dataesr/scientific-paragraphs-categorization huggingface dataset:
Correlation between immunohistochemical and molecular data Correlation analyses were performed both for BRAF V600E and for other BRAF mutations (BRAF mt ) which are relevant for patients who may benefit from BRAF or MEK inhibitors molecules. The 109 BRAF V600E immunopositive samples were all detected also by molecular analysis either as c. 1799T. A (BRAF V600E ) (n = 101) or c. 1799_1800TG. AA (BRAF V600E2 ) (n = 8) mutations corresponding to a perfect match between the two techniques in informative samples. As expected, no immunostaining difference was observed between BRAF V600E and BRAF V600E2 mutations, as they encode for  Among the 116 IHC negative cases, molecular analysis showed a BRAF wild-type (BRAF wt ) status in 104 samples (89. 6%), a BRAF V600K mutation in 6 (5. 2%), a BRAF K601E mutation in 3, (2.
High Throughput Screening (HTS) C33A-2D2 cells were seeded into white, solid-bottom, tissue culture-treated, 384-well polystyrene plates at a density of 5610 3 cells per well in 25 ml media. Compounds, BMP-4 (positive control), or DMSO (negative control) were transferred with a V&P 384-well pintool at 30 nl/well to give a final compound concentration of 12 mM into individual wells. The final positive BMP-4 control concentration was 100 ng/ml and the final DMSO concentration was 0. 12%. The assay plates were then incubated overnight at 37uC, 5% CO2, 95% relative humidity followed by luminescence assay for luciferase reporter activity with SteadyLite HTS reagent. Activity data were normalized to 100 ng/ml of BMP-4 as 100% activation and 0. 12% DMSO as 0% activation. For unique hits identified in the primary screening, dose response (DR) assays were implemented in triplicate against the C33A-2D2 cells in the same HTS setting at ten different concentrations, following a 3 fold dilution scheme from 56 mM down to 2.
High Throughput Screen of a library of bioactive compounds We used the optimized assay to screen the 'bioactives' compound collection using a fixed concentration of 12 mM. BMP-4 (100 ng/mL) and DMSO (0. 12%) on each plate as positive and negative controls, respectively. Data was analyzed using a custom informatics application (RISE). The assay demonstrated good discrimination between positive and negative controls, maintained stable signal, and lacked any significant plate artifacts (Figure  3A-D ). Four compounds had activity greater than 50%. One of these, the potent CDK inhibitor kenpaullone (SJ000287948), was excluded from further study. Thirty-two compounds (1% of the unique molecules screened), with activation of BMP signaling between 40-60% relative to BMP-4 (set at 100%), were selected for further study.
This result was confirmed by increasing expression levels of ALP in a dosedependent manner, above DMSO control, providing further functional evidence that this compound is a BMP signaling activator (Figure  6B ). Quantification of ALP was performed by measuring luminescence from cleavage of a chemiluminescent substrate (Sensolyte ALP kit, Anaspec). The other chalcone, 49hydroxychalcone and the two flavonoid analogs luteolin and biochanin A diacetate did not induce ALP, as expected (negative data not shown).
Acknowledgments Authors would like to thank  CTV  staff in 'Thibar' for their permanent help in the field. Authors are so grateful to SQPOV team in  INRA-Avignon  for their excellent technical and scientific support in the lab. in particular to Mrs Line Tichit. This work is jointly financed by  Ministry of Higher Education and Scientific Research MESRS  ( UR03AGR04 ) -Tunisia, and the   Agence Universitaire de la Francophonie  -AUF  (Grant ref. G3-110/1649 ).
Statistical Analysis For quantitative imaging, results of non-Sx GD patients were compared with those of the matched controls. Comparisons between non-Sx and Sx GD patients were made for all study parameters. Non-parametric, two-tailed tests were employed on all statistical analyses. For correlations, Spearman's rho was calculated. For comparison of means and proportions, Mann Whitney U and Fisher's exact test was used. A p-value of less than 0. 05 was considered statistically significant. All analyses were performed with PASW statistics 18 (SPSS, Chicago, Ill, USA) and GraphPad Prism 5 (GraphPad Software, INC, La Jolla, CA, USA).
