dataesr/scientific-paragraphs-categorization huggingface dataset:
The structures were definitively demonstrated on the basis of analytical and spectroscopic data as well as specific experiment that contributed in the stereochemical definition of every single compound. X-Ray diffractometric analyses also corroborated the spectroscopic attributions. Biological assays were conducted to investigate the metabolic and pro-apoptotic activities of the designed compounds. Compound 11 a demonstrated a good capacity to induce cell death and an appreciable nuclear fragmentation was evidenced in cells treated with 11 a. These results nicely fit with some previous observations  [9]  regarding the role of the heterobases and the relative stereochemistry with substituents in C3 of the isoxazolidine ring and these SAR observations pave the way to further studies that require the synthesis of new compounds, even through different synthetic methods already located in our research activities.
X-Ray Crystallographic Analysis of Compounds 8 and 13 a Unit-cell dimensions for compounds 8 and 13 a were obtained by least-squares fit of 2θ values for 25 reflections, using an Enraf-Nonius CAD4 diffractometer with graphite-monochromated Mo-Kα radiation at the Centro Grandi Strumenti (CGS) of the University of Pavia, Italy. The structure was solved by direct method and the Ε-map correctly revealed the non-hydrogen atoms in the molecules. The positions of the hydrogen atoms were located from a difference Fourier synthesis, compared with those calculated from the geometry of the molecules, and refined isotropically in the subsequent leastsquares refinement. The programs SHELXL  [18]  is used to solve the structure. The ORTEP  [19]  program is used for molecular graphics. CCDC depositions numbers: 8, 1981058; 13 a, 1981060.
The amperometric spikes were recorded with a patch clamp amplier (EPC-10, HEKE Electronics) at a constant potential of +750 mV  52, 53  with an Ag/AgCl as the reference/counter electrode. Signals were sampled at 20 kHz, and raw amperometric data were collected using "pulse" soware, and analyzed according to previously described method 52,53,64 using a routine in Igor Pro (Igor Pro, Wave Metrics) kindly provided by Dr E. V. Mosharow in Columbia University. I max and Q values were recorded for each current spike and statistically analyzed provided that the I max value was larger than 6-fold standard deviation of the background noise. Superimposed current spikes and/or spikes with complex shapes were discarded to avoid unwanted interferences.
Acknowledgements We gratefully acknowledge nancial support from the  National Natural Science Foundation of China  (Grants  21725504 ,  21675121 , and  21721005 ), the  University of Xiamen  and the  State Key Laboratory of Physical Chemistry of Solid Surfaces (PCOSS, University of Xiamen, China)  through a  Distinguished Scientist Chair  awarded to C. A. In France, it was supported in part by  PSL University, École Normale Supérieure ,  CNRS , and  Sorbonne University  ( UMR 8640 ). Both teams gratefully acknowledge the  CNRS Sino-French support (LIA "NanoBioCatEchem").
, 2012). Molecular structures of HBI alkenes measured in this study (IP 25 , diene, and triene) can be found in Figure  S1. HBIs were analyzed by gas chromatography-mass spectrometry and quantified by measuring the mass spectral intensities for each HBI in selective ion monitoring mode  (Brown et al. , 2017a). The data were obtained and analyzed using the Agilent Chem-Station software.
Acknowledgments Our sincere thanks to the  Green Edge  project (http:// www. greenedgeproject. info) for providing us with the financial resources to make this research possible. We also thank  Sentinel North  and  Quebec-Oce  ´an for providing financial resources for training purposes. We wish to thank officers and the crew of the  Canadian research icebreaker CCGS Amundsen  for providing the support and facilities during the oceanographic campaign of 2016 in the Arctic. We also express our gratitude to  Cindy Grant  and the sampling team  Katrine Chalut  and  Noemie Pelletier  for their great work in the field campaign. Likewise, we thank the research professionals  Laure de Montety ,  Lisa Treau de Coeli , and  Caroline Guilmette  for the help with the benthos and Geochemistry lab. We are thankful to  Laval University, Takuvik ,  ArcticNet , and  Quebec-Oce  ´an for their contribution in terms of logistic, equipment, and facilities.
