dataesr/scientific-paragraphs-categorization huggingface dataset:
Nanoparticle tracking on a NS300 system (Malvern) and the NTA3. 0 software was utilized to determine the concentration of exosomes as well as their mean size and size distribution with the same instrument and software settings used for all samples. Settings were as follows: 5 movies of 60 second duration at room temperature were acquired for each sample at camera level 15. The processing threshold was kept constant (at 6) for all measurements. NTA3. 0 software was used to determine average particle size and count and mode sizes of 90-120nm in diameter were obtained for exosome samples independent of isolation method. Exosome purity, as indicated by a particles/μg protein value  [26] , was determined by dividing the particle count by total protein concentration as measured using a micro BCA protein assay kit (Thermo Fisher Scientific)).
Doxorubicin content was analysed on a Fortessa (BD) using TexasRed-PE filter settings. Live cells were defined by DAPI-exclusion. Data was analysed using the FloJo version 10 software (TreeStar). For comparison between samples the geometric mean of the medium fluorescence instensity (MFI) was determined. For microscopy Hoechst33342 (ThermoFisher Scientific) was added at 1 μg/ ml for 10 min. 2 images per well were acquired at 20x magnification on an image express high content epifluorescence microscope (Molecular Devices) using filter settings for DAPI and Cy3.
Improved potency of exosomal doxorubicin in cultured immortalised and primary cell lines Our time-lapse video microscopy data showed that Exo-Dox causes a greater level of mitochondrial swelling and results in apoptosis in a greater fraction of cells compared to free Dox, but the method is limited in the number of conditions that can be tested. To compare potency of Exo-Dox to other formulations, we employed a standard cell viability assay measuring cellular ATP content. A small panel of immortalised cell lines (HEK293, SK-BR-3 and BT-20) were treated with Exo-Dox, free Dox or liposomal Dox for 48 h (  more potent than other formulations of Dox (~20-fold compared to Dox, ~5-fold compared to Myocet and >50-fold compared to Doxil). As cardiotoxicity is the major side effect of doxorubicin treatment, we also examined hiPS cardiomyocytes that were obtained by differentiating human iPS cells, as well as low passage human cells HUVEC or PASMC which were treated in an identical manner and analysed by cell viability assay after 72 h (Fig  5 ).
Drought management plan DMPs define specific actions to be undertaken to enhance preparedness and increase resilience to drought. In France DMPs include regulatory frameworks to be applied in case of drought, called arrêtés cadres sécheresse. The past and operating DMPs and the water-restriction orders were inspected in the 28 departments of the RM district. They were obtained from the following: the database of the DREAL Auvergne-Rhône-Alpes ("Direction Régionale de l'Eau, de l'Alimentation et du Logement" in French), including water-restriction levels (WRLs) and duration at the catchment scale available over the period 2005-2016 within the RM district, the online national database PROPLUVIA (http:// propluvia. developpement-durable. gouv. fr, last access: 1 August 2019), with WRLs and dates of adoption at the catchment scale for the whole of France available from 2012.
Hydrological data The hydrological observation dataset is a subset of the 632 French near-natural catchments identified by  Caillouet et al. (2017). Daily flow data from 1958 to 2013 were extracted from the French HYDRO database (http://hydro. eaufrance. fr/, last access: 1 August 2019). Time series with more than 30 % missing values or more than 30 % null values were disregarded. Finally, the total dataset consists of 106 gauged catchments located in the RM district, with minor human influence and with high-quality data. The selected catchments are benchmark catchments where near-natural drought events are observed and current water availability is monitored. Water can be abstracted from other nearby streams. A selection of 15 evaluation catchments (Table  1 ) were used to calibrate and to evaluate the WRL (WR level) modelling framework (Sect.
