dataesr/scientific-paragraphs-categorization huggingface dataset:
Cell proliferation After extraction of cells from the chitosan fibers and films using a 0. 05% Trypsin-EDTA solution, the quantity of total cell detached and viability were determined. Living cell quantification on chitosan substrates for different proliferation times are shown in Figs. 8  and 9  involving the two different diameter fibers compared with film. The effect  of the neutralization treatment of the chitosan fibers, being important for fiber stability is joined. An increasing cell development is observed with time in Figs. 8  and 9  , as expected, for colonization on a compatible substrate. From Fig. 8  , on the thinner fibers, after 7 days of culture, around 3. 5 times more cells were found to be detached from the neutralized fibrous substrates compared with film. These data allow to conclude also that fibers made of pure chitosan (after neutralization step) favor proliferation of chondrocytes compared to results before neutralization, being higher in both cases in contrast to the chitosan film.
Funding sources This work has been financially supported by  Mexican CONACYT  grant  611845/788990  attributed to  Christian E. García García  to prepare a PhD thesis in cooperation between LRP ( University Grenoble-Alpes, France)  and  CUCEI (University of Guadalajara, Mexico). The Laboratoire Rhéologie et Procédés is part of the  LabEx Tec 21  ( Investissements d'Avenir -grant  agreement  n°ANR-11-LABX-0030 ) and of the  PolyNat Carnot Institut  ( Investissements d'Avenir -grant  agreement  n°ANR-11-CARN-030-01 ). This work was also supported by  ANR2016-BIOSCAFF  ( ANR-16-CE09-0024 ) held by the  University of Grenoble-Alpes.
Acknowledgments We would like to thank  Pierre Heidmann  for sharing the unpublished scaling geometries B and C. We would also like to thank  Massimo Bianchi ,  Vitor Cardoso ,  Bogdan Ganchev ,  Yixuan Li ,  Andrea Puhm ,  Bert Vercnocke , and  Nick Warner  for useful discussions and comments on the manuscript. The work of IB is supported by the  ANR  grant  Black-dS-String   ANR-16-CE31-0004-01 , by the  John Templeton Foundation  grant  61149 , and the  ERC Grants 787320-QBH Structure and 772408-Stringlandscape. DRM is supported by the  ERC Starting  Grant  679278 Emergent-BH.
CAD Test Environment The CAD tests are realized in the University of Pau (France) area. It is a typical terrain in the university with some low buildings and trees. A transmitter was placed on a tripod in a fixed position. LoRa data rate is initially set to SF12BW125 (spreading factor of 12 and bandwidth of 125 kHz), and the LoRa radio module was the SX1276. The choice of SF12 provides the longest time-on-air to test the CAD procedure. A CAD device continuously realizing a CAD procedure every 1000 ms and a simple receiver (denoted in the figure as gateway, but it is a more simple device than a gateway with a radio concentrator) were connected on a laptop computer as shown in Figure  2. The preamble length is set to the default value which is 8 + 4. 25 symbols. Depending on the data rate, the preamble duration will therefore vary according to the symbol time.
First Capture Effect Experimentation Settings Our first experimentation setting consists of a very simple scenario to better catch Capture Effect property in a real LoRa deployment. We start with two transmitters (transmitter A and transmitter B) and one receiver (acting as gateway) as depicted in Figure  6 : transmitter A and transmitter B are at about 20 m distance from each other, and the gateway is placed approximately in the center of the two nodes. The first set of tests is performed in LOS conditions. During the test, both of the transmitters have the same maximum output power of 14 dBm and the LoRa data rate is SF12BW125. The choice of SF12 here facilitates the synchronization of nodes to study the impact of concurrent transmissions overlapping the packet's preamble. Both transmitters have the same payload, which is 240 bytes (resulting in 244 bytes transmitted with the 4-byte application-level header), which will remain constant throughout the experiment.
The random backoff timer is expressed in number of DIFS whose value is set to the duration of the LoRa packet's preamble. DIFS therefore depends on the LoRa data rate in order to adapt the various timer according to the time-on-air of packet transmission. A node willing to transmit a data packet will either start by listening for an RTS with probability 1 -P (phase 1) or start directly by sending an RTS with probability P (phase 2). By choosing P with a small value such as 0. 1, only 10% of transmitters will actually start by claiming for the radio medium. The other transmitters will then listen for the RTS. In Figure  13 , node D i will start by listening while nodes D j and D k start by trying to send an RTS. Prior to the RTS transmission, a random backoff timer expressed in number of DIFS is applied in order to further separate transmitter nodes starting directly in phase 2.