Methods: A retrospective multicenter study was conducted that included all patients younger than 18 years with PPGL diagnosed in France between 2000 and 2016. Patients were identified from 4 different sources: the National Registry of Childhood Solid Tumors, the French Pediatric Rare Tumors Database, the French registry of succinate dehydrogenase (SDH)-related hereditary paraganglioma, and the nationwide TenGen network. 2.
A. Patients All patients with a PPGL diagnosed in France between 2000 and 2016 before age 18 years were eligible. Pediatric patients were identified in the National Registry of Childhood Solid Tumors (RNTSE). In addition, all centers of the French Society of Pediatric Oncology (SFCE), the French registry of SDH-related hereditary paraganglioma (PGL. R), the TenGen network, and the French Rare Pediatric Tumor database (FRACTURE)  [9] , as well as all pediatric pathology and surgery units in Paris, were contacted to identify additional cases. There were no specific guidelines in France for treatment and follow-up of pediatric PPGL.
B. Clinical Information A case report form was used to collect demographic, clinical, and biochemical data as well as the tumor histological characteristics, detailed description of the clinical management, and outcome. The family clinical history and the genetic analysis results, when PPGL genetic testing was performed, were also recorded. In accordance with French law, the parents of each child signed an informed consent before genetic testing. Measurements of tumor largest diameter were based on computed tomography imaging. The French FRACTURE database has obtained legal and ethical approval from the French Data Protection Authority (CNIL) registration number DR-2011-408, and date October 14, 2011.
C. Statistical Analyses Statistical analyses were carried out using GraphPad Prism software. Results were reported as medians with ranges for quantitative data, and as numbers and percentages for qualitative data. Overall survival (OS) was defined as the time from diagnosis to death or last follow-up. Event-free survival (EFS) was defined as the time from diagnosis to disease progression, second malignancy, death whatever the cause, or last follow-up. Several prognostic factors (tumor type [PHEO or PGL], tumor size [≥ 5 cm or < 5 cm], quality of surgical resection [complete or incomplete], presence of metastases at diagnosis or not, and identification of a mutation in a PPGL-susceptibility gene vs no germline mutation identified) were evaluated using Peto's test rather than unweighted log-rank tests because the relatively short follow-up time required a specific analysis of late events with very few patients at risk.
A. Demographic and Tumor Characteristics Overall, 77 patients with a PPGL that was diagnosed between 2000 and 2016 were registered in the RNTSE and treated in the 18 SFCE centers participating in this study. In addition, 36 patients with PPGL who were not registered in the RNTSE were identified in the archives of the participating SFCE centers for the 2000 to 2016 period. Among these 113 patients, 81 had available clinical data and were included in the analysis. The tumor characteristics are detailed in Table  1. The tumor site was adrenal in 41 patients and extra-adrenal in 40. The median age at diagnosis was 13. 3 years (range, 2. 2-18 years). In 75 patients (93%), clinical symptoms, such as abdominal pain or high blood pressure, led to the diagnosis. The tumor was detected during a systematic clinical screening in 6 patients identified as mutation carriers in families with PPGL predisposition.
We thus measured nuclear import kinetics over early development (Figs. 1A, S3A-C). While nuclear growth and size generally correlated with import rates, which steadily decreased over development in accordance with Xenopus studies  (Levy and Heald, 2010) , we noted that in very early stages a plateau was reached such that further increase in import rates did not lead to faster nuclear growth (Fig. S3C-E ). Nuclear import rates were also not significantly altered in halved embryos and were similar in 16-cell stage micromeres and non-micromeres (Fig. S3F-G ). However, in 2and 4-cell stage embryos forced to divide asymmetrically with magnetic beads, nuclear import was greater in large blastomeres even though nuclear growth was similar in small and large blastomeres (Fig. 2E -F and S3H). Although these data do not definitively disprove a role for import in nuclear growth, they suggest that growth and import rates can be uncoupled, indicating that import may not serve as the prime local factor limiting and scaling nuclear growth.
Image analysis Images were processed and analyzed with Fiji (ImageJ; National Institutes of Health) and assembled in Photoshop and Illustrator (Adobe). For publication, images were cropped and pseudocolored using Fiji, but were otherwise unaltered. To quantify nuclear size, the maximum cross-sectional (CS) nuclear area was measured using GFP-NLS or mCherry-NLS and nuclear surface area was extrapolated by multiplying by 4. We validated this method for estimating nuclear surface area by showing that actual nuclear volume measured from confocal z-stacks matches well with nuclear volume estimated from the CS area assuming a sphere (Fig. S1B ), showing that the nuclear shape approximates a sphere. This is consistent with previous data from various systems showing that CS nuclear area accurately predicts total nuclear surface area and volume as measured from confocal z-stacks  (Vukovic, et al.
