dataesr/scientific-paragraphs-categorization huggingface dataset:
Peptide, PTM and protein identifications. All (m/z: retention time) coordinates found regulated with relative ratios below -2 or above +2 with significance (t-test p-value < 0. 05) at any time point were selected by creating corresponding scheduled precursor lists in ProfileAnalysis, which were then used for automated MS/MS fragmentation in dedicated automatic methods in WARP-LC (Bruker). In addition, all masses found with s/n > 20 in one random sample of each analysis were also selected for MS/MS. All obtained MS/MS spectra together with the corresponding (m/z; retention time) coordinates were exported to Proteinscape server 2. 4 and used for Swissprot mouse database interrogation through Mascot server 2. 4. There were distinctions in database interrogation filters and data handling, depending on the considered extracts, which are detailed in Supplemental data legends.
3. 1 The chondrogenic-like phenotype of iATDC5 confirmed at the proteome level by soluble secretome analysis. After confirming that the phenotype of our samples were in accordance with the literature  [26, 28]  (Supplemental data S. 2), we examined their soluble secretomes  [43]  as previously described  [35, 37]. 72 proteins being significantly up-or down-regulated were revealed. To obtain a comprehensive description of the related groups of regulated proteins, we performed Gene Ontology (GO) annotation enrichment analyses, focusing on biological processes. [figure  1 ] Figure  1. A shows the significant top four enriched GO term categorization that classifies 33 proteins. Two of the most enriched terms are consistent with chondrogenic differentiation. Collagen fibril organization [GO: 0030199; including α1(II), α1(V), α2(V), α1(XI), α2(XI) collagens, but also PGCA, ANXA2, FMOD, LYOX], the most enriched of all, and ECM organization (GO: 0030198; SMOC2, CCD80, FBLN1, FBLN5, LEG3, NID2, POSTN, PGBM), with both early and late protein regulations, depicting one major valuable feature of iATDC5 cells: the ability to produce large amounts of ECM components.
Yet, it is absolutely missing in the present dataset. Likewise, other functionally important cartilage ECM components, notably, type IX collagen  [56]  and Matrilins  [57] , though less obviously evidenced by mass spectrometry in cell culture systems, are not found either. Type X collagen is found specifically in guanidine extracts prepared from iATDC5 (figure  2 ), but it remains close to the minimal detection threshold. These findings are worth being considered prior to using the model, especially when interested in the processes in which these proteins are involved. In particular, COMP, type IX collagen and Matrilins are believed to work collectively at interconnecting ECM molecules within cartilage and their absence in the model is likely to alter the ECM ultrastructure  [58]. Nevertheless, the model synthesizes and assembles into its ECM the major cartilage components, aggrecan and type II collagen.
BIBLIOGRAPHY FIGURE LEGENDS Lack of data is indicated by white boxes. Proteins implicated in at least one of four described biological processes are in bold. The whole output data are listed in Supplemental data S. 3. proteins found unregulated at any time point were not listed here. The whole output data are listed in Supplemental data S. 4. Proteins/genes previously reported in vivo  [20] , ex vivo  [21]  or in vitro  [33]      UniprotKB database. The PTMs annotated here for the bovine protein are according to  [47]  and serve as comparison to those found here in iATDC5. Residues annotated in grey correspond to peptides which were not identified. Residues annotated in italic correspond to peptides which were identified only from soluble secretome analysis, the others being from CNBr extracts.
ABT-263-mediated ER stress was analyzed in the cell lines panel using detection of BIP, ATF4 (PERK signaling) and CHOP as surrogates for an ER stress response. In both Mel270 and 92. 1 cells, ABT-263 enhanced ATF4 and CHOP as well as BIP level (Fig. 4a ). In contrast, induction of ATF4 and CHOP by ABT-263 was hardly detectable in OMM1 and OMM2. 5 human uveal melanoma cells, and BIP was not detected in OMM1 cells. We also did not detect PERK and IRE1α phosphorylation (Thy980 and Ser724 respectively) in OMM1 and OMM2. 5 cell lines treated with ABT-263 (data not shown). Of note, in contrast to ABT-263, tunicamycin, another ER stress inducer, was able to stimulate CHOP in OMM1, thus ruling out that the ER stress pathway is deficient in OMM1 and OMM2. 5 cell lines (Supplementary Fig. 3 ). Furthermore, XBP1 splicing was significantly higher following ABT-263 exposure (Fig.
mRNA preparation and real-time/quantitative PCR The mRNA was isolated using TRIzol (Invitrogen) according to a standard procedure. QRT-PCR was performed using SYBR Green I (Eurogentec, Seraing, Belgium) and Multiscribe Reverse Transcriptase (Applied Biosystems) and subsequently monitored using the ABI Prism 7900 Sequence Detection System (Applied Biosystems, Foster City, CA, USA). The detection of the SB34 gene was used to normalize the results. Spliced Xbp1 primers were previously reported  33. Primer sequences for each cDNA were designed using either Primer Express Software (Applied Biosystems) or qPrimer depot (http://primerdepot. nci. nih. gov), and these sequences are available upon request.
