dataesr/scientific-paragraphs-categorization huggingface dataset:
Funding This work was delivered as part of the Mutographs team supported by the  Cancer Grand Challenges  partnership funded by  Cancer Research UK  ( C98/A24032 ). This work was supported by the  Wellcome Trust  grants  206194  and  220540/Z/20/A. The work was also partly funded by  Barretos Cancer Hospital , the  Public Ministry of Labor of Campinas (Research, Prevention , and  Education of Occupational Cancer , 2015 to R. M. R. ), and by  Hospital de Clínicas de Porto Alegre  ( 180330  to P. A. -P. , M. B. , B. S. N. ). The work was also partly supported by the  Practical Research Project for Innovative Cancer Control  from the  Japan Agency for Medical Research and Development (AMED)  ( JP20ck0106547h0001  to T. S. ), and by the  National Cancer Center Japan Research and Development Fund  ( 2020-A-7  to A.
F. ). The work was also partly funded by the 1 st and  2 nd Faculties of Medicine, Charles University, Prague  (CAGEKID to I. H. ; Occupation,  Environment and Kidney Cancer in Central and Eastern Europe  to A. H. ). The work was also partly supported by the  Ministry of Health of the Czech Republic  ( MH CZ -DRO  (MMCI,  00209805 ) to L. F. and M. N. ). Measurement of PFAS compounds was funded by  Division of Cancer Epidemiology and Genetics of the National Cancer Institute (USA). Measurement of cystatin C was funded by  Cancer Research UK  ( C18281/A29019 ). Contributions The study was conceived, designed and supervised by M. R. S. , P. B. and L. B. A. Analysis of data was performed by S. Senkin, S. Moody, M. D. -G. , T. C. , A. F. -I. , J. W. , S. F. , M. K. , R. V. , A. P. L. , E. N. B.
Recruitment of cases and informed consent The International Agency for Research on Cancer (IARC/WHO) coordinated case recruitment through an international network of over 40 collaborators from the 11 participating countries (Table1; Supplementary table  12 ). The inclusion criteria for patients were >=18 years of age (ranging from 23 to 87, with a mean of 60 and a standard deviation of 12), confirmed diagnosis of primary ccRCC and no prior cancer treatment. Informed consent was obtained for all participants. Patients were excluded if they had any condition that could interfere with their ability to provide informed consent or if there were no means of obtaining adequate tissues or associated data as per the protocol requirements. Ethical approvals were first obtained from each Local Research Ethics Committee and Federal Ethics Committee when applicable, as well as from the IARC Ethics Committee.
Defects are observed (black arrows) between the two small cracks (Fig. 5b ) and in the uncracked ligament separating the two small cracks from the main crack tip (Fig. 5c ). Furthermore, the latter area appears darker in the EBSD band contrast map (Fig. 5d ), which is a first indication of locally intense plastic deformation. The band contrast and inverse pole figure (IPF) maps shown in analysis of a secondary internal crack extracted from a pre-charged specimen tested at 10 -5 s -1. Fig. 5d  suggests intense plastic deformation concentrated between cracks. To study these plastic zones, HR-EBSD was applied to calculate the lattice rotation tensor elements (ω ij ) and geometrically necessary dislocation (GND) density (ρ GND ) using the BLGVantage CrossCourt v4. 0 software (Fig. 6 ). HR-EBSD is an image cross-correlation technique utilized on the raw EBSD patterns  [20] , where a reference diffraction pattern is chosen at each grain to relate the state of each other pixel within that grain to this point.
Acknowledgements This research was mainly funded by  Aubert & Duval and Airbus , with the support of  ANRT  ( Association Nationale de la Recherche et de la Technologie ). Fruitful discussions in the  CASHMERE R&T consortium (Airbus ,  Aubert & Duval ,  University of Manchester, Mines Saint-Etienne, La Rochelle University and French Corrosion Institute ) are acknowledged, as well as the material supplied by  Aubert & Duval. The authors wish to express their sincere thanks to  Claire Roume  and  Marilyne Mondon  ( Mines Saint-Etienne ) for their technical support in this study.
Purpose To analyze and summarize the efficacy of immune checkpoint inhibitor (ICI) alone or in combination therapy for renal cell carcinoma (RCC) and urothelial carcinoma (UC) stratified by sex. Methods Three databases were queried in October 2022 for randomized controlled trials (RCTs) analyzing RCC and UC patients treated with ICIs. We analyzed the association between sex and the efficacy of ICIs in RCC and UC patients across several clinical settings. The outcomes of interest were overall survival (OS) and progression-free survival for the metastatic setting and disease-free survival (DFS) for the adjuvant setting. Results Overall, 16 RCTs were included for meta-analyses and network meta-analyses. In the first-line treatment of metastatic RCC (mRCC) and UC (mUC) patients, ICI-based combination therapies significantly improved OS compared to the current standard of care, regardless of sex.
