dataesr/scientific-paragraphs-categorization huggingface dataset:
Feature selection and comparison of the signicantly altered metabolites related to the presence of the magnetosomes The 2556 metabolite features detected in the spent media of magnetosome compared to non-magnetosome producing cells (Fig. 4A ) were submitted for metabolite identication using Compound Discoverer 3. 1 SP1. The m/z, RT and/or MS/MS of these features were interrogated against the specic BioCyc database of Mgryph, the retention times (RT) of 235 authentic standards and the mzCloud fragmentation database. 423 metabolites were identied in which only 137 metabolites were reported with high condence in identication (i. e. Level 1 and 2 only) based on MSI levels of identication  25, 26  as detailed earlier (Fig. 4B , Table  S2  in the ESI †). The signicantly altered metabolites in the samples were selected using both multivariate (OPLS-DA) and univariate analysis (adjusted p-values).
Acknowledgements This work was supported by the  NanoPrime EPSRC  grant  EP/ R025282/1 ;  Royal Society Research  grant  RGS\R1\191377 ; the  Aston Institute of Materials Research (AIMR)  Seed-corn grant; the  Energy Research Accelerator (ERA)  grant from  Innovate UK  and the  Green Chemicals Beacon of Excellence, University of Nottingham. The authors acknowledge the assistance of the visiting student  Jonathan Andraud  of the  Université Clermont Auvergne  for the pre-culture experiments; and  Tim W Overton  and  Owen RT Thomas  of the  University of Birmingham  for enabling the access to the C mag measurement system.
Study Population Consecutive patients aged 18 to 54 years, treated for first-ever CS in a tertiary hospital, were included in this retrospective study. Patients with cerebral venous thrombosis, subarachnoid hemorrhage with secondary brain ischemia, or transient ischemic attack as defined by transient neurologic dysfunction without evidence of infarction on brain imaging were not included. Clinical, biological, and radiological data from all individual patients were reviewed using the electronic database. Hypertension, diabetes, and migraine were diagnosed by history. Overweight (including obesity) was defined as body mass index (BMI) >24. 9. Hypertension was defined as persistent systolic blood pressure >130 mmHg or diastolic blood pressure >80 mmHg, as documented before stroke or treatment with antihypertensive drugs before stroke.
Diabetes was defined as a previous diagnosis of type 1 or type 2 diabetes. Tobacco use was recorded in patients who were currently smoking. Hyperlipidemia was defined as elevated low-density lipoprotein cholesterol >1. 6 g/L or hypertriglyceridemia >2. 0 g/L. The study conformed to the principles outlined in the Declaration of Helsinki. All patients were informed that clinical data collected during their hospitalization could be used for research purposes and gave their consent. The study was approved by our Institutional Review Board (internal reference RnlPH 2019-73).
Statistical Analysis Continuous variables were expressed as mean ± standard deviation or median and interquartile range. Intra-and interrater reliability for LA strain measurement were assessed by intraclass correlation coefficient from 10 randomly selected patients reanalyzed by two observers. Nominal values were expressed as numbers and percentages. We used Mann-Whitney rank sum test and Fisher exact test for comparison of continuous and nominal variables, respectively. A multivariable analysis was performed using logistic regression analysis. Reduced LA strain was defined as LA strain < median value. All tests were bilateral. Differences were considered as statistically significant for a P < 0. 05. All analyses were performed using SPSS, version 20 (SPSS Inc. , Chicago, IL, United States).
PDMS is an elastomer with excellent optical properties that is commonly used in microfluidic applications. In addition, its refractive index (normalized by that of sea water) is ∼1. 06 which falls within the typical range of phytoplankton cells (1. 02-1. 07) [40]. The thin PDMS plates engraved on one side with arrays of cylindrical pillars (with elliptical cross-section) were made using standard soft photo-lithography techniques. The primary molds used to obtain the PDMS plates were made using conventional glass slides onto which the opposite pattern was printed with SU-8 photoresist (GM 1060; Gersteltec Sàrl) giving a final thickness ∼15 µm (which is also the final thickness of the pillars appearing on the PDMS). The patterns on the transparency masks used to print the primary molds were generated using Matlab software.