Implementation We implemented the proposed solution in our LoRa framework  [32]. Depending on the LoRa data rate, the duration of the DIFS is set to the duration of the default packet's preamble. We set W = 7 and the listening period duration is defined as W × DIFS + TOA(sizeo f (RTS)). As stated previously, for data rate SF12BW125, the duration of listening period is about 3. 6 s for instance. The RTS packet is five bytes long (four bytes for the application header and one byte to indicate the size of the future data packet). The listening period is implemented as a regular LoRa packet reception. As explained previously, a LoRa radio actually provides a ValidHeader interrupt and an RXDone interrupt when a correct packet is received. The LoRa packet's header is managed at the radio level; it is not a user or application level header.
Channel Access and Similarity with Neighbor Discovery Protocols As CCA can not be reliably stated, the proposed channel access mechanism borrows ideas from Neighbor Discovery (ND) protocols in wireless networks with active/inactive periods  [33]. The main objective here is therefore to maximize the probability to have overlapping active periods between nodes, and there are similarities with Birthday  [34] , DiffCode/ADiffCode  [35] , SearchLight  [36] , Nihao  [37] , and Griassdi  [38]  to name a few. The last three have been recently proposed in the context of IEEE 802. 15. 4 or BLE networks. However, the main difference between ND protocols and channel access protocols resides in the fact that ND protocols try to discover neighbor nodes much less frequently than a channel access protocol.
Materials All reagents, including oleyl alcohol (technical grade, 85%) and 2-decyl-tetradecan-1ol (97%), were purchased from commercial sources and used as received (Aldrich, TCI). Solvents (THF, CH 2 Cl 2 ) were dried with an MBRAUN solvent purification system and kept under a molecular sieve. Milli-Q water was used as solvent for the liposomal formulations. NMR spectroscopy data were recorded with a Bruker Avance 400 ( 1 H: 400. 0 MHz, 31 P: 161. 9 MHz, T = 293 K) or a Bruker Avance 500 ( 13 C: 125. 7 MHz, T = 293 K). The 13 C NMR spectra were recorded with a J-MOD sequence (J-modulated spin-echo). The chemical shifts are reported in δ[ppm] (multiplicity, coupling constant J, number of protons) relative to the solvent residual signal as the internal standard. For 31 P NMR, an external reference (H 3 PO 4 ; δ = 0 ppm) was used.
Materials All reagents, including oleyl alcohol (technical grade, 85%) and 2-decyl-tetradecan-1-ol (97%), were purchased from commercial sources and used as received (Aldrich, TCI). Solvents (THF, CH2Cl2) were dried with an MBRAUN solvent purification system and kept under a molecular sieve. Milli-Q water was used as solvent for the liposomal formulations. NMR spectroscopy data were recorded with a Bruker Avance 400 ( 1 H: 400. 0 MHz, 31 P: 161. 9 MHz, T = 293 K) or a Bruker Avance 500 ( 13 C: 125. 7 MHz, T = 293 K). The 13 C NMR spectra were recorded with a J-MOD sequence (J-modulated spin-echo). The chemical shifts are reported in δ[ppm] (multiplicity, coupling constant J, number of protons) relative to the solvent residual signal as the internal standard. For 31 P NMR, an external reference (H3PO4; δ = 0 ppm) was used.
Supplementary Materials: The following are available online, in the supplementary materials part: Figures S1-S35 correspond to NMR and MS spectra ( 1 H, 31 P, 13 C, MALDI TOF or ESIqTOF MS spectra) for the compounds 2-4/a-b, Table  S1  "Sizes and zeta potentials of the liposomes at t = 0 and 5 months later. ", Table  S2  "Sizes and zeta potentials of the lipoplexes at different charges ratios", Table  S3  "Fraction of complexed DNA and free DNA after complexation process with the cationic lipids determined by densitometry analysis on the electrophoresis gel", Figure  S36  "Proportion of complexed and free DNA after complexation process with the cationic lipids determined by densitometry analysis on the electrophoresis gel. " Funding: This research was funded by grants from the ANR-Agence Nationale de la Recherche (project no.
ANR-17-CE18-0015-03, "monop-DNA-Nanoparticules Virus-Inspirées pour transfert de gènes"; ANR, Paris, France); the Association de Transfusion Sanguine et de Biogénétique Gaétan Saleün (Brest, France); and the Région Bretagne (France). M. K. and A. H. were recipient of a PhD fellowship from the French Ministry of Higher Education, Research and Innovation.
