dataesr/scientific-paragraphs-categorization huggingface dataset:
Disclosures. Ramin Tadayoni reports grants and is consultant for  Novartis, AbbVie Allergan , and Bayer; is consultant for  Alcon ,  Genentech ,  Roche ,  Thea, KHB, Apellis ,  Iveric Bio , and Oculis; his department has received non-financial support from  Zeiss. Glenn J. Jaffe  is a consultant for  Novartis ,  Roche/Genentech ,  Eyepoint pharmaceuticals, Implicit Biosciences, Annexon, Lumithera, Regeneron. Frank G. Holz  reports research grants and personal fees from  Acucela, Allergan, Apellis, Bayer, Bioeq/Formycon, Roche/Genentech, Geuder, Heidelberg Engineering, ivericBio, Pixium Vision, Novartis, Zeiss ; personal fees from  Alexion, Boehringer-Ingelheim, Grayburg Vision, LinBioscience, Stealth BioTherapeutics, Aerie ,  Oxurion. Ursula Schmidt-Erfurth  reports research grants and/or a consultancy fees for Apellis,  Boehringer Ingelheim ,  Novartis ,  Roche ,  RetInSight ,  Genentech ,  Kodiak.
However, on genus level, the addition of ciprofloxacin had a significant impact on the diversity of the microbiota of the in vitro hospital WW biofilm (Fig. 3  and Supplementary Figure  4 a ). As described in methods (supplementary data), a relatively large proportion, between 42% and 70%, of the total RNA reads from the metatranscriptomic RNA sequencing approach of the biofilm communities were transcripts of ribosomal RNA (rRNA) reads. These 16S rRNA reads were filtered out by mapping them on the Silva database, allowing for the taxonomic assignment of a small proportion of those reads (between 0. 68% and 12%) on family level. It is important to note that the taxonomy composition extrapolated from rRNA reads obtained from RNA sequencing after in vitro and in silico rRNA depletion is not directly correlated to the microbial community diversity.
Assessing the expression of ARGs based on the CARD database To identify additional ARGs that were not included in our targeted resistome approach, mRNA reads of our samples were mapped against the Comprehensive Antibiotic Resistance Database (CARD) that archives thousands of gene sequences encoding resistance determinants to antimicrobial agents (see supplemental data for details). ARG expression was higher for in situ hospital WW biofilms compared to their in vitro counterpart (10. 4% and 0. 5% of total mRNA reads respectively) (Supplementary Table  7 ), and lower in the in situ urban WW biofilms compared to their in vitro counterpart (respectively 0. 04% and 0. 4%; supplementary Table  7 ). A 260-fold higher expression level of ARGs was detected in the in situ hospital WW biofilm (10. 4% of all mRNA reads coding for ARGs) compared to the urban WW in situ biofilm (0.
The active resistance mobilome To study the expression of MGEs and more specifically MGEs associated with ARGs, assembled contigs resulting from the RNA-sequencing approach, were mapped against the plasmid sequence collection v0. 4 available at the ACLAME database  (Leplae et al. , 2010). Subsequently, the contigs associated with plasmid identified by this approach were mapped back to the CARD database to specifically identify plasmids carrying ARGs. These ARG-associated plasmids are referred to as the "active resistance mobilome" in the respective samples. Global expression of the active resistance mobilome was very low in all the samples studied (0. 48% of all assembled contigs for hospital in situ biofilm and 0. 14% for urban in situ biofilm (Supplementary Table  7 ). In total, we counted respectively 115 and 66 ARG-associated plasmid contigs for the hospital and urban in situ biofilms and identified a diverse range of plasmid genes (71 individual plasmids identified across all samples) expressing a diverse range of ARGs that could be grouped into 10 classes conferring resistance to antimicrobials, quaternary ammonium compounds and heavy metals.
In front of suggestive symptoms, LPAC syndrome can be confirmed in 3 different ways such as ABCB4 genotyping, bile analysis and abdominal ultrasound  [2] [3] [4] [5]. In  routine practice, abdominal ultrasound performed by an operator trained to look for suggestive signs is the most relevant way to confirm the diagnosis. This expert ultrasound reveals typical anomalies in 80 to 85% of cases  [3] [4] [5] [6]. In our patient, the diagnosis was made with a second ultrasound performed by an expert radiologist, finding a typical comet tail image. Our patient had several previous ultrasounds performed by a non-expert radiologist who was not aware of the suspected diagnosis of LPAC syndrome and did not detect any particular abnormality in this sense. This finding confirms the data in the literature where non-expert ultrasound will describe signs of the disease in only 5% of LPAC cases  [3, 7].