Acknowledgements J. S. F-M received a French state aid managed by the  National Research Agency  under the  ISblue program  ( ANR-17-EURE-0015 ). R. J. acknowledges funding by an  individual postdoctoral fellowship "Juan de la Cierva -Incorporación " and by the  LabEx ENS-ICFP :  ANR-10-LABX-0010/ANR-10-IDEX-0001-02 PSL*.
Exclusion criteria included targeted therapies, known genetic cause of CRC, acute and chronic infections, poor ECOG performance status (N = 10). Samples from 2 patients were not collected within the required timeframe; in addition, response data of one patient was not available (lost to follow up). Finally, data of 72 subjects, who had received at least one CHT cycle, were included in the analysis. Control group consisted of consecutive all-comer patients hospitalized in the Department of Endocrinology, admitted in sequence for diagnosis of hormonally inactive suprarenal incidentalomas or thyroid gland diseases (found free of disease). To evaluate if selected cytokines could be used as prognostic markers, the whole group was divided into 2 subgroups of patients: progressors and non-progressors.
Data analysis Several authors found that a cytokine profile in metastatic CRC patients differs from those in less advanced stages. 7, 14 Therefore, we performed a separate analysis for patients treated with palliative and adjuvant CHT. Palliative group consisted only of patients in CS IV (CS, clinical stage); adjuvant group included patients in CS II and III. Characteristics of all analyzed groups are shown in Tables  1  and 2. Then, to establish predictive significance of particular cytokines, we calculated receiver operator curves (ROC) for the whole group, palliative and adjuvant subgroups. Next, we applied multivariate analysis to find the model which has the best predictive power regarding clinical response (progressors, non-progressors) for the whole group. All the patients' demographics, clinical and histopathological variables were tested for association with levels of immune mediators.
Assessed CRC patients' population was heterogeneous, including patients before and after surgery, before and after radiotherapy; included patients were in differ-ent disease stages. The follow up period was relatively short (6 months). Some of these limitations could be addressed. Nagtegaal at al. 53  reported that, although preoperative RT/CRT potentially affected immune cell densities and serum cytokine levels, their correlation data were parallel in patients who did not receive RT/CRT. According to the authors, this indicated that preoperative RT/CRT was not a significant confounding factor. Other authors indicated  54  that sex, tumor, site, and N-stage had little association with the serum cytokine fluctuations reported. The authors conclude that the presence of a systemic inflammatory response was associated with IL-1RA, IL-6, IL-7, IL-8, IL-9, IL-12, IFN-gamma, IP-10, MCP-1, MIP-1B, and PDGF-BB levels.
Subsequently, the crystal measurements including area, 2D aspect ratio, major and minor ellipses were retrieved from the digitized binary images imported into ImageJ. CSDSlice  (Morgan and Jerram (2006) ) was used to estimate the 3D crystal aspect ratios of the population which returned 1:5:9 (R 2 0. 82) and 1:5: 10 (R 2 0. 94) for the plagioclases of Phase I and Phase II, respectively, and 1:1. 2:1. 6 (R 2 0. 81) and 1:1. 2:1. 9 (R 2 0. 88) for the oxides of Phase I and Phase II, respectively. Each population consisted of more than 300 crystals as recommended by  Morgan and Jerram (2006). Finally, the conversion of the apparent crystal dimensions to 3D crystal shapes was performed using the software CSDCorrections (version 1. 6;  Higgins, 2000)  which   2018 ), with locations (red stars) of the 19 samples that were used for further analysis.
ACKNOWLEDGMENTS This work is based on CL Master's thesis at LMV,  Université Clermont Auvergne. CL and AH thank the  Labex ClerVolc  and LMV (équipe volcano) for field and travel support. OC wishes to thank the  Auvergne  fellowship. The authors acknowledge the thorough reviews of the Field Chief Editor  Valerio Acocella  and two reviewers whose advice, questions and remarks on this manuscript vastly improved the resulting content. The authors are also grateful to  Rosa Anna Corsaro  for her constructive suggestions. Matthew Patrick  and an reviewer are also acknowledged for their suggestions and feedback on an initial version of this manuscript.
Observations and Data Analysis Target of Opportunity (ToO) observations of PKS 0736+017 with H. E. S. S. were triggered on February 18, 2015, following the detection of flaring activity in Fermi-LAT data (see next Section). H. E. S. S. observations were carried out with the full array in the same night. Follow-up observations were performed on February 19, 21, and 24 (with the full array for the first two nights, while data were recorded with CT5 only during the last night). All observations were taken in "wobble mode" where the source position is offset by 0. ˝5 from the camera center to allow for simultaneous background estimation  (Berge et al. 2007 ). The details of H. E. S. S. obsevations are reported in Table  1. Data were analyzed with the ImPACT analysis chain  (Parsons & Hinton 2014; Parsons et al.
