dataesr/scientific-paragraphs-categorization huggingface dataset:
Article screening and data extraction All articles (abstracts and papers) were screened in duplicate against the eligibility criteria by three reviewers (JOR, CT and EM), and results were recorded by each reviewer independently. Disagreements were resolved by discussion and with other members of the project team where necessary. Data from selected articles were extracted into a standard Microsoft Excel form by a single reviewer. Extracted data were independently checked by a second reviewer. Likewise, risk of bias was assessed and recorded by one reviewer and checked by a second reviewer, using the Cochrane Risk of Bias Tool (Version 2) for randomized controlled trials (RCTs), the National Institutes of Health quality assessment tool for non-randomized interventional studies and the CLARITY tool for cohort studies.
The list of questions for each tool is presented in Table  2. Data on study characteristics, subject characteristics, efficacy/effectiveness and safety were extracted (Table  1 ). The primary outcomes were CD4 counts, HIV RNA viral load, mortality, grade 3/4 adverse events and treatment discontinuation. Additional outcomes are listed in File S1. For binary and categorical outcomes, number and proportion of subjects with the event were extracted, or estimated using available data, while for continuous outcomes, mean, median, range, interquartile range (IQR), change from baseline (start of study drug), regression coefficients and 95% confidence intervals (CI) were extracted. Data reported in figures only were extracted using the online tool "Web Plot Digitizer"  [14].
Study selection The searches for the review were conducted on 12 August 2020 and rerun on 21 March 2021 to capture studies published subsequently. Results of the searches and screening are presented in a PRISMA flow diagram (Figure  1 ). Overall, 3626 abstracts and 371 papers were screened. Nineteen studies relating to dolutegravir and/or raltegravir were included. These studies were published in 17 papers and 14 conference presentations; two studies reported data for both dolutegravir and raltegravir  [16, 17]. Screening of trial registries identified 13 studies assessing dolutegravir and three assessing raltegravir that were either ongoing or completed, but with no published results identified in this review (File S2, Table  S1 ).
Study and subject characteristics Eleven studies reported data on dolutegravir, with median follow-up duration of 6-36 months: one RCT  [18] , one singlearm trial  [19]  and nine observational studies  [16, 17, [20] [21] [22] [23] [24] [25] [26] [27]  (Table  3 ). Six studies recruited subjects from Europe only, three from sub-Saharan Africa only and two from multiple geographic regions (Table  3 ). Of note, three studies included subjects being treated at the same hospital  [20] [21] [22] ; as the study time periods overlapped, some individuals may have been included in more than one study. In addition, we identified two sub-studies of ODYSSEY assessing safety and pharmacokinetic outcomes in children and adolescents with and without tuberculosis  [28, 29]. We included results from these sub-studies if the studies reported safety outcomes not presented for the main trial.
0057)  [23]. A significant difference was also reported for low-density lipoprotein cholesterol (decrease from 109 to 96 mg/dl; p = 0. 025), but the change was not significant for highdensity lipoprotein. S6 ); subjects or events may, therefore, appear in more than one row. Numbers in coloured cells correspond to the number of subjects who experienced events. Where data are reported for grade 3/4 clinical adverse events and for grade 3/4 laboratory adverse events but not for all grade 3/4 adverse events, this is because overlap between clinical and laboratory events was unclear or not reported. * Subjects in the ODYSSEY pharmacokinetic sub-study were also included in the main trial; results.
This review also highlighted the need for further safety data in infants, who were included only in registrational trials  [30, 42]. ODYSSEY has since presented data showing no safety concerns for children weighing <14 kg treated with dolutegravir (median follow-up 120 weeks)  [45]. Two single-arm trials assessing raltegravir in infant populations were identified through searches of trial registries, with planned completion dates in 2019 and 2031 (IMPAACT P1115/NCT02140255 and IMPAACT P1101/NCT01751568). There were also limited data on weight gain in children and adolescents on dolutegravir or raltegravir, although the ODYSSEY trial recently published additional data, showing improved growth with no excess weight gain in children and adolescents on dolutegravir, compared with standard of care  [46].
