dataesr/scientific-paragraphs-categorization huggingface dataset:
Data source All data were obtained from the French National Healthcare Data System (Système National des Données de Santé, SNDS), which gathers data on reimbursements received by beneficiaries of the main health insurance schemes, covering about 98% of the French population. This medical administrative database contains anonymized individual patient data. The diagnoses related to long-term conditions (LTC) and hospital stay diagnoses (including main, related and associated hospital diagnoses) are identified in specific SNDS tables using International Classification of Diseases -10th revision (ICD-10) codes. Reimbursed medicinal products issued in the community are identified by their Anatomic Therapeutic Chemical (ATC) code.
2 | METHODS 2. 1 | 221 Data source All data were obtained from the French National Healthcare Data System (Système National des Données de Santé, SNDS), which gathers data on reimbursements received by beneficiaries of the main health insurance schemes, covering about 98% of the French population. This medical administrative database contains anonymized individual patient data. The diagnoses related to long-term conditions (LTC) and hospital stay diagnoses (including main, related and associated hospital diagnoses) are identified in specific SNDS tables using International Classification of Diseases -10th revision (ICD-10) codes. Reimbursed medicinal products issued in the community are identified by their Anatomic Therapeutic Chemical (ATC) code.
Intervals with obvious large-scale inhomogeneities, comparable to the size of the interval, are disregarded and the dataset is further refined by trimming or removing intervals based on an assessment of the Taylor hypothesis at the spacecraft separation scale and the convergence of the magnetic correlation length, resulting in the 60 intervals used in this study. Further details about the examination of the Taylor hypothesis and magnetic correlation lengths are discussed in Section III and Section IV, respectively, and a demonstration for the example interval is provided in Figure  1h-j. Within each interval, the background plasma properties are characterized using temporal averages over the entire interval. Denoting the temporal average with. , the background 8 This is the author's peer reviewed, accepted manuscript.
Therefore, a Walén test is not incorporated into the automated portion of the reconnection event identification. These criteria result in an over-selection of potential reconnection events and a manual inspection and refinement of each event is performed to select those which appear most consistent with reconnection. This procedure results in the identification of 256 events or ∼ 10% of the observed intense current structures undergoing reconnection. Based on the length of each turbulent interval, roughly one reconnection event is observed every two minutes on average in the dataset. The locations of the observed reconnection events in the example interval are marked with solid red lines in Figure  1g. The possible presence of ion jets in the reconnection events is assessed by examining the Walén relationship between ∆V A,L and ∆u i,L , in which a change in correlation between these two quantities is expected within the current sheet for a reconnection-driven ion jet.
PLEASE CITE THIS ARTICLE AS DOI: 10. 1063/5. 0071106 A potential bias can be introduced into the distributions due to the finite time resolution of the measurements, since it will not be possible to observe a reconnecting current sheet below a particular thickness for larger u i,N 10di and a fixed measurement cadence. To examine the impact of this bias, Figure  8b  and Figure  9b  show the same analysis of the cumulative distributions, but limiting it to reconnection events where u i,N 10di < 250 km/s and the current sheet thickness > (250 km/s) × (0. 06 s) based on twice the temporal resolution of the electron measurements. These criteria limit the analysis such that all permitted current sheet thicknesses are observable at any u i,N 10di in the dataset if a given reconnection event were of that thickness.
However, the behavior of the electron jets and current sheet thicknesses with λ C appears to be consistent with electron-only reconnection becoming more prevalent as λ C gets shorter, in accordance with expectations from laminar and turbulent numerical simulations. The results provide observational evidence that the correlation length of the turbulence can impact the nature of turbulence-driven reconnection, thus influencing the small-scale nonlinear dynamics and dissipation of the turbulent fluctuations. The dataset compiled through this work will likely be useful for directly comparing with turbulence simulations containing magnetic reconnection, such as those performed in Refs. 67 and 82. However, importantly further work needs to be done to explore how to connect diagnostics associated with the global configuration of a turbulent current sheet that can be extracted from a numerical simulation to the more local current sheet diagnostics that can be extracted from the 1D spacecraft trajectories through an event  138.
