dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS The authors gratefully acknowledge the staff of the  Kampong Cham Referral Hospital , the patients and parents who participated in the study, and the  Arbovirus Team in the Virology Unit at the Institut Pasteur du Cambodge  who contributed to this study. We acknowledge the contribution of the ICAReB facility in setting up the recruitment of donors and the acquisition of blood samples, in particular  Gloria Morizot ,  Bianca Liliana Perlaza ,  Sophie Chaouche ,  Linda Sangari ,  Céline Chapel ,  Philippe Esterre  and  Hélène Laude. We are most grateful to  Christine Girard-Blanc  and  Evelyne Dufour  for their contribution in producing and purifying the recombinant DENV NS1 protein. We thank  M. Nilges  and the  Equipex CACSICE  for providing the Falcon II direct detector and  David Vreesler  for his help in acquiring the first electron microscopy images of the bovine NS1-HDL complex.
Molecular Weight Analysis of EPS Molecular weight of the purified EPS was checked on a gel permeation chromatograph (GPC) equipped with TSK gel guard PWXL, TSK gel GMPWXL, and TSK gel G-2500 PWXL (7. 8 × 300 mm) columns (TOSOH, Tokyo, Japan) in conjunction with a refractive index detector. Two hundred microliters of 3 mg/mL EPS was injected and eluted with 0. 1 M NaNO 3 solution at 40 • C at a flow rate of 1. 0 mL/min. Data were detected and processed using the EcoSEC software (Tosoh Bioscience, Tokyo, Japan). Molecular weights were calculated using pullulan standards (Sigma-Aldrich, St. Louis, MO, USA).
The cDNA was analyzed by qPCR (Applied Biosystems, Carlsbad, CA, USA) using the TaqMan Probe-Based Gene Expression analysis system in combination with TaqMan Gene Expression Master Mix containing ROX (Applied Biosystems). Quantification of MMP1 (Hs00899658_m1), MMP2 (Hs01548727_m1), MMP3 (Hs00968306_g1), HAS1 (Hs00987418_m1), HAS2 (Hs00193435_m1), SPT1 (Hs00370543_m1), TNFα (Hs99999043_m1), IL-1β (Hs01555410_m1), IL-6 (Hs00174131_m1), IL-13 (Hs00174379_m1), ZO-1 (Hs01551861_ m1), OCL1 (Hs00170162_m1), and GAPDH (Hs03929097_g1) transcripts was performed using gene-specific primers. Expression data were normalized against the corresponding level of GAPDH. To compare mRNA levels between groups, relative mRNA levels were calculated using the 2 (-∆∆CT) method.
Electric vehicle charging load dispatch We consider three different types of interactions between PEVs, drivers, and the electric grid: immediate charging, smart charging, and vehicle-to-grid (V2G). Further detail on their formulation is presented in the Supplemental Information. For all three types, we derived the temporal and locational travel patterns based on data from the National Household Travel Survey (NHTS)  [25]. Data for vehicle trips in California were extracted from the U. S. -wide database to coincide with the study region. These data were then filtered by removing from consideration trips without a personally-owned vehicle, with survey errors (i. e. infeasible average speed), and chains that did not start and end at home. Of the remaining trips, vehicle data on trip distances and dwelling times at different locations (home, work, etc.
) were recorded. Vehicle trip data was combined with parameters for PEV charging infrastructure such as locations where charging stations are accessible and their peak charging power. Here, we assume that charging is performed at home and work only and that peak charging power at each location is 6. 6 kW. Previous studies have shown that home represents the longest proportion of vehicle dwelling time (75%) with an average dwelling time of 10 h  [7] , followed by work (14%) with an average dwelling time of 6 h  [7]. Therefore, these locations represent much of the opportunity for charging. A 6. 6 kW charging power was selected due to its prevalence as the conventional Level 2 charging power. With immediate charging, PEV drivers plug in their vehicles immediately upon arrival to a location with available charging stations and do not communicate with the electric grid.
The vehicles charge at the station's full power until either the battery is full or the driver unplugs the vehicle. The hourly profile is developed strictly based on the NHTS travel patterns. With smart charging, PEV drivers provide their local utility with information on the expected dwell time for that charging session and the required additional charge that must be provided by the end of the session upon plugging in. Within these constraints, the local utility will control and shape the vehicle charging profile to minimize charging costs. Here, smart charging will optimize the PEV charging load profile in response to the net load demand and seek to maximize the uptake of variable renewable generation. This exercise is conducted for each vehicle in the filtered NHTS dataset for each trip throughout the year to produce the hourly-resolved PEV charging load profile.