weeks"; ‡ all children were on raltegravir, ritonavir-boosted darunavir and etravirine; ǁ 13 of the 16 children were on raltegravir, 10 of whom also received darunavir. Abbreviations: 1, first-line; 2+, second-or subsequent-line; A, adolescents; AE, adverse event; C, children; CHIPS, Collaborative HIV Paediatric Study (United Kingdom and Ireland); CoRISPe, Cohort of the Spanish Paediatric HIV Network; discont. , discontinuation; DRV, darunavir; DTG, dolutegravir; Gr 3/4 AE, grade 3 or 4 adverse event; I, infants; IeDEA, International epidemiology Databases to Evaluate AIDS; IMPAACT, International Maternal Pediatric Adolescent AIDS Clinical Trials; mix, mixed or unspecified line of treatment; PK, pharmacokinetics; RAL, raltegravir arm; SoC, standard of care arm.
To mitigate any potential negative connotations that may arise when species were named after a person, place or object, a devised mutation of the assembled list of terms (also known as 'strings') was performed using R code; the terms were mutated using 'gsub' functions. A specific seed was set for reproducibility; before each letter of each term to be mutated the numbers 1, 2 or 3 were randomly assigned using the 'stringi' package in R  [33]. Alternating between each character and its corresponding number, an alphanumeric combination was concatenated. The letter-number combinations were then passed through a three-step script, with each step uniquely changing specific alphanumeric combinations. Substitutions of specific alphanumeric combinations to a new letter were designed to minimally change the phonetics of the resultant term.
bisdtx. org/cms/lib/TX02218757/Centricity/Domain/2450/Scientific%20Root%20Words. pdf for a broad list of affixes and Latin root words). Consequently, just a few dozen roots were used to generate more than 150 unique and linguistically well-formed species epithets. For detailed information on the etymology of all created species epithets, the interested reader is referred to the comments section of the Excel module of ratified ICTV TaxoProp 2020. 095B. R. Leviviricetes; https://ictv. global/taxonomy/ taxondetails?taxnode_id=202107200. Because the same set of species epithets may be used across distinct genera, this set of epithets enabled the creation of the 871 unique species names in combination with the newly created ones. Similar approaches can easily be programmed for any batch of genus/species names; by using various input parameters and diverse sets of affixes the number of created names can be increased as needed in an iterative manner.
Funding information This work was supported in part through  Laulima Government Solutions , LLC prime contract with the  U. S. National Institute of Allergy and Infectious Diseases (NIAID)  under Contract No. HHSN272201800013C. A. C. and J. W. performed this work as employees or affiliates of Laulima Government Solutions, LLC. J. H. K. performed this work as an employee of Tunnell Government Services (TGS), a subcontractor of Laulima Government Solutions, LLC under Contract No. HHSN272201800013C. This publication has emanated from research conducted with the financial support of  Science Foundation Ireland  under grant numbers  SFI/12/RC/2273_P2  and  SFI/14/SP APC/B3032  (J. C. , L. A. D, C. H. and S. R. S). E. M. A. gratefully acknowledges the support of the  Biotechnology and Biological Sciences Research Council (BBSRC) ; this research was funded by the  BBSRC   Institute Strategic Program Gut Microbes and Health   BB/R012490/1  and its constituent project(s)  BBS/E/F/000PR10353  and  BBS/E/F/000PR10356.
Acknowledgements The authors thank  Dr. Petr Formanek  for the Cryo-TEM investigations and  Mr. Andreas Schurig  for the synthesis of BCPs. The authors also thank the  Institut Laue-Langevin  for supplying beam-time under the proposal number 9-12-644 (doi: 10. 5291/ILL-DATA. 9-12-644 ). Open Access funding enabled and organized by Projekt DEAL.
24  In this work, we propose a photonic ANN based on an array of nanolasers, which is able to process and classify two classes of images. As a proof-of-concept demonstration, we process a database containing images of handwritten numbers. In terms of ANN architectures, our scheme corresponds to an input layer given by the input image (pixels in a 2D real space), an output decision layer given by the optical spectrum (pixels in the 1D frequency space), and hidden layers given by the nanolaser array. Th  input image is encoded into a spatially modulated pump beam. Therefore, each input pixel may excite many different nanolasers, and each nanolaser emission is connected to many output pixels because of the Fourier transformation that is performed all-optically. Thus, the result of the classification task-to fix the ideas, yes if the image has a handwritten zero, no otherwise-is read from the optical spectrum of the light emitted by the nanolaser array.
