dataesr/scientific-paragraphs-categorization huggingface dataset:
The upper limits at 95% CL on the branching fraction B(t → H + b) are calculated using the statistical tools in ROOSTAT  [85]  and the CL s criterion  [86, 87]  with a profile likelihood ratio as a test statistic  [88]  and using an asymptotic formulae  [89]. The expected branching fraction limit is calculated using an Asimov dataset with a null hypothesis. Systematic uncertainties are treated as nuisance parameters and profiled in the fit following a log-normal distribution for the normalization uncertainties and using distorted templates for shape systematic uncertainties. With the assumptions of B(H + → cb) = 1. 0 and B(t → H + b) + B(t → Wb) = 1. 0, the expected and observed limits as a function of M H + are shown in Fig. 3. The expected limits without systematic uncertainties are also shown to illustrate that the analysis sensitivity is largely limited by the present level of our knowledge of the systematic uncertainties.
Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Tech-nologie (IWT-Belgium); the F. R. S. -FNRS and FWO (Belgium) under the "Excellence of Science-EOS" -be. h project n. 30820817; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lend ület ("Momentum") Programme and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the NKFIA research grants 123842, 123959, 124845, 124850 and 125105 (Hungary); the Council of Scientific and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus programme of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa de Excelencia María de Maeztu and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).
In summary, we have shown through in vitro cell based mutagenesis screening and molecular analysis of patient samples that treatment with sequential first-, second-, and third-generation ALK inhibitors fosters the development of diverse compound ALK mutations, some of which are highly refractory to all available ALK inhibitors. It is tempting to speculate that upfront treatment with the third-generation inhibitor lorlatinib may be able to prevent the emergence of single and subsequently compound ALK mutations, potentially improving clinical outcomes. This hypothesis will be formally addressed in an ongoing randomized phase 3 trial comparing lorlatinib with crizotinib as first-line therapy in advanced ALK-positive lung cancer (NCT03052608). However, our data also suggest that highly potent target inhibition with lorlatinib could ultimately select for ALK independent resistance mechanisms which may be difficult to overcome once established.
Acknowledgments Funding Sources: This work was supported by grants from the  National Cancer Institute  ( R01CA164273 , to ATS), by a  National Foundation for Cancer Research  (to ATS), by  AACR-AstraZeneca Fellowship in Lung Cancer Research  ( 17-40-12-DARD , to LD), by Be a Piece of the Solution, by the  Evan Spirito Foundation , and by the  Targeting a Cure for Lung Cancer Research Fund at MGH.
The purities of final D 3 compounds, as analyzed by an Agilent 1100 HPLC system (Santa Clara, CA, USA), were above 98%. Highresolution MS spectra were obtained from a Waters UPLC-Q/Tof-MS system with the function of molecular formula prediction (Milford, MA, USA). NMR data were collected at 25 °C. Chemical shifts were referenced to residual solvent peaks of methanol-d 4 or CDCl 3. NMR measurements were performed on either a Bruker Avance III 400 MHz (Bruker BioSpin, Billerica, MA, USA), or a Varian Unity Inova 500 MHz spectrometer (Agilent Technologies Inc. , Santa Clara, CA, USA). Metabolism of analogs by CYP24A1 and CYP27B1. Rat CYP24A1, mouse CYP27B1 and adrenodoxin and human adrenodoxin reductase were expressed in E. coli and purified as described before  28, 30, 35. To test metabolism of each analog, they were incorporated into phospholipid vesicles made from dioleoyl phosphatidylcholine and cardiolipin by sonication, as before  24, 28.
Real time PCR-based gene expression analysis. HaCaT cells were purchased from Thermo Fisher Scientific (Waltham, MA, USA) and were cultured as for the VDRE reporter assay. The RNA from HaCaT keratinocytes treated with secosteroids or from DMSO controls was isolated using the Absolutely RNA Miniprep Kit (Stratagene, La Jolla, CA, USA). Reverse transcription (100 ng RNA/reaction) was performed with the Transcriptor First Strand cDNA Synthesis Kit (Roche Inc. , Mannheim, Germany). Real-time PCR was performed using cDNA diluted 10-fold in sterile water and a SYBR Green PCR Master Mix. The primers for both forward and reverse strands for CYP24A1 were designed based on the mouse and rat sequences using Primer Quest software (Integrated Device Technology, San Jose, CA, USA). Reactions (in triplicate) were performed at 50 °C for 2 min, 95 °C for 10 min and then 40 cycles of 95 °C for 15 s, 60 °C for 30 s and 72 °C for 30 s.