Acknowledgements The authors thank  Dr. M. J. Jager  for the critical reading and editing of this manuscript. This work was funded by  La Ville de Nice ,  ARC  grant # 20171206312  to  C. B ,  ARC  grant # 20171206287  to BB-M and cancéropôle PACA. CP is a fellowship from  la Ligue Nationale Contre le Cancer. The authors thanks  Karine Bille  and  Marjorie Heim  for their technical help. 92. 1 uveal melanoma cells were provided by  Dr. M. J. Jager  ( Leiden, The Netherlands ), Mel202 and Mel270 uveal melanoma cells by  Dr. B. Ksander  ( Boston, USA ) and OMM1 uveal melanoma cells from  Prof. G. P. M. Luyten , (Rotterdam, The Netherlands).
Materials and Methods The DFT calculations were performed in the VASP-Vienna Ab initio Simulation Package  [37] [38] [39]. The interactions between the valence and core electrons are described using the projected augmented wave (PAW) method  [40]. The Perdew-Burke-Ernzerhof (PBE) exchange-correlation function is used for geometry optimisations  [41]. To accurately predict the electronic band gap and density of states (DOS) features of CuSCN, the screened hybrid functional HSE06  [42]  with an exchange value of 25% was used. A kinetic energy cut-off of 600 eV and Monkhorst-Pack  [43]  K-points mesh of 7 × 5 × 3 converge the total energy of β-CuSCN to within 10 -6 eV, and the residual forces on all relaxed atoms reached 10 -3 eVÅ -1. The METADISE code  [44]  was used to create the (100) and (110) β-CuSCN surfaces.
Acknowledgments: The simulations were performed using the computational facilities of the  Advanced Research Computing @ Cardiff (ARCCA) Division, Cardiff University. This work also made use of the facilities of  ARCHER  (http://www. archer. ac. uk), the  UK 's national supercomputing service via our membership of the UK's  HEC Materials Chemistry Consortium , which is funded by  EPSRC  ( EP/L000202 ). Information on the data that underpins the results presented here, including how to access them, can be found in the Cardiff University data catalogue at http://doi. org/10. 17035/d. 2020. 0124286506.
Design and study population Obese patients referred for sleep apnea to the Sleep department of Grenoble Alpes University Hospital between 2007 and 2010 were included in a prospective cohort study. These patients were re-examined after at least 4 years of CPAP treatment, with cardio-metabolic assessments including arterial stiffness. Hypertension was defined following the ESC/ESH guidelines. [23]  At inclusion, patients were aged from 20 to 75 years with a body mass index (BMI) > 30 kg/ m 2. Patients with central apnea were excluded. The study was conducted in accordance with good clinical practice requirements in Europe, French law, ICH E6 recommendations, and the Helsinki Declaration  (1996 and 2000). The protocol was approved by an independent Ethics Committee (Comitede Protection des Personnes, Grenoble, France, IRB0006705) and registered on the ClinicalTrials.
Statistical analysis Statistical analyses were performed with SAS v9. 4 software (SAS Institute Inc. , Cary, NC, United States). A p-value < 0. 05 was considered as significant. Continuous data are presented as median and interquartile range (IQR) and categorical data as frequency and percentage. A comparison of the main quantitative variables at baseline and at follow-up was performed using a non-parametric Mann-Whitney test. A non-parametric Wilcoxon signed-rank test was used to compare the PWV before and after CPAP use. Due to the non-normality of PWV values, a log-transformation was performed and a log-linear mixed effect model with a patient random effect adjusted for the delay between the two measurements was used to analyze the evolution in arterial stiffness. A univariate analysis between PWV and potentially contributing factors was performed to select variables for the multivariate model.
inclusion, patients had a median age of 55. 8[47. 4;62. 0]years,52. 8% were men, with a median (IQR) BMI of 38. 5[35. 4;43. 1]kg/m 2. Median (IQR) AHI at diagnosis was 36. 1 [23. 3; 75. 2] events/hour. Patients with hypertension (58. 3%), had type 2 diabetes (20. 8%) and were current or former smokers (59. 7%). Baseline data concerning medical history, comorbidities, arterial blood gases, biological parameters, sleep studies and pulmonary function tests are shown in Table 1. The comparison between imputed and non-imputed datasets is available in S1 Table of the online supplement.
