dataesr/scientific-paragraphs-categorization huggingface dataset:
Because strong cuticle alterations are detrimental to fruit quality, we preferred to focus in a first step on the phenotypic alterations responsible only for variations in fruit brightness (glossy or dull fruits), which likely arise from more subtle changes in cuticle properties. Pleiotropic mutations were also excluded because the origin of the cuticular defect is not always easy to trace (e. g. in fruit developmental mutants;  Czerednik et al. , 2012). The disadvantage of using fruit brightness as a screen for detecting cuticle mutations is that this trait can be very sensitive to environmental conditions such as the growing season (data not shown). However, of the 40 emutants examined (from the 274 originally found in the mutant database), more than 20 were further confirmed as being fruit brightness mutants.
ACKNOWLEDGMENTS The authors thank  Michel Hernould  for fruit cytology analyses,  Aurélie Petit  for her help in statistical analyses,  Isabelle Atienza  for taking care of the plants in the greenhouse, and  Isabelle Svahn  for her participation. The ESEM experiments were performed at the  Electronic Imaging pole of the Bordeaux Imaging Center , and lipid analyses were performed at the  Bordeaux Metabolome Facility.
Array-CGH experiments were performed with the maximum amount of DNA available. Array-CGH analysis was performed according to the Agilent protocol with minor protocol modifications: DNA was labeled by direct incorporation of Cya-5 and Cya-3 using a CGH labeling kit for Oligo-array (Enzo Life Sciences, COVALAB, France) for 4 hr, and labeled products were purified by QIAamp DNA Mini kit (Qiagen, Valencia, CA). A graphical overview was obtained using CGH analytics software (v4. 0), and the statistical algorithms ADM-2 according to a sensitivity threshold at 6. 0 and a moving average window of 0. 5 Mb  [20]. Mapping data were analyzed on the human genome sequence build hg18 using ensemble (www. ensembl. org). Copy Number Variations (CNV) were assessed in the Database of Genomic Variants (http:// projects.
Specificity: The five samples with normal karyotypes showed that the smaller the amount of DNA, the greater the DLRS (between 0. 26 and 0. 60). Detection of CNV showed an average of three per patient ranging from 400 bp to 600 kb; all were found in the Database of Genomic Variants (DGV). Twelve samples. 16 weeks of gestation. For the 12 samples of uncultured amniotic fluid with aneuploidy or structural abnormalities at more than 16 weeks' gestation, all of the chromosomal imbalances were detected and characterized by array-CGH (Table  2  and Figure  2 ).
In prenatal diagnosis, the detection of new CNV not reported in the Database of Genomic Variants (DGV), or variants with incomplete penetrance without ultrasound abnormalities could lead to major difficulties in genetic counseling. In conclusion, this study describes a reproducible method for DNA extraction from only 1 ml of uncultured amniotic fluid with significantly greater quantities recovered in our study than in the Bi et al. study  [8]. This improved protocol for DNA extraction from 1 ml of uncultured AF permits array-CGH analysis in prenatal diagnosis from patients at less than 16 weeks' gestation. This technique can be applied to retrospective and prospective studies and benefits from a number of advantages: short turnaround time, absence of culture and high resolution. Until array-CGH becomes a standard technique for prenatal diagnosis, it should be considered a complement to the standard prenatal karyotyping.
EXPERIMENTAL PROCEDURES Identification of PDZ Domain Sequences in the Human Genome-Domain boundaries were obtained by cross-searching Interpro (V18), PFAM (V23), and SMART version 5. 0  (30). Each domain was extended on each side with a 10-amino-acid tail from the original protein to account for variations in border prediction and to ensure the integrity of the structure of the domain. In some cases, the sizes of these tails had to be slightly modified according to the position of the PDZ in protein (extreme end or start) or to ensure correct amplification. PDZ Domain Cloning-Primers containing Gateway ® (Invitrogen) B1 and B2 recombination tails were designed using the OSP program as described elsewhere  (31) , including a stop codon before the B2 tail (supplemental Table  S1 ). DNA fragments encoding each PDZ domain were amplified via polymerase chain reaction (Platinum HIFI polymerase, Invitrogen) from human cDNA libraries and cloned into a pDONRZeo Entry vector using the Gateway ® cloning system as described elsewhere  (32, 33) , creating a collection of PDZ Entry clones.