2015)  using both monoscopic and stereoscopic reconstruction and were crosschecked with an independent analysis chain  (De Naurois & Rolland 2009; Holler et al. 2015)   takes into account the absorption on the EBL  (Franceschini et al. 2008). loose configuration of the monoscopic analysis, an excess of 473 γ-like events with a signal-to-background ratio of 0. 17 is found at the source position in the overall good-quality 7. 2 hour dataset, corresponding to a detection significance of 8. 5σ using Eq. 17 of  Li & Ma (1983). The overall signal is dominated by the strong excess coming from the second night of observations  (February 19, 2015). The monoscopic (respectively, stereoscopic) analysis of this 1. 8 h live time data set yields an excess of 364 (49) γ-like events, corresponding to an 11.
4+0137, in order to perform a binned analysis as implemented in the gtlike tool. To encompass the entire active state studied here, data between February 1, 2015 and April 1, 2015 are considered, in the 100 MeV-500 GeV energy range. The P8R3 SOURCE V6 instrument response functions were used, together with a zenith angle cut of 90 ˝to avoid contamination by the γ-ray bright Earth limb emission. The model of the region of interest was built based on the 3FGL catalog  (Acero et al. 2015) , and it has been checked a posteriori that no significant residual remains, which could have hinted for new sources not referenced in the 3FGL catalogue. The Galactic diffuse emission has been modeled using the file gll iem v06. fits  (Acero et al. 2016 ) and the isotropic background using iso P8R3 SOURCE V6 v06.
In the light curve, flux upper-limits at the 68% level are provided when T S ă 9. The evolution in time of the best-fit photon index is shown in panel "c". To better compare the Fermi-LAT data of PKS 0736+017 with H. E. S. S. data during the night it was detected at VHE, as well as to retain sufficient statistics, a Fermi-LAT data subset was analyzed for the time window MJD 57072. 5-57073. 5. The source is detected in this subset with a TS=339 ("18σ), a flux of F p100 MeV´500 GeVq " p2. 08 ˘0. 26q ˆ10 ´6 cm ´2 s ´1, and a photon index of Γ " 2. 15 ˘0. 10. In this case, no evidence of curvature is found (log-likelihood ratio of -0. 12). The Fermi-LAT highest energy for a photon associated with PKS 0736+017 (at the 95% confidence level) is 106 GeV (detected on MJD 57072, at 14:42:20 UTC). This is also the highest photon energy when considering the larger two-months interval described above.
Given the high significance of the detection, a Fermi-LAT data analysis has also been performed in a time window strictly simultaneous with the H. E. S. S. detection  (MJD 57072, (18) (19) (20). PKS 0736+017 is detected in this dataset with a TS= 37 ("6σ), a flux of F p100 MeV´500 GeVq " p4. 57 ˘1. 52q ˆ10 ´6 cm ´2 s ´1, and a photon index of Γ " 2. 43 ˘0. 33. The highest-energy LAT photon simultaneous with the H. E. S. S. detection has E " 1. 71 GeV (detected on MJD 57072, at 20:40:16 UTC). Fig. 1  shows the Fermi-LAT spectra of PKS 0736+017 for the two time windows described here. To estimate the variability in the HE γ-ray band, the fractional variability F var,HE of the 12-hours binned light curve   was computed following  Vaughan et al. (2003). This results in F var,HE " p62 ˘7q%, clearly supporting the presence of variability of the HE γ-ray flux.
Swift-XRT Following the detection of the γ-ray flaring activity in PKS 0736+017, ToO observations were requested to the Neil Gehrels Swift satellite  (Gehrels et al. 2005 ) in order to measure the flux of PKS 0736+017 in soft-X-rays and optical/UV. The ToO resulted in four observations with Swift starting from February 20, 2015, for a total exposure time of around 12. 3 ks. The details are provided in Table  2. Data from Swift-XRT  (Burrows et al. 2005 ) are analyzed using Heasoft version 6. 18. All observations are taken in the standard Photon Counting observing mode. The event files are cleaned using standard screening criteria. Images, spectra and light curves are extracted using a circular region with radius equal to 20 pixels. The background is extracted from an annular region with inner radius equal to 50 pixels, and outer radius equal to 160 pixels.
