dataesr/scientific-paragraphs-categorization huggingface dataset:
Nonstandard Abbreviations and Acronyms For the first scenario, we pooled data from patients randomized to aspirin (aspirin arm from CAPRIE, ESPS-2, CHARISMA, and ESPRIT trials, n=8127). For the second scenario, we combined data from MATCH and CHARISMA trials (n=11 492). Patients randomized to either aspirin or clopidogrel were pooled in a monotherapy group and compared with the dual therapy group comprising those randomized to aspirin-clopidogrel. For the third scenario, we used data from the PRoFESS trial (n=19 589), comparing aspirin-dipyridamole with clopidogrel. For the last scenario, we studied patients included in the CAPRIE trial (n=6201), comparing aspirin with clopidogrel. All analyses were performed according to the intention-to-treat principle. Patients were censored at the time of a major bleed or recurrent ischemic event (depending on the outcome of interest), death or end of follow-up.
(Risk of ischemic event [with treatment A]-Risk of ischemic event [with treatment B])-(Risk of major bleeding [with treatment B]-Risk of major bleeding [with treatment A]). A positive net benefit indicates that the benefits of treatment B outweigh the risks. A major bleed may be deemed less severe than a recurrent ischemic stroke; therefore, we performed a sensitivity analysis including only intracranial hemorrhages instead of all major bleedings. Intracranial hemorrhages were assigned a weight of 1. 5 to account for their generally worse outcome. The same analyses were performed stratified for risk of a recurrent ischemic event, for which we used the Essen Stroke Risk Score (ESRS), originally derived from the CAPRIE data. 21 he score consists of 9 variables (age, hypertension, diabetes, previous myocardial infarction, other cardiovascular disease, peripheral arterial disease, smoking, prior TIA, or ischemic stroke in addition to qualifying event) and ranges from 0 to 9 points (Table  III  in the Data Supplement).
Aspirin-Dipyridamole Versus Clopidogrel For the analysis comparing aspirin-dipyridamole with clopidogrel, we analyzed data from 19 589 patients included in the PRoFESS trial. Among patients randomized to aspirin-dipyridamole, 1146 had a recurrent ischemic event and 403 had a major bleed. Among patients randomized to clopidogrel, 1173 patients had a recurrent ischemic event and 354 had a major bleed. There was no clear preference for either of the 2 treatments according to bleeding risk group when all major bleeds were taken into account (Figure  3 , Table  IV  in the Data Supplement), or when only intracranial hemorrhages were taken into account (Figure IV in the Data Supplement).
Sixth, we could not investigate the influence of stroke subtype (eg, large artery atherosclerosis versus small vessel disease) on the balance between benefits and risks of antiplatelet treatment, as these data were collected in too few patients. In conclusion, we showed that the risk of recurrent ischemic events and major bleedings increase in parallel in patients with a TIA or ischemic stroke included in clinical trials on antiplatelet treatment. Bleeding risk assessment based on patient characteristics cannot be used as single element to guide decision on long-term antiplatelet treatment for individual patients. To meaningfully inform treatment decisions for antiplatelet treatment, stronger predictors for major bleeding and ischemia need to be identified.
Acknowledgments We thank  Sanofi-Aventis and Bristol-Myers Squibb  for giving access to the databases of  CAPRIE (Clopidogrel Versus Aspirin in Patients at Risk of Ischemic Events ),  MATCH (Management of Atherothrombosis With Clopidogrel in High-Risk Patients), and CHARISMA (Clopidogrel for High Atherothrombotic Risk and Ischemic Stabilization, Management, and Avoidance). We thank the  ESPRIT (European/Australasian Stroke Prevention in Reversible Ischemia Trial) Steering Committee  for providing access to the  ESPRIT data. Boehringer Ingelheim Pharmaceuticals, Inc  supported this work by providing access to the clinical trial databases of  ESPS2  (European Stroke Prevention Study-2) and  PRoFESS (Prevention Regimen for Effectively Avoiding Second Strokes).