ACKNOWLEDGMENTS JES is supported by the  Royal Society University Research Fellowship   URF\R1\201286. JPE is supported by  UKRI/STFC  grant  ST/S000364/1. TDP is supported by  NASA  grant  80NSSC20K1781  and  National Science Foundation (NSF)  grant  2024211. ILG is supported by the  Royal Society University Research Fellowship   URF\R1\191547. MAS is supported by  National Science Foundation (NSF)  grant  AGS-2024198. The French LPP involvement for the SCM instrument is supported by  CNES  and  CNRS. The authors thank the entire  MMS  team for their work on the mission and the  International Team "Unravelling Solar Wind Microphysics in the Inner Heliosphere " supported by the  International Space Science Institute  for invaluable discussions.
Swift-XRT catalog: 2SXPS The 2SXPS catalog  (Evans et al. 2020 ) was used to test our classification method. It consists of 206335 unique sources covering 3790 deg 2 of the sky, detected during 1. 1 million observations of the Swift X-Ray Telescope (XRT;  Burrows et al. 2004 ) during its first 13 years of operations (from 2005 January 1 to 2018 August 1). The rather uniform sky coverage of 2SXPS and its typical sensitivity of co-added images of ∼ 1. 7 × 10 -13 erg s -1 cm -2 make it a great database for serendipitous searches. For each source, the location, fluxes in all three bands (0. 3-1 keV, 1-2 keV, and 2-10 keV), hardness ratios, quality flags and association with other catalogs are given. Some spectral parameters resulting from an absorbed power law or APEC (Astrophysical Plasma Emission Code,  Smith et al.
Correlations between X-ray catalogs were used to build for each source a light curve of X-ray observations and compute their maximum to minimum flux ratio. Second, we built a sub sample of known sources, henceforth called the "reference sample", by cross-correlating their positions with catalogs of stars, AGN, XRBs, CVs, and ultraluminous X-ray source (ULX) candidates (Table  2 ). Finally, we selected a test sample of unknown sources, similar to the reference sample in terms of data quality to test our classification under proper conditions.
(5) the soft, medium and hard bands were used to compute this column. (6) a positional crossmatch between 2SXPS, 4XMM-DR10 and CSC2 was done to identify sources in common and gather their observations in a single light curve. (7) P varP chiSnapshot band3 is the probability that the source flux is constant between Swift snapshots in the hard band. See  Evans et al. (2014)  for more details. (8) given by the GLADE  (Dalya et al. 2016 ) association. (9) given by the catalog of Gaia distances  (Bailer-Jones et al. 2021). (2014) for more details) for determining if the two positions agree. We therefore performed our own positional crossmatch using TOPCAT version 4. 5. 1  (Taylor 2005). Besides the catalogs mentioned above, we broadened the search for optical counterparts to the catalogs Gaia Early Data Release 3 (EDR3; Gaia Collaboration et al.
Acknowledgements. This research has made use of several tools and services that we acknowledge here: TOPCAT version 4. 8 (Taylor 2005) ; the VizieR catalog access tool 2 , CDS, Strasbourg, France (Ochsenbein et al. 2000); " Aladin sky atlas " 3 developed at  CDS, Strasbourg Observatory, France  (Bonnarel et al. 2000;Boch & Fernique 2014); the SIMBAD database 4 , operated at  CDS, Strasbourg, France  (Wenger.
3 software) using anti-glycophorin A-FITC (1:100) and anti-CD71-FITC (1:200) and anti-TER119-PE (1:400), respectively, and data were analyzed using FlowJo (version 10. 7. 1) (Supplementary Fig. 21 ). Four non-GLP rat toxicity studies were performed for MMV693183: ( See the summary of the study design in Supplementary Table  31. Nine-week-old Wistar (Crl:WI (Han)) rats were obtained from Charles River Laboratories (Domaine des Oncins, Saint-Germain-Nuelles, France). The Test Item (MMV693183) was administered by oral gavage at different doses and dosing regiments (Supplementary Table  30 ). Animals were examined daily for any altered clinical signs, body weights, and food consumption. Blood samples were taken at different timepoints after the test item administration, and toxicokinetic exposure assessed under the defined experimental conditions and analyzed using Phoenix (version 6.
