dataesr/scientific-paragraphs-categorization huggingface dataset:
BLASTp searches were first conducted with an e-value cutoff of e 28. However, proteins sequences retrieved with an e-value ranging from e 28 to e 23 were maintained in the dataset if a domain related to the considered query was detected using the Conserved Domain search engine  [151]. When no hit could be found for a given protein query in one of the Mollicutes genomes, the protein of the closest species identified as a putative hit for this query was used as a query for additional BLASTp and tBLASTn searches. For each query, sequences of the putative Mollicutes homologs were aligned with Clustal W  [152]. Subsequent phylogenetic analyses were conducted by using the Neighbour Joining method in Mega5  [153]. Annotation of paralogs was resolved, when possible, by analyzing the microsynteny in MolliGen and the topology of the corresponding phylogenetic trees.
pulmonis from Dybvig et al 2010  [17] , for B. subtilis from Kobayashi et al 2003  [154]  and from data compiled on the Ecocyc database for E. coli  [26]. (PDF) Figure  S3  Dispensable proteins of translation apparatus in Bacteria. General information is the same as in Figure  4 , except that results are now divided into 2 main boxes: part A corresponds to the proteins that are easily lost during reductive Mollicutes evolution and part B corresponds to proteins that have not been found in any of the 39 Mollicutes analyzed. Proteins are classified according to the 7 categories defined in Table  1. Acronyms indicated in black italics letters correspond to proteins absent in many Mollicutes but found in both E. coli and B. subtilis; in red italic letters are proteins absent in E. coli and present in B.
In other words, when an essential gene is lacking in the genome of an endosymbiont, one never sure whether the missing cellular function can be full fit (or not) by a 'foreign' protein originating from the co-endosymbiont, the host mitochondria and/or the host cell itself. (PDF) Table  S1  List of selected  (39)  Mollicutes with some genomics and phenotypic (cultivability) features. The list of the 39 selected Mollicutes is given following the numbering used throughout the manuscript. The genomics features (Genome size, % G+C, #CDS) were obtained from Genbank. The data from the six non-cultivated Mollicutes are framed with a red dashed line. (PDF) Table  S2  Proteins implicated in the biosynthesis and functions of translation machinery in bacteria. List of queries of E. coli and B. subtilis sequences used to search for homologs in Mollicutes.
Accession numbers are from the NCBI Reference Sequence or UniProt databases. The product names for E. coli and B. subtilis proteins are from the Ecocyc and the Subtiwiki databases, respectively. (XLSX) Table  S3  Table of putative homologs detected in the selected mycoplasma genomes. The orthologs for the queries either from E. coli or B. subtilis were searched as indicated in Material and Methods in the 39 selected Mollicutes When a hit was found its mnemonic was indicated in the corresponding cell of the table. When there was no homolog, the cell was left empty with a red background. In some cases, the ortholog in a given genome corresponds to a putative pseudogen; it is indicated as ''pseudo'' in the cell following the mnemonic(s). In some other cases, the Mollicutes gene seems to correspond to a fusion between the gene encoding the given homolog and another entity; it is indicated as ''fusion'' in the cell following the mnemonic.
Acknowledgments HG is an emeritus Scientist at  CNRS in Gif-sur-Yvette-France. We thank  Marat Yusupov ,  Sergey Melnikov  ( IGBMC-Illkirch, France ),  Leo Fourmy ,  Marie-Pierre Dubrana  for their help at elaborating Figure 5,  Pascale Romby  ( IBMC-CNRS Strasbourg ) for expertise on RNases, and  Patrick Thiaville  for editing the manuscript. The authors also thank  Guillaume Bouyssou  and  Gabriel Ferrand  for their contribution to Mollicutes gene identification and annotation.
