dataesr/scientific-paragraphs-categorization huggingface dataset:
Using the same data cutoff as that used for the final OS analysis (October 4, 2018), PROs were assessed and analyzed, as prespecified, in patients with PD-L1 TC ≥ 25% and, for purposes of exploratory analyses, in populations defined by a bTMB cutoff of 20 mut/Mb. Summary statistics were compiled for overall compliance and compliance over time for both the QLQ-C30 and QLQ-LC13 questionnaires. In addition, summary statistics were compiled for all items included in the questionnaires at all assessed time points. Scores for the QLQ-30 and QLQ-LC13 questionnaires were calculated according to the published scoring guidelines or developer's guidelines. The raw scores from the scales in both questionnaires were standardized by linear transformation in order to range from 0 to 100 total. Higher scores for symptom items indicate greater symptom severity; higher scores for function and global health status/QoL items indicate better function and health status.
Acknowledgments The authors thank the patients, their families and caregivers, and all investigators involved in the MYSTIC study ( NCT02453282 ). Medical writing support, which was in accordance with Good Publication Practice (GPP3) guidelines, was provided by  Andrew Gannon, MS, MA , and  Beena John, PhD , of  Cirrus Communications (New York, NY ), an Ashfield company, and was funded by  AstraZeneca. The MYSTIC study (NCT02453282) was funded by  AstraZeneca.
Acknowledgements This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreements No  639638  and No. 883363 ). JAC was partially supported by the  EPSRC  through grant number  EP/P031587/1. FH was partially supported by  Caltech 's von Karman postdoctoral instructorship. FH is grateful to  Camille, Marine  and  Constance Bichet , and  Joachim Schmitz-Justin  and  Rita Zimmermann  for their unbelievable hospitality during the SARS-CoV-2 outbreak.
Quantitative comparison of theory vs experiment In this section, we check that the measured variations in reflectivity R and transmission T can be quantitatively described by the Fabry-Pérot model presented in section 3. According to Eqs. (3), R and T at a given wavelength λ are determined by the complex refractive index ñ = n + iκ and the film thickness h. Thus, the measured reflectivity R and transmission T as a function of the temperature θ L can be fully described, using Eqs. (  4 ) and (  5 ) 2. Using this description, at each wavelength, we can perform a fit of R and T on the two cantilevers up to 500 °C, with H 14 , H 28 , n 0 , a n , κ 0 , θ as the fitting parameters, with H 14 and H 28 the thicknesses of cantilevers C14 and C28 respectively. We apply a least-squares method using simultaneously the datasets from the two cantilevers: a single set of optical parameters is deduced and should describe both thicknesses.
Background: Acromegaly is characterized by excess GH and elevated IGF-I often treated by surgery, pharmacotherapy (somatostatin analogs, GH receptor antagonists, dopamine agonists) and/or radiotherapy. 1 ommon associated comorbidities include cardiovascular disorders and hypopituitarism, often requiring additional pharmacotherapy. 2 We therefore assessed the most common comorbidities and related pharmacological burden in patients with acromegaly in a real-world clinical setting. Methods: The MarketScan database was examined for medical claims from Jan 2010 to Jan 2020. We defined 2 groups: Group 1 -patients with acromegaly (2 diagnoses [ICD-9-CM/ICD-10-CM] on dates within >30 days) who had ≥1 medication for acromegaly since diagnosis, with ≥3 months coverage prior to index date (diagnosis date or first treatment available); Group 2 -a matched cohort (MC) with no acromegaly-related medical claims; direct matching (1:5 based on age, sex and follow-up duration) was performed.
Clinical and radiographic analysis Lower-limb axes were assessed by the surgeon in the preoperative consultation with the patient in bipedal weight-bearing. Demographic data were also collected then. All radiographic measurements were made on the preoperative radiographs: AP knee view under standard weight-bearing, lateral view under unipedal weight-bearing in 20 • flexion as described by Dejour et al. [14] , schuss view in 30 • flexion, and axial patella view following Merchant et al. [15]. TD grade was assessed on lateral view on the Dejour classification  [14, 16]. Patellar height was measured on Caton-Deschamps index  [17]. PFOA stage was assessed on axial patella view on the Iwano classification  [5]. All radiographs were analyzed by 2 blinded orthopedic surgeons, by consensus or with the opinion of a third surgeon.