Search strategy This systematic review, meta-analysis, and NMA was conducted based on the guidelines of the Preferred Reporting Items for Meta-Analyses of Observational Studies in Epidemiology Statement (Supplementary Table  1 )  [15]. A literature search on PubMed ® , Web of Science™, and Scopus ® databases was performed in October 2022 to identify studies investigating the oncologic outcomes of ICI monotherapy or ICI-based combination therapies for RCC or UC. The detailed search strategy is described in Supplementary Appendix. Abstracts presented at recent major conferences were reviewed to include unpublished RCTs and trials' updates. The outcome measurements of interest were OS and progression-free survival (PFS) for the metastatic setting and disease-free survival (DFS) for the adjuvant setting.
Data extraction The following data were independently extracted by two authors; studies and the first author's name, publication year, inclusion criteria, agents, number of patients stratified by sex, follow-up periods, International Metastatic RCC Database Consortium (IMDC) classification and objective response rates (ORRs) for mRCC patients. Subsequently, the hazard ratios (HRs) and 95% confidence intervals (CIs) for OS and/or PFS, or DFS were retrieved. The IMmotion151 trial, which compared the efficacy of atezolizumab + bevacizumab versus sunitinib in previously untreated mRCC, did not provide data on differential oncologic outcomes stratified by sex  [16]. In addition, the IMvigor211 trial, which compared the efficacy of atezolizumab versus chemotherapy in mUC, also did not provide data on relevant oncologic outcomes; therefore, these two RCTs were excluded  [17].
Funnel plots were created to evaluate the publication bias using Review Manager 5. 3 Software (RevMan; The Cochrane Collaboration, Oxford, UK, Supplementary Fig. 2 ). For network meta-analysis, we performed a network meta-analysis using random-effect models with a frequentist approach for direct and indirect treatment comparisons with regard to OS, PFS, and DFS  [21, 22]. In the assessment of oncologic outcomes, contrast-based analyses were applied with estimated differences in the log HR and the standard error calculated from the published HR and CI  [23]. The relative effects were presented as HRs and 95% CI  [21]. We also estimated the relative ranking of the different regimens for OS, PFS, and DFS using the surface under the cumulative ranking (SUCRA)  [21]. All analyses were conducted using R version 4.
Acknowledgments We congratulate our colleagues in the  CERN accelerator departments  for the excellent performance of the LHC and thank the technical and administrative staffs at  CERN  and at other  CMS institutes  for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the  Worldwide LHC Computing Grid  and other centers for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies:  SC (Armenia) ,  BMBWF  and  FWF (Austria) ;  FNRS  and  FWO (Belgium) ;  CNPq ,  CAPES ,  FAPERJ ,  FAPERGS , and  FAPESP (Brazil) ;  MES  and  BNSF (Bulgaria) ;  CERN ; CAS, MoST, and  NSFC (China) ;  MINCIENCIAS (Colombia) ;  MSES and CSF (Croatia) ;  RIF (Cyprus) ;  SENESCYT (Ecuador) ;  MoER ,  ERC PUT and ERDF (Estonia) ;  Academy of Finland, MEC , and  HIP (Finland) ;  CEA  and  CNRS/IN2P3 (France) ;  BMBF ,  DFG , and  HGF (Germany) ;  GSRI (Greece) ;  NKFIH (Hungary) ;  DAE and DST (India) ;  IPM (Iran) ;  SFI (Ireland) ;  INFN (Italy) ;  MSIP and NRF (Republic of Korea) ;  MES (Latvia) ;  LAS (Lithuania) ;  MOE and UM (Malaysia) ;  BUAP ,  CINVESTAV ,  CONACYT ,  LNS ,  SEP , and  UASLP-FAI (Mexico) ;  MOS (Montenegro) ;  MBIE (New Zealand) ;  PAEC (Pakistan) ;  MES and NSC (Poland) ;  FCT (Portugal) ;  MESTD (Serbia) ;  MCIN/AEI and PCTI (Spain) ;  MOSTR (Sri Lanka) ;  Swiss Funding Agencies (Switzerland) ;  MST (Taipei) ;  MHESI and NSTDA (Thailand) ;  TUBITAK and TENMAK (Turkey) ;  NASU (Ukraine) ;  STFC (United Kingdom) ;  DOE  and  NSF (USA).
