dataesr/scientific-paragraphs-categorization huggingface dataset:
In silico Effects of Pharbitis nil Metabolites Against Entodinium caudatum Cyclic GMP (cGMP)-dependent protein kinase (cGK), the central regulator of cGMP signaling in malaria parasites and a potential target for new antimalarial drugs  (Baker et al. , 2020) , was used to evaluate the potential antiprotozoal effects of major PA metabolites. Because the rumen protozoa-specific protein sequence of cGK was not available in non-redundant databases, we used a manual method to determine the protein sequence. The partial mRNA sequence of cGK 9-1(XM_001017123) from Tetrahymena thermophila SB210, a widely used protozoal model, was retrieved from the NCBI database (accessed on 02 September 2021). The non-annotated genome assembly of E. caudatum MZG-1 (NBJL00000000. 3) was downloaded from the NCBI database (accessed on 02 September 2021), and a local nucleotide database was created in BioEdit version 7.
2. 5 (Scripps Research, La Jolla, CA, United States)  (Hall, 1999). A local nucleotide BLAST (BLASTn) search of the T. thermophila SB210 cGK nucleotide sequence was performed against the E. caudatum strain MZG-1 genome database. The result revealed nucleotide homology with E. caudatum strain MZG-1 (NBJL03004678. 1). Furthermore, a protein homolog of the E. caudatum strain MZG-1 protein was searched for using the BLASTx algorithm 1. The results revealed that the sequence of E. caudatum strain MZG-1 was 67% homologous (e-value = 0) to Bacillus cyclic nucleotidebinding domain-containing protein (MBP3841481) and its corresponding nucleotide (JAGAWU010000032) sequences. The corresponding aligned nucleotide sequence of E. caudatum strain MZG-1 was extracted and translated to an amino-acid sequence using the BLASTx algorithm.
The amino-acid sequence was confirmed to encode cGK and was later used as the query for structure prediction. The primary structural parameters of the E. caudatum strain MZG-1 specific cGK (query) protein were determined using ProtParam 2. The physicochemical characters such as molecular weight, theoretical isoelectric point, amino-acid composition, extinct coefficient, estimated half-life, instability index, aliphatic index, and grand average of hydropathicity were computed. Secondary structure conformational parameters related to the presence of α-helices, β-turns, extended strands, and random coils were computed using the self-optimized prediction method with alignment (SOPMA) tool 3. The similarity of the query protein with publicly available homologs was assessed by searching against non-redundant databases, including NCBI and Protein Data Bank (PDB) databases.
The online protein structure prediction tool PS 2 4  was used to predict the three-dimensional structure of the protein. Superimposition of predicted models of the query onto the template was performed using SALIGN 5  and visualized using the UCSF Chimera package  (Pettersen et al. , 2004). The models were analyzed based on the DOPE score, and their stereochemical quality was validated by generating a Ramachandran plot using PROCHECK 6  on the SAVES server 7. For molecular docking studies, the chemical structures of the major metabolites (ligands) of PA (dicaffeoyl quinic acid, quercetin-3-O-glucoside, chlorogenate, palmitic acid, linoleic acid, and oleic acid) were retrieved from the PubChem compound database 8. The retrieved ligand structures in. sdf format were converted to. pdb format using PyMOL version 1.
7. 4. 5 software (DeLano Scientific LLC, San Carlos, CA, United States). Docking analysis was carried out using AutoDockTools version 1. 5. 4 and AutoDock version 4. 2 software (Scripps Research Institute Molecular Graphics Laboratory, La Jolla, CA, United States) as described previously  (Arokiyaraj et al. , 2015). The docked complexes were visualized using Discovery Studio Visualizer version 4. 5 (BIOVIA, San Diego, CA, United States).
Statistical Analyses In vitro data were analyzed using the PROC MIXED procedure of SAS version 9. 4 (SAS Institute, Cary, NC, United States) with a Tukey-Kramer adjustment. The dose was considered a fixed effect and each incubation run a random effect. Linear, quadratic, and cubic components of the response to increasing doses of PA were evaluated using orthogonal polynomial contrasts. The CONTRAST option of the MIXED procedure uses the coefficient matrix generated in PROC IML for unequally spaced treatments. Pearson's correlation coefficients were calculated to identify correlations between substrate FA concentration, CH 4 production, fermentation characteristics, and digestibility using the PROC CORR function in SAS. In sacco data were also analyzed using the PROC MIXED procedure of SAS.