1 software (Bruker Daltonics, Inc. ). Protein searches were done using an in-house Mascot search engine (MatrixScience Ltd. , London, UK) against the SwissProt database 2012_02 version, using "human" for taxonomy (20,247 sequences). Mascot search results from E6 and Vangl2 pull-down on Caco-2 and/or HEK 293T cell lysates are shown in separate folders. Each folder contains the whole set of protein bands that were analyzed and identified for a peptide pull-down. For each analyzed band, a Mascot search result folder containing a protein summary report, a protein view file, and the Mascot generic file is available in E6 and Vangl2_PullDown. 7z files. Immunofluorescence Experiments-Cells grown on coverslips coated with rat-tail collagen I (Roche) were stimulated with 1 nM heregulin (HRG), fixed in 4% paraformaldehyde in PBS for 20 min, permeabilized in 0.
1% Triton X-100 for 5 min, and blocked with 10% fetal calf serum in PBS for 30 min before the addition of antibodies as described elsewhere  (37). Images were acquired using a Zeiss Axiovert 200mot microscope linked to a Meta LSM 510 confocal module operated by LSM-FCS software (Carl Zeiss MicroImaging Inc. , Jena, Germany) using a 63ϫ oil-immersion objective (plan achromatic lens; numerical aperture ϭ 1. 3). Boyden Chambers Assays-Cell migration was evaluated using 8-m pore polycarbonate membrane transwell chambers (Corning Costar, Amsterdam, NL). The bottom side of the membrane was coated with 25 g/ml rat-tail collagen I for T47D and SUM149 cells, or 5 mg/ml human fibronectin for MEF cells. Cells were serum-starved for 16 h and then plated in the top chamber. Medium with or without 1 nM HRG was added to the bottom chamber, and cells were incubated for 12 h.
RESULTS Building a Human PDZome Array-We have set up a rational approach to test the potential interactions of a given protein against an array of almost all human PDZ domains. This approach, based on a single Y2H assay, has been shown to be effective in probing the entire set of C. elegans PDZ domains for interacting proteins  (23). An initial cross-database search allowed us to identify a total of 256 PDZ domains in 145 distinct proteins, excluding isoforms sharing identical PDZ domains (supplemental Table  S1 ). The DNA fragments coding for 246 PDZ domains were successfully amplified from human cDNA libraries and cloned into the Gateway ® Entry vector (32) (supplemental Table  S1 ). Note that the PDZ domains of AHNAK2, ARHGAP23, LIMK1, SHANK3, SHROOM2, SHROOM3, SIPA1, SNTB2, SYNPO2L, and TJP1-PDZ1 are missing from the resource as a result of unsuccessful amplification.
Out of 17 PDZ proteins co-purified with the E6 peptide, 11 were also identified as direct E6 interactors by the PDZome Y2H array, among which CASK and SNX27 are newly identified E6 interactors. The results and the overlap between Y2H and biochemical approaches are presented in Fig. 1C. To test our interaction dataset further, we produced some of these PDZ domains as recombinant GST proteins (supplemental Fig. S1 ) and directly tested their interaction with the synthetic E6 peptide in vitro. In addition, we produced additional proteins: GST alone as a negative control, Scrib_3 and SNX27 as positive controls, and several additional PDZ domains present in DLG2, DLG4, and MAGI2, for a total of 25 PDZ domains. HTRF and ELISA were used to measure the interaction between E6 and the panel of PDZ domains.
1 KIAA0488 SYJ2B_HUMAN 1 P57105 NP_060843. 2 SYNJ2B, OMP25 TAX1BP3_HUMAN 1 O14907 NP_055419. 1 Tax-1, TIP1 Yes 3 USHBP1_HUMAN 3 (2) Q8N6Y0 AAH16057. 1 AIEBP, MCC2, USH1C confirmed by in vitro binding assays using HTRF or ELISA (17 out of 25) and that the testing PDZ array is robust enough to limit the false positive rate and build a high-confidence dataset. Our results are in accordance with previous work using both high-throughput two-hybrid and affinity purification assays  (45). It is commonly admitted now that the incomplete overlap observed with different techniques is mainly due to a high false-negative rate for each of the techniques used, but this overlap allows one to build a high-confidence dataset  (46). However, the non-overlapping sets increase the likelihood of finding new partners that can in turn be validated further.