Introduction The first mutations in the gene GNAO1 were uncovered to cause early-onset epileptic encephalopathy (EOEE) in 2013 with the advent of next-generation sequencing  [1]. Since then, a number of GNAO1 mutations have been linked with different pathological phenotypes, primarily including epilepsy and motor development disorders. Developmental delay is also frequently experienced by patients, with variable severity  [2, 3]. Currently, around 80 missense variants in Gαo, the protein product of GNAO1, reported in the ClinVar database  [4]  are assigned the status of "pathogenic" or "likely pathogenic". So far, the specific correlation between the exact mutation and the severity and specific characteristics of the disease remains unclear, with more research being necessary to improve our understanding of the disease.
Trio-based WES revealed the presence of a heterozygous de novo variant in GNAO1 (NM_020988. 3) c. 509C>G p. (Pro170Arg). The variant was interpreted as likely pathogenic according to the ACMG guidelines (PS2, PM2, PP2, PP3). The variant was not registered in the Genome Aggregation Database (gnomAD), and the involved Pro residue is highly conserved across species. The missense Z-score for GNAO1 from gnomAD is 3. 19, indicating that the gene is intolerant to missense variation  [24]. The in silico prediction tool REVEL scored the variant as pathogenic (score 0. 961)  [25]. The girl was also investigated with an SNP array revealing a Turner syndrome mosaicism, which was also confirmed via standard G-banding showing a mos 45,X [6]/46,XX  [24]  karyotype in blood. At her current age of 16 months, her height is -3 SD, which may be due to her Turner syndrome mosaicism, but she does not have other clinical signs of Turner syndrome.
Study design Selection and evaluation phases This study used parallel-selected populations of maize (Zea mays ssp. mays L. ), created by first intermating seven tropical inbred lines to establish a common base population (G0) and subsequently selecting the population for early flowering time at eight field sites for two generations (Fig. 1a ; Supporting Information Table  S1 ). Details about population development and the experimental conditions used for parallel selection were described in a germplasm registration article  (Weldekidan et al. , 2022) ; the populations are publicly available via the US National Germplasm System. Additional information about the parallel selection experiment and evaluation trials is described in Methods S1. Briefly, 2 yr of selection metadata and 2 yr of multitrait evaluation data were combined for this study.
In the 16 evaluation environments, seedling emergence was recorded for each single-row plot. Following germination, eight individual plants from within each single-row plot were tracked and measured for as many as 25 traits (not all traits were measured in both years; Table  S2 ). Therefore, trait measurements were recorded on 1600 individual plants at each of 16 evaluation environments, constituting a final dataset with c. 450 000 phenotypic data points. Weather variables and summarization for separate periods of development Using the geographical coordinate of each field site, daily environmental variables from the 32 site-year environments were obtained using nasapower  (Sparks, 2018). Environmental variables consisted of maximum temperature (T max ), minimum temperature (T min ), relative humidity (RH), solar radiation (SR), and precipitation (P).
Precipitation consisted of just rainfall, even though most fields were irrigated. Additionally, vapor pressure deficit (VPD) was calculated using the R package PLANTECOPHYS  (Duursma, 2015). To control for the impact of temperature on flowering time variation within each environment, days from sowing to anthesis (male flowering) and to silking (female flowering) were converted into growing degree days (GDD), using the SM(B,30-) equation  (Bonhomme et al. , 1994) , with a base temperature of    10°C for planting to emergence and 8°C for emergence to flowering  (Kiniry, 1991). The GDD data were used to define three phases of plant development in each selection and evaluation environment, including periods for emergence, tassel initiation, and flowering time (Methods S1). Weather data from within each site-year environment were then averaged across days per period.
This quantifies the magnitude of phenotypic change for each step of selection, generating 256 estimates corresponding to selection responses linked to the original 16 selection environments (e. g. G1 is selected from G0 grown in a given selection environment) and the 16 evaluation environments (Fig. 3 ). Here, we distinguish sites (fixed locations) from the separate year-environments at each site. Combining the estimates of phenotypic change (dependent variable) and period-specific envirotype data (independent variables), a forward model selection procedure using Bayesian information criterion  (Schwarz, 1978)  was used to identify significant explanatory variables, considering main and interaction effects (Model 5, Methods S2; Fig. 3 ). Both GDD to flowering time and calendar days to flowering time were evaluated as dependent variables.
