dataesr/scientific-paragraphs-categorization huggingface dataset:
Genome mining targeting the orphan NRPS gene cluster is therefore a powerful approach to discover novel NRPs. During our genome survey of sequenced strains, an orphan NRPS gene cluster (asm) was identied from a marine Streptomyces sp. NA03103. The asm gene cluster is unusual for three reasons: (i) no homologous gene clusters can be found in the public genome databases through ClusterBlast, a dereplication module in online soware antiSMASH;  10  (ii) the upstream and downstream genes anking the putative asm gene cluster are highly conserved (>93% identity) in a model Streptomyces strain S. lividans TK24 (Scheme 1); (iii) all four NRPSs (AsmC, AsmM, AsmN and AsmS) are small monomodule NRPSs, which are in sharp contrast to the canonical multimodule NRPS megaenzymes in bacterial gene clusters.
Hence, we carried out a large-scale (20 L) fermentation from which we isolated compounds 1-9 (Fig. S3  †), the latter seven of which were barely observed in the HPLC prole. Compound 1 (1. 0 mg L À1 ) was obtained as a pale yellow crystal with a molecular formula of C 19 H 20 N 4 O 10 as determined by its HRESIMS and  13  C NMR data (Table  S4  †). The planar structure, along with the absolute congurations, was unambiguously determined by analyzing its NMR and single-crystal X-ray diffraction data with a ack parameter value of À0. 03 (7)  collected using Cu Ka at low temperature (Fig. S4 †   S5 , Fig. S5 † ). Structures of 3-9 were characterized through extensive analyses of HRMS and NMR data (Tables S6-S12 †). To assess the biological activity, we then evaluated the cytotoxicity of 1-9 against MCF-7 cell lines using the MTT assay.
Acknowledgements Authors thank  Dr Brian Traw  ( Nanjing University ) for critical reading and helpful discussion. This work was nancially supported by the  National Natural Science Foundation of China  (No. 81522042 ,  21572100 ,  81773591 ,  81530089 ,  21672101 ,  81673333 ,  21861142005 ,  21761142001 ,  21661140001 ,  J1210026 , and  J1103512 ),  Ministry of Science and Technology  ( 2018YFC1706205 ) and  Fundamental Research Funds for the Central Universities  (no. 020814380092 ).
Study design This retrospective, observational study included all patients with HSCT from all donor types and stem cell sources for acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML) or chronic myeloid leukemia (CML) between 1980 and 2015, reported by 588 centers from 51 countries to the EBMT database. This patient selection and the two time periods (cohort 1 from 1980-2001and cohort 2 from 2002-2015) were based on a previous study, but did include now all disease stages, not only first CR patients  [1]. There were no exclusion criteria. All data collection was performed by the IDWP Data Office (Leiden) according to EBMT guidelines (http://www. ebmt. org/retrospectivestudies). The analysis followed a stepwise approach. First, the data cohort was set up: all transplants in the EBMT data file from 1980 to 2015 were retrieved and assessed for completeness as specified below.
GVHD was used as "any GVHD ever", not separated by acute or chronic GVHD. The cumulative incidence estimator was applied, with the Gray test being used to compare different groups. Differences in CumInc rates without overlapping of the 95%CI's were considered as significant. The cause-specific Cox model was used to detect the factors related to the infection death for the four posttransplant phases. The death due to infection was considered as event of interest and death due to other causes as competing event. Factors integrated into the analysis were sex and age of the patients, main diagnosis (ALL or AML or CML), stage of the disease, donor/recipient sex matching (HY -vs HY + ), type of donor (HLA-matched sibling vs other donor types), type of conditioning (RIC vs MAC), source of stem cells (PB vs BM vs CB), year and number of transplantation and presence or absence of in vivo and ex vivo T-cell depletion, and macro-and microeconomic center data as explained above.
Factors with a p-value < 0. 2 from the univariate analysis were included in the multivariate analysis. Factors with a p value of <0. 05 were considered as significant. Comparisons for categorical variables were done using the Fisher's exact test or the χ 2 test. The proportional hazard assumption was verified using graphical methods: scaled Schoenfeld  [19]  residuals and graphical checks proposed by Klein-Moeschberger  [20]  were performed without finding evidence of relevant violations. All the analyses were performed using the statistical software SAS (SAS Institute Inc. , Cary, NC, USA) version 9. 4.
