dataesr/scientific-paragraphs-categorization huggingface dataset:
Synaptosomal membrane (P2) and PSD fractions were size fractionated in 7. 5% Tris Glycine (Bio-Rad) gels and examined by Western blotting with the antibodies for Homer1 (anti-mouse, Santa Cruz Biotechnology Inc. , sc-136358), mGlur5 (anti-goat, Santa Cruz Biotechnology Inc. , sc-47147), PSD-95 (anti-mouse, Neuro Mab, 75-028), and β-actin (anti-mouse, MilliporeSigma, A2228). The quantified band intensities were analyzed and plotted using the Graph Pad Prism software; all data were expressed as mean ± SEM. Students' t test, unpaired and 2-tailed, was used for between-group comparisons.
Field excitatory postsynaptic potentials (fEPSPs) were recorded using an aCSF-filled glass microelectrode (A-M Systems) with a resistance between 1 and 5 MΩ placed in the stratum radiatum region of CA1. Data collection was handled by Clampex software (Molecular Devices) and was analyzed using Clampfit software (Molecular Devices). The peak fEPSP amplitude induced by the stimulating electrode was required to be at least 5 mV, and stimulus intensity during the recording was set to produce a response of 40% of the maximum fEPSP amplitude. Test stimulation occurred once every minute. Baseline responses were recorded for 20 minutes before LTP induction or drug application. To examine early-phase LTP (E-LTP), one 1-second, 100 Hz train of stimuli was applied through the stimulating electrode. To examine L-LTP, four 1-second, 100 Hz trains of stimuli were delivered 5 minutes apart.
3 Na-GTP. Electrode resistance in the bath was 4-9 MΩ, and series resistance was 15-25 MΩ; bridge balance and capacitance compensation were used to minimize the resultant errors. Recordings were made using a Dagan BVC-700 amplifier (Dagan Corporation). Data were low-pass filtered at 3 or 5 kHz and were digitized at 50 kHz via an ITC18 digital-analog converter (HEKA Instruments Inc. ) under control of IGOR Pro (Wavemetrics) using the DataPro software package from the lab of Nelson Spruston (www. janelia. org/lab/ spruston-lab/resources/software). Patched cells were maintained at a potential of -65 mV, with a holding current when needed no larger than ± 100 pA. A 100-Hz burst of 5 somatic spikes was induced by current injection (+2000 pA, 2 ns, × 5), with an ISI of 20 seconds. Baseline responses were recorded for 3 minutes before beginning drug or vehicle perfusion.
Recordings lasted for 30 minutes after the baseline recording period. Drug perfusion lasted for 15 minutes before washout. Electrophysiological data was analyzed using custom scripts written for use with IGOR Pro software and the DataPro package. Statistical analyses were performed using STATISTICA 11 software and Prism 6 software (GraphPad). Data from multiple cells was pooled and tested for statistically significant differences using unpaired 2-tailed Student's t tests, a 1-way repeated-measures ANOVA with Tukey's post hoc comparisons, or 2-way ANOVA with Holm-Sidak's multiple comparisons test. For all tests, significance was defined as P < 0. 05. Drugs. All drugs used in the electrophysiology experiments were mixed as stock solutions and stored as individual aliquots at -20°C, except for DHPG, which was made fresh for each experiment.
For evaluation of input-output characteristics, a 2-tailed independent samples t test was performed, comparing the average linear regression slopes for control mice and Sin3aNH mice. Potential differences in the maximum fEPSP slope were evaluated using a 2-tailed independent samples t test. Between-group differences in LTP maintenance were determined using a repeated measures ANOVA on the final 20 minutes of the recordings, followed by Tukey's post hoc test when appropriate  (6). Normality and variance of LTP data were checked to determine suitability for analysis by ANOVA. Normality of the data was evaluated by Shapiro-Wilk tests and examination of normal probability plots of the residuals. Variance was evaluated by examination of residual plots of observed versus fitted values. All statistical analyses were performed using STATISTICA software (StatSoft Inc.
insight. jci. orghttps://doi. org/10. 1172/jci. insight. 92385insight. jci. orghttps://doi. org/10. 1172/jci. insight. 92385Acknowledgments MB was supported by a predoctoral  NRSA  fellowship from the  NINDS  ( 1F31NS079019 ). HS was supported by  NIH  training grant  T32-MH017168. The work was supported by  NIH  grant  R01-MH087463  to TA, as well as the  Brush Family Professorship (Penn)  and the  Roy J. Carver Chair in Neuroscience (Iowa). Additional thanks to the entire Spruston lab and the  HHMI Janelia Research Campus  for providing animal care, training, material, and other resources to MB. Funding to NS was provided by the  HHMI. Address correspondence to:  Ted Abel ,  Iowa Neuroscience Institute, Departments of Molecular Physiology and Biophysics, Psychiatry, and Biochemistry, Carver College of Medicine, University of Iowa, 2312 Pappajohn Biomedical Discovery Building, 169 Newton Road, Iowa City , Iowa 52242-1903, USA.