To quantify the radial distribution pattern of the ER (Fig. 4C ), we plotted the mean KDEL intensity in 2. 5 µm wide concentric rings, starting from the nuclear envelope and radiating towards the cell periphery. The area and total KDEL intensity were quantified for the first 2. 5 µm wide perinuclear ring closest to the NE as described above for Fig. 4A  and 4C. This process was repeated for up to fourteen 2. 5 µm-wide concentric rings around the first perinuclear ring, until their radial distribution reached the cell boundary. Mean KDEL intensities were calculated by dividing the total intensity of each ring by its area. In vitro droplet volumes (Fig. 6C-F ) were calculated from droplet diameter measurements. To measure nuclear size, we first compared nuclear volumes quantified from 3D reconstructed confocal z-stacks to nuclear volumes extrapolated from maximum nuclear CS areas assuming spherical nuclei, finding these values agreed within 3% on average (data not shown).
Modeling of nuclear growth kinetics The equation for nuclear stage  ! t can be solved analytically, leading to: 𝑁 ! t = 𝑆 ! !"! -𝑆 !"# 𝐿𝑎𝑚𝑏𝑒𝑟𝑡𝑊 𝑆 ! !"! -𝑁 ! ! 𝑆 !"# 𝑒 ! ! !"! ! ! ! ! ! ! ! (!!! ! ) ! !"# In which  ! ! is the initial nucleus size at stage i (obtained experimentally) and  ! is the initial time. To fit the four parameters, we used Matlab's fminsearch function to minimize the relative error or nuclear size: E = 1 𝑀 (𝑁 ! !"# (𝑡) -𝑁 ! !"#$% (𝑡)) ! 𝑁 ! !"# (𝑡) ! ! ! !!! In which  = 113 is the total number of experimental points. We found the parameters  ! = 52. 07  !! , λ = 0. 171 , α = 0. 546,  !"# = 241. 9 µμm !. This results in a fitting error of 0. 36 % (defined such that  ! !"#$% = 2  ! !"# would yield an error of 100%). The fitting scripts, together with the necessary experimental data, are available online: https://github.
ACKNOWLEDGEMENTS We thank  Matthew Dilsaver  for purifying recombinant Rtn4b protein and  Amanda Johnson  for validating its ER localization,  Abdullah Bashar Sami ,  Miroslav Tomschik , and  Jay Gatlin  for providing recombinant p150CC1, and  Eloise Fadial  for fabricating microfluidic devices. Research in the Levy lab is funded by the  National Institutes of Health/National Institute of General Medical Sciences  ( R01GM113028  and  P20GM103432 ) and the  American Cancer Society  ( RSG-15-035-01-DDC ). Research in the Minc lab is funded by the  Centre National de la Recherche Scientifique  and the  European Research Council  ( CoG Forcaster  no. 647073 ). SD acknowledges funding from the  CNRS Momentum. We acknowledge the  ImagoSeine core facility  of the  Institut Jacques Monod, member of Infrastructure en Biologie Santé et Agronomie and France-BioImaging  ( ANR-10-INBS-04 ) infrastructures.
form of infection where there is evidence of systemic hyperinflammation. Here, systemic inflammation markers are elevated. Patients progress to shock, vasoplegia, respiratory failure and cardiopulmonary collapse. Stage 3 is associated with a poor prognosis. 5  of 11 June 2020, there were 1166 clinical interventional studies registered in clinicaltrials. gov with therapies targeting COVID-19. 7] [8] [9]  Significant inefficiencies in global clinical trials efforts for COVID-19 have also resulted in calls for action from the clinical and quantitative pharmacology community to support streamlining of efforts, including using model informed approaches. 10 ven the dearth of effective antiviral monotherapies for COVID-19, the need to evaluate therapeutic combinations is being re-emphasized, as was initially described in the World Health Organization's Novel Coronavirus Global Research and Innovation forum.