LP1 and LP2 exhibit the free fiber noise on the loop link (upper link + lower link). They can be used to correct the phase noise of either the upper-or lower-link, for bi-directional or uni-directional set-up  [19]. All the beat notes are then filtered, tracked, and simultaneously recorded by a multi-channel dead-time free frequency counter operated in Π-type and Λ-type with 1 s gate time. At the same time, the temperature and humidity data are logged both in Lab1 and Lab2. For this experiment we added a 50-50 fiber coupler and a polarization analyzer (General Photonics POD-201) at the output port in Lab2, so that the SOP of the light upcoming from the upper-link and that reaches the p-FM can be recorded and analyzed. We record one point per 10 s. A Polarization Controller (PC) is used to optimize the amplitudes of the beat notes without polarization scrambling in a first stage.
This work was supported in part by  Agence Nationale de la Recherche  ( Labex First-TF   ANR-10-LABX-48-01 ,  Equipex  REFIMEVE+  ANR-11-EQPX-0039 ), in part by  Institut National des Sciences de l'Univers, Centre National de la Recherche Scientifique  (Action spécifique GRAM), and in part by the  European Metrology Programme for Innovation and Research in  project  15SIB02  (OFTEN) and  18SIB05  (TiFOON). The EMPIR is jointly funded by the  EMPIR participating countries within EURAMET  and the  European Union.
55/S1-0. 55, S0-0. 35/S1-0. 35, S0-0. 15/S1-0. 15 when DAE molecules are at an arbitrary state with both ring-open and ringclosed forms. As presented in Figure  S12 -S14, the current exhibited the similar evolution trend and 9 distinct levels were obtained for each pair. The results imply that multilevel data storage can be achieved by precisely controlling the programming top gate voltage. When it comes to optical switching, starting from S1-1, the device was exposed to a periodic short time UV pulses. The corresponding dynamic current behavior was displayed in Figure  3c , with enlarged regions in Figure  3d. Note that in order to eliminate the gate bias stress effect, we applied 0 V to the back gate during the measurement. [28] The current decreased progressively after each light dose, proving a continual electron depletion from the WSe2 channel.
Totally 84 UV doses were employed, enabling to reach 84 current states with the final saturation state corresponding to S1-0. The clear current difference between each two neighbouring levels proves the validity of each state. As previously demonstrated, 9 ferroelectric states can be generated at each fixed DAE state. Therefore, with 84 photogenerated levels, the device can ideally yield a maximum number of 756 current levels, corresponding to a memory with a data storage capacity exceeding 9 bit. In order to prove such prediction, Figure  3e  illustrates the multilevel current achieved by controlling both electric field and light illumination during 5 cycles between S1-1 and S0-0. In the first cycle, in the absence of a contribution from P(VDF-TrFE), the current between S1-1 and S1-0 was divided into 5 well-defined levels by illumination with different time of UV dose:10 s S1-0.
55, 20 s S1-0. 35, 40 s S1-0. 15 and 80 s S1-0. Then at S1-0, the device went a step further by switching the P(VDF-TrFE) into Pup direction, arriving at the final state S0-0. The stored optical and electrical information can be erased by vis irradiation and positive bias, restoring to S1-1. In the following cycles, the P(VDF-TrFE) switching step was inserted during DAE switching process. Notably, we found that the polymer switching is accessible from any photo generated interstate and yields 4 new states: S0-0. 15, S0-0. 35, S0-0. 55 and S0-1, confirming our preliminary prediction that the device possesses the unequivocal data storage exceeding 9 bit. Moreover, the interstate obtained by different routes held stable values with negligible standard deviation, proving an accurate readout (Table  S1 ).
In addition, by taking full advantage of the bistability of both DAE molecules and P(VDF-TrFE) polymer, the devices demonstrated an excellent performance in cyclic endurance (10 cycles) and data retention (over 1000 hours), paving the way for their application as high-density nonvolatile memories. This novel ternary Janus device architecture is generally applicable to other 2D materials and stimuli-responsive molecules, thereby opening new opportunities for nextgeneration multi-stimuli-responsive electronics and promoting the development of "More than Moore" technologies by enriching diversification.