This is supported by the increased risk of infectious deaths in HY + donor recipient combinations. Of note, disease specific center experience in years was strongly associated with reduced infectious deaths in the early post-transplant phase  [22]. Cumulative incidences of mortality for the respective cause of death during the 4 post-transplant time periods, day 0 to day 30, day 30 to day 100, day 100 to 1 year, and 1 year to 5 years (see methods section for details), are shown There are major caveats in this study. It looks at very heterogeneous data over a long time period with many changes in disease indications, choice of donor type, stem cell source. over calendar year time. Data were derived from a multitude of centers from many countries with different micro-and macroeconomic backgrounds.
Some data, such as cytogenetic profiles were not in the data set. Some decisions had to be arbitrary, such as the use of economic factors as of the year 2016. Centers had varying attitudes regarding data collection, and potentially different interpretations of "cause of death". Simply, we used the data as they were reported to the database, and we accepted the information as given by the center, including the high rate of deaths and infectious deaths of "unknown" origin. Still, the consistency of the findings in the four post-transplant phases, and the confirmation of key risk factor elements are strong arguments that the data are valid. They were as well in line with our pre-set hypotheses, that factors associated with overall mortality and from infections would differ depending on the post-transplant phase.
Funding The study was funded by the  European Group for Blood and Marrow Transplantation EBMT. EBMT is supported by grants from the corporate members:  Amgen Europe ,  ViroPharma Europe ,  Celgene International SARL, Genzyme Europe B. V. , Gilead Sciences Europe Ltd. , MiltenyiBiotec GmbH, Schering-Plough International Inc. , Bristol Myers Squibb, Caridia BCT Europe NV, Cephalon Europe, F. Hoffmann-La Roche Ltd, Fresenius Biotech GmbH, Therakos Inc. , Alexion Europe, Chugai Sanofi-Aventis ,  Merck Sharp and Dohme ,  Novartis ,  Pfizer ,  Pierre Fabre Médicament.
Signals were detected with an enhanced chemiluminescence (ECL) kit (ECL western blotting detection kit; GE Healthcare) and captured with ImageQuant 400 (GE Healthcare). The relative intensities of the immunoreactive bands were analyzed with ImageQuantTL software (GE Healthcare). The loading was verified by Ponceau S red (Sigma-Aldrich, St. Louis, MO, USA), and the same blot was stripped and reblotted with an anti-b-actin monoclonal antibody (Sigma-Aldrich) to normalize the VEGF and PEDF levels.
Choroidal Flatmounts and Neovascularization Brown Norway rats (n = 6 per study group) were euthanized at 7 and 14 days post-laser. Eyes were enucleated and fixed for 1 h in 4% paraformaldehyde diluted in PBS at 4 C. RPE-choroid-sclera complexes were microsurgically isolated and incubated with blocking buffer containing PBS, 3% Triton X-100, 0. 5% Tween 20, 2% sodium azide, and 1% FBS for 1 h at 4 C. Then, they were incubated with biotinylated isolectin (GS-IB4; Vector Labs, Burlingame, CA, USA) overnight at RT, and the flatmounts were washed in PBS and incubated in Alexa Fluor Streptavidin 594 (1:250; S32356; Life Technologies, Carlsbad, CA, USA). The CNV lesions were captured under a confocal microscope (LSM800; Zeiss, Oberkochen, Germany), and the areas were measured by Fiji ImageJ software.
org/links/genelists). The orthologous positions were obtained from Ensembl (http://www. ensembl. org/ biomart/martview/59de4d4d3503246cb451221246ed7978). UCRs of the rat genome were arbitrarily determined from the phastCons13way track for the rn5 assembly retrieved from the University of California Santa Cruz (UCSC) table browser (http://genome. ucsc. edu/) by filtering regions with scores R800. Expressional data on the rat retinal transcriptome were published by Kozhevnikova et al. 103  We used the expressional dataset obtained from the retinas of 3-month-old Wistar rats. Non-expressed genes of the retina were defined on the bases of absence of reads from the genes in the dataset. The expressed genes were grouped into five sets of the same size according their expression levels, and insertions were counted in them and compared with a random expected frequency determined with the random insertion dataset.