Acknowledgements This work was supported by the  Agriculture and Food Research Initiative, USDA National Institute of Food and Agriculture , Grant nos. 2011-67003-30342  and  2019-67013-29170 , in addition to the  French National Research Agency  ( ANR-16-IDEX-0006 ) and the  France 2030 program. This study was part of the  Maize ATLAS project (Adaptation Through Latitudinal Artificial Selection ). The maize parallel selection experiment would not be possible without institutional land resources and excellent field crews that support crop research. We are grateful to many staff and student assistants who helped with the fieldwork and data collection. Key contributors we would like to especially thank include:  Jason Brewer  ( USDA-ARS, Raleigh, NC );  Marina Borsecnik ,  Dustin Eilert , and  Dr German Muttoni  ( University of Wisconsin );  David Wills  ( USDA-ARS, MO ),  Miriam Lopez  ( USDA-ARS, Ames, IA ),  Amee Bumguardner  and  Justine Christman  ( Texas A&M University );  Heather Manching  and  Kip Rogers (University of Delaware ).
Sampling of adult trees and seeds The big-leaf mahogany populations studied were located in two Forest Management Units in the western part of the MUZ: Asociación Forestal Cruce a la Colorada (AFICC), covering 20,469 ha; and Cooperativa Carmelita (RL), covering 53,797 ha (Fig. 1 ). Studies were carried out with active support in sampling, experimental set-up, and data collection on the part of community members  (van Zonneveld et al. , 2018a). In each Forest Management Unit, sampling was carried out in three different Annual Cutting Areas, each managed according to a Plan Operativo Anual Forestal (POAF). These POAFs guide timber harvesting and include a geo-referenced census or inventory of individuals of commercial trees larger than 30 cm diameter in the harvest area  (Grogan et al. , 2015).
PCR products were run on an ABI3500 XL Genetic Analyzer (Applied Biosystems, Foster City, CA, USA). The LIZ 500 was used as reference to determine the size of the PCR fragments, using the Peak Scanner v1. 0 software (Applied BioSystems). The final dataset was composed of six of the eleven nuclear microsatellites: sm08, sm28, sm31, sm32, sm39 and sm51. The number of loci was reduced when it became clear that some were replicated (identical loci but named differently), which had not been referenced as such in  Lemes et al. (2002 Lemes et al. ( , 2011)). We found that: sm8 = sm36, sm20 = sm31, sm32 = sm45, and sm39 = sm48.
Genetic diversity analyses We first determined the following genetic diversity parameters: allelic richness (A R ), genetic diversity given as expected heterozygosity (H E ), the observed heterozygosity (H O ), and the inbreeding coefficient (F IS ) using SPAGeDi v. 1-5  (Hardy and Vekemans, 2002). We also estimated the inbreeding coefficient unbiased by null alleles (Fnull) using  the software INEST  (Chybicki and Burczyk, 2009). The influence of forest management practices on the genetic diversity of mahogany was investigated by comparing the genetic diversity parameters: (i) between adults (leaves) and offspring (seeds) for each Forest Management Unit and for each sampling year; and (ii) between samples (adults and seeds bulked together to provide a larger sample size) collected before and after harvest from POAF 2014/2015.
Similarities in genetic diversity parameters between leaves and seeds, and between collecting years, were analyzed using an ANOVA test carried out in R-4. 0. 3. (R Core Team, 2020). The mating system parameters multi-locus outcrossing rate (t m ), single locus outcrossing rate (t s ), and their standard deviations (SD) were analyzed using the Multi Locus Mating System Program (MLTR,  Ritland, 2002). To approximate biparental inbreeding, t m and t s were used as t m -t s , since this difference is used to estimate selfing caused by biparental inbreeding  (Shaw et al. , 1981). The neighborhood size and the gene dispersal distance (σ g ) were calculated using SPAGEDi v. 1-5  (Hardy and Vekemans, 2002). Assuming drift-dispersal equilibrium, these can be estimated for each population relying on patterns of Spatial Genetic Structure, as described in  Hardy et al.
Acknowledgments The funds for the study were donated by the  CGIAR  donors who funded the program " Forests, Trees and Agroforestry " (FTA), by the donors to  Bioversity International , notably the government of Italy; and by the  Austrian Development Agency (ADA). The organizations which provided the funding had no input in study design; the collection, analysis and interpretation of data; the writing of the report; or the decision to submit the article for publication. We acknowledge the Maya Biosphere Reserve (MBR) Forest Concessions Association members and Committees, and particularly thank the  Asociación Forestal Integral de Cruce a la Colorada (AFICC)  and  Cooperativa Carmelita , RL for their trust and participation in this study. We appreciate the support from the  Consejo Nacional de Áreas Protegidas, CONAP , and its personnel:  MSc.
