dataesr/scientific-paragraphs-categorization huggingface dataset:
Germline mutations, if any, and relevant incidental findings are included as well. Additionally, the clinician (on behalf of the patient and family) can request the comprehensive sequencing raw data. The SPECTA infrastructure also allows for long-term follow-up and collection of additional clinical data including patientreported and neurocognitive outcomes. Such variables have not been selected for the AYA pilot project, but could be easily added in a follow-up cohort. The pan-European nature of the project, the comprehensive molecular analysis, and the virtual central pathology review process combine into a complex workflow (Fig. 1 ) with subsequent operational challenges. The collaboration between three major academic cancer research organizations in Europe-the UK National Cancer Research Institute, EORTC and DKFZ-has been a major facilitator in mastering these challenges.
2015) , and superluminous SN candidates  (Renault-Tinacci et al. 2018). The possibility of CR acceleration in young SNe motivates the search for signatures of TeV gamma-ray emission. Such a detection could be indicative of pion production (and subsequent decay) arising from acceleration of CR protons and nuclei beyond TeV energies. We analysed H. E. S. S. observations towards nine serendipitously observed cc-SN events and towards the nearby event SN 2016adj, which triggered Target of Opportunity (ToO) observations. The data selection and analysis details are presented in Section 2. 2. Upper limits on gamma-ray flux from the direction of the CR source candidates are shown in Section 2. 4 before constraints on the local environment of these SNe are derived in Section 3.
Serendipitous sample The online IAU 2 Central Bureau of Astronomical Telegrams (CBAT) supernova catalogue 3 was used to compile an initial, extensive list of SN candidates. The NASA/IPAC 4 Extragalactic Database (NED) 5 was then queried for the redshift of each SN host galaxy to compile a short-list of SNe with redshift z < 0. 01 to ensure that only nearby SNe were considered. If a host galaxy was not stated for a given SN in the CBAT SN catalogue, the SN was discarded from the short-list. The H. E. S. S. database was then queried for observations in the direction of each short-listed SN, within a time range spanning seven days prior to a year after, the SN discovery date. This time range was chosen to account for likely delays between the dates of the discovery and the outburst to be sure to include the peak energy suggested to occur a few days  (Marcowith et al.
2014 ) after the SN event, but potentially lasting months. After reaching this peak emission, the gammaray flux is predicted to decline proportionally to 1/t, as we will discuss later. All H. E. S. S. data taken from December 2003 until the 31st of December 2014 were searched, and all SNe presented on CBAT on the 30th of March 2015 were considered. We removed type Ia and Ic SNe from our sample, because these types are unlikely to occur in a CSM density large enough to accelerate CRs up to TeV energies (see e. g. Smith 2014). (Marples et al. 2016). It appeared in the Centaurus A (Cen A, NGC 5128) galaxy, a few arcminutes from its nucleus, at a distance of ∼3. 8 ± 0. 1 Mpc  (Harris 2010, and references therein). The SN type was soon suggested to be of type IIb by  Stritzinger et al. (2016) , because of the presence of a Hα line, and later confirmed by  Thomas et al.
Data Analysis Standard quality cuts were applied to remove bad-quality data from each data set: observation runs with a minimum of three telescopes, a fraction of broken pixels < 10 % and trigger-rate fluctuations < 30 % were kept (see  Aharonian et al. 2006). Then, for each target, the selected data were analysed using the Model analysis framework outlined in de  Naurois & Rolland (2009). For a given SN, an ON-region is selected centred on the SN position, and multiple OFF regions are selected at the same offset as the ON region, using the Reflected Background method  (Berge et al. 2007 ). The ON region radius is 0. 1 deg for the serendipitous sample and 0. 08 deg for SN 2016adj. Results were confirmed by an independent calibration and analysis chain using the ImPACT framework  (Parsons & Hinton 2014)  with standard quality cuts and the same Reflected Background method.
E. S. S. non-detection of this apparent SN 1993J twin. Van Dyk et al. (2016)  proposed that SN 2016adj originated from a progenitor with a lower luminosity than the SN 1993J progenitor, suggesting that the explosion might be of compact IIb-type. This claim, however, was later disfavoured by  Sugerman & Lawrence (2016). Further multi-wavelength observations will weigh in on the nature of this object, and an analysis of radio and X-ray data is forthcoming  (Hajela at al. in prep. ). For the rest of the sample, in addition of being Type II SNe (mostly IIP), the nine selected candidates did not have any strong indication of the conditions necessary for significant early CR acceleration. Several of the SNe have been studied at various levels of detail, with results consistent with our study. Radio and X-ray observations are of prime interest to check the consistency of our result, as they can provide additional constraints on the wind parameters.