This work is organized as follows: Sec. II presents the model used to describe the nanolaser array and introduces the definition of a particular type of collective mode, known as zero-mode. Section III describes the use of zero-mode lasing for binary classification, i. e. , to determine whether an image that is encoded in the spatial profile of the pump corresponds (yes/no) to a particular digit. The dataset used, the machine learning algorithm developed to optimize the system's performance, and its implementation are described in Secs. III A and III B. Sections IV-VI-present the results obtained, the discussion, and the conclusions, respectively.
Therefore, for classification purposes, if the frequency separation between zero and non-zero modes is large enough such that they can be spectrally resolved using optical filters before detection, zero-mode lasing can be used for binary classification. For a proof-of-concept demonstration, we consider an 8 × 8 array, and we use a freely available database of images of handwriting numbers (details are presented in Sec. III A). Let us consider an image of a handwritten zero, for instance, the one shown in Fig. 1 , top left corner, and resize it to a 8 × 8 matrix of pixel values, I  (1). To encode the image information into the pump profile, P  (1)  , we define an appropriate transformation matrix M such that P  (1)  = |MI  (1)  |, where the absolute value ensures that the elements of the pump profile are not negative.
A. Machine learning optimization of the linear transformation matrix Clearly, the choice of the transformation matrix, M, is crucial for obtaining a good classification performance. As previously stated, we are interested in using the zero-modes as detectors of a class of input images, and thus, we want a zero-mode to turn on if and only if the pump pattern encodes an image that represents the digit of choice. In this section and Sec. III B, we will describe how to optimize the array elements of M in order to obtain the best possible classification skills. We have employed the digit dataset freely available at the University of California-Irvine (UCI) ML repository,  28  which is a standard dataset for assessing the performance of image recognition systems. We used images that have a resolution that fits the size of the nanolaser array (8 × 8).
A. One-vs-one classifier The one-vs-one classifier is, on average, the most precise. In the case of the ultra-narrow filter, if we simply look at the performance metrics, we have the best classifier; the algorithm only fails on one example of the test set. In Fig. 2 , we report two examples of classification for a 0 and of a 1. As we can see, the images are correctly classified, but the difference in frequency between the zero-mode and the non-zeromode is very small. To understand this small difference, we plot in Fig. 3 (a) the distribution of the frequencies of the lasing for the whole image dataset. We can identify two main regions: one at extremely low real parts-limited to the floating point numerical resolution-that contains the zero-modes and another one between 10 -4 and 10 -1. The latter has a bimodal distribution with a main peak above the selection threshold and a minor secondary peak right below.
We stress that our aim is not to overcome the performance of state-of-the-art in silico classifiers as a perceptron or a random forest can perform very well on this dataset, achieving nearly 100% accuracy both in the train and the test sets of the binary classification we considered here. Instead, our goal is to show that a nanolaser array can serve to implement an all-optical multilayer ANN device, a longstanding goal in optical computing, which is expected to outperform single layer NNs in problems where classification cannot be linearly approximated, such as non-convex problems, including the XOR logic-gate. As a matter of fact, as explained in Sec. II, by virtue of the sublattice decomposition, the 2D nanocavity array with nearest-neighbor couplings can actually be mapped to a bi-hiddenlayer system-the checkerboard-without any intralayer coupling.
Occasionally, garnet (Grt), quartz (Qz), phlogopite (Phl), and amphibole (Amp) grains can be found. Thermodynamic modelling was conducted using Perple_X  (Connolly, 1990). The thermodynamic database used was from  Holland and Powell (1998) , and we chose melt (HP), Gt (HP), Pl(h), Pheng (HP), and Omph (HP) as solution models  (Holland & Powell, 1996 , 1998 , 2001 , 2003; White et al. , 2001).