For example, let us consider thresholds based on the annual monthly minima of V C d. The block minimum approach is carried out on the N years of records for each month i, i = 1. , 12, leading to 12 datasets, {min{V C d (t), month(t) = i, year(t) = j }, j = 1,. , N}. The 12 fitted distribution allows the calculation of 48 values of thresholds (month-V CN d ; 12 months × 4 levels) with four T -year recurrence intervals. -the maximum discharge Q C d for a window with length d days, Q C d (t) = max(Q daily (t ), t ∈ [t -d +1, t]), The meteorological situation is also examined in terms of precipitation deficit and likelihood of significant rainfall event considering available short-to medium-range weather forecasts. There are heterogeneities in the droughtmonitoring variables, the time period on which deficit is calculated and the permissible deviation from long-term average values.
The exposure measures the probability of changes occurring for different lead times based on available regional projections. All the components of the framework together contribute to the vulnerability of the system (including its management) to systematic climatic deviations. The sensitivity analysis was conducted by applying a water-restriction modelling framework. Climate conditions were generated by applying incremental changes to historical data (precipitation and temperature) and introduced as inputs in the developed models to derive occurrence and severity of water restriction under modified climates. The tool chosen here to display the interactions between water restriction and the parameters that reflect the climate changes is a two-dimensional response surface, with axes represented by the main climate drivers.
The criterion KGE SQRT and the Nash-Sutcliffe efficiency criterion on the log-transformed discharge NSE LOG  (Nash and Sutcliffe, 1970)  were calculated over the whole period 1958-2013 for the subset of 15 evaluation catchments (Table  1 ), showing KGE SQRT and NSE LOG values are above 0. 80 and 0. 70, respectively. These two goodness-of-fit statistics indicate that GR6J adequately reproduces observed river flow regime, from low-to highflow conditions. The less satisfactory performances of GR6J are observed for the Tarn and Roizonne river basins, both characterized by smallest drainage areas and highest elevations of the dataset. These lowest performances are likely to be linked to their location in mountainous areas (snowmelt processes are difficult to reproduce) and to their size (the grid resolution of the baseline climatology fails to capture the climate variability in the headwaters).
( , 2013a Prudhomme et al. ( , b, 2015)). Following  Prudhomme et al. (2015) , monthly correction factors P and T are calculated using single-phase harmonic functions: P (i) = P 0 + A P • cos (i -ϕ P ) • π 6 , (1) T (i) = T 0 + A T • cos (i -ϕ T ) • π 6 , (2) with P 0 and T 0 as mean annual changes in precipitation (Eq. 1) and temperature (Eq. 2), respectively, i as the indicator of the month (from 1 to 12), ϕ as the phase parameter, and A as the semi-amplitude of change (e. g. half the difference between highest and lowest values) for precipitation (Eq. 1) and temperature (Eq. 2). These correction factors were applied to the baseline climate datasets to create perturbed daily forcings: The baseline climate (precipitation and temperature) time series were extracted from the Safran reanalysis over the period 1958-2013 (56 years), and perturbed time series were generated for the same length.
, 1984) , aimed at performing successive binary splits of a given dataset according to decision variables. Through a set of "if-then" logical conditions the algorithm automatically identifies the best possible predictors of group membership, starting from the most discriminating decision variable to the less important factors. The optimal choices are fixed recursively by increasing the homogeneity within the two resulting clusters. At each step, one of the clusters (node) is divided into two non-overlapping parts. Here, to free results from catchment size influence, descriptors related to severity were expressed in millimetres per year, millimetres per month or millimetres per day. Results show three top discriminators, with the aridity index being the strongest: the AI given by the mean annual precipitation divided by the mean annual potential evapotranspiration (UNEP, 1993), the base-flow index (BFI), a measure of the proportion of the base-flow component to the total river flow, calculated by the separation algorithm separation suggested by  Lyne and Hollick (1979) , the concavity index (CI;  Sauquet and Catalogne, 2011)  to characterize the contrast between low-flow and highflow regimes derived from quantiles of the flow duration curve.
The national system of compensation to farmers is initiated for areas classified under the agricultural disaster status. Over 2005-2012, only one agriculture disaster was declared, in 2011, and this applied to 70 of the 95 departments in continental France and to 16 of the 28 departments fully or partly located in the RM district. Data are collected by the French Ministry of Agriculture and Food, and they are not publicly available. The year 2011 was the only year when the national system of compensation was triggered between 1958 and 2013, and the analysis of simulated water restrictions for this year fixed the value for T c. The duration of water restrictions was calculated individually for each catchment and converted into anomalies WR * (2011) with respect to the benchmark value (mean over the period.