PK parameters were calculated by naïve pooled approach using WinNonLin software (Phoenix, version 6. 3). In vivo Pharmacokinetic-Pharmacodynamic (PKPD) relationship. The effect of MMV693183 on P. falciparum Pf3D7 0087/N9 and Pf3D7 20161128TAD17N214 66 was investigated in vivo using female NSG mice (Charles River) and was assessed in three different studies at TAD (The Art of Discovery, Spain) using their standard protocol (Supplementary Table  30 )  67. Briefly, humanized mice were engrafted daily with 0. 7 ml of 50%-75% hematocrit human erythrocyte suspension until the end of the drug administration period to obtain a minimum of 40% human erythrocytes in peripheral blood during the entire experiment. Subsequently, mice were injected intravenously with 35. 1×10  6  infected RBCs in a volume of 0.
Samples were processed under liquid-liquid extraction methods and analyzed by LC-MS/MS for quantitation in a Waters UPLC-TQD (Micromass, Manchester, UK). The lower limit of quantification for MMV693183 ranged from 1 to 5 ng/ml, depending on the study. Data preparation, exploration and model pre-and postprocessing were performed using R (version 3. 6. 3) and R package IQRtools (version 1. 2. 1 IntiQuan GmbH). Non-linear mixed-effects (NLME) modeling was used to estimate the PK and PD parameters using Monolix (Lixoft version MLX2018R2). The population PKPD model was developed with a two-stage approach: first, a population PK model was determined; then, the individual PK parameters were used as regression parameters and the PD parameters were estimated. The PD model consists of the balance between a parasite net growth rate and a drug killing rate.
Two sets of predicted human PK parameters were considered. The first set included human hepatic clearance estimated from in vitro hepatocyte clearance and human renal clearance estimated from dog pharmacokinetic data using allometry. The second set included the total human clearance estimated using allometry and was considered as the worst-case scenario due to the higher total clearance estimated using this approach. Induction of drug-resistant parasites. Dd2-B2 and NF54-HGL parasites were exposed to suboptimal concentrations of MMV693183 to induce and select for drug-resistant parasites. Dd2-B2 parasites were set up at different parasite densities ranging from 10 7 -10 9 and exposed to 3. 5-9 × IC 50 (Dd2-B2 mean IC 50 = 3. 0 nM) in at least three independent experiments. Drug media was changed daily until cultures were cleared and every other day subsequently.
5 µm particle diameter. Chromatography was performed using a 25-min gradient of 3% methanol with 10 mM tributylamine and 15 mM acetic acid (solvent A) and 100% methanol (solvent B). For each analytical run, a pooled sample was generated by combining equivalent volumes of each parasite sample to assess metabolite detection and run at the beginning, middle, and end of each analytical batch to detect any possible time-dependent sensitivity changes. The full metabolomics datasets are publicly available on the Metabolomics Workbench database under ST001985  76. Whole genome sequencing. The Dd2-B2 parent and resistant clones were subjected to whole-genome sequencing at the Columbia University Irving Medical Center using the Illumina Nextera DNA Flex library preparation protocol and NextSeq 550 sequencing platform.
Briefly, 150 ng of genomic DNA was fragmented and tagmented using bead-linked transposomes and subsequently amplified by 5 cycles of PCR to add dual index adapter sequences to the DNA fragments. The libraries were quantified, pooled and sequenced on the Illumina NextSeq high output flow cell to obtain 150 bp paired-end reads. The sequence data generated were aligned to the P. falciparum 3D7 genome (PlasmoDB version 36. 0) using BWA (Burrow-Wheeler Alignment). PCR duplicates and reads that did not map to the reference genome were removed using Samtools and Picard. The reads were realigned around indels using Genome Analyses Tool Kit (GATK) RealignerTargetCreator and base quality scores were recalibrated using GATK Table-Recalibration. GATK HaplotypeCaller (Min Base quality score ≥ 20) was used to identify all possible variants in clones.
Variants were filtered based on quality scores (variant quality as a function of depth QD > 1. 5, mapping quality > 30) and read depth (≥ 5) to obtain high-quality SNPs that were annotated using snpEFF. The list of variants from the resistant clones were compared against the Dd2-B2 parent to obtain homozygous SNPs present exclusively in the resistant clones. Copy number variations were detected using the BicSeq package by comparing the read counts of the resistant clones against the Dd2-B2 parent. Integrative Genomics Viewer was used to verify the SNPs and copy number segments in the resistant clones. Genomic DNA from the parental NF54 line and MMV693183-induced resistant lines were sequenced at the Pennsylvania State University according the Illumina® Truseq Sequencing protocol. Following sequencing, the data were processed using the Tadpole Galaxy scientific data analysis platform  77.