Overall study design This is a multicentric, prospective, population-based dataset in which 600 patients who survived an OHCA and were discharged alive from hospital, are subsequently followed-up using regular phone interviews. Time of study entry corresponds to the day of ICU discharge. After enrollment, we perform a phone interview (visit) at the 3rd month, at the 6th month and every 6 months thereafter. Depending on the date of inclusion, the duration of follow-up is up to 48 months (for the first patients included) and at least 26 months (for the last patients included). (Figs. 1  and 2 ).
Follow-up interviews The first interview took place at the third month after the event and then at the 6th month. Following interviews were performed each semester (Fig. 2 ). A researcher assistant, trained for phone interviews, called patients to submit the different questionnaires. The main investigators from the Sudden Death Expertise Center supervised both training and quality completion of the data using regular monitoring. In severely disabled patients, telephone interviews were carried out with their representatives. To minimize the risk of cohort attrition, up to 6 attempts to reach each patient were provided at different days and hours. For patients lost to sight and impossible to contact, their vital status was assessed at each interview by checking the death registry of the native commune.
Data collection At inclusion, the following data were assessed: the characteristics of the event: location of the arrest, presence of a witness, initial cardiac rhythm, use of a defibrillator, resuscitation interval times, initial treatments (defibrillations, epinephrine or anti-arhythmic treatments. ), pattern of the ECG obtained ROSC, and presumed cause of arrest. the hospital clinical and biological data at admission: repeated measures of temperature, blood tests results at admission (lactate, potassium, creatinine, troponin), coronary angiogram findings (presence of acute or chronicle coronary occlusion, location of lesions and performance of percutaneous intervention), temperature management (intentional cooling, interval times, length of treatment). the outcome during initial hospitalization: occurrence and cause of death, complications (infection, post-resuscitation shock, neurological complications), other treatments (such as coronary artery bypass graft or insertion of automatic internal cardiac defibrillator).
at hospital discharge: destination (home, specialized center, or nursing home), CPC level. During each follow-up interview, the following data have been collected: if applicable, date and cause of death (interview with the next of kin); neurological status using the CPC scale, functional status as measured by OPC and autonomy using the ADL scale; during interviews performed at the 6th month and then every 12 months, HR-QOL assessed by the SF-36 questionnaire that evaluates different aspects (functional, emotional and physical) of QOL; -List of current medications;   Severe cerebral disability (conscious but disabled and dependent). Conscious; dependent on others for daily support (in an institution or at home with exceptional family effort). Has at least limited cognition. This category includes a wide range of cerebral abnormalities, from patients who are ambulatory but have severe memory disturbances or dementia precluding independent existence to those who are paralyzed and can communicate only with their eyes, as in the locked-in syndrome.
It is therefore appropriate to extend the results of previous studies by examining a large sample size, using a longer follow-up (at least over 26 months). Moreover, the originality of the design is based on the repeated measurements (up to 6 repeated evaluations of CPC/OPC scores and up to 4 repeated evaluations of SF 36 scale) and on the variety of the domains explored during follow-up, which will make it possible to evaluate with precision the trajectories of several dimensions of the prognosis of these survivors including neurological, functional and quality of life dimensions. The data collected during hospitalization will also permit to describe the patient characteristics and their initial clinical management. In addition, this registry will provide important characteristics to assess the influence of resuscitation interventions on long-term outcomes, such as early defibrillation or post-cardiac arrest interventions.
Introduction: Pelvic retroversion is a condition for bipedalism. An increase in pelvic tilt (PT) is a sign of compensation, to allow keeping the upright position. It is known that the PT increases physiologically with age and pelvic incidence (PI). However, pelvic anteversion is a much less described. Materials and Methods: 1163 patients from a large ASD database, with no prior surgery or severe hip arthrosis, were included. First, 4 methods were used to define AP: anatomic method (PT<0 ), relative pelvic version method (RPV¼ Measured Sacral Slope (SS) -Ideal SS; anteverted if RPV >5 ), Roussouly method (Pelvic Incidence (PI)<50 and SS>35 ) and low PT method (PT/PI <25th percentile). Descriptive analysis and multiple linear regression were performed to evaluate the relationship between age, PI and PT.