44, 45 Details on each sample preparation are provided in the Supporting Information (SI). NMR Data Acquisition. All spectra were recorded on Bruker Avance III 800 or 1000 spectrometers operating at Larmor frequencies of 800 or 1000 MHz for 1 H, at 60 kHz MAS using triple-resonance HCN 1. 3 mm probes. The temperature of the sample was regulated using a VT gas flow in the range of 230-243 K, in order to achieve an estimated sample temperature of 300 K. In the 2D CP-HSQC spectra (Figure  1 ), the nonselective 90°pulses were set to 2. 5 μs at 100 kHz rf-field amplitude ( 1 H), 5. 0 μs at 50 kHz rf-field amplitude ( 15 N), and 3. 12 μs at 80 kHz rf-field amplitude ( 13 C). 1 H-  15  N forward cross-polarization (CP) was achieved using a contact time of 1. 5 ms, during which the 1 H rf-field amplitude was ramped linearly from 12 to 30 kHz, and the 15 N rf-field amplitude was held constant at 38 kHz.
5 ppm. After these two initialization steps of the algorithm, the genetic optimization process of MATCH was started in order to find the best possible solution to the assignment problem. For each protein data set, 10 independent optimization runs were performed, and sequence-specific resonance assignments which occur in more than 50% of the optimization runs were accepted as being correct and yielded the final list of assigned resonance frequencies. The overall calculation time was in all cases below 5 min on a single CPU of a contemporary Mac desktop equipped with a dual-core Intel Core i5 processor. The new version of MATCH is available free-of-charge for the academic community as a submodule of the UNIO application suite. Download information is available under http://perso. ens-lyon. fr/torsten.
This is realized stepwise: first, CA and CB chemical shifts of each spin system allow for a rough classification of the residue type, and second, a robust sequential matching of spin systems is established. Fragments of three and more sequentially connected spin systems can then usually be unambiguously matched to the protein sequence. Following cross-peak selection, these steps may be quickly performed interactively by an experienced spectroscopist or by application of computational backbone assignment algorithms. This latter possibility is an attractive feature that is essential to accelerate the data analysis and to render the procedure more impartial. For each protein automatically investigated by MATCH, we first interactively generated peak lists of NMR resonance signals from the six NMR experiments and subjected them together with the protein sequence to a modified version of the program UNIO-MATCH.
Here we report the backbone resonance assignments of the five proteins (see SI for chemical shift lists). Resonance assignments were automatically obtained and validated interactively for all data sets, except for OmpG. OmpG presented an extremely challenging data analysis task that turned out to be most reliably done by interactive analysis. For the crystalline proteins, 52 and 75 backbone amide crosspeaks were automatically assigned for the SH3 domain (62 residues) and β2m (99 residues), respectively. For both proteins, this corresponds to 100% of the observed backbone H N -N resonances in the 2D CP-HSQC (Figure  2a, b ), where prolines and flexible or disordered parts such as N-and Cterminal tails are absent. Both proteins show long transverse coherence lifetimes (∼20 and 45 ms, respectively for  13  CA and 13 CO); hence, efficient magnetization transfers are guaranteed also in the experiments with multiple  13  C homonuclear  a The table reports the sensitivity (S/N/√t) of the CP-HSQC, calculated on the integral of the first increment, acquired for 20 ms, after 20 Hz of exponential apodization (120 Hz in the case of OmpG), as well as the estimated experimental times necessary to achieve a S/N per peak [(S/N) p ] > 4.
■ CONCLUSIONS Our results from this diverse and challenging set of proteins demonstrate the excellent performance of the proposed standard suite of triple-resonance experiments for studies of proteins of different condensed states and show that modern, error-tolerant computational algorithms can be applied for the efficient and robust NMR data analysis. For microcrystalline and sedimented proteins, we find that the efficiencies of these experiments as compared to the basic 1 H-detected CP-HSQC experiment range from 0. 5 for the (H)CONH and (H)CANH to 0. 1 for the (H)(CA)CB(CACO)NH, while these efficiencies range from 0. 32 to 0. 03 for the membrane proteins. Acquisition times range from 36 h (SH3) to 2 weeks (M2 and OmpG) for the set of six spectra. The incorporation of an additional CB dimension accelerates and strengthens the reliability of backbone sequential assignment, and notably, triply redundant sequential chemical shift matching between intra-and interreside CA, CB, and CO resonances is the crucial component for the robustness of the procedure, using interactive or unsupervised methods alike.