The count rates are around 0. 11-0. 16 s ´1, and are low enough that no pile-up affects the analysis. Spectral analyses of Swift-XRT data are performed using XSpec version 12. 9. The ancillary response files are recomputed using xrtmkarf, while the redistribution matrix files provided by the Swift team are used. Data are rebinned using grppha imposing a minimum of 30 counts per bin, and data below 0. 3 keV are excluded. The X-ray spectrum from each of the four Swift-XRT observations is fitted with an absorbed powerlaw model (phabs*cflux*powerlaw within Xspec, to access the unabsorbed flux in the 0. 3-10 keV band), to take into account the absorption by neutral material in the Milky Way. The value of N H in the direction of PKS 0736+017 is fixed to 7. 8 ˆ10 20 cm ´2 as estimated by  Dickey & Lockman (1990).
ATOM The ATOM telescope  (Hauser et al. 2004 ), located on the H. E. S. S. site, regularly observes PKS 0736+017 as part of its blazar monitoring program, providing a long term light curve of the source in the R band. Fluxes from ATOM observations are extracted using a 4 2 -radius aperture, and have been de-reddened using the same value of Galactic extinction E B´V " 0. 121 as for the UVOT data analysis. There are no ATOM observations during the night of February 19, 2015, when H. E. S. S. detected VHE emission from PKS 0736+017. On the other hand, ATOM observations on the night of February 20, 2015, are contemporaneous with the UVOT ones. The light curve from ATOM data is provided in Fig. 2 , panel "e".
ASAS-SN and KAIT PKS 0736+017 is also regularly monitored in the optical by the ASAS-SN project  (Shappee et al. 2014 ) and the KAIT telescope  (Cohen et al. 2014). Their public data have been retrieved for the observations around the February 2015 γ-ray flare. ASAS-SN V-magnitudes, and KAIT unfiltered magnitudes (which are close to the R ones, see  Li et al. 2003)  have been converted to fluxes and de-reddened using E B´V " 0. 121 as for the other optical observations. ASAS-SN and KAIT observed PKS 0736+017 during the morning (UTC) of February 19, respectively 11. 5 hours and 14 hours before the H. E. S. S. VHE detection, and complement the optical light curve from UVOT, ATOM, and Steward Observatory. The contribution of the host-galaxy to the optical measurements has not been investigated.
Acknowledgements. 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 lnergie atomique et aux nergies alternatives (CEA), the  U. K. Science and Technology Facilities Council (STFC) , the  Knut and Alice Wallenberg Foundation , the  National Science Centre, Poland  grant no. 2016/22/M/ST9/00382 , the  South African Department of Science and Technology and National Research Foundation , the  University of Namibia , the  National Commission on Research, Science & Technology of Namibia (NCRST) , the  Austrian Federal Ministry of Education, Science and Research and the Austrian Science Fund (FWF) , the  Australian Research Council (ARC) , the  Japan Society for the Promotion of Science  and by the  University of Amsterdam.
We appreciate the excellent work of the technical support staff in  Berlin, Zeuthen, Heidelberg, Palaiseau, Paris, Saclay, Tbingen  and in Namibia in the construction and operation of the equipment. This work benefited from services provided by the  H. E. S. S. Virtual Organisation , supported by the national resource providers of the  EGI Federation. The  CC-IN2P3  (cc. in2p3. fr) is gratefully acknowledged for providing a significant amount of the computing resources and services needed for this work. Part of this work is based on archival data, software or online services provided by the  Space Science Data Center -ASI. Blazar observations at Steward Observatory are funded though  NASA / Fermi Guest Investigator Program  grant  NNX15AU81G. Matteo Cerruti  has received financial support through the  Postdoctoral Junior Leader Fellowship Programme  from  la Caixa Banking Foundation  ( LCF/BQ/LI18/11630012 ).
