dataesr/scientific-paragraphs-categorization huggingface dataset:
Principal coordinates analysis was calculated using the weighted UniFrac distance. Operational taxonomic units were identified using the uclust consensus taxonomy classifier with a 0. 97 threshold against the Greengenes database. Phylogenetic trees were generated using QIIME 1. 7. 0 and visualized using iTOL v2. 2. 2. SDS-PAGE and immunoblotting. For the total lysates, tissues were homogenized with TissueLyser II (Qiagen) in RIPA buffer  61  supplemented with a cocktail of protease inhibitors (Sigma) and phosphatase inhibitors. Equal amounts of proteins were separated by SDS-PAGE and transferred to nitrocellulose membranes. For detection of proteins of the insulin pathway, tissues were homogenized in ERK buffer (Triton X-100 0. 1%, HEPES 50 mM, NaCl 5 M, Glycerol 10%, MgCl 2 1. 5 mM and DTT 1 mM) supplemented with a cocktail of protease inhibitors and phosphatase inhibitors.
The resulting lipid fraction was analyzed by HPLC-MS using a LTQ Orbitrap mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA) coupled to an Accela HPLC system (Thermo Fisher Scientific). Analyte separation was achieved by using a C-18 Kinetex C-18 column (5 mm, 4. 6 Â 150 mm; Phenomenex, Utrecht, Netherlands) and a C-18 pre-column. Mobile phases A and B were composed of MeOH-H 2 O-NH 4 OH (75:25:0. 1, v/v/v) and MeOH-NH 4 OH (100:0. 1, v/v), respectively. The gradient (0. 5 ml min À 1 ) was as follows: from 100% A to 100% B in 15 min, followed by 10 min at 100% B and subsequent re-equilibration at 100% A. Mass spectrometry analysis in the negative mode was performed with an ESI source. The measurement of eCB were generated as previously described  32  , and the data were normalized to tissue sample weight.
Statistical analyses. The data are expressed as the mean±s. e. m. Differences between the groups were assessed using one-way analysis of variance (ANOVA), followed by the Tukey post-hoc test. A two-way ANOVA analysis with a Bonferonni post-test on repeated measurements was performed for the evolution of body weight, fat mass and glycaemia during the OGTT. The data were analyzed using GraphPad Prism version 5. 00 for Windows (GraphPad Software, San Diego, CA, USA). Data with different superscript letters or symbols are significantly different at Po0. 05 according to the post-hoc ANOVA statistical analysis. Comparisons between the WT-CE and cKO-CE, the cKO and cKO-Abx groups, and the GF-WT and the GF-KO groups were performed using a two-tailed Student's t-test. The results were considered statistically significant when Po0.
Acknowledgements We would like to thank  A. Barrois ,  A. Bever ,  I. Blave ,  H. Danthinne ,  B. Es Saadi  and  R. Selleslagh  for excellent technical assistance. We thank  R. M. Goebbels  for histological assistance. We thank  M. Osto  for the help in breeding mice. We thank  J. F. Collet  for the anaerobic chamber. P. D. C. is a research associate at  FRS-FNRS  ( Fonds de la Recherche Scientifique ),  Belgium. A. E. and M. A. are postdoctoral researchers at  FRS-FNRS, Belgium. H. P. is a doctoral fellow at FRS-FNRS. P. D. C. is the recipient of grants from  FNRS  (convention J. 0084. 15, convention 3. 4579. 11)and  PDR (Projet de Recherche , convention :  T. 0138. 14 )and  ARC  ( Action de Recherche Concertee-Communautefranc¸aise de Belgique convention  :  12/17-047 ). This work was supported by the  Fonds de la Recherche Scientifique-FNRS  for the  FRFS-WELBIO  under Grant no.
In silico analysis of FGE mutants The Polyphen software was used to predict the possible impact of amino acid substitutions on the structure and function of the FGE protein  [21]. The Human Splicing Finder software  [22]  allowed to predict potential transcripts induced by mutations occurring at splicing sites. The Swiss-model program  [23] [24] [25]  was used to deduce hypothetical structures from the sequences of FGE mutants. The 1Y1E. pdb and 1Z70. pdb structures were used as templates, and homology models were produced using the Automated mode. Structure visualization and analyses were carried out using the PyMOL program  [26].