Statistics Demographic data were analyzed using descriptive statistics. Qualitative variables were reported as number and percentage, and quantitative variables as mean ± standard deviation. Chi-square and Fisher exact tests were used for comparison of qualitative variables. Quantitative variable independence was assessed on Spearman correlation test. Mean values for non-matched groups were compared on Student t-test. Interobserver concordance was assessed on weighted Kappa coefficient (linear system). The significance threshold was set at p < 0. 05. Analyses used R software version 3. 6. 1 (R Development Core Team, Vienna, Austria).
16% FWHM initial energy spread. A small negative skewness (i. e. , a low-energy tail) is introduced in the accelerated spectrum, caused by imperfections in the trailing-bunch current profile compared to the ideal shape described by Tzoufras et al. [19]. To ensure good energy resolution, the spectrometer was configured to form a point-to-point image for the mean energy of the trailing bunch in spectrum measurements both with and without plasma interaction. A 5000-shot high-statistics dataset [Fig. 2(b) ] shows that the energy gain was ð45. 4 AE 1. 4Þ MeV-stable to 3% rms. The energy spread was fully preserved in 6. 4% of these shots [Fig. 2(c )], while the rest had a median energy spread of 0. 2% FWHM (a relative increase of 28%), indicating that the optimal operating point is highly sensitive to even lowlevel jitters in beam or plasma parameters.
Material and methods In 2006, a prospective registry for patients with afDAVF was established at the Montpellier University Hospital Center from which clinical data were retrospectively retrieved and analyzed in this study. From 2006 to 2018, six patients with afDAVF were included in the registry. After multidisciplinary discussion, endovascular treatment of the afDAVF was proposed and accepted by all six patients. All patients underwent six-vessel DSA to visualize the fistula anatomy and plan a treatment strategy. The post-treatment followup included a clinical examination, DSA and MRI at six months and one year, and a visit and MRI at two years. In the absence of signs of residual fistula or symptoms, imaging follow-up was stopped after two years. The patients' characteristics and the afDAVF description (arterial supply, venous drainage and Cognard classification) were extracted from the registry, as well as the presentation symptoms.
Antioxidant activity The concentration-response curve representing the inhibitory effect of D. carota essential oil on DPPH stabilizer group was illustrated in figure  2. The data were expressed as mean ± standard deviation and three repetitions were performed each time. According to our knowledge, no data for the antioxidant activity of the studied essential oil is available in the literature. However, some studies contributed to characterize the effect carrot extract were reported their antioxidant activity  [21]. The essential oil antioxidant effect was determined by IC50 values calculated from equations of lines reporting in Figure  2. The same method was used to measuring the free radical scavenging of ascorbic acid. The low value of IC50 indicates effectively, the strongest activity of the tested sample.
Study endpoints and assessments Efficacy was assessed in the intent-to-treat (ITT) population, defined as all patients randomly assigned to each arm. The primary endpoints were OS and investigator-assessed progressionfree survival (PFS). Secondary endpoints included clinical benefit response (CBR) rate, overall response rate (ORR) per investigator assessment, carbohydrate antigen 19-9 (CA19-9) response, and patient-reported outcomes (PRO) via the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 (QLQ-C30), measured by time until definitive deterioration (TUDD1, defined as time between randomization and first occurrence of a decrease ≥10 points in QLQ-C30 score without further improvement ≥10 points or further data due to discontinuation).
