dataesr/scientific-paragraphs-categorization huggingface dataset:
Comparison between P and type 1 pili The interface between subunits N 0 and N +3 is extremely important in maintaining the FimA helical rod. Previously, two atomic models (PDB ID: 2N2H and 2MX3) for the type 1 pilus have been generated using the same solid-state NMR data  (Habenstein et al. , 2015) , with the helical symmetries for these models shown in Supplementary file 2. The results were described as being FimA from uropathogenic E. coli (UPEC)  (Habenstein et al. , 2015) , however, the sequence corresponds to that of E. coli K12 strains, as does the recent FimA cryo-EM structure  (Hospenthal et al. , 2017)  that is also described as being from UPEC. When subunit N 0 is superimposed between our cryo-EM model with a subunit in 2N2H and 2MX3, significant differences can be seen in the interface with subunit N +3 in the different models (Figure  2  Comparison of our type 1 pilus model with the P pilus structure  (Hospenthal et al.
Conservation and variability of FimA sequences To explore the variation and evolution of FimA, we examined a set of 1,872 FimA protein sequences in the Ensembl Bacteria database  (Kersey et al. , 2016)  (Supplementary file 3). After filtering to remove protein sequences that are expected to be non-functional and trimming of the signal sequence, the remaining 1,828 protein sequences were aligned. Here, we found that many of the FimA sequences were comprised of 159 residues, including BW25113, while other FimA sequences, such as the one from UTI89, a prototypical UPEC isolate, contained an additional two amino acid residues at the N-terminus of the mature protein (Figure  3A ). Global alignment revealed a consensus sequence of 161 residues where half of the FimA residues in the mature protein are invariant (79/161 residues) and that 83.
9% are highly conserved (139/161 residues with >95% sequence identity) (Figure  3A ). We found the FimA sequences to be significantly more variable than other parts of the type 1 pilus machinery. For example, the mature forms of the FimC chaperone and FimH adhesin (n = 1,760 and n = 1,943, respectively; Supplementary file 4) obtained from the same database contain 97. 6% and 97. 5% highly conserved residues, respectively, as compared to 83. 9% in FimA. In general, most E. coli genes evolve slowly  (Lee et al. , 2012) , so the degree of divergence between alleles of FimA is abnormally high. This suggests that the selection forces acting on the FimA protein are different from the forces acting on the rest of the fim operon. Interestingly, the non-conserved residues within the FimA sequences are all located on the exterior surface of the solved cryo-EM model (Figure  3B ), which is likely indicative of immune pressures selecting for antigenic diversification  (Wildschutte et al.
Evidence of evolutionary pressures on FimA To evaluate the evolutionary pressures shaping FimA and thus the type one pilus rod, we obtained gene sequences encoding the 1,828 FimA proteins from the Ensemble database to measure the selection pressures acting on the gene. After removing incomplete and duplicate sequences from the analysis, we were able to compare a total of 191 unique fimA sequences (Supplementary file 3), which were then trimmed to remove the signal sequence. These sequences encoding the mature protein were examined for evidence of recombination, which can result from horizontal transfer of genetic sequences between distinct strains and confound evolutionary analyses that assume all sequences were vertically inherited  (Anisimova et al. , 2003). Phylogenetic trees were thus corrected for use in subsequent analyses  (Kosakovsky Pond et al.
Every residue facing the lumen is 100% conserved. Overall, FimA displays strong signals of purifying selection resulting in conservation with hotspots of adaptive selection resulting in variability of surface residues. DOI: https://doi. org/10. 7554/eLife. 31662. 009 The following figure supplement is available for figure  3 : To more specifically determine if variation in FimA correlated with E. coli clades or pathogenic lifestyles, such as uropathogenicity, we examined the diversity and distribution of the fimA gene in a curated set of 67 E. coli genomes. This dataset included 21 distinct UPEC strains isolated from a cohort of women with frequent, recurrent UTI and 46 reference E. coli strains that included lab and commensal strains, as well as a variety of intestinal and extra-intestinal pathogens  (Schreiber et al.