Briefly, the Trimmomatic tool was used to trim adapter sequences and genomes were mapped using the Map with BWA-MEM tool against a P. falciparum 3D7 reference genome. The Filter Sam or Bam, output Sam or Bam tool was used to consolidate the reads and generate the BAM file for the remaining analyses. The Depth of Coverage on Bam File tool was used to assess the depth of coverage of the dataset. Finally, the Freebayes -Bayesian genetic variant detector tool was used to assess the data for SNPs, inserts, and deletions. Generation of antigen for AcAS antibody production. Recombinant protein fragment used for immunization was obtained by cloning the first 414 nucleotides of a codon-optimized coding sequence of AcAS in frame with an N-terminal Glutathione S-transferase (GST)tag, into the expression vector pGex-4T.
Proteins were transferred to a nitrocellulose membrane that was blocked with 5% skim milk (Sigma) in PBS overnight and incubated with rabbit antiserum against AcAS (1:1000) for 1 h. Subsequently, membranes were washed three times with PBS-Tween for 5 min, followed by incubation with secondary horseradish peroxide (HRP)-conjugated goat anti-rabbit antibodies (Dako P0448, 1:1000) for 1 h. Blots were then washed three times with PBS-Tween for 5 min and twice with PBS. Following a 5-min incubation with Clarity Max Western ECL Substrate (BioRad), protein blots were imaged using the ImageQuant LAS4000 (GE Healthcare). The band intensity was quantified using Fiji software. Immunofluorescence microscopy. Asynchronous asexual blood-stage AcAS-GFP or wild-type NF54 parasites were allowed to settle on poly-L-lysine coated coverslips for 20 min at room temperature.
Images were Airyscan processed before analysis with Fiji software. Since no quantitative comparisons were performed, brightness and contrast were slightly altered in Fiji to improve visualization of AlexaFluor488 and DAPI signals. Statistics and Reproducibility. Dose-response assays were analyzed by a nonlinear regression using a four-parameter model and the least squares method to find the best fit. One-way Analysis of variance (ANOVA) was performed using the Bonferroni's Multiple Comparison Test. For the majority of experiments, 2-4 biological replicates were performed. Typically, 2 replicates were performed for screening activities, and a minimum of 3 replicates are performed for other experiments unless stated otherwise.
Acknowledgements We gratefully acknowledge  S. Mok  for assistance with whole-genome sequencing analysis,  C. Bioni  for providing access to the laboratory for the Brazilian-field isolates ex vivo assessments,  O. Byaruhanga ,  S. Orena ,  M. Okitwi  and  T. Katairo  for assistance with ex vivo assays on fresh P. falciparum isolates in Uganda,  S. Sax  for technical assistance with the SCID mouse P. falciparum in vivo efficacy studies performed at Swiss TPH. We thank  D. F. Wirth ,  A. K. Lukens  and  R. Summers  for pre-publication sharing of data and fruitful discussions. T. Spielmann  is acknowledged for providing the plasmid  SLI-TGD. We also thank the  Huck Institutes of Life Sciences Metabolomics Core Facility at Penn State University. LEdV was supported by a PhD fellowship from the  Radboud Institute for Molecular Life Sciences, Radboudumc  ( RIMLS015-010 ), JMJV by an individual Radboudumc Master-PhD grant, TWAK by the  Netherlands Organisation for Scientific Research  ( NWO-VIDI 864.
, 2020b). Differentially expressed genes (DEGs) were selected when FC threshold > 2. 0 or < 0. 5 and presented in log2 FC. For the functional annotation of DEGs and relevant biological pathways of selected genes NCBI GenBank, UniProt, AmiGO 2 Gene Ontology and KEGG pathway analysis were used. The microarray data from this study have been submitted to the NCBI GEO with the accession number GSE180397.
Acknowledgement We would like to thank  Loïc Brunet  and  Anne-Sophie Lacoste  of the  BICeL-University of Lille  for their technical assistance. The TEM observations were performed on device of the BICeL-Campus CS core facility acquired through a funding from the  Agence Nationale de la Recherche ,  ANR  ( 10EQPX-04-01 ). The authors are grateful to  Rezak Mendil  for assistance in cell cytotoxicity and cell adhesion assays. The authors would like to thank  Dr. Steve W. Elson  for reading and improving the English of the manuscript.