This splicing could be predicted by Human Splicing Finder software  [22]. Unexpectedly, this change in the genomic sequence induced the deletion of only one alanine residue at position 175. To further characterise the impacts of the SUMF1 mutations on the expression of the protein, we individually expressed some of the mutants identified. Protein expression and stability were evaluated by western blotting analysis after transient overexpression of the C-terminally Flagged mutants in HEK293T cells (Figure  1 ). The anti-Flag antibody revealed three bands, comprising an approximately 42-kDa band corresponding to full-length FGE and two bands corresponding to N-terminally processed forms intended for secretion, as previously reported  [27]. While the p. Y340H and p. R343S mutants were expressed at the same level as the wild-type (wt) protein, the p.
Of note, however, and despite several attempts, no stable cell transfectants could be obtained for the p. V174-P318dup mutant, suggesting that it may exert some cytotoxicity. Structural analyses were performed to complete the characterisation of the missense SUMF1 mutations, based on the known 3D structures of FGE  [12, 13]  (Figures  2  and 3 ). The structural consequences of the p. S155P, p. G263V, p. A279V, and p. R349W mutations have already been reported  [12] , and will not be discussed here. Besides the previously described p. S155P mutation, Patient 1 also carried the novel p. R343S substitution. Arg343 is strictly conserved within all species, and the p. R343S mutation is "probably damaging" (with the highest score) according to the Polyphen prediction software. Interestingly,   1 , where they are ranked on an ascending scale of disease severity.
Figure2Representation of FGE and the main mutated residues identified in this and previous studies. Cartoon representation of the FGE structure (PDB code 1Y1E) with helices in blue, beta-strands in violet, and loops in yellow. Represented in ball-and-stick and labelled are (i) essential or important residues for substrate binding and catalytic activity (orange carbon atoms), (ii) residues whose mutations have been previously described (magenta carbon atoms) [6, 16, 17, 27] , and (iii) newly identified mutations (cyan carbon atoms). N, O, and S atoms are in blue, red, and green, respectively. The two structural calcium ions are also represented (green spheres).
Database One of the functionalities implemented in the Biathlon X5 was the ability to compete against other users. For this reason, we created a special highscore system. In Kurt Thune Training and Pete Patruuna we used a simplified solution, but now we had to extend the multiplayer functionalities. The system is responsible for storing data on the server, retrieving it and creating new competitions. Although the idea was simple, resolving the real-time skiing of other players' overview turn out to be challenging. Therefore, the saved information is used in two ways: (1) just to display the best result of a player and, based on the score, place the players in the ranking list, and (2) to store the checkpoint times, to re-create and simulate back the skiing on the diagram. Based on that, the player can follow the other contestants like during a real-world competition.
We also took security matters into account, when designing and implementing the system. The database consists of three tables: users, race events, and high scores for all competition events. When a player starts the application, a new user is created in the database. When the player launches the competition, the application retrieves the 50 best players relevant to the selected event. After the player has finished the competition, the data is uploaded to the server. The data consists of four entries in the form of the checkpoint times, the number of misses on each shooting, the final time, and the total number of misses. The entries are stored in JSON format. On the server side, the score is checked, and only the better score gets updated in the database table. Before accessing the server, the request needs to pass a security control, which uses a public key encryption system.
neoformans were dead yeast cells with low transcriptional and mitochondrial activity, and disorganized cytoplasm and nucleus architectures, despite having been initially selected in the TOPRO low (viable) population. This was confirmed by dynamic imaging after observation that drop C. neoformans cells from lung homogenates were unable to bud over 48 h (data not shown). Additional experiments showed that the relative proportion of the different yeast cell populations in terms of multiplication and stress response (see Fig. S5A  to D), and the proportion of drop C. neoformans (see Fig. S5A ) varied among C. neoformans strains, when comparing H99 and two previously characterized clinical isolates  (19). multiplication was evaluated after Calcofluor (CALCO) staining of yeast cells prior to incubation into YPD medium, interaction with murine macrophages, or inoculation to outbred OF1 mice.