To extend a single pilus (Figure  4 ) the piezo stage was moved at a constant speed of 10 nm/s and the sampling frequency was set to 10,000 Hz that was downsampled by 800. Occasionally, we measured the responses of multiple pili attached to the bead resulting in a force-extension response as the sum of all attached pili. This was, however, not a problem in general since the shorter pili detached from the bead in a sequential order, leaving only the single, longest pili attached to the bead for measurement (Figure  4 -figure supplement 2). Finally, we controlled the piezo-stage and sampled the data using an in-house LabView program  (Andersson, 2018 ; copy archived at https://github. com/elifesciences-publications/ot-control). To make a flow chamber, we added a ring of vacuum grease (Dow Corning, Midland, MI) around the area containing the poly-L-lysine-coated microspheres on one of the coverslips.
Cryo-EM data collection and image processing 3 mL of sample was applied to glow discharged lacey carbon grids (TED PELLA, Inc. , 300 mesh). Then the grids were plunge-frozen using a Vitrobot Mark IV (FEI, Inc. ), and subsequently imaged in a Titan Krios at 300keV with a Falcon II direct electron detector (pixel size 1. 05 A ˚/pixel). A total of 6803 images, each of which was from a total exposure of 2 s dose-fractionated into seven chunks, were collected at a range of underfocus between 0. 5 ~3 mm. Images were motion corrected using MotionCorr  (Li et al. , 2013) , and the program CTFFIND3  (Mindell and Grigorieff, 2003)  was used for determining the defocus and astigmatism. Images with poor CTF estimation as well as defocus >3 mm were discarded. The SPIDER software package  (Frank et al. , 1996)  was used for most other operations with the first two-chunk sums (containing a dose of ~20 electrons/ A ˚2) of the motion-corrected image stacks.
Model building and refinement We used a previous FimA NMR model (PDB id: 2JTY, a single chain) as an initial template to dock into the cryo-EM map by rigid body fitting, and then manually edited the model in Chimera  (Pettersen et al. , 2004)  and Coot  (Emsley et al. , 2010). We then used the combined model  (1-19 and 21-159)  as the starting template to re-build a single chain of the FimA protein using the RosettaCM protocol  (Wang et al. , 2015). Next, the full length model of FimA missing the first two residues and the last residue was iteratively refined by Phenix real-space refine  (Adams et al. , 2010)  and manually adjusted in Coot. The refined single chain of the FimA model was then re-built by RosettaCM  (Wang et al. , 2015)  with helical symmetry and refined by Phenix to improve the stereochemistry as well as the model map coefficient correlation.
Bioinformatic analyses The protein sequences of closely-related homologs of E. coli FimA, FimC, and FimH were obtained by individual searches the Ensembl Bacteria Genome database  (Kersey et al. , 2016)  using the phmmer web-server  (Finn et al. , 2015)  with a BLOSUM62 (FimA) or a BLOSUM90 (FimC and FimH) scoring matrix using the full-length E. coli UTI89 protein sequences as queries. The sequence matches were then filtered to remove low scoring hits and non-functional sequences (i. e. , those predicted to lack critical sequence features such as complete signal sequences and/or C-terminal tyrosine residues in FimA and FimH). The signal sequences were trimmed from the remaining homologs using Geneious v 6. 1. 7  (Kearse et al. , 2012)  and the protein sequences were aligned with the MAFFT program using two iterations of the FFT-NS-i algorithm based on the PAM200 scoring matrix  (Katoh and Standley, 2013).
Conservation at each amino acid position was calculated using custom Python scripts and a sequence logo was created using the ggseqlogo package in R (R Core Team, 2017) using RStudio  (RStudio Team , 2015). To estimate selection pressures on each codon in fimA, we obtained all available gene sequences encoding the protein sequences described above from the Ensembl Bacteria Genomes database (n = 1,825, three were removed by submitter's request) using custom bash scripts (Supplementary file 3). A total of 191 unique sequences were identified using Geneious v 6. 1. 7 and trimmed to remove the signal sequence. Evolutionary model selection was performed using maximum likelihood ratio testing on the Datamonkey webserver  (Pond and Frost, 2005; Delport et al. , 2010) , which identified the TIM2 model (model 010232) as the most likely model of nucleotide substitution for the fimA homologs.
1. 7, trimmed to remove signal sequences, and aligned using the MUS-CLE program  (Edgar, 2004). A phylogenetic tree was estimated using the RAxML program  (Stamatakis, 2006 ) with the GTRCAT model and supported with 1000 bootstraps  (Stamatakis et al. , 2008). Evidence for episodic, diversifying selection was then identified using a random effects likelihood ratio test for each branch of the fimA phylogenetic tree  (Kosakovsky Pond et al. , 2011)  using unique sequences from the genomes (32 duplicates removed, n = 25). Branches showing statistically significant evidence for episodic, diversifying selection, as measured by a chi-squared test were then indicated on the corresponding branches of the phylogenetic tree constructed using RAxML.
