dataesr/scientific-paragraphs-categorization huggingface dataset:
Molecular dynamics. Simulations of conformational stability on both MvicOBP3 and NribOBP3 were performed using NAMD v2. 9 and CHARMM36 force field. Proteins (chain A) were solvated with water (TIP3P model) in a cubic box with a minimum distance of 10 Å between the protein and the edge of the box. Likewise, the system was neutralised by adding Na + or Cl -randomly placed in the box. All protein preparation was carried out using Visual Molecular Dynamics software (VMD). Configuration files were prepared in order that the system was simulated under periodic boundary conditions with a cutoff radius of 12 Å for non-bonded interactions and a time step of 2 fs. Extensive energy minimisations (50000 steps) were performed followed by heating through short simulations of 1 ps at 50, 100, 150, 200, 250 and 300 K.
Long simulations were kept at 300 K and 1 bar pressure in the NTP (referred to a constant number of particles, temperature and pressure) during 10 ns for each aphid OBP. Root-mean-square deviation (RMSD) trajectory tool in VMD was used to calculate the RMSD with reference to the starting structure. When the plotted RMSD did not showed any big changes, coordinates were analysed every 50 frames to obtain the best representative structure (lowest energy). Conformational changes were visually analysed by PyMOL software. Conformational energies (i. e. bond, angles, dihedral and improper features) for both MvicOBP3 and NribOBP3 were calculated using the DCD files resulted from MD simulations through NAMDEnergy plugin provided by VMD software, and plotted for the same software. A point mutation was performed on NribOBP3 structure using PyMOL, where Val98 was replaced by Ile (i.
Quantitative PCR Standard phenol/guanidine thiocyanate extraction protocol served for the preparation of total RNA samples from early passage cell lines. An RNA sample isolated from first passage primary oral keratinocytes (ScienCell Research Laboratories, USA) was used as a calibrator in gene expression quantification. All RNA samples were reverse transcribed using the RevertAid First Strand cDNA Synthesis Kit (Thermo Scientific) according to manufacturer's protocol. Primer sequences for the analysis of the transcript level of CXXC4, DACT2, and HHIP were designed using the Beacon Designer software and further BLAST searched to minimize non-specific binding. Each primer pair covered a region spanning two distinct exons. The sequences are listed in Table  4. Quantitative real-time PCR reactions were performed in a Chromo4 thermal cycler (Bio-Rad Laboratories, USA) using the HOT FIREPol Eva Green qPCR Mix (Solis BioDyne, Estonia).
Statistical analysis The association between clinicopathological variables and the occurrence of single gene methylation was analyzed using chi-square or Fisher's exact tests. The association between clinicopathological variables and methylation index was analyzed using the Mann-Whitney U test or Kruskal-Wallis test. The analysis of the association of single gene methylation with overall survival time was performed using the F-Cox test. Multiple regression analysis allowed for the establishment of the association between methylation index and overall survival time. All the analyses were performed using the STATISTICA 10 software (StatSoft, Poland), and differences between groups were considered significant when p ≤ 0. 05.
In the present study, any females with recently spawned follicles (stages I-IV) were not selected. Subsequently, slices from the central area of the 31 selected ovaries were weighed (±0. 1 mg) and the oocytes separated using a washing process, as described by Lowerre-  Barbieri and Barbieri (1993) , and sorted by size through several sieves (from 200 to 600 µm). The oocytes were counted and their diameters measured using a computer-aided image analysis system (Image-Pro ® Plus 5. 1; Media Cybernetics, Inc. , Bethesda, MD, USA). Given that the oocyte size distribution followed a two-component mixture model, we applied an algorithm of the mixtools package  (Benaglia et al. , 2009)  for R software (www. r-project. org). This statistical procedure, which had been successfully used in a previous study  (Ferrer-Maza et al.