Acknowledgements We acknowledge funding from the  European Commission  through the  ERC  projects  SUPRA2DMAT  ( GA-833707 ) and  Light4Function  ( GA-308117 ), the  Graphene Flagship Core 3 project  ( GA-881603 ), the  Agence Nationale de la Recherche  through the  Labex projects CSC  ( ANR-10-LABX-0026 CSC ) and  NIE  ( ANR-11-LABX-0058 NIE ) within the  Investissement d'Avenir program  ( ANR-10-120 IDEX-0002-02 ), the  International Center for Frontier Research in Chemistry (icFRC) , the  Institut Universitaire de France (IUF) , the  German Research Foundation  (DFG via SFB 658, project  B8 ) as well as the  Chinese Scholarship Council. Received: ((will be filled in by the editorial staff)) Revised: ((will be filled in by the editorial staff)) Published online: ((will be filled in by the editorial staff)).
Acknowledgements We thank  Kaustubh Agashe ,  William A. Bardeen ,  David Lin ,  Maurizio Piai ,  Alex Pomarol , and  Alberto Zaffaroni  for useful discussions. The project leading to this publication has received funding from the  Excellence Initiative of Aix-Marseille University  -A*MIDEX, a French " Investissement d'Avenir" programme  ( ANR-11-LABX-0060 -OCEVU  and  AMX-19-IET-008 -IPhU ). This project has received support from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Sk lodowska-Curie  grant agreement No  860881-HIDDeN.
Studies should enroll patients at the time of transplant or shortly after and follow them closely in order to detect early signs of disease before meeting current NIH diagnostic criteria. Patients will need to be followed for at least 1 to 2 years post-transplant in order to best correlate early findings with important late outcomes (Figure  1 , Table  3 ). At least 2 current trials are attempting to identify diagnostic and prognostic signs of chronic GVHD, including both clinical characteristics and biomarkers, one in pediatric patients and one in adult patients (NCT04372524 and NCT04188912, respectively). More specifically, future research efforts should attempt to: a Validate that patient-reported symptoms can predate the development of current NIH diagnostic criteria and determine whether some of these symptoms are closely associated with later development of moderate or severe chronic GVHD.
Patients should be enrolled prior to or shortly after HCT and followed serially every 2 to 3 months for clinical assessments and data collection. efforts using ML should focus on combining known risk factors, provisional early signs and symptoms of disease, biomarkers, patient-reported outcomes (PROs), and other data hypothesized to be associated with chronic GVHD or its outcome (eg, laboratory data, infectious history) to help identify patients at highest risk for morbidity and mortality (Table  3 ). It is important to note the limitations to ML such as lack of standard ML techniques for challenges such as data quality issues and methods for integration of highdimensional data  [56]. A planned CIBMTR study will investigate patient-, disease-, and transplant-specific factors available within the CIBMTR database with predictive ML models to develop a prototype clinical decision support tool to help identify patients at high risk for developing acute and chronic GVHD (GV20-01)  [57].
ACKNOWLEDGMENTS Special acknowledgment goes to the  Meredith Cowden GVHD Foundation, France Lymphome Espoir, NBMTLink ;  Anthony Nolan ,  National Marrow Donor Program ,  BMT Info-Net ; and other patient advocacy groups for partnering and collaboration. Thanks go to all working groups and consensus conference participants, professional societies, US government agencies, and stakeholders in the field of hematopoietic stem cell transplantation for the generous donation of their work, time, talents, and expertise. Particular acknowledgment to the  American Society of Transplantation and Cellular Therapy and European Society for Blood  and  Marrow Transplantation  for their roles in the dissemination, education, and implementation of the concepts and best practices evolving from this project. Special thanks to the independent external peer reviewers who provided they comments and critiques to the 2020 NIH Chronic GVHD Consensus Project:  Nicolaus Kr€  oger, MD, Professor & Clinical Director of the  Department of Stem Cell Transplantation, University of Hamburg, Hamburg, Germany, President EBMT ;  Ryotaro Nakamura, MD ,  Professor & Director  of the  Center for Stem Cell Transplantation City of Hope Cancer Center , Duarte, California;  John DiPersio, MD, PhD , Chief, Division of Oncology; Director, Center for Gene and Cellular Immunotherapy; Deputy Director,  Siteman Cancer Center, Washington University School of Medicine, St.