Data taking, analyses, and interpretation of these possible signals are still ongoing within the AMS-02 collaboration. For the purpose of this review, it needs to be highlighted that the antihelium detection has not yet been confirmed. Therefore, any discussion of cosmic-ray antihelium fluxes in this review should be seen as theoretical case study. Although these results are not yet published, they have prompted significant theoretical work on the implications for dark matter models and predicted antideuteron and antiproton fluxes. Antihelium arriving from antimatter-dominated regions of the universe is already nearly excluded  [46, 47]. Proposed models span a range includ- The BESS-Polar II experiment consists of inner drift chambers and a jet-type drift tracking chamber, surrounded by a solenoid magnet, aerogel Cherenkov counter, and time-of-flight system.
By 2024, more than 1,000,000 antiprotons will be collected in the range up to 525 GV. As discussed further in Sec. 3. 2, AMS-02 has announced several candidate events with mass and charge consistent with antihelium  [43, 44]. The analyses of heavy antinuclei, including antideuterons, are ongoing while more data are collected. At an estimated signal to background ratio of one in one billion, a detailed understanding of the instrument is required for these rare antinuclei searches. An equivalent of 100 billion of proton, deuteron and antiproton events in the rigidity range 0. 5-100 GV must be simulated.
Antiproton Production Cross Section The cross section for antiprotons to be produced by cosmic-ray interactions with the interstellar medium is key to interpreting cosmic antinuclei measurements. For example, AMS-02 data revealed that the cosmic-ray antiproton flux at energies above approximately 100 GeV is harder than was anticipated. Although this prompted a number of different interpretations, including antiprotons produced by heavy DM  [21, 23] , it was found that the antiproton production cross section in p-p collisions at higher energies was underestimated. A new parameterization  [24] , especially at energies above √ s > 100 GeV, considering PHENIX  [109] , STAR  [110, 111] , CMS  [112] [113] [114] [115] , and ALICE  [116, 117]  data (Fig. 9 ), together with a new parameterization of the boron-to-carbon ratio (see Sec.
The detector consists of different subdetectors for the particle identification. NA61/SHINE already recorded p-p interactions with beam momenta from 13 to 400 GeV/c, and also collected data for other hadron interactions, including p-C, π + -C, Ar-Sc, p-Pb, Be-Be, Xe-La, Pb-Pb at different energies. NA49 and NA61/SHINE have published several relevant data  [118, 187]  that are used for tuning cosmicray formation and propagation models (Secs. 4. 1 and 4. 3). The analysis of large p-p data sets at 158 GeV/c and 400 GeV/c are of particular interest. The measurement of light nuclei in various A-A data sets can be used to study the production of light ions at the threshold. These measurements will complement the NA49  [123, 188]  and ALICE results and allow to test the coalescence and thermal models in a different regime.
Acknowledgments This work is supported in the U. S. by  NASA   APRA grants  ( NNX17AB44G ,  NNX17AB45G ,  NNX17AB46G , and  NNX17AB47G ). R. A. Ong  received support from the  UCLA Division of Physical Sciences. P. von Doetinchem received support from the  National Science Foundation  under award  PHY-1551980. H. Fuke is supported by  JSPS   KAKENHI grants  ( JP17H01136  and  JP19H05198 ) and  Mitsubishi Foundation  research grant  2019-10038. N. Fornengo ,  F. Donato , and  M. Korsmeier  are supported by the  "Departments of Excellence "  2018-2022  grant awarded by the  Italian Ministry of Education, University and Research (MIUR)   L. 232/2016 , research grant  TAsP (Theoretical Astroparticle Physics)  funded by  INFN , research grant ' The Dark Universe: A Synergic Multimessenger Approach ' No.