Acknowledgements We would like to thank  Wandy Beatty  and  Bryan Anthony  of the  WUSM Molecular Microbiology Imaging Facility. This work was supported by grants from the  National Institutes of Health  [GM122510 (EHE),  AI048689  and  DK064540  (SJH),  1F31DK107057  (CNS), and  DK101171-02  (MSC)], the  Swedish Research Council   621-2013-5379  (MA) and the  Agence Nationale de la Reserche   ANR-14-CE09-0004  (OF). ALR was funded by the  Pasteur Paris University PhD program. The cryo-EM work was conducted at the  Molecular Electron Microscopy Core facility  at the  University of Virginia , which is supported by the  School of Medicine  and built with  NIH  grant  G20-RR31199. The Titan Krios and Falcon II direct electron detector within the Core were purchased with  NIH SIG   S10-RR025067  and  S10-OD018149 , respectively.
Materials and methods Data were obtained from 9139 subjects [4928 females aged 5-96 years (M = 31. 8, SD = 18. 9) and 4211 males aged 5-91 years (M = 30. 7, SD = 17. 7)]. Among them, 3432 (37. 5%) had been included in a previous study to establish normative data  [15]. According to the inclusion criteria for the respective studies, all subjects were healthy and none reported histories for any olfactory disturbances. Odors were delivered using felt-tip pens ("Sniffin' Sticks") of approximately 14 cm length and an inner diameter of 1. 3 cm. These pens carry a tampon soaked with 4 ml of liquid odorant. For odor presentation, the cap was removed from the pen for approximately 3 s, the pen's tip brought in front of the subject's nose and carefully moved from left to right nostril and backwards  [3].
Statistical analyses Data were analyzed by means of SPSS v. 25 software (SPSS Inc. , Chicago, Ill. , USA). Subjects were divided into nine age groups:   1 ). We examined the effects of sex (female vs male) and age (groups A-I) on TDI scores by means of analysis of variance (ANOVA). Further, we modelled effects of sex and age on separate subtest scores obtained for threshold, discrimination and identification scores, controlling for within-subject variance using repeated measures analysis of variance (rm-ANOVA). Pairwise comparisons were Bonferroni-corrected for multiple comparisons between the nine age groups. To provide guidance for assessing individual olfactory abilities in relation to specific age groups, we calculated the tenth percentile of TDI score for each age group.
Discussion The current study provides updated norms for the "Sniffin' Sticks" olfactory test based on a large sample. The present data obtained from 9139 subjects corroborate previous normative findings-which is noteworthy given that Fig. 1  Mean TDI scores obtained from female and male subjects across the nine age groups. Error bars represent SEM. The bottom table shows differences between mean scores of two groups (group in a column -group in a row) and the level of post-hoc test significance: ***p < 0. 001; **p < 0. 01; *p < 0. 05 Fig. 2  TDI scores obtained from female and male subjects with polynomial trendlines for both sexes  1 3  approximately two-thirds of the data are newly added to the database, as compared to the previous version from 2007  [15]. We observed similar values of the tenth percentile in all age groups, although the exact comparison cannot be made due to the more narrow age categories in the present study, e.
g. , previously, age group A was 5-15 years, whereas in the current study we present data for age groups A (5-10 years) and B  (11-20 years). With the current investigation we found the hyposmia cutoff point of 30. 75 points in the reference group aged 21-30 years. Hitherto, the hyposmia cutoff score was 30. 5 points  [15]  and in the proposed normative dataset, the same exact value of 30. 5 points is the tenth percentile value of age group D (31-40 years). This 0. 25 point difference between age groups C and D is likely to result from the division of the previously investigated group aged 16-35 years into two decade-wide age groups C (21-30 years) and D (31-40 years). The diagnosis of hyposmia remains to some extent an arbitrary decision, as the cutoff point of 30. 75 has been established with respect to group C aged 21-30 years, representing the overall best smelling subsample.
