dataesr/scientific-paragraphs-categorization huggingface dataset:
However, when compared with WT plants, Atg3bp1-1 mutants were compromised in stomatal closure in nontreated controls at 0 hpi and 1 h after treatment (Fig 4B and C at 0 and 1 hpi, respectively). Importantly, Atg3bp1-1 plants were completely insensitive to Pst-mediated stomatal reopening at 3 hpi (Fig 4C, 3 hpi). These data indicate that Atg3bp1-1 mutants counteract CORdependent reopening of stomata and that resistance to Pst hrcC -in Atg3bp1 mutant lines may, therefore, be due to the stomatal closure response. To further evaluate the role of AtG3BP1 in stomatal immunity, WT plants and Atg3bp1-1 mutant lines were challenged with Pst and Pst COR -by spray inoculation. Bacterial titers were evaluated at 3 hpi. Bacterial titers were significantly reduced in Atg3bp1-1 compared with WT plants when challenged with Pst (Fig  4D ).
Global transcriptomic profile shows that AtG3BP1 negatively regulates defense gene expression To identify the AtG3BP1-dependent genes, we performed whole transcriptome analysis (RNA-seq) with 14-d-old seedlings of WT and Atg3bp1-1 genotypes treated for 24 h with or without 1 × 10 8 CFU⋅ml -1 Pst hrcC -by spray inoculation. Samples from three independent biological experiments were collected for RNA extraction and RNA-seq was carried out on Illumina HiSeq (Illumina Inc. ). The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus (GEO) and are accessible through GEO Series accession number GSE107786. Differentially expressed genes (DEGs) were based on at least a twofold change in gene expression and the false discovery rate (FDR) value (P ≤ 0. 05) as described in the Bioinformatics part of the Materials and Methods section  (Fig S3A).
RT-PCR The mRNA expression was assayed using RT2 ProfilerTM Cell motility PCR Array (Qiagen). Briefly, RNA isolated from HBEC-3 cells transfected with siRASSF1A or siNeg was reverse transcribed and relative gene expression data was obtained using the Human Cell motility PCR Arrays. The expression profile of 84 genes relevant to cell motility as well as five housekeeping genes was assayed. Fold change calculations were done using SABiosciences' data analysis software which automatically calculates the fold change in gene expression between the treated and control groups.
Confocal imaging For living cells, the real-time acquisitions were performed using an inverted microscope (Leica DMi8). The microscopes were enclosed in environmental chambers (Incubator i8) that were maintained at 37 °C with 5% CO 2 level. The Metamorph 7. 8. 13. 0 software used for image acquisition took a snapshot of four different observation fields every minute for 1 to 3 h. The acquired images were then analyzed with the ImageJ software (version 1. 50d). For fixed cells, images were captured with highthroughput confocal microscopy (FluoView FV1000, Olympus™).
Acknowledgements We are indebted to  Dr. Michael White  for providing the HBEC-3 cell line. We are grateful to members of the  CERVOxy laboratory  for their helpful suggestions and discussions. We thank  Professor Romain Ghérardi  for his helpful advice and valuable help. Funding F. Dubois and  M. Keller  were recipients of PhD. grants from the  Association des Insuffisants Respiratoire de Basse-Normandie (AIR)  and from  Fondation pour la Recherche Médicale (FRM). E Maille  was recipient of PhD. grants from both  AIR  and  Région Basse-Normandie ,  B. Jean-Jacques  received a master grant from the  Fondation du Souffle. This work was supported by research grants from the  "Ligue contre le Cancer de Normandie" (Comité du Calvados  (to EB and GL) and from the  Rouen Institute of Research and Innovation In Biomedicine (IRIB)  (to LG and GL).
Their ndings and comments appear to be in favor of the skeptical conclusion drawn in  [6, 7] , where WSD algorithms are required to display at least 90% accuracy in order to be useful for IR. Such comments, however, refer to the straightforward task of WSD, which is either supervised (thus requiring the existence of annotated/parallel corpora) or knowledge-based (thus using external knowledge-sources, such as dictionaries or Word-Net (WN)-type synsets). The few studies that remain optimistic concerning the possible bene ts brought by WSD to IR use mostly supervised WSD techniques  [8]. However, it is well known that supervised WSD cannot be used in practice, due to the absence of the necessary annotated/parallel corpora. A majority of studies applying knowledge-based WSD are prone to the same problems  [3] : they conduct tests on small data sets  [4, 5, 9] ; when based on large test collections they report improvements against a weak baseline  [6] ; the reported improvements are minor ones  [10].