J o u r n a l P r e -p r o o f Response evaluations were performed every 8 weeks and all radiologic scans were assessed for response or progression using RECIST 1. 1 guidelines. Grading for best response was categorized as complete response (CR), partial response (PR), stable disease (SD; ≥8 weeks), or progressive disease (PD). Safety was assessed in the safety population, defined as all patients receiving ≥1 dose of any study drug. Adverse events (AEs) were graded using National Cancer Institute Common Terminology Criteria for Adverse Events, version 4. 03. An independent DMC monitored data on an ongoing basis to ensure the continuing safety of the patients enrolled/randomized in this study.
design RESOLVE (PCYC-1137; ClinicalTrials. gov ID NCT02436668) was a randomized, multicenter, double-blind, placebo-controlled, phase 3 study comparing ibrutinib plus nab-paclitaxel and gemcitabine versus placebo plus nab-paclitaxel and gemcitabine in the first-line treatment of patients with metastatic PDAC. Prior to the randomization portion of the trial, a safety run-in of 6 patients (ibrutinib plus nab-paclitaxel and gemcitabine) was conducted. The results of this safety run-in were reviewed by the Data Monitoring Committee (DMC) and used to determine the ibrutinib dose for the randomized portion (560 mg). Patients were randomly assigned in a 1:1 fashion to receive either ibrutinib in combination with nab-paclitaxel and gemcitabine or placebo in combination with nab-paclitaxel and gemcitabine.
Trial design Detailed methods of the Cryo-FIRST trial (ClinicalTrials. gov Identifier: NCT01803438) have been previously published. 12 In brief, this was a multicentre, prospective, open blind-endpoint controlled randomized (1:1) study to compare cryoballoon CA against AAD therapy in treatment naive patients with symptomatic, recurrent PAF. The steering and publication committees were composed of physicians who assumed a leadership role in the conduct of the study. This study complied with the Declaration of Helsinki and ISO 14155. Local ethics review committees approved the study at each participating centre. The study was sponsored by Medtronic. Data were inputted by each participating centre into an internet-based data collection system (Oracle Clinical), and an independent adverse event committee and Holter core laboratory were used to insure impartial classification of the study events.
Acknowledgements The authors would like to thank the Cryo-FIRST sites and staff for their valuable contributions to this study. Also, the authors thank  Prof. Thomas Neumann  and  Christine Scheld  for their contributions to the  Holter Core Lab , and  Ralf Meyer ,  Rachelle Kaplon ,  Kelly van Bragt ,  Laura Manotta ,  Hae Lim ,  Federica Fonti , and  Alessandra Gentili  from  Medtronic  for support with the study.
For example, Kühn et al. [26]  observed, in the case of an aluminum layer of 300 µm with an area of 0. 3 m × 0. 2 m, the near-field magnetic shielding effectiveness obtained from the Moser model is close to the experimental measurements, especially in the lower frequency range (f < 1 kHz). The frequency range f < 2. 5 kHz is not described correctly by the Schelkunoff decomposition. Both the Moser model and Schelkunoff decomposition match the experimental results by 2. 5 kHz to 200 kHz. Moreover, two numerical models are also implemented in COMSOL Multiphysics: One with an AC/DC module for the near-field application and one with an RF module for the far-field application. Thin-layer modeling is quite challenging, especially for 3D applications. In order to simplify numerical calculations and consider integrating the proposed multilayered composite into future 3D models, a homogenization method  [6]  and Artificial Material Single Layer (AMSL) method  [27]  are used.
By combining both layers, the SE of the trilayer composite is greater than 75 dB for the whole frequency range. Note that the SE at 1 MHz in the near-field is different from the one in the far-field due to the different assumptions of AC/DC and HF approaches. As a consequence, AC/DC and RF modules of COMSOL Multiphysics are limited to their respective range of frequencies and give accurate results only in those frequency bands.
For a low frequency (<10 kHz), this difference is around 1. 9, 0. 9, and 0. 3 dB for a distance d of 3, 2, and 1 cm, respectively. Reducing the sample radius in the numerical model deviates from the infinite plane assumption in the Moser model, and the difference is then greater at around 6. 5, 3. 1, and 0. 9 dB, respectively, for a sample radius of 5, 7, and 10. 5 cm. for the whole frequency range. Note that the SE at 1 MHz in the near-field is different from the one in the far-field due to the different assumptions of AC/DC and HF approaches. As a consequence, AC/DC and RF modules of COMSOL Multiphysics are limited to their respective range of frequencies and give accurate results only in those frequency bands.
