dataesr/scientific-paragraphs-categorization huggingface dataset:
Integrative analysis of TRCC and gene expression reveals enrichment of translocations within the cc2B subgroup We considered whether TRCC has a distinct signature according to its fusion partners. Although the number of samples was small, unsupervised clustering performed on all samples in the MDACC and TCGA datasets revealed two subgroups that clustered independently from the partners of TRCC (Figure  5B ). Another interesting consideration was whether the MITF-related TRCC identified in the data from TCGA formed a distinct subgroup. We performed hierarchical unsupervised consensus clustering on the entire TCGA cohort. Our results were consistent with previous results by Brannon et al. (21) , which showed that ccRCC can be divided in two dominant types, ccA and ccB. In our analyses, five of the seven samples of MITF-related TRCC were associated with ccB cluster, while the two samples of TFE3-related TRCC (minor clones) were associated with the ccA cluster (Figure  5C ).
We extracted from COSMIC database the list of confirmed somatic missense mutations related to three of the seven MITF/TFE family TRCC cases identified in the TCGA, and for which data were available. The K570501 was the only case with VHL mutation. None of the two other cases had VHL, PBRM1 or BAP1 mutations. Interestingly, all three cases had mutations in chromatin remodeling genes including CHD9 in K570701, CHD7 and INO80D in K568101, and MLL3 in K554601. Thus, 75% of TRCCs (six of eight cases) display mutations in chromatin remodeling genes.
INO80D knockdown affects cell proliferation Since we identified missense mutations in IN080D in two TRCC cases, we decided to assess the frequency of INO80D mutations in ccRCC using COSMIC database. Among 334 cases assessed, only two cases had missense-substitution mutations, and one of those is the TRCC case K570701. Since the INO80 chromatin remodeling complex has not been implicated in cancer, we decided to analyze the effect on proliferation of this ATP-dependent chromatin remodeling factor, which has been demonstrated to control the amplitude of the S phase  (25). We used the HCR-59 cell line that we generated from RCC-T1 (3), which bears the INO80D mutation at both DNA and RNA levels. Interestingly, this mutation was predicted to be deleterious by Provean (cutoff=2. 5) and SIFT (cutoff=0.
Quantum-mechanical approaches for describing the ionization process In the present work, as well as those previously published, the biomolecule here considered as impacted by electrons is described via its molecular orbitals by employing the quantum chemical GAUSSIAN 03 program. Briefly, let us note that the target wave functions were computed at the Hartree-Fock level optimized at the MP2/6-31G(d) computational level, i. e. by including correlation calculations at the second order of perturbation theory MP2 and by using GAUSSIAN-type orbitals added to a double-zeta valence shell and polarization orbitals on non-hydrogen atoms. Total-energy calculations were then performed in the gas phase with the Gaussian 09 software at the RHF/3-21G level of theory. Furthermore, the ionization potentials (IP's) also calculated at the RHF/3-21G level have shown a very good agreement with the experiments.
Acknowledgments This work has been developed as part of the activities planned in the  Programme de Coopération PICS 5921  (THEOS) as well as the PEPS-PTI 2013 (ARISTOTE) of the  Centre National de la Recherche Scientifique , the project PICT 2145 of the  Agencia Nacional de Promoción Científica y Tecnológica  and the projects  PIP 1026  and  PIP 0033  from  CONICET.
Preprocedural neurologic scores consisted of an independent assessment of the mRS score for all subjects plus a Hunt and Hess scale assessment for subjects with ruptured aneurysms. Long-term follow-up is to occur by telephone annually to 5 years post-index procedure. All enrolled Matrix and Platinum Science (MAPS) Trial subject data are included in the intent-to-treat analysis except for 4 excluded subjects. One subject did not have an aneurysm, and 3 subjects were excluded at the request of the local institutional review board due to noncompliance with good clinical practice in obtaining informed consent. Overall, 626 MAPS Trial subjects were included in the intent-to-treat analyses.