The dust emission calculation requires a soil properties database (roughness length, texture and soil aggregates size distribution) as developed in  [39]  for China. Saltation fluxes are defined in  [40]  and calculated as follows (Equation (  1 )): F h (D p ) = Kρ air U * 3 g 1 - U * t U * 1 + U * t U * 2 (1) where U * is the friction wind speed, U * t is the threshold friction wind speed, calculated following Marticorena and Bergametti (1995). K is constant with value equal to 1, ρ air is the air density and the gravitational acceleration g = 9. 8 m s -2. The sandblasting process and vertical emission fluxes were calculated in CHIMERE from a parameterization by  [41] , which calculates the emission fluxes for a given aerosol size distribution, following Equation (2)  [40] : F (v,m,i) (D p ) = Nclass ∑ k=1 πρ p βp i (D p,k )d 3 m,i 6e i dF h (D p ) (2) where Nclass corresponds to the intervals of soil size distribution, p i the relative fraction corresponding to Nclass, e i is individual kinetic energy of aggregate, ρ p is particle density and β an acceleration constant.
5,dust /PM 10,dust distribution is finally the difference of transport behavior between the 2 particle range sizes, as the PM 2. 5,dust fraction is most efficiently transported-the ratio increases to 0. 32, 0. 25 and 0. 34 for Beijing, Chengdu and Shanghai respectively-which might induce an overestimation of PM 10,dust mass. CHIMERE model and modules are described in details in the model documentation. In our study, simulations were performed for 2011, 2013 and 2015, to study inter annual variability of dust emissions. The years 2011 and 2013 were chosen because numerous dust events have been observed for those years  [50, 51]. However, these years were not abnormally high in total dust emissions from deserts  [52]  or in mineral dust detected in cities [53].
m. local time) with those calculated from simulated dust distributions by CHIMERE (  [57] , using a Mie code and Asian dust refractive indexes from). IASI-derived AODs in the thermal infrared are estimated with the newly-developed AEROIASI retrieval approach (  [58, 59] , version 2). We used CHIMERE simulations at 10:00 a. m. local time for the comparisons of AODs derived by both MODIS and IASI. We first focused on dust emissions areas, to evaluate the simulated emissions. We verified that changes brought by dust emission inhibition by rainfall have improved correspondences between MODIS and CHIMERE AODs. For the 4 arid sub regions, AOD is mostly controlled by mineral dust, as mineral dust emissions represent more than 90% of the mass of total pollutant emissions for these regions. The large dust emitting areas were divided into 4 regions (Figure  1 ) and compared to MODIS observations: the so-called Taklimakan desert area, which includes Taklimakan, the Kumtaq desert and the Qaidam desert; the Gobi desert, mainly situated over Mongolia; the Gurban desert, situated between the Taklimakan and Gobi desert; the last and smallest area, which is also the closest to China's biggest cities, contains several Chinese deserts (Tengger desert, Ulan Buh desert, Qubqi desert and Mu Us sandy land) and is called hereafter the Northern China desert.
Surface Measurements Data Set and Comparison Methods CHIMERE PM modeling in populated areas was also evaluated against PM 2. 5 and PM 10 measurements from background stations close to cities, during spring periods and full years. We first wanted to assure that CHIMERE correctly models particulate pollution levels and variability in Beijing, Chengdu and Shanghai. A comparison between model and hourly measurements from Chinese monitoring was performed from PM 2. 5 and PM 10 spring season for 2013 (March-April) and 2015 (March-April-May). We focused our comparisons on these periods, because of data availability and because the dust impact was expected to be the strongest in spring. PM measurements are from TEOM instruments  [61]. We first used a method to evaluate the representativeness of monitoring stations, from  [62]  which uses the relative diurnal variability of SO 2 or O 3 , in order to evaluate if the considered stations were representative of rural, suburban, urban or traffic environment.
Simulated model concentrations are bi-linearly interpolated at stations' coordinates. We also used data from the U. S. Embassy and consulates over 3 cities (e. g. , in Beijing, Chengdu and Shanghai, in urban background environment) to evaluate the PM 2. 5 correspondences over a larger period (2011, 2013 and 2015). PM 2. 5 is measured on an hourly basis with a MetOne BAM 1020 instrument  [63]. It has to be noted that 2011 measurements are available only for Beijing. Comparison methods applied are the same as for previous comparisons, but daily values are calculated from hourly data depending on measurements availability, and compared. Statistical results of comparisons, such as normalized bias, Normalized Root Mean Square Error (NRMSE) and correlation mean are presented in Tables  3  and 4  for spring seasons in 2011, 2013 and 2015 and in Figure  S2  (in supplement).