dataesr/scientific-paragraphs-categorization huggingface dataset:
To describe clinical outcomes of patients aged 75 years and above after partial nephrectomy (PN), and to assess independent factors of postoperative complications. We retrospectively reviewed information from our multi-institutional database. Every patient over 75 years old who underwent a PN between 2003 and 2016 was included. Peri-operative and follow up data were collected. Multivariate logistic regression was performed to determine independent predictive factors of postoperative complications. We reviewed 191 procedures including 69 (40%) open-surgery, and 122 (60%) laparoscopic procedures, of which 105 were robot-assisted. Median follow-up was 25 months. The mean age was 78 [75-88]. The American Society of Anesthesiologist's score was 1, 2, 3 and 4 in 10. 5%, 60%, 29% and 0. 5% of patients respectively.
Material and methods Patients. This is a retrospective analysis of a multi-institutional, prospectively-maintained dataset of patients treated with PN for renal tumors between 2003 and 2016 at 15 French centers that are involved in the French network of research on kidney cancer UroCCR (NCT03293563). Patients > 75 yr(s) old undergoing PN for a localized renal tumor were included. The technical approach for the PN was at the surgeon's discretion. The study was approved by the Institutional Review Board CPP Sud-Ouest et Outre mer III (DC 2012/108). All methods were performed in accordance to the relevant guidelines and regulations. All patients received oral and written information about the objectives and methodology of the UroCCR project, and informed consent was obtained.
Data measurements. Based on UroCCR database, we evaluated the patients peri-operative data and the complications up to 3 months after surgery. General demographics information were analyzed along with the main comorbidities. Predictive operative risk was evaluated with the American Society of Anesthesiologists (ASA) and Eastern Cooperative Oncology Group (ECOG) scores. The specific tumor characteristics analyzed were the TNM stage and the RENAL and PADUA nephrometry scores. The technical characteristics of the surgery analyzed were surgical approach, indication for PN (elective or imperative), operative and warm ischemia times, estimated blood loss (EBL) and transfusion. Regarding the safety, we analyszed the length of stay (LoS), decrease in renal function (estimated glomerular filtration rate (eGFR) calculated with the Modification of Diet in Renal Disease formula (MDRD)and based on the creatinine level measured in µmol/L), intra and post-operative complications reported with the modified Clavien-Dindo classification  7.
Using the Surveillance, Epidemiology, and End Results database, Tan et al. demonstrated that the use of PN vs RN was significantly higher among younger patients. In comparison to the 65-69 yr(s) old age group, the PN odds ratio among the 70-74, 75-79, 80-84 and ≥ 85 yr(s) old patients were 0. 82, 0. 80, 0. 55 and 0. 30 respectively  10. Leppert et al. reported the evolution of PN and RN relative use (2002-2014) from the Veterans Health administration database. While they found an overall shift from 17 to 38% in favor of PN during this period, older patients, and patients with worse baseline kidney function showed the least increase  11. The large development of this procedure in clinical practices was more limited among older patients, who were likely to remain treated with RN  6, 9. The older patients were nevertheless more likely to present altered renal function at the time of diagnosis.
The simulation tracks particles through the detector medium, simulating their interactions in water as well as the production of secondary particles and the response of the PMTs to Cherenkov radiation. Detailed tuning and calibration has been performed to provide a tailored simulation of photon propagation in Super-K  [35]. The interaction of hadrons with water is simulated using the GCALOR package  [36] , except for pions below 500 MeV/c, which are simulated using a model based on NEUT's FSI simulation. The final background is reweighted to the result of the analysis in  [37] , adjusting its central value to the best fit oscillation and systematic error parameters favored by the Super-K data.
Among these pseudoexperiments, 14% had a K-S distance larger than 0. 33, indicating no significant deviation from the assumed uniform distribution and is consistent with the expectation from atmospheric backgrounds. A comparison of the expected atmospheric neutrino background, signal efficiency and observed data in each SK run period is shown in Table. and background rates are slightly different across these run periods, and the majority of candidate events are found in SK-IV, which has the longest livetime. The Poisson probability of observing 9 or more events in SK-IV with an expectation of 5. 5 events (ignoring systematic uncertainties) is 10. 6%. This observation is similarly consistent with the background expectation. In the absence of a statistically significant excess in data, a lower limit is established.