An independent steering committee was responsible for overall oversight of the science and execution of the trial. Patient safety data were reviewed at regular intervals by an independent Data-Monitoring Committee. An independent Clinical Events Committee was responsible for reviewing and adjudicating all deaths and neurologic events. Monitoring and source document verification were performed by an external monitoring clinical research organization, Geelen and Geelen. On-site monitoring and source document verification of Case Report Forms against original patient records were completed for Ͼ40% of patients at the completion of the 1-year follow-up.
The stepwise method was used with P ϭ. 1 entry and exit criteria for model selection. A Student t test was used for distributions of continuous variables between the groups. Either the 2 or Fisher exact test was used to analyze binary variables according to standard statistical practice. For ordinal variables, such as the modified Raymond Scale, recanalization, and mRS scores, the Wilcoxon rank sum test was used to test the distribution between the groups. The differences between the groups were presented with the 95% confidence interval estimated by the normal approximation. For the binary outcomes, the relative risks as well as the 95% confidence intervals were also presented. All statistical analyses were performed by using SAS, Version 9. 2 (SAS Institute, Cary, North Carolina).
4 Plan NeoFluor objective lens. Cell surface area was measured upon phalloidin staining, and Tks5 staining was used as a marker for linear invadosomes. We used a custom macro (macros 1-3, available as supplemental files) with ImageJ software (W. Rasband, National Institutes of Health) that allowed measurement of all required parameters of linear invadosomes: number, size (using the Feret diameter, the longest distance between any two points), and area (A. U. ). Collagen degradation using the anti-collagen type I cleavage site antibody (rabbit, Col1 3/4 short C) was done using a custom macro (see supplemental files) with ImageJ.
SHG imaging of collagen fibers and quantification The SHG imaging system consists of a confocal TCS SP2 scanning head (Leica) mounted on an inverted microscope (DMIRE2; Leica) and equipped with a MAITAI femtosecond laser (Spectra Physics). A 10× dry objective lens (NA 0. 4; Leica) was used for applying an 820-nm excitation to the sample. The SHG signal was collected in the forward direction using the condenser (S1, NA = 0. 9-1. 4; Leica), and the two-photon-excited fluorescence (TPEF) was epi-collected in the backward direction. IRSP 715 band-pass and 410-nm infrared (IR) filters (10-nm full width at half-maximum [FWHM]) were placed before the photomultiplier tube. All image analysis was performed with the ImageJ software, using a custom macro (see supplemental files). For collagen quantification, SHG images were thresholded and the mean pixel numbers corresponding to collagen were converted to square micrometers, multiplying by a factor of 8.
2 h later, living cells were imaged using an inverted microscope (TE Eclipse; Nikon) equipped with a motorized heated and CO 2 -regulated incubator. Images were taken using a Nikon 100× Plan-Apochromat VC 1. 4 oil objective lens and captured with an EM charge-coupled device (CCD) camera (C9100-13, ImagEM; Hamamatsu Photonics) controlled by the MetaMorph 7. 0 software. A ratio image of YPF/CFP was created to represent FRET efficiency, which correlated with the activities of the G proteins. Pseudocolored ratio images were generated from images of CFP and FRET channels, as described previously  (Hodgson et al. , 2006). For quantification, the frequency of colocalization between active probe and collagen I fibrils was observed and presented as the number of cells presenting active probe on collagen I fibrils per number of cells observed (two independent experiments).
Statistical tests Data were reported as the mean ± SEM of at least three experiments. Statistical significance (P < 0. 05 or less) was determined using a paired t test or analysis of variance (ANOVA) as appropriate and performed with GraphPad Prism software (GraphPad Software). Online supplemental material Fig. S1  demonstrates the impact of type I collagen fibrils on cell degradation activity and confirms the DDR1 localization with linear invadosomes. Fig. S2  reveals DDR1 involvement in linear invadosome formation in A549 cells and shows a rescue experiment on cells depleted for DDR1 and infected with DDR1-GFP. Fig. S3  describes the DDR1 role in classical invadosome formation and activity. Figs. S4 and S5 demonstrate that the role of DDR1 in collagen degradation and cell invasion is MMP dependent but Src independent.