Minimal activation voltage of the Na + currents was defined as the voltage at which the peak current reached 10% of its maximum value. To obtain the inactivation curves, we plotted the peak currents evoked by a test pulse (30 ms) to 0 mV following a range of prepulses (50 ms) from 2120 to 2 30 mV. Currents were filtered at 10 kHz and sampled at 50 kHz using a Digidata 1440A interface and pClamp10 software (Molecular Devices). Current traces underwent an on-line digital subtraction of leakage currents using a P/4 procedure, in which the currents evoked by four hyperpolarizing pulses with one-fourth amplitude of the test pulse P were summed and added to the current trace evoked at pulse P. Activation and inactivation data were fitted with Boltzmann function. Current traces were fitted with Hodgkin-Huxley function to obtain the activation time constant.
The time t 1 and t 2 were calculated as: somatic -axonal AP peak time. Because somatic stimulation will cause AP initiation at the regular initiation site and then propagation to the axonal recording site and backpropagation to the somatic recording site, t 1 is actually the time spent on the distance L -2a (for t 1 ,0; that is, somatic AP occurs earlier than axonal AP) or 2a -L (for t 1. 0; that is, axonal AP occurs earlier). When AP arrives at somatic and axonal recording sites simultaneously-that is, t 1 = 0-the estimated initiation site locates at the midpoint of L. In whole-cell current clamp experiments, the voltage signals were sampled at 50 kHz using a CED Micro1401 and Spike 2 software. Recordings with an access resistance larger than 20 MV at the soma and 25 MV at the axon were discarded.
Sections were then mounted on slides with fluoromount-G (Electron Microscopy Science). We took images with a laser scanning confocal microscope (Nikon FN1) with a 606 objective and an appropriate zoom. Automated sequential acquisition of multiple channels was used to obtain single or z-stack images with an interval of 0. 5 or 1 mm. For quantitative analysis of fluorescence intensity along the AIS, we extracted the fluorescence signals only at the AIS with the FIJI software and calculated the fluorescence intensity in three dimensions using the Amira software. Deconvolved by Autoquant X2 software (Media Cybernetics), all three channels of fluorescence signals were integrated in an 8-bit image with image expression parser function. We traced the AIS in the image, filled it out, and extracted the mask image of this fillout.
Acknowledgments The transgenic mouse lines were kindly provided by  Dr. Z. Josh Huang  at  Cold Spring Harbor Laboratory. We thank  Cristina Regondi ,  U. O. of Clinical Epileptology and Experimental Neurophysiology, Foundation IRCCS Neurological Institute Carlo Besta , for her skillful technical experience. We thank  Dr. Xiao-Bo Qiu  and his group at  College of Life Sciences, Beijing Normal University , for his help in purifying the blocking peptide.
This work was supported by the  973 Program  ( 2011CBA00400 , YS), the  National Natural Science Foundation of China Project  ( 31025012 , YS), the  Hundreds of Talents Program  from  Chinese Academy of Sciences ,  PICS-NavROLE (MM) , and  European Union   FP7 Grant no. 602531 ''DESIRE'' (MM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The top panel is for events with at least one W jet, the bottom panel for events without W jets. The left column is for events with a muon and the right column for events with an electron. either two or three jets, H T > 300 GeV, and S T > 900 GeV. The final selection requirements are optimized by computing expected limits on the T-quark mass. The DY background is not modeled adequately at low invariant mass and in the presence of missing transverse energy. We therefore use data to measure the residual background in events with two muons or two electrons. The observed event count in the Z-boson mass peak is rescaled by the ratio of DY events outside and inside the mass window as measured in a control data sample consisting of events with no b-tagged jets, E miss T < 10 GeV, S T < 700 GeV, and H T > 300 GeV.