Means were calculated using the LSMEANS function and were compared using the PDIFF option in SAS. Significant treatment effects were detected by pairwise comparisons employing Tukey's test. Regarding differences according to treatment, p < 0. 05 was taken to indicate significance and 0. 05 < p < 0. 1 was considered to indicate a trend toward significance. To identify bacterial lineages that drive the clustering of microbial communities in different phases, we performed principal component analysis (PCA) using the fviz_pca_biplot function in the FactoMineR package  (Husson et al. , 2020)  in R version 4. 0. 3 software (The R Foundation for Statistical Computing, Vienna, Austria).
In silico Analysis of the Effects of Active Metabolites From Pharbitis nil on cGK The results of a primary structural evaluation of the deduced cGK protein using ProtParam are shown in Supplementary Tables  3, 4. Evaluation of secondary structure conformational parameters using the SOPMA tool indicated that cGK is composed of 29. 06% loops, 46. 39% helices, 16. 83% extended strands, and 7. 72% β-turns (Supplementary Figure  2 ). Homology modeling of cGK performed based on the crystal structure of the A chain of Plasmodium vivax Sal-1 cGK (PDB ID: 4RZ7) as the template yielded sequence identity and e-values of 41. 8 and 2e-94, respectively (Supplementary Figure  3A ). The predicted model of cGK was superimposed on the cGK template (PDB ID: 4RZ7; Supplementary Figure  3B ). PROCHECK analysis to assess the quality of the predicted model using a Psi/Phi Ramachandran plot indicated that 85.
To estimate the grain size of the ceramic matrix, cross section surfaces of the composites were polished with diamond paste up to 1 µm, annealed for 15 min in air at a temperature 100 ºC lower than the composite sintering temperature, and analyzed by low magnification conventional scanning electron microscopy (SEM, FEI-Teneo, FEI, USA, Centro de Investigación, Tecnología e Innovación de la Universidad de Sevilla, CITIUS). The equivalent planar diameter, d = 2(area/π) 1/2 , namely the diameter corresponding to a circle with the same area as the measured grain, was taken as a measure of the ceramic grain size. The shape factor of the grains was calculated as F = 4π area/(perimeter) 2. The ImageJ and Origin software were used to quantify these morphological parameters, averaging 200-300 grains, according to UNE-EN ISO 13383-1:2016 standard.
Microstructural characterization of the EDMed surfaces The microstructure of the EDMed surfaces was analyzed by different techniques. Confocal microscopy (DM3D, Leica, Germany) was used to estimate the tolerances and the surface roughness. Raman spectroscopy (3-4 spectra acquired from each eroded surface) was used to evaluate the integrity of the graphene nanostructures after the EDM process. The equipment was a spectrometer Raman Horiba Jobin Yvon LabRaman HR800 with Olympus BX 41optic system and Labsec 5. 25. 15 data acquisition software (Instituto de Ciencia de Materiales de Sevilla, ICMS), using a 20 mW power green He-Ne laser (532. 1 nm), a diffraction grid of 600 lines/mm and a 100x objective with 100 µm confocal aperture. Finally, scanning electron microscopy, SEM,) and energydispersive X-ray spectroscopy, EDS (JEOL 6460LV, FEI-Teneo, FEI, CITIUS) were performed on the eroded surfaces and on polished cross sections cut through the machined areas.
In order to elucidate quantitative differences obtained on profiles, 3D roughness parameters were evaluated. Fig. 9  shows the evolution of the maximum valley depth (Rv), maximum peak height (Rp), peak-peak height (Rz), surfaces kurtosis (Rku), surface skewness (Rsk), root mean squeare (Rq) and arithmetic mean roughness (Ra). A diminution in roughness parameters, compared to the surface of the unmachined sample, occurs for the EDMed surfaces of the e-GNP composite, being Ra below 0. 5 µm. These values are lower than other reported data for micro-EDM milling of non-conductive zirconia  [27]  and make possible to use EDM as finish process  [28]. When the process becomes unstable, a significant increase can be observed in all the calculated parameters, although Rku and Rsk remain mainly invariable, there is no increase in the asymmetry of the profile.