Participants Of the 23 included participants (16 GD and 7 controls), 21 completed all study procedures. Two patients were excluded after inclusion: one Sx GD patient was unable to participate due to complications unrelated to the study procedures; one non-Sx GD patient withdrew consent before study procedures were completed. One patient was included shortly after undergoing a partial liver resection of segment IV because of a HCC. MR-LIC measurement was technically unsuccessful initially in one patient, but was repeated successfully six months later. Due to prolonged technical problems with our TE system, examinations could not be performed in six participants during the visit in which MRI was performed and biochemical data were collected. The TE examinations were completed three to twelve months later.
I N T RO D U C T I O N A strong knowledge of the long-term variations of palaeofield intensity is essential for a complete description of the geomagnetic field and its behaviour. Absolute palaeointensity data are difficult to recover because of the high failure rate of the widely used Thellier-Thellier method  (Thellier & Thellier 1959 ). This method is the most reliable palaeointensity method because it reproduces the process of thermoremanent magnetization (TRM) acquisition by heating a sample in a laboratory field. As a result of the difficulty to obtain reliable results, the palaeointensity database is unevenly distributed throughout the geological time: seventy percent of palaeointensity data are concentrated in the last 20 Myr, whereas 35 per cent of the data span the last 1 Myr. We, therefore, lack a complete description of the geomagnetic field over many timescales, particularly beyond the last million years.
In particular, the experimental data published so far and gathered in the PINT database  (Biggin et al. 2010)  show that there is an ongoing controversy about the intensity of the geomagnetic field during the. By compiling data since Triassic time,  Prévot et al. (1990)  suggested the existence of a period of low field intensity between 100 and 200 Ma. This seemed to be confirmed by other studies:  Perrin et al. (1991)  from Jurassic continental tholeiites;  Perrin & Shcherbakov (1997)  by showing that the dipole nature of the field was preserved during the Mesozoic Dipole Low;  Kosterov et al. (1998)  in 133 Myr basalts from Brazil; and  Shcherbakova et al. (2009)  by revisiting palaeointensity results from baked contacts formed around 150 Ma in Armenia. Another study on lava flows in China formed just before the Cretaceous Normal Superchron  (124-133 Ma; Zhu et al.
The raw susceptibility data were corrected for the empty sample holder and normalized to the maximum susceptibility. U1347: 6 samples were measured and they showed 3 different behaviours. Although they all have rather low Curie temperatures between 150 and 250 • C, they showed various degrees of reversibility. The susceptibility increases strongly from low-temperature to the Curie temperature and then decreases very sharply. Sample 324-U1347A-28R-1, 5-7 cm (Fig. 5a ) is almost perfectly reversible. This indicates the presence of homogeneous Ti-rich titanomagnetites  (Kontny et al. 2003; Camps et al. 2011 ). According to these previous studies, this type of curve also corresponds to samples that are predominantly MD at room temperature, but the FORC measurements for these samples are rather characteristic of PSD grain size.
Selection criteria The representation and statistical analysis of palaeointensity data were carried out with the ThellierTool software provided by  Leonhardt et al. (2004). In this software, the basic statistical parameters are those introduced by  Coe et al. (1978)  with the modifications proposed by  Prévot et al. (1985). We adopted a standard set of strict criteria derived from those of  Selkin & Tauxe (2000)  and  Plenier et al. (2003)  to interpret the individual palaeointensity data and screen out those of poor quality. These criteria are based on three considerations: (1) NRM-TRM diagrams: Palaeointensity measurements were represented and analysed by means of an Arai diagram in which the NRM remaining is plotted against the TRM acquired after each pair of heating experiments  (Nagata et al.
VDM values Palaeointensity values must be converted into VDM to be compared with data from other locations, using the inclination measured at this site. The directions obtained from the palaeointensity experiments show a very large scattering, and the averaging is not sufficient. Therefore we prefer to use inclinations measured from shore-based thermal and alternating-field demagnetizations at Doshisha University, Kyoto. We obtain weighted averages VDM values of 4. 9, 5. 1 and 4. 8 × 10 22 Am 2 , respectively, for each of the three lava flows. We can compare these values with other values obtained only with the Thellier-Thellier method, from the PINT database  (Biggin et al. 2010). When plotting all the available data dated between 110 and 160 Ma (which, therefore, includes the beginning of the Cretaceous Normal Superchron) it is obvious that there is a very large discrepancy in between data from rocks of the same age range, and even within the same study (Fig.
Computational Thermodynamics is based on physically realistic models to describe metallic and oxide crystalline phases as well as the liquid and the gas in a consistent manner  [1]. The models are used to assess experimental and theoretical data for many different materials and several thermodynamic databases has been developed for steels, ceramics, semiconductor materials as well as materials for nuclear applications. Within CEA a long term work is ongoing to develop a database for the properties of nuclear fuels and structural materials [2]. An overview of the modeling technique will be given and several examples of the application of the database to different problems, both for traditional phase diagram calculations and its use in simulating phase transformations. The following diagrams (Fig.