2017X7X85K  funded by  MIUR. N. Fornengo  is further supported by the research grant " The Anisotropic Dark Universe " No. CSTO161409 , funded by  Compagnia di Sanpaolo and University of Turin. M. Kachelriess ' and  J. Tjemsland 's work was partially supported by the  Research Council of Norway (NFR). I. V. Moskalenko acknowledges a partial support from  NASA APRA  grant  NNX17AB48G. M. Naskret 's work was supported by the  Polish National Science Centre  grant  2017/27/N/ST2/01009. F. Rogers  is supported through the  National Science Foundation Graduate Research Fellowship  under Grant No. 1122374. M. W. Winkler  acknowledges support by the  Vetenskapsradet (Swedish Research Council)  through contract No. 638-2013-8993.
In published observational studies on 186 Dutch  [12]  and 135 British  [13]  children treated with statins, a positive influence on lipid profiles was also found, and no significant adverse effects were revealed. The safety of statin use in children has been assessed most often only in the context in which adverse effects in adults were previously described. It is known that the use of pharmacotherapy to reduce risk factors rather than for treatment of existing disease must be undertaken only when there is a low risk of harm. Therefore, despite important data on the ability of statins to lower the concentration of total cholesterol and LDL, the effectiveness of this type of treatment in the prevention of atherosclerosis and the safety of its long-term use with respect to the development and maturation of various systems and organs remain open questions in the pediatric population  [11].
Determination of Plasma Lipophilic Antioxidants Determination of plasma vitamin A (all-trans-retinol), vitamin E (L-tocopherol) and CoQ10 was performed using a highperformance liquid chromatograph (HPLC) coupled with a mass spectrometry (MS) detector equipped with a triple quadrupole (Shimadzu LCMS-8040). The ionization was conducted using the APCI [atmospheric pressure chemical ionization] mode, and data were processed using Shimadzu LabSolutions LCMS software. Compounds were separated using an analytical column from Phenomenex (Kinetex XB-C18 100A; 50 mm × 3. 0 mm, 1. 7 um). The mobile phase consisted of isocratic solvent A (methanol; 0. 01-2 min) and then isocratic solvent B (methanol/n-hexane, 72:28, v/v; 2. 5-6 min). The temperature of the column was 40 °C. The flow rate was 0. 4 mL/min, and sample injection volume was 10 μL.
Statistical Analysis The obtained results underwent statistical analysis in which, for quantitative variables, the arithmetic mean, median and standard deviation (SD) were calculated. The examined variable distribution was assessed by the Kolmogorov-Smirnov test. Because the tested variables were inconsistent with normal distribution, the Mann-Whitney U test was used. Spearman's method was applied for assessing correlations between the variables. In calculations, a relevance level of p < 0. 05 was accepted as statistically significant, authorizing the rejection of individual null hypotheses. The data were processed using the Polish version of Statistica 12. 0 statistical software for Windows.
15 A basic version of this story along with its relation to the question of heresy can be found in van Ess, The flowering. 16 El-Shamsy, The social construction 105-106. 17 El-Shamsy 106. For information on the Sunni revival in general, see shafir dition in Shahrastānī's hands was less a call for the persecution of the infidels and heretics of the sixth/twelfth century than a clear expression of the modus vivendi that marked the new Sunni consensus. Yet, it would be a mistake to assume that Shahrastānī's work, or really any other heresiography, was commonly read in Anatolia before the tenth/sixteenth century. The IslamAnatolia database of 7,000 texts written in medieval Anatolia finds no easily identifiable heresiography, for example. 21 When we look at the extant copies of Shahrastānī's text in Istanbul's libraries today, we find that the dated copies are nearly all from the sixth/twelfth and seventh/thirteenth centuries, following its release, and from the mid-eleventh/seventeenth century onward.
Kutluay, did not provide the accession number of his source. See Hanefi, Sapıklarla dinsizlerin. I found the original copy in SK, MS Süleymaniye 791. It was copied by a ʿAlī b. Yāsīn b. Muḥammad al-Ṭarābulusī al-Ḥanafī, a scholar of seemingly Arab origins on 9 Shawwal 904/ 20 May 1499. The timing of this only surviving copy fits well with a renewed interest of the Ottoman establishment in heresiographies (i. e. , right before the start of Shah Ismāʿīl's campaigns). Not much is known about the copyist, but his last name suggests that he came from greater Syria. There is a collection of fatwas from him in Beyazıt Devlet  Kütüphanesi, MS Veliyüddin 1587. 34  Lüṭfī Pasha, Risāle-i Fıraḳ-i ḍālle, SK, MS Ayasofya 2195. Parts of this text, such as the list of ten qualities, are found in his other works.