Acknowledgements This research was supported by the projects  PGC2018-101377-B-100  funded by  MCIN/AEI/ 10. 13039/501100011033  ( Ministerio de Ciencia e Innovación, Spanish Government ,  Agencia Estatal de Investigación)  and  ERDF (European Regional Development Funding)  " A way of making Europe ", by the  European Union  and project  P20_01024  ( Junta de Andalucía/FEDER ,  UE 2014-2020 ). C. López-Pernía  acknowledges the financial support of  MINECO (Ministerio de Economía y Competitividad ,  Spanish Governmet)  through the  FPI  contract ref:  BES-2016-078711. C.
Acknowledgments The authors thank the  Tanzania Commission for Science and Technology (COSTECH)  and  Tanzania National Parks Authority (TANAPA)  for providing research permits. Also, the authors thank  Laura Segers  and  Stefanie Rombaut  for their assistance during fieldworks. Thanks to  Martine Leermakers  and  Natacha Brion  ( AMGC, Vrije Universiteit Brussel ) for their help with chemical analysis of some water samples. Ines Tomašek  acknowledges the support received from the  VUB Strategic Research Program (SRP)  and the  Agence Nationale de la Recherche  of the  French government through the program  " Investissements d'Avenir". Karen Fontijn  acknowledges support from  F. R. S. -FNRS MIS  grant  F. 4515. 20. We also thank the two anonymous reviewers for their thoughtful comments that greatly improved this manuscript.
The procedure is intended to be permanent, but sterility is not achieved immediately  [7]  as there are sperm in the distal vas that need to be expelled, and other forms of contraception must be utilized until the success of the vasectomy is confirmed. Rare failures due to recanalization can occur. Hence, correct postvasectomy monitoring to document the success of the procedure is very important. Between January 1990 and December 2017, the Westlaw database identified 67 lawsuits related to vasectomy in the United States, of which pregnancy/wrongful birth was the most common reason for suing  [8]. According to the American Urological Association (AUA) vasectomy guidelines, the success of the vasectomy procedure is confirmed when a post-vasectomy semen analysis (PVSA) (Fig. 1 ) demonstrates either complete absence of sperm (azoospermia) or the presence of only rare non-motile sperm (RNMS, ≤100,000 non-motile sperm/mL) in one well-mixed, fresh, uncentrifuged post-vasectomy semen sample  [7, 9, 10]  (Fig.
DISCUSSION 1. Post-vasectomy semen analysis: laboratory aspects The PVSA is an important test with significant clinical ramifications and needs to be performed and interpreted carefully as advised in relevant guidelines. The various guidelines vary (Table  1 ) in technical aspects (e. g. , timing of sample collection and the need for centrifugation of the sample) and in the interpretation Fig. 7. Type of sample analyzed after vasectomy to check for the presence of motile sperm. Data are reported as number of participants (n) and percentage (%) out of the total (n=78). PVSA: postvasectomy semen analysis. www. wjmh. org of test results. Clinicians need to be aware of the official guidelines for the region/country they are working in. Proficiency testing and competency assessment for PVSA and quality control are important and are dis-cussed below.
jejuni strain used. All five C. jejuni strains tested survived in the co-culture with S. Typhimurium, where 1. 9, 1. 7, 1. 1, 0. 8 and 0. 2 log CFU/mL were observed for the AC 541, AC 302, AC 400, AC 473 and AC 4322 strains, respectively. Three tested C. jejuni strains showed survival in the co-culture with S. Blegdam, where 2. 2, 1. 9 and 1. 7 log CFU/mL of C. jejuni were recorded for the AC 400, AC 541 and AC 302 strains, respectively. In co-culture with S. Enteritidis, only the C. jejuni strain AC 541 showed a survival of 0. 5 log CFU/mL. However, no survival was observed for any of the different combinations of co-cultures of C. jejuni with S. Infantis or S. Hadar (data not shown). In the co-culture with S. Virchow, for the first series where all five of the C. jejuni strains were tested on mCCD plates, C.
Effect of C. jejuni on Salmonella Growth under Aerobic Conditions In all the tested combinations of co-cultures between Salmonella and C. jejuni strains, the effect of C. jejuni on Salmonella growth under aerobic conditions was also assessed. Analyzing the same samples from all of these trials, the combinations showed that the different initial conditions of C. jejuni (2, 3, 4, 5, and 6 log CFU/mL) had no effect on Salmonella growth (data not shown) and that the presence of different C. jejuni strains had similarly no impact on the growth of the different Salmonella serovars and strains; the results are presented in Table  1. All samples showed comparable results, with mean enumeration concentrations of 8. 5 ± 0. 09 log CFU/mL after incubation during 16 h in aerobic conditions at 37 • C. This observation indicates that all of the Salmonella serovars and strains tested in this study grew in the same way in the absence or presence of different concentrations of C.