All of the macrophage populations except MP_CMFDA low clustered together. The pattern of expression of MP_CMFDA low and MO_CMFDA low was different from that of the other populations and between them, except for PCK1 and COX1 (red arrows). Four clusters of genes can be differentiated, with C1 specifically composed of genes involved in lung adaptation during infection (21) and C4 composed of genes expressed more in the MP_CMFDA low population. tal material). For multiplication and stress response analyses, gates were determined on the basis of the CALCO/CMFDA dot plot considering the intensity algorithm and optical control of the events pictured in the gates. For each population of interest, the geometric mean was calculated with the IDEAS software. From the whole data set and each algorithm, data were then normalized between 0 and 1, with 0 as the minimal value and 1 as the maximal value.
If a probe matched the selected gene, the corresponding primers were designed with the dedicated ProbeFinder Software (Roche Universal ProbeLibrary). At the end, 37 assays (see Table  S2 ) were implemented for real-time quantitative PCR, including 33 for nuclear genes, 1 for a ribosomal RNA gene (18S rRNA), 1 for a mitochondrial gene (COX1), and 2 for reference genes (ACT1 and GAPDH). Quantitative reverse transcription-PCR that allows primer-specific reverse transcription (50°C for 15 min) and quantitative PCR amplification on the basis of probe detection (95°C for 2 min and 45 cycles of 95°C for 15 s and 60°C for 30 s) was performed in a total volume of 10 l including 2 l of a 1:10 dilution of each RNA samples. Each RNA sample was normalized with the geometric mean of the quantification cycle of the corresponding ACT1 and GAPDH gene expression  (78).
ACKNOWLEDGMENTS We acknowledge  Assistance Publique-Hôpitaux de Paris  and  CNRS  for their financial support (Poste d' accueil APHP/CNRS). We thank  Stéphane Bretagne  for his continuous support and  Milena Hasan  and the  Centre d'Immunologie Humaine (CIH) of the Institut Pasteur  for their technical support.
Software and hardware design of complex systems is becoming difficult to maintain and more time and effort are spent on verification than on construction. One of the reason is the number of constraints that must be hold by the system. Recently, Formal methods such as probabilistic approaches gain a great importance in real-time systems verification including avionic systems and industrial process controllers. In this paper, we propose a probabilistic verification framework of SysML state machine diagrams extended with time and probability features. The approach consists of mapping a SysML state machine diagrams to PRISM input language. To ensure the correctness of proposed approach, we capture the semantics of both SysML state machine diagrams and their generated PRISM code. We demonstrate the approach efficiency by analyzing PCTL temporal logic on ATM case study.
We extract the adequate semantics model related to state machine diagram then, we present the underling semantics related to the produced PRISM model. Furthermore, we show tht the relation between both semantic preserves the satisfiability of PCTL properties. The remainder of this paper is structured as follows: Sect. 2 discusses the related work. Section 3 describes SysML state machine diagram. Sections 4 and 5 provide syntax and semantic meaning of probabilistic and timed state machine diagrams. The syntax and semantics of PRISM Model Checker is presented in Sect. 6. Section 7 provides a mapping mechanism from state machine diagram into the input language of the probabilistic model checker PRISM. The approach soundness is proved in Sect. 8. Section 9 illustrates the application of our mapping rules on Automatic Teller Machine (ATM) case study.
UPPAAL uses Computational Tree Logic (CTL) properties to check if the model is satisfied with liveness and safety properties. Ouchani et al. [17]  propose a verification framework of SysML activity diagram. The authors address a subset of SysML activity diagram artifacts with control flow. The different artifacts have been formalized and mapping algorithm has been proposed to translate these artifacts to PRISM input language. The transformation result is a probabilistic automata to be checked by PRISM. Timing verification is not considered. Kaliappan et al. [12]  propose a verification approach for system workflow especially in communication protocol. The approach takes as input three UML diagrams: state machine diagram, activity diagram and sequence diagram. State machine diagram or activity diagram is converted into PROMELA code as a protocol model and its properties are derived from the sequence diagram as Linear Temporal Logic (LTL).
Pajic et al. [18]  develop a framework for verification and generation of real time applications either in C/C++code for software or in Hardware description language (HDL) like VHDL or Verilog. The focus of the work is a development of model translation tool from UPPAAL  [5]  to Stateflow (UPP2SF). The checked UPPAAL model is translated to Stateflow using Simulink which provides full support for C/C++ and HDLs. Ando et al. [3]  propose a verification approach of SysML state machine diagram. The diagrams are translated to communication sequential process description (CSP) and they apply the PAT  [20]  model checker to check the CSP models against the LTL properties. The paper proposes a mapping rules of different state machine artifacts. However, time and probability are not addressed. Compared to the existing works Table  1 , our contribution improves the verification of SysML State Machine diagram by extending state machine with elements of UML MARTE profile to support time and probability.