Conclusion We selected a sample of nine type II SNe that were observed by chance with H. E. S. S. within one year after the SN event, and in addition we triggered ToO observations on SN 2016adj. No significant gamma-ray signal has been detected from any of these ten SNe and we derived flux upper limits of the order of 10 -13 TeV cm -2 s -1. This result is amending previous efforts (Lennarz & the H. E. S. S. Collaboration 2013) and complements other recent non-detections, namely the Fermi-LAT studies of type IIn SNe at GeV energies  (Ackermann et al. 2015) , the upper limit at TeV energies established by the MAGIC collaboration for the closest type Ia SN 2014J  (Ahnen et al. 2017) , and a recent search for GeV emission from super luminous SNe using Fermi-LAT data by  Renault-Tinacci et al. (2018).
Acknowledgements The authors would like to thank  R. Margutti  for her useful input as well as the anonymous referee for his/her constructive comments. R. Simoni  thanks  M. Renzo  and  M. Zapartas  for helpful discussions. The support of the  Namibian authorities and of the University of Namibia  in facilitating the construction and operation of H. E. S. S. is gratefully acknowledged, as is the support by the  German Ministry for Education and Research (BMBF) , the  Max Planck Society , the  German Research Foundation (DFG) , the  Helmholtz Association , the  Alexander von Humboldt Foundation , the  French Ministry of Higher Education, Research and Innovation ,  the Centre National de la Recherche Scientifique  ( CNRS/IN2P3  and  CNRS/INSU) , the Commissariat à l'énergie atomique et aux énergies alternatives (CEA), the  U.
Experimental details The data for the present study have been obtained from the two experimental campaigns conducted at the Institute Laue-Langevin in Grenoble. During the first one, named EXILL  [5] , the reactor neutron beam, with a flux of 10 8 /(s×cm 2 ), induced fission reactions (n,f) of the 235 U and 241 Pu targets. Gamma rays emitted from the fission product were detected by an array which consisted of eight HPGe clover detectors and 16 LaBr3(Ce) FATIMA scintillators  [6] , mounted about 15 cm from the target position. The events were registered by using a fully digital acquisition system in a triggerless mode, with 100 MHz clock. For the gamma spectroscopy measurement, the LaBr3 detectors where replaced by additional 6 large HPGe coaxial detectors and 2 clovers. The success of the EXILL campaign triggered the development of a permanent gammaspectroscopy experimental setup at ILL.
The new array, called FIPPS, (FIssion Product Prompt γ-ray Spectrometer)  [7]  consists of up to 16 HPGe clovers. For the new fission runs, 233 U and 235 U active targets have been used  [8]. Scintillation light in the target cell provides precise information about the time when the (n,f) reaction occurs, giving a clean fission tag. Data from the FIPPS campaign were partially sorted and included into the results presented in the current work.
Conclusion The hypothesis that large deformation might occur also in yttrium isotopes with N < 60 is in line with recent results from the EXILL campaign, where, for the first time, a rotational band in N = 57 nucleus has been suggested  [4]. According to this interpretation, deformed structures start to be present in lighter nuclei at high excitation energy and become dominant and yrast for isotopes with N ≥ 60. This scenario calls for further studies of the high-spin structures in the neutron-rich Y isotopes. The issue is being investigated taking advantage of new high quality and high statistic data from the FIPPS campaign, where a fission trigger based on an active scintillating target is used.
NUMERICAL RESULTS In this section, we study the sensitivity of the model to parameter changes. First, we study the interactions of the model parameters on the small-size instances, and then, we launch the model on the data provided by EDF. We consider one type of tariff: Off-Peak / Peak as it is one of the most subscribed tariffs. The price per kWh of HC hour is cheaper than one of HP hour. The computational experiments were performed on a PC Intel Xeon X5675, 3 GHz, RAM 96 GB running under the Windows Server 2008 operating system. We use ILOG CPLEX 11. 0 as an optimization mixed integer programming solver.
The variability of the vertical distribution of aerosols around Henties Bay during the later period is assessed using lidar and dropsonde measurements acquired over the ocean, as detailed in Sect. 4. In Sect. 5, we investigate the different origins and transport pathways of aerosols in the free troposphere towards Henties Bay during the three periods. The last section is dedicated to the summary and conclusion. The description of the ground-based lidar is given in Appendix A, together with the calibration and data inversion processes.