jejuni and Salmonella spp. under atmospheric conditions; we highlighted an aspect of C. jejuni whereby it benefits from the presence of Salmonella spp. to survive. Thus, the interaction between these two bacteria was examined, showing how C. jejuni can survive under stressful aerobic conditions in the poultry-processing chain, despite the fact that it is an obligate microaerophile, meaning that it usually cannot survive in aerobic conditions. Despite the general perception that C. jejuni is microaerophilic and therefore sensitive to oxygen, our data showed that C. jejuni C97Anses640 was able to survive alone under aerobic conditions, particularly at the highest initial concentration of 6 log CFU/mL, but not at the lower concentrations. Some previous studies have already reported the ability of C.
4 ). Thus, we infer magnesioferrite in SL82 and SL5_2 to be located under the surface. The compositions of magnesioferrite calculated from the X-ray diffraction and SMS data are reported in Supplementary Table  4. Magnesioferrite has previously been reported with magnesiowüstite, but mainly as small, nanometre-size crystals in magnesiowüstite/ferropericlase matrix, ascribed to either exsolution in ferropericlase  7, 13, 14  or the breakdown of complex iron oxides  15, 16. Interestingly, all magnesioferrite inclusions in diamonds reported in the literature, including the results of this study, coexist either with Ferich ferropericlase or, more often, with magnesiowüstite.
Acknowledgements E. S. K. thanks  Oliver Richards  and  Gil Costa  for help with the figures. D. A. Z. was supported by the  Russian foundation for basic research  (grant No. 21-55-50011 ) and E. S. K. was supported by  NERC  grant  NE/L010828/1  and  IRC grant   IRCLA/2022/2638. The  European Synchrotron Radiation Facility  is acknowledged for beamtime provision at the Nuclear Resonance beamline ID18. We thank  Mr. J. -P. Celse  for technical assistance during the experiment at ID18. We acknowledge  DESY (Hamburg, Germany) , a member of the  Helmholtz Association HGF , for the provision of experimental facilities. Parts of this research were carried out at P02. 2 beamline of PETRA-III, DESY. We thank  Laura Uenver-Thiele  for productive discussions.
65. Each sample spectrum was collected for about 4 h over a velocity range of ±6 or ±12 mm/s depending on whether magnetic interactions were present or not. Velocity scales were calibrated using Fe foil. Mössbauer spectra were fitted to quadrupole doublets and magnetic sextets using MossA software  66  with a full transmission integral assuming a Lorentzian-squared line shape for the instrumental function. The fitted parameters were centre shift (CS), quadrupole splitting (QS), FWHM of the linewidth, hyperfine magnetic field (B) and area (I). Centre shift values are reported relative to α-iron at ambient conditions. X-ray optical components at ESRF, and particularly at the ID18 beam-line, are carefully selected in order to contain the minimum amount (ppm level) of iron. Generally, this amount of iron does not affect SMS spectra due to the strong signal from the sample.
Reduction and analysis of the optical data were performed as described above. At the same time, NIR (2MASS JHK bands) observations were acquired with the REMIR camera mounted on REM, alternating the filters, performing 15 s integration exposures. A total of 90 images/filter were acquired. Dithering of the images was performed with the aim of evaluating the variable contribution of the sky, which was then subtracted from each image. Images were then combined five by five to increase the signal-to-noise ratio. Flux calibration of the NIR images was performed against a group of 2MASS stars in the field.
Swift X-Ray and Optical/UV Monitoring The Neil Gehrels Swift Observatory (hereafter Swift;  Burrows et al. 2005)  observed Cen X-4 16 times between 2020 December 28 and 2021 January 23 with the X-Ray Telescope (XRT;  Burrows et al. 2005)  and Ultraviolet and Optical Telescope (UVOT;  Roming et al. 2005)  instruments. For the XRT, we only analyzed data obtained when the instrument was in Photon Counting mode, as the source was too faint to be detected in the short Window Timing mode exposures. For each XRT observation, we extracted source spectra from a circular aperture with a radius of 20 pixels (∼47″) centered on the source. Background-only spectra were extracted from an annulus with inner and outer radii of 40 and 60 pixels (∼94″ and ∼141″), respectively, also centered on the source. From the background-subtracted spectra, we created a 0.