This study was funded by an unrestricted grant from the  French National Research Agency  ( ANR-12-TECS-0010 ) in the framework of the " Investissements d'avenir" program  ( ANR-15-IDEX-02 ), the "e-health and integrated care" Chair of excellence of the  University Grenoble Alpes Foundation  and the endowment fund "Agir pour les maladies chroniques". This study was funded in part by  ORKYN Society and Perimètre Association.
Multiscale framework Figure  1  shows the structure of the complete multiscale framework that consists of four cyclically repeated steps  [28]. First, an idealized 3D model of the lumen of a tortuous portion of healthy Superficial Femoral Artery (SFA) is built and a 3D mesh of the fluid dynamic domain is generated using ICEM CFD (v. 18. 0, Ansys Inc. , Canonsburg, PA, USA). To compute the hemodynamics, a steady-state CFD simulation is performed in Fluent (v. 18. 0, Ansys Inc. ), and the WSS profiles are extracted at the lumen interface of a discrete number ( = 10) of 2D vessel cross-sections. For each plane, the local, hemodynamic-driven remodeling is replicated with an ABM implemented in Matlab (v. 2016b, MathWorks, Natick, MA, USA) that simulates cellular, extracellular and lipid dynamics.
Geometry preparation and meshing A simplified 3D geometry of the lumen of a healthy artery with SFA-like features was initially built using the CAD software Rhinoceros (v. 6. 0, Robert McNeel & Associates, Seattle, WA, USA) (Fig. 2A ). The initial geometry presented a centerline length of   = 84. 02 , and circular inlet and outlet cross-sections with diameters   = 4. 10  and   = 3. 71 , respectively. The 3D geometry was imported into ICEM CFD to generate the 3D mesh of the lumen for the CFD simulation. A hybrid tetrahedral mesh with five boundary layers of prism elements was created with the Octree method  [30]. As global mesh parameters, an element maximum size of 0. 39 mm was set and the curvature/proximity based refinement was enabled with a minimum element size of 0. 156 mm and a refinement of 20 edges along a radius of curvature.
While cell agents are responsible for cell mitosis and apoptosis and ECM production, ECM agents are involved in ECM degradation, meaning that the code scans the grid looking for cells or ECM, respectively. It results that, due to the prevalence of ECM on cells, the model has the tendency to preferentially degrade ECM, instead of producing it. Accordingly, to replicate a baseline condition where ECM production and degradation are averagely balanced, an adjusting coefficient β was introduced and calibrated for each layer. Specifically, since the intima and the media layer have the same cell/ECM ratio = 0. 72, a single βint/med was defined for these two layers, while a different value, βadv, for the adventitia, being the adventitia composed by a cell/ECM ratio of 0. 43. To this aim, ten ABM simulations were run under physiologic conditions with several tentative βint/med and βadv values and, at a 2-months follow-up, the ratio between final and initial ECM,   = 1, βint/med = 1.
Moreover, two additional values were included in the analysis to explore the ABM behavior at the extremes of the parameter range, thus investigating seven values for each of the seven parameters, shown in Tab. 2. As mentioned above, in this analysis only one parameter at a time was varied, while keeping all the others at their default values, resulting in 49 cases, each with ten replicates. The results were analyzed in terms of lumen area and intimal content of SMCs, ECM and lipids. Indeed, the intima is the layer that is mostly affected by the pathologic wall remodeling occurring in atherosclerosis. The statistical analysis of the results was performed in Matlab. The normality of data was assessed using Kolmogorov-Smirnov test. After verifying that all data were not parametric, Kruskal-Wallis test with multiple comparison was used to detect differences among the variables.