Acknowledgements L. Z. acknowledges financial support from  National Key R&D Program of China  ( 2021YFA0717900 ),  National Natural Science Foundation  ( 21875100  and  62174083 ), the  NSF of Jiangsu Province  ( BK20180338 ), the  Fundamental Research Funds for the Central Universities in China  ( 14380222 ,  14380159  and  14380273 ), and the  Interdisciplinary Thematic Institute SysChem via the IdEx Unistra  ( ANR-10-IDEX-0002 ) within the  program Investissement d'Avenir  and the  Institut Universitaire de France (IUF).
Data and Models This study covers the Argo era starting from 2004, when the Argo array reached a nearly global extent. To focus only on interannual time scales, all data used in this study was processed as follows: (i) the seasonal cycle was removed by subtracting the monthly mean climatology over 2004-2020 and (ii) the data was low-pass filtered using a running mean with a 1. 5-year cutoff period.
5 • × 2. 5 • monthly grids) and JRA55 (1. 25 • × 1. 25 • monthly grids) for the 2004-2020 period were interpolated to the ERA5 0. 25 • × 0. 25 • grid prior to computing the relative contribution of net surface heat fluxes to interannual sea level variations (see Section 2. 4). Air-sea fluxes from atmospheric reanalysis datasets are well-known to show a significant spread in the tropical and subtropical regions, notably because of differences in bulk flux parameterizations (e. g. ,  [44] ). This implies that discrepancies between the surface heat flux contributions derived from ERA5, NCEP1 and JRA55 can be observed; however, the results presented in Section 3. 3 will suggest otherwise. To characterize ENSO events, we use the Niño 3. 4 sea surface temperature (SST) index calculated by averaging the SST anomalies (with respect to the 1981-2010 time mean) in the Equatorial Pacific region of 5 • S-5 • N, 120 • W-170 • W (dark red box in Figure  1a ), from the National Oceanic and Atmospheric Administration (NOAA) Physical Sciences Laboratory (PSL).
The overbars represent the mean temperature or salinity over time. Regional changes in SSL, TSL and HSL are obtained by removing the global mean from each component time series, as described earlier for SLA time series. Recent studies  [46, 47]  identified a significant and fast "salty drift" in the near-real time (NRT) Argo salinity profiles since about 2015. Consequently, a spurious decrease in global mean HSL has been observed with gridded Argo products, which predominantly rely on NRT salinity data after about 2015 rather than the delayed mode (DM) data  [48]. Since the RG climatology quality control procedure  [45]  includes a step to correct salinity drifts by relaxing, when necessary, the NRT values towards the World Ocean Circulation Experiment (WOCE) climatology, the global mean HSL derived from RG climatology remains close to zero during 2015-2020 (Figure  1d  in  Barnoud et al.
These differences can mostly be attributed to: (i) SSL changes in the deep-ocean, which cannot yet be directly considered here due to the lack of Argo data below 2000 dbar, (ii) removing global means based on different spatial coverage from SLA and the steric sea level components, and to a lesser extent, (iii) regional manometric (ocean mass-related) changes. Inherent errors in altimetric measurements and Argo data might also explain part of the observed differences. Overall, we also note a good agreement between the steric components derived from the RG Climatology (solid curves in Figure  1b, c ) and ISAS20 (dashed curves in Figure  1b, c ), although some differences (notably in TSL) are observed during 2014-2016. This suggests that using Argo-based steric data either from the RG climatology or ISAS20 can be considered for assessing the respective contributions of TSL and HSL (despite the GMHSL drift seen with ISAS20 in 2019 and beyond) to the interannual sea level variability in the tropical Pacific and the midlatitude southwest Pacific.
Data Availability Statement: Publicly available datasets were analyzed in this study. The monthly SLA maps were freely downloaded from the CMEMS portal (http://marine. copernicus. eu; last access on 2 January 2023). The ECMWF's ERA5 reanalysis data were freely downloaded from the Copernicus Climate Change Service portal (https://climate. copernicus. eu; last access on 2 January 2023). Time series of the Niño 3. 4 SST anomalies and the AAO index were freely downloaded from NOAA's PSL website (https://psl. noaa. gov/data/climateindices; last access on 2 January 2023). The 15 arc-second gridded bathymetry (GEBCO Compilation Group, 2022) GEBCO_2022 Grid (doi:10. 5285/e0f0bb80-ab44-2739-e053-6c86abc0289c) was also freely downloaded from GEBCO's website (https://www. gebco. net; last access on 2 January 2023).