Therefore, sperm with VAP < 20 µm/s and VCL < 20 µm/s were assumed to be immotile and moved by drift. These estimates were based on 134 ± 121 sperm tracks (mean ± SD; minimum: 20; maximum: 463) per ejaculate. A small droplet from the ejaculate was immediately smeared with 10% formalin (1:9 v:v; i. e. 4% formaldehyde) on a glass slide. From each slide, we took photos of ten intact sperm cells using the Nikon ACT-1 v2. 70 software (Nikon Corporation, Japan) with a Nikon DFC7000T camera (Nikon Corporation, Japan) mounted on a Leica DMR microscope (Leica Microsystems GmbH, Germany) at 400× magnification and phase contrast 2. Seven to 16 sperm cells (mean ± SE: 10. 1 ± 0. 5) were measured for head, midpiece, flagellum and total length. Additionally, each cell was independently measured twice to assess the amount of variance due to measurement error using random models  (Helfenstein et al.
2010). We used a re-sampling procedure to verify that measuring ten sperm cells accurately estimates male means, amongmale variation and within-ejaculate variation in total sperm length and length of sperm components (Additional file 3: Fig. S1, S2 ; Additional file 4: Supplementary dataset). The percentage of measurement error was 4. 7% for head length, 12. 5% for midpiece length, 1. 3% for flagellum length, and 0. 2% for total length. The average coefficient of variation [(SD/mean) × 100] for the two measures of the same sperm was 2. 5% for head length, 5. 2% for midpiece length, 1. 1% for flagellum length, and 0. 6% for total length. For further analyses the two measures per spermatozoon were averaged. We estimated the variability in sperm morphology among males by computing an unbiased estimate of among-male coefficient of variation (CV am ) using the formula adjusted for small sample sizes  (Sokal and Rohlf 1995)  based on average sperm measures for each individual.
Membrane construction and simulation. The experiments used an algorithm that took as input the desired lipid scan, increments for the scan, and number of simulations for each given composition (10 times for all experiments shown here), membrane size, simulation duration, and as output it provided the final structure and trajectory of the simulated membrane from its initial to final configuration. The algorithm used a program called insane  24  to generate model membranes according to membrane dimensions and relative lipid compositions, and solvate them -the models here solvated only in water. Insane (short for INSert membrANE) uses preset templates for orienting and placing lipid species into bilayer configurations, with relative lipid compositions and membrane size as inputs. Lipids for these membranes are defined by the coarse-grained MARTINI force field  7  , which specify unique bead types for groups of 2, 3, or 4 heavy atoms.
Porosity Measurement Untreated and treated nail samples were analyzed using a Micromeritics 9305 pore sizer (Norcross, GA, USA) fitted with a 3 mL powder penetrometer and working pressures in a 0. 004-172. 4 MPa range. Nail tips were used as described in Valdés et al. [19]. The nails were soaked in 10 mL of either water, solution ethanol 50% (v/v), Ony-Tec ® and Formulation A PU19-10% TH. Later, the samples were stored at room temperature for 24 h. After that time, the nails were removed from the solution, tested, dried, and the porosity determined. The amount of nail tip for test was approximately 0. 6 g. The pore size data were used for modelling the porous structure of the samples as simulated porous networks using PoreXpert™ 1. 3 software (Environmental and Fluid Modelling Group, University of Plymouth, UK)  [23].
The author explains that the data were not corrected in terms of nail thickness; however, the number of replicated were n = 5-7 for caffeine, n = 11-13 for the amorolfine and n = 13-15 for terbinafine, which did not prevent the finding of equal and superior deviations from the determination  [4]. The quantities of each drug were determined in the nail plate. Results are shown in Figure  4. The amount of CPX and TH determined in nail plate showed similar values; furthermore, the formulations-based polyurethane retain more drugs in the keratin structure than Ony-Tec ®. The amount of TH determined in the nail presented higher values (>0. 004-1 µg/mL), and value of minimum inhibitory concentration of TH against C. albicans and Aspergillus species  [18]. By contrast, the values of CPX determined in the nail are superior to the range 0.
Porosity Study The amount of CPX and TH diffused and retained in the nail plate showed similar values for PU19-based formulations. Thus, to evaluate the influence of the vehicle in nail plate hydration, a porosity study was performed. The porosity of the nail is another parameter to take in count to explain changes in the diffusion of drugs due to modification on the hydration of nail plate. This hydration allows a drug flux from certain vehicles  [23]. Indeed, an increase in nail plate hydration was found to increase the permeation of ketoconazole by three-fold and the diffusivity of water by more than 400-fold, when relative humidity increased from 15 to 100%  [37]. One method useful for characterizing the internal microstructure of the nail is mercury intrusion porosimetry (MIP) in combination with PoreXpert™ software.