ACKNOWLEDGMENTS We gratefully acknowledge the cooperation of the  Kamioka Mining and Smelting Company. The Super-Kamiokande experiment has been built and operated from funding by the  Japanese Ministry of Education, Culture, Sports, Science and Technology , the  U. S. Department of Energy , and the  U. S. National Science Foundation. Some of us have been supported by funds from the  National Research Foundation of Korea   NRF-2009-0083526  (KNRC) funded by the  Ministry of Science, ICT, and Future Planning  and the  Ministry of Education  ( 2018R1D1A3B07050696 ,  2018R1D1A1B07049158 ), the  Japan Society for the Promotion of Science , the  National Natural Science Foundation of China  under Grants No. 11620101004 , the  Spanish Ministry of Science, Universities and Innovation  (grant  PGC2018-099388-B-I00 ), the  Natural Sciences and Engineering Research Council (NSERC) of Canada , the  Scinet and Westgrid consortia of Compute Canada , the  National Science Centre, Poland  ( 2015/18/E/ST2/00758 ), the  Science and Technology Facilities Council (STFC)  and  GridPPP, UK , the  European Union 's  Horizon 2020 Research and Innovation Programme  under the  Marie Sklodowska-Curie  grant agreement no.
Reanalyses combine past observations with weather forecast models to reconstruct past weather. The main advantage of this type of precipitation data set is its regular spatial and temporal coverage. Reanalyses ensure consistency of the precipitation data with the atmospheric conditions, which is important for weather and climate process studies. Here, we focus on  ERA-5 precipitation (C3S, 2017). ERA-5 is the latest reanalysis product from the European Centre for Medium-Range Weather Forecasts (ECMWF). ERA-5 precipitation is computed in short-term forecast started from reanalysis initial conditions  (Hennermann, 2020). The ERA-5 precipitation production process does not include precipitation observation inputs. Hence comparison with observational data makes sense, keeping in mind that observation data have (partly substantial) uncertainties as well  (Sun et al.
ERA-5 Precipitation Reanalysis precipitation in this study are extracted from ERA-5 reanalysis data set. ERA-5 is the latest global reanalysis data set provided by the European Center for  Medium-Range Weather Forecasts (C3S, 2017; Hersbach et al. , 2020). In this data set, precipitation stem from short-term forecasts and are available at an hourly resolution that we aggregate to daily precipitation. The precipitation data calculation does not rely on observed precipitation. The data is interpolated to a regular grid with 0. 25 • resolution.
Observation-based Data Sets The two gridded observation-based precipitation data sets used in this study are EOBS  (Haylock et al. , 2008)  that is based on European station observations and CMORPH that is based on satellite observations  (Joyce et al. , 2004). The EOBS data set is provided by the European Climate Assessment & Dataset and is a daily gridded data set based on spatially interpolated station data. The version used is 19. 0e, with a 0. 25 • by 0. 25 • grid. The interpolation to a 0. 25 • by 0. 25 • grid is a combination of monthly precipitation totals and daily anomalies products. Figure  1a  in  Cornes et al. (2018)  displays the station coverage for version 16. 0. This coverage is heterogeneous, with a very dense network in Ireland, the Netherlands, Germany, Switzerland, and northern Italy, for example, and very few stations in northern Africa, in the Middle East, in Iceland, in Norway, and in Sweden.
EOBS covers land precipitation only, and the comparison with ERA-5 is conducted for the time period between January 1979 and December 2018. The second observational data, CMORPH, is provided by the National Center for Atmospheric Research (NCAR) (Climate Prediction Center, National Centers for Environmental Prediction, National Weather Service, NOAA, U. S. Department of  Commerce, 2011). This gridded precipitation product combines passive microwave satellite scans and geostationary satellite infrared data and provides 3 hour accumulations that we aggregate in daily accumulation. CMORPH stands for climate prediction center morphing method, the name of this combination technique. The precipitation estimation algorithm of this data set is not able to capture snow  (Joyce et al. , 2004). The spatial resolution of the gridbox is also 0.