Statistical Analysis Data are presented as mean ± SEM. Statistical analysis was performed using SPSS 2. 0 (SPSS, Chicago, IL, USA) and GraphPad Prism 5. 0 (GraphPad Software, San Diego, CA, USA) programs. In vitro studies were analyzed applying an ANOVA for repeated measures. For CNV area results, one-way ANOVA was followed by Bonferroni post hoc tests for multiple comparisons after confirming normal distribution of the data. p < 0. 05 was considered statistically significant.
ACKNOWLEDGMENTS This work was supported by the  European Union 's  Seventh Framework Programme  for research, technological development, and demonstration (grant agreement no. 305134 ) and  Fundación Jesús Gangoiti Barrera. Publication costs have been financed by  Fundación Multiópticas (Spain)  within a collaborative project with the  University of Navarra. L. G. -G. received a predoctoral grant from the  Asociación de Amigos de la Universidad de Navarra, Spain. Z. Izsvák was funded by  European Research Council ,  ERC Advanced  [ ERC-2011-ADG 294742 ].
We use a similar approach to study the effect of duty cycle and voltage on the comb-drive as we do with the parallel plate. The results are shown in Fig. 3b. Again, each color represents a different driving scenario with black as the DC voltage control and the other colors (i. e. green, purple, blue and red) as different PWM voltages. The DC voltage curve holds a constant 90% duty cycle while increasing the voltage, whereas, the PWM drives hold a constant voltage while varying the duty cycle. The open circles are the experimental data points and the solid lines represent the analytic solutions. The analytic solutions use equation (  8 ) instead of equation (  10 ) due to the aforementioned fringe field effects. We use an optical microscope to measure the comb-drive geometry and use these measurements in Comsol Multiphysics to simulate a value for dC/dx.
To operate properly the normalized oscillation amplitude needs to be less than 0. 01 and we can experimentally determine the necessary frequency. Fig. 5b  shows that the performance of the switching circuit and amplifier are comparable. This gives us confidence moving forward that we can use the switching circuit in place of the amplifier. Fig. 5b  also shows that the oscillation of the DM drops below the amplitude limit at 700 kHz. We use this frequency to demonstrate the steady state response. For the steady state response, we use the white light interferometer to measure the vertical displacement of the mirror. Fig. 5c  shows a central result of this paper. The DC voltage control is shown in black with data points as solid black squares and the solid line is a quadratic fit to the data.
Additionally, this progressive degeneration varied among muscle and fiber types. Finally, the lack of glycogen content increase was associated with the inactivation of glycogen synthase and not with compensatory expression of the Pygl and/or Pygb genes in mature muscle. McArdle disease (glycogen storage disease V; myophosphorylase deficiency; OMIM database number ♯232600; ORPHA: 368) is an autosomal recessive disorder caused by pathogenic mutations in the gene (PYGM) encoding the muscle isoform of glycogen phosphorylase (GP-M, also known as myophosphorylase) 1,2. GP-M initiates the breakdown of muscle glycogen, leading to the release of glucose-1-phosphate in muscle fibers. Patients are unable to obtain energy from their muscle glycogen stores 3 , and present with exercise intolerance, usually in the form of reversible, acute crises of early exertional fatigue and contractures that can also be accompanied by rhabdomyolysis, as reflected by marked increases in serum levels of creatine kinase (CK) or even myoglobinuria ('dark urine')  4, 5.
The survival curve was calculated for all the genotyped post-weaning mice of the colony that were born between 01/01/2013 and 05/08/2018 (n = 2,088). The Kaplan-Meier survival function, also known as the product-Limit estimator was used  13. For each mouse, the following data were entered (GraphPad Prism version 6. 00 for Windows, GraphPad Software, La Jolla, CA, www. graphpad. com): 1) X-values: time (number of days alive until an event or censoring occurred); 2) Y-values: Y value is "1" when the mouse died at the specified time, and "0" when the mouse's data was censored at that time. Histology and immunohistochemistry. Dissected muscles were flash frozen in isopentane cooled in liquid nitrogen and stored at -80 °C until analysis. Twelve μm cryosections were stained with hematoxylin and eosin (H&E) for general histopathological evaluation as previously described  6.