Data collection and follow-up Preoperative, perioperative, and postoperative data until POD 90 were recorded routinely in a prospective database. Demographic information included age, sex, body mass index (BMI), American Society of Anesthesiologists (ASA) physical status (PS) classification, comorbidities, and previous abdominal surgery. Surgical information included the main procedure (PME or TME), surgical approach (laparoscopic or robotic surgery), duration, and combined procedures. All perioperative care items of our program were prospectively recorded. Overall compliance with 20 items was assessed and expressed as a percentage. Good compliance was defined as a score of ≥ 80% per criteria and/or per patient. Patients underwent a follow-up outpatient evaluation 7 to 10 days after discharge.
The same applies for metabolites in considerable excess in human material as compared to animals when deemed essential from toxicity point of view. Currently no validated test methods are available to conduct these studies. Consequently, in the context of the toxicological dataset submitted for the approval or renewal of pesticide active substance, these studies are either conducted using different experimental layouts or in some cases they are not provided. Therefore, this poses some challenges for the national authorities and EFSA when evaluating the studies received by the applicants during the peer review process of pesticide active substance. In vitro comparative metabolism studies are widely used for pharmaceuticals in various stages of development, from a new chemical entity characterization to a pre-clinical safety assessment and this knowledge could support the use of these studies in the pesticide context  (FDA, 2020).
However, it became clear in the context of the EU pesticide peer review that further guidance on the minimum requirements in conducting in vitro comparative metabolism studies on pesticide active substances and assessing related data would be needed (Outcome of the pesticides peer review meeting on general recurring issues in mammalian toxicology, EFSA, 2016). In addition, following implementation of Regulation (EU) 283/2013, biomonitoring methods for human body fluids and tissues are required. In the absence of a minimal set of data on interspecies differences in metabolism, it could be very complex to address the question of using the metabolism data in rat as a surrogate of metabolism in human for biomonitoring methods. In order to set a common scientific background among all the stakeholders involved in the peer review process (i.
2) would begin with the application of QSAR and read-across methodologies, and proceed to various in vitro toxicological testing methods and batteries. If these approaches do not provide sufficient level of necessary information, in vivo animal toxicity studies, e. g. a 90-day rat study, could be considered. This step-wise approach is in alignment with earlier EFSA guidance documents and scientific opinions. In case a human metabolite is not covered by parent compound and even if a limited toxicological database exists, additional UF can be applied for setting health-based guidance value for this unique human metabolite (Section 6. 3). The additional UF may be determined by expert judgement on a case-by-case basis. It is also possible to apply an additional uncertainty factor for extrapolation of a low observed adverse effect level (LOAEL) to a no observed adverse effect level (NOAEL), or the data from the critical study may be modelled to derive a benchmark dose (lower confidence limit) (BMDL), which can then be used as the reference point (also referred to as point of departure) for the derivation of the health-based guidance value.
The test item The PPR Panel recommends to gather existing knowledge from the open literature (retrieved by means of the literature search, EFSA, 2011) and/or additional databases (e. g. ADME data in US-EPA dashboard 3  , ECVAM databases 4  or OpenFoodTox, see Appendix F) on the test item itself (when it is an existing one subject to renewal) or on structurally similar test items before the comparative in vitro metabolism study is conducted. Other information, e. g. on hepatic clearance, may also be helpful for selecting the test conditions, when a comparative metabolism study is designed. In silico testing, such as QSAR analysis for metabolism prediction can facilitate the planning of the study by postulating the main metabolic pathways in humans and potential human metabolites, including primary and more distal metabolites (also called secondary metabolites, i.
If the problem formulation is to address the uncertainty from human variability in metabolism (currently addressed by a subfactor of 3. 16 of the default UF value of 10 to account for TK differences across humans), the best strategy would be to identify the isoform-specific metabolism in simplified test systems (e. g. recombinant enzymes, microsomes) and confirm results by using hepatocytes from different single donors characterised for their relative (iso)enzyme content. It is expected that comparison and analysis of metabolic pathways between species could be facilitated by using an electronic database like OECD MetaPath  (Kolanczyk et al. , 2012)  if comparative in vitro metabolism is submitted electronically (EFSA, 2021).