Chavrier and A. Blangy for helpful discussions. A. Juin is supported by a predoctoral fellowship from the Ministère de l'Enseignement Supérieur et de la Recherche. J. Di Martino is supported by a PhD fellowship from Institut National de la Santé et de la Recherche Médicale/Région Aquitaine. L. Paysan is supported by a PhD fellowship from Région Aquitaine. E. Henriet is supported by a PhD from the Ministère de l'Enseignement Supérieur et de la Recherche. This work was supported by grants from ANR-13-JJC-JSV1-0005, l'AFEF (Association Française pour l'Etude du Foie), La Ligue Nationale contre le Cancer, and Association pour la Recherche sur le Cancer. V. Moreau and J. Rosenbaum are supported by funding.
Computational procedure All structures were computed using the hybrid functional M06-2X 13 and the def2-TZVP  17  basis set for all atoms. All calculations were performed with the Gaussian 09 computational software package. 18 isualizations were done with the beta version of CYLview. 19 ransition states and energy minima were characterized by analytical calculations of harmonic frequencies. IRC-calculations were performed to confirm the connection of transition structures to reactants and products. In these bimolecular reactions, the transition states connects to an adduct between the two reactants. The most stable form of this adduct (obtained from the IRC calculations) serves as origin of energy for calculating the Gibbs energy profiles for each set of reactants. We report Gibbs energies calculated in gas phase for T = 298 K and p = 1 atm.
Acknowledgements J. H. A. thanks the  Centre for Theoretical and Computational Chemistry (CTCC)  and  NOTUR  for use of their computational resources. E. U. , O. E. and H. F. thank for support by the  Norwegian Research Council  through the  CoE for Theoretical and Computational Chemistry  (Grant No. 179568/V30 ). This work has received support from the  Norwegian Supercomputing Program (NOTUR)  through a grant of computer time (Grants No. NN4654K ). O. E. thanks the CTCC for an adjunct professorship position and the  French CNRS  and the  MENESR  for funding.
ACKNOWLEDGEMENTS We thank to  Petra Hlou  skov a for help with statistical analysis,  Dr. Ale s Pe  cinka for valuable discussions and providing us with the fas1-4 and fas2-4 seeds, and  Jana Kapustov  a for technical assistance. This work was funded by the  Czech Science Foundation  ( P501/11/0289 ,  13-11563P ), by project  CEITEC  ( CZ. 1. 05/1. 1. 00/02. 0068 ) of the  European Regional Development Fund , and project  CZ1. 07/2. 3. 00/30. 0009co-financed from  European Social Fund  and the  State Budget of the Czech Republic. This work was also partly financed by the  Centre National de la Recherche Scientifique , the  Universit e Blaise Pascal , the  Universit e d'Auvergne  and the  Institut National de la Sant e et la Recherche Medicale.
RESULTS AND COMPARISONS A 4-th order Butterworth filter is used as an illustrative example. The chosen realization to compute this = 0 δ 3 = ⌈log 2 (n f )⌉ δ 1 = min i (ℓ i ) Figure  4 : Bits representation of the sum of the example. filter is the Direct Form I: y(k) = 4 ∑ i=0 b i u(k -i) - 4 ∑ i=1 a i y(k -i). ( 44 ) Its coefficients a i s and b i s are given by the Matlab command butter(4,0. 136): b 0 = 0. 001328017792779 a 1 = -2. 871116228316502 b 1 = 0. 005312071171115 a 2 = 3. 208250066295749 b 2 = 0. 007968106756673 a 3 = -1. 634594881084453 b 3 = 0. 005312071171115 a 4 = 0. 318709327789667 b 4 = 0. 001328017792779 For implementations, the output variables y(i)s, input variables u(i)s, constants a i s and b i s are 16-bit words. Moreover, variables u(i)s are considered in this example to be in the interval  [-13; 13]  (the corresponding FPF is (4, -11)), and variables y(i)s (including result output y(k)) are known to be in the interval  [-17.