Central nuclei quantification. For the assessment of centrally nucleated fibers (CNF), sections were stained for laminin (for antibodies, see Supplementary Table ) to distinguish individual muscle fibers and DAPI to visualize the nuclei. Total and CNF were counted manually, and the results were recorded using the cell counter plug-in from the image J software 1. 37 version (NIH; Roth Bethesda, MO). Between 491 and 5,079 fibers (median 1682 fibers) from at least three different mice were counted per age and genotype. Results were expressed as the mean percentage of CNF per muscle. For enhanced visualization of nuclei staining surrounding the sarcoplasmic membrane [(peripheral nuclei (PN)], laminin-DAPI staining images were opened in TIFF format with the Adobe Photoshop program (Adobe ® Photoshop ® CS5 extended v.
12. 0, San Jose, CA, USA) and tone-and saturation-adjusted. Fiber size determination. Fiber size was calculated from laminin-DAPI stains using the minimal Feret's diameter (Image J software ver. 1. 37) to attain the fiber size least influenced by sample sectioning angle  14. Between 240 and 1,444 fibers (median 459 fibers) from at least three different mice were counted per age and genotype.
37. Muscle glycogen. One hundred and fifty mg of tissue were boiled for 30 min with 30% KOH and, subsequently, 1. 2 volumes of 95% ethanol were added to precipitate glycogen. After a centrifugation step (25 min at 840 g), the glycogen pellet was resuspended in 0. 3 ml of water. Next, 0. 1 ml of 5% phenol was added to 0. 1 ml of sample and treated with 0. 5 ml of H 2 SO 4 (to hydrolyze glycogen to glucose). The mixture was allowed to stand for 30 min at room temperature and the glucose released was measured spectrophotometrically at 490 nm. A standard curve made with glycogen purified from rabbit liver (Sigma-Aldrich), ranging from 0. 1 to 0. 8 mg mL -1 , was processed in parallel. The results were expressed as mg glycogen (g wet tissue) -1,17. statistics. All statistical analyses were performed using the GraphPad Prism software.
Acknowledgements The present study was funded by grants received from the  Fondo de Investigaciones Sanitarias (FIS , grant  PI16/01492  and  PI15/00558 ) and cofunded by  'Fondos FEDER'. Gisela Nogales-Gadea  is supported by a Miguel Servet research contract ( ISCIII CD14/00032  and  FEDER)  and  Instituto de Salud Carlos III  grant  PI15/01756  and by a  Trampoline Grant  # 21108  from  AMF Telethon.
An understanding of astrophysical feedback is important for constraining models of galaxy formation and for extracting cosmological information from current and future weak lensing surveys. The thermal Sunyaev-Zel'dovich effect, quantified via the Compton-y parameter, is a powerful tool for studying feedback, because it directly probes the pressure of the hot, ionized gas residing in dark matter halos. Cross-correlations between galaxies and maps of Compton-y obtained from cosmic microwave background surveys are sensitive to the redshift evolution of the gas pressure, and its dependence on halo mass. In this work, we use galaxies identified in year one data from the Dark Energy Survey and Compton-y maps constructed from Planck observations. We find highly significant (roughly 12σ) detections of galaxy-y cross-correlation in multiple redshift bins.
A. DES redMaGiC catalog The primary goal of this analysis is to constrain the redshift evolution of the pressure of the Universe by measuring the correlation between galaxies and maps of the Comptony parameter. To this end, we require a sample of galaxies that have well measured redshifts, and which can be detected out to large redshift. An ideal catalog for this purpose is the redMaGiC catalog  [15]  derived from first year (Y1) DES observations. The Dark Energy Survey is a 5. 5 year survey of 5000 sq. deg. of the southern sky in five optical bands (g, r, i, z, and Y) to a depth of r > 24. In this analysis, we use first Y1 data from DES covering approximately 1321 sq. deg. to roughly r ∼ 23  [16, 23]. redMaGiC galaxies are identified in DES data based on a fit to a red sequence template using the methods described in Rozo et al.
We compare this fiducial CIB frequency dependence to Planck  [44]  and Sehgal simulations in Fig. 3. The Planck points are derived from the rms fluctuations of the CIB anisotropy spectrum over the range 200 < < 2000. We note these measurements are consistent with the frequency scaling of the mean of the CIB field, as described in Planck Collaboration et al. [44]. Fig. 3  shows that the frequency dependence of the CIB in both the simulations and the Planck data are consistent at roughly the 10% level over the frequency range relevant to this  analysis. Larger deviations are observed at 545 and 857 GHz, but these channels are not used in the y map reconstruction (see below). We also show the redshift dependence of the frequency scaling by cross-correlating with halos in different redshift bins, finding some variation.