Acknowledgements. The authors thank  Météo-France  for providing access to the Safran database. We thank  Jan Seibert  as well as the anonymous reviewers for their critical but very constructive comments. Financial support. This research was partly funded by the  Rhône-Méditerranée-Corse Water Agency. Review statement. This paper was edited by  Roberto Greco  and reviewed by  Brunella Bonaccorso  and two anonymous referees.
Data availability. Regional climate model (RCM) projections were obtained from the DRIAS portal (http://drias-climat. fr/, last access: November 2016) and consulted on November 2016. Analyses were performed in R (R Core Team, 2016), with packages airGR  (Coron et al. , 2017) , chron  (James and Hornik, 2017) , circular  (Lund et al. , 2017) , doParallel (Calaway et al. , 2017), dplyr (Wickham and  François, 2015), ggplot2  (Wickham, 2009) , hydroTSM (Zambrano-Bigiarini, 2014), RColorBrewer  (Neuwirth, 2014 ), reshape2 (Wickham, 2017), rpart  (Therneau et al. , 2018) , scales  (Wickham, 2016) , stringr  (Wickham, 2017)  and zoo  (Zeileis and Grothendieck, 2005).
We then processed the resulting matrix with the dudi. pca() function of the ade4 package  (Thioulouse et al. 1997 ) (version 1. 7-6, http://pbil. univ-lyon1. fr/ADE-4/home. php?lang=eng; ) using parameters scan = FALSE, scale = FALSE and nf = 4. We then processed the resulting object with the ade4::wca() function using lineages as classes and parameters scan = FALSE, nf = 2. The first column of attribute c1 of the resulting object corresponded to the WCA scores reported in text and figures.
Acknowledgements We thank  Dieu Huong Hoang ,  Sonia Grzeskowiak  and  Chloé Exbrayat-Héritier  for help with experiments,  Laurent Modolo  ( Pôle Bioinformatique, LBMC ) for suggesting multivariate class analysis, developers of R, ade4 package and Ubuntu for their software. S. S. is supported by  NIH  grant  R01 GM34059 , F. P. by  ANR  grant  N° 15-CE12-0018-01 , the  Fondation ARC  and the  Centre National de la Recherche Scientifique.
Aerosol optical properties Aerosol optical properties were computed by the authors using their own Mie routines, and results were cross-checked Table  1. Aerosol physical and optical properties for the different aerosol types considered in the benchmark. σ g is the geometric standard deviation. The refractive indices are linearly interpolated from the OPAC database  (Hess et al. , 1998). Dust refractive indices are linearly interpolated from  Woodward (2001)  for consistency. The Mie routine used to generate the input data was rewritten in Fortran based on the implementation of  Toon and Ackerman (1981)  and was compiled with the Intel Fortran compiler in quadruple precision. The calculations are monochromatic (i. e. no integration was performed on the wavelength). The aerosol size distribution is integrated over the size range reported for each type in Table  1 , with a Gaussian quadrature of 10 000 points in logarithm of the radius.
Measured variables We aim to provide a standardized dataset to evaluate the possibility of assimilating satellite radiances in operational forecasts of atmospheric composition. Thus, two variables are important to estimate for each case: the simulated reflectance (or radiance) that would be observed by the satellite and a "sound" estimate of the radiative transfer code runtime. We will describe the accuracy of the models in terms of the reflectance, ρ I , of the intensity (i. e. the first Stoke component), which is related to the radiance, I , through the following relationship: ρ I = π I I s cos(θ s ) , (4) where I s is the incident solar flux at the top of the atmosphere (conveniently taken to equal 1 for reflectance calculations) and θ s is the solar zenith angle. The runtime may be difficult to estimate and compare between different models.