In order to fill in these gaps, event types specification is utilized to construct database queries which extracts attributes from all event logs, groups them into cases, orders them by time stamps, and then writes the result into a classical logs in separate database columns. Many approaches have been tested to extract event logs from ERP (Enterprise Resource Planning) systems such as SAP  [13]  and PeopleSoft  [14]. Consequently, as ERP systems in general provide multiple case identifiers, the majority of these approaches failed. The authors in  [12]  argue that success could only be reported when database tables are carefully selected by hand or a better view of data is semantically annotated. Another research direction is focused on discovering common structures that can be found in a variety of processes describing the Workflow Activity Patterns (WAPS).
Semantic Modelling and Reasoning Ontology is the Science that can be used to model different kinds and structure of objects, events, processes and behaviours as they happen in reality, such as learning process as described in this paper. In this section, we describe our process model using the Web Ontology Language (OWL). Below is an OWL version 2 model for our learning process, which we implemented in Protégé 4. 3 and reasoned upon using Pellet 2. Protégé OWL editor  [23]  supports Description Logic (DL) Queries and SWRL rules [26].
Future work will focus on first applying the approach described in this paper to a case study of users with a particular learning difficulty. Then, we intend to tap on the increase in recording of information related to study behaviour of individuals in many organisations that are involved in the educational sector. For this, we plan to use our technique to analyse study behaviour using a database containing detailed information about learning styles of students, as some of these educational processes are very unstructured The goal is to cover the whole spectrum of the approach presented in this paper to provide more authenticity and better support for automated learning systems.
Trial design and drug administration The study protocol was approved by the institutional review board/ethics committee at all the study sites and was conducted in accordance with ''Good Clinical Practice'' and the Declaration of Helsinki. The trial is registered in clinicaltrials. gov number NCT00424164. This was an open label, randomized, multicenter, phase I trial to assess the pharmacokinetics (PK) of lapatinib and tamoxifen combination in MBC. Patients were centrally randomized. A minimization technique allowing a maximum imbalance up to two, with no stratification factor, was used for random treatment allocation. Patients dropping out of the study for any reason before they completed the PK sampling in cycle 2 (i. e. patients who are not in the PK analysis dataset defined below), or who were not compliant with PK procedures were to be replaced (using the same order for cycle 1 as the patient who is being replaced).
The duration of dosing prior to sampling was sufficient to achieve steady state. These sampling schemes allowed reliable calculation of the pharmacokinetic parameters: Cmin (minimum concentration at the end of a dosing interval for tamoxifen, and Cmin, Cmax (maximum concentration in a dosing interval), and AUCt (area under the concentrationetime curve within a steadystate dosing interval for lapatinib, determined using standard non-compartmental methods and WinNonlin software Version 5. 1. In case of toxicity grade 3e4, one PK sample was collected for lapatinib and one for tamoxifen, before decreasing the dose. Before re-starting treatment, one PK sample was collected for lapatinib and one for tamoxifen.
Statistical analysis Data are the means ± SEM. Differences between groups were analyzed by one-way analysis of variance (ANOVA) and the Fisher test, or by the paired t test. P < 0. 05 was considered significant. A) and B) Cells were incubated at 37°C with tritiated RSV (75 μM) for the indicated times at 37°C. The uptake of labeled RSV was assessed as described in Methods. Data points are means ± SEM of at least three independent experiments each performed in triplicate wells. C) Cells were loaded for 1 h with tritiated RSV (75 μM, 37°C), the labeled medium was removed from the well and replaced by fresh unlabeled medium to measure the remaining cellassociated radioactivity, reflecting RSV efflux at the indicated time points. The values represent means ± SEM relative to uptake value observed after 1 h of treatment (maximal RSV uptake by cells).