Acknowledgments The authors gratefully acknowledge partial support of this work by the  Office of Science of the US Department of Energy  as part of research in the Multi-Sector Dynamics, Earth and  Environmental System Modeling Program  led by the  Pacific Northwest National Laboratory  Contract No. 508509. This material is also based upon work supported by the  Directorate for Social, Behavioral and Economic Sciences of the National Science Foundation  under Award No. 1829343. The views expressed in the article do not necessarily represent the views of the DOE or the  U. S. Government. The authors are also grateful to the  #EnergyTwitter community  which enabled the authors of the study to meet and hosted the initial discussions of ideas that led to this study. Credit author statement Brian Tarroja: Conceptualization, Methodology, Investigation, Resources, Writing e original draft, Writing e review & editing, Funding acquisition, Eric Hittinger: Conceptualization, Methodology, Writing e review & editing.
Parameters and data collection In this geo-epidemiological study, we assessed the ecological factors associated with in-hospital COVID-19 incidence, mortality, and case fatality rates across the 96 administrative departments of France during the national lockdown. Ecological factors included the spatiotemporal spread of the epidemic before the national lockdown, demographic structure of the population, baseline intensive care capacities, baseline population health and health-care services, new chloroquine and hydro xychloroquine dispensations, economic indicators, urbanisation, and climate. Numbers of suspected COVID-19 outpatients were not systematically recorded by the French surveillance system coordinated by Santé publique France (Public Health France). Indeed, most infectious cases, symp tomatic or not, were not detected during the first epidemic wave, and, due to a shortage of tests, RT-PCR tests were reserved for in-hospital cases.
However, confirmed (by RT-PCR) or probable (according to clinical and CT-scan signs) in-hospital COVID-19 cases and deaths were systematically compiled by Santé publique France from March 19, 2020, onwards. We downloaded these in-hospital data, aggregated at the departmental level, from the open data portal of the French Government (appendix pp 1-3), and we calcu lated cumulative values from March 19 to May 11, 2020, covering the first national lockdown. Inci dence rate was defined as the cumulative number of in-hospital COVID-19 cases per 100 000 inhabitants, mortality rate as the cumulative number of in-hospital COVID-19 deaths per 100 000 inhabitants, and case fatality rate as the cumulative number of in-hospital COVID-19 deaths per cumulative number of in-hospital COVID-19 cases. Before March 19, 2020, COVID-19-associated deaths at the departmental level were routinely declared by the Regional Health Agencies (Agences régionales de santé).
Statistical analysis We calculated in-hospital COVID-19 incidence, mortality, and case fatality rates for each of the 96 administrative departments of metropolitan France. We mapped these indicators and deviations from nationwide rates. We also estimated spatial autocorrelation using Moran's I statistic for areal data (Queen criterion of contiguity). 20 o analyse the factors associated with epidemiological indicators and avoid the curse of dimensionality and multicollinearities, we first summarised multi dimensional factors using a non-supervised classification technique: hierarchical ascendant classification on principal component analysis. 21 To classify departments into similar age-pyramid profiles, we did a principal component analysis on the relative composition of the 5-year age and sex population groups, and we then included the coordinates of each variable in the first 25 principal components in a hierarchical ascendant classification.
Spatial adjustments were verified by Moran I statistics on Pearson residuals. Sensitivity analyses of the three models were done by substituting the three outcomes (incidence, mortality rate, and case fatality rate) by emergency allergies and in-hospital allergies among patients at emergency departments, and in-hospital allergies among emergency allergies (appendix pp 11-13). All analyses and maps were made using the software program R version 4. 0. 0 and the tidyverse, mgcv, FactoMineR, rgdal, spdep, and dagitty packages.
This effect of the lockdown strategy is in line with other publications that are based on modelling or observational studies. Among them, Salje and colleagues  15  and Di Domenico and colleagues  24  estimated that the lockdown reduced the reproductive number by 77% in France and 81% in Île-de-France. Using databases across 149 countries, Islam and colleagues 25 also estimated that earlier implementation of lockdown was associated with a larger reduction in the incidence of COVID-19. Mortality rate was also strongly associated with the incidence rate of in-hospital COVID-19 cases, even after adjusting for the interaction between incidence and the relative lag to lockdown. However, the number of ICU beds available in 2018 was not associated with mortality or case fatality rate. In addition, we found no association between baseline population health and health-care services and incidence and mortality rates.