The re-ranking method Chifu et al. [3]  proposed a re-ranking method for IR that uses unsupervised WSD based on spectral clustering (performing its own feature weighting). They achieved signicant improvement of high precision in the case of ambiguous queries (8% above current state of the art baselines) when testing on data collections from the TREC competi-tion². The ambiguity of a query was evaluated with refer-ence to the title part of the topic³. These authors were interested in improving the level of precision after 5, 10 and 30 retrieved documents (P@5, P@10 and P@30, respectively). Their method is summarized by Algorithm 1. Algorithm 1: Re-ranking method based on unsupervised WSD Input: TREC topics, document collection 1. Consider the title part of a topic and check for ambiguous terms.
A context is represented as a feature vector and the similarity between two contexts is given by the value of the dot product of the corresponding feature vectors. In  [16]  the choice of the dot product as measure of similarity is motivated by the success of the linear kernel in supervised WSD  [18]. Spectral clustering had also been used, in a similar way, for an unsupervised sense induction task, in  [19]. This approach uses the same number of clusters as the number of senses in the Ontonotes sense inventory, in order to study the correspondence between the obtained clusters and the Ontonotes senses. Goyal and Hovy  [19]  quantitatively and qualitatively analyze their clusters on the Semeval-2010 dataset and comment that this type of clustering should be extremely useful in tasks like Machine Translation and Information Retrieval which require modeling semantics of rare words and unconventional senses of the target words (that may not exist in sense inventories but could be extremely useful in tasks requiring di erentiations of senses at various granular levels, as is the case in IR).
Tests We have conducted evaluation with reference to the following test collections: WT10G⁸, corresponding to which Chifu et al. [3]  obtain the best results when applying their method, and GOV2⁹. We have focused on the three top lev-els of precision studied and improved in  [3] : P@5, P@10 and P@30. The usual, standard data preprocessing was performed and the Stanford POS Tagger was used. When implementing Algorithm 1, the retrieval model (step 3) was the language model provided by the Indri search engine, with Dirichlet smoothing (µ = ) and with a maximum of 1000 retrieved documents per query. This is a widely used baseline. The same fusion function CombMNZ  [20]  as in  [3]  was used (step 8), in order to enable comparisons with the original method. The parameter which assigns a weight to the fusion function (alpha of Figure  1  and Figure  2 ), representing the weight of the clustering method for the nal results, has values ranging from 0 to 2, which are increased by 0.
The questionnaire was distributed to 300 pediatricians at the 12th Annual Congress of the Lebanese Pediatric Society and the North Lebanon Pediatric Society, on 24-25 April 2015 at Hilton Habtoor Grand Hotel, Beirut-Lebanon. The questionnaire was completely anonymous. The data of the completed questionnaires were converted and calculated by percentages. Data were analyzed using SPSS version 20. 0 for windows release (IBM SPSS Statistics for Windows, Version 20. 0. Armonk, NY, USA).
2a, b ). None of these mutations are present in the GnomAD database (http://gnomad. broadinstitute. com). Except for four individuals, all individuals have missense mutations. Interestingly, within our cohort there are multiple cases of recurrent identical de novo mutations, revealing mutational hotspots. The most striking is p. Arg985Trp, found in six children from five different families, while two additional individuals have a different substitution affecting the same residue (p. Arg985Gln). The CHD3 protein is characterized by a SNF2-like ATPase/ helicase domain, together with two plant homeodomain (PHD) fingers and two chromodomains (Fig. 2b, c )  1, 11  , which mediate chromatin interactions and nucleosome remodeling  1. The overwhelming majority of missense mutations (17/19) cluster within and around the ATPase/helicase motif, a functional domain that consists of two subdomains: a Helicase ATP-binding lobe and a Helicase C-terminal lobe.
This domain provides energy for nucleosome remodeling through its ATPase activity. All missense mutations affect amino acids that are highly conserved, both in different species and also in the other CHD proteins that can be part of the NuRD complex (Supplementary Fig. 1 ), and clearly cluster in and around highly conserved SF2-family helicase motifs (Supplementary Fig. 1 ). All are predicted to be pathogenic by Polyphen-2 and/or SIFT, and have CADD scores above 24 (Supplementary Data 1). The identified de novo mutations also include one in-frame deletion of one amino acid (p. Gly1109del) and two truncating mutations (p. Glu457* and p. Phe1935Glufs*108), although the latter causes a frameshift at the very end of the protein, leading to a stop codon after 108 amino acids. RNA sequencing of transcripts with and without cycloheximide showed that this mutation escapes nonsense-mediated decay (Supplementary Fig.