The data reported in this article have been deposited in the Gene Expression Omnibus (GEO) database, including GSM705329 to GSM705333, and GSE89565. Only transcriptomic data (Affymetrix HG-U133 Plus 2. 0 arrays) have been partially presented. In our previous study 19 : 12 BPDCN out of 13, 65 AML out of 79, and 35 T-ALL out of 61 are available in the GEO database (GSE89565). The 5 primary cDCs and the 5 primary pDCs are also available on the GEO database (GSE28490, GSM705321-25 and 29-33, respectively).
NGS and bioinformatics analysis Next-generation sequencing (NGS) was performed from a Halo-Plex HS Target Enrichment System designed for Illumina Sequencing (Agilent) targeting 68 genes (supplemental Table  1 ) in paired-end, 2 3 150 cycles on a MiSeq platform (Illumina Inc, San Diego, CA). Raw data were analyzed using an in-house bioinformatics pipeline (supplemental Methods). 43 Sequencing by the Sanger method was performed on an ABI PRISM 3500 DNA Genetic Analyzer (Thermo Fisher Scientific) with a BigDye Terminator v3. 1 Cycle Sequencing kit (Thermo Fisher Scientific).
Gene expression profiling and data analysis Gene expression profiling was obtained using Human Genome U133 Plus 2. 0 arrays (Affymetrix) from 176 leukemia samples (12 BPDCN, 164 AL) and compared with 5 normal cell-sorted cDCs and 5 pDCs from the GEO database, GSE28490: GSM705321-25 and 29-33, respectively (see supplemental Methods for analysis and supplemental Table  2  for published signatures).
BPDCN exhibit many mutations and chromosomal imbalances The NGS panel was informative for all cases, with many detected mutations ranging from 1 to 7 (median 3). Twenty genes were found to be mutated among the 68 of the panel (Figure  3A ; supplemental   45  and confirmed here by SNP array. The 15q24. 1-15q25. 3 MCDR was detected in 4 patients, including NTRK3 (31%). Three patients (P1, P3, P4) had a 6q23. 3 deletion (23%), located next to MYB, prompting us to suspect a rearrangement of this gene, known to be involved in recurrent fusion transcript in BPDCN. 23 Similarly, a del(8q24) downstream to MYC was detected in patient P2. Expression data were also in favor of an MYC rearrangement, with overexpression of MYC in 2 cases (P2 and P6) compared with other patients (Figure  3C ). Two del(17p) were detected, in patients P8 and P11, involving the TP53 locus 17p13.
Acknowledgments The authors thank  Fiona Ecarnot  for English proofreading. They thank the Laboratory of Immunology (E. Seilles) , the  Laboratory of Cytology (F. Schillinger) , the  French BPDCN network , the  Groupe Français d'H ématologie Cellulaire (GFHC) , the  Groupe d' Étude Immunologique des Leuc émies (GEIL) , the  Groupe Français de Cytog én étique H ématologique (GFCH) , and the  Soci ét é Française d'H ématologie (SFH). This work was supported by  La Ligue Contre le Cancer 2008, Fondation ARC  (Aides Individuelles  DOC20170505805 ),  Institut National de Cancer Translational Research program  ( DM/FC/sl/ RT07 ), and  Association Laurette Fugain  ( ALF 2018/08 ).
PATIENTS AND METHODS Data were extracted from the registry of the European Society for Blood and Marrow Transplantation (EBMT). The EBMT is a nonprofit, scientific society representing more than 600 transplant centers mainly in Europe that are required to report all consecutive stem cell transplantations, including follow-up, once a year. Data are managed in a central database with Internet access, in which each EBMT center is represented. Annual audits are performed to verify data accuracy. Patients provide informed consent authorizing the use of their personal information for research purposes before transplantation. For this study, the registry was screened for adult patients with acute leukemia (AL) and undergoing alloSCT3 between 2001 and 2018, independently from donor type or graft source.
, 2020)  data from the GOME-2A instrument and NIRv from the Moderate Resolution Imaging Spectroradiometer (MODIS) to assess the usefulness of these signals to capture the seasonality and magnitudes of GPP derived from six eddy-covariance flux towers from Africa in the overlap years between the years 2007-2014. We also test the robustness of SIF and NIRv to track the seasonality of GPP for the major biomes in comparison to the widely used machine-learning approach of Max Planck Institute for Biogeochemistry (MPI-BGC) GPP, as well as to other vegetation remote-sensing indices like the NDVI  (Kong et al. , 2016)  and enhanced vegetation index (EVI;  Arvor et al. , 2011). Further, we assess the relationship between the satellite observations and (modelgenerated) soil moisture (SM) and incoming shortwave radiation (SWR) in the region.