We included numbers of chloroquine and hydroxychloroquine dispensations in our models because previous statements suggested that this might be responsible for the lower COVID-19 burden observed in some regions. 18, 19 owever, our findings do not support this hypothesis because chloroquine and hydroxy chloroquine dispensations were not associated with in-hospital incidence, mortality, or case fatality rates at the departmental level. We could not include data for in-hospital dispensations, which are not publicly available in France, and the prescription of chloroquine and hydroxychloroquine for COVID-19 was limited by a French regulation on May 26, 2020, after the end of our study period. Although univariate analyses showed important associations between in-hospital incidence and mortality rates and new chloroquine and hydroxy chloroquine dispensations, these associations were positive (ie, higher chloroquine and hydroxychloroquine dispensations were associated with higher incidence or mortality rates).
28 The age of patients admitted to hospital for COVID-19 has not been made available at the departmental level to account for these differences. This factor could partly account for why our multivariate analysis explained only 44•6% of the case fatality rate. Additional factors might also have been associated with case fatality rate, suggesting a need for further analysis at a more accurate scale. For instance, it was not possible to analyse ethnicity, because this characteristic is not recorded in French databases for legal reasons. Finally, this was an ecological study rather than an individual population study, which introduces classical ecological fallacy. Even if the sensitivity analyses support our results, we cannot infer any direct individual risk,  29  nor interpret the results in terms of causality.
Study design and participants COMBI-v (ClinicalTrials. gov: NCT01597908) was an open-label, randomized, phase III trial (N ¼ 704) that included previously untreated patients with unresectable stage IIIC or IV BRAF V600E/ K-mutant melanoma (per American Joint Committee on Cancer Staging Manual, 7th edition) treated with dab þ tram or vemurafenib monotherapy. Study design details were published previously  (16). For comparison, treatment-naive tumor samples from 95 patients with BRAF V600 wild-type melanoma were randomly selected at the Essen Department of Dermatology. The study was approved by the ethical committee of the University Hospital Essen (approval No. 16-7190-BO). COMBI-v was conducted in accordance with the provisions of the Declaration of Helsinki and Good Clinical Practice guidelines.
Digital pathology A duplex CD3/CD19 IHC assay was developed. CD3 and CD19 were selected as pan-T-cell and B-cell markers to assess both immature and mature cellular patterns. Duplex CD3/CD19 IHC staining (n ¼ 59) using anti-CD3 (clone LN10) and anti-CD19 (clone BT51E; both of Leica Biosystems) was performed on the Leica Bond Rx autostainer. Slides were scanned at 20Â magnification using Aperio AT2, Leica digital whole-slide scanner. Digital image analysis (IA) was performed using the multiplex IHC module, HALO v2. 3 software platform (Indica Labs). Analysis enabled clear distinction of melanoma tumor nests (or tumor compartment) and intratumoral and peritumoral stroma (or stroma compartment) and excluded lymphoid tissue (Supplementary Fig. S1 ); melanoma lesions were annotated by a pathologist in collaboration with imaging scientists.
Statistical analysis Comparison of groups defined by gene expression was performed using a Cox regression model; HRs and 95% confidence intervals (CIs) are presented. Univariate Cox proportional hazards models were fitted to assess or rank the importance of biomarkers on clinical response. Kaplan-Meier nonparametric survival function estimates were fitted and plotted to visualize the survival characteristics of specific subgroups. For continuous biomarker values, we used optimal cut point determination as implemented in the R Maxstat package v0. 52. 2. P values derived from this method were corrected using a conditional Monte Carlo-based method. The multivariate Cox proportional hazards model was generated using the R Survminer package.
Data sharing Novartis is committed to sharing with qualified external researchers, access to patient-level data, and supporting clinical documents from eligible studies. Requests are reviewed and approved by an independent review panel on the basis of scientific merit. All data provided are anonymized to respect the privacy of patients who have participated in the trial in line with applicable laws and regulations. This trial data availability is according to the criteria and process described on ClinicalStudyDataRequest. com. The BMS-CA209-038 data set is available in the Gene Expression Omnibus (GSE91061; ref. 17). All TCGA data are available through the NCI Genomics Data Commons Data Portal (https://portal. gdc. cancer. gov/).