2 ). Finally, one case has a splice-site mutation (c. 4073-2A>G) which is predicted to yield skipping of exon 27, while preserving the reading frame (Fig. 2a ). Data from the ExAC database (http://exac. broadinstitute. com) indicate that CHD3 is extremely intolerant for loss-of-function mutations (loss-offunction intolerance score of 1. 0) and highly intolerant for missense mutations (Z-score of +7. 15)  25  , supporting the pathogenicity of the mutations that we found. All CHD3 mutations were determined to be the most likely causal variant contributing to the disorder of the proband. In proband 15 who has a de novo CHD3 p. Asp1120His mutation, a de novo truncating mutation in CIC was also identified (NM_015125. 3:c. 1444G>T; p. Glu482*). Since truncating mutations in CIC were recently suggested as a potential cause of intellectual disability (ID)  26  , both mutations might be involved in the phenotype of this proband.
Annotation of mutations. All mutations in this report are annotated in GRCh37 (hg19) and CHD3 transcript variant 1 (NM_001005273. 2). Next-generation sequencing. For the index case (individual 22), whole genome sequencing was performed using Illumina's HiSeq X Ten technology, the Burrows-Wheeler Aligner (BWA) software version 0. 7. 8-r455  31  and GATK v. 3. 4  32. In other individuals, exome or genome sequencing and data analysis were performed as previously described  [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44]. Expression and purification of FLAG-CHD3. CHD3 proteins were prepared as previously described  45  , with the following modifications. FLAG-CHD3 constructs were cloned into expression vectors (kindly provided by Guang Hu) using Gateway Cloning technology. Primer sequences are provided in Supplementary Table  1.
The reaction was quenched by the addition of EDTA to a final concentration of 100 mM. Aliquots (2. 5 μL) were removed and spotted on PEI-cellulose thin-layer chromatography plates and developed in 1 M formic acid and 0. 5 M LiCl. ATP hydrolysis was quantified using a Phosphorimager with Image Quant Software. For the mixing experiment, all reaction components except for CHD3 protein were incubated for 10 min at 37 °C, and the CHD3 protein mixture was added last to start the reaction. This experiment was performed 3 times per condition (N = 3) for all conditions, except for the conditions "no CHD3", "WT 12. 5 nM" and "WT 25 nM" (N = 2). For the quantification analysis, we performed 3 individual experiments for each of the two biological replicates (total N = 6), except for the p. Trp1158Arg mutant (one biological replicate, total N = 3).
At 36 h post-transfection, cells were fixed using 4% paraformaldehyde solution (Electron Microscopy Sciences) for 10 min at room temperature. The mCherry fusion proteins were visualized by direct fluorescence, nuclei were visualized with Hoechst 33342 (Invitrogen). Fluorescence images were obtained using an Axiovert A-1 fluorescent microscope with ZEN Image Software (Zeiss). Three-dimensional modeling. As no experimentally solved 3D-structure of CHD3 exists, we performed homology modeling using the modeling option with standard parameters in the YASARA  48  & WHAT IF  49  twinset. Several models of the ATPase/helicase domain were created. The best scoring model was based on template PDB-file 5JXR (sequence identity 41% over the aligned residues). We also studied the model based on PDB-file 3MWY (sequence identity 45%), which shows a more open conformation and contains an ATP substitute.
Acknowledgements We thank all individuals and families for their contribution. We thank  Amaia Carrión Castillo  and  Else Eising  for assistance with the WGS analysis of the index individual, and  Sarah Graham  and  Elliot Sollis  for cloning the wild-type CHD3 construct for immunofluorescence. This work was supported by the  Netherlands Organization for Scientific Research (NWO) Gravitation  Grant  24. 001. 006  to the  Language in Interaction Consortium (L. S. B. , S. E. F. , and H. G. B. ), the  Max Planck Society (S. E. F. ) , the  National Institute on Deafness and Other Communication Disorders  Grant  DC000496  ( L. Sh. ) and a core grant to the  Waisman Center  from the  National Institute of Child Health and Human Development  (Grant  U54 HD090256 ) to L. Sh. , the  Canadian Institutes of Health Research Grants   MOP-119595  and  PJT-148830  to W.