Data analysis The aggregated distribution of parasites leads to the concentration of a high proportion of individuals of a particular parasite in a few specimens of the host. As argued by  Rózsa et al. (2000) , it is useful to report the CI for the median intensity of infection. For this reason, the median 95% CI was calculated using the free Quantitative Parasitology 3. 0 software  (Reiczigel and Rózsa, 2005). This software, which was developed to manage the particularly left-biased frequency distribution of parasites, was also used to compare the prevalences (Fisher's exact test) and the median intensities (Mood's median test) for each parasite species throughout the different ovarian developmental phases of the hosts. As normality could not be achieved by any method, several non-parametric tests [Mann-Whitney U-test (U) and Spearman's rank correlation coefficient (r s )] were performed to assess the possible relationships between parasitism and energy reserves (I LM ) and/or fecundity (F Brel ).
Recently a new ensemble of simulations has been set up in order to simulate the state and the evolution of the Mediterranean domain. The simulations are conducted in the frame of the Mediterranean coordinated experiment Med-CORDEX  (Ruti et al. 2015)  and supported by the HyMeX program  (Drobinski et al. 2014). The simulations use the RCSMs and are intended to reproduce in a model the functioning of the Mediterranean region including for most of them the sea, the atmosphere, the land and the river components. The added-value of this new set of simulations is the use of such multi-component models with high resolution downscaled atmospheric conditions. In this paper we use the results from this new data set to characterize the mean values and long term changes of the heat budget components of the Mediterranean Sea.
Models and data used The Med-CORDEX data used in this study are RCSM outputs from six coupled models all forced laterally by the ERA-Interim reanalyses and six ocean forced models that use dynamically downscaled versions of ERA40/ERA-Interim reanalyses as surface forcing. The simulations cover the Mediterranean region and the entire data set is available from the Med-CORDEX data base (www. medcordex. eu/medcordex. php). The models used and the simulations performed are detailed in the 'Appendix'. The simulated temperature time series are compared to two observational data sets based on in situ profiles. The first set is the RIXEN gridded data set  (Rixen et al. 2005). It provides a reconstruction of the Mediterranean Sea temperature for the period 1950-2000 on a 0. 2° × 0. 2° grid using a variational inverse model.
Formal errors at each grid point were obtained from this approach  (Rixen et al. 2001 ). The second one is EN4 (EN4. 0. 1,  Good et al. 2013). It is an update of EN3  (Ingleby and Huddleston 2007)  obtained by optimal interpolation on a 1° × 1° grid. The data used cover the period 1910-2013. The basin averaged temperature and its uncertainty for these two data sets are obtained by averaging the temperature and its uncertainty at each data grid point over the Mediterranean Sea volume. The quantitative comparison between model outputs and observations use simple statistics. The period 1980-2010 common to most data sets is considered as a reference period. However some simulations start after 1980 or end before 2010. In this case the statistics are performed based on the shorter simulated period.
g. Brankart and Pinardi, 2001)  are particularly well reproduced. The average correlations with the two observational data sets (using detrended series, not shown) are 0. 55 for RIXEN and 0. 65 for EN4. On the other hand correlations are larger for the forced models (0. 60 for RIXEN and 0. 73 for EN4) compared to the coupled ones (0. 50 for RIXEN and 0. 57 for EN4). As it will be shown below this illustrates the stronger constraints set in the forced models. 4. All trends are positive and, except INSTMED06-ARPERA2, are significant at the 95 % level. The simulated trends are higher than the observed ones except those of the two INSTMED06 simulations. The low trends for these two simulations may be related to the use of the correction of atmospheric heat fluxes. Also, these simulations use a monthly climatology rather than monthly varying values when relaxing the sea surface temperature (see the 'Appendix' and Table  1 ).
Different approaches are used in the models shown in this study to simulate the Atlantic zone (see Table  1 ). In particular the internannual variability of the temperature and salinity are considered in some models whereas others use climatological values. The sea level is also used with climatological or interannually varying values but in addition some models consider open boundary conditions permitting explicit mass exchange (INSTMED06) or a mass exchange deduced by relaxing the sea level towards an observational data set (e. g. NEMOMED12). Attempts were made to investigate the impacts of the varying Atlantic conditions but due to the limitation in the number of cases no conclusive results were reached. The models used have different resolutions both in the horizontal and vertical coordinates.