Difference in Number of Wet Days The intensity comparison is based on the EGPD, which is fitted to wet days only. Discrepancies in the number of wet days between ERA-5 and the observational data sets could have an impact when comparing the EGPD fitted to ERA-5 and the observational data sets. To quantify these discrepancies at a fixed grid point, we use two simple measures. The first measure is the ratio of the seasonal number of wet days, defined by : N wd ERA-5 N wd OBSER (5) where, for a fixed season, N wd ERA-5 and N wd OBSER are the number of wet days in ERA-5 and OBSER, respectively. The second measure is the absolute value of the difference in the number of wet days between ERA-5 and OBSER, normalized by the time series length of OBSER, given by: 100 × N wd ERA-5 -N wd OBSER N wd OBSER.
Co-occurrence of Precipitation Events In the comparison between ERA-5 and both observation-based data sets, the hit rate decreases with increasing intensity of the events and is similar across the seasons (Table  2 ). Grid points with a given percentile of less than 1 mm are not considered. Over Europe the average hit rate between ERA-5 and EOBS for the 75 th percentile is between 73 % (in JJA) and 77 % (in SON), i. e. about three quarters of the events exceeding the 75 th percentiles coincide. For the 95 th percentile, the mean hit rate is between 53% (JJA) and 60% (SON). For the 99 th percentile, the hit rate varies between 39 % and 45 % depending on the season. The global mean hit rate is of the same order of magnitude as for Europe. The mean hit rate between ERA-5 and CMORPH for the 95 th percentiles is above 50%.
95) than for moderately extreme precipitation (p = 0. 9), with an overlap rate 1% higher, for all seasons. This can be explained by confidence intervals becoming larger for larger quantiles, and there is thus a higher chance of overlap between ERA-5 and the observational data set. This remark holds also for the EOBS results. The Kullback-Leibler test presents little variation with season, like for the quantile study. Between 52% (SON) and 57% (DJF) of the grid points studied did not reject the null-hypothesis of the test. The analysis of the entire precipitation distribution reveals proportionally more grid points agreeing between ERA-5 and CMORPH than between ERA-5 and EOBS (see last row of Table  3 ). This can be due to the longer time series in EOBS leading to a stricter test. Another explanation can be that there are proportionally more challenging regions for a model over Europe, with the Alps for example, whereas globally the largest regions compared are oceans, where the agreement is good in general.
They computed the empirical 99 th percentiles of 6-hourly precipitation in ERA-interim and CMORPH for the period 2003-2016 (Figure  2  in their article). The authors showed a strong underestimation of ERA-interim precipitation over the tropics compared to CMORPH. They concluded that the deep convection, a central process in tropical extreme precipitation, was not properly captured by the reanalysis data set. Even though Nogueira (2020) found an improvement of the precipitation simulation over the tropics in ERA-5 compared to ERA-interim the previous reanalysis data set from ECMWF, we assume ERA-5 to still contain an underestimation of the tropical extreme rainfall. One limit of CMORPH that it is important to emphasize is the limitations of this data set to capture snow  (Joyce et al. , 2004 ) and low-intensity precipitation during winter in the mid-latitudes  (Sun et al.
Conclusion We compare daily precipitation from the ERA-5 reanalysis data set with daily precipitation from two observation-based data sets, EOBS and CMORPH. The comparison addresses three aspects i) the temporal co-occurrence of moderate to high extreme events in two data sets, ii) the agreement of return values for moderate to extreme nonexceedance probabilities derived from the extended generalized Pareto distribution (EGPD), and iii) a comparison of the full precipitation distribution captured by the EGPD using the Kullback-Leibler divergence. We quantify the co-occurrence of precipitation events with the hit rate. We compare the EGPD distributions between ERA-5 and the observational data sets with confidence intervals for several non-exceedance probabilities and with a test based on the Kullback-Leibler divergence.
Between ERA-5 and EOBS over Europe the hit rate is above 65% for moderate precipitation and approximately 50% for extreme precipitation. Between ERA-5 and CMORPH globally the hit rate is above 60% for moderate precipitation and around 40% for extreme precipitation. Over Europe areas with the least agreement are the southern Mediterranean region and Iceland and for the global comparison areas with the least agreement are land areas between 15 • S and 15 • N, North-West America and Central Asia. For a majority of grid points confidence intervals for non-exceedance probabilities of 0. 3 to 0. 95 overlap between ERA-5 and EOBS. We find a disagreement between ERA-5 and EOBS in areas where EOBS uses fewer input stations. We therefore hypothesize that the reanalysis data set might better capture moderate to extreme precipitation in regions where the station coverage is sparse.