, 2014). The final real space images were obtained by averaging 20 reconstructions. We used 7. 0 and 8. 1 keV X-rays and different sample-todetector distances, so the real space images have a voxel size of 32. 5 Â 32. 5 Â 32. 5 nm for 8 mM 1 g l À1 1 min, 8 mM 1 g l À1 30 min and 30 mM 0. 27 g l À1 72 h; 17. 7 Â 17. 7 Â 17. 7 nm for 30 mM 1 g l À1 min, 30 mM 1 g l À1 30 min, 30 mM 1 g l À1 8 h, 30 mM 1 g l À1 24 h and 30 mM 1 g l À1 72 h; 16. 4 Â 16. 4 Â 16. 4 nm for 8 mM 1 g l À1 8 h, 8 mM 1 g l À1 24 h and 8 mM 1 g l À1 72 h; 13. 8 Â 13. 8 Â 13. 8 nm for 8 mM 1. 94 g l À1 24 h; and 12. 6 Â 12. 6 Â 12. 6 nm for 8 mM 0. 27 g l À1 24 h. The reconstructed real space images are subject to smooth, lowfrequency density variations due to missing data behind the beamstop, strongly resembling the 'unconstrained modes' reported by  Thibault et al.
Acknowledgements We gratefully acknowledge the  European Synchrotron Radiation Facility (Grenoble, France)  for the provision of synchrotron beam time at the ID10 beamline (proposal Nos. CH4568  and  CH4936 ) and the ID16A beamline (proposal No. CH4916 ). The authors thank  Jerome Kieffer  and  Pierre Paleo  for accelerating the reconstruction code. Author contributions: OC and TB synthesized the samples. YC, FZ, AG, OC, JDS and TB managed the CXDI and XRF measurements at the synchrotron. IS and TB obtained the SEM images. TB performed the pH measurements, infrared spectroscopy and optical observations. TB wrote the paper with feedback from all authors. The authors declare no competing interests.
| Follow-up and identification of cancer cases Incident skin cancer cases were identified through a combination of several methods, including record linkage with population-based cancer registries, health insurance records, pathology registries, and active follow-up of study subjects. During follow-up, mortality data or vital status was obtained from cancer or mortality registries at the regional or national level. Skin cancer events were mostly ascertained through population-based cancer registries or pathology reports (96% of cases; melanoma: 92%; BCC: 96%; SCC: 99%), and a small proportion (4%) was identified from hospital admission and discharge records or national/regional mortality registries. Although melanomas are more accurately recorded in cancer registries, registration of KCs, especially BCCs, was often incomplete in some centers because these cancers are not systematically recorded in cancer registries.
Follow-up began on the date of recruitment and ended on the date of skin cancer diagnosis, death, emigration/loss of follow-up, or completion of the last returned questionnaire, whichever came first. Cancer incidence data were coded according to the International Classification of Diseases for Oncology (ICD-O-3). Cancer cases were defined as subjects with a first primary incident skin cancer (including KC; C44). Information on stage, site, morphology, and grade of melanoma was collected from each center, where possible. In this current study, skin cancer cases combine melanoma, BCC, SCC, and unknown skin cancer type.
| Study sample From the cohort of 521 448 women and men, we first excluded subjects with prevalent cancer cases (including KCs) or those with missing data on date of diagnosis and follow-up information (n = 29 456), and those with missing information on lifestyle factors (n = 6259) or extreme energy intake values (<first and > 99th percentiles of the distribution) (n = 9573). We further excluded subjects from the Greece cohort (n = 26 048) due to data restriction issues, leaving a final sample of 450 112 participants for analysis of baseline alcohol intake. Analysis of lifetime alcohol intake was based on 363 310 EPIC participants after exclusion of 112 850 participants-from Norway, Sweden, Naples, and Bilthoven-for whom data on lifetime alcohol was missing.
In addition, we conducted separate analyses by country, using alcohol as a continuous variable (12 g/day increments in intake). We further assessed associations by tumor anatomical site (head, neck and extremities, and trunk)  25, 26  and, for melanoma, histologic subtype (superficial spreading, lentigo maligna, nodular, acro-lentiginous, and other), using competing-risk analysis, excluding cases with missing information on tumor characteristics for these analyses. Homogeneity tests were performed using Wald chi-square tests to compare estimates by tumor sites and types. All statistical analyses were performed using the SAS software (version 9. 4, SAS Institute), and all significance tests were two-sided, with P-values less than 5% considered statistically significant.