Crystals were obtained in 50 mM Bis-Tris pH 6. 5, 1. 6 M lithium sulfate and 50 mM magnesium sulfate. Protein crystals were mounted in a fiber loop and flash-cooled under a nitrogen flux after cryo-protection with 20% glycerol. Data collection from a single frozen crystal was performed at 100 K on the ID30 beamline at ESRF (France). The raw data were processed and scaled with the HKL2000 program suite  37. The crystals belong to the space group P6522, with one LBD complex per asymmetric unit. The structure was solved and refined using BUSTER  38  , Phenix  39  and iterative model building using COOT  40. Crystallographic refinement statistics are presented in Table  S1. All structural figures were prepared using PyMOL (www. pymol. org/). Accession codes. PDB ID codes 5OW9, 5OWD, 5OW7, 5MX7 and 2HC4 for co-crystals of 20S(OH)D 3 , 4, 33 1,20S(OH) 2 D 3 and 1,25(OH) 2 D 3 in complex with VDR ligand binding domain.
Acknowledgements This work was supported by grants  1R21AR063242  (W. L. , D. D. M. ),  1S10OD010678  (W. L. ),  1S10RR026377  (W. L. ),  R21AR066505  (A. S. ), and  1R01AR071189  (A. S. ) from  NIH , grant  ANR-13-BSV8-0024-01  (N. R. ) from  ANR  and institutional funds (N. R. ) from  Instruct-ERIC  for support and the use of resources of the  French Infrastructure for Integrated Structural Biology. The authors would like to thank  Dr. Dejian Ma  in  Department of Pharmaceutical Sciences at UTHSC , and the staff of the ID30 beamline at  ESRF  synchrotron for the experimental assistance. Z. L. would like to thank the  Alma and Hal Reagan Fellowship  from  College of Graduate Health Science of UTHSC , and a national award from  China Scholarship Council. The content is solely the responsibility of the authors and does not necessarily represent the official views of the  NIH.
• How much inter-year variability is there in wines from one vineyard or region? It is well known that these aspects may confound the practical issues of legal fingerprinting of wines, however, the most important monitor on composition appears to be the geographic origin of the grapes  [11, 12]. Three other points have occurred: (i) multi-element dataset is needed for fingerprinting; (ii) multivariate statistical techniques are required for data analysis; and (iii) Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) is one of the most promising analytical methods for trace and ultra-trace element fingerprinting of wines, which is characterized as fast, routine and accurate. The present study is focused on the determination of selected metals in wines originating from different Polish vineyards and two analytical techniques were applied to gain this aim: ICP-MS and ICP-OES.
Chemometric Assessment of Multiparametric Data Set Obtained during Analysis of Wine Samples The input dataset consisted of 44 wine (red and white) samples (objects of the study) from different regions of Poland (West Pomerania, Kyuavian Pomerania, Subcarpathia, Lesser Poland, and Masovia) and 30 metal concentrations (variables) or matrix with dimensions (44 × 30). The major goal of the chemometric assessment was to reveal specific relationships between the wine samples or between the chemical variables in order to classify the wines according to their metal content, showing in such a way which were the discriminating chemical indicators for each group of clustered wine types. The chemometric methods used were cluster analysis (hierarchical and non-hierarchical with K-means algorithm) and principal components analysis (PCA).
Conclusions This study presents the results of the determination of 30 metals in Polish wines samples originating from several vineyards located in different regions of Poland. Almost all analytes selected were determined in wine samples, excluding Ag, Co, Cu, Sn, and V. However, the type of element, as well as the quantity, depended on the sample analyzed. Data obtained showed that none of the wine samples surpassed the toxic levels of metals reported in the literature. Thus, these wines appeared to be safe as regards the risk associated with the potentially toxic metals intake. However, analyzing concentration levels of metals, it can be concluded that depending on the color of the wine, the content of the individual element was different, for example, for silver, higher concentration levels were recorded for white wine samples than for red ones.
Acknowledgments:  Justyna Płotka-Wasylka  would like to thank Faculty of  Chemistry, Gda ńsk University of Technology  for financial support within the  minigrant program  (Decision no. 4914/E-359/M/2017 ). The authors would like to thank  Zodiak Vineyard ,  PrzyTalerzyku Vineyard ,  Kozielec Vineyard ,  Pod Orzechem Vienyard ,  Stok Vineyard ,  Spotkaniówka Vineyard , and  Dwór Kombornia Vineyard  for the samples of wine.