The model has 43 z-coordinate levels. The atmospheric forcing also uses the downscaled ERA40 reanalyses using the ARPEGE-Climate model. SST is relaxed to the ERA40 values and monthly flux correction is applied for salinity. In the Atlantic zone, varying temperature and salinity from analysed fields are used and sea level is set to a value equilibrating the net evaporation at the basin sea surface. The initial conditions use the MEDTALAS data set. The simulation is started after a 15-year spin-up. The INSTMED06 model  (Alioua and Harzallah 2008 ) is based on the Princeton Ocean Model  (Mellor and Yamada 1982; Mellor and Blumberg 1985). The same configuration was used to study the long-term changes in the Mediterranean Sea  (Gualdi et al. 2013b ) and to investigate the impact of tide on the thermohaline circulation of the Mediterranean basin  (Harzallah et al.
1997 ) adapted for the Mediterranean basin. The model is used in its hydrostatic, implicit free-surface, partial step topography formulation. It has been implemented at a horizontal resolution of 1/12° with 72 vertical unevenly spaced z-levels. MITGCM-REMO is forced at the surface using six hourly heat and salt fluxes derived by a dynamical downscaling of the ERA40 reanalysis performed with the regional atmospheric model REMO. The simulation covers the period 1958-2004; it is initialized using the MEDATLAS monthly climatology data for January. The run has been performed using a relaxation to daily SST and monthly SSS climatological values, with relaxation times of 8 and 15 days respectively. A 3D relaxation of temperature and salinity toward climatological monthly Levitus data is applied at the Atlantic boundary.
Reynolds SST are used as background during the simulation. ENEA-PROTHEUS is an atmosphere-ocean coupled climate model for the Euro-Mediterranean region  (Artale et al. 2010). The atmospheric component is the regional climate model RegCM3 and the ocean one is a regional configuration of the MITgcm model  (Marshall et al. 1997 ). The ocean model has a horizontal resolution of 1/8 × 1/8° and uses 42 vertical z-levels. The initial conditions for the ocean are derived from a stand-alone run performed using 3D relaxation of temperature and salinity towards MEDAT-LAS climatology, with a relaxation coefficient of 5 days. At the surface, the model was forced perpetually by heat and water fluxes derived from year 1958 of the ERA40 data set. The two-way exchange through the Strait of Gibraltar is achieved by means of 3D relaxation of salinity and temperature toward the climatological monthly  Levitus (1982)  data.
Acknowledgments This work is part of the  Med-CORDEX initiative  (www. medcordex. eu)supported by the  HyMeX programme  (www. hymex. org). Naveed Akhtar acknowledges the research program MiKlip funded by the  German ministry of education and research (BMBF). G. Jordà  acknowledges a Ramón y Cajal contracts funded by the  Spanish Ministry of Economy  and the  Regional Government of the Balearic Islands. Special thanks to two anonymous reviewers for their constructive comments, which helped us to significantly improve the manuscript.
) is much smaller, the influential propagation environment can be described as simpler and better defined with respect to UHF. Considering these characteristics, deterministic ray models such as Ray Tracing (RT) or Ray Launching seem to represent the natural base to model mm-wave propagation. Being founded on a sound, albeit approximate, theory such as Ray Optics, ray-based models can be considered fairly reliable when the wavelength is small compared to the size of the obstacles and when the propagation environment is limited and therefore a detailed environment description is possible. However, very accurate building floor-plans -such as those contained in the Architectural CAD files -are necessary. For outdoor urban databases, a good accuracy can be attained through aerial stereo photogrammetry instead of using satellite images, but even in this case the error still has a lower bound of about 0.