Acknowledgements. The authors acknowledge support from the  Copernicus Atmosphere Monitoring Service  implemented by ECMWF on behalf of the  European Commission. The authors thank  Didier Tanré  for his interesting comments on the draft of the manuscript. The authors would also like to thank the  6SV2  development team for their help in resolving small issues with the model and  Vijay Natraj  and  Robert Spurr  and the two anonymous reviewers for their comments in the discussion phase. Computing was partly performed on the ESPRI data and computing centre of the  Institut Pierre-Simon Laplace. Edited by: Andrea Stenke Reviewed by: two anonymous referees.
INTRODUCTION Molecularly targeted agents (MTAs) given based on specific molecular alterations (MAs) were shown to be highly effective in several cancer types, such as vemurafenib in V600E BRAF-mutated melanoma patients or gefitinib in EGFR-mutated non-small cell lung cancer (NSCLC) patients  [1, 2]. Several actionable MAs were identified across tumour types raising the question of comprehensive molecular profiling clinical utility to guide therapy. Precision medicine trials have been designed to assess the value of molecular profiling to allocate therapy in a histology-independent way  [3] [4] [5]. SHIVA01 (NCT01771458) was the first randomized trial comparing matched MTA versus conventional therapy in patients with any kind of metastatic solid tumour refractory to standard of care  [3]. SHIVA01 was negative for its primary endpoint with no statistical difference in progression-free survival (PFS) between the experimental and the control groups suggesting that SHIVA01 treatment algorithm was not able to improve patient outcomes.
PATIENTS AND METHODS SHIVA01 was a proof-of-concept open-label randomized controlled phase 2 trial conducted in France  [3]. MTAs used in the experimental group were drugs given outside their indications. Patients treated with MTAs following randomization or at cross-over in SHIVA01 were included in the study. All MAs used to allocate MTAs in SHIVA01 were classified according to ESCAT by assessing the level of evidence in the literature (Supplementary Figure  S1 ). To this end, for each MA, we first searched for clinical trials performed with the MTA in the same tumour type that would support ESCAT levels of evidence Tiers I or II. If no data supported Tiers I or II, we then searched for clinical trials performed with the same MTA and based on the same MA but in other tumour types that would support Tier III.
Funding sources: This work was supported by the grant  ANR-10-EQPX-03  from the  Agence Nationale de le Recherche  (Investissements d'avenir) and  SiRIC (Site de Recherche Intégré contre le Cancer). High-throughput sequencing was performed by the  NGS platform of the Institut Curie , supported by the grants  ANR-10-EQPX-03  and  ANR-10-INBS-09-08  from the  Agence Nationale de le Recherche  (investissements d'avenir) and by the  Canceropôle Ile-de-France.
The African continent has a very low density of rain gauge stations, and long time-series for recent years are often limited and poorly available. In the context of global change, it is very important to be able to characterize the spatio-temporal variability of past rainfall, on the basis of datasets issued from observations, to correctly validate simulations. The quality of the rainfall data is for instance of very high importance to improve the ef ficiency of the hydrological modeling, through calibration/validation experiments. The HydroSciences Montpellier Laboratory (HSM) has a long experience in collecting and managing hydro-climatological data. Thus, HSM had initiated a program to elaborate a reference dataset, in order to build monthly rainfall grids over the African continent, over a period of 60 years (1940/1999).
The large quantity of data collected (about 7000 measurement points were used in this project) allowed for interpolation using only observed data, with no statistical use of a reference period. Compared to other databases that are used to build the grids of the Global Historical Climatology Network (GHCN) or the Climatic Research Unit of University of East Anglia, UK (CRU), the number of available observational stations was significantly much higher, including the end of the century when the number of measurement stations dropped dramatically, everywhere. Inverse distance weighed (IDW) was the chosen method to build the 720 monthly grids and a mean annual grid, from rain gauges. The mean annual grid was compared to the CRU grid. The grids were significantly different in many places, especially in North Africa, Sahel, the horn of Africa, and the South Western coast of Africa, with HSM_SIEREM data (database HydroSciences Montpellier_Système d'Information Environnementales pour les Ressources en Eau et leur Modélisation) being closer to the observed rain gauge values.