PRISM Formalization In this section, our formalization focus on probabilistic timed automata (PTA) that extends the standard probabilistic automata (PA). The PRISM model checker supports the PTA with the ability to model real-time behavior by adding real-valued clocks (i. e. clocks variable) which increases with time and can be reset (i. e. updated). A Timed Probabilistic System (TPS) that represents a PRISM program (P) is composed of a set of "m" modules (m > 0). The state of each module is defined by the evaluation of its local variables V L. The global state of the system is defined as the evaluation of local and global variables: V=V L ∪ V G. The behavior of each module is described as a set of statements in the form of: [act]guard → p 1 : u 1. + p n : u n , which means, for the action act if the guard g is true, then, an update u i is enabled with a probability p i.
The update u i is a set of evaluated variables expressed as conjunction of assignments (V j = val j )&. &(V k = val k ) where V j ∈ V L U V G and val j are values evaluated via expressions denoted by eval, eval: V → R U {T rue, F alse}. The formal definition of a command is given in Definition 2. Definition 2. A PRISM command is a tuple c = < a, g, u >. -act is an action label. -guard is a predicate over V. -u = {(p i , u i )} ∃m > 1, i < m, 0 < p i < 1, m i p i = 1 and u = {(v, eval(v)) : v ∈ V l }. The set of commands are associated with modules that are parts of a system and it definition is given in Definition 3. Definition 3. A PRISM module is tuple M = <V l , I l , Inv, C>, where: -V l is a set of local variable associated with a module, -Inv is a time constraint of the form v l d\ ∈ {≤, ≥} and d ∈ N, -I l is the initial value of V l.
-C= {c i , 0 < i ≤ k} is a set of commands that define the module behavior. To describe the composition different modules, PRISM uses CSP communication sequential process operators  [10]  such as Synchronization, Interleaving, Parallel Interface, Hiding and Renaming. Definition 4 provides a formal definition of PRISM system. Definition 4. A PRISM system is tuple P = <V, I g , exp, M, CSPexp>, where: -V = V g m (i=1) V li is.
PRISM Semantics The probabilistic timed automata of a PRISM program P is based on the atomic semantics of a command C denoted by  [[c] ]. The latter is a set of transitions defined as follows: [[c]] = {(s, a, μ)|s |= g} where μ is a distribution over S such that μ(s, v t ) = {|0 ≤ p i ≤ 1, v ∈ V, s (v) = eval(V )|}. The stepwise behavior of PRISM is described by the operational semantic as follows: INIT V i , init(V i ) → V i ([[init(V i )]]), -INIT initializes variables. For a module M i , init returns the initial value of the local variable v i ∈ V i. LOOP V i , -→ V i This axiom presents a loop in a state without changing variables evaluations. It can be applied to avoid a deadlock. UPDATE V i , v i = eval(V ) → V i ([[v i ]] ) UPDATE axiom describes the execution of a simple assignment for a given variable v i.
The Verification Approach This section describes the transformation of SysML state machine diagrams S into a PTA written in PRISM input language. Listing. 1 propose a mapping function Γ that takes as input the SMC terms defined in Table  2  to produce a PRISM commands. The action label of a command is the label of its related term n. The guard of this command depends on how the term is activated and minimal clock valuation. The flag related to the term is its label l that is initialized to false except for the initial node it is true which conforms to the premise of the SMC rule Ax-1. The updates of the command deactivate the propositions of the term, activate that ones related to its successors, reset the clock variable of its successors. The functions L(n), Start(S i ) and E (S i ), return the label of the initial term n , the initial and final term of S i , respectively.
Each PRISM code generated for each state machine diagram starts from module S i and terminates with endmodule. The call of substates transitions (line 30 and 31) synchronize with the initial (line 42) and the final (line 44) transition, respectively to enable the internal transitions of substate. The final transition (line-38) reset the local variables to false. However, the PTA model in PRISM model checker does not support the shared variables. To overcome, we use the implication operator to set the proposition to true as shown in line 31 and line 42. The clock variable x is used as guarded condition for state successors activation. In line 34, Listing 1. PRSIM Commands Generation.