Ground-based lidar The ALS lidar measurements were carried out continuously between 22 August and 13 September 2017. The data coverage for aerosol study is low because of the quasi-ubiquitous presence of marine stratocumulus and fog during a large part of the observation days. The fog opacity was often such that the laser beam was fully attenuated after a few hundred metres. We therefore considered average profiles taken during periods when no low-level clouds or fog events are observed, i. e. between about 1 and 4 h on a given day (see Table  1 ). The description of the lidar is given in Appendix A, together with the calibration and data inversion processing.
Modelling The meteorological patterns are studied using meteorological fields provided by the 6-hourly operational analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF; http://apps. ecmwf. int/datasets/, last access: 23 November 2019,  Dee et al. , 2011). We also use the near-real-time analyses of atmospheric dynamics and aerosols from the Copernicus Atmosphere Monitoring Service (CAMS; https://atmosphere. copernicus. eu/, last access: 23 November 2019). The calculations for synoptic analysis are computed on a 0. 75 • horizontal regular grid. Daily means are computed by averaging time steps at 03:00, 09:00, 15:00 and 21:00 UTC of daily forecasts initialized at 00:00 UTC. For local analyses, the meteorological wind fields are computed by using 1 h data on a 0. 25 • horizontal regular grid from the fifth ECMWF Reanalysis (ERA5; https://www.
ecmwf. int/en/forecasts/ datasets/archive-datasets/reanalysis-datasets/ERA5, last access: 23 November 2019;  Hoffmann et al. , 2019). The back-trajectory analyses are based on the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model  (Draxler and Rolph, 2014; Stein et al. , 2015). The wind fields used as input from the HYSPLIT model are from GDAS (Global Data Assimilation System; http://www. ncep. noaa. gov/, last access: 23 November 2019) at 0. 5 • horizontal resolution. The isentropic ensemble mode with 24 individual back trajectories is used to take into account the transport trajectory spread associated with the wind field variability around the trajectory's starting point. Using different modelling approaches also allows the consistency of results to be verified. 3 Temporal evolution of the aerosol properties and vertical distribution over Henties Bay.
To the authors' knowledge, this is the first time that the evolution of the optical properties of aerosols in the FT over coastal Namibia is characterized, in relation to different transport regimes. The main contribution of the BBA from Angola and the arguably smaller contribution of the South American anthropogenic fires and/or wildfires to the atmospheric aerosol composition over the Namibian coast were shown. The synergy between active and passive remote sensing observations performed from ground-based and spaceborne platforms, together with back-trajectory analyses, was essential to provide these conclusions. Data availability. The aircraft and ground-based data used here can be accessed using the AEROCLO-sA database at http://baobab. sedoo. fr/AEROCLO/ (last access: 6 December 2019).
An embargo period of 2 years after the upload applies. After that, external users can access the data in the same way as AEROCLO-sA participants before that time. Before the end of the embargo period, external users can request the release of individual datasets. It is planned for AEROCLO-sA data to get DOIs, but this has not been carried out for all datasets yet. The back-trajectory data can be obtained upon request to the first author of the paper. Appendix A: Ground-based lidar analysis -link with space-borne lidar observations A1 Description of the ground-based lidar The ground-based lidar system used at the Henties Bay site is the ALS450 ® lidar manufactured by Leosphere and initially developed by the Commissariat à l'Energie Atomique (CEA) and the Centre National de la Recherche Scientifique (CNRS)  (Royer et al.
A2. The dates were chosen to be representative of the dataset of vertical lidar profiles encountered during the AEROCLO-sA campaign. The curves in black are the ABC profiles and those in red correspond to the molecular backscatter coefficient computed using ERA5 data. We note that in the top of the profiles there is a very good agreement that ensures that the lidar is well aligned. The area comprised between the black and red curves corresponds to the contribution of atmospheric aerosols and, in the upper part of the profiles, to that of optically thin clouds (Fig. A2c  and d ). The aerosol content increases rapidly between 22 and 28 August, showing a significant evolution of aerosol contributions in the free troposphere (FT) between 1 and 5 km a. m. s. l. It is notable that the vertical profiles of the ABC vary little during the averaging period; the average profiles are therefore quite representative of the state of the atmosphere for all the considered periods.