Transcriptional B-cell profile We used an in-house GES (Supplementary Table  S3 ) to evaluate the association of the transcriptional B-cell profile with clinical survival outcomes. High B-cell GES strongly associated with improved OS and contained independent prognostic information compared with T-cell expression in the TCGA melanoma data set (Supplementary Figs. S4A  and S4B ) and in patients with melanoma treated with nivolumab [BMS-CA209-038 data set  (17) ; Supplementary Figs. S4C  and S4D ]. When we analyzed the transcriptional immune profiles of COMBI-v biomarker data sets 1 and 2, almost all GES of specific immune-cell subpopulations (e. g. , T cells, B cells, macrophages) significantly correlated with each other; therefore, most immune GES were associated with positive clinical outcomes.
Acknowledgments We thank the patients and their families for their participation. We also thank the study site staff; additional investigators;  Noelle Hanoteau ,  Catarina Campbell ;  LaSalette Charette ,  Annette Quail , and  Nan Fei Jiang  from the  Novartis Precision Medicine In situ Diagnostics IHC/ISH Team ;  Navigate BioPharma ; and others for their contributions. We also thank  Matthew Squires  ( Novartis Institutes for Bio-Medical Research ) and  Maurizio Voi  ( Novartis Pharmaceuticals Corporation ) for guidance and critical review. Medical writing assistance was provided by  Zareen Khan, PhD  ( ArticulateScience LLC ), and was funded by  Novartis Pharmaceuticals Corporation. The trial was originally sponsored by GlaxoSmithKline; dabrafenib and trametinib were designated as assets of Novartis on March 2, 2015, after which Novartis took over sponsorship of the trial.
S1 ). In the microfluidic setup, these vSUVs were injected in the top channel so that, when a fusion pore opens, ions can flow from one side of the suspended membrane to the other through the fusion pore and the α-hemolysin channels (Fig. 1B )  (14). A -80-mV voltage was applied between the two sides of the tPLM, and series of 5-s current measurements separated by 0. 5 s for data saving were acquired at 100 kHz. The corresponding current noise of the raw data in the 5-s traces was ∼1 pA, as observed, for instance, in SI Appendix, Fig. S2A. As expected, sudden current increases were observed when vSUVs containing ∼70 outward facing vSNAREs were injected on the tPLM (Fig. 1C ). These current jumps typically occurred over a few milliseconds. Then either the current decreased back to zero or remained plateauing for up to several seconds at a few tens of picoamperes.
Data were collected until the permanent background increase due to many hemolysins on tPLM after several fusion events. Data Analysis. Detection of the small pores. The typical noise in the raw current data was ∼1 pA. To detect the small nascent fusion pores, we chose to perform two separate procedures: a rolling average over 10 traces and filtering by removing the frequencies around 50 Hz, that is, the standard frequency of alternating current in Europe, and above 10 kHz. The two resulting and independently obtained sets of traces display a typical noise of ∼0. 2 pA to 0. 3 pA for the initial 5-s traces. After several fusion pores have opened, some α-hemolysin channels have diffused in the tPLM. Their conformation fluctuates slightly, and sometimes they display opening/closing cycles. These fluctuations increase the background noise to a level that is unacceptable for the detection of small pores.
Hence, when the noise increased above 0. 3 pA, we disregarded the subsequent 5-s traces. Once the two sets of traces were obtained, sequences in which the current was higher than 1 pA for 2 ms or higher than 0. 3pA for 5 ms were automatically detected by a homemade MatLab script. Then, we manually analyzed these events to verify they actually correspond to fusion pores, that is, to remove the small electric glitches that can occur and that are often characterized by positive currents followed by unrealistic negative currents. Derivation of the pore diameter from the measured current. To obtain the apparent pore diameter, we used α-hemolysin as a reference. With the HK buffer, we measured that the conductance of hemolysin is 0. 125 nS. Hence the current passing through a α-hemolysin channel is I h = 10 pA.
Calculation of the energy landscapes. The distributions of instantaneous apparent diameters presented in Fig. 3A  contain 0. 1-nm bins. Calling f i the fraction of pore diameters in bin i, and f max the maximum of these fractions, the energy for the apparent diameter i is -k B T ln(f i /f max ), where k B T is the thermal energy. The results for both pore sizes are presented in Fig. 3B. Data Availability. All study data are included in the article and/or SI Appendix.