5-10 keV light curve (with one data point per observation), correcting for changes in the effective area between observations that resulted from differences in how bad columns affected the source counts. The UVOT instrument observed Cen X-4 during the 2020/ 2021 flare, using all available filters (v, b, u, uvw1, uvm2, and uvw2), for a total of 14 epochs between MJD 59211 (2020 December 28) and MJD 59237 (2021 January 23). The data were analyzed using the uvotsource HEASOFT routine, defining as the extraction region a circular aperture centered on the source with a radius of 3″, and as background a circular aperture (away from the source) with radius of 10″. Several detections have been obtained, in addition to some upper limits in all bands. The light curves are shown in the middle panel of Figure  2.
NICER Monitoring The Neutron-star Interior Composition Explorer (NICER,  Gendreau et al. 2012 Gendreau et al. , 2016) )  observed Cen X-4 extensively in early 2021. We analyzed all observations made between January 1 and February 19. The observations, each comprised of one or more good time intervals, were reprocessed using the nicerl2 script that is part of the NICERDAS package in HEASOFT v6. 28, using calibration version 20200722. Spectra were extracted for each good time interval (GTI) using the tool nibackgen3C50, which also creates background spectra  (Remillard et al. 2022). For some GTIs, the parameters used to calculate background spectra could not be matched with the precalculated library of background spectra that is used by nibackgen3C50. In those cases, the GTI was excluded from our analysis, leaving a total of 186 spectra, with exposure times ranging from 51 s to 2627 s.
Spectral Energy Distribution In order to shed light on the nature of the misfired outburst, we built SEDs during the period of activity (using Swift/ UVOT and REM data obtained on 2021 January 4-5) and during quiescence (using REM and LCO data acquired on 2021 May 22-23). To do so, fluxes were dereddened using the absorption coefficient A V = 0. 31 ± 0. 16 mag as reported in  Russell et al. (2006) , and considering the relations of  Cardelli et al. (1989)  to evaluate the absorption coefficients at all wavelengths. Although the light curves already make it clear that both disk and companion star contribute to the quiescent and flare emission of Cen X-4, we tried to model the two SEDs with a simple irradiated blackbody function, using the known parameters of the companion star (a 0. 6 R e radius and a 0.
We thank the anonymous referee for useful comments and suggestions. This research has made use of data and/or software provided by the  High Energy Astrophysics Science Archive Research Center (HEASARC) , which is a service of the  Astrophysics Science Division at NASA/GSFC. This work is also based on observations made with the  REM Telescope, INAF Chile , and makes use of observations performed with the  Las Cumbres Observatory  network of telescopes. D. M. R. and D. M. B. acknowledge the support of the  NYU Abu Dhabi Research Enhancement Fund  under grant  RE124. J. H. acknowledges support for this work from the  NICER   Guest Investigator program  under  NASA  grant  80NSSC21K0662. We thank the  Swift  and  NICER  teams for rapidly approving, scheduling, and performing the X-ray observations.
S. C. and P. D. A. acknowledge support from  ASI  grant  I/004/11/5. J. v. d. E. is supported by a  Junior Research Fellowship  awarded by  St. Hilda's College, Oxford. N. M. acknowledges the ASI financial/programmatic support via the  ASI-INAF  agreement n. 2017-14-H. 0and the INAF Mainstream-project on the same subject. T. M. D. acknowledges support from the  Spanish ministry of science  under grant  EUR2021-122010. T. M. D. acknowledges support from the  Consejeria de Economia ,  Conocimiento y Empleo del Gobierno de Canarias  and the  European Regional Development Fund  under grant  ProID2020-010104.
Systematic reviews are based on standardized protocols that have been developed in the field of ecology over the last few years and have proven very successful to provide strong scientific evidence for practitioners  [38] [39] [40]. To consolidate the existing knowledge and earlier published reviews, we used a comprehensive search strategy based on several databases and performed a critical analysis of accepted studies in order to assess their susceptibility to bias and to attribute levels of confidence in CFF values. A database was produced, containing all collected CFF values, as well as their associated metadata. Our analysis identified patterns in the distribution of CFF across the animal kingdom, which may notably result from the influence of some species traits. This work focused on wild and domestic animals, excluding humans, and aimed at answering the following questions: what is the distribution of CFF between species? Are there differences in how flicker is perceived between taxonomic classes? Which species are more at risk of being impacted by artificial lighting flicker?.