INTRODUCTION Adeno-associated viruses (AAVs) were discovered in electron micrographs as contamination in adenovirus preparations, and soon became the subject of interest of scientists around the world. 1  Over 50 years later, the interest in AAV as a vector in gene therapy continues to grow. The AAV belongs to the parvovirus family, specifically the dependoparvovirus subfamily. The members of this subfamily require a helper virus, such as the adenovirus (Ad) or herpes simplex virus (HSV), to facilitate productive infection and replication. Although it is estimated that 90% of the human population is AAV seropositive, 2,3 these viruses do not cause any known disease in humans, being an important safety criterion for their use in gene therapy approaches. Clinical trials using recombinant AAV (rAAV) vectors have shown impressive results for Leber congenital amaurosis,  4  hemophilia B,  5  spinal muscular atrophy (ClinicalTrials.
gov: NCT02122952), and other diseases. The first commercial product based on rAAV was approved in 2012 by the European Medicine Agency for the treatment of lipoprotein lipase deficiency, and a second drug could be approved soon according to positive results of a phase III trial. 4 onetheless, a major bottleneck to commercialize these products is the manufacturing of rAAV in accordance with current good manufacturing practices (cGMPs) on a large scale. Production of rAAV in human cells (HEK293) transiently transfected with plasmids is probably the most common approach,  6  but the use of insect cells and baculoviruses is highly convenient for industrial manufacturing. 7 ther viable approaches consist of using a recombinant HSV complementation system in suspension-cultured mammalian cells (BHK21 or HEK293)  8, 9  or mammalian-derived producer cell lines containing the rep and cap genes and the AAV vector integrated into the genome.
It also showed the complete absence of VP1 in AAV8DVP1-GFP preparation, which was further confirmed by western blot analysis with anti-VP1/2/3 antibody B1 (Figure  1B , lane 4). 22  an additional quality control, particle size was measured in AAV8-GFP control and AAV8DVP1-GFP vector preparations by dynamic light scattering (DLS) (Figure  S2 ). The results showed that both vector preparations had a very similar particle size distribution (24. 57 ± 7. 02 and 24. 33 ± 7. 38 nm, respectively), and they were quite homogeneous with no detectable particle aggregates (Table  S2 ). AAV8-GFP control and AAV8DVP1-GFP vectors were also analyzed by differential scanning fluorimetry (DSF), and they were shown to have similar thermal stability with a melting temperature (Tm) of $70. 5 C. 23  These data indicated that the absence of VP1 had no major impact on AAV8 particle size and capsid stability in Dubelcco's phosphate buffer saline (DPBS).
Analysis of AAV8 Vector Intracellular Trafficking To further characterize the AAV8DVP1 vector, we analyzed AAV8 particle intracellular trafficking in HeLa cells infected with AAV8DVP1-GFP or AAV8-GFP control vector. To this end, HeLa cells were infected at an MOI of 20,000 VG/cell during 1, 5, or 16 hr, intracellular AAV8 particles were labeled with ADK8 antibody that specifically recognizes assembled AAV8 capsids  24  and Alexa Fluor 555 secondary antibody, and nuclei were stained with DraQ5 fluorescent dye. Confocal microscopy images (Figure  2A ) were then analyzed, using the compartmentalization task of Volocity software, for counting viral capsids according to their localization. Intranuclear particles were counted using the "inside" class (full colocalization with DraQ5 staining), perinuclear particles were calculated as the difference between "overlapping" (full or partial colocalization with DraQ5) and "inside" classes, and cytoplasmic particles were the difference between "nearest by edge" (no colocalization with DraQ5) and "overlapping" classes.
Reducing the incubation time in the TCID 50 assay also resulted in about 10-fold lower infectious titers for both AAV8 and AAV2 vectors, thus mitigating the DNA samples from infected HeLa cells were prepared from whole cells (procedure 1) or subcellular fractions (procedures 2, 3, and 4), and vector genomes were quantified in each sample by qPCR targeting the SV40 poly(A) sequence. Results were normalized to an input of 1,000 vector genomes per cell at the time of infection, in order to compile data obtained with the different MOIs (2,000 and 10,000 VG/cell). Bars represent the amount of vector genomes per sample ± SD. discrepancy between the TCID 50 and ICA methods. However, the infection-defective AAV8DVP1 vector was still found to be 1,000-fold more infectious with the modified TCID 50 compared to the ICA.