Acknowledgements. The authors would also like to thank the  AERIS data centre  for their support during the campaign and managing the AEROCLO-sA database. The research leading to these results has received funding from the  European Union 's  Seventh Framework Programme  ( FP7/2014-2018 ) under EUFAR2 contract no. 312609. Airborne data were obtained using the aircraft managed by SAFIRE, the  French facility  for airborne research, an infrastructure of the  French National Center for Scientific Research (CNRS) ,  Météo-France  and the  French National Center for Space Studies (CNES). The authors would like to thank  Frédéric Blouzon  and  Abdel Abchiche  ( DT-INSU ) as well as  Pascal Genau and Mathilde van Haecke (LATMOS)  for their support in operating and processing the LNG data. The invaluable diplomatic assistance of the  French Embassy in Namibia , the administrative support of the  Service Partnership and Valorisation of the Regional Delegation of the Paris-Villejuif Region of the CNRS  and the cooperation of the  Namibian National Commission on Research, Science and Technology (NCRST)  are sincerely acknowledged.
Financial support. This work was supported by the  French National Research Agency  under grant agreement no. ANR-15-CE01-0014-01 , the  French national programme LEFE/INSU , the  Programme national de Télédetection Spatiale  (PNTS; http:// programmes. insu. cnrs. fr/pnts/,last access: 23 November 2019) grant no. PNTS-2016-14 , the  French National Agency for Space Studies (CNES)  and the  South African National Research Foundation (NRF)  under grant  UID 105958. Review statement. This paper was edited by  Paquita Zuidema  and reviewed by  Michael Diamond  and one anonymous referee.
Cell lysates from WT, CSE À⁄À and WT MEFs treated with D-Cys (2 mM, 1 h) were compared. Results are presented as a mean ± SD from 3 independent experiments. (M) Ribbon structure of two subunits from human MnSOD (PDB: 1pl4), highlighting the cysteine residues and manganese containing active site. (N) Persulfidation of MnSOD protects it from the H 2 O 2 -induced inactivation. SOD activity was measured using cytochrome c as a reporting molecule, which is reduced by the superoxide generated from the xanthine/xanthine oxide system. Results are presented as a mean ± SD from 3 independent experiments. WT cells resulted in increased persulfidation of DJ-1 (in 15 and 30 min) and increased sulfenylation and sulfonylation (PSO 3 H) after 30 min. However, in CSE À⁄À cells already low PSSH levels continued to decrease in cells treated with H 2 O 2.
04 mg/ml, T0198, Sigma Aldrich); (3) GAPDH (0. 04 mg/ml, G8795, Sigma Aldrich); (4) HSP70 (0. 04 mg/ml, ab5439, Abcam); (5) KEAP1 P586 (0. 0062 mg/ml, 4678, Cell Signalling); (  6 ) eNOS (0. 0025 mg/ml, 32027, Cell Signalling); (  7 ) Parkin (0. 04 mg/ml, sc-136989, Santa Cruz Biotechnology); (8) SOD-2 (0. 04 mg/ml, sc-137254, Santa Cruz Biotechnology); (9) anti-TST (0. 04 mg/ml, GTX114858, GeneTex); (10) anti-SQR (0. 04 mg/ml, HPA017079, Sigma Aldrich). For experiments with lysates of HeLa cells treated in a time-dependent manner with EGF and labeled as described above. The following antibodies were used: (1) PTEN (1:1000, sc-7974, Santa Cruz Biotechnology,); (2) PTP1B (1:1000, sc-133259, Santa Cruz Biotechnology); (3) SH-PTP2 (0. 04 mg/ml, sc-7384, Santa Cruz Biotechnology); (  4 ) EGFR (0.
Immunoblotting Untreated or specifically treated cells were washed twice with cold PBS and harvested in RIPA lysis buffer supplemented with 1% protease inhibitor. Cells were scrapped, and lysates were collected, homogenized with syringe and needle, and centrifuged at 30,000 3 g for 5 min at 4 C. Clear lysate was transferred to a new tube. Protein concentration of lysate was determined using the DC assay (BioRad). Protein samples were resolved by SDS-PAGE and transferred to a nitrocellulose membrane (GE Healthcare). Primary antibodies used included: (1) CBS (1:1000, sc-133154, Santa Cruz Biotechnology), (2) MPST (1:4000, HPA001240, Sigma Aldrich), (3) CTH (MEF cells, 1:4000), (4) CTH (HeLa cells, 1:1000, sc-374249, Santa Cruz Biotechnology), (  5 ) p-ERK (1:1000, sc-7383, Santa Cruz Biotechnology), (6) total-ERK (1:1000, sc-271269, Santa Cruz Biotechnology), (7) DJ-1 (1:250, sc-55572, Santa Cruz Biotechnology), (8) DJ-1 Oxidized At C106 (1:1000, HCA024, BioRad), and (9) b-tubulin (1:5000, T0198, Sigma Aldrich).