METHODS We conducted a case-control study design using patient data and operative video logs from Aquablation clinical trials. Cases were sexually active participants with functional baseline ejaculation and postoperative anejaculation. Controls were sexually active participants with functional baseline ejaculation and no postoperative decline in sexual function. Each case was matched to 1 or 2 controls. Video logs from the procedure were scored for: verumontanum cut coverage, penetration of ejaculatory ducts, depth of cut below the verumontanum, angle offset of verumontanum to centerline of protection zone, number of passes, and intraprostatic calcifications. Conditional logistic regression was used to calculate univariate odds ratios relating anatomic findings to case/control status.
These features allow precise determination of the location of structures and the resecting waterjet. A second limitation is that it was not possible to further characterize the EjD of the cases. For example, we did not ascertain if the cases had retrograde ejaculation. Third, we did not account for a number of factors that have been shown to be predictors of postoperative sexual outcomes, such as underlying comorbidities. Finally, despite a large number of trial participants, our sample size was relatively limited due to the small number of participants who had postoperative EjD. Analysis of a larger dataset and commercial experience may help to determine the role of other anatomic factors in predicting anejaculation after Aquablation. Additionally, double-blind, randomized controlled trials of different Aquablation approaches would further confirm our suggested findings.
The Study RT-PCR testing for SARS-CoV-2 strains was conducted using 2 assays, VirSNiP SARS-CoV-2 Spike del+501 (TIB Molbiol, https://www. tib-molbiol. de) and ID SARS-CoV-2/UK/SA Variant Triplex (ID Solutions, https://www. id-solutions. fr), which target the Δ69-70 deletion and N501Y mutation. We performed tests on 42,229 positive samples collected during January 26-February 16, 2021, from 40,777 persons from 12 regions in France. Most samples came from the general population, and 3,323 (7. 9%) samples came from hospitals. For the 1,397 patients for whom multiple tests were performed, only the fi rst test was considered. We only included data from persons 5-80 years of age to minimize the weight of preschool children and persons living in aged-care facilities in our analysis. Finally, we removed persons whose age or testing region was unknown.
This study was approved by the Institutional Review Board of the CHU of Montpellier and is registered at ClinicalTrials. gov (identifi er NCT04738331). Overall, we analyzed 35,208 SARS-CoV-2-positive samples from the same number of persons (Appendix 1 Table  1 , https://wwwnc. cdc. gov/EID/ article/27/5/21-0397-App1. xlsx). Results of 6,702 (19%) variant-specifi c RT-PCR tests were uninterpretable, mainly because of an insuffi cient amplification of the control, which targets the SARS-CoV-2 N gene. These results were treated as missing in the analyses. Given that most of the variants were B. 1. 1. 7 (Appendix 2 Figure  1 , https://wwwnc. cdc. gov/EID/article/27/5/21-0397-App2. pdf), we grouped all samples bearing the N501Y mutation into a broader class of variant-positive. We used a generalized linear model (GLM) to analyze the binary strain variable (with values wildtype or variant).
Conclusions We used 2 variant-specific RT-PCR tests to detect the fraction of infections caused by SARS-CoV-2 lineages B. 1. 1. 7, B. 351, and P. 1 in regions in France during January 25-February 16, 2021. We did not find any significant difference between the 2 specific RT-PCR kits used, suggesting that similar data collected in France could be pooled. Our results have several practical implications. In general, we found that many infections screened were caused by variants, especially B. 1. 1. 7, and the trend increased over time. On the basis of our estimates, by February 16, 2021, more than half of SARS-CoV-2 infections in France could have been caused by variants, although with pronounced spatial heterogeneity. In a conservative scenario, where all uninterpretable tests were assumed to be caused by the wild type, most infections would have been caused by variants by the end of week 7 of 2021, and the estimated variants transmission advantage was 36% (95% CI 26%-48%) (Appendix 2 Figure  4 ).