A low efficacy of the PRCC is, indeed, associated with non-monotonic input-output relationships  [45]. To obtain more reliable correlation estimates between each output and input, it is necessary to hugely increase the sample size, implying large computational effort. For this purpose, the Matlab code of the ABM might be converted in C, which is thought to extremely reduce the computation time for each ABM simulation. This will also allow extending the sensitivity analysis to more input parameters that were not considered in the present work, namely those related to the diffusion equation for the inflammation and the threshold on the WSS condition. In particular, the WSS threshold of 1 Pa is a Accepted manuscript at https://doi. org/10. 1016/j. compbiomed. 2020. 103623 48  strong assumption which is thought to largely affect the output of the model.
The automation of the fully coupled CFD-ABM framework will reduce the user time consumption in the coupling processes, namely for the generation of the CFD model, the CFD simulation settings and the initialization of the subsequent ABM simulations. Once automated, a more extensive sensitivity analysis on the coupling period will be possible, as well as a sensitivity analysis on the number M of 2D cross-sectional planes, which was not addressed in the present work, although considered important to determine the effect of the spatial resolution on the results. Finally, the automation of the framework and the conversion of the Matlab code in C, will facilitate the calibration of the ABM parameters on patient-specific geometries and the future validation, which otherwise would require excessive computational efforts and time.
MinHash-based p-distance approximation Varying d from 0. 05 to 1. 00 (step = 0. 05), a total of 200 nucleotide sequence pairs with d substitution events per character were simulated under the models GTR and GTR+Γ. Each model was adjusted with three different equilibrium frequencies: equal frequencies (f 1 ; π A = π C = π G = π T = 25%), GC-rich (f 2 ; π A = 10%, π C = 30%, π G = 40%, π T = 20%), and AT-rich (f 3 ; π A = π T = 40%, π C = π G = 10% ). The GTR substitution rates and the Γ shape parameters were obtained based on a maximum likelihood (ML) analysis of 142 real-case phylogenomics datasets. Overall, ML estimates of Γ shape parameters were quite low (i. e. varying from 0. 162 to 0. 422, with an average of 0. 314), confirming that the heterogeneity of the substitution rates across sites is a non-negligible factor when studying evolutionary processes.
15 and p ≤ 0. 35 reference phylogenetic trees were obtained based on a ML analysis of real-case phylogenomics datasets. Sizes of the reference trees ranged from 10 to 154 taxa (31 on average), with diameters (i. e. maximum distance between any two leaves of a tree) varying from 0. 204 to 2. 883 (0. 975 on average). Sequence lengths and indel events were simulated in the same way as the previous sequence pair simulations. The script JolyTree v2. 0 was used to reconstruct phylogenetic trees from the simulated sequences. For each pair of unaligned sequences, this script estimates the MH p-distance using Mash, and transforms it into an evolutionary distance. Using these MH-based distances, JolyTree next reconstructs a minimum evolution phylogenetic tree with confidence supports at branches, based on a ratchet-based hill-climbing procedure (for more details, see 29).
On the other hand, simple (underparameterized) distance estimates should often be preferred, because they frequently result in more accurate tree topologies  21, [38] [39] [40] [41] [42]. Here, the simple PC and EI transformations (2) (one and five parameters, respectively) enable many reference trees to be recovered (Figure  5 ). However, the EI transformation (3) is able to approximate realistic distance measures (e. g. GTR+Γ) by using only one supplementary parameter a (Figure  3 ). It therefore enables more reference trees to be recovered (Figure  5 ). In line with 43, most suitable values of a (e. g. between 1. 0 and 2. 0) are all higher than the Γ shape parameter values used for simulating the sequence datasets (i. e. varying from 0. 162 provide distance estimates that are quite comparable to the ones returned by Equation (  3 ) with a ranging from 1.
Phylogenetic reconstruction from MinHash-based evolutionary distances To assess whether MH p-distance transformations may translate into reliable phylogenetic trees, additional simulations were performed. A total of 142 sets of sequences was simulated under the model GTR+Γ along reference phylogenetic trees. Representative GTR+Γ model parameters (same as above) and to 0. 422, with an average of 0. 314). This can be explained by the MH upward bias (see above), but also by the large variance of the estimate (3) when a becomes low. Reminding that the Γ shape parameters (and the reference trees) used in these simulations were inferred from real-case datasets, these results suggest that using EI transformation (3) with a ≈ 1. 5 may be suitable to infer genus phylogenetic trees. In light of this, it should be stressed that the article  29  describing the first distributed version of JolyTree (v1.