Acknowledgments I would like to thank the editors of this volume,  Tijana Krstić  and  Derin Terzioğlu , as well as the anonymous reviewers for their very insightful comments on earlier drafts. Research for this essay was supported by the  European Research Council (ERC)   Consolidator Grant  under the European Union's  Horizon 2020 research and innovation program  (grant agreement No  648498 ).
Analysis of the protein contents of velocity and density fractions by filter trap For filter trap assays, native fractions were spotted onto nitrocellulose 0. 2-m membranes (Protran, GE) using a dot blot vacuum device (Whatman). Nitrocellulose membranes were fixed for 30 min in PBS with paraformaldehyde (PFA) at 0. 4% (v/v) (Sigma-Aldrich) final concentration. After three washes with PBS, membranes were blocked with 5% (w/v) skimmed powder milk in PBS-Tween 0. 5% (v/v) and probed with primary and secondary antibodies in PBS-Tween with 4% (w/v) bovine serum albumin (table  S1 ). Immunoreactivity was visualized by chemiluminescence (Bio-Rad). The amount of the respective protein in each fraction was determined by the Image Studio Lite software after acquisition of chemiluminescent signals with a ChemiDoc digital imager (Bio-Rad).
Nanoliquid chromatography-tandem MS analysis and label-free quantitative data analysis Peptide mixture was analyzed on an UltiMate 3000 Nano LC system (Dionex) coupled to an Electrospray Orbitrap Fusion Lumos Tribrid mass spectrometer (Thermo Fisher Scientific). Ten microliters of peptide digests was loaded onto a 300-m-inner diameter × 5-mm C18 PepMap trap column (LC Packings) at a flow rate of 10 l/min. The peptides were eluted from the trap column onto an analytical 75-mm-inner diameter × 50-cm C18 PepMap column (LC Packings) with a 4 to 40% linear gradient of solvent B in 105 min (solvent A was 0. 1% formic acid, and solvent B was 0. 1% formic acid in 80% ACN). The separation flow rate was set to 300 nl/min. The mass spectrometer operated in positive ion mode at a 1. 8-kV needle voltage.
Data were acquired using Xcalibur 4. 1 software in data-dependent mode. MS scans [mass/charge ratio (m/z), 375 to 1500] were recorded at a resolution of R = 120,000 (at m/z of 200) and an AGC target of 4 × 105 ions collected within 50 ms. Dynamic exclusion was set to 60 s, and top speed fragmentation in HCD mode was performed over a 3-s cycle. Tandem MS scans with a target value of 3 × 103 ions were collected in the ion trap with a maximum fill time of 300 ms. In addition, only +2 to +7 charged ions were selected for fragmentation. Other settings were as follows: no sheath or auxiliary gas flow; heated capillary temperature, 275°C; normalized HCD collision energy of 30%; and an isolation width of 1. 6 m/z. Monoisotopic precursor selection was set to peptide, and an intensity threshold was set to 5 × 103.
Database search and results processing Data were searched by SEQUEST through Proteome Discoverer 2. 3 (Thermo Fisher Scientific) against the Mus musculus Reference Proteome Set (from UniProt 2019-07; 55,121 entries). Spectra from peptides higher than 5000 Da or lower than 350 Da were rejected. The search parameters were as follows: Mass accuracy of the monoisotopic peptide precursor and peptide fragments was set to 10 parts per million and 0. 6 Da, respectively. Only b-ions and y-ions were considered for mass calculation. Oxidation of methionines (+16 Da) and protein N-terminal acetylation (+42 Da) were considered as variable modifications, and carbamidomethylation of cysteines (+57 Da) was considered as fixed modification. Two missed trypsin cleavages were allowed. Peptide validation was performed using Percolator algorithm, and only "high confidence" peptides were retained corresponding to a 1% false-positive rate at peptide level.
Peaks were detected and integrated using the Minora algorithm embedded in Proteome Discoverer. Proteins were quantified on the basis of unique peptide intensities. Normalization was performed on the basis of total protein amount. Protein ratios were calculated as the median of all possible pairwise peptide ratios. A t test was calculated on the basis of background population of peptides or proteins. Quantitative data were considered for proteins quantified by a minimum of two peptides, fold changes above two, and a statistical P value lower than 0. 05.