| Simulations Simulations were conducted in R (3. 6. 1) using the RxODE (0. 9. 2) package for numerical integration and the tidyverse (1. 2. 1) family of packages. An R script reproducing these results is provided in Supporting Information Data S1. Each of the five checkpoints (β, k, ρ, δ, c) was probed with seven drug effect levels (0, 0. 333, 0. 667, 1, 1. 33, 1. 67, 2 log10 change) for a total of 16 797 simulation conditions. Each condition was replicated over five intervention times (viral peak at 9-6, -3, 0, +3, +6 days) for a total of 84 035 condition-times. However, simulations were reduced to cases with summed intervention effect between 0. 333 and 2 log10 change, reducing the total simulations to 2310 intervention conditions.
ACKNOWLEDGEMENTS The authors acknowledge the review of the work by  Dr Jeremie Guedj of INSERM  and  Drs Patrick Smith  and  Kashyap Patel of Certara. The authors are grateful to  Jim Gallagher of Certara  in the generation of the graphic. The authors acknowledge review of the work from  Drs Dan Hartman  and  Steve Kern  from the  Bill and Melinda Gates Foundation , and financial support from the  Bill and Melinda Gates Foundation. This work has been supported by the  Bill and Melinda Gates Foundation.
living in the department of Côte d'Or at the time of diagnosis of the primary cancer, and it is the only registry in France focusing on these cancers. Women diagnosed with HR+/HER2-, MBC from January 1998 to December 2016 were retrospectively selected in the registry data and included in this study. Only invasive ductal or lobular carcinomas were included. HR and HER2 status were determined using immunohistochemistry, completed by a fluorescent in situ hybridisation exam in patients with an equivocal result. Pathologists in Côte d'Or usually classify a patient as RH+ when one of the 2 receptors (oestrogen receptor or progesterone receptor) is >10%. HER2 status was retrospectively determined for cases diagnosed before routine analyses. Women who had metastasis after 2016, those who did not receive a systemic anti-metastatic treatment and those who had concurrent CT and ET in the first line were excluded.
Patient population The patients' characteristics and primary results of the RENEW trial (NCT01608490) have previously been reported. 7 This was a retrospective analysis in which we included patients who participated in the RENEW trial and who were treated with coils bilaterally and had evaluable inspiratory and expiratory CT scans at baseline and 12-month follow-up (FU). Furthermore, patients were excluded when they were treated in one or both lobes that were not deemed as the most destructed when analysed by quantitative CT (QCT) analysis. As implanting coils in a lobe of lesser ipsilateral destruction may result in a differing mechanism of action, these patients were excluded from this mechanistic analysis. 8, 9 The RENEW trial was approved by all the 31 trial sites' medical ethical review committees, and all patients provided written informed consent.
To evaluate whether there is a difference in clinical outcome between two potential mechanisms of action, we performed an independent sample t-test to evaluate the difference between patients with and without compensatory expansion of the untreated lobes. Compensatory expansion of the untreated lobes was defined as a change in lobar TLC volume in the untreated lobe of higher than 0 mL. All statistical analyses were performed using SPSS statistics version 23 (IBM, Armonk, NY, USA). P-values of <0. 05 were considered statistically significant.
Spirometry and body plethysmography techniques measure whole lung volumes, while differential effects in treated versus untreated lobes must be expected after coil treatment. In a small cohort of 18 patients, it had been shown for the first time that the lung volume reduction coil treatment reduces the volume and the emphysema score at the treated lobes. 3 In our analysis Data are presented as mean AE SD or number (%). Cardiac comorbidities were based on medical history reported by the investigator and included current coronary artery disease, congestive heart failure or atrial fibrillation, but in a stable situation (subjects were excluded when there was active/symptomatic CAD, CHF (LVEF < 45% on echocardiogram) or uncontrolled atrial fibrillation). † Heterogeneous: ≥15% ipsilateral difference in %LAA950 in both lungs, homogeneous: <15% ipsilateral difference in % LAA950 in both lungs and mixed: one heterogeneous lung and one homogeneous lung.