The timetemperature data were plotted to obtain the ohmic heating curves for the batter. Electrical conductivity was plotted against the corresponding temperature to obtain the electrical conductivity curves. Electrical conductivity was measured using the following equation: = ( × ) ( × ) (1) Lelect/A denotes the cell constant and is equal to 67. 72 m -1. It is calculated from a calibration, using the method of  Olivera et al. (2013). Solutions of potassium chloride and sodium chloride were used as references, for which their electrical conductivities are known for their temperatures and concentrations.
a b s t r a c t Introduction: Healthcare-associated infections (HAI) are a major public health concern. Monitoring of HAI rates, with feedback, is a core component of infection prevention and control programmes. Digitalization of healthcare data has created novel opportunities for automating the HAI surveillance process to varying degrees. However, methods are not standardized and vary widely between different healthcare facilities. Most current automated surveillance (AS) systems have been confined to local settings, and practical guidance on how to implement large-scale AS is needed. Methods: This document was written by a task force formed in March 2019 within the PRAISE network (Providing a Roadmap for Automated Infection Surveillance in Europe), gathering experts in HAI surveillance from ten European countries.
Results: The document provides an overview of the key e-health aspects of implementing an AS system of HAI in a clinical environment to support both the infection prevention and control team and information technology (IT) departments. The focus is on understanding the basic principles of storage and structure of healthcare data, as well as the general organization of IT infrastructure in surveillance networks and participating healthcare facilities. The fundamentals of data standardization, interoperability and algorithms in relation to HAI surveillance are covered. Finally, technical aspects and practical examples of accessing, storing and sharing healthcare data within a HAI surveillance network, as well as maintenance and quality control of such a system, are discussed. Conclusions: With the guidance given in this document, along with the PRAISE roadmap and governance documents, readers will find comprehensive support to implement large-scale AS in a surveillance network.
This article does not aim to cover all possible IT aspects of AS in depth; rather, it provides practical information and advice on how healthcare data is stored, how IT infrastructure is generally organized and how to succeed with AS in this setting. The development and maintenance of AS systems requires access to a multidisciplinary team of epidemiologists, IPC nurses, clinical physicians, hospital IT staff, software developers, statisticians and project leaders. The intended audience for this document is primarily the infection prevention team, including the medical informatics and data analysts on that team, at the facility and national level. Also, the IT staff of healthcare facilities can use this document for an overview about the topic, although it could serve as a source of information for all readers with a specific interest in healthcare informatics in the context of HAI surveillance.
Scope and definitions The focus is on automated HAI incidence surveillance for the purpose of comparison, prevention and quality improvement initiatives within surveillance networks. AS is defined as any form of surveillance where (parts of) the manual assessment are replaced by an automated process. This is often achieved by algorithms that use source data extracted from data routinely documented in electronic health records (EHR) during care (so-called routine-care data). Surveillance of HAI can be automated to varying degrees, and AS in this document refers to both semiautomated and fully automated surveillance. In fully automated surveillance, the classification of HAI state data (numerator) and denominator data collection are performed by algorithms without any human interpretation, while semiautomated surveillance combines algorithms that retrospectively select high-probability episodes for manual chart review to ascertain HAI state (Box 1).
Semiautomated surveillance of surgical site infections (SSI) The numerator in SSI surveillance is the occurrence of SSI along with details of the infection (e. g. date, depth, causative pathogen). Establishing the diagnosis of SSI usually requires clinical interpretation of the patient's condition using chart review. An example of a semiautomated solution for SSI is a classification algorithm applied to all patients at 120 days after prespecified surgical interventions to stratify according to a high or low probability of having developed an SSI  [15]. Indicators of SSI are collected from routine-care data and dichotomized into subjects with a high probability of SSI (e. g. meeting a prespecified number of indicators), which are flagged for chart review. Every SSI is allocated to a specific surgical procedure.
The denominator for SSI is based on the aggregated number of surgical procedures, making it easy to collect from structured data. documents: centrally implemented AS and locally implemented AS (Fig. 1 ). The main distinctions are based on where the responsibilities for implementing surveillance and developing the algorithms are located. An elaboration of both approaches can be found in the roadmap  [11]. A requirement for incidence surveillance is the classification of both HAI state data and calculation of denominator data. The HAI state data are a binary classification reflecting the presence or absence of HAI for each patient, patient episode or hospital episode, depending on the population definition, while denominator data are based on aggregated data collected from the entire population under surveillance.