Patients and methods We surveyed all 43 Spanish institutions treating pediatric cases (1 month -18 years of age), with solid and hematologic malignancies, non-malignant hematologic conditions (those receiving immunosuppressive treatment or bone marrow failure syndrome) and after allogeneic-stem cell transplantation, or CAR-T cell therapy who were diagnosed with COVID-19 from the start of the SARS-CoV-2 pandemic on January 31 to April 24, 2020. This is a collaborative SEHOP initiative. Demographic and clinical data were collected from medical records. This study was approved by the Hospital Sant Joan de Déu Research Ethical Committee. Definitions: Symptoms severity was classified using the WHO criteria 10 : Asymptomatic infection, mildmoderate (presence of fever, symptoms of upper respiratory tract infection, pneumonia without the need for respiratory support), severe (dyspnea, tachypnea, blood oxygen saturation [?]93%), critical (respiratory failure, septic shock, and / or multiple organ dysfunction / failure).
Results Information of SARS-CoV-2 positive cases was received from 41 hospitals. According to the Spanish Pediatric Cancer Registry (RETI-SEHOP), these centers are responsible for the treatment of 97. 6% of pediatric cancer patients in Spain. As to non-malignant hematological cases, no global database is available due to the heterogeneity of the different diseases, but the sample seems to be representative because these chronic diseases are treated in the same Pediatric and Oncology Units. Demographic data, underlying diagnosis, clinical features, therapy received and outcome related to RT-PCR confirmed SARS-CoV-2 (nasopharyngeal swab) infection of 47 patients are summarized inTable 1. The median age of our cohort was 8. 2 years, with male predominance (72. 3%). The majority of cases had leukemia or lymphoma (51.
Moreover, the data was collected both retrospectively and prospectively. Thus, it may be a limitation when reporting disease evolution and other time-dependent factors. Finally, as the present study is multicentric and data was collected from different hospitals around the country, a potential interindividual variability may exist when reporting the different clinical scenarios. However, since most of the physicians of the Spanish Units of PHO took part in this initiative, we believe our report represents an accurate infection prevalence among children diagnosed with cancer and chronic hematological disorders in our country. This is one of the largest series of COVID-19 in pediatric cases with solid and hematological malignancies, benign hematologic conditions, and post allo-SCT reported during the present pandemic.
Institut des Sciences de la Terre d'Orléans, UMR 7327, Université d'Orléans/BRGM/CNRS, 45100 France Due to concerns regarding potential impacts of the development of natural gas from unconventional hydrocarbon resources on groundwater systems in North America and elsewhere, it has been crucial to improve methods of Environmental Baseline Assessment (EBA). Any subsequent deviations from the EBA could indicate migration of natural gas into the monitored groundwater systems. In collaboration with Alberta Environment and Parks, over 800 groundwater samples have been collected from dedicated monitoring wells since 2006 resulting in an extensive high-quality database of aqueous and gaseous geochemical and isotopic compositions. Because methane is the main component of natural gas, it had been the principal target of our groundwater studies.
The adaptor ligated library size (458bp, 516bp, 678bp) was confirmed on an Agilent 2100 Bioanalyzer with the DNA7500 assay. All libraries were quantified with the Library Quantification Kit for Illumina Platforms (Roche-Kapa Biosystems). The sequencing library with the mean insert size of 429bp (agarose gel, fraction E) was sequenced using TruSeq Rapid SBS Kit v2 (Illumina), in paired-end mode, 2x251bp, in two sequencing lanes of Illumina HiSeq2500 flowcell v2 (Illumina) according to standard Illumina operating procedures with a minimal yield of 170 Gb of raw data. Primary data analysis, image analysis, base calling and quality scoring of the run, were processed using the manufacturer's software Real Time Analysis (RTA 1. 18. 66. 3) and followed by generation of FASTQ sequence files by CASAVA.
Genome size and complexity As there is no empirical estimate for P. clavata genome size, we downloaded 41 C-value estimates corresponding to the Cnidaria phylum in the Animal Genome Size Database  (Gregory 2017). In addition, we ran two different k-mer analyses on the raw PE reads to estimate the ploidy (Supplementary Information), the size and the complexity of the genome. First, we examined the frequency distribution of 57-mers using Jellyfish v2. 2. 6  (Marçais and Kingsford 2011). Second, we determined the ploidy with Smudgeplot  (Ranallo-Benavidez et al. 2020). Lastly, we ran GenomeScope v2. 0 (Ranallo-Benavidez et al. 2020) using two different k-mer lengths (k = 21 and k = 57) and the appropriate ploidy level. Filtering contaminated reads and trimming Paired-End (PE) reads to 150 bp Before de novo assembly, all reads from the paired-end library (PE400) were filtered of contaminants by mapping  (gem-mapper (Marco-Sola et al.