Conclusion In this paper, we presented a formal verification approach of probabilistic systems modeled by using SysML state machine diagram. For this purpose, the approach maps state machine into the input language of the probabilistic model checker PRISM. We proposed a calculus dedicated to this diagram that captures precisely their underlying semantics. In addition, we formalized PRISM language by showing its semantics. Thus, we proved the soundness of our proposed approach by defining adequately the relation between the semantics of the mapped diagrams and the resulting PRISM models. In addition, we proved the preservation of the satisfiability of PCTL properties. Finally, we have shown the effectiveness of our approach by applying it on a case study representing an ATM state machine diagram where time and probability are evaluated using PCTL properties.
Data Collection and Analysis. PCR efficiency and coefficient of determination ( 2 ) values were calculated by the software Rotor Gene Q Series and Mx3005Pro, respectively. Negative and positive controls were included in each assay, in which a threshold setting (Ct) of 0. 03 was used as the reference for the Rotor Gene Q MDx thermocycler. A threshold setting of 300 was used as the reference for the Mx3005P thermocycler for all tested kits except for one two-step kit (Express) for which a threshold setting of 0. 05 was used.
Statistical analysis The survival of the different treatment groups was compared by Kaplan-Meyer survival analysis using SigmaPlot for Windows version 12. 0 (Systat Software Inc. , California, USA) using time to reach a tumor volume higher than 4 times the initial tumor volume or euthanasia due to radiation toxicity symptoms as the end points. Hematology and biodistribution data were compared using one-way ANOVA. Multiple comparisons were performed using the Holm Sidak method. A significance level of p < 0. 05 was used in all tests.
Loci were screened for null alleles and scoring errors with Micro-checker v. 2. 2. 3  (Van Oosterhout et al. 2004 ). Sources of error (i. e. excess of homozygote or heterozygote combinations and rare allele combinations) were determined in GenAlex 6. 5  (Peakall and Smouse 2012) , and offending genotypes were double-checked. Number of alleles (N a ), observed (HO) and expected heterozygosity (HS), locus-specific inbreeding coefficients (F IS ), fixation indexes (G 0 ST )  (Nei 1987 ) and heterozygosity standardized fixation indexes (G 00 ST ) (Meirmans and Hedrick 2011) were all estimated with the package diveRsity  (Keenan et al. 2013)  for the software environment R. Deviations from Hardy-Weinberg equilibrium (HWE) and linkage equilibrium were tested in GENEPOP V4. 0 160  (Rousset 2008 ) (10 000 dememorizations and 100 batches of 5000 iterations).
Acknowledgements This work was supported by  Natural Environment Research Council (NERC; UK)  grants  AFI06/16 ,  NE/ H023038/1  and  NE/H023704/1. The microsatellite sequences were isolated at the  NERC Biomolecular Analysis Facility at Sheffield. We thank  Deborah Dawson  for assistance during the microsatellite marker development and  Jonathan Kool  for his advice on implementing the genetics projection model. Simulated currents from NEMO were provided by the  National Oceanography Centre, Southampton. We thank two anonymous reviewers, whose comments helped us improve the original manuscript.
Data archiving statement Sequencing information has been deposited in the  European Molecular Biology Laboratory (EMBL) , accession numbers  FM878464-FM878589  and  LN614714-LN614727  (Appendix B). Full genotypic data are stored on the  Molecular Ecology and Fisheries Genetics Laboratory (MEFGL) database at Bangor University. Output from the modelling work is archived at the  British Antarctic Survey.
Prospective data Patients were selected from among non-ambulant patients (i. e. , patients not able to walk more than 10 meters without human assistance) included in two observational natural history studies (Pre-U7 and ULE-NAP) carried out by the Institute of Myology (Paris) (Table  1 ). These studies were approved by the local ERB and by the French health authority (ANSM) and were registered with www. clinicaltrials. gov (NCT01385917 and NCT00993161, respectively) General design and preliminary data of the multicentric study ULENAP have been already reported  [20] [21] [22]. In this study, we assessed upper limb strength and function in 53 non-ambulant DMD patients (regardless of their mutation) every six months for one year. All patients were evaluated using a standardized evaluation. Age at loss of ambulation, steroid intake, left ventricular ejection fraction (LVEF) and forced vital capacity (FVC) were obtained from the available medical files.