Yeast cells were then washed once in PBS and collected by centrifugation (5000 3 g, 3 min). Cells were then resuspended in PBS supplemented with 2 mM propidium iodide, at 1310 6 cells/ml and incubated for 5 min in the dark. Analysis was performed by flow cytometry using 150,000 cells per condition, on a BD AccuriÔ C6 (BD Biosciences) and results were analyzed using the CFlow Plus Software. For the quantification of H 2 S levels, overnight cultures were washed with PBS and diluted as described for survival assays. Cell suspensions were incubated with 20 mM MeRho-Az sensor for 45 min at 30 C and analyzed by flow cytometry, on a BD AccuriÔ C6 (BD Biosciences).
3% H 2 O 2 in MeOH for 15 min to block endogenous peroxidase. Slides were washed in PBS (pH 7. 4) and reduction of nonspecific background staining was achieved by incubation with normal swine (1:10, X0901, Dako) and donkey serum (1:10, X0903, Abcam) for 45 min at RT. Next, sections were incubated with primary antibodies; CBS (1:200, sc-67154, Santa Cruz Biotechnology), MPST (1:500, HPA001240, Sigma Aldrich), or with CTH/CSE antibody (1:200, sc-365382, Santa Cruz Biotechnology), overnight at 4 C. For the negative control, the primary antibody was substituted with PBS. After washing for 5 min in PBS, brain tissue sections were incubated with swine-anti-rabbit (1:100, P0399, Dako) and donkey-anti-mouse IgG-HRP (1:100, ab6820, Abcam) for 1 h at RT. Slides were washed in PBS and visualization was performed using Dako liquid 3,3 0 -diaminobenzidine tetrahydrochloride (DAB) substrate chromogen system (Dako) at concentrations suggested by the manufacturer.
QUANTIFICATION AND STATISTICAL ANALYSIS The experiments were performed in at least in triplicates by at least 2 different researchers. Key methodological experiments were verified by at least three different researchers in three different laboratories and all data are presented as mean ±SD. Protein expression levels, persulfidation, sulfenylation, and sulfinylation levels were compared with an unpaired t test using the asterisk (*) or the number sign (#). No results/data points were excluded. For both signs, the single symbol represents a p value of < 0. 05 and two symbols of p values of < 0. 01, throughout the study. Data of Mass Spectroscopy was analyzed using PEAKS Studio. Lifespan data were analyzed using Kaplan-Meier survival analysis to detect statistical differences. For lifespan experiments at least 100 worms per experiment were used.
ACKNOWLEDGMENTS The authors would like to thank  Dr. Michel Toledano  for careful reading of the manuscript and helpful discussions and  Dr. Bertrand Daignan-Fornier  for his help with yeast experiments. Funding: this work was supported by the  ATIP-Avenir  grant, by the  French State in the frame of the ''Investments for the future'' Programme IdEx Bordeaux  ( ANR-10-IDEX-03-02 ) and by  FRM  ( DEQ20180339181 ). M. W. acknowledges support from  MRC, UK  ( MR/ M022706/1 ), the  Brian Ridge Scholarship  (to R. T. ), and the  Northcott Devon Medical Research Foundation , UK. M. M. and V. M. were supported by the  Ministry of Education, Science and Technology Development of the Republic of Serbia  ( 173009 ). K. S. C. acknowledges support by  NIH  ( GM102187 ). G. S. and J. B. K. acknowledge support by the  DFG, Germany  ( SFB1218 TP B08 ).
DATA AND CODE AVAILABILITY The raw data corresponding to the antibody microarray Detection of persulfidation of EGFR Pathway kinases represent entirely new application of the dimedone switch method and are therefore available in more detail from the corresponding author on request. Proteomic data used for Figure  S2C  are stored in Data S1 and S2 and for Figures S3H and S3I in Data S3 and S4. All in-gel persulfidation, as well as Western blot sufenylation and sulfynilation data are reported in main and supporting Figures. Other raw data are available at https://data. mendeley. com/datasets/pw2wz39tsk/2.
Data from the European Sleep Apnea Database group have recently confirmed that there is a dose-response relationship between triglycerides and the severity of IH but this was modulated by geographical variations, suggesting that genetic background and lifestyle habits alter the relationship  [68]. Personalised medicine is among the next challenges in OSA  [69]. To better define the appropriate treatment for a single patient, we need combinations of biomarkers that are able to characterise IH consequences at the level of the different metabolic organs. Metabolomic and lipidomic profiles in OSA have been reported as distinct from a control group matched for age, BMI and body composition  [70]. Also, in a relatively large sample of nonobese and obese OSA, we recently found an independent correlation of OSA severity with the M1 macrophage inflammatory marker sCD163  [23].