The PPR Panel acknowledges that testing of certain metabolites may be challenging, e. g. in case a metabolite is unstable. Therefore, the PPR Panel recommends a tailored testing strategy depending on the nature of the metabolite and by considering whether synthesis and testing of a metabolite is possible. The PPR Panel recommends to assemble, weight and integrate all available evidence in a weight of evidence approach (EFSA Scientific Committee, 2017a,b) in order to reach conclusion on the biological relevance of human metabolites with regard to their toxicity (see Appendix I). Although the different sources of information are reported separately, the PPR Panel recommends to follow an integrated approach to testing and assessment (IATA) (OECD, 2020a) by integrating all available data derived from multiple methods and sources, starting from in silico to in vitro and then to in vivo data.
QSAR and Read-across methods A first step to identify the potential hazard of the metabolite under investigation would be the use of non-testing methods such as QSAR and read-across. These methods allow to infer toxic properties (e. g. genotoxicity or general toxicity) of UHM or DHM based on data for structurally similar substances. The application of QSAR and read across for genotoxicity and general toxicity, and some worked examples, have been previously described in detail in the PPR Panel Guidance on the establishment of the residue definition for dietary risk assessment (EFSA PPR Panel, 2016). Below a brief description of both approaches is presented. QSAR models are statistically based or knowledge-based models which link chemical structure to biological activity for a number of compounds and then predict such biological activity for data-poor chemicals within the same applicability domain.
For the QSAR as well as read-across approaches, it is essential that all steps in the process are well documented so that the adequacy and scientific validity of the approaches can be assessed. The PPR Panel recommends to draw a final conclusion on the similarity between toxic potential of the UHM or DHM and the structurally related chemicals upon the outcome from the QSAR and readacross approaches and other available information, e. g. for in vitro tests, using a weight of evidence approach (EFSA Scientific Committee, 2017a). In vitro methods. Genotoxicity testing of UHM or DHM (in case genotoxicity is not adequately covered by available data or QSAR predictions) should follow the outline of the EFSA genotoxicity testing strategies  (EFSA, 2011; EFSA PPR Panel, 2016 , 2017c). It is important to consider the structure of the metabolite, because this could affect the behaviour of the compound, e.
Risk characterisation Analogously to cosmetic ingredients (SCCS, 2021), an approximate risk assessment to human metabolites could be based on internal doses, if considered justified. For this assessment of the internal dose, the PPR Panel highly recommends building a generic PBK model to estimate the internal human exposure to the parent compound and on this basis also to the metabolites of concern, following the OECD Guidance document on the characterisation, validation and reporting of PBK models for regulatory purposes (OECD Guidance Document No331, 2021). In the absence of data and in judiciously selected cases, the use of an adjusted internal threshold of toxicological concern (TTC)  (Partosch et al. , 2014 ) might be a suitable approach in case of a very low exposure (below 1 µg/kg bw per day).
Work is ongoing to develop robust internal TTC thresholds, especially in the area of cosmetics; meanwhile the SCCS has proposed an interim conservative internal TTC of 1 lmol/L plasma concentration, which is supported by the published experience on pharmaceuticals, a literature review of non-drug chemical/receptor interactions and analysis of ToxCast TM data (SCCS, 2021). This internal TTC value applies only to non-genotoxic substances. If a human metabolite is considered to be covered by toxicological evaluation of a parent compound, also its risk assessment is covered. When the toxicity of a human metabolite is not covered by the parent compound data, even if only a limited toxicological database exists, available data may still be useful for risk assessment. In such cases an additional UF might apply to setting of health-based guidance value for a human metabolite (EFSA Scientific Committee, 2012).
• Development of a database providing quantitative information on the expression and activities of phase I, phase II enzymes and transporters in organs with biotransformation capacity, including the liver, intestine and kidney at the isoform level in test species and humans. • Development of quantitative in vitro-in vivo extrapolation (QIVIVE) and PBK models for each species integrating liver, intestinal, kidney metabolism, etc. , transport and excretion while testing and validating them with pesticide active substances with known and unknown ADME properties.