Gridded datasets In this study we use Level-3 GOME-2 Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval SIF (v2. 0) with 737 nm monthly data at a spatial resolution of 0. 5 • × 0. 5 • covering the period from 2007 to 2016. For a fair comparability of the SIF with vegetation indices we normalized SIF by the cosine of the solar zenith angle. We used the Royal Netherlands Meteorological Institute (KNMI)-Wageningen University & Research (WUR) SIF retrieval, which is particularly suited for tropical conditions  (van Schaik et al. , 2020; Koren et al. , 2018). The retrieval code uses a much larger dataset to construct the reference atmospheric spectra used to distinguish the small SIF signals from the complex structure of transmittance and reflectance from other atmospheric constituents such as water vapor  (van Schaik et al.
bgc-jena. mpg. de/ geodb/projects/Data. php, last access: 5 January 2020) covering the period from 2007 to 2011. The enhanced vegetation index (EVI) and the normalized difference vegetation index (NDVI) are the two most widely used vegetation indices for monitoring vegetation conditions and have significant relationships with GPP  (Xiao et al. , 2005). The monthly EVI and NDVI from the MODIS collection of MOD13C2 at a spatial resolution of 0. 05 • ×0. 05 • in the years 2007-2015 were used in the study. Compared with the NDVI, the EVI is less sensitive to soil background variations and remains sensitive over dense vegetation  (Huete et al. , 2002). For that reason we focus on comparison with the EVI rather than with the NDVI. Moreover, MODIS does not provide NIRv in the MOD13C2 dataset, so we calculated it using the BRDF-corrected surface reflectances from MCD43C4, following the steps outlined in  Badgley et al.
Flux tower data Standardized eddy-covariance flux data are available under the fair-use data policy of the FLUXNET2015 dataset. The data processing of the FLUXNET2015 dataset ensures inter-comparison and quality assurance and control across sites  (Vuichard and Papale, 2015). A collection of eddy-covariance flux data from six regions in Africa were used in this study to assess the correlation between SIF, NIRv, and GPP at an ecosystem level, specifically, available monthly GPP products from the daytime partitioning of fluxes (GPP_DT_VUT_REF) from Tier-2 FLUXNET2015 synthesis https://fluxnet. org/ (last access: 15 January 2020). These variables were screened using quality flags so that only samples that are either measured (flag = 0) or good quality (flag = 1) were retained. An overview of the selected towers is given in Table  1.
Analysis method To compare the gridded datasets (SIF, NIRv, MPI-GPP) with the GPP measurements from flux towers, we extracted data from a 4 • × 4 • window surrounding each flux tower. The flux towers have a footprint of about 1 km 2 , and it is hard to compare them to areas that are 200 km 2 , centering around the towers, which include many vegetation types. However, we use the vegetation mask to exclude grid cells with different vegetation from the tower's vegetation; this will account for the land heterogeneity of the regions. The variation in climate condition was addressed by splitting up the shrubs and C 4 grasses over the Northern and Southern hemispheres. We used good quality data as recommended by each data source, and we further processed these datasets to match the spatiotemporal grids.
, 2013). The partitioning approach is furthermore not well-tested for tropical ecosystems because of a lack of long data records, the larger uncertainty in determining nighttime TER  (Kruijt et al. , 2004) , and the often-seen nighttime storage that results in peak NEE fluxes in the early morning  (Araújo et al. , 2002). Finally, tropical TER is likely to experience a larger control of temperature and moisture on TER  (Chambers et al. , 2004). The tower GPP from the GH-Ank site shows limited seasonality (Fig. 3 ). GPP over evergreen tropical forest vegetation is poorly captured by all products. Where NIRv, the EVI, and MPI-BGC GPP all show a phase-lag of nearly 4 months, SIF manifests a double-peak structure and much too low annual mean SIF relative to the other datasets. In general, SIF and NIRv were better proxies for capturing the seasonal dynamics of GPP over most sites.
The relationships can be improved by using higher-resolution products instead of these coarse resolutions. Here we used SIF from the GOME-2 instrument which has a larger footprint (40 × 80 km 2 ) and global gridding with a spatial resolution of 0. 5 • × 0. 5 • at a monthly timescale. TROPOMI SIF is a promising alternative for future studies of the African carbon cycle. TROPOMI SIF has a higher spatial resolution than GOME-2 SIF and more frequent coverage. Global TROPOMI SIF data were first shown by  Köhler et al. (2018). Their study also included a detailed view of the North African Nile Delta. In addition,  Doughty et al. (2019)  used TROPOMI to study the seasonality of the Amazon, showing the capability of this instrument to capture seasonal dynamics of tropical ecosystems. Moreover, high-resolution (0.