The analysis also showed that ERA-5 underestimates extreme precipitation compared to CMORPH in the tropics. In general, the magnitudes of the non-exceedance probabilities agree between ERA-5 and the observationbased data sets in the mid-latitudes. The Kullback-Leibler test on the entire precipitation distributions over Europe shows an agreement of the EGPD distributions in ERA-5 and EOBS over Germany, Ireland, Sweden and Finland. The precipitation distributions differ significantly between in ERA-5 and EOBS in all four seasons in Iceland, Norway, Karelia, Hungary and the Balkan. The Kullback-Leibler test between ERA-5 and CMORPH shows that precipitation distributions are generally in agreement over the mid-latitudes and differ significantly over the tropics for all seasons, confirming the results of the quantile comparison.
Transcriptomic, proteomic & phospho-proteomic characterization The EpCAM+ve lung cells, isolated from two cohorts of wild type mice [either untreated (WT) or intranasally injected with an adenoviral vector encoding the Cre recombinase under the control of the Sftpc promoter (WT Ad-SPC-Cre )], were further characterized by transcriptome and proteome analysis. Overall, 13. 274 transcripts were identified and quantified by RNA sequencing, and 5. 952 proteins by LC-MS (Tables  S2  & S3 ) -a significantly larger dataset than previously reported for these cells  (Treutlein et al. 2014 ). Among the translated transcripts (Fig. 2A, B ), the most highly expressed were surfactants (Sftpa, Sftpb, Sftpc) and Lyz2 -all known AT2 cell markers  (Fehrenbach, 2001)  -thus confirming AT2 cell enrichment in both WT (Fig.
To this end, we sequenced the whole lung tissue of WT Ad-SPC-Cre mice, and compared the expression profile of lung tissue to that of the EpCAM+ve cell fraction. First, clustering analysis of genes expressed at both transcript and protein level, detected by RNA-Seq and MS methodologies, revealed striking differences in expression pattern between the lung and isolated cells from WT Ad-SPC-Cre mice (Table  S2 , Fig. 2C ). Established AT2 cell markers (e. g. Sftpc, Lyz2) are found in the cluster (C2) of genes that are highly enriched in the EpCAM+ve cell population, when compared to the lung (Fig. 2C ). Second, we sought to identify cell-surface proteins that could be used in direct isolation of mouse AT2 cells. Using LogCPM>1 and FDR<0. 05 as AT2 cell isolation, omics profiling & organotypic culture 5 / 29 threshold, from 109 transcripts highly enriched in the EpCAM+ve fraction seven (Table  S3 ) are predicted to encode cell surface proteins (Cell Surface Protein Atlas database,  Omasits et al.
2015. For measurements of phosphopeptide enriched samples 23 DIA windows method was used. Mass Spectrometric Data Analysis: For generation of spectral libraries for DIA searches the DDA and DIA data were analyzed with the Pulsar search engine using SpectroMine™ v1 (Biognosys) applying the default settings. Search criteria included carbamidomethylation of cysteine as a fixed modification, oxidation of methionine and acetyl (protein N-terminus) as variable modifications and additionally phosphorylation of S, T, Y as variable modification for phosphopeptide enriched samples only. The DDA and DIA files were searched against the Mus Musculus Ensembl v87 database and the Biognosys' iRT peptide sequences  (Escher et al. 2012). The identifications were filtered to obtain a false discovery rate (FDR) of 1 % on peptide and protein level.
The DIA data was analyzed using Spectronaut™ v13 software (Biognosys) applying default settings. The FDR on peptide and protein level was set to 1 %. Local normalization was performed on the peptide quantities to compensate for loading differences and spray bias  (Callister et al. 2006 ). Top3 peptides were used for calculation of protein quantities in total proteome data. DIA-specific PTM site localization score in Spectronaut was applied for the analysis of phosphopeptide enriched samples and phosphopeptides with score > 0. 75 were reported. Mapping mouse and human proteins: UniProt gene identifiers of phosphorylated proteins reported to be significantly changed after SARS-CoV-2 infection in C. sabaeus vero E6 cells  (Bouhaddou et al. 2020)  were mapped to Ensembl mouse gene identifiers to compare with AT2 cell data.