Figure2Time-course of resveratrol uptake and efflux by control and CPT2 (patient 1)-or VLCAD (patient 3)-deficient fibroblasts. A) and B) Cells were incubated at 37°C with tritiated RSV (75 μM) for the indicated times at 37°C. The uptake of labeled RSV was assessed as described in Methods. Data points are means ± SEM of at least three independent experiments each performed in triplicate wells. C) Cells were loaded for 1 h with tritiated RSV (75 μM, 37°C), the labeled medium was removed from the well and replaced by fresh unlabeled medium to measure the remaining cellassociated radioactivity, reflecting RSV efflux at the indicated time points. The values represent means ± SEM relative to uptake value observed after 1 h of treatment (maximal RSV uptake by cells). Data are from a representative experiment among two and each point represents the mean of three determinations on separate wells.
Acknowledgements We thank  M. Jean-Paul Païs de Barros  ( Lipidomic platform INSERM UMR 866 ) for resveratrol metabolites analysis. These studies were supported by grants of the  Association Française contre les Myopathies (AFM)  and the  Agence Nationale de la Recherche  ( ANR , grant  ANR-09-GENO-024-01 ).
For the as-received sample, the polished surface was etched by an ASTM 163 etchant. This etchant contains 30 mL of water (H 2 O), 30 mL of sulfuric acid (H 2 SO 4 ), 30 mL of hydrofluoric acid (HF) and 3 to 5 drops of 30% hydroxide peroxide (H 2 O 2 ). The sample was immersed in the etchant for 20 to 40 seconds. Then the sample surface was observed in dark field mode using an Olympus BX51 optical microscope in order to determine the initial grain structure. The grain size was measured using the linear intercept method with Image J software. The grain structures in the HPT-processed samples were examined by electron backscattered diffraction (EBSD) using a JSM6500F thermal field emission scanning electron microscope (SEM). The values of the Vickers microhardness, Hv, were measured on the polished surfaces and at positions along the disc diameters separated by incremental distances of 0.
Follow-up and data collection The evaluation will be performed at seven different time points: baseline (T0 after randomization and before starting lidocaine or placebo introduction) and 40 minutes (T1), 120 minutes (T2), 12 hours (T3), 24 hours (T4), 48 hours (T5), and 14 days (T6) after baseline. The study procedure and data collection are detailed in Table  3.
Data analysis The data will be analyzed using SPSS Statistics for Windows, Version 17. 0. Chicago, USA. The patients found to be eligible but not included in the study will be described and compared with the included patients. The patients who present at least one of the following conditions will be not in the final analysis: patients inappropriately included despite not providing consent and patients who withdraw their consent. The full analysis population (including all subjects who will be randomized and will be at least evaluated at T1) will be used in the primary analysis, and the per protocol population (including all subjects who will be randomized and will not have major protocol deviations) will be used in the secondary analysis to assess the robustness of the results. No interim analysis is planned.
In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www. vls3d. com). We first introduce the field of proteinÀprotein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators.
It is indeed the first Nobel Prize given to work carried out in the field of computational biology and chemistry. The present review will primarily focus on in silico approaches (focusing somewhat more on software packages and databases reported in 2013-2014) that can assist the rational design of "drug-like" orthosteric PPI inhibitors, while the readers can find recent reviews about other types of molecules able to modulate PPIs such as peptides, macrocycles and antibodies. [21, [34] [35] [36] [37] [38] [39] [40]  Fragment-based technologies are well-suited to target PPIs but will be only briefly commented upon here as recent reviews on the topic have been reported. [37, 41, 42]  We will discuss some aspects of PPIs, from networks to structural analysis of the interface with notes on diseases and target selection.
PPI Network The explosive growth of PPI data derived from small-scale to genome-scale studies implied the development of over 100 databases and in silico services dedicated to PPIs. These many public PPI databases are important because they help the scientific community to gain new insights about PPIs (i. e. , data have to be collected, integrated, curated and translated into knowledge). At present, some databases focus on some specific species and can be very specialized, others may contain data coming from large-scale studies. Overall and at present, many databases contain redundant information. Some databases contain data about "experimentally" identified proteinÀprotein complexes (e. g. , with Y2H, gene co-expression, split ubiquitin, protein complementation assays, AP-MS…each method has strengths and weakness and there are known artifacts  [45]  ) while others are built using interactions collected from literature searches; some databases contain the 3D structures of protein complexes (please see for example  [45] [46] [47]  ).