in clinical studies. Statistical analyses were performed with StatView software (Abacus Concepts Inc. , Berkeley, CA, USA). Data are presented as mean ± standard deviation (s. d. ). Percentages were compared with the Chi-square test and means with Student's t-test or the Mann-Whitney U-test depending on the normality of the data distribution. Results are presented in Table  1. Double ejaculates were necessary in 4. 4% of IUI, mainly in cases of male subfertility. All basic semen parameter values were significantly lower at the time of diagnostic test selection in the cases with two sperm collections (Table  1 ). The threshold of 10 6 spermatozoa was obtained by pooling a second ejaculate in 82. 3% (79/96) of the cases. Compared with IUI with one ejaculate (n = 2066), the clinical pregnancy rate per IUI was not lower when two ejaculates were needed (n = 96) although the number of inseminated motile spermatozoa was significantly lower.
Couples were considered eligible for IUI when at least one fallopian tube was proven permeable and the total motile sperm count (TMSC) was above 1 million after a diagnostic sperm selection test. This test was performed according to the WHO guidelines (2010)  4  using discontinuous density gradient centrifugation (three layers: 60%, 80%, and 90% with Puresperm®, Nidacon, Mölndal, Sweden). Ovarian stimulations were conducted as previously described. 5  For IUI, spermatozoa were selected in the same way as in the sperm selection test. If the TMSC was <10  6  after selection, a second ejaculate was requested 1 h or 2 h later. The two sperm preparations were then pooled for insemination. Clinical pregnancies were defined as the presence of a fetal heartbeat 7 weeks after insemination. Data were extracted from the Gynelog clinical database used in our department.
This database is approved by the French National Commission for Information Technology and Civil Liberties (CNIL) to be used for clinical research. According to French law (2012-300), patients are aware that their data can be used for anonymous clinical studies unless they specifically state otherwise. This information is detailed in posters in the rooms of the center, and patients can inform the center through a letter if they do not want to participate spermatozoa) were higher than that in our study (fewer than 1 × 10 6 ) or reported in other studies that separated good and bad results in IUI. 1  Regarding the number of inseminated spermatozoa, a recent systematic review found that the value of 1 × 10 6 spermatozoa is the most frequently cited threshold for optimizing IUI results in retrospective studies.
Study design Data from two studies were analyzed: WOBASZ Senior was carried out in 2007, which included 1096 subjects, and a subsample of 461 people over 74 years of age from the WOBASZ II study completed in 2013-2014 (WOBASZ Senior II). The assumptions and objectives of both projects as well as a detailed description of the respondents were described previously  [18, 19]. The methodology (study protocol, training materials, a set of questionnaires and instructions for each element of the study) was based on protocol of the first edition of WOBASZ  [20]  and European Union guidelines concerning the methodology of epidemiological studies of CVDs (EHES)  [21]. The examined sample was randomly selected from the Polish population, at the Department of National Registers MIA (an electronic register -PESEL).
Data collection and measurement The participants were stratified into the following three age groups: 75 to 79, 80 to 84, and 85 years. Subsequent to overnight fasting, blood specimens were obtained for the measurement of serum lipids and glucose, and the samples were sent to a central certified laboratory (Diagnostyka Sp. z o. o. , Warsaw, Poland)  [19]. BMI was calculated as the ratio of weight (kg) and height squared (m). The following definitions were accepted: -obesity -when BMI ≥ 30 kg/m 2 ; -diabetes -when diagnosed previously or if the patient received hypoglycemic drugs; -hyperlipidemia -when TC level exceeded 5. 0 mmol/L or cholesterol LDL exceed 3. 0 mmol/L or if the patient received lipid-lowering drugs; -coexisting CVD -previously diagnosed coronary artery disease, past myocardial infarction, myocardial revascularization, previous stroke, peripheral atherosclerosis; -education -the participants were divided into two groups -less than 7 years of education or 7 years and more; -physical activity -at least 30 min of uninterrupted activity, e.
We acknowledge the support of the project " Quantum Fluids of Light"  ( ANR-16-CE30-0021 ), of the  ANR Labex Ganex  ( ANR-11-LABX-0014 ), and of the  ANR Labex IMobS3  ( ANR-10-LABX-16-01 ). D. D. S. acknowledges the support of  IUF (Institut Universitaire de France ).