7A ). When endogenous SNX27 function was inhibited through injection of an MO, neural tube closure was strongly impaired in a dose-dependent manner (Figs. 7B  and 7C ). This phenotype is typical of defective PCP signaling  (71). Furthermore, co-injection of sub-optimal amounts of SNX27 and Vangl2 MOs yielded stronger neural tube closure phenotypes than separate injections (Fig. 7D ), suggesting that these two factors cooperate to achieve proper morphogenesis. Together with the above biochemical evidence, these in vivo data confirm the importance of the newly detected interaction between Vangl2 and SNX27 and illustrate the power of our Y2H array to uncover novel interactions and associated biological functions. DISCUSSION PDZ domains are one of the most widely distributed protein interaction domains encoded in genomes.
LIN7C_HUMAN 21935 Yes No No  60  No No  56 No 56  * This work was supported by grants from  Association pour la Recherche contre le Cancer  (fellowship to E. B. and " Projet ARC" program  to MS) and  La Ligue Contre le Cancer  ( Label Ligue  (J. P. B. ) and  Ligue  fellowship to A. M. D. ), EUCAAD ( FP7 program ),  INCa  and  IBiSA ,  ANR-08-MNPS-040-01  (M. M. ), and  Region Regional Aquitaine. The  Marseille Proteomic IBiSA platform (MaP)  is supported by  Institut Paoli-Calmettes ,  INCa ,  Canceropole PACA. □ S This article contains supplemental material.
Defining the model space is an important exercise as it characterizes what is possible geologically given the modelling method, geodiversity metrics and input data set. Knowledge of the model space parameters assists definition of geological possibility, given the input data set, method of model calculation and geodiversity metrics employed. We performed the PCA in Matlab with the 'princomp' function (http://www. mathworks. com. au/help/toolbox/stats/princomp. html). The multivariate distance of the model from the centre of the data set (i. e. the model's rank within model space) is determined using Hotelling's T 2 statistic, also obtained from the 'princomp' function  (Hotelling 1931; Krzanowski 1995). The PCA is carried out in two stages. The first stage involves analysing the contact relationship, volume, depth and complexity metrics individually.
Acknowledgements We wish to thank  Itai Benjamini  for suggesting the problem to us. This paper was written during the visit of the first two authors to the Weizmann Institute in Israel. The first author was supported by the  EU Marie-Curie RTN CODY , the  ERC AG CONFRA , as well as by the  Swiss FNS  and the Weizmann institute. The fourth author is a Horev fellow and is supported by the  Taub Foundation , and by grants from  ISF  and  BSF.
A score between 0 and 3 is given for each 10-year cluster for different items: residence location, occupation, passive UV exposure, active UV exposure, and photo-protection habits. The value from 0 (none) to 3 (very) is given by considering the importance of UV exposure for the considered item. SBSH is the sum of scores for all the items and varied from 4 to 30 for volunteers in their twenties, and from 14 to 105 for volunteers in their seventies. Linked with age and phototype, SBSH is a key descriptor of the UV exposure level of each panelist. Therefore, the description  to ensuring that evaluation will be scientifically correct. We obtained these data by implementing a paired tests approach, as discussed in the Skin Aging Atlas. Volume 3, Afro-American Type  15  and other literature,  16, 17  which consists of a classification by 15 volunteers on a screen in standardized conditions of lighting, position, and calibration of each grade for a considered scale by comparing all the possible pairs of two grades.
Evaluation was carried out on pictures resized and reframed according to a standard operational procedure with editing software (Photoshop ® , version 10; Adobe Systems Incorporated, New York, NY, USA) to ensure that only the scored facial area was displayed on the screen. Pictures are presented to each expert in random order to eliminate any possibility of bias. The evaluation took place in entirely standardized conditions of lighting, position (expert is seated 1 m from the screen), and calibration (a 24-inch, 1,920 × 1,200-pixel high-resolution screen calibrated with of panel and labeling of S-S and S-P groups was performed with the following thresholds: 25 for the cluster aged 30 to 39 years, 34 for the cluster aged 40 to 49 years, 43 for the cluster aged 50 to 59 years, 51 for the cluster aged 60 to 69 years, and 60 for the cluster aged 70 to 78 years.
To this end, for each zone, one predictor domain from the five-domain ensemble has to be selected such that contiguous areas with the same predictor domain are formed. The smooth distribution of the domain centre locations together with their rather small range should facilitate this. The domain size has a higher spatial variability that could hamper the attempt of aggregating zones by same domain, but this goes along with a larger range that may compensate it to a certain degree. Acknowledgements. The authors would like to thank Météo-France for providing access to the Safran database and ECMWF for providing access to the ERA-40 data. We would like to thank Pascal Horton, Tobias Sauter and an anonymous reviewer for their constructive comments on the discussion paper that helped to significantly improve the manuscript.