Slides were finally mounted with Prolong Gold antifade reagent (Life Technologies). Images were captured on a Nikon A1 confocal microscope (Nikon Instruments, Amsterdam, Netherlands), and quantification of AAV8 particles according to their localization was then performed using the compartmentalization task of Volocity software (PerkinElmer, Courtaboeuf, France). Images were processed with ImageJ software (https://imagej. nih. gov/ij/) for picture presentation.
ACKNOWLEDGMENTS We thank all the staff of the  Vector Core at the University Hospital of Nantes  (http://umr1089. univ-nantes. fr/facilities-cores/cpv/vector-core-2203910. kjsp? RH=1519296954157 ) for the production of the AAV reference vectors and for technical assistance. We are grateful to  Nicolas Jaulin  for performing the flow cytometry analysis, to  Philippe Hulin  and  Steven Nedellec  for their assistance in confocal imaging and analysis, and to  Stéphanie Bucher  and  Sandy Douthe  for their contribution to the intracellular AAV genome qPCR assay design. Flow cytometry and confocal microscopy analyses were conducted at the  Cytocell and MicroPICell core facilities of Nantes University , respectively. This research was supported by the  Fondation d'Entreprise Thérapie Génique en Pays de Loire , the  Commissariat Général à l'Investissement (ANR Program, Investissements d'Avenir, Preindustrial Gene Therapy vector consortium) , the  Association Française contre les Myopathies (AFM) , the  Agence Nationale de Sécurité des Médicaments (ANSM) , the  Centre Hospitalier Universitaire (CHU) of Nantes , and the  INSERM.
Future studies in larger cohorts of nonhuman primates will be required for the clinical translation of the results shown here. We have previously demonstrated the functional benefit of using SVP [Rapa] to mitigate the formation of anti-drug antibodies (ADAs) against a variety of biologic drugs, including coagulation factor VIII in a model of hemophilia A  23  , anti-TNF monoclonal antibody in a model of spontaneous arthritis  18  , acid alphaglucosidase in Pompe disease mice  20  , immunotoxins in a model of mesothelioma  21  , and pegylated uricase in uricase-deficient mice and in nonhuman primates  18. Additionally, the safety and ability of SVP [Rapa] to inhibit the formation of ADAs against pegisticase, a highly immunogenic enzyme therapy, in a dose-dependent manner was demonstrated in a phase 1 clinical trial (Clinicaltrials.
gov NCT02648269)  22. SVP[Rapa] is currently being evaluated in combination with pegsiticase in an ongoing multi-dose phase 2 clinical trial (Clinicaltrials. gov NCT02959918)  22. One open question about the work presented here is whether SVP[Rapa] administration will impair the ability of the immune system to fight infections. Because of the need for SVP[Rapa] to be co-administered with the antigen, in order to guarantee uptake from the same subset of antigen presenting cells  18, 21  , it is less likely that SVP[Rapa] will lead to global immunosuppression, although future studies are needed to carefully address this point. The lack of immune cell depletion observed in animals treated with AAV vectors and SVP[Rapa], both rodents and nonhuman primates, provides additional data supporting the safety of the approach.
Initial clinical data in small numbers of patients treated with SVP[Rapa] are consistent with these results, as they do not show any increased risk of infection (Clinicaltrials. gov NCT02648269; NCT02959918)  22. Although AAV is considered to be a non-pathogenic virus and is not associated with any disease, it is unknown if there would be any consequences of inducing immune tolerance to AAV. Further evaluation of safety will have to be addressed in preclinical studies and clinical trials. Finally, another question about the technology is whether it could be used to eradicate established antibody responses to AAV. SVP [Rapa] has been shown to reduce antibody titers against protein antigens in primed animals  21, 23. However, since very low titers of neutralizing antibodies can inhibit AAV transduction, it is unclear if a reduction in anti-AAV titer would be sufficient to enable productive transgene expression, particularly in the presence of long-lived plasma cells.