In this article, we investigate numerical solution of a class of multi-order fractional differential equations with error correction and convergence analysis. According to fractional differential definition in Caputo's sense, fractional differential operator matrix is deduced. The problem is reduced to a set of algebraic equations, and we apply MATLAB to solve the equation. In order to improve the precision of numerical solution, the process of error correction for multi-order fractional differential equation is introduced. By constructing the multi-order fractional differential equation of the error function, the approximate error function is obtained so that the numerical solution is corrected. Then, we analyze the convergence of the shifted Chebyshev polynomials approximation function. Numerical experiments are given to demonstrate the applicability of the method and the validity of error correction.
Acknowledgements The authors would like to thank the referees for careful reading and several constructive comments and for making some useful corrections that have improved the presentation of the paper. The authors would like to thank the  School of Science, Yanshan University, Qinhuangdao, Hebei ,  P. R. China  for providing a good learning environment and  INSA Centre Val de Loire, Université d'Orléans  for offering to help.
All antibodies were used in a dilution of 1:200. For IF detection, cells were incubated with Alexa-488-conjugated (Invitrogen) anti-rabbit antibody and Alexa Fluor-633-conjugated (Invitrogen) anti-mouse antibody. For the PLA, the PLA RED kit (Sigma) was used and the method described previously was followed  (Weibrecht et al. , 2013; Koos et al. , 2014). DAPI was used for the labeling of the nucleus. Images were captured using 640 nm filters; or, when higher resolution was needed, by confocal microscopy. Each sample was tested in triplicates and the PLA signal dots were counted by the ImageJ software. For each sample, the counted cytoplasmic signals were localized in individual cells, as observed by visible-light microscopy, during the capturing of each image. DAPI staining was used to determine nuclear signals and for each sample, we counted dots in 50 cells randomly selected during the imaging.
This was repeated in at least three independent experiments. As a transfection control, cells were co-transfected with GFP. In the cases, transfection was required for the assay, non-transfected cells were excluded from the statistical analyses. The values were used for the preparation of a graph and for statistical analysis to calculate the mean, the standard deviation and the one-tailed P-values using the GraphPad Prism 5 software. The asterisks in the graphs of the figures represent P-values of three independent experiments, as follows: 'n/s' for P > 0. 05; '*' for values P ≤ 0. 05; '**' for values P ≤ 0 01; and '***' for values P ≤ 0. 001. The statistical analyses are based on results obtained by at least 50 cells of each experiment.
Acknowledgements We thank  Dr Borivoj Vojtesek  ( RECAMO, Brno ) for developing and providing antibodies used in this work ( GACR P206/12/G151 ). We thank  Dr Niclas Setterblad  ( Plateforme Technologique de l'IUH'  and the  University of Paris-Diderot 7, Paris)  for providing spectrophotometer and microscopy services and for his valuable advices. We thank  Biosan (Uruguay)  and  Prof. Monica Marı ´n  ( Biochemistry-Molecular Biology, Facultad de Ciencias, Universidad de la Republica, Montevideo, Uruguay ) for chicken anti-p53 antibodies.
Figures  2(b, c ) show the angular velocity distributions and the mean angular velocities of the dimer center, ω c , as a function of interparticle separation for the full homodimer and a heterodimer dataset, respectively. The instantaneous angular velocity ω c,n is defined as the difference in the central angle of the pair in the sequential frames n,n+1 (i. e. ! !,! = (! !!! -! ! )/Δ!, n is the frame number, Δ! is the time step). In an overdamped system ! ! ∝ ! !". In order to combine data with different heterodimer orientations, we define positive velocity as the vector from the smaller particle towards the larger particle. Heterodimers exhibit a positive mean angular velocity when the particles are at optical binding separation (600±150 nm), and a negative mean angular velocity when the separation is 3λ/2n b (i.
Data analysis and combination: We performed 11 independent experiments, each of which was 7,000 frames in length. Of these experiments we limited the analysis to cases in which we observed two particles in the trap without a third particle near by. We then used the intensity information from the sCMOS detector to identify whether the particle pair was a homodimer (5 particle pairs, 8,500 frames) or a heterodimer (12 particle pairs, 18,900 frames). These combined data enabled us to bin the mean angular velocity ω c as a function of interparticle separation, as shown in Fig  2(b, c ) and calculate the MSD and the transport exponent, !, for all ranges of interparticle separation. Separation dependent MSD curves were calculated by first identifying 9 trajectories of homodimer pairs and 11 trajectories of heterodimer pairs that were at optical binding separation (less than 1.