The quality of the grids computed was checked, following two approaches-cross-validation of the two interpolation methods, ordinary kriging and inverse distance weighting, which gave a comparable reliability, with regards to the observed data, long time-series analysis, and analysis of long-term signals over the continent, compared to previous studies. The statistical tests, computed on the observed and gridded data, detected a rupture in the rainfall regime around 1979/1980, on the scale of the whole continent; this was congruent with the results in the literature. At the monthly time-scale, the most widely observed signal over the period of 1940/1999, was a significant decrease of the austral rainy season between March and May, which has not earlier been well-documented. Thus, this would lead to a further detailed climatological study from this HSM_SIEREM database.
Introduction On a global scale, the first climate observations began during the second part of the 19th century. Among these climate variables, rainfall data sets have been the most complete, since the beginning of the 1950s  [1]. In Africa, the most well-known change in rainfall regime occurred in Sahel, but all of Western and Central Africa experienced an abrupt decrease in mean annual rainfall, at the end of the 1960s or towards the beginning of the 1970s  [2] [3] [4]. To study rainfall changes at the scale of the whole African continent, rainfall grids can be downloaded from several institutions, but it is well-known that the African continent is less documented than other parts of the world  [5, 6]. This has led to some discrepancies between rainfall calculated from different databases, as has been shown for Western Africa, by Mahé et al.
[7]. Among the available data sets, Climatic Research Unit of University of East Anglia, UK (CRU)  [8, 9]  is used very often and seems to be the most accurate, compared to other sources. However, for instance, for Western and Central Africa, rainfall data are not very well-documented  [10, 11]. The first objective of the present work is to elaborate monthly grids of the best possible quality, over the African continent. For this, it was necessary to build the most exhaustive rainfall database to help improve understanding of the climatic processes and other applications, such as hydrological modeling. Hydrologists at the Institut de Recherche pour le Développement (IRD) or the French National Research Institute for Sustainable Development, previously ORSTOM (Office de Recherche Scientifique Outre-Mer), had historically participated in the acquisition of climatological data and built up a digital database, as early as the end of the 1960s.
However, by the end of the 1980s, the IRD stopped collecting and managing rainfall data for Western and Central Africa. The researchers of the HSM decided to valorize this unique set of data for Africa, first, in the search of additional data to cover the whole continent, and to update the database up to 1999. This project was an opportunity to create a reference database, called HSM_SIEREM database, which is still managed by the HSM. The HSM_SIEREM  [12]  database has been used for sub-continental studies of climate change, like those by Paturel et al. [10, 11] , many regional studies of river-runoff relationships  [13, 14] , and studies of the impact of climate change on hydrological regimes in Western Africa  [15]. These data were first used at a continental scale, for a study of rainfall-runoff variability over the past decades  [16].
In this article, we have presented, for the first time, the methods through which the data were selected and evaluated, the process leading to the creation of the monthly-gridded dataset over Africa (at a 0. 5 × 0. 5 degree resolution), and a first assessment of the content of this new database. In the second part, we have compared this new HSM_SIEREM grid, with the CRU grid and have pointed out the similarities and the differences to help improve the future uses of both bases. In the third part, we have presented a first study of rainfall variability, over the 1940/1999 time period, for the whole continent, to check the general quality of the dataset, by searching if the main rainfall signals were visible in large-scale regional averaged time-series. This first study will be followed by further detailed studies on the spatio-temporal variability of rainfall over the African continent.
History of the HSM_SIEREM Database Created in 1943, ORSTOM/IRD's mission was to promote scientific cooperation and education in Western and Central Africa. In this framework, hydrologists installed and managed most of the hydro-meteorological stations in French speaking countries-the former colonies. The records were noted in paper booklets and a long process of data entry began, as early as 1967, on punched cards, first, and were then transferred onto magnetic tapes of the CNRS (Centre National de la Recherche Scientifique) computers in Orsay/Paris. This transfer was taken into account to run a first control on Water 2019, 11, 387 3 of 17 the data quality check for duplicate cards, removal of data for non-existent days (such as, 31st of April and 30th of February), before building up the first database.