Computational Thermodynamics: Assessment 2 All kinds of data that can be calculated from the Gibbs energy of the system can, and must, be used to fit the model parameters. O/U T=2700 K T=2600 K T=2500 K T=2400 K T=2300 K T=2250 K T=2200 K T=2100 K T=2000 K T=1950 K T=1900 K T=1800 K T=1700 K T=1600 K T=1500 K T=1400 K T=1300 K T=1200 K T=1100 K T=1000 K T=900 K T=800 K All kinds of data that can be calculated from the Gibbs energy of the system can, and must, be used to fit the model parameters. O/U T=2700 K T=2600 K T=2500 K T=2400 K T=2300 K T=2250 K T=2200 K T=2100 K T=2000 K T=1950 K T=1900 K T=1800 K T=1700 K T=1600 K T=1500 K T=1400 K T=1300 K T=1200 K T=1100 K T=1000 K T=900 K T=800 K At CEA there is an ongoing project to develop the fuelbase database for nuclear fuels, fission products, and structural materials.
Computational Thermodynamics: Assessment 2 All kinds of data that can be calculated from the Gibbs energy of the system can, and must, be used to fit the model parameters. O/U T=2700 K T=2600 K T=2500 K T=2400 K T=2300 K T=2250 K T=2200 K T=2100 K T=2000 K T=1950 K T=1900 K T=1800 K T=1700 K T=1600 K T=1500 K T=1400 K T=1300 K T=1200 K T=1100 K T=1000 K T=900 K T=800 K At CEA there is an ongoing project to develop the fuelbase database for nuclear fuels, fission products, and structural materials. In recent assessments results from DFT calculations have been included for the formation of defects and metastable compounds. Diagrams calculated from fuelbase  Modelling ionic systems 2 The C1 structure, CaF 2 , is the same structure as MO 2 in nuclear fuels modelled with several metallic valencies and defects on the oxygen sublattice and interstitial oxygen.
We developed a new phage-display based approach, the Large Fragment Phage Display (LFPD), that can be used for mapping conformational epitopes on target molecules of immunological interest. LFPD uses a simplified and more effective phage-display approach in which only a limited set of larger fragments (about 100 aa in length) are expressed on the phage surface. Using the human HER2 oncoprotein as a target, we identified novel B-cell conformational epitopes. The same homologous epitopes were also detected in rat HER2 and all corresponded to the epitopes predicted by computational analysis (PEPITO software), showing that LFPD gives reproducible and accurate results. Interestingly, these newly identified HER2 epitopes seem to be crucial for an effective immune response against HER2-overexpressing breast cancers and might help discriminating between metastatic breast cancer and early breast cancer patients.
The sera from MBC recognized 3 epitopes on fragments hum1, hum7 and hum11 (Figure  2a ). Interestingly, the sera from EBC recognized the same 3 epitopes recognized by sera from MBC (hum1, hum7 and hum11), plus an additional epitope, positioned on hum9 fragment (Figure  2a ). The possibility to use the epitope contained in fragment 9 for discriminating between MBC and EBC could be of clinical interest and warrants further analysis. Finally, we used the PEPITO software analysis for the prediction of conformational epitopes  [22]  on the entire hHER2-ECD molecules (Figure  2c ). Remarkably, the PEPITO analysis predicted the presence of the same epitopes identified by ELISA screening of breast cancer patients. In particular, PEPITO predicted conformational epitopes corresponding to the four epitopes present on fragments hum1, hum7, hum9 and hum11 of the human LFDP, therefore validating LFDP method.
The screening with sera of non-tolerant mice permitted to identify conformational epitopes corresponding to fragments rat1, rat2, rat9 and rat11. This result was confirmed using the sera obtained from tolerant mice, although with a lower reactivity. In addition, sera from mice vaccinated with a truncated form of rat HER2, encoding the TM domain associated with amino acids 311 to 654 of the EC domain (EC4)  [11] , showed a strong reactivity for fragment rat6, other than for rat9 and rat11, and, as expected, ignored the first part of the molecule (Figure  2b ). The strong reactivity toward rat6 may be explained by an immunodominant effect caused by epitopes that could be present in the first part of the molecule. Furthermore, all the conformational epitopes recognized by the polyclonal antibodies present in the sera of vaccinated mice corresponded to the epitopes predicted by PEPITO software analysis (Figure  2d ).