An example of the point cloud measured at an open square of dimension 80 x 80 m 2 is shown in Fig. 9 (a). The point cloud records roughness of surfaces with 1 mm accuracy and covers objects such as lampposts, trees and human body that would be missing in many available environment databases. It is therefore well suited for high frequency channel simulations where these small irregularities in the environment may make a difference. Proper ray-based methods that can make use of such point-clouds -instead of flat polygonal surfaces -in the input database for channel simulation have been proposed recently  [68]. A comparison of measured and simulated PDPs in the open square shown in Fig. 9  (a) is presented in Fig. 9 (b). The transmitter and receiver antennas are located in one of the red and green triangles in Fig.
5%. Interestingly, our strain showed an ANI value of 99. 52% with P. acnes SK182B-JCVI (accession no. AFUN00000000. 1), recovered during the Human Microbiome Project, which is significantly above the cutoff value of 95% for species delineation  (14). Therefore, this strain is likely to be another isolate of this species. Comparing both sequences of the rpoB gene, we observed only one point mutation at nucleotide 1319 (G¡A) in strain NTS 31307302 T leading to an amino acid modification at position 440 (R440H), previously described to be involved in rifampin resistance in P. acnes  (11). This draft genome of P. namnetense NTS 31307302 T will be used for studying virulence features associated with bone infection, especially hemolysin, lipase, or hyaluronidase  (15). Accession number(s). The draft sequence of P.
At 9 years of age, his visual acuity was estimated at hand movements in both eyes. His developmental milestones were delayed. He sat at eight months of age and walked at 24 months of age. His language was delayed. His auditory evoked potentials were normal. He entered a specialized institution at the age of eight because of his apparent intellectual disability. At 8 years of age, he had a OFC of 52 cm (À0. 5 SD) height of 130 cm (þ0. 5 SD) and weight of 24 kg (À0. 5 SD). He had moderately low-set ears, but no other facial anomalies. Cranial Magnetic Resonance Imaging with spectroscopy, renal ultrasound, and transthoracic echocardiography were normal. Direct sequencing of OTX2, PAX6, RAX, SOX2, and VSX2 failed to identify any causative mutation (data not shown).
Libraries were pooled and sequenced on an Illumina HiSeq 2000 as paired-end 75 bp reads. The bioinformatics analysis of sequencing data was based on the Illumina pipeline (CASAVA1. 8. 2). Alignment by CASAVA was performed on a sequencing run to a reference genome (hg19), single nucleotide variants (SNVs) were called based on the allele calls and read depth and detected variants (SNVs & Indels). Genotypes were called at all positions with high-quality sequence bases and filtered to retain SNVs and insertion-deletions with Phred-like quality scores of >20. We focused on indel, nonsynonymous and canonical splice-site variants with minor allele frequency <0. 5% from public datasets (including dbSNP135, HapMap and the 1000Genomes Project) and in-house exome, and full-genome data. We used PolyPhen-2 and SIFT software tools to predict the functional effects of mutations.
RESULTS Using targeted high throughput sequencing of known and AM candidate genes, we identified an individual with a homozygous c. 2968-2A>T variant (RefSeq: NM_001080477), which predicted loss of function mutation in the TENM3 gene by disruption of a canonical splice site. This variant was absent from the Exome Variant Server and ExAC databases. Familial segregation studies showed that both parents and his sister were heterozygous for the c. 2968-2A>T variant, while his brother had two wild-type alleles. The RT-PCR analysis demonstrated the deleterious effect of this substitution on splicing, leading to the skipping of exon 17 of the TENM3 gene (r. 2968_3235del), predicting a frameshift and the introduction of a premature stop codon at the protein level (p. Val990Cysfs Ã 13) (Fig. 2 , and Supplementary Fig.
Thr695Asnfs Ã 5) in TENM3 in two siblings from one consanguineous family. Since only one family was reported previously, this gene was classified with an "uncertain likelihood of pathogenic significance" in a recent review  [Williamson and FitzPatrick, 2014]. We report herein a third patient bearing a homozygous putative loss of function mutation in TENM3. Interestingly, there are no homozygotes with nonsense or canonical splice mutations in the ExAC database, thus, arguing for the deleterious effect of the homozygous mutation in this gene. The mutation identified in our study leads to exon skipping of exon 17 of the gene and predicts a premature stop codon. This stop codon is located more than 50 nucleotides from the last exon-exon junction and the protein is predicted to undergo nonsense mediated decay.