1 mg/mL. Particle shape and size were observed by means of transmission electron microscopy using the high-performance and high-contrast 120 kV JEM-1400Flash Electron Microscope (JEOL Ltd. , Tokyo, Japan) from the Electron Microscopy Service at Univeristat Autònoma de Barcelona (Cerdanyola del Vallès, Spain). For their visualization, samples were placed on a copper carbon-coated grid and negatively stained with uranyl acetate for 1 min at RT. Gatan software V 2. 32. 888. 0 (Gatan, Inc. , Pleasanton, CA, USA) was used to process information and obtain measures from transmission electron microscopy images.
Hemodynamic Measurements The measurement of hemodynamic parameters was performed in fasted conditions (O/n) 90 min after the last treatment administration. Mean arterial pressure (MAP; mmHg) was measured by means of catheterization of the femoral artery and portal pressure (PP; mmHg) via ileocolic vein catheterization using highly sensitive pressure transducers from a PowerLab data acquisition device associated with the physiological data analysis software LabChart 5. 0 (ADInstruments, Dunedin, New Zealand). Superior mesenteric artery (SMA) blood flow (SMABF; (mL/min)•100 g) and portal blood flow (PBF; (mL/min)•100 g) were evaluated with a 1. 0 mm-diameter ultrasonic perivascular flowprobe connected to a TS420 Perivascular Flow Module (Transonic Systems Inc. , Ithaca, NY, USA). SMA resistance (SMAR; (mmHg•min)/(mL•100 g)) and IHVR ((mmHg•min)/(mL•100 g)) were calculated as ((MAP-PP)/SMABF) and (PP/PBF), respectively.
Immunohistochemistry Immunohistochemistry detection of CD32b receptor was carried out on frozen OCTembedded 8 µm sections of rat liver. Sections were incubated with primary antibody against SE-1 (Cd32) at 1/100 dilution (NB110-68095, Novus Biologicals, Centennial, CO, USA), followed by EnVision + Dual Link System-HRP (Dako, Glostrup, Denmark) and visualized with the VIP substrate kit (Vector, Burlingame, CA, USA). Samples were counterstained with hematoxylin. Quantitative analysis of stained areas was carried out with Image J software version 1. 54d (http://imagej. org (accessed on 13 September 2023))  [28]  on ten fields per sample, randomly captured at 10× magnification with an optical microscope Olympus BX61 (Olympus, Hamburg, Germany).
Statistical Analysis IBM SPSS Statistics 20 (IBM, Armonk, NY, USA) was used for statistical analysis. Quantitative results were expressed as mean ± standard error of the mean (SEM) and compared with analysis of variance followed by unpaired Student's t test (between two groups) or one-way analysis of variance (ANOVA) with Tukey's HSD post hoc correction (among three or more groups). When data were not normally distributed, nonparametric tests were applied, using the Mann-Whitney U test to compare two groups and the Kruskal-Wallis test for multiple comparisons. Pearson's correlation coefficient was calculated to show the correlation of two parameters. A p-value ≤ 0. 05 was considered statistically significant.
Acknowledgments: Characterization of the PM was conducted at the  ICTS Nanbiosis , more specifically in the U20 or in vivo Experimental Platform of the Functional Validation & Preclinical Research (FVPR) area (http://www. nanbiosis. es/portfolio/u20-in-vivo-experimental-platform/ (accessed on 18 February 2020 and 22 March 2021).
HPLC Analysis of Baicalin and Baicalin-α-Glucosides Quantification of baicalin and its α-glucosides was performed using an Ultimate 3000 system (Thermo Scientific, Courtaboeuf, France) composed of a quaternary pump (LPG 3400 SD), an autosampler (WPS 3000), and UV and MS detectors (DAD 3000 and ISQ EC, respectively). Software used was Chromeleon 7. 2. 10 ES. Column (Kinetex C8 2. 6 µm, 4. 6 × 100 mm Phenomenex, Le Pecq, France) temperature was maintained at 40 • C. Solvent A was ultrapure water with 0. 1% acetic acid and solvent B was acetonitrile with 0. 1% acetic acid. Flow rate was set at 1 mL/min, and LC gradient was as follows: 0 min, 10% B; 2 min, 10% B; 9 min, 20% B; 12 min, 45% B; 15 min, 45% B; 16 min, 10% B; and 20 min, 10% B. UV absorption was monitored at 280 nm. ISQ EC was in full-scan negative mode at 100-1000 Da, CID was 20 V, dwell scan time was 2 s, SIM widths were set at 0.