Model parameter estimation To simulate the evolution of nucleotide sequences according to realistic substitution processes, the 187 genus datasets compiled in 29 (available at https://doi. org/10. 3897/rio. 5. e36178. suppl2) were first considered to infer a representative range of GTR parameter values. For each of the 187 genera, the associated genome assemblies were processed using Gklust v0. 1 to obtain one representative genome assembly for each putative species. This analysis provided 142 sets of representative genome assemblies after discarding genera containing < 10 putative species. For each of these 142 sets, coding sequences were clustered using Roary v3. 12  55. Each cluster with at least four coding sequences was used to build a multiple amino acid sequence alignment using MAFFT v7.
407  56. Multiple sequence alignments were back-translated at the codon level and concatenated, leading to 142 supermatrices of nucleotide characters. A phylogenetic tree was inferred from each supermatrix of characters using IQ-TREE v1. 6. 7. 2  57  with evolutionary model GTR+Γ. All data related to these analyses are publicly available as Extended data at https://doi. org/10. 5281/zenodo. 4034244  58.
org/10. 5281/zenodo. 4034461  60. f 1 = (0. To compare the efficiency of p-distance transformations for phylogenetic reconstruction, the program INDELible v1. 03 was also used to simulate the evolution of a sequence along each of the 142 phylogenetic trees previously inferred from different genera (see above). For each of the 142 genera, sequence evolution was simulated under the model GTR+Γ with the corresponding parameters (i. e. four nucleotide frequencies, six relative rates, and one Γ shape parameter). Sequence length and indel events were simulated as described above. The 142 simulated sequence sets are publicly available as Extended data at https://doi. org/10. 5281/zenodo. 4034643  61. Sequence and phylogenetic analyses MH p-distances were estimated with Mash v2. 2, BinDash v1. 0, and Dashing v0.
The conclusion of the manuscript presents the approach of phylogenetic inference from pairwise MH-based distance estimates as a possible alternative to classical methods of phylogenetic reconstruction (especially in bacteria). Indeed, a classical phylogenomic approach involves the chaining of a complex set of procedures: the identification of orthologous genes in multiple species; the alignment of these genes; and finally, the building of a tree from the concatenation of those alignments. I think that the inclusion in the paper of a comparison of two phylogenies obtained with: i) the MH-based distance and ii) a concatenation would strengthen this claim. A lot of concatenation datasets extracted from complete bacterial genomes are available and it would be not too difficult to do the experiment.
e. the number of mismatches per position in an (unknown) alignment of the compared sequences. The present paper shows how distances based on complex models of evolution (GTR, GTR + \Gamma) can be approximated using MinHash-based p-distances. The approach is carefully evaluated based on simulated sequences. The proposed method is a welcome and useful addition to existing alignment-free methods, extending them to more realistic models of evolution. The approach is novel, the paper is very well written and clear, and references are given to the literature for more details. Therefore, I support indexing of the manuscript. A certain limitation is that the manuscript is restricted to MinHash distances. According to the author, these methods are accurate for p-distances roughly < 0. 25 (for reasonable k-mer length), but are less accurate for larger distances.
However, a number of other alignment-free methods have been proposed that accurately estimate distances for much larger distances, e. g. Kr  (Haubold et al. , 2009 1  ), FSWM  (Leimeister et al. , 2017 2  ), Phylonium (Klötzl and Haubold, 2019 3 ), Slope-SpaM  (Röhling et al. , 2020 4  ). All these methods estimate distances based on the simple Jukes-Cantor model; the program Co-phylog estimates non-corrected p-distances (Yi and Jin, 2013  5  ). It should be straight-forward to transform these distances to more complex models, as done in the present paper, and to compare them to the MinHash methods evaluated in the paper. of pure k-mer counting a la Fan et al. , rather than the MinHash approaches, which trade some accuracy of the Jaccard estimation for speed. This is still useful, but could be somewhat misleading for those that need the speed benefits of running MinHash with more typical parameters.
Additionally, since the sweep of s is linear, but MinHash error bounds relate to an exponential of s, the sweep ends up being less informative than it could be, which is likely why the columns of Figure  1  are nearly identical. As a simple remedy, I would suggest sweeping the parameter s exponentially rather than linearly, starting closer to the default sketch size for the tools. It could still end closer to the genome size to get a sense of the behavior of MinHash as it degenerates to the actual k-mer Jaccard score. Along these lines, it would also make sense for the later phylogenetic experiments to either use a smaller s or do another sweep of values. As a minor point when listing relevant software in the introduction: Dashing is based on HyperLogLog sketching, which is similar in concept to MinHash but algorithmically distinct.