Similar results were obtained by Nogueiras et al. [9]  for healthy untreated nails using MIP plus PoreCore™ software. These results indicated that PU19-10% placebo and Ony-Tec ® did not produce microstructural changes in the nail plaque, probably due to the presence of organic solvents and the absence (PU19-10%) or the low proportion of water (Ony-Tec ® ) used in the formulation of these nail lacquers.
Ulvan is a complex sulfated polysaccharide present in the cell wall of green algae of the genus Ulva (Chlorophyta). The first ulvan-degrading polysaccharide lyases were identified several years ago, and more were discovered through genome sequencing of marine bacteria. Ulvan lyases are now grouped in three polysaccharide lyase (PL) families in the CAZy database, PL24, PL25, and PL28. The recently determined structures of the representative lyases from families PL24 and PL25 show that they adopt a seven-bladed ␤-propeller fold and utilize the His/Tyr catalytic mechanism. No structural information is yet available for PL28 ulvan lyases. NLR48 from Nonlabens ulvanivorans belongs to PL28 together with its close paralog, NLR42. Biochemical studies of NLR42 have revealed that it can cleave ulvan next to both uronic acid epimers.
Ulvan lyases degrade ulvan through a ␤-elimination mechanism, cleaving the 1-4-glycosidic linkage on the nonreducing end of a uronic acid residue with the formation of an unsaturated product at the newly formed nonreducing end of the polysaccharide. The first identified ulvan lyase and the first representative of the PL28 family was NLR42 (NCBI accession number AEN28574; 46 kDa with two domains) isolated from Nonlabens ulvanivorans (synonym, Persicivirga ulvanivorans)  (8). The enzyme was able to cleave ulvan next to both GlcA and IdoA. In addition to the catalytic domain, NLR42 also harbors carbohydrate-binding and sorting domains  (9). Genome sequencing of marine microorganisms undertaken in the last few years led to the identification of more genes exhibiting ulvan lyase activity  (10 -12).
Polysaccharide-degrading machineries occur often as coregulated gene clusters called polysaccharide utilization loci (PUL). The PUL regions include genes coding for various transport proteins, highly specific carbohydrate-acting enzymes (glycoside hydrolases, polysaccharide lyases, and sulfatases), and recognition proteins. The complete degradation of the polysaccharides requires the coordination of these different components. We had previously characterized the ulvan PUL from Alteromonas and Pseudoalteromonas species  (13) , which led to addition of the families PL24 (LOR107) and PL25 (PLSV3936) to the CAZy database (http://www. cazy. org) 3 (14). Both LOR107 and PLSV3936 display Ͻ14% sequence identity; nevertheless, they both adopt a ␤-propeller scaffold. LOR107 is reported to degrade ulvan specifically after the IdoA site  (15) , whereas PLSV3936 can cleave after both GlcA and IdoA sites  (16).
Recently, a new ulvan polysaccharide family, PL28, was added to the CAZy database. Here, we report first crystal structure and catalytic mechanism of ulvan lyase NLR48 from N. ulvanivorans grouped in the PL28 family. NLR48 is a 30-kDa protein that was first identified as an ulvan lyase together with its larger homolog, NLR42  (8). NLR48 shows 37% sequence identity with the catalytic module of NLR42, suggesting structural and functional similarity of these enzymes. NLR42 can cleave the ulvan polysaccharide next to both GlcA and IdoA  (8). We have determined the crystal structure of NLR48 at 1. 9-Å resolution. Unlike the previously characterized ulvan lyases LOR107 and PLSV3936, NLR48 has a ␤-jelly roll fold. The structure of the NLR active-site mutant K162M in complex with a tetrasaccharide substrate facilitated the identification of active-site residues and allowed us to propose a catalytic mechanism for ulvan degradation.
Results and discussion We have determined the three-dimensional structure of NLR48, the first representative of the polysaccharide lyase family PL28, which has recently been added to the CAZy database. Several constructs were cloned and tested for expression. Expression yields of His-NLR48 and a shorter construct starting at Asp 53 , called His-NLR48(53D), were high, but the proteins aggregated in solution and were not suitable for crystallization. Therefore, the MBP and GST fusions were tested. The expression level of His-MBP-NLR48 was low in BL21(DE3), but that of the GST-NLR48 fusion was moderate, and no aggregation was observed. It was essential to purify the latter construct at 4 °C to prevent aggregation. This protein yielded well-diffracting crystals.