identify potentially relevant studies. Additionally, we performed a manual search on Google Scholar to identify additional studies that cited any included primary studies on the development, validation or cultural adaptation of CARAT.
| Data extraction The following data were independently extracted from each included primary study by two authors (RJV and ACF) into a purposely built form: sample size, distribution of participants' age and gender, frequency of patients with AR and/or asthma, setting (e. g. , primary care, secondary care…), country and language of questionnaire administration. In addition, we retrieved information on the results obtained by each primary study on the measurement properties of CARAT. When more than one report assessed the same participants (or overlapped in the assessed participants), information was retrieved from the article assessing a larger sample, and the remaining articles were screened for additional information not presented in the main article.
32 ; meta-analytical results were then back-transformed into the natural scale. For performing metaanalysis of Cronbach alphas, variances were estimated based on computed confidence interval limits. 33  Heterogeneity was assessed using the I 2 statistic and the p-value for the Q-Cochran statistic-an I 2 >50% and a p-value <0. 10 were deemed to represent substantial heterogeneity. Whenever information was available, sensitivity analyses were performed for patients with asthma and patients without asthma. In addition, to ensure inclusion of studies with similar methodology, for outcomes assessed by primary studies using different data retrieving strategies (e. g. , outpatient consultation with physicians versus patient self-reporting through mHealth tools), our main meta-analytical results were those not considering mHealth data.
| Study selection Our database search returned a total of 283 search results (Figure  1 ). After duplicates removal, a total of 136 references were assessed through title and abstract reading, of which 48 were fully read. We identified and screened 216 unique articles from Google Scholar reference searching, and 30 were fully read. We included 16 original studies (published throughout 23 reports) in our systematic review (Table  1 ). [17] [18] [19] [20] [21] [22] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50].
| Characteristics of included studies Table  1  summarises the characteristics of included studies. The original Portuguese version of CARAT was used in 8 studies (11 reports). 17, 19, [34] [35] [36] [37] [38] [39] 42, 46, 47  There were 2 studies (3 reports) on the Italian,  40, 41, 45  German and Dutch  18, 21, 40  versions of CARAT. 22, 43, 44  The Turkish version was assessed in one study. 20  One further study, published in 3 reports and using data from a mobile app, enrolled patients from 25 countries, displaying CARAT in multiple languages. [48] [49] [50]  A total of 4467 participants were assessed, with the mean reported age ranging between 15 and 55 years old. In four studies (eight reports), all the 2622 participants were reported to have AR,  36, 37, 41, 43, 44, [48] [49] [50]  while asthma was reported in all the 1245 participants in six studies (seven reports).
Purpose To evaluate changes in global perioperative data of GreenLight-XPS 180-Watt photo-selective vaporization of the prostate (GL-XPS) of the Global Greenlight Group (GGG) database. Methods 3441 men, who underwent GL-XPS for symptomatic BPH between 2011 and 2019 at seven high volume international centers, were included. Primary outcome measurements were operative time (OT; min), effective laser time (LT; min of OT), as well as intraoperative and postoperative adverse events (AEs), all analyzed by year of surgery (2011-2019) and prostate volume (PV) group (< 80 ml vs. 80-150 ml vs. > 150 ml).