The Monthly fields of surface fluxes derived from the NCEP1 and JRA55 products were, respectively, freely obtained from the NOAA's PSL website (https://psl. noaa. gov; last access on 2 January 2023) and the Research Data Archive at the National Center for Atmospheric Research (https://rda. ucar. edu; last access on 2 January 2023). This work also acknowledges the use of gridded Argo data (https://doi. org/10. 17882/42182). This data was collected and made available by the International Argo Program and the national programs that contribute to it (https://argo. ucsd. edu; https://www. ocean-ops. org; last access on 2 January 2023). The Argo Program is part of the Global Ocean Observing System.
The nature of the crystalline basement of the Ligurian-Provence back-arc (LPB) basin is a matter debate as it remains unexplored by direct drilling methods. Several models have been proposed for the lower crustal structure comprising hyperextended continental crust or serpentinized mantle. In this paper, a new Vp-Vs geophysical dataset and corresponding tomography are used to propose a new petrological model for the LPB basin and for the formation of the crust of this back-arc domain. By crossing values of Vp, Vs and Vp/Vs ratios, the Messinian salt layer can be clearly identified down to 5 km depth, which highlights salt diapir structures into its overlying sedimentary cover. The 7. 5 km depth corresponds to the transition with a heterogeneous basaltic oceanic crust about 4. 5-5 km thick, intruded by rounded felsic gabbro plutons and underplated by a more mafic/ ultramafic gabbro.
Seismic cross section of the central oceanic domain The 3D Vs model by  Nouibat et al. (2023)  covers the Ligurian-Provence basin and goes down to 100 km depth. This model has been derived using wave-equation tomography of ambient noise data recorded by the OBSs of the AlpArray temporary network  (Hetényi et al. , 2018)   Klingelhoefer et al. , 2008; Gailler et al. , 2008; Leprêtre et al. , 2013; Dannowski et al. , 2020). (2023) as the inversion method used is not the same. This discussion focuses on the portion of LPB following the LOBTSER-P02 profile where Vp is defined. Figs. 3a-b  show the 2D crosssections of the probability of interfaces and Vs computed along the same profile, and the Vp section from  Dannowski et al. , 2020. We are aware that these Vp and Vs models have different resolutions and different sensitivities as they are obtained from different datasets, with different imaging techniques.
In the absence of in situ measurements, satellite observations are the most robust and reliable sources for monitoring and forecasting extreme wind/waves, taking advantage of their availability, regularity, bandwidth, and improved spatial resolution. At present, large multi-mission databases of surface wind and significant wave height (SWH) from altimetry are available to study ocean wind, wave properties, and climate  [14]. Although satellite altimetry suffers from incomplete temporal and spatial coverage, the amount of available data from successive satellite passes enables the calculation of wind and SWH distributions and allows estimating climatological fields, trends, and extreme values prediction  [3, 15]. In addition to existing satellite capabilities for monitoring extreme events, the CFOSAT (Chinese-French Oceanographic Satellite) mission, launched in 2018, can now simultaneously provide the ocean surface wind field and 2D spectral wave distributions.
This investigation is motivated by the present-day enhanced satellite coverage offered by multiple altimeter and CFOSAT-SWIM measurements. For the data analysis, we apply a classical approach based on the theory of self-similarity of wave development, supplemented by the extended fetch/duration concept (see, e. g. ,  [23, 24, 28]  and references cited therein). This approach is now commonly used to describe the waves generated by TC and PL, and is extended here for ETC cases. The paper is organized as the following. 1. Description of two ETCs in North Atlantic selected for the present study is represented in Section 2. 1. 2. Section 2. 2 introduces the satellite data used to investigate surface waves generated by ETCs. 3. A description of profiles of SWHs and the spectral peak parameters (wavelength, direction, and steepness) across the storm area of ETCs is presented in Section 3.