Acknowledgements We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at  CERN  and at other  CMS institutes  for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies:  BMWF  and  FWF (Austria) ;  FNRS  and  FWO (Belgium) ;  CNPq ,  CAPES ,  FAPERJ , and  FAPESP (Brazil) ;  MES (Bulgaria) ;  CERN ;  CAS, MoST , and  NSFC (China) ;  COLCIENCIAS (Colombia) ;  MSES (Croatia) ;  RPF (Cyprus) ;  MoER ,  SF0690030s09  and  ERDF (Estonia) ;  Academy of Finland ,  MEC , and  HIP (Finland) ;  CEA  and  CNRS/IN2P3  (France);  BMBF ,  DFG , and  HGF (Germany) ;  GSRT (Greece) ;  OTKA  and  NKTH (Hungary) ;  DAE  and  DST (India) ;  IPM (Iran) ;  SFI (Ireland) ;  INFN (Italy) ;  NRF  and  WCU (Republic of Korea) ;  LAS (Lithuania) ;  CINVESTAV ,  CONACYT ,  SEP , and  UASLP-FAI (Mexico) ;  MBIE (New Zealand );  PAEC (Pakistan) ;  MSHE  and  NSC (Poland) ;  FCT (Portugal) ;  JINR (Dubna) ;  MON, RosAtom, RAS  and  RFBR (Russia) ;  MESTD (Serbia) ;  SEIDI  and  CPAN (Spain) ;  Swiss Funding Agencies (Switzerland) ;  NSC (Taipei) ; ThEPCenter,  IPST ,  STAR  and.
Collection and Maintenance of Gammarids Gammarids were collected by kick sampling at La Tour du Pin, upstream of the Bourbre River (France). This station has good water quality according to the data records of the RNB (French Watershed Biomonitoring Network) and a high density of gammarids. Adult G. fossarum were collected using a hand-held net and recovered using 2-2. 5 mm mesh sieves. Immediately after sampling, the organisms were kept in a plastic bucket and transferred promptly to the laboratory. The organisms were maintained during a 15-day acclimatization period in 30-L tanks with constant aeration at 1460. 5uC using a 10/14 h light/dark photoperiod. The tanks were supplied continuously with drilled groundwater mixed with softwater (obtained by reverse osmosis) to adjust the sampling site conductivity to 600 mS cm 21.
Statistical Analysis The statistical procedures were performed using XLSTAT  [37]. The normality and homogeneity of the data were tested first using Shapiro-Wilk and Levene tests. These criteria were not satisfied, so nonparametric tests were used to analyze the data. The Kruskal-Wallis test was used to study the effects of the molt stage or gender on the physiological responses. For the starvation study, the diet effect and time exposure were assessed independently using the Mann-Whitney test.
Conclusion The present study assessed the effects of physiological parameters (gender and female reproductive cycle) and food availability on two energy metabolic responses (digestive enzyme activities and Ea) in G. fossarum. This ecophysiological study of Gammarus fossarum provides novel biological information, which will facilitate a better understanding of the physiological and biochemical responses of gammarids. These data could also help to understand energy metabolism in gammarids. We determined the effects of the reproductive cycle on the activities of digestive enzyme and Ea in females, and highlighted the more stable responses found in males. In female gammarids, two hypotheses may explain the fluctuations in their digestive activities and energy storage levels: (i) physiological events (molt, oogenesis, and spawning) and (ii) reproductive behavior (amplexus).
g. database, memory). Often the legacy applications follow monolithic architecture design approaches, implemented in technologies which may be deprecated or cannot easily deal with the notion of "as a Service" and are installed on owned infrastructures. The modernization and adaptation of legacy applications to cloud environments is a great challenge for all involved stakeholders, not only from a technical perspective, but also in business level with the need for adaptation of the business processes and models of the application which will be deployed on the Cloud and offered "as a service". In this paper, we present a novel model-driven  [22]  approach for the migration of legacy applications in modern cloud environments which covers all aspects and phases of the migration process, as well as an integrated framework that supports all migration process.
Unlike current methodologies, in this work we present an end-to-end approach developed in frame of ARTIST EU Project  [1]  that covers both all migration and modernization phases and also considers both the technical and business aspects of the application. This complete model-driven modernization and migration approach (initially discussed in  [12] ) is supported by an innovative toolbox as a "one stop shop" for the migration, modernization and cloudification of legacy applications. ARTIST Migration Methodology introduces three phases for the migration of legacy applications to cloud environments starting from a feasibility analysis to the core modernization of the software and its validation and certification during the post-migration. All aspects of the migrated software are examined in the methodology including the migration of the data and the adaptors which may be required for the handover between the legacy data source and the modern cloud data stores.