Molecular modeling and conformational epitope prediction All the calculations have been carried out on MacPro (Apple, Cuppertino, Ca) workstations, using the Discovery Studio 2. 1 (Accelrys, Inc. ) software package. The rat 1-11 fragment structures were constructed with homology modeling using the extracellular portion of rat HER2 (1n8yc) as template and Swiss-Model Server with SPDBV program suite 3. 0. The structures were then submitted to minimization cycles, using a Newton-Raphson minimization algorithm with at least 5000 iterations. The minimization cycles were repeated until energy global minimum was reached. The models obtained were checked using standard validation programs as PROCHECK e VERIFY_3D. The prediction of conformational epitopes has been carried out on the proteins human HER2 (1n8z) and rat HER2 (1n8y).
Flow cytometric analysis Indirect immunofluorescence assay was performed on live cells (HEK293 stable transfected with human HER2) with human sera. Cells were incubated with sera (1:200) for 30 min at 37uC, washed twice, and incubated with goat anti-human IgG (1:100) (Kirkegaard & Perry Laboratories, Gaithersburg, MD, USA) for 30 min at 0uC. After a final wash, cells were suspended in PBS. Fluorescence was analyzed by FACScalibur with CellQuest and FLowJo software (Becton Dickinson, Mountain View, CA, USA). Epitope-based DNA vaccines pFUSE-mIgG2A-Fc2 (Invivogen, San Diego, CA) was used as backbone for the construction of epitope-based DNA vaccines. To anchor the encoded protein to the plasma membrane, a synthetic oligo codifying the TM domain of rat HER2 was cloned in frame in pFUSE-mIgG2A-Fc2 using NheI restriction enzyme (Celbio, Milan, Italy).
They studied bubbly and sluggish flow pattern at low heat flux and thin annular and churn flows at high heat flux using three different mass fluxes. Fang et al. [8]  conducted a comparative study of existing correlations for flow boiling heat transfer in microchannels. They collected 1158 data points of flow boiling heat transfer of R134a in minichannels and reviewed 18 flow boiling heat transfer correlations. They found that no correlation has satisfactory accuracy and that more efforts should be made to develop better correlations for boiling in minichannels. In addition, the recent development of nanotechnology materiel led to intensify the heat transfer coefficient in microscale devices by using suspended metallic nanoparticles in conventional working fluids. Most studies published in the literature on nanofluids heat transfer have reported that using nanoparticles with average sizes below than 100 nm in traditional working fluids increases the thermal conductivity of fluids and enhances heat transfer coefficient  [9, 10].
Experimental procedure, data reduction, and uncertainties For all tests, the heat exchange surface was oriented vertically. The liquid in the tank was first preheated to the required temperature. The liquid flow rate was adjusted with a regulating valve at the desired value. All temperatures were recorded during time. The total power supplied to the heater source was set at the maximum value. When the boiling phenomenon had occurred and the temperatures have reached almost a steady state, the values of the liquid flow rate or the heat flux of the power source were varied and the same procedure was repeated. For each fixed experimental condition, the test section was heated and the temperatures were monitored continually. Experiments were performed with deionized water and silver-water nanofluids.
, 2012)  if d 18 O in phloem OM reflects the oxygen isotopic signature of leaf water or if changes in d 18 O during phloem loading and/or transport can be accounted for. Moreover, if phloem OM d 18 O does not directly reflect the leaf water oxygen isotope signature, interpretation of tree ring d 18 O data would need to be reconsidered as cellulose is produced from the phloemtransported sugars.
Meteorological measurements Air temperature (T a ), vapour pressure deficit (VPD) and photosynthetically active radiation (PAR) were determined above the canopy at the Hartheim, Hesse II and Tumbarumba sites. For details of the instrumentation see  Holst et al. (2008) ,  Granier et al. (2000)  and  Leuning et al. (2005) , respectively. At the L€ otschental sites, the meteorological parameters were determined 2 m above ground in open patches close to the trees examined. All data are averages over a 30-min period.