Materials and Methods This section introduces two Extra-tropical cyclones (ETCs) traveling over the North Atlantic from 11 to 15 February 2020, and satellite measurements of surface waves generated by these ETCs. Data on significant wave heights (SWH) of surface waves were obtained from measurements by satellite altimeters Sentinel-3A, Sentinel-3B, AltiKa, CryoSat-2, and JASON-3. In addition, more wave data, namely SWH, spectral peak parameters, and wave spectra, were obtained from China-France Ocean Satellite for Surface Wave Investigation and Monitoring (CFOSAT-SWIM). The hourly fields of wind velocity at the height of 10 meters above the sea surface and the surface pressure taken from the National Centers for Environmental Prediction Climate Forecast System version 2  [33]  (from now on NCEP/CFSv2) were used to identify and trace the selected ETCs and to analyze the surface wave field.
Acknowledgments: CFOSAT-SWIM measurements were provided by  IFREMER Wind  and  Wave operational Center (IWWOC  (accessed on 20 March 2022)), co-funded by  CNES  and  IFREMER. NCEP/CFSv2 data provided by the  OAA/OAR/ESRL PSD, Boulder, CO, USA , from their Web site at NCEP/CFSv2 website (accessed on 24 September 2022). We also acknowledge the  ESA   MAXSS  Project  4000132954/20/I-NB.
BRAIN AND SPINE 3 (2023) 102351 102628 MORBIDITY AND MORTALITY OF MAJOR ADULT SPINAL SURGERY: AN AMBISPECTIVE COHORT ANALYSIS OF 977 PATIENTS E. Xie 1. 1 Xi'an Honghui Hospital affiliated to Xi'an Jiaotong University, Spinal surgery, xi an, China Introduction: Patients admitted at our institution with lumbar spinal stenosis from January 2009 to December 2018 were identified. Patients with full spine adverse events severity system (SAVES) data were included. Materials and Methods: Data on all patients undergoing surgery over a 12month period were prospectively collected using a preoperative morbidity abstraction tool at weekly dedicated mortality and morbidity rounds. Data on uncooperative, preoperative, and postoperative adverse events (AEs) were prospectively collected using the SAVES data collection.
Materials and Methods: The medical records of the DCSM patients who had undergone ACCF from January 2016 to January 2019 in a single center were abstracted. Patients were divided into the 3DP group (28 patients) and TMC group (23 patients) according to the implant type. The hospital stays, operation time, and intraoperative blood loss were compared between the two groups. The modified Japanese Orthopedic Association (mJOA) scores and neck disability index (NDI) were recorded pre-operatively, 2 weeks postoperatively, 3, 6, 12, and 24 months post-operatively for both groups. Radiological data was measured at each follow-up time point to evaluate fusion, subsidence rate, cervical lordosis(CL), fused segment angel (FSA), and mean vertebral height (MVH). Results: The differences between the two groups in operative time, intraoperative blood loss, and the hospital stay were not statistically significant.
1 kit has a double quencher (Zen), which reduces background signal and potential false-negative results that are associated with using certain real-time machines, such as the Qiagen Rotor Gene Q  (5). The qPCR was performed in duplicate on material from single RNA extractions. The samples were run in parallel with the Sabin 1 DNA standards to estimate the viral genome copies present in the samples. A C T value of 40 was assigned to samples that tested negative in the real-time RT-qPCR. To validate comparison of data between qPCR assays, cross-points for the Sabin 1 standards were collected for all qPCR runs and analyzed. There was no significant difference detected between qPCR runs neither at ICL nor at NIBSC, with R 2 ranging from 0. 999 to 0. 984, a slope of 23. 57 to 23. 18, and similar deviations, indicating little interrun variability (data not shown).
ACKNOWLEDGMENTS This work was funded by  Bill and Melinda Gates Foundation  under grant agreement  INV-024477 ; the  Medical Research Council (MRC) Centre for Global Infectious Disease Analysis  (reference  MR/R015600/1  to J. O. A. , A. G. S. , C. T. , and N. C. G. ) jointly funded by the  UK MRC  and the  UK Foreign, Commonwealth & Development Office (FCDO) , under the  MRC/FCDO Concordat  agreement, and also part of the  EDCTP2 program  supported by the  European Union ; and  Community Jameel. We thank  Lucy Williams  and  Elizabeth Gray  from  Imperial College London  for useful discussions on the statistics. We declare no conflict of interest.