Finally, testing is carried out throughout the evolution process to ensure that the target system delivers the functionalities specified at the start of the evolution. Warren and Ransom  [25]  developed the Renaissance method which examines a legacy system from all technical, business and organizational perspectives. The method guides users through assessment of these perspectives by selecting assessment characteristics and assigning values to them. According to this approach system assessment is used to gain an understanding of a legacy system, which is fundamental to any system evolution exercise. System assessment should be an initial activity for evolution projects. The first important Software Modernization and Cloudification using the ARTIST Migration Methodology and Framework 133 milestone in the Renaissance method is a viable, cost effective system evolution strategy which can be presented to higher management.
In addition, REMICS executes the migration on brute force, without considering the feasibility or convenience to migrate. In the following table we summarize the various aspects of the migration methodologies defining the baseline for the ARTIST Migration Methodology: SMART ✘ ✔ ✘ ✔ ✔ Butterfly ✔ ✔ ✘ ✔ ✔ Renaissance ✔ ✔ ✘ ✔ ✘ OMG ADM ✘ ✔ ✘ ✔ ✘ XIRUP ✔ ✔ ✘ ✔ ✔ MoDisco ✘ ✔ ✘ ✘ ✔ REMICS ✘ ✔ ✔ ✘ ✔ 3. ARIST Migration Methodology. 3. 1. Methodology Overview. The methodology was developed to cover all aspects of software migration and modernization, including the business and technical requirements posed from the modern cloud ecosystems as common target environments for the deployment and provisioning of applications. The methodology consists of three (plus one) major phases which are analysed below: These three main phases are: • Pre-migration: In this phase a study of the technical and economic feasibility will be conducted as a prerequisite to the migration/modernization of the legacy system so as to effectively define the exact steps and effort that will be required.
The validation activities that are foreseen are mainly focused on behavioural equivalence, model based testing and end-user functional and non-functional testing. Moreover, a certification model will be created in order to increase customer confidence in the SaaS system. In addition to the three phases described above, another phase, named Migration Artefacts Reuse and Evolution, was defined in order to enable the effective reuse of software artefacts and optimization of the migration processes. This phase includes all needed application maintenance activities after migration to the Cloud (software updates, cloud provider changes, etc. ). The complete methodology is formally described using the Eclipse Process Framework EPF  [7]  and SPEM2. 0  [17]  specification and the generated diagrams of each phase are presented in the following sections.
3. 2. Pre-Migration Phase. The pre-migration phase (Figure  3. 1) is the starting point of each migration. Migration of legacy applications is considered as a very challenging project that involves not only changing the way companies are going to deliver their software, but also their business model, and how the company is organized in terms of processes. Thus, software vendors need to analyse whether the targeted objectives are actually feasible to them both technologically and economically. The first step in this pre-migration phase is to analyse how mature the application is in terms of technology (i. e. architecture, programming language, database, integration with third party offerings, etc. ) and business (i. e. current business model, maintenance and upgrades procedures, etc. ). It also considers how the customer wants the application to be in those two axes (i.
These migration tasks aim at building and deploying the migrated component corresponding to selected legacy components (e. g. implementations of application features). MDFE strongly relies on models and model transformations e. g. model to model (M2M) and model to text (M2T) for the technical materialization of the described MDFE tasks. The main aim for these transformations is to generate diverse models providing different views over the migrated application, including its source code. The skeleton of the application is generated automatically, and developers have to write manually some code to complete upgraded and newly added functionalities. In cloud applications, the business model is tightly intertwined to the technical solution and the methodology defines several tasks in order to define the business model, taking as baseline the principles by Osterwalder  [20].
The ARTIST Repository and Marketplace thus provide a central place to store, archive and organize MDE artefacts which could be merchandized as services in cloud marketplace environments  [13]. The second purpose of this phase is to support maintenance activities during and after migration. This is achieved on the workspace level by supplying developers with information about the (modelling) artefacts in the workspace including their types, their relationships and dependencies and their history. This information is gathered from the workspace and from associated source code management and ticketing systems. One possible way to exploit this data is to provide traceability between artefacts and perform change notifications and change impact analyses. On the artefact level, evolution is supported by a change description service.