ACKNOWLEDGMENTS. This work was supported by a European Research Council funded grant under the European Union's  Horizon 2020 research and innovation program  (Grant Agreement  669612 ) to J. E. R. and F. P. and by Grant  ANR-14-1CHN-0022-01  (to J. E. R. ). J. -B. F. acknowledges funding from  SFB1027 (Deutsche Forschungsgemeinschaft ). We are grateful to  Prof. Thomas Söllner , who first suggested the use of protein channels to probe fusion with current measurements.
Protein Overexpression and Purification The exonuclease-deficient (exo -with the mutations of D222A and D327A) RB69pol variant gene was a gift from Professor William H. Konigsberg (Yale University, New Haven, CT, United States ) and amplified by PCR using a 2,720 thermal cycler (Applied Biosystems). PCR was run in ThermoPol buffer (New England Biolabs) using Pfu DNA polymerase (New England Biolabs). The forward and reverse primers of RB69pol RB69pol (5′-CGC GGA TCC ATG AAA GAA TTT TAC TTA AC-3′ and 5′-CCG CTC GAG TCA AAA ATC GAA CAT ATC G-3′) were designed from the nucleotide sequences in GenBank, accession numbers AAP75958. 1. The amplified genes and the modified pET28b expression vector were digested using BamHI and XhoI and then ligated into the expression vector, which was used to transform Escherichia coli strain BL21 (DE3).
). The final crystallization conditions were obtained via optimization from the initial crystallization setup performed using Natrix HT (Hampton Research). Crystals were grown at 21 °C in 2 μl of the drop containing equal volumes of the protein/DNA solution and the reservoir solution, which was composed of 50 mM sodium cacodylate (pH 5. 0), 2-7% (v/v) isopropanol, 5 mM MgCl 2 , 2 mM NaCl, and 12 mM spermine. The crystals were cryo-protected by transferring them to the reservoir solution supplemented with 30% (v/v) polyethylene glycol 400 (PEG 400) and flash-frozen in liquid nitrogen for data collection.
Structure Determination A complete data set was collected at a resolution of 2. 2 Å at 100 K at BL-NW12A of the Photon Factory, Japan. Data were indexed and initially processed using the HKL-2000 package  (Otwinowski and Minor, 1997)  and then reprocessed using iMOSFLM  (Battye et al. , 2011)  and merged using AIMLIESS in the CCP4i package  (Battye et al. , 2011). The crystals of the RB69pol-P/T complexes belonged to the P3 2 21 space group and had the unit-cell dimensions of a b 164. 44 Å, c 165. 60 Å, α β 90 °, γ 120 °. Assuming one dimeric RB69pol-P/T DNA complex molecule was in an asymmetric unit, the Matthews coefficient was 2. 23 Å 3 /Da, which corresponded to a solvent content of 45%  (Matthews, 1968). Initial molecular replacement calculations were performed using Phaser in the CCP4 suite  (McCoy et al.
, 2007)  using search models derived from the previously reported structure (PDB ID 3nci) after the P/T duplex, the C-terminal tail, and the Fingers domain were removed  (Franklin et al. , 2001). Afterward, the P/T duplex, the Fingers, the C-terminal tail, dUpNpp, and Ca 2+ were manually built using Coot  (Emsley et al. , 2010) , followed by automated water picking with ARP/wARP  (Langer et al. , 2008). Several steps of manual rebuilding and refinement of this structure were performed using Coot and Refmac5  (Murshudov et al. , 2011) ; the final crystallographic R value was 19. 3% (R free 24. 5%). The statistics for data collection and refinement are summarized in Table  1.
RESULTS AND DISCUSSION The Crystal Structure of the Two Polymerase Complexes From Bacteriophage RB69 We crystallized the exonuclease-deficient RB69pol complex with the P/T duplex and determined its structure at a resolution of 2. 2 Å with a free R-factor of about 24. 5% (PDB ID 7f4y) (Table  1 ). Two RB69pol- P/T complexes are present in one asymmetric unit (Figure  1A ). The N-terminal domain (NTD) of RB69pol and the part of the P/T duplex away from the active site participate in the dimerization of the two complexes. One RB69pol-P/T complex (MolA) is identified as a new closed ternary complex with dUpNpp, which was similar to many other known ternary complexes of this enzyme. However, this complex contained only one divalent metal ion. The other complex (MolB) is identified as a new open binary RB69pol-P/T complex in the pre-insertion state but without dUpNpp bound and with a vacant dNTP-binding pocket.