The piston-cylinder experiments were performed at the Institut de Physique du Globe Paris, France. The recovered samples were embedded in epoxy, cut lengthwise, polished, and carbon coated for microstructural analyses in the scanning-electron microscope (SEM). The SEM analyses include low-and high-magnification images taken in backscatter electron (BSE) mode, energy-dispersive X-ray spectroscopy (EDX), and electron-backscatter diffraction (EBSD). The BSE images were taken at an acceleration voltage of 20 kV, and the EBSD maps were acquired with an acceleration voltage of 10 kV and a step or pixel size of 0. 5 μm. The EBSD data were processed using the open-source crystallographic toolbox MTEX  (Bachmann et al. , 2010). We considered non-indexed pixels to have a mean angular deviation value <1 and non-indexed grains to contain less than 2 indexed pixels (<1 μm).
5 GPa. However, due to the sample geometry as well as due to graingrain contacts, stresses may have been locally much higher. These high differential stresses would lead to a twin-induced temperature increase of $110 C to 160 C and of $80 C for sample G_2. 5_700. Considering an error for the temperature of $20 C together with the uncertainty of modelling partial melting using thermodynamic databases, a temperature increase of 80 C due to twinning shear in conjunction with a high defect density may have caused partial melting along deformation twins in sample G_2. 5_700. Thus, under high stresses in the GPa range due to elevated deformation rates, twinning shear could initiate local melting at background temperatures significantly lower than the melting point. This is especially interesting for situations in which dry and therefore strong plagioclase-rich rocks survive metastable at HP high temperature conditions of the eclogite-facies  (Austrheim & Griffin, 1985; Stünitz & Tullis, 2001; Tullis & Yund, 1992).
ACKNOWLEDGEMENTS The authors want to thank the handling editor  Katy Evans  and the two reviewers,  Jun Muto  and  Holger Stünitz , for their thorough reviews that helped improving this manuscript and especially thank  Holger Stünitz  for additional discussions. S. I. is very grateful to  Marieke Rempe  for the fruitful discussions during coffee breaks and walks, to  Jörg Renner  and  Ralf Dohmen  for helpful comments on the experimental results, and to  Christopher Beyer  for discussions on crystal melting. S. I. thanks  Damien Deldicque  for the EBSD analyses performed at ENS Paris. S. I. and A. S. thank  Yanbin Wang ,  Nadège Hilairet , and  Julien Gasc  very much for their help during the experiments, and M. B. thanks  Julien Siebert  and  Nicolas Wehr  from the  Institut de Physique du Globe Paris  for the support during the piston-cylinder experiments.
Statistical analyses For time-to-first-event analyses, differences between the placebo and empagliflozin groups for the primary endpoint across the various BMI categories were assessed for statistical significance using a Cox proportional hazards model, with pre-specified covariates of age, gender, geographical region, diabetes status at baseline, left ventricular ejection fraction, and eGFR at baseline. These analyses were performed according to the intention-to-treat principle for all randomized patients and included data up to the end of the planned treatment period. Event rates per 100 patient-years and adjusted hazard ratios (HR) are reported for each BMI category. For the analysis of total (first and repeated) events, between-group differences were assessed using a joint frailty model, with CV death as a competing risk.
| Study design and population The source population for this cohort study consisted of the participants of the Hokusai-VTE trial (NCT00986154). 37 The Hokusai-VTE trial was an international, randomized, double-blind, noninferiority trial evaluating the efficacy and safety of edoxaban (30 or  The present Hokusai PTS study is part of the Hokusai post-VTE study, which is dedicated to assessing long-term outcomes (NCT04007653). We previously reported the methods and findings of the Hokusai post-PE study. 38 In short, in 2016, we approached 78 study centers, based on the number of patients included in the original Hokusai-VTE trial (>10 patients) and language, and located in Austria, Australia, Belgium, Canada, Denmark, France, Germany, Italy, the Netherlands, New Zealand, Norway, United Kingdom, and United States of America to participate in the Hokusai post-VTE study.
Data were entered in an international database platform (castor EDC database). Additionally, the original Hokusai-VTE trial database was accessed and data on characteristics during trial inclusion (VTE history, thrombus characteristics, and management of DVT) as well as allocation of treatment were retrieved. In this database, compliance with edoxaban or matching placebo was analyzed as the percentage of doses taken of the planned number of doses during the study treatment period. Compliance with warfarin was analyzed by using the subjects' duration of time in the INR therapeutic range of 2. 0-3. 0 during the study treatment period. The study protocol was approved by the institutional review board of Amsterdam UMC, University of Amsterdam (NL587525. 018. 16), and by local review boards in all participating centers.