ACKNOWLEDGMENTS We acknowledge generous support from the families published in this article. This work was supported by grants from the  Clinical Research Hospital Program  from the  French Ministry of Health  ( PHRC 09 109 01 ),  Fondation Maladies Rares ,  Retina France patient association, VICTA (Visually Impaired Children Taking Action ), and  MACS (Microphthalmia, Anophthalmia Children's Society ).
Statistical analysis Data are presented as mean ± SD or median (interquartile range) as required. Normality of variables was tested according the Kolmogorov-Smirnov test. Repeatedmeasures analysis of variance or Friedman's test was used to evaluate the effect of time and mPaw level. The Tukey test or the Wilcoxon test was used for intergroup comparisons. Bivariate correlations with Spearman's test for each period of ventilation were performed. All statistics and figures were performed with the SPSS 20. 0 package (SPSS, Chicago, IL, USA).
Indeed, positive studies on HFOV are limited  [16, 19]  and predate the era of low tidal volume conventional mechanical ventilation. During HFOV, there is uncertainty about the real pressure that is applied to the alveoli and therefore the distending pressure applied into the lung. Henderson et al. [12]  have previously described the use of esophageal manometry to measure P L during HFOV. With a mean airway pressure of 27 ± 5 cm H 2 O during HFOV, they measured a mean esophageal pressure of 14 ± 4 cm H 2 O and computed a mean P L of 18 ± 4 cm H 2 O. These data are  Lung Injury Score at the inclusion 3. 0 ± 0. 5 Time from ARDS to inclusion (d) 0 ± 0. 5   [20]. The P L value recorded during HFO remains below this threshold whatever the level of mPaw. One interesting result is the correlation between mPaw and esophageal pressure that we obtained; the more mPaw is set, the more Pes is measured.
Study design and population The Consortium on Health and Ageing: Network of Cohorts in Europe and the United States (CHANCES) project is a multi-country study aiming at the harmonization of data from prospective cohort studies in Europe and the US in order to produce evidence on ageing-related health characteristics and determinants of healthy ageing among the elderly in these countries  [13]. The CHANCES project includes cohorts from 14 studies across Europe and the USA. In most CHANCES cohorts, elderly are defined as those who were 60 years or older at recruitment. The CHANCES project as a whole has received ethical approval by the Hellenic Health Foundation Committee on Bioethics (HHFCB). We did not have any access to personal information regarding the participants included in this paper.
EPIC is a multicenter, prospective cohort study, where 519,978 apparently healthy volunteers from 23 centers in 10 European countries were recruited between 1992 and 2000. The EPIC-Elderly cohort includes all participants aged 60 or over at recruitment. The EPIC study has received ethical approval by the IARC Ethical Review Committee. The Rotterdam Study is a prospective cohort study among 7,983 persons aged 55 years and over who live in a defined geographic area in Rotterdam, the Netherlands. Baseline examinations were performed between 1990 and 1993. Within the cohorts that were eligible for the present study, analyses were conducted upon all subjects without missing data on alcohol and dietary intake. For some cohorts, the confounding variables education, employment status, physical activity, and smoking were missing, not available or not applicable.
Data assessment and harmonization Data in the CHANCES project have been collected within the framework of independent cohort studies, with different protocols for data collection and distinct original research foci. Data harmonization was a major task of the project and the data harmonization and conversion rules of the CHANCES project have been described elsewhere  [14]. Data standardization and harmonization procedures were largely based upon the experience from the MORGAM project  [19]  and previous experiences of project partners. Data assessment procedures included examination of availability and comparability of cohort data, questionnaires and measurement procedures used in the individual cohorts, methods for collection of data on health outcomes and of blood samples.