Analysis of images was performed using the Cellprofiler software; staining signal was isolated from background signal (intensity 1 to 19 random units). A minimum of four fields per animal were acquired and analyzed to generate the data on distribution of signal intensity. The signal intensity was then divided by the surface in mm 2 to obtain number of positive hepatocytes per mm 2. Flow cytometry analysis. Single-cell suspensions from spleen and lymph nodes were prepared and stained for the surface markers with different fluorochrome combinations: anti-CD3 (APC-eFluor780, clone 17A2, dilution 1:300, BD Biosciences, San Jose, CA), anti-CD4 (PB, clone RM4-5, dilution 1:200, BD Biosciences), anti-CD25 (PE, clone PC61, dilution 1:300 BD Biosciences), anti-CD45R (FITC, clone RA3. 6B2, dilution 1:300, Thermo Fisher Scientific Waltham, MA), anti-CD19 (PE, clone 1D3, dilution 1:300 BD Biosciences), anti-IgD (APC-eFluor780, clone 11-26 c.
All antibodies were used at one test per 10 6 cells. Samples were acquired using Sony Spectral cell analyzer SP6800 (Sony Biotechnology Inc. , San Jose, CA). Data analysis was performed using the SP6800 software (Sony Biotechnology Inc. San Jose, CA) and FlowJo software (Tree Star, Ashland, OR). Anti-AAV T and B cell ELISpot assays. Spleens were isolated, single-cell suspensions were then prepared and 2 × 10 5 cells were stimulated for 24 h with an AAV8 peptide pool  6  (1 μg ml -1 of each peptide, Mimotopes, Victoria, Australia) in 100 μl of complete medium (RPMI supplemented with 10% FBS, Pen/Strep and L- Glutamine) (Thermo Fischer Scientific, Waltham, MA). Medium only was used as negative control and ConA (Concanavalin A Lectin Type IV, dilution 1:1000, Sigma-Aldrich, St. Louis, MO) was used as positive control.
After three washes, streptavidin-ALP (Mabtech, Nacka Strand, Sweden) was added for 1 h at RT, followed by the addition of the substrate for spot development (Mabtech). All antigens and controls were tested in triplicate. The plates were read on AID ELISpot reader system using the ELISpot 6. 0 iSpot software (Autoimmun Diagnostika, Strassberg, Germany). RNA extraction and RT-PCR. Total RNA were isolated from livers using the Magna Pure 96 cellular RNA large volume kit (Roche Diagnostics, Indianapolis IN) according to the manufacturer's instructions. RNA samples were then pretreated with DNAse (Thermo Fischer Scientific, Waltham, MA) and reverse transcribed using RevertAid H minus first strand cDNA synthesis kit (Thermo Fischer Scientific). RT-qPCR was performed using SybrGreen (Thermo Fisher Scientific) with primers specific for CD8 (Supplementary Table  4 ).
Gene expression was calculated using the ΔΔC t method relative to GAPDH housekeeping gene (Supplementary Table  4 ) and by normalizing to the mean expression of untreated mice. Statistical analysis. Statistical analysis was performed using GraphPad Prism (GraphPad Software Inc, La Jolla, CA) version 6. 0. Analysis of statistical significance between two groups was assessed using the two-tailed unpaired t-test. For multiple group comparisons, one-way or two-way ANOVA with Tukey multiple comparison test was used.
Acknowledgements This work was supported by  Genethon  and  Selecta Bioscience , by the  European Union ,  FP7-PEOPLE-2012-CIG Career Integration Grant , Grant Agreement No. 333628  (Nos-Mod to F. M. ), ERC-2013- CoG Consolidator Grant , Grant Agreement No. 617432  (MoMAAV to F. M. ),  European Union's research and innovation program  under Grant Agreements No. 667751  (Myocure, to F. M. ),  E-Rare2  grant  SMART-HaemoCare  (to F. M. ), and the  Bayer   Early Career Investigator Award  (to F. M. ). A. Meliani was supported by a grant of the  DIM-Biotherapies Ile-de-France.
After surgery, all animals recovered for a period of 2 weeks before starting temperature recordings. A receiver board (RPC-1; Data Sciences International, Saint Paul, MN, United States) was positioned under each individual cage to collect the radio frequency signals from transmitters. T b was recorded for 10 s every 5 min. Data were analyzed using the Dataquest software (LabPro Data Sciences). Several parameters were derived from the temperature recordings. We determined the onset of hibernation as the time between the food removal and entrance into the first torpor bout with a T b threshold of 25 • C and lasting at least for 24 h. We also computed the number of arousals, mean and total arousal and torpor durations (with a T b threshold of 25 • C), and minimal T b during torpor.