Aims: Pharmacovigilance signals of heart failure (HF) following exposure to protein kinase inhibitors (PKIs) have been detected in recent years. Our aim was to identify the PKIs most frequently associated with the development of HF. Methods: Using the French National Healthcare Database, all patients newly exposed to a PKI between January 2011 and June 2014 were followed up for 18 months. Specific hospitalization diagnosis and long-term HF-related disease codes were used to identify HF patients. HF incidence rate ratios (IRRs) were measured and adjusted hazard ratios (aHRs) were estimated using a Cox model. Sensitivity analyses were performed to limit the potential indication and competitive risk bias. Results: Thirteen PKIs were studied. Among the 49 714 new PKI users registered during the study period, the mean IRR of HF was 3.
| Description of drug management in HF The management of HF occurring in patients after exposure to PKIs was described, specifying the overall and cardiovascular drugs dispensed (using ATC codes) from 1 year prior to the onset of heart failure to 1 year after, divided by the number of patients. All analyses were conducted using SAS statistical software (version 9. 4; SAS Institute, Cary, NC, USA) and R Studio software (CRAN version 1. 3).
| DISCUSSION The current study investigates the occurrence of HF following exposure to PKIs using data from a medical administrative database (SNDS). Of the 13 PKIs studied, six were found to be significantly associated with an increased incidence of HF: dasatinib, ruxolitinib, crizotinib, everolimus, pazopanib and vemurafenib. The onset of HF appeared to occur relatively early, with more than half of the events occurring within 6 months of introducing the PKI. The incidence rate ratio of HF in our study population was increased compared to the general population. The predictors associated with the occurrence of HF corresponded with the main predictors described in the literature: age, male gender, diabetes, cardiovascular history and use of antihypertensive and lipid-lowering drugs. 24, 25 Our sensitivity analyses confirmed this risk for dasatinib, ruxolitinib, pazopanib and everolimus.
Our results are noticeably different from those documented in the study previously conducted by our team using the global pharmacovigilance database, VigiBase. Dasatinib is the only PKI to be significantly associated with an increased risk of HF in this study and the previous one. 10 is may be explained by the differences in the medicinal products studied, the methodology applied (case/noncase analysis versus survival analysis) and the data sources used (reporting versus medical administrative data). Indeed, data based on spontaneous reports are subject to an under-reporting bias and cannot be used to estimate the incidence of an adverse drug reaction. A nested case-control study conducted in Israel using medical administrative data showed that among the 13 PKIs studied, four were found to be significantly associated with an increased risk of HF: trastuzumab, cetuximab, panitumumab and sunitinib.
T A B L E 2 Thus, their confidence intervals were particularly wide, ranging from 0. 37 to 11. 92 and from 0. 77 to 7. 93, respectively. The lack of patients exposed to vemurafenib resulted in a lack of power, and vemurafenib was the only PKI indicated for melanoma. We were therefore unable to estimate an aHR in subgroups by indication and thus we cannot exclude an indication bias for this PKI. Several potential mechanisms of cardiotoxicity have been suggested, but they remain unclear. 15, 27, 28 e main strength of this initial study in France is the nearexhaustive nature of the data analysed at national level using data from the SNDS. These data include the healthcare consumption data of more than 65 million French people, that is, 98% of the French population, thus reflecting the entire French population and constituting one of the largest healthcare databases in the world.
We were not able to adjust for all covariates not recorded in the SNDS and involved in the occurrence of HF, such as smoking or obesity, but we were able to adjust for the major covariates. There are inherent limitations to the use of data from medical administrative databases, such as patient compliance, which cannot be verified, or the presence of potentially unobservable periods of drug intake, such as during hospitalization. A competing risk of death was present in our analyses and might overestimate the occurrence of the event of interest. However, we have taken this risk into account by performing a Fine-Gray model, which was consistent with our primary analysis. Moreover, a significant patient loss was recorded for everolimus and pazopanib in the metastatic kidney cancer subgroup (29.