Background: We conducted this systematic review and meta-analysis to address the crucial public health issue of the suspected association between air pollution exposure during pregnancy and the risk of infant mortality. Methods: We searched on MEDLINE ® databases among articles published until February, 2019 for case-control, cohort, and ecological studies assessing the association between maternal exposure to Nitrogen Dioxide (NO 2 ) or Particular matter (PM) and the risk of infant mortality including infant, neonatal, and post-neonatal mortality for all-and specific-causes as well. Study-specific risk estimates were pooled according to random-effect and fixed-effect models. Results: Twenty-four articles were included in the systematic review and 14 of the studies were taken into account in the meta-analysis.
Search Strategy A systematic literature search was conducted using the PubMed platform which provides access to the MEDLINE ® database and Academic Search Complete databases, among articles published up until February, 2019. The search strategy followed the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines  [11]  and was performed with the following keywords found in articles' titles and/or abstracts: "Air pollution" OR "Air pollutant" OR "Air Pollutants" or "outdoor Pollution" OR "Particular matter" OR "PM25" OR "PM10" OR "Black Emission" OR "Black Carbon" OR "Nitrogen Dioxide" AND "Infant Mortality" OR "Infant Mortalities" OR "Infant Death" OR "Child Mortality" OR "Child Mortalities" OR "Child Death" OR "Child Deaths" OR "Under-one Mortality" OR "Under-one Mortalities" OR "Under-one Death" OR "Under-one Deaths" OR "Neonatal Mortality" OR "Neonatal Mortalities" OR "Neonatal Death" OR "Neonatal Deaths".
Data Extraction For each study, we extracted and reported the following information in several tables: In the first stage, the inclusion criteria were peer-reviewed papers written in English and articles published after 2000 without restriction on geographical location and human studies. We restricted our systematic review on the children aged under 1 year. Papers presenting non-original studies (e. g. , comments, systematic reviews, meta-analysis, reports, case reports, animal and mechanistic studies, and biological experiments) were ultimately excluded. Using these criteria, 173 of the 280 articles published were selected for inclusion. In the second stage, titles and abstracts of the 173 articles were screened. A total of 100 studies were then excluded when they: (i) Investigated adult mortality, other pregnancy, birth, infant, or child outcomes (ii) Considered indoor air pollution, smoking exposure, or were traffic-related (industrial plants, all types of wastes, cooking and biomass fuels consumption, ambient conditions, other environmental exposures) (iii) Dealt with other outdoor air pollutants measured (not including PM 2.
Data Extraction For each study, we extracted and reported the following information in several tables: (i) General information: first author's name, date of study, and country of origin, (ii) Main study characteristics: study design, spatial unit, statistical methods, population definition, main findings (related to infant outcomes and PM 10 , PM 2. 5 , and NO 2 only), (iii) Participant characteristics: information on confounders and exposure measures, (iv) Outcome measures: outcomes classification, definition, and source, (v) Measures of association were extracted including Hazard Ratios (HRs), Odds Ratios (ORs), Relative Risks (RRs), and other metrics measuring the strength of association between mortality and exposure to different pollutants including PM 10 , PM 2. 5 , and NO 2. Where several measures of association were available, we reported those taken from the fully adjusted models.
Sensitivity Analysis In addition, we also evaluated the influence of each individual study on the overall meta-analysis estimate; we implemented several meta-analyses in which the meta-risk is re-estimated, omitting each study in turn (we used the metaninf function in STATA software (StataCorp, College Station, TX, USA). While there is no formal statistical test to prove that such a study should, or should not, be removed from the analysis, we followed two general guidelines to assess the influence of a given study. We analyzed if the point estimate of this omitted analysis lies outside the confidence interval of the combined analysis and second, if the omitted study excessively influenced the significance of the combined risk.
Several studies stratified their analysis on an additional covariate. In 2011, Scheers et al. [25]  analyzed the risk of death among a subgroup of newborns according to their birth weight (low birth weight versus normal birth weight) as well as the studies of Son et al. in 2011  [27]  and  Woodruff et al. in 2008 and 2006 [13,16]. Other authors stratified their analysis according to birth term (preterm versus at term)  [15]. The definition of infant mortality by causes was relatively homogeneous across studies (see Table  S1 ). Among studies investigating respiratory causes of death or SIDS, all but four (which did not give any precision [10,  17, 19, 21] ) based their outcome definition on the International Classification of Disease 9 and 10 (ICD 9-10). Databases were drawn mainly from birth and death certificates as well as from institutes such as the Institute of National Health Statistics or the Ministry of Health (see Table  S1 ).