Acknowledgements. The authors acknowledge the  NOAA Earth System Research Laboratories, Met Office Hadley Centre, Global Precipitation Climatology Centre , Global Land Data Assimilation System, MODIS dataset, and  ECMWF  for the data products. We would also like to acknowledge the FLUXNET data principal investigators of the  GH-Ank (Ghana) ,  ZA-Kru (South Africa ),  ZM-Mon (Zambia) , and  BR-Sa1  (Brazil) sites. The first author also acknowledges  Addis Ababa University, Addis Ababa Science and Technology University , the  Coimbra Group Scholarship Programme , and the  University of Groningen  for their support through fellowship and access to research facilities. Data were processed on Cartesius (SURFsara) using a grant for computing time ( SH-312-14 ) from the  Dutch Research Council (NWO).
Jonas Ardö  was supported by  Lund University. We would like to thank the associate editor  David Bowling  and the anonymous reviewers for their constructive and thoughtful comments and suggestions that significantly improved the paper. Financial support. This research has been supported by the  European Research Council (ERC)  under grant no. 649087  (ASICA), by  H2020  grant no. CASSECS, and by grant no. 95/15  of the  Swedish National Space Board (SNSB). Review statement. This paper was edited by  David Bowling  and reviewed by two anonymous referees.
Data availability. All data used for this research are publicly available under a fair-use policy. The SIF data are available at https:// doi. org/10. 21944/gome2a-sifter-v2-sun-induced-fluorescence (last access: 20 February 2021)  (Kooreman et al. , 2020). The surface reflectance data used to calculate NIRv are accessed from https: //lpdaac. usgs. gov/products/mcd43c4v006/ (last access: 10 February 2020)  (Schaaf and Wang, 2015). The FLUXNET2015 datasets used in this study can be accessed from the FLUXNET data portal at https://fluxnet. org/data/fluxnet2015-dataset/ (last access: 15 February 2020). The eddy-covariance data processing guidelines are available at https://doi. org/10. 1038/s41597-020-0534-3 (last access: 15 February 2020) (Pastorello et al. , 2020). The MPI-BGC GPP dataset can be downloaded from https://www.
However, single-agent pembrolizumab in first-line therapy has demonstrated superior response rates and progression-free survival (PFS) versus standard-of-care chemotherapy with or without bevacizumab or cetuximab in patients with MSI-H/MMR-D mCRC (KEY-NOTE-177  [31] ). Additional data are currently awaited from clinical studies involving atezolizumab (NCT02912559; NCT02997228), avelumab (NCT03150706; NCT03186326), and durvalumab (NCT02227667; NCT03435107) in patients with mCRC characterised by MSI-H/dMMR. Notwithstanding the development of molecularly targeted treatments, cytotoxic chemotherapy regimens still represent the backbone of treatment for the majority of mCRC patients, with biological therapy supplementing rather than replacing chemotherapeutic agents, except possibly in MSI-H tumours  [2].
Subsequently, stability, production, and administration issues associated with oxidation have been overcome with the development of arfolitixorin ([6R]-5,10-methylene-THF). Arfolitixorin represents a stabilised molecule which does not require metabolic activation  [74]. Following administration of a dose of 200 mg/m 2 , arfolitixorin resulted in significantly higher plasma C max and AUC last of methylene-THF than the same dose of leucovorin. At the same dose, intratumoural and intramucosal concentrations of methylene-THF and THF were also significantly higher after treatment with arfolitixorin versus leucovorin  [74]. This may, in turn, translate to more effective ternary complex formation. Clinical efficacy and tolerability of arfolitixorin/5-FU combination therapy was demonstrated alone and in combination with irinotecan or oxaliplatin, with or without bevacizumab in the multicentre phase 1/2 study, ISO-CC-005, in patients with mCRC (NCT02244632;  [117] ).
Data Collection Demographical and clinical data, including morbidities, were collected. Patients' prior health status was evaluated by the Charlson Comorbidity Index  [20]. Chronic heart disease was defined as a medical history of myocardial infarction, coronary ischemia treated by angioplasty and/or stents, cardiac surgery, or chronic heart failure (i. e. , exertional or paroxysmal nocturnal dyspnea that has responded to digitalis, diuretics, or afterloadreducing agents). The severity of disease was assessed 24 h after ICU admission using the Simplified Acute Physiology Score (SAPS) II  [21]. At ICU admission, the oxygen arterial partial pressure to the fraction of inspired oxygen (PaO 2 /FiO 2 ) ratio  [22]  was recorded. Biological data were also collected at admission, particularly hs-cTnT, C reactive protein (CRP), and D-dimer.