Phloem metabolite analysis Samples (250 ll) of the bulk phloem exudate of pine, oak and beech were dried under vacuum and derivatisation (methoxyamine and silylation with N-methyl-N-trimethylsilylfluoroacetamide) as well as GC-MS analysis for metabolite profiling were performed without further purification according to  Erxleben et al. (2011). The derivatised phloem samples were injected into a GC-quadrupole MS system (GC: 7890A; MS: 5975C; Agilent Technologies, Waldbronn, Germany) operating in electron impact ionization. Data were deconvoluted and peak areas quantified using the AMDIS software (http://chemdata. nist. gov/ mass-spc/amdis/). Peak identifications were carried out by matching retention indices and mass spectral similarity against the NIST 05 mass spectral library (http://www.
nist. gov/srd/nist1a. cfm) and a user-defined metabolite library based on the Golm metabolome database (  (Kopka et al. , 2005) ; http://csbdb. mpimp-golm. mpg. de/csbdb/gmd/msri/gmd_msri. html). For the 25 most abundant identified compounds calibration curves were made with external standards to quantify metabolite concentrations.
Acknowledgements A. G. acknowledges support by the  Deutsche Forschungsgemeinschaft (DFG)  under contract numbers  GE 1090/8-1  and 9-1. Meteorological data for the Hartheim and Tumbarumba site were provided by  Helmut Mayer  and  Ray Leuning , respectively. G. D. F. acknowledges support from the  Australian Research Council  through  DP110105376. Data development in the L€ otschental was supported by the  Swiss National Science Foundation  ( 200021_130112  'ISOPATH'; 200021_121859 ' INTE-GRAL '). We thank  Matthias Saurer  for carrying out part of the leaf water extraction.
Introduction Wireless communication systems may offer high data bit rates by achieving a high spectral efficiency using Multiple-Input Multiple-Output (MIMO) techniques. MIMO systems make use of antenna arrays simultaneously at both transmitter and receiver sites to improve the capacity and/or the system performance. However, the transmitted electromagnetic waves interact with the propagation environment. Thus, it is necessary to take into account the main propagation parameters during the design of the future communication systems. The current communication standards indicate a clear trend in industry toward supporting MIMO functionality. In fact, several studies published recently present systems that reach a MIMO order of 8×8 and higher  [1]. This is made possible by advances at all levels of the communication platform, as the monolithic integration of antennas  [2]  and the simulator platforms design  [3].
Each block RAM has a memory of 64 (kB), thus 512 (kbits). The impulse responses are quantified on 16 bits, therefore, up to 32,000 MIMO profiles can be supplied in the RAM blocks. Each environment needs 4 blocks RAM for the power of the impulse responses and 4 blocks for the delays, which is a total of 8 blocks RAM. Reading the file can be done either from USB or PCI interfaces, both available on the used prototyping board. The PCI bus is chosen to load the profiles. It has a speed of 30 (MB/s). In addition, this is a bus of 32 (bits). Thus, on each clock pulse two samples of the impulse response are transmitted. The Nallatech driver in Figure  5  provides an IP sent directly to the "Host Interface" that reads it from the PCI bus and stores these data in a FIFO memory. The module called "Loading profiles" reads and distributes the impulse responses in "RAM" blocks.
A2 Model #1 GENLN2-DISORT (G. Myhre) GENLN2-DISORT is the GENLN2  (Edwards, 1992)  lineby-line (LBL) model coupled to a discrete-ordinate method (DISORT;  Stamnes et al. , 1988)  for calculation of radiative fluxes. The model has been used for radiative transfer calculation in the solar spectrum previously  (Myhre et. al. , 2002)  and in an intercomparison study  (Forster et al. , 2011). The GENLN2 LBL code is updated with absorption data from the HITRAN-2008 database  (Rothman et al. , 2009). Absorption by H 2 O, CO 2 , O 3 , O 2 , and CH 4 has been included in the simulations. The spectral resolution in the computations was 0. 02 cm -1. The extraterrestrial spectral solar irradiance had a 1 nm resolution from  Lean et al (2005)  in simulations and the full spectral region considered has been from 0.
A3 Model #2 RFM DISORT (RFMD; E. Highwood, C. Ryder, B. Harris) RFM DISORT is the Reference Forward Model (RFM), a line-by-line radiative transfer model, coupled to a discrete ordinate method (DISORT;  Stamnes et al. , 1988)  for scattering calculations. RFM has been developed at Oxford University, UK (http://www. atm. ox. ac. uk/RFM/) and is based on the GENLN2 model  (Edwards, 1992). The spectral resolution used was 1 cm -1 , covering wavelengths from 0. 2 to 10 microns with 4 streams in DISORT. The HITRAN 2004 database  (Rothman et al. , 2005)  is used for gaseous absorption coefficients.