Destructive measurements of leaf dimensions Groups of 62, 17, and 18 plants were selected at random from the 2007-Sp, 2010-LD, and 2010-HD crops, respectively, and destructively sampled at various times (5-11 times, according to the crop), beginning when the basal leaves were expanding and ending when all the leaves were fully expanded. We determined the number of leaflets per leaf for all leaves  (197, 201 ,   and 2010-HD). For 2010-LD and 2010-HD, we also determined the area of each leaflet by image analysis. For lateral leaflets, there was no significant difference between opposite leaflets for length, width or area, thus, for data analysis we used the mean value of length, width or area of each pair of opposite leaflets of an individual leaf.
Modeling time of the inflexion point of the expansion function The time t 0 p, k (i) of the inflexion point of the time course function of the organ k (lea for terminal leaflet, int for internode) at relative rank i of plant p was estimated from observed data as described in Fitting of Organ Expansion. We also aimed to predict the time of the inflexion point t 0 p, k (i) from the time of leaf appearance t a p (i), therefore t 0 p, k (i) was calculated as polynomials of the time of leaf appearance t a p (i) of the corresponding phytomer: t 0 p, lea (i) = δ lea, 0 + δ lea, 1 t a p (i) + δ lea, 2 t a p (i) 2 (4. 1) t 0 p, int (i) = δ int, 0 + δ int, 1 t a p (i) if i < 1 δ ped, 0 + δ ped, 1 t a p (i) if i = 1 (4. 2) The reasons for using such polynomials are given in the results section.
ACKNOWLEDGMENTS We would like to thank  P. Favre  ( UMR IRHS ) for helpful suggestions concerning the protocols and data management,  O. Douillet ,  S. Delépine , and  J. Pineau  ( UMR IRHS ) for experimental measurements,  G. Guillemain  and  G. Sintès  ( UMR IRHS ) for maintaining growth conditions,  M. Laffaire  and  C. Bouffard  ( UMR IRHS ) for plant multiplication. We also thank  J. Sappa  (scientific translator,  Alex Edelman and Associates ) for reviewing the paper for English usage. This work was supported by  Angers Loire Métropole , through a postdoctoral grant (grant number  26000046 ).
armigera COI haplotype, present in all sampled regions in India (10 sites), Africa (2 sites), Australia (3 sites), China (1 site), and Pakistan (1 site)  [25]. Two specimens were identified as Spodoptera frugiperda (KF150294, KF150295) matching HQ177352. 1 for this species (e-value: 0. 0; 99% identity (463/467)), and two were identified as S. eridania (KF150296, KF150297) that matched three existing GenBank entries for this species (HQ177329. 1, HQ177322. 1, and HQ177321. 1; e-value: 0. 0, 99% identity (465/467)); both species are established pests in the Americas. One sample was an unknown lepidopteran species with COI partial sequence (432bp, KF150298) that best matched two GenBank entries (AJ420367. 1 and AJ420368. 1) for Diachrysia tutti (Noctuidae: Plusiinae) (e-value: 3e-176, Identities: 398/432, 92%).
The availability of a global mtDNA COI and Cyt b haplotype database (  [25, 33] ; Table  S1 ) and extensive sampling and EPIC population genetic study of H. armigera from the Old World  [34]  enable us to explore the possible origins from which the founding individuals originated from. However, we have been unable to define the precise origins of the Brazilian H. armigera because they possessed mtDNA COI and Cyt b haplotypes that were prevalent in all regions of the Old World. The implications of a recent invasion of H. armigera for Brazilian agriculture are potentially serious, mainly due to its history of rapidly evolving resistance to insecticides  [22] [23] [24] , and the year round presence of potential cultivated hosts. Monitoring for pest resistance to insecticides and Bt varieties by researchers independent of technology providers has only recently begun in Brazil.
Acknowledgments The authors greatly appreciate the support of growers who permit access to crops to collect material used in our research. Expert technical assistance was provided by  Bruno B. Batista  and  Danielle Souza. Owain Edwards ,  Karl Gordon  and  John Oakeshott  (CSIRO), and  Derek Russell  ( University of Melbourne ) provided comments on an earlier draft of this manuscript that improved its clarity, and  Paulo E. Degrande  ( Federal University of Grande Dourados, Brazil ) helped improve clarity of a final version of this manuscript.