Gene Set Enrichment Analysis (GSEA) GSEA was performed using gsea2-2. 2. 2. jar  (Subramanian et al. 2005). Expression data was first selected for the subset of genes for which the protein was measured by MS and for genes with a minimal expression of 0. 5 RPKM. Orthology mapping between mouse and human was performed using Ensembl v87 orthology tables. GSEA was performed on a pre-ordered list based on a ranking of isolated cells versus lung tissue with the distance D and fold-change FC by the metric: Ranking=sqrt( log10(D)^2 + log2(FC)^2) * sign(log2(FC)). Further GSEA was performed using the gene sets h. all. v5. 2, c2. cp. biocarta. v5. 2, c2. cp. kegg. v5. 2, and c2. cp. reactome. v5. 2. G, H, I, G', H', I', G", H", I'' ).
The tiled images were automatically stitched to a single image per monolayer imaged, during image acquisition (Zeiss ZEN software). Four representative fields-of-interest, cropped from each tiled image, were used for quantification of cell subtypes using Cell Profiler (proSPC, CC10, p63)  (McQuin et al. 2018)  or ImageJ (AQP5)  (Schindelin et al. 2012; Rueden et al. 2017). Quantification of proSPC and CC10 labelled cells was performed on an average of 11000 cells per replicate (n=3) and cell fraction (EpCAM+ve/-ve); of p63 and CC10 labelled cells on an average of 5800 cells per replicate (n=3) and cell fraction (EpCAM+ve/-ve cell fraction); of AQP5 and proSPC labelled cells on average of 2600 cells per replicate (n=2) (EpCAM+ve fraction). Maximum and average intensity per cell was measured in Cell Profiler; the cell types were first classified according to thresholds set based on the distribution of average intensities (Fig.
Histochemistry and immunofluorescence microscopy of organoids & lung De-paraffinized and rehydrated 4μm thick sections of formalin-fixed paraffin-embedded lung tissue or organoids were processed for histochemical staining or immunofluorescence labelling according to  Li et al. (2016)  except for labelling with anti-proSPC (antigen retrieval at 95 °C). The following antibodies were used, in the indicated dilutions: Microscopy of the histochemically-stained specimens employed a transmission light microscope (Olympus BX61VS) and images were acquired with a 20x objective using VS110 software (Olympus). Microscopy of the fluorescently-labeled specimens was performed according to  Li et al. 2016.
ACKNOWLEDGEMENTS The support of the  Animal House, Histology, Imaging and Functional Genomics Core Facilities  of the FLI as well as of the Animal House of  PHENOMIN-ICS  is gratefully acknowledged; in particular the expert assistance at FLI of  Jenny Buchelt ,  Hellen Ahrens & Sabine Landmann  and at  PHENOMIN-ICS  of  Emilie Peter ,  Solene Schmitt & Peggy Mellul. This study was funded by the  European Union   Horizon 2020 research and innovation program  under grant agreement No. 686282 , as part of the  CanPathPro  project. The FLI is a member of the  Leibniz Association  and is financially supported by the  Federal Government of Germany  and the  State of Thuringia.
Patients This repeated cross-sectional single-center study retrospectively collected secondtrimester ultrasound images of women with obesity (i. e. , BMI ≥ 30 kg/m 2 ) during two separate periods. The first period ran from January 1, 2014, to May 31, 2015, and the second from January 1, 2016, to May 31, 2017. This study was approved by our Institutional Review Board (IRB approval 5921). Eligible files were selected from among pregnant women who underwent their secondtrimester ultrasound examination for fetal anomalies, in compliance with French national recommendations (at 20-24 gestational weeks)  [9]. Women with multiple pregnancies and those with BMI < 30 were excluded. Patients were extracted from our database through the ICOGEM ® electronic medical file used in our department (Medicode™, 13390 Auriol, France) by two investigators (A.
It has previously been shown that sharpness and precision are both better when a lower propagation velocity in adipose tissue is applied for image formation  [21]. It therefore enhances the visibility of each anatomical element studied and improves the operator's ability to meet the standard criteria. Therefore the main interest of this work was to study the completion rate and the anatomical quality of fetal second-trimester ultrasound scans of women with obesity when the sonographer had a free choice of ultrasound velocities. The modification of the calculation of ultrasound propagation velocity does not change intrinsic ultrasound properties such as mechanical and thermal indexes. This study was conducted retrospectively on data previously collected under routine working conditions. This explains why indicators such as Salomon's score and examination duration may look suboptimal compared with those obtained in prospective studies designed to evaluate image quality  [8, 20].