F. Validation of model assumptions and pipeline We apply our analysis pipeline to the simulated data by correlating the mock y maps with both the simulated redMaGiC and halo catalogs. In the two-halo regime, both the redMaGiC galaxies and the halos should lead to consistent estimates of bP e. The left panel of Fig. 5  shows the ratio of these two measurements for both the Buzzard and MICE simulations. Indeed, we find that the redMaGiC and halo measurements are consistent in both simulations, a strong test of our modeling assumptions and methodology. We can also compare the recovered values of bP e from the simulations to the value computed from the Eq. 15. Since we know the true cosmological and profile parameters used to generate the simulated y map, the measurement in simulations should match the theory calculation, provided our assumptions and methodology are correct.
VI. CONCLUSIONS We have measured the cross-correlation of DES-identified galaxies with maps of the Compton-y parameter generated from Planck data. We detect significant cross-correlation in four redshift bins out to z ∼ 0. 75. Using these measurements and measurements of galaxy clustering with the same galaxy sample, we constrain the redshift evolution of the biasweighted thermal energy of the Universe, which we call bP e. Our measurement of bP e extends the previous measurement of this quantity from V17 from z ∼ 0. 15 to z ∼ 0. 75. High redshifts are of particular interest given the large uncertainties in both the modeling and data in this regime. Several features make bP e an interesting probe of gas physics. First, it can be measured robustly even without a complete understanding of the galaxy-halo connection, as demonstrated in this analysis.
For instance, our measurements would not be sensitive to feedback processes that only move gas around without injecting any additional energy. If one is interested in separating changes to the thermal energy from changes in the bulk distribution of gas, then bP e is a powerful tool to this end. As shown in Fig. 8 , our measurements are consistent with the shock heating model from B10, with small variations depending on the extent of the profile. We use the bP e measurements to constrain departures from the purely gravitational shock heating model, with the results shown in Fig. 9. Our measurements constrain such departures at roughly the 20-60% level. The measurements presented here use data from only the first year of DES observations, covering roughly 25% of the full survey area of DES. We also employ several conservative data cuts: (1) the highest redshift bin (0.
ACKNOWLEDGMENTS We thank the  Websky group  for making their simulations publicly available, and for providing support for their use. We thank  Mathieu Remazeilles  for assistance in understaning the Planck y-maps. We also thank  Nicholas Battaglia  for valuable discussions regarding pressure profile models and the formalism of the paper. SP, EB, ZX and JOS are partially supported by the  U. S. National Science Foundation  through award  AST-1440226  for the  ACT  project. SP and EB are also partially supported by the  US Department of Energy  grant  DE-SC0007901. Funding for the DES Projects has been provided by the  U. S. Department of Energy , the  U. S. National Science Foundation , the  Ministry of Science and Education of Spain , the  Science and Technology Facilities Council of the United Kingdom , the  Higher Education Funding Council for England , the  National Center for Supercomputing Applications  at the  University of Illinois at Urbana-Champaign , the  Kavli Institute of Cosmological Physics at the University of Chicago , the  Center for Cosmology and Astro-Particle Physics at the Ohio State University , the  Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University ,  Financiadora de Estudos e Projetos, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro ,  Conselho Nacional de Desenvolvimento Científico e Tecnológico  and the  Ministério da Ciência, Tecnologia e Inovação , the  Deutsche Forschungsgemeinschaft  and the  Collaborating Institutions in the Dark Energy Survey.
Based in part on observations at  Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory , which is operated by the  Association of Universities for Research in Astronomy (AURA)  under a cooperative agreement with the  National Science Foundation. The DES data management system is supported by the  National Science Foundation  under Grant Numbers  AST-1138766  and  AST-1536171. The DES participants from Spanish institutions are partially supported by  MINECO  under grants  AYA2015-71825 ,  ESP2015-66861 ,  FPA2015-68048 ,  SEV-2016-0588 ,  SEV-2016-0597 , and  MDM-2015-0509 , some of which include ERDF funds from the  European Union. IFAE is partially funded by the  CERCA program  of the  Generalitat de Catalunya. Research leading to these results has received funding from the  European Research Council  under the European Union's  Seventh Framework Program  (FP7/2007-2013) including  ERC  grant agree-.