Non-transplant cohort Data from non-transplanted MDS patients with RAEB or RAEB-t were derived from the Düsseldorf registry. Only patients aged 55-69 years at diagnosis were selected. Patients who received transplantation were excluded. 137 patients were eligible for the analysis. Supportive care consisted of blood transfusions, growth factors, low dose cytosine arabinoside or in some cases intensive chemotherapy without transplantation. Diagnosis was RAEB in 100 and RAEB-t in 37 patients and the date of diagnosis was known in all cases (see table  1 ). The Düsseldorf registry is an MDS registry from a region in West-Germany which includes about 5 million inhabitants, data on morphology, treatment and death were reported on an annual basis.
Transplant cohort The transplanted patients were obtained from the EBMT database. 247 patients (male: n = 169, female: n = 78) were eligible for analysis. Disease status at diagnosis was RAEB (n = 173) and RAEB-t (n = 74). At time of transplantation diagnosis was RAEB (n = 135), RAEB-t (n = 83) and transformed secondary acute leukemia (n = 29). One-hundredthirty five patients received induction chemotherapy and 75 achieved CR, while 1 achieved only PR and 20 relapsed or progressed after initial response and 37 patients were primary refractory and in 2 patients response status was not given, so overall at time of transplantation 75 patients were in CR, 149 in non-CR and in 23 patients information about pre-treatment were missing. All patients gave written informed consent for this study. The transplant cohort gave consent to The European Group for Blood and Marrow Transplantation (EBMT) for using their data for scientific purposes.
Comparison of treatment modalities Applying the multi-state method, the overall (average) hazard ratio of the transplant group versus best supportive care, assuming proportional hazards, is estimated as 1. 29 (95% CI: 0. 95-1. 76; p = 0. 11). After adjustment for year of diagnosis as a continuous variable, the hazard ratio is the same 1. 28 (95% CI: 0. 94-1. 74; p = 0. 12). There was no evidence that the effect of year of diagnosis differed between Düsseldorf registry and EBMT database (p = 0. 79) The median overall survival from diagnosis for the non-transplant and the transplant cohort was virtually identical: 19 months, (see Figure  2 ). From Figure  2  we may infer that both populations, given the (unknown) selection mechanisms underlying the selection of patients for (non-)transplant, both groups have the same survival.
The horizontal axis measures time in years since diagnosis (on a non-linear scale). Here we see from Figure  4  that the entire detrimental effect of transplant when estimated as one average over the entire follow up time, is generated in the first year after diagnosis while thereafter the Hazard Ratio is 1 (log(HR)=0). The null hypothesis that the hazard ratio is constant over time is rejected (p= 0. 028; for the test description see  15). Further detailed analysis leads to an estimated HR of 5. 8 during the first 3 months after diagnosis and a HR of almost exactly 1 after a year. In our population with age above 55, the interval between diagnosis and transplant turns out not to be a risk factor at all (after transplant). Although in the entire transplanted population in the EBMT registry, the interval is indeed an adverse risk factor, this well-known phenomenon turns out to hold only for the younger patients: a strong and significant interaction between age at transplant and interval between diagnosis and transplant is indeed present in The EBMT Registry (data not shown) and actually totally removes the supposed effect of the interval in older patients.
This is not a matter of being right or wrong for any of these approaches: they just rely on crucial assumptions. Moreover, even with an optimal choice of statistical methodology, no valid analysis can be done without the availability of a comprehensive dataset including all variables with solid prognostic significance (such as IPSS-R). In our analysis, an early disadvantage for stem cell transplantation was probably by the non-relapse mortality of the transplant cohort which exceeded 30% at 3 years. The nonrelapse mortality has been reduced in the more recent years by reducing risk of severe GvHD and lowering the therapy-related toxicity of the conditioning regimen  [5, 6, [8] [9] [10] [11]. Furthermore, if no HLA-identical sibling is available a careful donor selection by high resolution HLA-matching lowers the risk of non-relapse mortality  [16].
For precipitation, a large set of monthly homogenized time series aggregated by department to form 51 time series that sample a large portion of France, from Météo-France, is used (HPS as homogenized precipitation series,  Moisselin et al. , 2002). HPS data are available from 1900 to 2000. In complement to this data-set that does not cover the beginning of the 21st century, the Global Precipitation Climatology Center data-set (GPCC) is also used  (full Data Reanalysis from 1901 to 2011 , Rudolph and Schneider, 2005). This data-set is not optimized for variability study and is therefore a priori less suitable than HPS to study low-frequency fluctuations. Homogenized temperature series at different stations over France from Météo-France are also used in this study  (Moisselin et al. , 2002).